C O N S U LTAT I O N D R A F T The Cost to Developing Countries of Adapting to Climate Change New Methods and Estimates The Costs to Developing Countries of Adapting to Climate Change New Methods and Estimates The Global Report of the Economics of Adaptation to Climate Change Study Consultation Draft © 2010 The World Bank Group 1818 H Street, NW Washington, DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org E-mail: feedback@worldbank.org All rights reserved. This volume is a product of the World Bank Group. The World Bank Group does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank Group concerning the legal status of any territory or the endorse- ment or acceptance of such boundaries. R I G H TS A N D PE R M I S S I O N S The material in this publication is copyrighted. Copying and/or transmitting portions or all of this work without permis- sion may be a violation of applicable law. The World Bank Group encourages dissemination of its work and will normally grant permission to reproduce portions of the work promptly. For permission to photocopy or reprint any part of this work, please send a request with complete information to the Copyright Clearance Center Inc., 222 Rosewood Drive, Danvers, MA 01923, USA; telephone 978-750-8400; fax 978- 750-4470; Internet: www.copyright.com. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy iii Table of Contents Acknowledgments....................................................................................................................................................................... IX Abbreviations................................................................................................................................................................................... Xi Executive Summary........................................................................................................................................................................1 Section 1. Background and Motivation..................................................................................................................... 11 Section 2. Study Objectives and Structure............................................................................................................. 13 Section 3. Operational Definition of Adaptation Costs............................................................................... 17 Links between adaptation and development............................................................................................................17 Defining the adaptation deficit.......................................................................................................................................17 Establishing the development baseline.......................................................................................................................18 How much to adapt.............................................................................................................................................................19 Adapt to what? Uncertainty about climate outcomes...........................................................................................20 Summing potential costs and benefits........................................................................................................................22 Section 4. Methodology and Value Added. ............................................................................................................. 25 Choosing the timeframe....................................................................................................................................................26 Using baseline GDP and population projections to account for continuing development.....................26 Choosing climate scenarios and global climate models........................................................................................27 Selecting adaptation measures.......................................................................................................................................27 Understanding the limitations of this study...............................................................................................................28 Stylized characterization of government decisionmaking environment...............................................28 Limited range of climate and growth outcomes...........................................................................................30 Limited scope in economic breadth and time................................................................................................30 Simplified characterization of human behavior...........................................................................................30 Top-down or bottom-up analysis......................................................................................................................32 Section 5. Key Results. ............................................................................................................................................................... 33 Sector analyses......................................................................................................................................................................33 Infrastructure. .........................................................................................................................................................33 Coastal zones..........................................................................................................................................................39 Industrial and municipal water supply and riverine flood protection. ...................................................44 Agriculture. ..............................................................................................................................................................47 Fisheries. ...................................................................................................................................................................50 Human health.........................................................................................................................................................54 Forestry and ecosystem services........................................................................................................................57 Extreme weather events.......................................................................................................................................60 iv The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Consolidated results............................................................................................................................................................64 Sensitivity analysis...............................................................................................................................................................70 Uncertainty about climate projections............................................................................................................70 Uncertainty about the development baseline...............................................................................................71 Model and parameter uncertainty....................................................................................................................74 Section 6. Key Lessons............................................................................................................................................................... 77 Development is imperative…..........................................................................................................................................77 …but not simply development as usual. .....................................................................................................................78 Though adaptation is costly, costs can be reduced.................................................................................................78 Uncertainty remains a challenge....................................................................................................................................79 References.......................................................................................................................................................................................... 81 Figures Executive Summary Figure 1. East Asia and Pacific has the highest cost of adaptation in the wetter scenario, followed by Latin America and the Caribbean....................................................................................... 5 Figure 2. East Asia and Pacific has the highest cost of adaptation in the drier scenario, followed by Latin America and the Caribbean and Sub-Saharan Africa....................................... 5 Figure 3. The absolute costs of adaptation rise over time.................................................................................... 6 Figure 4. ...but fall as a share of GDP............................................................................................................................. 6 Main Report Figure 1. Economics of Adaptation to Climate Change study structure: global and country tracks..........................................................................................................................................14 Figure 2. A simplified interpretation of adaptation deficit.................................................................................18 Figure 3. Changes in productivity as a result of climate change have large impacts on trade flows...................................................................................................................................................50 Figure 4. Development greatly lowers the number of people killed by floods and affected by floods and droughts, 2000–50............................................................................................77 Tables Executive Summary Table 1. Total annual costs of adaptation for all sectors, by region and climate change scenario, 2010–50................................................................................................................................................................ 4 Table 2. Comparison of adaptation cost estimates by the United Nations Framework Convention on Climate Change and the Economics of Adaptation to Climate Change.................................................................................................................... 7 Main Report Table 1. Definition of development baseline, by sector....................................................................................19 Table 2. Welfare proxies for defining sectoral adaptation costs.....................................................................20 The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy v Table 3. Types of adaptation measures considered, by sector. .......................................................................28 Table 4. Estimates of adaptation costs for infrastructure from previous studies.....................................33 Table 5. Examples of dose-response relationships for paved roads, 2010–50..........................................35 Table 6. Annual delta-P costs of adaptation for infrastructure, by region and period, 2010–50..............................................................................................................................................................36 Table 7. Annual delta-P costs of adaptation for infrastructure for the National Centre for Atmospheric Research (NCAR) climate scenario, by region and cost type, 2010–50..............................................................................................................................................................37 Table 8. Breakdown of baseline and delta-P costs of adaptation for the National Centre for Atmospheric Research (NCAR) climate scenario, by region and infrastructure category, 2010–50..........................................................................................................................................39 Table 9. Alternative measures of the annual cost of adaptation for infrastructure, by region............................................................................................................................................................40 Table 10. Sea-level rise under four scenarios, 2010–2100...................................................................................43 Table 11. Annual costs of adaptation for coastal zone protection, by scenario and cost component, 2010–50...........................................................................................................................43 Table 12. Annual cost of adaptation for coastal zone protection and residual damages for the medium seal-level rise scenario, by region, 2010–50..........................................................44 Table 13. Gross and net annual adaptation costs for water supply and riverine flood protection, by region, 2010–50..................................................................................................................46 Table 14. Value of net cereal trade by region, with and without climate change and with and without adaptation investments, by region, 2000 and 2050.......................................49 Table 15. Adaptation costs in agriculture—number of malnourished children under age five for three scenarios, by region, 2000 and 2050.....................................................................51 Table 16. Annual cost of adaptation for agriculture—countering the effects of climate change on children’s nutrition levels, by region and cost type, 2010–50...................52 Table 17. Loss in landed values of fish catches under three scenarios, 2050...............................................53 Table 18. Annual cost of adaptation for fisheries—loss in landed catch values under three scenarios, by region, 2010–50...........................................................................................54 Table 19. Average annual adaptation cost for human health—preventing and treating malaria and diarrhea, by region and decade, 2010–50....................................................56 Table 20. Percentage change in regional timber production based on climate scenarios used for ecological projections, by region, 1995–2050.................................58 Table 21. Use of wood fuel in 2006 and projections to 2030, by region........................................................59 Table 22. Disaster preparedness and management data from the Asian Disaster Reduction Center............................................................................................................................................61 Table 23. Average annual cost of adaptation for extreme weather events—climate change— neutralizing costs of female education and additional numbers of female students, by region, 2010–50.........................................................................................................................................65 Table 24. Total annual costs of adaptation for all sectors, by region, 2010–50...........................................66 Table 25. Total annual costs of adaptation for all sectors, by region and period, 2010–50....................66 Table 26. Total annual costs of adaptation as a share of GDP, by region and period, 2010–50.............67 Table 27. Total annual costs of adaptation, by country income groups and decade, 2010–50............68 vi The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 28. Comparison of adaptation cost estimates by the United Nations Framework Convention on Climate Change study (2007), Parry and others (2009), and the Economics of Adaptation to Climate Change study, by sector..............................................68 Table 29. Delta-P costs for infrastructure as a percentage of base infrastructure costs for the two global climate models used in the Economics of Adaptation to Climate Change study and Monte Carlo simulations of all models, by region and period, 2010–50......................................................................................................................................72 Table 30. Percentage change in number of malnourished children with a 10 percent increase in GDP per capita and population growth, by region and climate scenario, 2010–50...............73 Table 31. Annual delta-P costs of adaptation for infrastructure, actual investment and investment adjusted for the adaptation deficit, by period, 2010–50..........................................76 Maps Map 1. Projected change in average maximum temperature based on two climate models, 2000–50..............................................................................................................................................................21 Map 2. Projected change in average annual precipitation based on two climate models, 2000–50..............................................................................................................................................................22 Map 3. Change in mean water runoff under the Commonwealth Scientific and Industrial Research Organization and National Centre for Atmospheric Research global climate scenarios, 2000–50............................................................................................................47 Boxes Box 1. Understanding what adaptation means for the most vulnerable social groups.....................14 Box 2. Climate-resilient investment planning. ...................................................................................................15 Box 3. Difficulties in operationalizing the adaptation deficit.......................................................................19 Box 4. Special Report on Emissions Scenarios of the Intergovernmental Panel on Climate Change...............................................................................................................................................21 Box 5. Taking climate uncertainty into account: how should national policymakers interpret global numbers?...........................................................................................................................23 Box 6. Calculating aggregate costs—gross, net, and X-sums......................................................................23 Box 7. Previous estimates of global adaptation costs.....................................................................................25 Box 8. Adaptation measures identified in participatory workshops.........................................................29 Box 9. Migration and climate change—Ghana’s experience.......................................................................31 Box 10. Infrastructure sector methodology..........................................................................................................34 Box 11. Urban housing and climate change.........................................................................................................38 Box 12. Why this study reports only delta-P and not delta-Q adaptation costs......................................40 Box 13. Adaptation costs for deltaic countries and small islands states. ....................................................41 Box 14. Coastal zone methodology.........................................................................................................................42 Box 15. Water sector methodology. .........................................................................................................................45 Box 16. Agriculture sector methodology...............................................................................................................48 Box 17. Private adaptation in agriculture and areas needing policy attention........................................49 The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy vii Box 18. Fisheries sector methodology....................................................................................................................53 Box 19. Health sector methodology........................................................................................................................55 Box 20. Gaps in coverage of ecosystem services................................................................................................59 Box 21. The importance of social protection measures...................................................................................62 Box 22. Costing social protection interventions under climate change. ....................................................63 Box 23. Extreme weather events methodology..................................................................................................64 Box 24. Critique of the United Nations Framework Convention on Climate Change estimates by Parry and others (2009)......................................................................................................69 Box 25. Local knowledge and ownership in water storage: the Kitui sand dams in Kenya.................78 The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy ix Acknowledgments the team is thankful to all of them. From the World Bank they include Vahid Alavian, Aziz Bouzaher, This report has been prepared by a core team led Jan Bojo, Henrike Brecht, Kenneth Chomitz, Vivian by Sergio Margulis (TTL) and Urvashi Narain Foster, Alexander Lotsch, Kseniya Lvovsky, Domi- and comprising Paul Chinowsky, Laurent Cre- nique van Der Mensbrughe, John Nash, Ian Noble, tegny, Gordon Hughes, Paul Kirshen, Anne Kuria- Giovanni Ruta, Apurva Sanghi, Robert Townsend, kose, Glenn Marie Lange, Gerald Nelson, James Walter Vergara, and Winston Yu. From outside the Neumann, Robert Nicholls, Kiran Pandey, Jason Bank they include Marten van al Aast, Roy Brou- Price, Adam Schlosser, Robert Schneider, Roger wer, Maureen Cropper, Anton Hilbert, Christine Sedjo, Kenneth Strzepek, Rashid Sumaila, Philip Pirenne, Tamsin Vernon, and Peter Wooders. None Ward, and David Wheeler. Major contributions of these colleagues and reviewers are, in any way, were made by Jeroen Aerts, Carina Bachofen, Brian responsible for the contents and eventual errors of Blankespoor, Ana Bucher, Steve Commins, David this report, which remain the sole responsibility of Corderi, Susmita Dasgupta, Timothy Essam, Wil- the EACC Team. We would also like to thank Meta liam Farmer, Eihab Fathelrahman, Prodipto Ghosh, de Coquereaumont, Bruce Ross-Larson, and Laura Dave Johnson, James Juana, Tom Kemeny, Benoit Wallace of Communications Development Inc, Laplante, Robin Mearns, Siobhan Murray, Hawa- and Jenepher Mosley for editorial services and Jim nty Page, Mark Rosegrant, Klas Sanders, Arathi Cantrell for editorial support and production man- Sundaravadanan, Timothy Thomas, Jasna Vukoje, agement. and Tingju Zhu. Sally Brown and Susan Hanson made important contributions to the coastal sec- This study is being conducted in partnership tor report, Miroslac Batka, Jawoo Koo, David Lee, between the World Bank (leading its technical Marilia Magalhaes, Siwa Msangi, Amanda Palazzo, aspects), the governments of the United Kingdom, Claudia Ringler, Richard Robertson, and Timo- Netherlands, and Switzerland (funding the study), thy Sulser to the agriculture sector report, Wil- and the participating case study countries. The liam Cheung to the fishery sector report, and Pieter findings, interpretations, and conclusions expressed Pauw and Luke M. Brander to the water sector in this paper do not necessarily reflect the views of report. the Executive Directors of the World Bank or the governments they represent. The World Bank does Since the beginning, the Economics of Adapta- not guarantee the accuracy of the data included tion to Climate Change (EACC) team has had in this work. The boundaries, colors, denomina- intense interaction with the Environment Depart- tions, and other information shown on any map in ment’s management, particularly Warren Evans and this work do not imply any judgment on the part Michelle de Nevers, who should, in fact, be con- of the World Bank concerning the legal status of sidered part of the EACC team. The team is grate- any territory or the endorsement or acceptance of ful to Sam Fankhauser and Ravi Kanbur for serving such boundaries. The material in this publication is on the advisory committee and to Julia Bucknall, copyrighted. Copying and/or transmitting portions Shanta Devarajan, Marianne Fay, Gherson Feder, or all of this work without permission may be a Armin Fidler, Kirk Hamilton, Tamer Samah Rabie, violation of applicable law. The International Bank Peter Rogers, Jim Shortle, Joel Smith, Michael for Reconstruction and Development / World Bank Toman, and Gary Yohe for acting as peer reviewers. encourages dissemination of its work and will nor- Numerous comments and suggestions were also mally grant permission to reproduce portions of received from a large number of colleagues, and the work promptly. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy xi Abbreviations LAC Latin America and Caribbean (World Bank region) AR4 Fourth Assessment Report of the MNA Middle East and North Africa (World Intergovernmental Panel on Climate Bank region) Control NCAR National Centre for Atmospheric CLIRUN The Climate and Runoff Model Research climate model CMIP3 Coupled Model Intercomparison NGO Nongovernmental organization Project phase 3 NREGA National Rural Employment Guarantee CSIRO Commonwealth Scientific and Act Industrial Research Organization OECD Organisation for Economic climate model Co-operation and Development DALY Disability-adjusted life year Ppm Parts per million DIVA Dynamic and Interactive Vulnerability SAR South Asia (World Bank region) Assessment SSA Sub-Saharan Africa (World Bank EACC Economics of Adaptation to Climate region) Changes SRES Special Report on Emissions Scenarios EAP East Asia and Pacific (World Bank of the IPCC region) UN United Nations ECA Europe and Central Asia (World Bank UNDP United Nation Development region) Programme GDP Gross domestic product UNFCCC United Nations Framework Convention IMPACT International Model for Policy Analysis on Climate Change of Agricultural Commodities and WCRP World Climate Research Programme Trade WHO World Health Organization IPCC Intergovernmental Panel on Climate $ All dollar values in the report are U.S. Change dollars The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 1 Executive Summary Yet, existing studies on adaptation costs provide only a wide range of estimates, from $4 billion Even with global emissions of greenhouse gases to $109 billion a year, and have many gaps. Simi- drastically reduced in the coming years, the global larly, National Adaptation Programs of Action (pre- annual average temperature is expected to be 2oC pared by Least Developed Countries under the above pre-industrial levels by 2050. A 2oC warmer United Nations Framework Convention on Climate world will experience more intense rainfall and Change, UNFCCC) identify and cost only urgent more frequent and more intense droughts, floods, and immediate adaptation needs, and countries do heat waves, and other extreme weather events. not typically incorporate adaptation measures into Households, communities, and planners need to long-term development plans. put in place initiatives that “reduce the vulnera- bility of natural and human systems against actual and expected climate change effects” (IPCC 2007). Putting a price tag on adaptation Without such adaptation, development progress will be threatened—perhaps even reversed. To shed light on adaptation costs—and with the global climate change negotiations resuming in While countries need to adapt to manage the December 2009 in Copenhagen—the Econom- unavoidable, they need to take decisive mitigation ics of Adaptation to Climate Change (EACC) study measures to avoid the unmanageable. Unless the was initiated by the World Bank in early 2008, world begins immediately to reduce greenhouse funded by the governments of the Netherlands, gas emissions significantly, global annual aver- Switzerland, and the United Kingdom. Its objec- age temperature will increase by about 2.5o–7oC tives are to develop an estimate of adaptation costs above pre-industrial levels by the end of the cen- for developing countries and to help decisionmak- tury. Temperature increases higher than 2oC—say ers in developing countries understand and assess on the order of 4oC—are predicted to significantly the risks posed by climate change and design better increase the likelihood of irreversible and poten- strategies to adapt to climate change. tially catastrophic impacts such as the extinction of half of species worldwide, inundation of 30 per- This initial study report, which focuses on the first cent of coastal wetlands, and substantial increases objective, finds that the cost between 2010 and in malnutrition and diarrheal and cardio-respira- 2050 of adapting to an approximately 2oC warmer tory diseases. Even with substantial public inter- world by 2050 is in the range of $75 billion to ventions, societies and ecosystems will not be able $100 billion a year. This range is of the same order to adapt to these impacts. of magnitude as the foreign aid that developed countries now give developing countries each year, Under the December 2007 Bali Action Plan but it is still a very low percentage of the wealth adopted at the United Nations Climate Change of countries as measured by their GDP. A second Conference, developed countries agreed to allo- report, based on seven country case studies (Ban- cate “adequate, predictable, and sustainable finan- gladesh, Plurinational State of Bolivia, Ethiopia, cial resources and [to provide] new and additional Ghana, Mozambique, Samoa, and Vietnam) and resources, including official and concessional fund- expected by March 2010, will focus on the second ing for developing country parties” (UNFCCC objective. 2008) to help them adapt to climate change. 2 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Using a consistent methodology oceans, forests), and on physical capital (infra- structure). The intuitive approach to costing adaptation involves comparing a future world without climate • Identifying adaptation alternatives and cost- change with a future world with climate change. ing. Adaptation costs were estimated by major The difference between these two worlds entails a economic sector—infrastructure, coastal zones, series of actions to adapt to the new world condi- water supply and flood management, agri- tions. And the costs of these additional actions are culture, fisheries, human health, and forestry the costs of adapting to climate change. With that and ecosystem services. Cost implications of in mind, the study took the following four steps: changes in the frequency of extreme weather events were also considered. Cross-sectoral • Picking a baseline. For the timeframe, the analysis of costs was not feasible. world in 2050 was chosen, not beyond (fore- casting climate change and its economic impacts becomes even more uncertain beyond Putting the methodology to work this period). Development baselines were crafted for each sector, essentially establishing The next step was adjusting and tailoring each step a growth path in the absence of climate change to the data and information available, a distinctive that determines sector-level performance indi- feature of the EACC study. The study used exten- cators (such as stock of infrastructure assets, sive global and national data sets, including World level of nutrition, and water supply availability). Bank projects and global economic indicators. In The baselines used a consistent set of GDP and the process, several questions arose. population forecasts for 2010–50. What exactly is “adaptation”? Is development adap- • Choosing climate projections. Two climate sce- tation? In reality, developing countries face not only narios were chosen to capture as large as pos- a deficit in adapting to current climate variation, let sible a range of model predictions. Although alone future climate change, but also deficits in pro- model predictions do not diverge much in pro- viding education, housing, health, and other ser- jected temperature increases by 2050, pre- vices. Thus, many countries face a more general cipitation changes vary substantially across “development deficit,” of which the part related to models. For that reason, model extremes were climate events is termed the “adaptation deficit.” captured by using the two model scenarios that yielded extremes of dry and wet climate pro- There are two ways to estimate the costs of adapta- jections. Catastrophic events were not cap- tion: with the adaptation deficit or without it. This tured, however. study chose to make the adaptation deficit a part of the development baseline, so that adaptation costs • Predicting impacts. An analysis was done to cover only the additional costs to cope with future predict what the world would look like under climate change. Thus, the costs of measures that the new climate conditions. This meant trans- would have been undertaken even without climate lating the impacts of changes in climate on var- change are not included in adaptation costs, but the ious economic activities (agriculture, fisheries), costs of doing more, doing different things (policy on people’s behavior (consumption, health), on and investment choices), and doing things differ- environmental conditions (water availability, ently are. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 3 Which adaptation measures? Adaptation measures How should benefits be costed? What happens if can be classified by the initiating economic sec- climate changes lead to lower investment or expen- tor—public or private. This study includes planned diture requirements for some sectors in some adaptation (adaptation that results from a deliber- countries—for example, if changes in demand for ate public policy decision) but not autonomous or electricity or water lead to lower requirements for spontaneous adaptation (adaptation by households electricity generating capacity, water storage, and and communities acting on their own without water treatment? In such cases, the “costs” of adap- public interventions but within an existing pub- tation are negative. For calculating global costs, lic policy framework). Since the objective is to help this becomes a summation problem. Rather than governments plan for risks, it is important to have making an explicit decision on whether to off- an idea of what problems private markets will solve set potential benefits of climate change against the on their own, how public policies and investments costs of adaptation, whether across sectors or coun- can complement markets, and what measures are tries, the study presents costs using three aggre- needed to protect public assets and vulnerable peo- gation methods—gross (no netting of costs), net ple—that is, planned adaptation. (benefits are netted across sectors and countries), and X-sums (positive and negative items are net- In all sectors, “hard” options involving engineer- ted within countries but not across countries). The ing solutions were favored over “soft” options based study opted to use X-sums in reporting most adap- on policy changes and social capital mobilization— tation costs in the interest of space, although simi- except in the study of extreme weather events, lar trends hold for the other aggregation methods. where the emphasis is on investment in human resources, particularly those of women. Although hard adaptation options are feasible in nearly all The global price tag settings, while soft options depend on social and institutional capital and thus may not be available Overall, the study estimates that the cost between in many settings, this focus on hard options was 2010 and 2050 of adapting to an approximately largely to ease computation of adaptation costs and 2oC warmer world by 2050 is in the range of $75 not to suggest that these are always preferable. billion to $100 billion a year (table 1). This range is of the same order of magnitude as the foreign How much adaptation is appropriate? Countries aid that developed countries now give developing have several options. They can try to fully adapt, so countries each year, but it is still a very low per- that society is at least as well off as it was before cli- centage of the wealth of countries (measured by mate change. They can choose to do nothing—to their GDP). suffer (or enjoy the benefits from) the full impact of climate change. Or they can decide to adapt to the Total adaptation costs average $10 billion a year level where the benefits from adaptation equal their more calculated by the gross sum method than costs, at the margin. The study assumes that coun- by the other two methods (the insignificant dif- tries will adapt up to the level at which they enjoy ference between the X-sum and net sum figures the same level of welfare in the (future) world as is largely a coincidence). The difference is driven they would have without climate change. This is not by countries that appear to benefit from climate necessarily the most economically rational deci- change in the water supply and flood protec- sion, but it is a practical rule that greatly simplifies tion sector, especially in East Asia and Pacific and the exercise. South Asia. 4 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 1 Total annual costs of adaptation for all sectors, by region and climate change scenario, 2010–50 ($ billions at 2005 prices, no discounting) Cost East Asia Europe and Latin America Middle East and South Sub-Saharan aggregation type and Pacific Central Asia and Caribbean North Africa Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario Gross sum 28.7 10.5 22.5 4.1 17.1 18.9 101.8 X-sum 25.0 9.4 21.5 3.0 12.6 18.1 89.6 Net sum 25.0 9.3 21.5 3.0 12.6 18.1 89.5 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario Gross sum 21.8 6.5 18.8 3.7 19.4 18.1 88.3 X-sum 19.6 5.6 16.9 3.0 15.6 16.9 77.6 Net sum 19.5 5.2 16.8 2.9 15.5 16.9 76.8 Note: The gross aggregation method sets negative costs in any sector in a country to zero before costs are aggregated for the country and for all devel- oping countries. The X-sums net positive and negative items within countries but not across countries and include costs for a country in the aggregate as long as the net cost across sectors is positive for the country. The net aggregate measure nets negative costs within and across countries. Source: Economics of Adaptation to Climate Change study team. The drier scenario (Commonwealth Scientific tion and coastal zones; and for South Asia, infra- and Industrial Research Organization, CSIRO) structure and agriculture. requires lower total adaptation costs than does the wetter scenario (National Centre for Atmo- Not surprisingly, both climate scenarios show spheric Research, NCAR), largely because of the costs increasing over time, although falling as a sharply lower costs for infrastructure, which out- percentage of GDP—suggesting that countries weigh the higher costs for water and flood man- become less vulnerable to climate change as their agement. In both scenarios, infrastructure, coastal economies grow (figures 3 and 4). There are con- zones, and water supply and flood protection siderable regional variations, however. Adapta- account for the bulk of the costs. Infrastructure tion costs as a percentage of GDP are considerably adaptation costs are highest for the wetter sce- higher in Sub-Saharan Africa than in any other nario, and coastal zone costs are highest for the region, in large part because of the lower GDPs in drier scenario. this region. On a regional basis, for both climate scenarios, The findings of the EACC analyses of sectors and the East Asia and Pacific Region bears the high- extreme events offer some insights for policymak- est adaptation cost, and the Middle East and North ers who must make tough choices in the face of Africa the lowest. Latin America and the Carib- great uncertainty. bean and Sub-Saharan Africa follow East Asia and Pacific in both scenarios (figures 1 and 2). On a Infrastructure. This sector has accounted for the sector breakdown, the highest costs for East Asia largest share of adaptation costs in past studies and the Pacific are in infrastructure and coastal and takes up a major share in the EACC study— zones; for Sub-Saharan Africa, water supply and in fact, the biggest share for the NCAR (wet- flood protection and agriculture; for Latin America ter) scenario because the adaptation costs for and the Caribbean, water supply and flood protec- infrastructure are especially sensitive to lev- The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 5 FIGURE 1 FIGURE 2 East Asia and Paci c has the highest cost of East Asia and Paci c has the highest cost of adaptation in the wetter scenario, followed by adaptation in the drier scenario, followed by Latin Latin America and the Caribbean America and the Caribbean and Sub-Saharan Africa Total annual cost of adaptation and share of costs for National Total annual cost of adaptation and share of costs for Centre for Atmospheric Research (NCAR) scenario, by region Commonwealth Scienti c and Industrial Research ($ billions at 2005 prices, no discounting) Organization (CSIRO) scenario, by region ($ billions at 2005 prices, no discounting) $3.0 $3.0 $9.4 $5.6 4% $19.6 10% $25.0 7% 28% 25% 3% $12.6 $15.6 14% 20% 22% 20% 24% 22% $16.9 $18.1 $21.5 $16.9 East Asia and Pacific South Asia East Asia and Pacific South Asia Latin America and Caribbean Europe and Central Asia Latin America and Caribbean Europe and Central Asia Sub-Saharan Africa Middle East and North Africa Sub-Saharan Africa Middle East and North Africa Source: Economics of Adaptation to Climate Change study team. Source: Economics of Adaptation to Climate Change study team. els of annual and maximum monthly precipi- mate change critical. The EACC study shows that tation. Urban infrastructure—urban drainage, coastal adaptation costs are significant and vary public buildings and similar assets—accounts for with the magnitude of sea-level rise, making it about 54 percent of the infrastructure adaptation essential for policymakers to plan while account- costs, followed by roads (mainly paved) at 23 per- ing for the uncertainty. One of the most striking cent. East Asia and Pacific and South Asia face results is that Latin America and the Caribbean the highest costs, reflecting their relative popula- and East Asia and Pacific account for about two- tions. Sub-Saharan Africa experiences the greatest thirds of the total adaptation costs (see figures 1 increase over time, with its adaptation costs rising and 2). from $1.1 billion a year for 2010–19 to $6 billion a year for 2040–50. Water supply. Climate change has already affected the hydrologic cycle, a process that is expected to Coastal zones. Coastal zones are home to an ever intensify over the century. In some parts of the growing concentration of people and economic world, water availability has increased and will activity, yet they are also subject to a number of continue to increase, but in other parts, it has climate risks, including sea-level rise and pos- decreased and will continue to do so. Moreover, the sible increased intensity of tropical storms and frequency and magnitude of floods are expected cyclones. These factors make adaptation to cli- to rise, because of projected increases in the inten- 6 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes FIGURE 3 FIGURE 4 The absolute costs of adaptation rise over time... ...but fall as a share of GDP Total annual cost of adaptation for National Centre for Total annual costs of adaptation for National Centre for Atmospheric Research (NCAR) scenario, by region and decade Atmospheric Research (NCAR) scenario as share of GDP, ($ billions at 2005 prices, no discounting) by decade and region (percent, at 2005 prices, no discounting) US$ billions Costs as percentage of GDP 30 0.8 2010–19 East Asia and Pacific 2020–29 2030–39 25 2040–49 0.6 20 Sub-Saharan Africa Latin America and Caribbean 0.4 15 South Asia 10 Europe and Central Asia 0.2 Middle East and North Africa 5 0.0 East Europe & Latin Middle East South Sub-Saharan 0 Asia & Central America & & North Asia Africa 2010–19 2020–29 2030–39 2040–49 Pacific Asia Caribbean Africa Source: Economics of Adaptation to Climate Change study team. Source: Economics of Adaptation to Climate Change study team. Note: EAP is East Asia and Paci c, ECA is Europe and Central Asia, LAC is Latin America and Note: EAP is East Asia and Paci c, ECA is Europe and Central Asia, LAC is Latin America and Caribbean, MNA is Middle East and North Africa, SAS is South Asia, and SSA is Caribbean, MNA is Middle East and North Africa, SAS is South Asia, and SSA is Sub-Saharan Africa. Sub-Saharan Africa. sity of rainfall. Accounting for the climate impacts, compared with 2000 levels. South Asia becomes a the study shows that water supply and flood man- much larger importer of food under both scenar- agement ranks as one of the top three adaptation ios, and East Asia and Pacific becomes a net food costs in both the wetter and drier scenarios, with exporter under the NCAR. In addition, the num- Sub-Saharan Africa footing by far the highest costs. ber of malnourished children rises with the decline Latin America and the Caribbean also sustain high in calorie availability brought about by climate costs under both models, and South Asia sustains change. high costs under CSIRO. Human health. The key human health impacts of Agriculture. Climate change affects agriculture by climate change include increases in the incidence altering yields and changing areas where crops can of vector-borne disease (malaria), water-borne be grown. The EACC study shows that changes in diseases (diarrhea), heat- and cold-related deaths, temperature and precipitation from both climate and injuries and deaths from flooding and in the scenarios will significantly hurt crop yields and prevalence of malnutrition. The EACC study, production—with irrigated and rain-fed wheat and which focuses on malaria and diarrhea, finds irrigated rice the hardest hit. South Asia shoulders adaptation costs falling in absolute terms over the biggest losses in production, but developing time to less than half the 2010 estimates of adap- countries fare worse for almost all crops compared tation costs by 2050. Why do costs decline in the with developed countries. Moreover, the changes in face of higher risks? The answer lies in the ben- trade flow patterns are dramatic. Under the NCAR, efits expected from economic growth and devel- developed country exports increase by 28 percent opment. While the declines are consistent across while under the CSIRO they increase by 75 percent regions, the rate of decline is more rapid in South The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 7 Asia and East Asia and Pacific than in Sub-Saha- young women who might otherwise be denied its ran Africa. As a result, by 2050 more than 80 per- many benefits. cent of health sector adaptation costs will be shouldered by Sub-Saharan Africa. Putting the findings in context Extreme weather events. In the absence of reli- able data on emergency management costs, the How does this study compare with earlier studies? EACC study tries to shed light on the role of socio- The EACC estimates are in the upper end of esti- economic development in increasing climate resil- mates provided by the UNFCCC (2007), the study ience. It asks: As climate change increases potential closest in approach to the EACC (table 2), although vulnerability to extreme weather events, how many not as high as suggested by a recent critique of the additional young women would have to be edu- UNFCCC study by Parry and others (2009). cated to neutralize this increased vulnerability? And how much would it cost? The findings show Why are the EACC estimates so much higher than that by 2050, neutralizing the impact of extreme those of the UNFCCC? To begin with, even though weather events requires educating an additional a comparison of the studies is limited by a number 18 million to 23 million young women at a cost of methodological differences (in particular, the use of $12 billion to $15 billion a year. For the period of a consistent set of climate models to link impacts 2000–50 as a whole, the tab reaches about $300 bil- to adaptation costs and an explicit separation of lion in new outlays. This means that in the devel- costs of development from those of adaptation in oping world, neutralizing the impact of worsening the EACC study), the major difference between weather over the coming decades will require edu- them is the sixfold increase in the cost of coastal cating a large new cohort of young women at a cost zone management and defense under the EACC that will steadily escalate to several billion dollars a study. This difference reflects several improve- year. However, it will be enormously worthwhile on ments to the earlier UNFCCC estimates under the other margins to invest in education for millions of EACC study: better unit cost estimates, including Table 2 Comparison of adaptation cost estimates by the United Nations Framework Convention on Climate Change and the Economics of Adaptation to Climate Change Economics of Adaptation to Climate Change study Commonwealth United Nations Framework National Centre for Scientific and Industrial Convention on Climate Atmospheric Research (NCAR), Research Organization Sector Change (2007) wettest scenario (CSIRO), driest scenario Infrastructure 2–41 29.5 13.5 Coastal zones 5 30.1 29.6 Water supply and flood protection 9 13.7 19.2 Agriculture, forestry, fisheries 7 7.6 7.3 Human health 5 2 1.6 Extreme weather events — 6.7 6.5 Total 28–67 89.6 77.7 Source: UNFCCC (2007) and Economics of Adaptation to Climate Change study team. 8 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes maintenance costs, and the inclusion of costs of projections of economic growth, structural change, port upgrading and risks from both sea-level rise climate change, human behavior, and government and storm surges. investments 40 years in the future. The EACC study has tried to establish a new benchmark for research of Another reason for the higher estimates is the this nature, as it adopted a consistent approach across higher costs of adaptation for water supply and countries and sectors and over time. But in the pro- flood protection under the EACC study, particularly cess, it had to make important assumptions and sim- for the drier climate scenario, CSIRO. This differ- plifications, to some degree biasing the estimates. ence is explained in part by the inclusion of riverine flood protection costs under the EACC study. Also • Adaptation costs are calculated as though deci- pushing up the EACC study estimate is the study’s sionmakers knew with certainty what the future comprehensive sector coverage, especially inclusion climate will be, when in reality current climate of the cost of adaptation to extreme weather events. knowledge does not permit even probabilis- tic statements about country-level climate out- The infrastructure costs of adaptation in the EACC comes. In a world where decisionmakers hedge study fall in the middle of the UNFCCC range against a range of outcomes, the costs of adap- because of two contrary forces. Pushing up the tation could be potentially higher. EACC estimate is its more detailed coverage of infrastructure. Previous studies estimated adaptation • Of the many global climate projections avail- costs as the costs of climate proofing new investment able for the baseline, only the set reporting flows and did not differentiate risks or costs by type maximum and minimum temperatures—and of infrastructure. The EACC study extended this within that set, only the two yielding the wet- work to estimate costs by types of infrastructure ser- test and the driest outcomes—were used. In vices—energy, transport, water and sanitation, com- addition, only one growth path was applied. munications, and urban and social infrastructure. A limited sensitivity analysis finds that a small Pushing down the EACC study estimate are mea- number of countries face enormous variability surements of adaptation against a consistently pro- in the costs of adapting to climate change given jected development baseline and use of a smaller the uncertainty about the extent and nature of multiplier on baseline investments than in the previ- climate change. Moreover, the costs of manag- ous literature, based on a detailed analysis of climate ing these risks could be substantially higher. proofing, including adjustments to design standards and maintenance costs. • Climate science tells us that the impacts will increase over time and that major effects such The one sector where the EACC study estimates are as melting of ice sheets will occur further into lower than the UNFCCC study is human health. the future. Even so, the study opted for project- This divergence is due in part to the inclusion of ing what is known today with greater certainty the development baseline, which reduces the num- rather than making even less reliable longer- ber of additional cases of malaria, and thereby term estimates. Thus the investment horizon of adaptation costs, by some 50 percent by 2030 under this study is 2050 only. A longer time horizon the EACC study. would increase the total costs of adaptation. The bottom line is that calculating the global cost of • The study looks only at additional public sector adaptation remains a complex problem, requiring (budgetary) costs imposed by climate change, The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 9 not the costs incurred by individuals and pri- uncertainty (especially on the science side), it gives vate agents. Similarly, the study generally opted policymakers—for the first time—a carefully cal- for hard adaptation measures that require an culated number to work with. The value added of engineering response rather than an institu- the study lies in the consistent methodology used tional or behavioral response. Soft adapta- to estimate the cost of adaptation—in particular, tion measures often can be more effective and the way the study operationalizes the concept of can avoid the need for more expensive physi- adaptation. cal investment. But as a first-cut global study, it was not possible to know whether effective Second, the world cannot afford to neglect miti- institutions and community-level collective gation. Adapting to an even warmer world than action, which are preconditions for the imple- the 2oC rise assumed for the study—on the order mentation of soft actions, exist in a given set- of 4oC above pre-industrial levels by the end of the ting. While incorporating private adaptation century—would be much more costly. Adapta- would increase cost estimates, including soft tion minimizes the impacts of climate change, but measures could potentially decrease them. it does not tackle the causes. If we are to avoid liv- ing in a world that must cope with the extinction of • Other limitations include not being able to half of its species, the inundation of 30 percent of incorporate innovation and technical change; coastal wetlands, and a large increase in malnutri- leaving out local-level impacts, particularly tion and diarrheal and cardio-respiratory diseases, the incidence on more vulnerable groups and countries must take steps immediately to sharply the distributional consequences of adapta- reduce greenhouse gas emissions. tion; not examining migration; and only par- tially accounting for adaptation costs related to Third, development is imperative, but it must take ecosystem services because of gaps in scientific a new form. Development is the most powerful understanding of the impact of climate change form of adaptation. It makes economies less reli- on ecosystems. Relaxing the first of these lim- ant on climate-sensitive sectors, such as agricul- itations could lead to significant reductions in ture. It boosts the capacity of households to adapt adaptation costs, while a more comprehensive by increasing levels of incomes, health, and educa- assessment of ecosystem services would lead to tion. It enhances the ability of governments to assist an increase. by improving the institutional infrastructure. And it dramatically reduces the number of people killed by floods and affected by floods and droughts. Lessons and recommendations But adaptation requires that we go about develop- ment differently: breeding crops that are drought Four lessons stand out from the study. and flood tolerant, climate proofing infrastructure, reducing overcapacity in the fisheries industry, and First, adaptation to a 2oC warmer world will be accounting for the uncertainty in future climate costly. The study puts the cost of adapting between projections in development planning. 2010 and 2050 to an approximately 2oC warmer world by 2050 at $75 billion to $100 billion a year. Countries may have to shift patterns of devel- The estimate is in the upper range of existing esti- opment or manage resources in ways that take mates, which vary from $4 billion to $109 bil- account of the potential impacts of climate change. lion. Although the estimate involves considerable Often, the reluctance to change reflects the polit- 10 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes ical and economic costs of changing policies and take research, collect data, and disseminate infor- (quasi-) property rights that have underpinned mation so that if climate change turns out to have decades or even centuries of development. Coun- worse impacts than anticipated in 20 or 30 years, tries experiencing rapid economic growth have an countries can respond more quickly and effectively. opportunity to reduce the costs associated with the In the meantime, countries should pursue low-cost legacy of past development by ensuring that future policies and investments on the basis of the best development takes account of prospective changes or median forecast of climate change at the coun- in climate conditions. The clearest, and probably try level. At the same time, countries should avoid most rewarding, opportunities to reduce adaptation making investments that will be highly vulnera- costs lie in the water sector, with coastal and flood ble to adverse climate change outcomes. For dura- protection. But other sectors also stand to benefit. ble climate-sensitive investments, strategies should maximize the flexibility to incorporate new climate Fourth, uncertainties are large, so robust and flex- knowledge as it emerges. Hedging against vary- ible policies and more research are needed. The ing climate outcomes, for example by preparing for imprecision of models projecting the future cli- both drier and wetter conditions for agriculture, mate is the major source of uncertainty and risk would raise the cost of adapting well beyond what for decisionmakers. Thus, it is crucial to under- has been estimated here. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 11 Section 1. Background and interventions, societies and ecosystems will not be Motivation able to adapt to impacts of this magnitude. Mit- igation, to avoid a further rise in greenhouse gas All countries, developing and developed, need to emissions, is the only way to deal with climate adapt to climate change. Even if global emissions change that is not already inevitable.2 of greenhouse gases are drastically reduced and concentrations are stabilized at 450 parts per mil- Adaptation will be costly, but there is little infor- lion (ppm) of equivalent carbon dioxide (CO2e), mation about just how costly. Under the Bali the annual global mean average temperature is Action Plan adopted at the 2007 United Nations expected to be 2oC above pre-industrial levels by Climate Change Conference, developed coun- the middle of the century.1 With a 2oC rise will tries agreed to allocate “adequate, predictable, come a higher incidence of intense rainfall events and sustainable financial resources and [to pro- and a greater frequency and intensity of droughts, vide] new and additional resources, including floods, heat waves, and other extreme weather official and concessional funding for developing events. Households, communities, and planners country parties” (UNFCCC 2008) to help them will need to take measures that “reduce the vulner- adapt to climate change. The plan views interna- ability of natural and human systems against actual tional cooperation as essential for building capac- and expected climate change effects” (IPCC 2007, ity to integrate adaptation measures into sectoral p. 3). Development will require such adaptation, and national development plans. Yet, studies on the and development progress may even be reversed as costs of adaptation (discussed in more detail later the increased incidence of extreme weather events in the report) offer a wide range of estimates, from and rising sea levels results in higher mortality and $4 billion to $109 billion a year. A recent critique of loss of assets, drawing resources from develop- these estimates suggests that they may be substan- ment; as greater incidence of infectious and diar- tial underestimates (Parry and others 2009). Simi- rheal diseases reverses development gains in health larly, National Adaptation Programmes of Action, standards; and as temperature and precipitation developed by the Least Developed Countries under changes reduce agricultural productivity and the Article 4.9 of the United Nations Framework Con- payoffs from agricultural investments. vention on Climate Change (UNFCCC), identify and cost only urgent and immediate adaptation While countries need to adapt to manage the measures and do not incorporate the measures into unavoidable, decisive mitigation is required long-term development plans. to avoid the unmanageable. Unless the world begins immediately to substantially reduce green- This Economics of Adaptation to Climate Change house gas emissions, annual global mean average (EACC) study is intended to fill this knowledge temperature will rise by some 2.5–7oC over pre- gap. Soon after the Bali Conference of Parties, a industrial levels by the end of the century. Temper- partnership of the governments of Bangladesh, ature increases of more than 2oC will substantially Plurinational State of Bolivia, Ethiopia, Ghana, increase the likelihood of irreversible and poten- Mozambique, Samoa, and Vietnam and the World tially catastrophic impacts such as the extinction Bank initiated the EACC study to estimate the cost of half of all species, inundation of 30 percent of coastal wetlands, and massive increases in malnu- 1 With current greenhouse gas concentrations at about 400 parts per million, annual average global temperature is already 0.8oC above pre- trition and diarrheal and cardio-respiratory dis- industrial levels. eases (World Bank 2010). Even with government 2 Mitigation is not discussed in this report, which focuses on adaptation. 12 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes of adapting to climate change. The study, funded by tries develop plans that incorporate measures nec- the governments of the Netherlands, Switzerland, essary to adapt to climate change. and the United Kingdom, also aims to help coun- The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 13 Section 2. Study Objectives For the global track, country-level data sets with and Structure global coverage are used to estimate adaptation costs for all developing countries by sector—infra- The EACC study has two broad objectives: to develop structure, coastal zones, water supply and flood a global estimate of adaptation costs for inform- protection, agriculture, fisheries and ecosystem ser- ing the international community’s efforts to help vices, human health, and forestry. The cost impli- the developing countries most vulnerable to climate cations of changes in the frequency of extreme change meet adaptation costs, and to help decision- weather events are also considered. For most sec- makers in developing countries assess the risks posed tors, a consistent set of future climate and precip- by climate change and design strategies for adapt- itation projections are used to establish the nature ing to it. That requires costing, prioritizing, sequenc- of climate change, and a consistent set of GDP and ing, and integrating robust adaptation strategies into population projections are used to establish a base- development plans and budgets. And it requires line of how development would look in the absence strategies to deal with high uncertainty, poten- of climate change. This information is used to esti- tially high future damages, and competing needs for mate economic and social impacts and the costs of investments for social and economic development. adaptation (left side of figure 1). Supporting developing country efforts to design For the country track, the impacts of climate adaptation strategies requires incorporating coun- change and adaptation costs are being estimated try-specific characteristics and sociocultural and only for the major economic sectors in each case economic conditions into analyses. Providing study country (see right side of figure 1). To com- macro-level information to developed and develop- plement the global analysis, vulnerability assess- ing countries to support international negotiations ments and participatory scenario development and to identify the overall costs of adaptation to cli- workshops are being used to highlight the impact mate change requires analysis at a more aggregate of climate change on vulnerable groups and to level. Reconciling the two needs involves a tradeoff identify appropriate adaptation strategies (see between the specifics of individual countries and a box 1). Macroeconomic analyses are being used global picture. to integrate the sectoral analyses and to identify cross-sector effects, such as relative price changes. The methodology developed for this study met Finally, in two country case studies (Bolivia and both objectives by linking the country-level analy- Samoa), an investment model is being developed sis with the analysis for estimating the global costs to prioritize and sequence adaptation measures of adaptation. Initially, the intention was to use (see box 2). country case studies to develop unit least costs of adaptation and then to apply them to similar adap- The two tracks are intended to inform each other, tation conditions in other developing countries. to improve the overall quality of the analysis. This As the country level analysis got under way, how- report presents the methodology and the results ever, it became clear that generalizing from the for the global track. The report for the case study seven country cases (the seven partnering coun- track will be released early in 2010, and lessons tries) would not work. A two-track approach—a from the country studies will be used to validate global track to meet the first study objective and a and improve the estimate of total adaptation costs, case study track to meet the second—would yield a resulting in a final report of the global track in more robust estimate. early 2010. 14 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Though the current report has undergone inten- is nonetheless considered a consultation draft. sive review, with internal World Bank reviews of Revisions to account for comments received dur- the concept note, methodology note, and draft ing the consultation process with a wide range of report and reviews of draft sector chapters by an stakeholders will also be incorporated in the final external and an internal expert, the current report report. FIGURE 1 Economics of Adaptation to Climate Change study structure: global and country tracks Global track Country track Sectors Projections Sectors Projections Infrastructure Climate Projections Global Infrastructure Climate Projections Sub-national Coastal Zones Water Runo Data Sets Coastal Zones Water Runo Data Sets Baseline GDP/Population Baseline GDP/Population Water Supply and Flood Management Water Supply and Flood Management Agriculture Agriculture Economic and Social Fisheries Economic and Social Fisheries Impacts Impacts Forestry and Ecosystem Services Forestry and Ecosystem Services Participatory Human Health Identi cation of Scenarios with Identi cation of Adaptation Measures Vulnerable Adaptation Measures Groups Cross-Sectors Cross-Sectors Decision Rule Extreme Weather Events Decision Rule Extreme Weather Events Cost of Adaptation Social Component Cost of Adaptation National Macroeconomic Analyses Source: Economics of Adaptation to Climate Change study team. Box 1 Understanding what adaptation means for the most vulnerable social groups The negative impacts of climate change will be experienced most intensely by the poorest people in developing countries. Just as development alone will not be enough to equip all countries or regions to adapt to climate change, neither do all individuals or households within a country or region enjoy the same levels of adaptive capacity (Mearns and Norton forthcoming). Drivers of physical, economic, and social vulnerability (socioeconomic status, dependence on natural resource–based livelihood sources, and physical location, compounded by factors that shape social exclusion such as gender, ethnicity, and migrant status) act as multipli- ers of climate risk for poor households. Social variables further interact with institutional arrangements that are crucial in promoting adaptive capacity, including those that increase access to information, voice, and civic representation in setting priorities in climate policy and action (World Bank 2010). Work is under way in six developing countries (Bangladesh, Plurinational State of Bolivia, Ethiopia, Ghana, Mozambique, and Viet- nam) under the EACC study to understand what adaptation means for social groups that are most vulnerable to the effects of climate change and what external support they need to help them take adaptation measures. This social component of the study combines vulnerability assessments in selected geographic hotspots with facilitated workshops applying participatory scenario development approaches. In the workshops, participants representing the interests of vulnerable groups identify preferred adaptation options and sequences of interventions based on local and national climate and economic projections. This approach complements the sectoral analyses of the costs of climate change adaptation in those countries. The findings on what forms of adaptation support various groups consider to be most effective—including “soft” adaptation options such as land use planning, greater public access to information, institu- tional capacity building, and integrated watershed management—have implications for the costs of adaptation. While this work is ongoing, some preliminary results from the country investigations in Bangladesh, Bolivia, Ethiopia, Ghana, and Mozambique are presented throughout this report to illustrate the range of adaptation options that are being suggested. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 15 Box 2 Climate-resilient investment planning A three-step methodology has been developed to help planners integrate climate risk and resilience into development policies and planning. The first is to identify and validate climate-resilient investment alternatives using a multicriteria decision analysis. This involves qualitative and quantitative impact assessments for each sector, consultation at the national level (government, policymak- ers, technical experts), and participatory workshops with community representatives and local authorities at the county level. The second step is to conduct a cost-benefit analysis for identified climate-resilient investment alternatives at a specific geographic unit. The final step is to implement an investment planning model that allows the government to prioritize and sequence robust adapta- tion strategies into development plans and budgets. Section 3. Operational Adaptation to climate change is also viewed as Definition of Adaptation Costs essential for development: unless agricultural soci- eties adapt to changes in temperature and precip- One of the biggest challenges of the study has been itation (through changes in cropping patterns, for to operationalize the definition of adaptation costs. example), development will be delayed. Finally, The concept is intuitively understood as the costs adaptation requires a new type of climate-smart incurred by societies to adapt to changes in climate. development that makes countries more resilient to The Intergovernmental Panel on Climate Change the effects of climate change. Urban development (IPCC) defines adaptation costs as the costs of plan- without attention to drainage, for example, will ning, preparing for, facilitating, and implementing exacerbate the flooding caused by heavy rains. adaptation measures, including transaction costs. But this definition is hard to operationalize. For one These links suggest that adaptation measures range thing, “development as usual” needs to be conceptu- from discrete adaptation (interventions for which ally separated from adaptation. That requires decid- adaptation to climate change is the primary objec- ing whether the costs of development initiatives tive; WRI 2007) to climate-smart development that enhance climate resilience ought to be counted (interventions to achieve development objectives as part of adaptation costs. It also requires decid- that also enhance climate resilience) to development ing how to incorporate in those costs the adaptation not as usual (rather than interventions that can deficit, defined as countries’ inability to deal with exacerbate the impacts of climate change and that current and future climate variability. It requires therefore should not be undertaken). Since the Bali defining how to deal with uncertainty about climate Action Plan calls for “new and additional” resources projections and impacts. And it requires specify- to meet adaptation costs, this report defines adap- ing how potential benefits from climate change in tation costs as additional to the costs of develop- some sectors and countries offset, if at all, adapta- ment. Consequently, the costs of measures that tion costs in another sector or country. would have been undertaken even in the absence of climate change are not included in adaptation costs, while the costs of doing more, doing different Links between adaptation and development things, and doing things differently are included. The climate change literature examines several links between adaptation and development. Many stud- Defining the adaptation deficit ies argue that economic development is the best hope for adaptation to climate change: develop- Adaptation deficit has two meanings in the litera- ment enables an economy to diversify and become ture on climate change and development. One cap- less reliant on sectors such as agriculture that are tures the notion that countries are underprepared most likely to be vulnerable to the effects of climate for current climate conditions, much less for future change. Development also makes more resources climate change. Presumably, these shortfalls occur available for abating risk. And often the same mea- because people are underinformed about climate sures promote development and adaptation. For uncertainty and therefore do not rationally allo- example, progress in eradicating malaria helps cate resources to adapt to current climate events. countries develop and also helps societies adapt to The shortfall is not the result of low levels of devel- the rising incidence of malaria that may accompany opment but of less than optimal allocations of lim- climate change. ited resources resulting in, say, insufficient urban 18 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes drainage infrastructure. The cost of closing this It is not obvious whether analyses that take a differ- shortfall and bringing countries up to an “accept- ent approach and measure costs of adaptation rela- able” standard for dealing with current climate tive to a baseline in which the adaptation deficit has conditions given their level of development is one been closed would estimate higher or lower adap- definition of the adaptation deficit (figure 2). The tation costs. In infrastructure, for example, closing second, perhaps more common, use of the term the adaptation deficit implies that a larger stock of captures the notion that poor countries have less infrastructure assets need be to climate-proofed, so capacity to adapt to change, whether induced by closing the deficit could increase adaptation costs. climate change or other factors, because of their In contrast, closing the adaptation deficit in agri- lower stage of development. A country’s adaptive culture might imply a lower percentage of rain-fed capacity is thus expected to increase with develop- agriculture and therefore a lower impact of cli- ment. This meaning is perhaps better captured by mate-change-induced droughts. Adaptation costs the term development deficit. are likely to be reduced in the agricultural sector as a result. Analyses that include the costs of clos- The adaptation deficit is important in this study for ing the adaptation deficit in the costs of adaptation establishing the development baseline from which are likely to estimate higher adaptation costs than to measure the independent, additional effects of those in this study. climate change. For example, should the costs of climate proofing infrastructure be measured rel- ative to current provision or to the levels of infra- Establishing the development baseline structure countries would have had if they had no adaptation deficit? Because the adaptation defi- Establishing the magnitude of the adaptation deficit cit deals with current climate variability, the cost of is not relevant for this study. Establishing the devel- closing the deficit is part of the baseline and not of opment baseline is. This is done sector by sector the adaptation costs. Unfortunately, except in the and assumes that countries grow along a “reason- most abstract modeling exercises, the costs of clos- able” development path. In agriculture, it is done ing the adaptation deficit cannot be made oper- by imposing exogenous, reasonable growth condi- ational (see box 3). This study therefore does not tions on current development achievements, such estimate the costs of closing the adaptation defi- as exogenous productivity growth, area expansion, cit and does not measure adaptation costs relative and investments in irrigation. In other sectors, to a baseline under which the adaptation deficit has such as infrastructure, the baseline is established by been closed. considering historical levels of infrastructure pro- FIGURE 2 A simpli ed interpretation of adaptation de cit Additional capacity needed to handle future climate change ADAPTATION COSTS Appropriate capacity ADAPTATION DEFICIT Appropriate capacity to deal with future climate change to deal with current climate variation Capacity to address current climate variation Source: Economics of Adaptation to Climate Change study team. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 19 Box 3. Difficulties in operationalizing the adaptation deficit Determining an acceptable level of adaptation to current climate variability is challenging. Some observers consider the cost of closing the adaptation deficit as the cost of making all developing countries—whatever their level of development—as prepared for current climate events as developed countries are. Others argue that the amount countries spend should depend on conditions in the country. For example, a poor country may devote fewer resources (than a rich country) on preventing loss of lives from storm surges and more resources on fighting malaria if more lives can be saved for the same amount of resources. Because these hard choices are necessary in a resource-constrained world, differences in the amount of resources devoted to adapt- ing to current climate variability cannot be used as a proxy for the adaptation deficit. Establishing the existence of an adaptation deficit requires first establishing that the benefit-cost ratio of expenditures in climate-sensitive areas exceed those of expenditures in all other sectors. Then estimating the size of the adaptation deficit requires estimating the degree of government underspend- ing in climate-sensitive areas relative to all other areas of the economy. Deficits for all developing countries would then need to be estimated to calculate the “global” adaptation deficit—clearly not feasible. vision, such as paved road density and length of projects, investing until the marginal benefits of sewer pipes, in countries at different levels of devel- the adaptation measure exceed the costs, which opment. Table 1 shows the definition of the devel- could lead to either to an improvement or a deteri- opment baseline adopted for each sector. oration in social welfare relative to a baseline with- out climate change. How much to adapt How much to adapt is consequently an economic problem—how to allocate resources to adapt to cli- The next issue is how much to adapt. One possi- mate change while also meeting other needs. And bility is to adapt completely, so that society is at there lies the challenge. Poor urban workers who least as well off as it was before climate change. At live in a fragile slum dwelling might find it diffi- the other extreme, countries could choose to do cult to decide whether to spend money to make nothing, experiencing the full impact of climate their living quarters less vulnerable to more intense change. Or countries could invest in adaptation rainfall, or to buy school books or first-aid equip- using the same criteria as for other development ment for their family—or how to allocate between Table 1 Definition of development baseline, by sector Sector Development baseline Infrastructure Average sector performance by income groups Coastal zones Efficient protection of coastline Water supply and Average municipal and industrial water demand by income groups; efficient protection against flood protection monthly flood with given return period Agriculture Exogenous productivity growth, area expansion, investment in irrigation Fisheries Maintenance of 2010 fish stocks Human health Health standards by income groups Forestry and ecosystem services Not establisheda Extreme weather events GDP-induced changes in mortality and numbers affected Source: Economics of Adaptation to Climate Change study team. a. For reasons discussed in section 5, development baselines were not established for this sector. 20 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes the two. Poor rural peasants might find it difficult plus residual damage (to the extent that resid- to choose between meeting these basic education ual damages are compensated, original welfare is and health needs and some simple form of irriga- restored). The one exception is coastal zones, where tion to compensate for increased temperatures and adaptation costs are defined as the cost of measures their impact on agricultural productivity. These to establish the optimal level of protection plus examples suggest that desirable and feasible levels residual damage. This study assumption is expected of adaptation depend on both available income and to bias the estimates upwards. other resources. Since costs are estimated by sector, sectoral proxies Corresponding to a chosen level of adaptation is for welfare were identified (table 2). In agriculture, an operational definition of adaptation costs. If the for example, welfare is defined by the number of policy objective is to adapt fully, then the cost of malnourished children and per capita calorie con- adaptation can be defined as the minimum cost of sumption. adaptation initiatives needed to restore welfare to levels prevailing before climate change. Restoring welfare may be prohibitively costly, however, and Adapt to what? Uncertainty about climate outcomes policymakers may choose an efficient level of adapta- tion instead. Adaptation costs would then be defined Operationalizing adaptation costs requires deal- as the cost of restoring pre-climate change welfare ing with the considerable uncertainty about future standards to levels at which marginal benefits exceed climate projections. Studies indicate that annual marginal costs. Because welfare would not be fully global mean average temperatures will increase restored, there would be residual damage from cli- (with a 2°C increase by 2050 now considered inev- mate change after allowing for adaptation. itable), rainfall will become more intense in most places and possibly less frequent, sea levels will In this study, largely due to limitations of exist- rise, other extreme climate events will become ing models, adaptation costs are generally defined more frequent and more intense, and regional cli- as the costs of development initiatives needed to mate systems such as the El Niño Southern Oscilla- restore welfare to levels prevailing before climate tion phenomenon and the Asian monsoon will be change and not as optimal levels of adaptation altered. Table 2 Welfare proxies for defining sectoral adaptation costs Sector Welfare proxy Infrastructure Level of services Coastal zones Optimal level of protection plus residual damage Water supply and flood management Level of industrial and municipal water availability; availability of flood protection Agriculture Number of malnourished children and per capita calorie consumption Fisheries Level of revenue Human health Health standard defined by burden of disease Forestry and ecosystem services Stock of forests; level of services Extreme weather events Number of deaths and people affected Source: Economics of Adaptation to Climate Change study team. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 21 Box 4 Special Report on Emissions Scenarios of the Intergovernmental Panel on Climate Change Adaptation requires understanding the potential impacts of climate change on human, economic, and ecological systems. Yet at- tempts to estimate such impacts have to take on a cascade of uncertainty, starting with the selection of an appropriate underlying emission scenario determined by economic and population growth and by energy use choices. Will the world grow rapidly or slowly? Will developing country populations soon adopt the consumption habits of high-income countries? And what kind of energy future are we to look forward to? To account for these questions, the Intergovernmental Panel on Climate Change (IPCC) has developed six socioeconomic scenarios that characterize possible trajectories of emissions. A scenario is a coherent, internally consistent, plausible description of a possible future state of the world. It is not a forecast; rather, each scenario is one alternative image of how the future could unfold, given a specific set of assumptions described in a set of four narrative storylines for the climate scenarios: A1 (focus on economic growth and globalization), A2 (regional focus), B1 (environmen- tal focused), and B2 (regional focus). According to the IPCC, all families of scenarios from each storyline are equally valid, with no assigned probabilities of occurrence. The choice of climate and related nonclimate scenarios is important because it can determine the outcome of a climate impact assessment. According to the IPCC, however, all scenarios have more or less the same projected temperature increase up to 2050 (a timeframe arguably more relevant for adaptation), even though there are large uncertainties regarding carbon dioxide emissions within each scenario. Therefore, the selection of scenarios for this study depends largely on the availability of global climate model data as well as some range of most “likely” future scenarios for the location of interest. While there is considerable consensus among cli- Atmospheric Research (NCAR)—for the A2 sce- mate scientists on these general outlines of climate nario (“storyline”) of the IPCC Special Report on change, there is much less agreement on how cli- Emissions Scenarios (SRES; see box 4). These maps mate change will affect a given location. Maps 1 illustrate qualitatively the range of potential cli- and 2 give a glimpse of this uncertainty for two mate outcomes with current modeling capabili- global climate models—that of the Common- ties and thus are indicative of the uncertainty in wealth Scientific and Industrial Research Organi- climate change impacts. For example, the NCAR zation (CSIRO) and that of the National Centre for model has substantially higher average maximum Map 1 Projected change in average maximum temperature based on two climate models, 2000–50 Commonwealth Scientific and Industrial Research National Centre for Atmospheric Research (NCAR), Organization (CSIRO), driest scenario wettest scenario Source: Maps are based on data developed at the Massachusetts Institute of Technology Joint Program for the Science and Policy of Global Change us- ing the WCRP’s CMIP3 multimodel dataset. Maps were produced by the International Food Policy Research Institute. Note: Projections are based on the A2 scenario of the IPCC Special Report on Emissions Scenarios (SRES). The Economics of Adaptation to Climate Change study team acknowledges the Program for Climate Model Diagnosis and Intercomparison and the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling for their roles in making available the WCRP’s Coupled Model Intercomparison Project phase 3 (CMIP3) multi- model dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. 22 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Map 2 Projected change in average annual precipitation based on two climate models, 2000–50 Commonwealth Scientific and Industrial Research National Centre for Atmospheric Research (NCAR), Organization (CSIRO), driest scenario wettest scenario Source: Maps are based on data developed at the Massachusetts Institute of Technology Joint Program for the Science and Policy of Global Change us- ing the WCRP’s CMIP3 multimodel dataset. Maps were produced by the International Food Policy Research Institute. Note: Projections are based on the A2 scenario of the IPCC Special Report on Emissions Scenarios (SRES). The Economics of Adaptation to Climate Change study team acknowledges the Program for Climate Model Diagnosis and Intercomparison and the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling for their roles in making available the WCRP’s Coupled Model Intercomparison Project phase 3 (CMIP3) multi- model dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. temperatures than does the CSIRO model and a against their benefits over a wide range of potential larger average increase in precipitation on land. climate outcomes (box 5). The EACC has calculated The CSIRO model has substantial precipitation the range of adaptation costs over dry (CSIRO) and declines in the western Amazon, while NCAR wet (NCAR) scenarios to bracket adaptation costs shows declines in the eastern Amazon. CSIRO has between the two extreme scenarios. In the real substantial precipitation declines in Sub-Saharan world, where decisionmakers must hedge against a Africa, while NCAR has increases there. range of outcomes, actual expenditures are poten- tially much higher than these estimates. Large-scale discontinuities create even greater uncertainty. Most uncertain are risks related to sys- temic changes, such as the melting of the Green- Summing potential costs and benefits land and West Antarctic ice sheets, the collapse of the Atlantic thermohaline circulation, and the die- This study estimates adaptation costs relative to back of the Amazon, all hard to predict and subject a baseline of what would have happened in the to sudden threshold changes that can trigger poten- absence of climate change. One possible outcome tially irreversible processes. The precise timing and is that changes in climate lead to lower investment level of these triggers cannot be projected with con- or expenditure requirements for some sectors in fidence, but the science is clear that these risks are some countries—for example, changes in demand substantial. for electricity or water that reduce requirements for electricity generating capacity, water storage, and Such inherent uncertainties in climate projections water treatment. In these cases, the “costs” of adap- suggest that a range of adaptation costs should be tation are negative. This is straightforward, but it estimated for a range of climate scenarios. They gives rise to another question: how should posi- also suggest that policymakers will have to hedge tive and negative costs be summed across sectors or when making decisions with long-term conse- countries? It is easy to envisage that higher expen- quences, weighing the current costs of investments ditures on coastal protection could be offset by The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 23 Box 5 Taking climate uncertainty into account: how should national policymakers interpret global numbers? Total adaptation costs for a specific climate projection are an estimate of the costs the world would incur if policymakers knew with certainty that that particular climate projection would materialize. But national policymakers do not have such certainty. At present, climate scientists agree that no climate model projection can be considered more likely than another. Disparities in precipitation projections, for example, mean that ministers of agriculture have to consider the risks of both the wettest and the driest scenarios and thus whether to invest in irrigation to cope with droughts or in drainage to minimize flood damage, while urban planners in flood-prone areas have to decide whether to build dikes (and how high) without knowing whether the future will be wetter or drier. The EACC has calculated the range of adaptation costs over dry (CSIRO) and wet (NCAR) scenarios to bracket adaptation costs between the two extreme scenarios. This provides a range of estimates for a world in which decisionmakers have perfect foresight. Actual expenditures are potentially much higher than these estimates because decisionmakers will have to consider a range of pos- sible outcomes. With such high costs involved, improving the certainty of the climate model projections is urgent, as are strategies that permit decisionmakers to remain flexible until better climate information is available. lower expenditures on electricity generation in the zero before costs are aggregated for the country and same country, but it is unlikely that higher expendi- for all developing countries. Under X-sums posi- tures on electricity generation in country A can be tive and negative items are netted within countries offset by lower expenditures in the same sector in country B.3 How then to define aggregates that add up consistently across sectors and countries? 3 A simple example illustrates the situation. Suppose that Brazil has a positive cost in both agriculture and water, meaning that both sectors will be negatively affected by climate change (relative to the no-climate- Box 6 illustrates three options for summing posi- change scenario), and suppose that India has a negative cost in agricul- ture and a positive cost in water, meaning that agriculture benefits but tive and negative costs when there are restrictions the water sector suffers from climate change. It may be reasonable to on offsetting negative and positive items: gross, net, assume that in India the gains in agriculture can compensate to some extent for the losses in the water sector. But it is unlikely that Brazil will and X-sums. Under the gross aggregation method, be compensated by India because Brazil incurs a cost and India a benefit negative costs in any sector in a country are set to in the agriculture sector. Box 6 Calculating aggregate costs—gross, net, and X-sums In summing positive and negative adaptation costs across countries, whether for a single sector or all sectors, three types of aggre- gate can be constructed (as illustrated by the hypothetical figures in the table). Summing positive and negative adaptation costs Country Sector aggregate Sector and type of aggregate A B C Sector gross Sector net Sector X-sum Sector 1 2 2 2 6 6 — Sector 2 8 –4 –2 8 2 — Sector 3 2 6 –4 8 4 — Country gross 12 8 2 22 — — Country net 12 4 –4 — 12 — Country X-sum 12 4 0 — — 16 — is not applicable. (continued on next page) 24 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Box 6 (continued) Calculating aggregate costs—gross, net, and X-sums Gross sum. The gross sum represents the aggregate costs incurred by countries with positive costs for a particular sector, ignoring all country and sector combinations resulting in negative costs. One difficulty with gross sums is that the results vary depending on how sectors are defined. This can be illustrated by recalculating the gross sums after combining sectors 1 and 2, giving an overall sectoral gross sum of 18 rather than 22, even though nothing else has changed (not shown in table). Net sum. The net sum treats positive and negative values symmetrically. It represents the pooled costs incurred by each country or each sector without restrictions on pooling across country borders. X-sum. X-sums take account of restrictions on pooling across countries, so all entries for a given country are set to zero if the net sum for the country is negative (see country C in the table). For the hypothetical data in the table, the overall gross sum is 22, and the overall net sums is 12. The difference between the two val- ues is the absolute value of negative entries for sectors 2 and 3 in countries B and C. The overall X-sum, which must fall between the overall gross and net sums, is 16. The difference between the overall X-sum and the overall net sum is 4, equal to the loss of pooling because of the net negative cost for country C. but not across countries, and costs for a country with the NCAR scenario. Most of these countries are included in the aggregate as long as the net cost are landlocked, buffering them from the substantial across sectors is positive for the country. In the net costs for coastal protection that constitute a large aggregate measure, negative costs are netted within part of the adaptation costs for coastal countries. and across countries. The net calculation is carried out by decade. Of 146 developing countries, 10 have All three options are used in the study to estimate negative net adaptation costs in at least one decade adaptation costs, though costs are mainly reported across all sectors with the CSIRO scenario and 5 as X-sums in the interest of space. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 25 Section 4. Methodology and the costs of planned, public policy adaptation mea- Value Added sures and exclude the costs of private adaptation. For agriculture, for example, the methodology allows for Although the methodology used to estimate the the effects of autonomous adjustments in the private impacts of climate change and the costs of adaptation sector, such as changes in production, consumption, is specific to each sector, the sectoral methodologies and trade flows in response to world price changes, share several elements. Adaptation costs in most sec- but does not include the costs of those adjustments tors were calculated for 2010–50 from a common in adaptation costs. These common methodological trajectory of population and GDP growth used to elements, along with wide and in-depth sectoral cov- establish the development baseline and a common erage and a consistent definition of adaptation costs, set of global climate models used to simulate cli- allow the study to substantially improve on earlier mate effects. For all sectors, adaptation costs include estimates (box 7). Box 7 Previous estimates of global adaptation costs World Bank (2006). The first estimate of costs of adaptation to climate change for developing countries was produced by the World Bank in 2006. Its report defined adaptation costs as the cost of climate proofing three categories of investment flows: official development assistance and concessional finance, foreign direct investment, and gross domestic investment. The study defined the proportion of total investments in each category that was likely to be climate sensitive and then estimated the percentage increases in costs to climate-proof these investments. Adaptation cost estimates ranged from $9 billion to $41 billion a year. Stern (2007) and UNDP (2007). Using the same methodology as World Bank (2006) but different values for the proportion of climate-sensitive investments and the increases in costs for climate proofing investments, the Stern Report (Stern 2007) estimated costs of adaptation of $4–$37 billion a year by 2050, somewhat lower than the World Bank estimate, while Human Development Report 2007/2008 (UNDP 2007) estimated costs of $5–$67 billion a year by 2015, somewhat higher than the World Bank estimate. In addition to the cost of climate proofing investments, Human Development Report 2007/2008 estimated that $40 billion a year would be needed by 2015 to strengthen social protection programs and scale up aid in other key areas and $2 billion a year to strengthen disaster response systems, boosting overall adaptation costs to $47–$109 billion a year by 2015. Oxfam International (2007). In contrast to these top-down approaches, Oxfam International (2007) used a bottom-up approach, estimating adaptation costs by assessing National Action Plans for Adaptation and the costs of adaptation projects initiated by non- government organizations. Assuming average warming of 2oC, the report estimated global adaptation costs of at least $50 billion a year: $7.5 billion a year to support adaptation efforts initiated by nongovernmental organizations, $8–$33 billion a year to meet the costs of the most urgent adaptation measures being proposed under the National Action Plans for Adaptation, and $5–$15 billion a year to address unknown and unexpected impacts. Though richer in the range of potential adaptation measures, this methodology uses a small and likely unrepresentative sample of projects and countries to generalize to all developing countries. UNFCCC (2007). Whereas previous efforts considered only the costs of planned adaptation, the United Nations Framework Conven- tion on Climate Change study considered the costs of both planned and private adaptation measures. Also, whereas previous studies had considered costs across all sectors, this report estimated the costs of adaptation by major sectors (agriculture, forestry, and fisheries; water supply; human health; coastal zones; and infrastructure), yielding total costs of $28–$67 billion a year by 2030. A recent critique of the UNFCCC estimates (Parry and others 2009) suggests that these estimates may be too low because some sectors were excluded (ecosystems, energy, manufacturing, retailing, and tourism), included sectors were not fully accounted for, climate proofing of infrastructure stocks ignored the need for additional stocks (financed through full funding of development) for handling current climate variability, and residual damages (impacts remaining after adaptation) were not accounted for. Project Catalyst (2009). The latest estimate was produced in 2009 by the Climate Works Foundation’s Project Catalyst initiative. This study estimated that annual average adaptation funding requirements for developing countries lie between $15 billion and $30 bil- lion for 2010–20 and between $30 billion and $90 billion by 2030. Softer measures, such as capacity building, planning, and research, are the focus of adaptation policy in the first decade, followed by more expensive structural investments in the second decade. Unlike previous estimates, the study accounts for potential co-benefits of adaptation actions and reduces the cost estimate to reflect these benefits. 26 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Choosing the timeframe Using baseline GDP and population projections to account for continuing development The choice of timeframe for the analysis of the costs of adapting to climate change will likely Most studies of adaptation to climate change hold affect the overall cost estimates, with a longer developing countries at their current level of devel- timeframe producing higher costs than would opment when estimating adaptation costs even a shorter one. The timeframe up to 2050 was over the medium term. Yet most developing coun- selected largely because forecasting climate change tries will become economically more advanced and its impacts on an economy becomes even over the medium term, which will alter the eco- more uncertain beyond this period, and the com- nomic impact of climate change and affect the type plexity of the analysis favors getting more pre- and extent of adaptation needed. As explained, the cise (or less imprecise) estimates in the near term EACC study accounts for the impact of develop- rather than less precise estimates over a more ment on estimates of adaptation costs by establish- extended timeline. ing development baselines by sector (see table 1). These baselines establish a fictional growth path Related to the issue of timeframe is the choice of in the absence of climate change that determines discount rate, which is related to the timing of sectoral performance indicators, such as stock of investments. The timing of all investments in the infrastructure assets, level of nutrition, and water sector models is determined by the outcomes of supply availability. Climate change impacts and specific climate projections. Given the expected cli- costs of adaptation are examined in relation to this mate outcome within the useful life of an invest- baseline. ment, each new investment must be designed to restore welfare (as defined in table 2) to levels that Baselines are established across sectors using a would have existed without climate change. Because consistent set of future population and GDP pro- of the complexity of modeling sectors at a global jections. The population trajectory is aligned with level, none of the sectoral models is capable of the United Nations Population Division’s mid- choosing the optimal timing of investments. This dle-fertility projections for 2006. To ensure con- implies that the time-paths of investments is insen- sistency with emissions projections, the GDP sitive to changes in the discount rate and there- trajectory is based on the average of the GDP fore all results are presented for a zero discount growth projections of the three major integrated rate though costs have been expressed in 2005 con- assessment models of global emissions growth— stant prices. Obviously, discounting the time stream Climate Framework for Uncertainty, Negotiation, of investment costs would lower the net present and Distribution (FUND; Anthoff and Tol 2008); value of total investment or adaptation costs, but it PAGE2002 (Hope 2006); and Regional Dynamic would not influence the choice of investments or Integrated Model of Climate and the Economy the underlying investment costs. The inability to (RICE99; Nordhaus 2001)—and growth projec- model policy tradeoffs across time is a clear limi- tions used by the International Energy Agency and tation imposed by the global nature of this study. the Energy Information Administration of the U.S. The selection of the discount rate and intertempo- Department of Energy to forecast energy demand. ral choices will be explored in depth in some of the All these sources provide growth estimates at a country case studies. regionally disaggregated level. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 27 The global average annual real GDP per cap- through 2050 to a historical climate baseline obtained ita growth rate constructed in this way is 2.1 per- from the University of East Anglia Climate Research cent, similar to global growth rates assumed in the Unit’s Global Climate Database time series 2.1. United Nations Framework Convention on Climate Change (UNFCCC) A2 emissions scenario (see box Analysis was limited to two scenarios rather than 4) from the Intergovernmental Panel on Climate the mean multiple of the global climate models Change (IPCC) Fourth Assessment Report (AR4), because the mean masks extreme values. A model once considered an extreme scenario but no longer average of near zero could be the result of mod- (IPCC 2007). The regionally downscaled GDP pro- els predicting near-zero change, but just as well the jections under different IPCC scenarios (available result of two opposing changes that differ in sign. from the Center for International Earth Science Using a group of global climate models (multi- Information Network, Columbia University) were model ensembles), as opposed to one model, can not used because they are based on older data. somewhat correct for biases and errors. The ques- tion with an ensemble approach is how to capture the full range of results from model runs. Choosing climate scenarios and global climate models Twenty-six global climate models provide cli- Selecting adaptation measures mate projections based on the IPCC A2 Special Report on Emission Scenarios (SRES) (see box 4). Adaptation measures can be classified by the types In this study, the National Center for Atmospheric of economic agent initiating the measure—pub- Research (NCAR) Community Climate System lic or private. The literature distinguishes between Model 3 (CCSM3) and Commonwealth Scientific autonomous or spontaneous adaptation (adapta- and Industrial Research Organization (CISRO) tion by households and communities acting on Mk3.0 models were used to model climate change their own without public interventions but within for the analysis of most sectors because they cap- an existing public policy framework) and planned ture a full spread of model predictions to represent adaptation (adaptation that results from a deliber- inherent uncertainty and they report specific cli- ate public policy decision). This study focuses on mate variables (minimum and maximum tempera- planned adaptation. This focus is not to imply that ture changes) needed for sector analyses. autonomous adaptation is costless. But since the objective is to help governments plan for risks, it Though the model predictions do not diverge much is important to have an idea of what problems pri- for projected temperature increases by 2050 (both vate markets will solve on their own, how public projecting increases of approximately 2oC above pre- policies and investments can complement markets, industrial levels), they vary substantially for pre- and what measures are needed to protect public cipitation changes. Among the models reporting assets and vulnerable people. For that, assessment minimum and maximum temperature changes, the of planned adaptation is needed. NCAR was the wettest and the CSIRO the driest sce- nario (globally, not necessarily the wettest and dri- In all sectors except extreme weather events, “hard” est in every location) based on the climate moisture options involving engineering solutions are favored index. Climate projections for these two models over “soft” options based on policy changes and were created at a 0.5 by 0.5 spatial degree scale and social capital mobilization (table 3). For adapta- a monthly time scale by applying model predictions tion to extreme weather events, the emphasis is on 28 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 3 Types of adaptation measures considered, by sector Sector Adaptation measure Infrastructure Design standards, climate proofing maintenance Coastal zones River and sea dikes, beach nourishment, port upgrades Water supply and flood Reservoir storage, recycling, rainwater harvesting, desalination; flood protection dikes and protection polders Agriculture Agricultural research, rural roads, irrigation infrastructure expansion and efficiency improvements Fisheries Fisheries buybacks, individual transferable quotas, fish farming, livelihood diversification mea- sures, marine protected areas Human health Prevention and treatment of disease Extreme weather events Investment in human resources Source: Economics of Adaptation to Climate Change study team. investment in human resources, particularly those countries and sectors and over time, establishing a of women. The decision to focus on hard options new benchmark for research of this kind. for the global cost assessment was motivated largely by fact that these are easier to cost. Though hard To do this, however, several important assump- adaptation options are feasible in nearly all set- tions and simplifications had to be made. The fea- tings, while soft options depend on social and insti- tures and limitations of the analysis for each sector tutional capital, the focus on hard options is not are discussed in the sector analyses in section 5. to suggest that they are always preferable. As dis- This section looks at five important limitations of cussed in box 8, adaptation measures being iden- the overall study methodology that arise from the tified in the companion case studies through need to simplify the problem sufficiently to derive participatory scenario workshops span both hard adaptation costs for all developing countries: char- and soft measures. Since hard options are typically acterization of government decisionmaking envi- more expensive than soft ones, this study assump- ronment, limited range of climate and growth tion is likely to give the estimates an upward bias. outcomes, limited scope in time and economic breadth, simplified characterization of human behavior, and top-down versus bottom-up analysis. Understanding the limitations of this study Calculating the cost of adaptation for develop- Stylized characterization of government ing countries requires simplifying a complex prob- decisionmaking environment lem involving multiple countries, institutions, decisionmakers, and projections of government The characterization of government decisionmak- investments into a world 40 years in the future. ing is the most problematic element of the study. This requires constructing projections of eco- As have all other attempts to estimate the total nomic growth, structural change, climate change, costs of adaptation, this study calculates adaptation and human behavior over a long time horizon and costs as if decisionmakers knew with certainty what for numerous sectors. Subject to these constraints, the future climate will be. In truth, current cli- the study has adopted a consistent approach across mate knowledge does not permit even probabilistic The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 29 Box 8 Adaptation measures identified in participatory workshops Participants in scenario development workshops identified several cross-cutting climate change impacts in infrastructure, natural resource management and agriculture, health and education, land tenure, governance and service delivery, and migration sup- port. Participatory scenario development methods were particularly good at eliciting information on intersectoral linkages among climate impacts and investments and the need for complementary investments. For example, female farmers and others in a local workshop in Kalu, Ethiopia, noted the multiple effects of climate variability on livelihood outcomes in the midland region. They noted that drought and water scarcity led to livestock disease, human health impacts, and reduced household farm productivity and income, resulting in the withdrawal of children from school, distress migration, and more deaths. Calls for adaptation support included investments in watershed management, drought-resistant crop varieties, nonfarm diversification, and capacity building. Lo- cal workshop participants in Xai-Xai, Mozambique, highlighted the different income groups within broad sectoral categories (such as commercial producers and nontimber forest collectors within agroforestry) and noted their varied preferences for adaptation invest- ments (see table). In addition, participants in both workshops identified not only vulnerable populations but also dynamic processes of migration, urbanization, and market development that were leaving some households more vulnerable than others. Livelihood groups identified in southern Mozambique participatory scenario development workshop Sector Income tiers Key climate impacts Select adaptation options sought Fishing • Commercial fishers • Sea level rise, abandonment of • Introduction of new fish species • Artisanal fishers fishing • Coastal zone pollution reduction • Increased salinity in estuaries, measures reduced fluvial fisheries Agroforestry • Harvesters (including commercial • Cyclones, loss of coastal vegeta- • Reforestation and dune protec- harvesters) tion, ecosystem change tion • Charcoal producers and fuelwood • Floods, destruction of forest ac- • Improved road construction plan- collectors cess routes ning • Construction pole gatherers • Drought, increased physical vul- • Community involvement and • Nontimber forestry product and nerability and species change education food gatherers Trade and • Informal and formal sector trading • Cyclones, destruction of infra- • Climate-proof infrastructure; im- commerce • Differential access to market structure and displacement of proved early warning systems (seasonal traders, retail traders, people • Improved erosion control through wholesale) • Sea level rise, coastal erosion and public works reduced land for development Agriculture and • Large, medium-size, and sub- • Floods and droughts, loss of • Barns for animals ranching sistence farmers (both rain-fed production, increased livestock • Improved early warning systems highland farmers and lowland/ disease and death • Better siting of farms floodplain farmers with irrigation) • Cyclones, loss of lives, crops, • Dam, floodgate construction infrastructure • Salinity intrusion Source: Xai-Xai, Mozambique, participatory scenario development workshop report. statements about country-level climate outcomes that decisionmakers know what future climate will and therefore provides virtually no help in inform- be and act to prevent its damages. ing country-level decisionmakers’ investment deci- sions.4 For most durable investment decisions, In fact, with current climate knowledge, country- decisionmakers know with certainty only that cli- level decisionmakers face a different problem—how mate in the future will differ from climate today. 4 Although some researchers have, as a practical expedient, constructed tri- The adaptation costs calculated in this study and angular probability densities to represent the range of global climate model in all other global studies are based on the fiction outcomes, most climate scientists would object to this use of their data. 30 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes to maximize the flexibility of investment programs means that the study has estimated only the addi- to take advantage of new climate knowledge as it tional public sector (budgetary) costs imposed by becomes available. While this decision problem can climate change, not overall economic damages. be explored at the country level, it is intractable in These additional costs for the provision of pub- a global study. Without the assumption of perfect lic goods must not be confused with overall eco- foresight, it would be impossible to calculate adap- nomic damages and cannot be usefully compared tation cost for developing countries in all but the with mitigation costs. The investment horizon of most highly stylized and aggregated models. If such this study is to 2050 only. Climate science tells us an analysis were possible, though, costs of adapta- that adaptation costs and damages will increase tion to climate change would likely be higher than over time, and that major effects such as melting those in this study. of major ice sheets are more likely to occur well beyond this horizon. Limited range of climate and growth outcomes Simplified characterization of human behavior Even with this strongly stylized characterization of the decision problem, overall model complex- Hard adaptation versus soft adaptation. Most ity permits systematic exploration of only a small difficult to project is human behavior, especially range of potential outcomes. The two major drivers developments in institutions and the political econ- of adaptation costs are climate outcome and eco- omy. Many adaptive measures are best imple- nomic growth. Of the 26 climate projections avail- mented through effective collective action at the able for the A2 SRES, a complete assessment of community level. However, the circumstances adaptation costs was possible only with 2. Explo- that elicit effective collective action are complex ration of alternative growth paths was even more (Ostrom 1990). Soft adaptation measures, such restricted, with only one future applied across all as early warning systems, community prepared- sectors.5 Sensitivity analysis was performed in var- ness programs, watershed management, urban ious sectors, however (as described later). For cli- and rural zoning, and water pricing, generally rely mate outcomes, sensitivity analysis suggests that on effective institutions supported by collective one or two global climate models predict adap- action. Because it is easier to cost hard measure and tation costs in several South Asian countries that because it is impossible to know, in a global study, are orders of magnitude greater than those of the whether such institutional preconditions exist in a other climate models. For growth, sensitivity analy- given setting, this study has generally opted to esti- sis indicates that the results are much less sensitive mate hard adaptation measures that require an than for climate outcomes, as would be expected. engineering response.6 Not a recommendation, While more growth increases the assets at risk, it this is rather a simplifying assumption to make raises incomes and reduces vulnerability. the study tractable. To the extent that local institu- tions exist that can employ more effective and less Limited scope in economic breadth and time 5 However, the growth path used in this study represents a consensus growth path among climate modelers and is chosen to be consistent with To make calculations tractable, the study had to the emissions level underlying the A2 SRES. limit both the breadth and the time span of eco- 6 An exception is the inclusion in the agriculture sector assessment of a number of soft measures, such as water harvesting in the adaptation nomic analysis. For the economic analysis, this measure “irrigation reform.” The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 31 Box 9 Migration and climate change—Ghana’s experience Climate change impacts are expected to induce large new migration flows. The number of environmental migrants (people moving in response to environmental degradation, extreme events, or related economic conditions; see Warner and others 2009) is projected to rise in coming decades, with the vast majority seeking residence in large cities. Migration was a recurring theme in the EACC participatory scenario development workshops, as well as in field-level investigations. This box highlights some key findings from Ghana. Drought in the northern savannah region of Ghana has long triggered migration to the country’s coastal cities. Rural-urban mi- gration creates vulnerabilities at a number of levels. New migrants live in informal housing and often in peri-urban areas without services. They also typically lack social ties and access to information in their new locations. Recent migrants to Accra reside in unplanned developments in highly risky sites including flood-prone and malarial marshlands. Migration occurs disproportionately among young men, leaving women, children, and the elderly to tend to agricultural lands and putting household farm production and food security at risk because of lack of household labor. Rural-rural migration also leads to problems, especially in land access and ownership for production. Resource rights are tenuous for recent migrants—at least 80 percent of land in Ghana is administered through customary law institutions, including local chiefdoms, that can be exclusionary. Focus group participants in Dzatakpo, Ghana, stated that the local chief has given only land use rights to immigrants, rather than full land rights. Immigrants in Buoyem, Ghana, were reluctant to plant long-gestation (and higher value) crops because of insecure access to land. Sharecropping and use-right rules in the Western Region of Ghana also impede sustainable land management. Because failure to clear a piece of forested land for cultivation within two years of acquisition results in forfeiture, the rule leads to destruction of forest resources. Despite rising numbers of migrants to the Western Region, this customary practice has not changed, highlighting the slow pace of adaptation of some local institutions to changing circumstances. Key policy responses to environmental migration include social protection support to migrants, such as easing place-based resi- dence requirements for accessing social services; investing in sending regions so as to reduce the flow of migrants, as Ghana is doing with its northern development strategy; and considering rights-based resettlement for populations directly displaced by climate impacts, such as sea-level rise. expensive soft adaptation measures, this assump- receiving substantial numbers of migrants. This is, tion imparts an upward bias to the global cost. however, more likely to become a serious issue in the second half of the century. Migration behavior. Decisions to migrate are also strongly mediated by community processes and The efficiency of adaptation. Economic models social capital. Because social processes that cre- normally assume fully rational behavior—produc- ate poverty and marginality are more important ers maximize profits, consumers maximize welfare, determinants of likely migration outcomes than governments provide public goods using cost-ben- are environmental changes themselves, in theory efit criteria to choose the most efficient projects, it should be possible to reduce the likelihood of and projects are implemented optimally through migration arising from climate change. However, time to maximizes the net present value of the gov- in the absence of vastly improved political and eco- ernment’s future investment stream. None of the nomic structures that can reduce poverty, environ- sector models used in this study is capable of inter- mental change will continue to be an important temporal optimization. Calculations in each sec- proximate factor in migration decisions (box 9). tor ensure that service levels are maintained despite The estimates in this study are based on demo- climate change, but no effort was made to iden- graphic projections by the United Nations Popula- tify whether the resources invested in one sector to tion Division that do not take climate change into counter the effects of climate change would have account. Population movements across countries yielded a higher benefit-cost ratio in another sector may impose heavy infrastructure costs in areas (except in the sea-level rise component) or whether 32 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes cash transfers would maintain welfare at less cost. Top-down or bottom-up analysis As a result, the adaptation costs calculated in this study are almost certainly inefficient, even within In the final report of this study, this global the framework of the study. This simplification approach will be supplemented by country case imparts an upward bias to the adaptation costs. studies. But this report on the global track relies on a mixed top-down sectoral approach to coun- Innovation and technical change. Most parts of try analysis because of the difficulty of generalizing the study do not allow for the unknowable effects from country studies when there is no clear basis of innovation and technical change on adapta- for scaling up country results. It is “mixed” because, tion costs. In effect, these costs are based on what for countries that are too large and too heteroge- is known today rather than what might be possible neous to be treated as a single analytical unit, the in 20–40 years. Sustained growth in per capita GDP basic analytical units include river basins and food for the world economy rests on technical change, production units. It would have been preferable which is likely to reduce the real costs of adaptation to estimate the costs of adaptation for infrastruc- over time. This treatment of technological change ture at the subnational rather than national level in also contributes to an upward bias in the calcu- all countries with a population of, perhaps, 50–100 lated costs. The exception is agriculture. Growth million or more. However, data availability and in total factor productivity in agriculture, based on economic consistency are difficult to ensure at the historical trends and expert opinion, is built into subnational level. the model, and explicit investment in research is included in the costs. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 33 Section 5. Key Results likely to be climate sensitive is multiplied by the percentage increase in construction costs (table 4). This section presents the key results of the EACC However, none of these studies provides a strong global track study of the costs of adaptation to cli- analytic basis for its choice of parameter values for mate change for developing countries. Results by climate proofing. And none accounts for the costs sector are followed by a discussion of consolidated of climate proofing existing stocks of capital. global costs and the results of sensitivity analysis. In this study, analysis of the infrastructure sector begins by projecting stocks of major types of infra- Sector analyses structure over 2010–50 that would have existed under the development baseline without climate The sector analyses cover infrastructure, coastal change. Infrastructure services include transport zones, water supply and flood management, agri- (mainly roads, rail, and ports), electricity, water culture, fisheries, human health, forestry and eco- and sanitation, communications, urban and social system services, and extreme weather events. infrastructure such as urban drainage, health and education facilities (rural and urban), and gen- eral public buildings. Adaptation cost is computed Infrastructure as the additional cost of constructing and operat- ing and maintaining these baseline levels of infra- Adaptation costs for infrastructure assets have structure services under the new climate conditions been one of the largest components of total adap- projected by the NCAR (wetter) and CSIRO (drier) tation costs in past estimates—the largest in the global climate models. This cost is referred to as United Nations Framework Convention on Cli- the delta-P cost of adaptation because it focuses on mate Change (UNFCCC 2007) study (the closest in price and cost changes for fixed quantities of infra- approach to this study). Previous studies have esti- structure (see box 10 for details). mated adaptation costs for infrastructure as the costs of climate proofing new investment flows (see Considerable work went into developing infra- box 6). The percentage of new investment flows structure-specific dose-response relationships Table 4 Estimates of adaptation costs for infrastructure from previous studies (billions) Percent of Additional costs to reduce New investment flows new investment sensitive risk from climate change Costs Study ($ billions) to climate (percent) ($ billions) World Bank (2006) 1,760a 2–40 10–20 9–41 Stern (2007) 1,760 a 2–20 5–20 4–37 UNDP (2007) 3,112 b 2–33 5–20 5–67 UNFCCC (2007) 5,417c 1–3 5–20 2–41 Source: Economics of Adaptation to Climate Change study team analysis of listed sources. a In 2000. b In 2005. c In 2030, backed out as mean of upper and lower bounds. 34 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes between climate variables (dose) and the unit costs distinguished for existing assets in 2010 and for new of construction (response) and between climate assets constructed after 2010. Existing assets require variables (dose) and operation and maintenance more maintenance and perhaps modification of (response), which were used to estimate adaptation short-lived components to cope with climate stresses costs (table 5 presents details for one type of infra- not taken into account when they were built, such as structure, paved roads). resurfacing roads or replacing heating and cooling equipment. New assets, built to standards that take For most types of infrastructure, dose-response func- climate change into account, require only normal tions for construction costs captured adjustments maintenance. Finally, allowances were made for the in building standards to enable assets to withstand impact of climate change on the efficiency of power predicted changes in climate conditions. Standards, generation and water and sewage treatment—partic- assumed to be forward looking, were adjusted so that ularly in response to higher maximum temperatures. infrastructure would withstand changes for 50 years from the date of construction, reflecting the typical Under the NCAR scenario, the total delta-P costs life of infrastructure assets. Maintenance costs were of adaptation average $29.5 billion a year over Box 10 Infrastructure sector methodology The starting point for estimating the costs of adaptation are baseline projections of infrastructure demand in physical units by coun- try at five-year intervals with no climate change. These projections are derived from econometric equations estimated using historic panel data, including GDP per capita at purchasing power parity exchange rates, population structure, urbanization, country charac- teristics, and climate variables as independent variables. Two econometric specifications were used: panel regressions representing average levels of infrastructure, and stochastic frontier regressions representing the “efficient” levels of infrastructure given the values of the independent variables. In the period from t to t + 1, say from 2010 to 2015, the country will have to invest to meet the new level of infrastructure in t + 1 and to replace infrastructure existing at date t that reaches the end of its useful life during the period. Thus, the total value of investment in infrastructure of type i in country j and period t is (1)  Iijt = Cijt [Qijt+1– Qijt+ Rijt]  where Cijt is the unit cost of investment, Qijt+1 – Qijt is the quantity of new investment in infrastructure, and Rijt is the quantity of existing infrastructure that has to be replaced. The change in the total cost of infrastructure investment may be expressed as the total differ- ential of equation 1 with respect to the climate variables that affect either unit costs or efficient levels of provision for infrastructure of type i: (2)  ∆Iijt = ∆Cijt [Qijt+1– Qijt+ Rijt] + (Cijt+ ∆Cijt [∆Q+ijt+1– ∆Qijt + ∆Rijt].  An equivalent equation may be derived for operation and maintenance costs. The first part of the right side of equation 2 is referred to as the delta-P component of the cost of adaptation, and the second part as the delta-Q component. These components cover several ways in which climate change might cause changes in the costs or quantities of infrastructure services. The delta-P component combines the baseline projections of infrastructure assuming no climate change with estimates of the percentage changes in the unit costs of constructing, operating, and maintaining infrastructure as a consequence of climate change. The changes in unit costs are derived from dose-response relationships estimated from the engineering-economic literature on the costs of adjusting asset design and operational standards to hold infrastructure performance constant under different climate condi- tions. The factors that drive the costs include average and maximum monthly temperatures, total annual and maximum monthly precipitation, and maximum wind speed. The dose-response relationships for operating and maintenance costs for existing assets differ from those for newly constructed assets, which are designed to cope with the projected climate over the life of the assets. (continued on next page) The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 35 Box 10 (continued) Infrastructure sector methodology The delta-Q component of equation 2 captures the impact of climate change on demand for infrastructure services, taking account of the higher unit costs of constructing and operating infrastructure. This has two dimensions. Climate change may change the level or composition of demand for energy, transport, and water at given levels of income, so the net impact on capital and operating costs has to be calculated. Climate change will also mean that countries have to invest in additional assets to maintain standards of protection for noninfrastructure activities or services. For water management and flood management and for coastal protection, this dimension of the delta-Q component is addressed in specific sector studies, while for infrastructure the analysis includes the first dimension plus other adjustments that are not captured elsewhere, such as changes in health infrastructure. The econometric analysis involves estimating a reduced form equation describing demand for infrastructure: (3)  Qijt= hi {Pjt , Yjt , Xjt , Vjt , t}  where Pjt is the population of country j in period t; Yjt is average income per capita for country j in period t; Xjt is a vector of country characteristics for country j in period t (including an index of construction costs); and Vjt is a vector of climate variables for country j in period t. Since there are no strong priors on the appropriate functional forms, a standard flexible functional form is used to represent the demand equation hi{ } in terms of the explanatory variables using a restricted version of the translog specification for variables other than population. Because in practice, it is often difficult to estimate the full translog specification using the more complex econo- metric models, the analysis started with the log-linear specification and then tested whether the coefficients on the quadratic and cross-product terms were significant. To deal with the claim that climate variables—especially average temperature—may act as a proxy for institutional and other fac- tors that shaped past patterns of economic development, the values of demographic variables in 1950 are used in the models as instruments for institutional development, following the approach of Acemoglu, Johnson, and Robinson (2001). Other country-fixed effects include country size and the proportions of land area that are desert, arid, semiarid, steep, or very steep and the proportion of land with no significant soil constraints for agriculture using standard Food and Agriculture Organization land classifications. The use of differently weighted climate variables (population-weighted and inverse population-weighted mean temperature, total precipi- tation, temperature range, and precipitation range) captures the differences between climate conditions in more and less densely populated areas. Table 5 Examples of dose-response relationships for paved roads, 2010–50 Type of cost Precipitation Temperature Construction costs Change in costs of constructing 1 kilometer Change in cost of constructing 1 km of paved road per (km) of paved road per 10 centimeter (cm) stepwise increase in maximum of monthly maximum change in annual precipitation projected dur- temperature values projected during lifespan relative ing lifespan relative to baseline climate; dose- to baseline climate; the first increase occurs after a 1oC response represents change in costs for every change in maximum temperature. Every other step 10 cm increment occurs at 3oC beyond that Maintenance costs Existing assets Change in annual maintenance costs for 1 km Change in annual maintenance costs for 1 km per 3oC of paved road per 10 cm change in annual change in maximum of monthly maximum tempera- rainfall projected during lifespan relative to ture projected during lifespan baseline climate New assets Paved roads constructed after 2010 would have no maintenance impact if designed for changes in climate expected during their lifetime Source: Economics of Adaptation to Climate Change study team. 36 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 6 Annual delta-P costs of adaptation for infrastructure, by region and period, 2010–50 ($ billions at 2005 prices, no discounting) East Asia and Europe and Latin America and Middle East Sub-Saharan Period Pacific Central Asia Caribbean and North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario 2010–19 6.8 1.5 1.8 0.9 3.8 1.1 15.9 2020–29 9.5 1.9 2.8 1.2 6.6 2.3 24.3 2030–39 11.3 4.4 3.9 1.5 8.7 3.9 33.7 2040–49 14.8 5.3 5.4 1.8 10.7 6.1 44.1 Average 10.6 3.3 3.5 1.4 7.5 3.4 29.5 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario 2010–19 3.1 0.7 1.3 0.6 1.4 0.7 7.8 2020–29 3.3 1.1 1.6 0.5 1.5 1.0 9.0 2030–39 4.3 1.5 1.8 0.9 3.9 1.7 14.1 2040–49 5.6 2.1 2.1 1.4 9.1 2.6 22.9 Average 4.1 1.4 1.7 0.9 4.0 1.5 13.5 Source: Economics of Adaptation to Climate Change study team. Note: Delta-P cost is the adaptation cost computed as the additional cost of constructing, operating, and maintaining baseline levels of infrastructure services under the new climate conditions projected by the two global climate models. 2010–50 (table 6). The decade averages increases The highest adaptation costs are in East Asia and from nearly $16 billion a year in 2010–19 to more Pacific and South Asia, reflecting their larger popu- than $44 billion a year for 2040–50. Adaptation lations. Sub-Saharan Africa experiences the largest costs are considerably lower under the CSIRO sce- increase over time, with its adaptation cost ris- nario, averaging $13.5 billion a year for the period ing from $1.1 billion a year for 2010–19 to $6 bil- compared with $29.5 billion for the NCAR sce- lion a year for 2040–50. This rapid rise is associated nario, though also increasing over time. The NCAR with a low share of maintenance costs in total costs scenario is significantly wetter than the CSIRO and is driven by the need for large investments in scenario in Asia and parts of Africa. Because adap- infrastructure to support future economic growth. tation costs for infrastructure are particularly sen- In contrast, countries in Europe and Central Asia sitive to levels of annual and maximum monthly face maintenance costs that are larger than capi- precipitation, the NCAR scenario has a larger tal costs after 2030, reflecting the pattern of climate impact on the costs of building and maintaining change under the NCAR scenario for Russia and roads, urban drainage, and buildings for countries Central Asia. The same result does not emerge for in South Asia, Southeast Asia, and Southern Africa. the CSIRO scenario, a reminder of how different climate scenarios can affect the character and the By far the largest delta-P costs of adaptation under magnitude of projected adaptation costs. the NCAR scenario are for constructing new or replacing existing infrastructure (table 7). The Urban infrastructure (urban drainage, public build- share of maintenance costs rises gradually but is ings, and similar assets) accounts for 54 percent of still less than 10 percent in 2040–50. The pattern the delta-P adaptation cost over 2010–50, followed for the CSIRO scenario is similar (not shown). by roads (mainly paved roads) at 23 percent. (Box The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 37 Table 7 Annual delta-P costs of adaptation for infrastructure for the National Centre for Atmospheric Research (NCAR) climate scenario, by region and cost type, 2010–50 ($ billions at 2005 prices, no discounting) East Asia and Europe and Latin America and Middle East Sub-Saharan Period and cost type Pacific Central Asia Caribbean and North Africa South Asia Africa Total 2010–19 Capital 6.7 1.2 1.8 0.9 3.8 1.1 15.5 Maintenance 0.1 0.2 0 0 0 0 0.3 Total 6.8 1.4 1.8 0.9 3.8 1.1 15.9 2020–29 Capital 9.3 1.7 2.7 1.2 6.5 2.3 23.7 Maintenance 0.2 0.2 0.1 0 0.1 0 0.7 Total 9.5 1.9 2.8 1.2 6.6 2.3 24.3 2030–39 Capital 11.1 1.9 3.8 1.3 8.6 3.9 30.6 Maintenance 0.3 2.5 0.2 0.2 0.1 0.1 3.4 Total 11.4 4.4 4.0 1.5 8.7 4.0 33.7 2040–49 Capital 14.1 2.3 5.0 1.5 10.4 5.9 39.2 Maintenance 0.7 3.0 0.4 0.2 0.2 0.1 4.6 Total 14.8 5.3 5.4 1.7 10.6 6.0 44.1 Source: Economics of Adaptation to Climate Change study team. Note: Delta-P cost is the adaptation cost computed as the additional cost of constructing, operating, and maintaining baseline levels of infrastructure services under the new climate conditions projected by the two global climate models. 11 describes some of the private adaptation costs adaptation cost is 1.6 percent of total infrastruc- for urban housing that are not covered by planned ture costs. These shares contrast with those of pre- adaptation.) Networks and associated assets (power vious studies, which use ranges of 0.01 percent to generation, electricity transmission and distribution, 8 percent to estimate adaptation costs (see table 4, fixed telephone lines, water and sewage treatment) where equivalent parameters are obtained by mul- account for less than 9 percent of the estimated cost tiplying percentage of climate sensitive new invest- of adaptation even though they account for about 45 ments by percentage increases in costs) and fail to percent of total infrastructure costs. differentiate by type of asset. These differences in parameter values explain in part why the EACC For comparison, table 8 also shows the total costs estimates of adaptation costs for infrastructure of providing each type of infrastructure (not just ($15–$30 billion a year) fall between the maximum climate proofing)—the baseline cost. The costs and the minimum of past estimates ($2–$67 billion of adaptation are 4.6 percent of the total costs of a year; see table 4). infrastructure provision over the period for urban infrastructure, 2.3 percent for roads and 2.1 per- Thus far the analysis has assumed that climate cent for other transport, and less than 1 percent change does not affect demand for infrastruc- for the other infrastructure categories. Overall, the ture, but only the cost of providing it compared 38 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Box 11 Urban housing and climate change Planned adaptation costs do not account for the high adaptation costs of urban housing, which are largely individually provided. EACC estimates annual average household investments in urban housing in response to climate change at $2.3 billion (in 2005 dol- lars) per year in 2010, rising to $25.6 billion a year by 2050, under the CSIRO climate scenario. Under the NCAR scenario, annual costs rise even more, from an average of $4.4 billion a year in 2010 to $45.5 billion by 2050. Under both scenarios, costs are highest in East Asia and Pacific (followed by Latin America and the Caribbean under CSIRO and Europe and Central Asia under NCAR). The costs of adaptation related to housing would be even higher if they also accounted for slums. Most informal settlements in developing countries share characteristics that intensify the vulnerability of their residents to climate change (Moser and Satterth- waite forthcoming). These include poorly constructed buildings; inadequate infrastructure; lack of safe drinking water, drainage, and sanitation services; and severe overcrowding with attendant public health impacts. Municipal governments often neglect or even criminalize such settlements, exacerbating the problem of underprovisioning of protective infrastructure and services. These factors combine with high concentrations of poor people with few assets to make slums especially vulnerable to flooding and other extreme events, which can lead to loss of lives and property and the spread of disease. As discussed in the participatory scenario workshops, Ghana presents considerable challenges in adapting urban slums to climate change. Rural migrants to Accra and increasingly to Ghana’s secondary towns cluster in overcrowded slums with poor sanitation. Workshop participants report that floods are more severe in these sprawling urban spaces of coastal Ghana than in inland towns, in part because of weak urban planning. Urbanization, especially in slums, increases the risk of climate-related disasters such as flood- ing and landslides, in part because natural ecosystem-based storm breaks and rain catchment areas are increasingly converted to public buildings and housing developments. with the no-climate change scenario. However, cli- and infrastructure demand (table 9). In most cases, mate change is likely to affect the demand for infra- the impact of climate change depends on interac- structure services as well. For example, the optimal tions among per capita GDP, urbanization, and the investment in roads would vary depending on range between maximum and minimum temper- whether climate change alters the structure of the atures or precipitation. As a consequence, the pre- economy and thus the location of economic activ- dicted impact of climate change on demand for ity, or more or higher dykes might be needed to infrastructure by country ranges from –5 percent cope with sea-level rise and storm surges (see the to +5 percent of baseline investment. discussion of adaptation cost for coastal zones). Called the delta-Q component of adaptation cost The overall impact is negative in most large coun- because it focuses on changes in the quantity of tries, with the exception of the Europe and Central infrastructure required in response to changes in Asia region, so the net quantity adjustment reduces demand, this component is difficult to estimate, for the overall cost of adaptation by $19 and $22 bil- reasons discussed in box 12, and in several cases lion a year for the two scenarios. This is equivalent it was also difficult to identify mechanisms that to a reduction of about 1 percent of the baseline cost could explain counterintuitive results. Therefore, of infrastructure, demonstrating that small shifts in although estimates of delta-Q are presented in table demand can have a very large impact on the total 9 for illustrative purposes, they are not used to cal- cost of adaptation. With the NCAR scenario, the culate adaptation costs for infrastructure assets. net cost of adaptation for infrastructure declines from $29.5 billion a year to $7.3 billion a year when A comparison of infrastructure estimates with the delta-Q adjustment is included. Since the total and without estimated changes in infrastructure delta-P cost of adaptation is relatively small for the demand indicates that the demand equations do CSIRO scenario, including delta-Q more than off- not imply any simple relationships between climate sets the price effect of climate change, leaving a net The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 39 Table 8 Breakdown of baseline and delta-P costs of adaptation for the National Centre for Atmospheric Research (NCAR) climate scenario, by region and infrastructure category, 2010–50 ($ billions at 2005 prices, no discounting) Infrastructure category and adaptation or East Asia and Europe and Latin America and Middle East and Sub-Saharan baseline cost typea Pacific Central Asia Caribbean North Africa South Asia Africa Total Health and education Adaptation 1.1 0.7 0.4 0.2 0.5 0.1 3.0 Baseline 123.6 87.8 68 36.3 54.3 16.2 386.2 Power and wires Adaptation 0.6 0.6 0.2 0.1 0.3 0.1 1.9 Baseline 164.3 108.8 62.9 25.9 82.8 21.3 466 Roads Adaptation 1.8 0.7 1 0.6 1.4 0.8 6.3 Baseline 60.1 47.9 43.1 23.4 57.2 36.5 268.2 Other transport Adaptation 0.2 0.3 0.1 0.1 0.1 0.1 0.9 Baseline 9.6 16.2 5.6 1.8 4.7 3.7 41.6 Urban infrastructure Adaptation 6.6 0.8 1.6 0.3 4.9 2.3 16.5 Baseline 105.1 83.3 40.3 12.2 85.7 29 355.6 Water and sewers Adaptation 0.3 0.1 0.1 0 0.2 0 0.7 Baseline 140.7 61 63 26.5 67.8 23.4 382.4 All infrastructure Adaptation 10.6 3.3 3.5 1.3 7.4 3.4 29.5 Baseline 603.5 405.1 282.8 126.2 352.5 130.1 1900.2 Source: Economics of Adaptation to Climate Change study team. Note: Delta-P cost is the adaptation cost computed as the additional cost of constructing, operating, and maintaining baseline levels of infrastructure services under the new climate conditions projected by the two global climate models. a The baseline cost is defined as the sum of capital and maintenance expenditures over the lifetime of the asset. reduction in the cost of infrastructure due to climate lead to either more or less demand for infrastruc- change. On the other hand, using the gross aggre- ture. However, for the reasons outlined in box 12, gate cost measure (not allowing for cross-country the delta-Q values are not used in this report’s esti- transfers and setting benefits to zero) leads to higher mates of the overall cost of climate change. estimates of adaptation costs because the larger neg- ative delta-Q adjustments are excluded (not shown). Coastal zones This is an important area for further investigation. The economic viability of certain areas will cer- Coastal zones, home to an ever-growing concentra- tainly be altered by climate change, which could tion of people and economic activity, are subject to 40 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes several climate risks, including rising sea level and making adaptation to climate change critical, partic- increased intensity of tropical storms and cyclones, ularly in small islands and deltaic countries (box 13). Box 12 Why this study reports only delta-P and not delta-Q adaptation costs The econometric equations used for this study, based on historical data, reflect the location of economic activity (and the conse- quent demand for infrastructure) in response to a given climate, not the relocation of economic activity (and the consequent change in the demand for infrastructure) as a result of a change in climate. These long-run relationships reflect an equilibrium between the influences of climate and economic variables. The literature on path dependency suggests that how a country responds to external shocks such as climate change may depend critically on its current stock of assets, which is codetermined with the current location of economic activity. The counterargument is that the effects of climate change on demand for infrastructure are small relative to the impact of economic development over 40 years or more, so the effects of path dependency are swamped by the structural changes implied by the development baseline. Another hurdle concerns econometric specification. The data used for the analysis are a combination of time-series and cross-country variables. Like other fixed country characteristics, climate variables are constant over time, so their influence has to be estimated from cross-country variation alone. Many studies rely on cross-country variation for key explanatory variables—for example, studies of the effects of governance and trade policy on economic growth. The cross-country variables help to explain a set of country-fixed effects that are combined with the influence of factors (GDP per capita, population, urbanization, and so on) that vary across time and countries. The difficulty is that one or more climate variable might act as a proxy for country characteristics that influence the demand for infrastructure but that are not included in the analysis, so the coefficient on the climate variable will reflect both its direct influence on demand and its correlation with the omitted factor. Omitted variables are a potential problem in all econometric analysis, and it is impossible to demonstrate a negative—that the coefficients on the climate variables are not affected by omitted variables. The most that can be done is to include additional variables that might be better proxies for potential influences that cannot be included in the equations and to use specifications—such as interactions with time-varying factors—that reduce or eliminate correlation between omitted variables and climate variables. The influence of climate variables on demand for infrastructure remains an open area of research. There is ample evidence that some climate variables have an impact on specific types of infrastructure, such as temperature on energy demand or precipitation on water use. There is much less agreement on how these influences operate in the longer term and on whether the relationships can be extended to all categories of infrastructure. In view of these uncertainties, the final estimates of the costs of climate change exclude the delta-Q adjustments. Table 9 Alternative measures of the annual cost of adaptation for infrastructure, by region ($ billions at 2005 prices, no discounting) East Asia and Europe and Latin America and Middle East and Sub-Saharan Cost component Pacific Central Asia Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario Delta-P only 10.6 3.3 3.5 1.3 7.4 3.4 29.5 Delta-P + Delta-Q (0.1) 8.9 (1.2) (0.7) 0.2 0.2 7.3 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario Delta-P only 4.1 1.4 1.7 0.9 4.0 1.5 13.6 Delta-P + Delta-Q (3.0) 6.5 (3.0) 0.2 (2.7) (3.0) (5.0) Source: Economics of Adaptation to Climate Change study team. Note: Delta-P cost is the adaptation cost computed as the additional cost of constructing, operating, and maintaining baseline levels of infrastructure services under the new climate conditions projected by the two global climate models. Delta-Q cost accounts for changes in the quantity of infrastruc- ture required in response to changes in demand under the new climate conditions projected by the two climate models. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 41 Box 13 Adaptation costs for deltaic countries and small islands states Deltaic countries and small island states are particularly at risk for sea-level rise induced by climate change. For deltaic communities, ongoing subsidence and land conversion may exacerbate the effects of sea-level rise or extreme sea levels caused by intense storms. Small island states are vulnerable because of their small size, limited resource base, and geographic isolation. Adaptation costs and residual damages for the medium sea-level rise scenario suggest that the costs of adapting to climate change for deltaic countries are nearly $4.5 billion per year (see table), or about 15 percent of the total cost of adaptation estimated here. Adaptation costs for small island states are more than $1 billion a year, or about 3 percent of the total estimated cost of adaptation. In relative terms, the adaptation costs are higher still, averaging 1 percent of GDP in small island states over 2010–50 compared with 0.03–0.1 percent for other developing countries. Residual damage costs as a percentage of GDP are also higher in deltaic and small island states than in other countries, even after the large adaptation investments considered here. Average annual coastal adaptation costs and residual damage, 2010–50 Brazil, Russia, India, and Other developing Cost category Deltaic countriesa Small island statesb China countries Adaptation cost Amount ($ billions, 2005 4.5 1.0 9.0 14.1 prices, no discounting) Share of GDP (percent) 0.1 1.0 0.03 0.1 Residual damage Amount ($ billions, 2005 0.62 0.01 0.52 0.36 prices, no discounting) Share of GDP (percent) 0.01 0.01 0.002 0.002 Source: Economics of Adaptation to Climate Change study team. Note: Residual damages are impacts remaining after adaptation. a Includes Bangladesh, Burma, China, Egypt, French Guiana, Guyana, India, Iraq, Mozambique, Nigeria, Pakistan, Romania, Suriname, Thailand, Ukraine, Venezuela, and Vietnam. While no country is entirely deltaic, in these countries the coastal impacts and adaptation costs are strongly influenced by deltaic areas. b State or territory with a land area of less than 30,000 square kilometers (sq km) occupying an island or group of islands that are separately less than 20,000 sq km. This definition excludes Cuba, Haiti, and the Dominican Republic. This study estimates costs for coastal adaptation pre-climate change levels. These improvements over 2010–50 by building on earlier UNFCCC significantly raise the cost of adaptation to cli- estimates (Nicholls 2007) in several ways. It mate change for coastal zones over the UNFCCC considers the adaptation costs of more intense estimate. storms as well as rising sea level, extends the UNFCCC estimates from 2030 to 2050, includes The analysis considers two main types of impact maintenance as well as construction costs, and (coastal erosion, and sea and river flooding and adds the costs of port upgrade. And, as discussed submergence) and three adaptation approaches in section 3, it defines costs as those needed to (beach nourishment, particularly in areas achieve an efficient level of adaptation. Selected with high tourism revenue; sea and river7 dike residual damages from climate change are also reported (impacts remaining after adaptation, such as land loss costs and number of people 7 This concerns the incremental costs of upgrading river dikes in coastal lowlands where sea-level rise will result in extreme water levels. Ad- flooded) and added to adaptation costs in esti- ditional upgrades may be required if extreme river flows are increased, mating the resources needed to restore welfare to but this is not investigated here. 42 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes construction; and port upgrade). Impacts due to Uniform population growth is imposed on the salinization and wetland loss are not considered EACC projections of population and GDP growth, (see box 14 for details). so that coastal populations do not grow relative to other areas. However, a scenario of no popula- The analysis considers four scenarios of global sea- tion growth is also considered, in which all future level rise: a no-rise (or reference) case of no cli- growth happens in areas that will not be affected by mate change and low, medium, and high sea-level sea-level rise. rise scenarios based on the Intergovernmental Panel on Climate Change (IPCC) Fourth Assess- Following best engineering practice for sea and ment Report (Meehl and others 2007) and Rahm- river dikes, dike building anticipates sea-level rise storf (2007) (table 10). These useful and plausible in terms of additional height needed 50 years into scenarios reflect the uncertainty in climate pro- the future (thus dike heights in 2050 are deter- jections. They are not specifically linked to tem- mined by expected extreme sea levels in 2100). perature rise, however, because of uncertainties in For other adaptation measures, there is no antic- the timing of glacial melting. An arbitrary 20 per- ipation of future conditions, again reflecting best cent increase in flood heights is assumed under engineering practice. Adaptation methods are the high sea-level rise scenario by 2100 to reflect applied in a standard way around all the world’s intensification of storms in areas currently subject coasts using criteria that select optimum or quasi- to such storms. optimum adaptation strategies. Selected residual Box 14 Coastal zone methodology Adaptation costs for coastal zones are derived mainly from the Dynamic and Interactive Vulnerability Assessment (DIVA) model, based on 12,148 coastal segments that make up the world’s coast (except for Antarctica) and a linked database and set of interacting algorithms (MacFadden and others 2007; Nicholls and others 2007; Vafeidis and others 2008). The sea-level rise scenarios are down- scaled with an estimate of the vertical land movement in each segment. The coastal erosion analysis considers only sandy coasts and takes account of the direct effect (Bruun effect) and indirect effects of sea-level rise, as well as beach nourishment where it occurs. The indirect effects occur at major estuaries and lagoons. The flooding analysis determines the flood areas for different return periods and extreme water levels, including the effects of dikes. Since empirical data on actual dike heights are not available at a global level, “optimum” dikes heights were estimated for the base year of 1995 using a demand for safety function.1 Dike heights are then upgraded according to projected sea-level rise to 2050. In- creased flooding due to sea-level rise along the coastal-influenced reaches of major global rivers (identified in the DIVA database) is also considered. Damages are evaluated in terms of physical, social, and economic indicators such as land lost to erosion or submer- gence, the number of people expected to be subject to annual flooding, the number of people forced to migrate because of land loss, and the costs of this migration. DIVA implements the adaptation options according to complementary adaptation strategies. For beach nourishment, a cost-benefit adaptation strategy balances costs and benefits (damage avoided) of adaptation, including the tourist value of beaches. For dike building, the demand function for safety is applied over time, subject to population density. Dikes are built only when population density exceeds 1 person per square kilometer, with an increasing proportion of the recommended height being built as population density rises—for example, 98 percent of the dike height is built at densities of 1,000 people per square kilometer. The unit costs of beach nourishment, dikes, and port upgrades were derived from the global experience of Delft Hydraulics (now Deltares). For this analysis, DIVA was extended to include a sensitivity analysis of more intense tropical storms. This influences adaptation costs only for dikes. The maintenance costs of sea and river dikes and port upgrades globally are also computed outside DIVA. Port costs are based on a strategy of continuously raising existing port areas as sea levels rise.2 1 The demand for safety function increases with per capita income and population density and decreases with the cost of dike building, an approach that is posited as the solution to a cost-benefit analysis (Tol 2006). 2 All new port areas are assumed to include sea-level rise to 2050 in their design, so upgrade costs will be effectively zero. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 43 Table 10 –2100 Sea-level rise under four scenarios, 2010­ (centimeters above 1990 levels) Year No sea-level rise Low sea-level rise Medium sea-level rise High sea-level rise 2010 0.0 4.0 6.6 7.1 2020 0.0 6.5 10.7 12.3 2030 0.0 9.2 15.5 18.9 2040 0.0 12.2 21.4 27.1 2050 0.0 15.6 28.5 37.8 2060 0.0 19.4 37.0 50.9 2070 0.0 23.4 47.1 66.4 2080 0.0 28.1 58.8 84.4 2090 0.0 33.8 72.2 104.4 2100 0.0 40.2 87.2 126.3 Source: Neumann (2009). Note: The low-rise scenario is derived as the midpoint of the IPCC AR4 A2 range in 2090–99, a trajectory consistent with a Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC, a coupled gas-cycle/climate model) IPCC Third Assessment Report A2 mid-melt 3oC sensitivity run. The medium-rise scenario is derived from the Rahmstorf (2007) A2 trajectory. The high-rise scenario is derived from the Rahmstorf (2007) maximum A2 trajectory. impacts that remain even with adaptation are also Coastal adaptation costs are substantial and vary reported (impacts remaining after adaptation, with the magnitude of sea-level rise (table 11), such as land loss costs, coastal flood costs, and the making it essential for policymakers to plan while number of people flooded), stressing that much accounting for the uncertainty. Flooding dominates larger investments would be required to avoid all both the adaptation costs (of building dikes) and impacts of sea-level rise, if this is even possible or the costs of damages due to the residual risk. Sea- desirable. level rise does not have a large effect on the size of Table 11 Annual costs of adaptation for coastal zone protection, by scenario and cost component, 2010–50 ($ billions at 2005 prices, no discounting) High sea-level rise with Coastal zone cost component Low sea-level rise Medium sea-level rise High sea-level rise cyclones Beach nourishment 1.7 3.3 4.5 4.5 River dikes 0.2 0.4 0.6 0.6 Sea dikes 10.7 24.6 36.7 39.1 Port upgrades 0.2 0.4 0.5 0.5 Residual damages a 0.7 1.5 2 2 Total 13.5 30.2 44.3 46.7 Source: Economics of Adaptation to Climate Change study team. Note: The low-rise scenario is derived as the midpoint of the IPCC AR4 A2 range in 2090–99, a trajectory consistent with a Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC, a coupled gas-cycle/climate model) IPCC Third Assessment Report A2 mid-melt 3oC sensitivity run. The medium-rise scenario is derived from the Rahmstorf (2007) A2 trajectory. The high-rise scenario is derived from the Rahmstorf (2007) maximum A2 trajectory. a Includes impacts remaining after adaptation, such as land loss, coastal flooding, and number of people flooded. 44 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes residual damages—the main effect is an increased steps could reduce the need for protection measures investment in adaptation. and could lead to lower adaptation costs than those estimated here (these softer measures are very diffi- An analysis of how adaptation costs and residual cult to cost, which is why that was not done). Real- damages are distributed for the medium sea-level izing these benefits will require long-term strategic rise scenario indicates that Latin American and planning and more integration across coastal plan- the Caribbean and East Asia and Pacific together ning and management. Few if any countries have account for some two-thirds of the total cost of this capacity today, and strengthening institutional adaptation (table 12). Deltaic countries and small capacity for integrated coastal management would island states are particularly at risk (see box 13). seem a prudent response to climate change (also yielding benefits in other areas). Increased tropical storm intensity does not raise annual costs substantially, and targeting future population growth outside the coastal floodplain Industrial and municipal water supply does not reduce costs substantially, as the existing and riverine flood protection development already creates a substantial need for protection. Climate change has already affected the hydrologic cycle, and the impacts are expected to continue and Clearly, a wider range of adaptation options than intensify over the century. Where water availability considered in the DIVA model (see box 13) are has increased, the increase is expected to continue, available in practice, including retreating from and where it has decreased it is expected to con- coastal zones and accommodating higher water lev- tinue to decrease. Projected increases in the inten- els by raising buildings above flood levels. These sity of rainfall are expected to boost the frequency Table 12 Annual cost of adaptation for coastal zone protection and residual damages for the medium sea-level rise scenario, by region, 2010–50 ($ billions at 2005 prices, no discounting) Type of adaptation East Asia and Europe and Latin America Middle East and Sub-Saharan cost and period Pacific Central Asia and Caribbean North Africa South Asia Africa Total Total adaptation cost a 2010–19 7.6 2.4 8.5 1.0 1.6 3.2 24.3 2020–29 8.4 2.6 9.5 1.2 1.7 3.7 27.1 2030–39 9.2 2.8 10.6 1.3 1.9 4.2 30.0 2040–49 10.0 3.1 11.7 1.4 2.1 4.8 33.1 Residual damageb 2010–19 0.3 0.0 0.1 0.0 0.0 0.0 0.4 2020–29 0.6 0.0 0.1 0.0 0.1 0.0 0.8 2030–39 1.1 0.0 0.2 0.0 0.3 0.0 1.6 2040–49 1.3 0.1 0.4 0.1 0.9 0.0 2.8 Source: Economics of Adaptation to Climate Change study team. a Includes beach nourishment, river and sea dikes, and port upgrades. b Includes impacts remaining after adaptation, such as land loss, coastal flooding, and number of people flooded. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 45 and magnitude of floods. Policymakers need to costs of adaptation for raw industrial and munici- understand these changes and adapt to them. pal water supply. Other methodological improve- ments include use of a longer time horizon (to 2050 The analysis of the costs of adaptation for water rather than 2030); analyses of the baseline without management includes industrial and municipal climate change and of the baseline changes under water supply (box 15) and excludes water for agri- climate change, whereas the previous studies exam- culture and ecosystem services. Irrigation is consid- ined the combined costs of adaptation to socioeco- ered in the discussion of the agricultural sector, and nomic development and climate change and then water management for ecosystem services is implic- assumed the costs related to climate change to be itly dealt with by limiting future withdrawals to no 25 percent of the total; and use of hydrologic mod- more than 80 percent of total runoff, with no further els to estimate change in generic reservoir capac- withdrawals permitted in river basins where current ity. In addition, this study estimates the global costs water withdrawals are already more than 80 percent. of adaptation related to riverine flood protection, which the other studies did not consider, by ana- In a methodological improvement over previ- lyzing the costs of protecting against river flooding ous studies (Kirshen 2007, subsequently modi- in urban and agricultural areas against the 50-year fied by UNFCCC 2007), the sectoral water balance monthly flood in urban areas and the 10-year is maintained, with any change in agricultural monthly flood (maximum monthly runoff) in agri- withdrawals accounted for before computing the cultural areas (see box 15). Box 15 Water sector methodology The effects of climate change on the water cycle were assessed by running the Climate and Runoff model (CLIRUN-II) on a monthly time-step. The key parameters were monthly runoff and the magnitude of the 10-year and 50-year maximum monthly runoff. The results were aggregated to the 281 food production units of the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) developed by the International Food Policy Research Institute. The analysis considers industrial and municipal water supply and riverine flood protection. Water supply. Costs of adaptation are defined as the cost of providing enough raw water to restore future industrial and municipal water demand to the levels that would have existed without climate change. Such demand is assumed to be met by increasing the capacity of surface reservoir storage, except when that would raise withdrawals to more than 80 percent of river runoff and when the cost of supplying water from reservoir yield is more than $0.30 a cubic meter. In these cases, supply is assumed to be met through alternative measures, such as recycling, rainwater harvesting, and desalination, at a cost of $0.30 a cubic meter. Additional reservoir storage capacity to meet future water demand is calculated using storage-yield curves showing the storage capacity needed to provide a given yield and reliability of water supply over the year. The storage yield curves were developed using simulated time series of monthly runoff and evaporation from CLIRUN-II. The costs of reservoir construction were based on a method relating topography to cost, and annual operation and maintenance costs were assumed to be 2 percent of construction costs. Three scenarios were used to estimate the size distribution of future reservoirs: small dams, with all future reservoirs having a storage capacity under 25 million cubic meters; large dams, with all future reservoirs having a storage capacity greater than 12,335 million cubic meters; and best estimate, with future construction assumed to follow the same size distribution as in the 20th century in the United States. The results in this section are shown for the best estimate scenario. Flood protection. Costs are defined as the cost of providing flood protection against the 50-year monthly flood (maximum monthly runoff ) in urban areas and the 10-year monthly flood in agricultural areas. First, the baseline costs (without climate change) of pro- viding flood protection to all urban and agricultural areas were estimated. Then, the costs of adaptation were estimated by assuming that the costs of providing flood protection rose by the same percentage as the percentage change in the magnitude of the 50-year or 10-year monthly flood event. Flood protection was assumed to be provided through a system of dikes and polders, at a cost of $50,000 per square kilometer in urban areas and $8,000 per square kilometer in agricultural areas (these cost estimates were derived from World Bank case studies). Annual operation and maintenance costs were assumed to be 0.5 percent of construction costs. 46 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Adaptation costs for industrial and municipal raw models, and South Asia sustains high costs under water supply are higher for the CSIRO simulations, CSIRO because these regions experience the larg- with its drier global mean conditions, than for est percentage decline in mean runoff (see map the NCAR simulations, with its wetter conditions 3). The gross costs of adaptation are significantly (table 13 and map 3), because more reservoir stor- greater than the net costs, especially for water sup- age capacity is required to provide the same yield. ply: $23.9 billion gross and $13.3 billion net annual The adaptation costs for riverine flood protection cost under NCAR and $26.2 billion gross and $16.9 are also greater for the CSIRO scenario because the billion net annual cost under CSIRO. These differ- model simulates a larger increase in the magnitude ences are driven mainly by the decreased need for of the 10-year and 50-year monthly flood events storage capacity in South Asia and East Asia and than does the NCAR scenario, despite relatively Pacific under both scenarios because of increased drier mean conditions. mean runoff (see map 3). The highest costs are in Sub-Saharan Africa under As do most sectoral studies of global adaptation both climate scenarios. Latin America and the costs, this study focuses on hard adaptation mea- Caribbean also sustain high costs under both sures, which are easier to cost than behavioral Table 13 Gross and net annual adaptation costs for water supply and riverine flood protection, by region, 2010–50 ($ billions at 2005 prices, no discounting) Type of cost calculation East Asia and Europe and Latin America Middle East and Sub-Saharan and protection category Pacific Central Asia and Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario Gross Flood protection 0.9 1.7 1.0 0.2 1.1 0.4 5.3 Water supply 3.1 1.7 5.3 0.5 1.8 6.2 18.6 Total 4.0 3.4 6.3 0.7 2.9 6.6 23.9 Net Flood protection 0.8 1.4 0.3 –0.2 1.0 0.3 3.6 Water supply 0.3 0.9 5.2 0.0 –2.3 5.9 10.0 Total 1.1 2.3 5.5 –0.2 –1.3 6.2 13.3 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario Gross Flood protection 1.6 0.9 2.0 0.6 1.7 0.2 7.0 Water supply 2.1 0.5 2.9 0.2 5.9 7.6 19.2 Total 3.7 1.4 4.9 0.8 7.6 7.8 26.2 Net Flood protection 1.6 0.6 1.7 0.5 1.6 –0.2 5.8 Water supply 0.6 –0.3 1.5 –0.4 2.4 7.3 11.1 Total 2.2 0.3 3.2 0.1 4.0 7.1 16.9 Source: Economics of Adaptation to Climate Change study team. Note: Gross costs set negative values to zero for sector protection in any country with negative costs. Net costs are the pooled costs without restrictions on pooling across country borders (positive and negative values are treated symmetrically). The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 47 Map 3 Change in mean water runoff under the Commonwealth Scientific and Industrial Research Organization and National Centre for Atmospheric Research global climate scenarios, 2000–50 Commonwealth Scientific and Industrial Research National Centre for Atmospheric Research (NCAR), Organization (CSIRO), driest scenario wettest scenario Percent Change –47.998565 – –27.340140 –27.340139 – –14.615619 –14.615618 – –5.301159 –5.301158 – –0.094757 –0.094756 – 7.634688 7.634689 – 18.756277 18.756278 – 35.557648 35.557649 – 71.269003 71.269004 – 121.399735 121.399736 – 251.572685 Note: The Economics of Adaptation to Climate Change study team acknowledges the Program for Climate Model Diagnosis and Intercomparison and the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling for their roles in making available the WCRP’s Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. Source: Maps are based on data developed at the Massachusetts Institute of Technology Joint Program for the Science and Policy of Global Change us- ing the WCRP’s CMIP3 multimodel dataset. Maps were produced by the International Food Policy Research Institute. measures. There is no implication that these are to pre-climate change levels. One of the few earlier the best measures for adaptation. Ideally, adapta- estimates of adaptation costs for agriculture takes tion options to ensure water supply during average a simpler approach, assuming that an arbitrary 10 and drought conditions should integrate strategies percent increase in research and extension funding on both demand and supply sides. While demand- and a 2 percent increase in capital infrastructure side adaptations are not explicitly costed in this costs are needed by 2030 to adapt to climate change study (demand projections already account for some (UNFCCC 2007). Also, the UNFCCC estimate increase in efficiencies over time, so this could lead includes no explicit link to climate impacts or any to double counting), there is wide scope for econ- accounting for autonomous (personal) adaptation. omizing on water consumption (see, for example, Zhou and Tol 2005). Adaptation options for flood The analysis of agricultural adaptation costs uses protection can reduce either the probability of flood the International Food Policy Research Institute’s events and their magnitude (reducing flood hazard) (IFPRI) International Model for Policy Analysis of or the impacts of floods. In both cases, adaptation Agricultural Commodities and Trade (IMPACT) to should consider structural and nonstructural mea- incorporate the direct impacts of climate change on sures that address both flood probability and impact. agricultural production (yields and crop area) and the indirect effects through food prices and trade on calorie availability and the number of malnour- Agriculture ished children (box 16). IMPACT includes 32 crops and livestock commodities, including cereals, soy- The analysis of agriculture brings together, for the beans, roots and tubers, meats, milk, eggs, oilseeds, first time, detailed biophysical modeling of crop oilcakes and meals, sugar, and fruits and vegetables. growth under climate change with the world’s Changes in the number of malnourished children most detailed global partial equilibrium agricul- between 2000 and 2050 without climate change are tural model to estimate the costs of adaptation for compared to changes with climate change to deter- returning the number of malnourished children mine costs of adaptation. 48 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Box 16 Agriculture sector methodology Climate change affects agriculture through changes in yields and in areas planted. Farmers respond by changing their manage- ment practices. The resulting production effects work their way through agricultural markets, affecting prices. Consumers respond by changing consumption patterns. When prices rise, consumption falls and the number of malnourished children rises. Adaptation expenditures on productivity-enhancing investments can offset these impacts of climate change. The biological effects of climate change are modeled with the Decision Support System for Agrotechnology Transfer (DSSAT) crop modeling program, assessing yield and area effects for five major commodities at 0.5 degree resolution. The DSSAT model includes a carbon dioxide fertilization effect of 369 parts per million (ppm) atmospheric concentration, reflecting recent research suggesting that fertilization effects are much weaker in the field than in the laboratory. Using a 532 ppm value reduces the costs of adaptation by less than 10 percent. The productivity effects of climate change are aggregated to 32 crops and 281 food production units of the International Food Policy Research Institute’s International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT). Growth in crop produc- tion in each country is determined by crop and input prices, exogenous rates of productivity growth and area expansion, investment in irrigation, and water availability. Demand is modeled as a function of prices, income, and population growth and has four compo- nents: food, feed, biofuels feedstock, and other uses. The model links national agricultural markets through international trade. World agricultural commodity prices are determined annually at levels that clear international markets. Costs of adaptation are measured against the human well-being measure of malnutrition in preschool children, a highly vulnerable group. The number of malnourished children is determined in part by per capita calorie availability but also by access to clean drink- ing water and maternal education. Investments in agricultural research, roads, and irrigation increase agricultural productivity under climate change, increasing calorie availability and reducing child malnutrition estimates. The costs of adaptation for agriculture are calculated solely from the perspective of the agriculture sector, so the starting point is investment and asset stocks in the base year (2000). Thus, the estimates of investments in research, irrigation, and rural roads do not take account of overlaps in spending on these activities or assets with the baseline growth or of adaptation costs for other sectors, such as infrastructure and water resources management. This is an unavoidable consequence of estimating the cost of adaptation for each sector separately and in parallel. For rural roads, an attempt was made to eliminate overlapping expenditures in compiling the consolidated estimates of the costs of adaptation for developing countries shown later in the report in table 24. The baseline provi- sion of rural roads up to 2050 used to estimate costs of adaptation is adjusted to take account of the additional length of rural roads consistent with the baseline projections for road investment. This adjustment reduces the investment in rural roads included in the cost of adaptation for agriculture by about 80–85 percent for the two climate scenarios. The adjustment for these overlaps amounts to $2.0–$2.2 billion a year averaged over the full period. Changes in temperature and precipitation in the out climate change, developed country net exports NCAR and CSIRO climate scenarios have strong rise from 83.3 million tons to 105.8 million tons negative effects on crop yields and production. Irri- between 2000 and 2050—a 27 percent increase. gated and rain-fed wheat and irrigated rice are South Asia switches from net exporter to net especially hard hit. South Asia experiences the big- importer, and East Asia and Pacific and Sub-Saha- gest loss in production, and developing countries ran African imports rise considerably (table 14 and fare worse than developed countries for almost all figure 3). Developed country exports rise 28 percent crops under both scenarios. under the NCAR scenario and a dramatic 75 per- cent under the CSIRO scenario compared with 2000 These productivity impacts, even after accounting levels (not shown). South Asia becomes a much for autonomous adjustments through changes in, larger importer of food under both scenarios than say, input and crop mix (see box 17 on some private under baseline conditions of no climate change, adaptation measures in agriculture in case study East Asia and Pacific becomes a net exporter of countries), lead to dramatic impacts on trade flows food under the NCAR scenario, and Europe and (another form of autonomous adjustment). With- Central Asian exports and Sub-Saharan African The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 49 Box 17 Private adaptation in agriculture and areas needing policy attention Farmers in Sub-Saharan Africa are already adapting to greater rainfall variability and higher temperatures by shifting sowing dates and changing crop mix or plot location. In Ethiopia and Ghana, farmers in focus groups reported on significant changes in the start of the rainy season and in the length and intensity of rainfall. In Ghana, male and female farmers reported that they had responded to the variable precipitation and higher temperatures by planting drought- and heat-resistant crops, selecting crops with a short ges- tation period, planting vegetables along river banks for easier access to water, shifting planting dates, and sowing half the plot later to spread the risk of early or late rains. Farmers in Bolivia also note adaptations in agricultural practices with climate change, includ- ing using new seed varieties and turning over pastureland to cropland in the Alturas (highlands), where temperatures have risen. In these settings, the coping strategies of the poorest farmers are even more constrained under conditions of climate change, leav- ing them less room for implementing adaptation responses. For example, a focus group of vulnerable women in rural Ghana noted that the Nandana (poorer people) lack collateral for loans and thus have to beg other community members for leftover seeds to sow. They are therefore the last to sow their crops and miss crucial sowing dates. In all the case study countries, land was identified as a policy area with an important bearing on potential climate adaptation activi- ties. Land tenure systems affect poverty outcomes directly. For example, priority adaptation investments are expected to include investments in water infrastructure (including irrigation) to cope with growing freshwater scarcity. However, the greatest impacts of such irrigation investments on poverty reduction have been found in countries with low levels of inequality in land holdings (Hussain 2005). Land inequity is greatest for women. In Tetauku, Ghana, members of an EACC focus group discussion on the elderly declared that “Women do not own land; even their own children who are boys have more inheritance rights than their mothers.” An elderly man added that “even if you are blind or physically challenged you would always have a piece of land as long as you are a boy or a man.” imports fall substantially under both scenarios. Cli- line of no climate change, with a decline in cereal mate change has a smaller impact on meat trade. consumption more than offset by increased meat and edible oil consumption as per capita In developing countries, per capita calorie con- income rises. Climate change reverses much of sumption increases over 2000–50 under the base- these gains: meat consumption growth slows and Table 14 Value of net cereal trade by region, with and without climate change and with and without adaptation investments, by region, 2000 and 2050 ($ millions at 2000 prices, no discounting) 2050 Commonwealth Scientific and National Centre for Atmospheric Industrial Research Organization Research (NCAR), wettest scenario (CSIRO), driest scenario Without climate Without With Without With Region 2000 change adaptation adaptation adaptation adaptation South Asia 2,589 –2,238 –14,727 –11,700 –14,927 –11,406 East Asia and Pacific –1,795 –7,980 6,530 7,304 –8,879 –4,220 Europe and Central Asia 750 24,276 6,662 6,381 14,377 12,789 Latin America and Caribbean –1,246 –6,027 480 –1,874 –342 –3,094 Middle East and North Africa –5,600 –12,654 –17,703 –12,985 –17,723 –13,233 Sub-Saharan Africa –2,995 –12,870 –11,153 –10,560 –10,914 –10,392 Developing countries –8,500 –18,184 –30,733 –24,163 –39,219 –30,273 Source: Economics of Adaptation to Climate Change study team. 50 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes FIGURE 3 about $8 billion annually are needed between 2010 Changes in productivity as a result of climate change and 2050 to restore development gains in nutrition have large impacts on trade ows Net cereal trade by region in 2000 and 2050, with and without levels, especially for children, to levels without cli- climate change and without carbon fertilization mate change (table 16). The types of adaptations (millions of metric tons) considered include more spending on research and Millions of Metric Tons extension, expansion of irrigated areas along with 200 2000 efficiency improvements, and expansion of rural road 2050 No Climate Change 150 2050 CSIRO NoCF networks for lower cost access to inputs and higher 2050 NCAR NoCF 100 farm-gate prices. Investment needs in Sub-Saharan 50 Africa dominate (mainly for rural roads), account- ing for about a third of the total. South Asia and East 0 Asia and Pacific also need large investments, mainly -50 in irrigation efficiency improvements. Differences -100 between gross and net costs of adaptation are small. -150 Adaptation costs of planned or public investments -200 SAR EAP ECA LAC MNA SSA Developed Developing do not, by definition, capture costs associated with Countries Countries autonomous adaptation, particularly important in Source: Economics of Adaptation to Climate Change study team. agriculture. One component of autonomous adap- tation costs in agriculture is changes in net trade values. Without climate change, cereal imports for cereal consumption declines more. These declines developing countries roughly double between 2000 reverse gains in calorie availability so that calorie and 2050 (see table 14). With climate change, cereal availability in 2050 is not only lower than in the imports roughly triple, and trade imbalances are no climate change scenario in 2050 but even less larger with the drier CSIRO scenario than with the than 2000 levels. NCAR scenario. Agricultural productivity invest- ments of the type needed for the child nutrition The decline in calorie availability brought about by adaptation also reduce net cereal imports for devel- climate change also increases the number of mal- oping countries, although not by much. nourished children (table 15). Without climate change, income and agricultural productivity gains result in large declines in the number of malnour- Fisheries ished children in all parts of the developing world except Sub-Saharan Africa, where the absolute This is the first study to establish the costs of adap- numbers increase from 33 million in 2000 to 42 tation to climate change in the fisheries sector. The million in 2050. Climate change eliminates most of analysis begins by detailing the likely impact of cli- these improvements. In South Asia, the numbers of mate change on the productivity of marine fish- malnourished children in 2050 rises from 52 mil- eries (more than 1,000 species) and, through that, lion without climate change to 59 million with cli- on landed catch values and household incomes. mate change. Adaptation costs are then estimated as the costs of restoring these revenue indicators to levels that The large impact in agriculture worldwide suggests would have prevailed in the absence of climate that public investments (planned adaptation) of change (box 18). Lack of readily available data pre- The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 51 Table 15 Adaptation costs in agriculture—number of malnourished children under age five for three scenarios, by region, 2000 and 2050 (millions) 2050 Commonwealth Scientific and Without climate National Centre for Atmospheric Industrial Research Organization Region 2000 change Research (NCAR), wettest scenario (CSIRO), driest scenario South Asia Number 75.6 52.3 59.1 58.6 Percent — 31 22 22 East Asia and Pacific Number 23.8 10.1 14.5 14.3 Percent — 58 39 40 Europe and Central Asia Number 4.1 2.7 3.7 3.7 Percent — 34 10 10 Latin America and Caribbean Number 7.5 5.0 6.4 6.4 Percent — 35 17 17 Middle East and North Africa Number 3.5 1.1 2.1 2.0 Percent — 69 40 43 Sub-Saharan Africa Number 32.7 41.7 52.2 52.1 Percent — +28 +60 +59 Total Number 110.63 136.72 135.78 Percent 25 7 8 Source: Economics of Adaptation to Climate Change study team. cludes the use of a more direct measure of welfare, levels) and climate change-induced losses of critical as with calorie intake for agriculture. Data limita- habitats, such as degradation of coral reefs through tions also restrict the analysis to marine capture coral bleaching. Three scenarios are examined that fisheries, leaving out inland fisheries and aquacul- reflect these impacts. All three scenarios assume ture. Marine capture fisheries constitute more than changes in primary productivity and shifts in spe- half of total global fisheries values and support cies distribution due to climate change. The less large numbers of economically vulnerable people intensive scenario in addition assumes a 10 percent in coastal communities. catch reduction due to habitat losses by 2050 com- pared with the baseline that maintains 2010 stock The impacts of climate change on marine fisheries levels out to 2050, the more intensive scenario occur through changes in primary productivity and assumes a 30 percent catch reduction due to habitat shifts in species distributions and through acidifi- losses, and the overexploitation scenario assumes a cation of the oceans (from higher carbon dioxide 40 percent reduction in 2010 stock levels by 2050. 52 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 16 Annual cost of adaptation for agriculture—countering the effects of climate change on children’s nutrition levels, by region and cost type, 2010–50 ($ billions at 2005 prices, no discounting) Cost type and investment East Asia and Europe and Latin America and Middle East and Sub-Saharan category Pacific Central Asia Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario Gross Agricultural 0.2 0.1 0.4 0.2 0.2 0.3 1.4 research Irrigation efficiency 0.8 0.1 0.1 0.1 1.1 0.2 2.4 Irrigation expansion 0.0 0.0 0.0 0.0 0.4 0.6 1.0 Roads 0.2 0.0 0.6 0.0 0.0 2.2 3.0 Total 1.1 0.2 1.2 0.3 1.7 3.3 7.9 Net Agricultural 0.2 0.1 0.4 0.2 0.2 0.3 1.3 research Irrigation efficiency 0.8 0.1 0.1 0.1 1.1 0.2 2.4 Irrigation expansion 0.0 0.0 0.0 0.0 0.4 0.6 1.0 Roads 0.1 0.0 0.6 0.0 0.0 2.2 2.9 Total 1.0 0.2 1.2 0.2 1.7 3.3 7.6 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario Gross Agricultural 0.2 0.1 0.4 0.2 0.2 0.3 1.4 research Irrigation efficiency 0.7 0.1 0.1 0.1 1.1 0.2 2.4 Irrigation expansion 0.0 0.0 0.0 0.0 0.4 0.6 1.0 Roads 0.2 0.0 0.8 0.0 0.0 2.1 3.1 Total 1.1 0.3 1.3 0.3 1.7 3.2 7.9 Net Agricultural 0.2 0.1 0.4 0.2 0.2 0.3 1.4 research Irrigation efficiency 0.7 0.1 0.1 0.1 1.1 0.2 2.4 Irrigation expansion 0.0 0.0 0.0 0.0 0.4 0.6 1.0 Roads 0.1 0.0 0.8 0.0 0.0 2.1 3.0 Total 1.1 0.2 1.3 0.3 1.7 3.2 7.7 Source: Economics of Adaptation to Climate Change study team. Climate change is predicted to lead to losses in areas beyond individual countries’ exclusive eco- landed catch values or gross fisheries revenues of nomic zones. $10–$31 billion globally by 2050 and $7–$19 bil- lion for developing countries (table 17). East Asia Governments have implemented various measures and Pacific is projected to experience the larg- to manage fisheries, both to conserve fish stocks est losses. Losses are also considerable in high seas and to help communities that depend on fishery The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 53 Box 18 Fisheries sector methodology Climate change is likely to alter ocean conditions, particularly water temperature, ocean currents, upwelling, and biogeochemistry, leading to productivity shocks for marine fisheries (IPCC 2007; Diaz and Rosenberg 2008). Other studies have documented shifts in species distribution (Perry and others 2005; Dulvy and others 2008) and growth rates (Thresher and others 2007) as a result of changes in ocean temperatures. Climate change may also alter the phenology of marine organisms, creating mismatches between prey availability and predator requirements and leading to coral bleaching and habitat loss for reef-associated fish species (Sumaila and Chaeung 2008). To account for distributional, productivity, and biogeochemical effects, a two-step process is used to establish climate change im- pacts on fish catches. First, potential losses and gains in fish catches due to the redistribution of fish biomass and changes in primary production are determined under various climate change scenarios for all maritime countries and the high seas. These impacts are then modified by including the potential catch impacts in climate change vulnerable hot spots, based on knowledge of the locations of different fish species. Potential effects of climate change on these areas include acidification of the oceans from higher carbon dioxide levels, loss of coral reef from ocean warming and acidification, and other changes in ocean biogeochemistry, such as oxygen levels. And second, potential losses and gains in landed catch values or gross revenues and household incomes from global fisheries under different climate change and baseline scenarios are estimated. Because of data limitations, losses in landed catch values are used as estimates of adaptation costs. resources adapt to changes caused by overfish- the dependence on fishery resources. But only lim- ing and other factors. Measures include buybacks, ited information is available on the potential costs transferable quotas, and investments in alternative of adaptation. The best documented are measures sources of employment and income. Adaptation to responding to the catastrophic decline in cod stock climate change is likely to involve an extension of off Newfoundland, Canada, where the cost was such policies with a focus on providing alternative equivalent to $4,950 per ton of reduced catches at sources of income in fishing communities to lessen 2005 prices. Table 17 Loss in landed values of fish catches under three scenarios, 2050 ($ billions at 2005 prices, no discounting) Country group and region Less intensive More intensive Overexploitation Global 16.75 31.31 9.64 Developed countries 4.13 8.07 2.27 Developing countries 11.19 18.77 7.02 High seas 1.43 4.47 0.35 Region South Asia 1.37 2.22 0.87 East Asia and Pacific 7.02 10.94 4.63 Europe and Central Asia 0.32 1.31 –0.01 Latin America and Caribbean 1.21 2.17 0.73 Middle East and North Africa 0.61 0.84 0.43 Sub-Saharan Africa 0.44 0.96 0.21 Other developing countries 0.22 0.34 0.16 Source: Economics of Adaptation to Climate Change study team. Note: The less intensive scenario assumes a 10 percent reduction by 2050 in annual catches compared with the baseline, the more intensive assumes a 30 percent reduction, and overexploitation assumes a 40 percent reduction. 54 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Because of the paucity of data, adaptation costs tional public health adaptation activities, with a were estimated as the damages caused by cli- focus on malaria and diarrhea (box 19). mate change or reductions in landed catch values induced by climate change. No attempt was made Adaptation costs are computed for these two dis- to allocate the loss associated with fisheries in the eases in each country for each of 16 demographic high seas. Most of this loss will fall on the fish- groups. As before, costs depend on the baseline ery sectors of developed countries, so this omis- incidence of disease without climate change and sion does not have much impact on the overall the additional risk that climate change poses. Costs cost of adaptation in developing countries. Adap- also depend on the unit cost of preventing and tation costs are highest under the more intensive treating additional cases of the disease. Earlier esti- scenario and not under the overexploitation sce- mates of the global cost of adaptation followed a nario, because there are fewer fish under the over- similar approach but held the baseline incidence exploitation scenario to be affected by climate of disease (the number of people affected) fixed at change (table 18). Regionally, nearly two-thirds current levels (Ebi 2007). This study incorporates of the costs of adaptation is incurred in East Asia a future baseline global burden of disease based and Pacific. on World Health Organization (WHO) projec- tions through 2030 plus extensions through 2050, which implies a reduction in incidence and inci- Human health dence rates. It also incorporates updates and revi- sions to the unit cost of prevention and treatment The main human health impacts of climate change for malaria and diarrhea and updates to the dose- are increased incidence of vector-borne disease response functions used to compute the relative (malaria), water-borne disease (diarrhea), heat- risk for malaria. and cold-related deaths, injuries and deaths from flooding, and greater prevalence of malnutrition. Unlike prior estimates (Ebi 2007), this study pro- While adaptation measures comprise all actions to vides partial estimates of the health sector costs of reduce or prevent these additional cases of disease other sectors. To avoid double counting, these esti- or death, including actions outside the health sec- mates are reported in the following sections: the tor such as disaster mitigation programs, food and additional cost of climate proofing health sector water security measures, and provision of infra- infrastructure in the infrastructure section; the cost structure, the analysis here looks only at conven- of reducing additional cases of malnutrition in the Table 18 Annual cost of adaptation for fisheries—loss in landed catch values under three scenarios, by region, 2010–50 ($ billions at 2005 prices, no discounting) East Asia and Europe and Latin America Middle East and Sub-Saharan Scenario Pacific Central Asia and Caribbean North Africa South Asia Africa Total Less intensive 1.05 0.03 0.20 0.08 0.08 0.08 1.52 More intensive 1.70 0.15 0.35 0.13 0.20 0.15 2.68 Overexploitation 1.18 0 0.18 0.10 0.08 0.10 1.64 Source: Economics of Adaptation to Climate Change study team. Note: The less intensive scenario assumes a 10 percent reduction by 2050 in annual catches compared with the baseline, the more intensive assumes a 30 percent reduction, and overexploitation assumes a 40 percent reduction. Excludes losses associated with high seas fisheries. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 55 Box 19 Health sector methodology Adaptation costs are computed on a disease-specific basis for malaria and diarrhea for 16 demographic (age and sex) groups in each country at five-year intervals. The adaptation cost for each disease and demographic group in a county is determined by the baseline incidence of disease that would have prevailed in the absence of climate change, the additional risk that climate change poses rela- tive to the baseline, and the unit cost of preventing and treating additional cases of malaria and diarrhea. The baseline incidence of diarrhea and malaria by country for 16 demographic groups for 2004 are available from the World Health Organization (WHO 2004). WHO has also developed econometric models using panel data on income and health to project cause- specific deaths and disability-adjusted life year (DALY) rates by demographic group through 2030. The EACC study extended this baseline to 2050 using the WHO econometric model results (WHO 2004). The additional risk of incidence for malaria and diarrhea was estimated from the epidemiological literature. The relative risk for malaria was estimated as the percentage change in popu- lation at risk based on Craig, Snow, and le Sueur (1999) and Tanser, Sharp, and le Sueur (2003). For diarrhea, the epidemiological literature is limited, and the estimates are based on the dose-response functions from the WHO global burden of disease study (WHO 2004). The relative risks were computed separately for 2010, 2030, and 2050 for the NCAR and CSIRO climate projections. Risks for interme- diate years were interpolated. The relative risk was applied to the projected baseline incidence to determine the additional number of cases attributable to climate change and, for malaria, to determine the number of DALYs attributable to climate change. The total cost of preventing or treating the additional cases is calculated by multiplying the additional cases by the average cost of preventing or treating additional cases. The average cost of averting additional cases of each disease is based on updated treatment costs from the Disease Control Priorities in Developing Countries Project (DCCP2) for the cost-effective methods of treatment. For diarrheal diseases, costs are based on breastfeeding promotion; vaccination against rotavirus, cholera, and measles; and improve- ments in water supply and sanitation. For malaria, costs are based on use of insecticide-treated bednets; case management with ar- temisinin-based combination therapy plus insecticide-treated nets; case management with artemisinin-based combination therapy with insecticide-treated nets plus indoor residual spraying; and case management with artemisinin-based combination therapy plus insecticide-treated nets plus indoor residual spraying plus intermittent presumptive treatment in pregnancy. agriculture section; and the total adaptation cost These estimates are lower than prior estimates of related to extreme weather (floods and droughts), $4–$12 billion in 2030 (Ebi 2007).8 Costs show a some of which occur in the health sector, in the consistent decline over time in absolute terms to section on extreme weather events. The health sec- less than half the 2010 estimates of adaptation costs tor adaptation cost reported here would be higher by 2050. While the declines are consistent across if any of the agriculture sector adaption measures regions, the rate of decline is faster in South Asia fail, raising levels of malnutrition. Despite the and East Asia and Pacific than in Sub-Saharan increased scope of this study compared with prior Africa. As a result, by 2050 more than 80 percent of estimates, the burden of disease and health sec- the health sector adaptation costs are borne by Sub- tor adaptation costs reported here are still under- Saharan Africa. estimates because they do not include many other infectious diseases, such as dengue, heat stress, Adaptation costs decline over time despite rising population displacement, and increased pollution risks from climate change for malaria and diarrhea and aeroallergen levels. These costs, however, can- under both climate scenarios in all regions. Com- not be reliably estimated given current scientific pared with current conditions, increases in tem- understanding. perature by 2050 are expected to increase the risk Average annual adaptation costs in the health sec- tor for diarrhea and malaria prevention and treat- 8 Ebi’s (2007) estimates also include the cost of malnutrition, which ac- counts for 2–5 percent of total adaptation cost. The majority of the costs ment lie in a narrow range of $1.3–$1.6 billion a in the Ebi study therefore also reflect costs due to malaria and diarrhea, year over the 40-year period 2010–50 (table 19). as in the EACC study. 56 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 19 Average annual adaptation cost for human health—preventing and treating malaria and diarrhea, by region and decade, 2010–50 ($ billions a year at 2005 prices, no discounting) East Asia and Europe and Latin America Middle East and Sub-Saharan Period Pacific Central Asia and Caribbean North Africa South Asia Africa All regions National Centre for Atmospheric Research (NCAR), wettest scenario 2010–19 0.7 0.1 0.0 0.1 1.0 0.9 2.8 2020–29 0.2 0.0 0.0 0.1 0.7 0.7 1.7 2030–39 0.1 0.0 0.0 0.1 0.3 0.7 1.2 2040–49 0.1 0.0 0.0 0.0 0.1 0.8 1.0 2010–49 0.2 0.0 0.0 0.1 0.5 0.8 1.6 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario 2010–19 0.5 0.0 0.0 0.1 0.8 0.6 2.0 2020–29 0.1 0.0 0.0 0.1 0.7 0.6 1.5 2030–39 0.1 0.0 0.0 0.0 0.3 0.6 1.0 2040–49 0.0 0.0 0.0 0.0 0.1 0.6 0.7 2010–49 0.2 0.0 0.0 0.0 0.5 0.6 1.3 Source: Economics of Adaptation to Climate Change study team. of diarrheal disease in vulnerable population by an costs. Sensitivity analysis holding the development average of 10 percent, while changes in temperature baseline incidence rate of the diseases constant at and precipitation are expected to increase the risk current levels shows that adaptation costs would of malaria by an average of 25 percent. The higher have increased in absolute terms by more than 500 risks result in increases in the share of deaths and percent without development, more in line with the number of cases of both diseases attributable to earlier estimates by Ebi (2007). climate change. In Sub-Saharan Africa, the share of malaria cases increases from the current 7–12 per- Several subsidiary analyses reconfirm the impor- cent to 12–19 percent by 2050, depending on the tance of accounting for development. First, base- climate scenario and dose-response functions. Sim- line improvements used to determine adaptation ilarly, the share of diarrhea cases increases from costs were validated through estimates of health the current 2–4 percent to 7–8 percent by 2050, outcome indicators (infant mortality rate, under- depending on the climate scenario. five mortality rate, low birth weight, and proportion of the population surviving to age 65) developed These increases in shares are more than offset by from country-level panel data, along with per cap- rapid declines in the baseline incidence of these ita income, urbanization, population, demographic diseases and deaths due to development. The structure, and climate variables over 1960–2005. declines in the baseline rates dominate all other These analyses indicate that improvements in these aspects of the projection—climate scenarios, dose- indicators are the types of improvements in base- response relationships, and population growth— line health that can be expected as part of nor- and are the primary explanatory variable for both mal development, and thus they indirectly reduce the temporal and spatial pattern of adaptation the vulnerability of communities and their cost of The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 57 adaptation. For instance, under the development can reduce losses of timber and other benefits that baseline (holding climate at historical levels) under- would occur if forests were allowed to adjust to cli- five mortality is projected to decline from 70 per mate change on their own. With the expansion of 1,000 live births to 19 per 1,000 in 2050. Climate plantation forests in developing countries, which variables have a small yet significant role in this are also becoming a source of industrial timber, trend, accounting for 100,000–200,000 additional adaptation for the industrial timber sector is likely deaths (1–2 percent) in 2010 and about 9,000– to be undertaken by the private sector as part of 15,000 additional deaths (0.4–0.6 percent) in 2050. business operations. Second, comparing adaptation costs with the pro- At the same time, most studies of the effects of cli- jected cost of current programs such as the Roll mate change on forests show an increase in bio- Back Malaria program also shows the importance logical productivity, with forest areas roughly of the development baseline. This program aims unchanged, over the period to 2050. This holds to scale up efforts in all malaria-endemic coun- for all large developing country regions. Addition- tries starting in 2009 and 2010 to eradicate malaria ally, studies show a modest increase in timber har- globally over the next few decades. The global vests and an overall decline in wood prices. Global cost of this program is around $5.2 billion annu- forest timber harvests increase by about 6 percent, ally through 2020 but declines to $3.3 billion annu- with the largest increases in China, South America, ally in the 2020s and to $1.5 billion by the 2030s. India, Asia-Pacific, and Africa (table 20). Though Assuming that about 5 percent of the current bur- forest stocks cannot be expected to increase indef- den of malaria is due to climate change, this implies initely and are likely to stabilize beyond 2050 with a share of around $250 million in adaptation cost. significant dieback, these findings suggest that If the share of the malaria burden attributable to planned adaptation may not be necessary for the climate change doubles to 10 percent by 2040, the industrial timber sector, at least up to 2050. adaptation cost for malaria would be $150 million, in the same ballpark as the estimates in this study. The Millennium Ecosystem Assessment established a classification of ecosystem services that is now widely used: provisioning services, regulating ser- Forestry and ecosystem services vices, cultural services and recreation, supporting services, and biodiversity. Most provisioning ser- Forests provide a multitude of goods and services, vices are addressed directly by the sector studies; and adaptation to climate change requires measures most of the remaining ecosystem services underpin that restore this range of benefits. At the same time, natural production systems, which are used as indi- lack of adequate data on the magnitude of forest rect inputs to the production of goods and service services and on the likely impact of climate change of value to human society—for example, pollina- on forest stocks, especially at subregional levels, tion clearing services to agriculture, water regulat- significantly constrains analysis for this sector. ing service of forests, and the habitat service of coral reefs for fisheries. Most of these inputs are included Climate change is expected to shift the geographic implicitly or explicitly in the sector studies and so distribution of plants and tree species. It is also are not assessed here to prevent double counting. expected to alter tree productivity, with the carbon fertilization effect being an important enhancer of Several important ecosystem services are not productivity. Harvesting and replanting measures addressed in the sector studies, however, including: 58 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 20 Percentage change in regional timber production based on climate scenarios used for ecological projections, by region, 1995–2050 University of Illinois at Urbana-Champaign Region Hamburg scenario (UIUC) scenario Oceania –3 13 North America –1 –2 Europe 6 11 Former Soviet Union 7 3 China 12 11 South America 19 10 India 22 14 Asia-Pacific 10 4 Africa 14 5 Total 6 5 Source: Adapted from Sohngen and Mendelsohn (2001). Note: The UIUC model is considered a high-temperature scenario and the Hamburg scenario a low-temperature scenario. The original results for 1995–2045 were straight line extended to 2050. • Provisioning services for nonmarket goods, Use of wood fuels is projected to increase except especially those provided by forests and wood- in Asia, with the largest increase in Africa (table lands, including wood fuels and nonwood for- 21). Based on the same projections used for indus- est products; trial timber, the impact of climate change on forest • Regulating services, such as protection from net primary productivity is positive in all develop- natural hazards, notably the flood and storm ing regions by 2050, from a low of 4–5 percent in protection services of wetlands; Africa to as much as 19 percent in South Amer- • Cultural services, recreation, and tourism; ica (and as high as 22 percent in India alone; see • Biodiversity (to the extent that the productiv- table 20). Consequently, there are no serious adap- ity of agriculture, fisheries, and forests is influ- tation costs for wood fuels and nonwood forest enced by biodiversity, the service is implicitly products at the regional level. However, while for- included). est net primary productivity does not decline at a regional level, there is great variation across and This study focused on two of the missing ecosystem within countries, with drier areas likely to suffer services: the provisioning services of wood fuels and losses. But there may be serious indirect impacts of nonwood forest products from natural forests, which climate change that have not been accounted for, are critical for the livelihoods of more than 2 billion such as increased disturbance (fire, disease, pests) people in developing countries, and the regulating and migration of populations clearing forests for services of mangrove wetlands, which protect coastal agricultural land. Communities living within these areas from destructive waves and storm surges. The forests are at great risk because of their high depen- adaptation costs for cultural and recreational ser- dence on forests for livelihoods. vices and biodiversity are not examined. Much work remains to be done on how to quantify the impact of Most adaptation studies have focused on hard infra- climate change in biodiversity (box 20). structure rather than natural systems for protection The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 59 Box 20 Gaps in coverage of ecosystem services Serious gaps in the coverage of ecosystem services remain. Additional work is especially needed on flood protection services of wetlands other than mangroves and on the potential for using mangroves as an adaptation measure. It is still not clear how to quantify the impact of climate change on biodiversity and what adaptation measures are effective for preserving it. The loss of biodiversity is likely to have substantial and unpredictable consequences. Over the past 200 years, biodiver- sity has come under threat mainly from habitat loss, land-use change, and other human activities. Climate change will intensify the threat and increase the losses, but most of the information needed to estimate adaptation costs for biodiversity is unavailable. The United Nations Framework Convention on Climate Change (UNFCCC 2007) report on adaptation costs omitted from its total figure the estimate it had commissioned for biodiversity because the estimate did not distinguish the “development deficit” from the adaptation deficit and there was no information about the effectiveness of the conservation measures proposed. The meth- odology and data used to derive this figure were developed in a much earlier report (Hansen and others 2001) to address what this study would term the development deficit—current gaps in conservation measures, not additional gaps that might arise from climate change. In a critique of the UNFCCC assessment, Parry and others (2009) propose reinstating this figure, which ranges from $12–$22 billion to as much as $290–$342 billion annually. Parry and others (2009, p. 11) argue that when the development deficit is great enough (as it is for biodiversity conservation), the adaptation deficit should be defined to include the development deficit. The urgency of filling this development deficit cannot be underestimated, but the figures proposed are not consistent with the definition of adaptation costs used for this study. from natural hazards, although ecosystems have Centre were used to measure mangrove coastlines great potential to contribute while also providing and the human resources they protect. Glob- additional services. The key issue for coastal protec- ally, 69 percent of mangroves have the potential to tion services provided by mangrove forests is their migrate and an additional 9 percent are at risk but ability to migrate landward in response to rising sea may survive. About 22 percent of mangroves, affect- level, based on topographical features of the coast- ing 29 million people, are likely to be lost to ris- line. The DIVA database and a global mangrove ing sea level. It is reasonably cost effective to plant database from the World Conservation Monitoring and rehabilitate mangroves, and in some places Table 21 Use of wood fuel in 2006 and projections to 2030, by region 2006 2030 Per capita wood Per capita wood Wood fuel fuel (cubic Wood fuel fuel (cubic (millions of cubic Population meters per (millions of cubic Population meters per Region meters) (millions) person) meters) (millions) person) South Asia 383 1,516 0.25 373 2,027 0.18 Southeast Asia 186 564 0.33 113 708 0.16 East Asia 213 1,531 0.14 152 1,654 0.09 Africa 589 940 0.63 1,185 1,513 0.78 South America 241 453 0.53 400 577 0.69 Rest of the World 258 1,556 0.17 328 1,788 0.18 Total 1,870 6,560 0.28 2,551 8,267 0.31 Source: FAO (2009) on use of fuel wood and charcoal in 2006; Broadhead and others (2001), as cited in Arnold and others (2003), for regional projections for charcoal and fuel wood for 2030; and World Bank (2009) for population in 2030. Note: Wood fuel includes fuel wood and charcoal. 60 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes they are being used with built infrastructure to pro- sures. The amount for Bangladesh is implausibly tect coasts. The success of mangrove migration as more than twice China’s and four times Indone- an adaptation measure depends on the availability sia’s and includes both emergency food assistance of land for colonization, and competition is fierce in and disaster management. Much of the Indone- coastal areas. Mangroves are already under severe sian amount undoubtedly relates to geologic disas- pressure from conversion for aquaculture and tour- ters (earthquakes, volcanic eruptions, tsunamis) as ism, overcutting, pollution, and other factors. well as weather-related disasters. Most reports do not provide time-series information, nor do they include local expenditures. Extreme weather events Even if adequate information were available to esti- The best available information indicates that mate cost functions for some countries, these func- more than 170,000 people have been killed by tions could not be imputed to other countries floods since 1960, 2.4 million have been killed by without adjusting for social, economic, and insti- droughts, and billions have been seriously harmed tutional characteristics that affect resilience to cli- by extreme weather events.9 It is widely agreed that mate change. Consider the deaths attributed to climate change will increase the frequency and Hurricane Gustav, which struck the northern Carib- intensity of extreme weather events. Any estimate bean in August 2008. The four island countries of adaptation costs requires considering how cli- most affected have very different levels of economic, mate change will alter the incidence and location of social, and institutional development, as indicated these events, how socioeconomic development will by their scores on the United Nations Development change the vulnerability of affected communities, Programme’s Human Development Index for 2008 and how much it will cost to neutralize the threat of (UNDP 2008): Haiti ranked lowest, at 148; Cuba additional losses. ranked highest, at 48; and Jamaica, at 87, and the Dominican Republic, at 91, were in between. Hur- From a narrow technical perspective, it might ricane Gustav first struck Hispaniola with category be desirable to address the question of adapta- 1 force (74–95 miles per hour), killing 77 people in tion costs with a detailed engineering cost analy- Haiti and 8 in the Dominican Republic. Weakening sis of specific disaster prevention measures and to slightly (to about 70 mph), the storm struck Jamaica develop country-specific cost functions for estimat- and killed 15 people. Then it strengthened rapidly ing the additional emergency management expen- to category 3|4 and made landfall twice in Cuba, ditures needed to neutralize the effects of climate reaching maximum wind speed (150 mph). Cuba change. However, there is no way to construct a reported no deaths from Gustav, despite a vastly reasonable cost analysis that could be used for pro- more powerful hurricane impact than in Hispaniola. jections from the information available, which is too spotty in time and country coverage, nonspe- The implications are clear: country-specific factors cific, and nonstandardized. Available data, such as are powerful determinants of losses from extreme from the Asian Disaster Reduction Center, gener- ally provide summary information rather than spe- cific information for emergency preparedness by 9 To the best of the EACC study team’s knowledge, the most comprehen- sive database on weather-related losses is that maintained by the Centre type of disaster, such as floods and droughts (table for Research on the Epidemiology of Disasters (CRED) at the School of 22). For Japan, for example, much of the $34 bil- Public Health of the Université Catholique de Louvain, Brussels. While deaths from floods have increased steadily since the 1960s, to a total of lion expenditure is for earthquake-related mea- 58,500 for 1990–99, deaths from droughts have fallen sharply. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 61 Table 22 Disaster preparedness and management data from the Asian Disaster Reduction Center Annual government expenditures on disaster prevention and Country National agency responsible Year mitigation ($ millions) Armenia Emergency Management Administration 2006 7 Bangladesh Food and Disaster Management Budget Annual 500 China Various agencies 2005 217.7 Indonesia Contingency budget for disaster response Annual 125.8 India Calamity Relief Fund 2000–05 5.1 Japan Budget for disaster risk reduction Annual 34,000 Kazakhstan Budget for debris flows 1999 200 Korea, Rep. National Emergency Management Agency Annual 300 Thailand Department of Disaster Prevention and Mitigation 2003 25.6 Department of Disaster Prevention and Mitigation 2004 32.4 Department of Disaster Prevention and Mitigation 2006 63.9 Department of Disaster Prevention and Mitigation 2005 46 Mongolia Total Budget 2006 12.5 Malaysia Disaster Relief Fund Annual 15.5 Nepal Emergency Fund 2006 0.02 Pakistan Ten-Year Perspective Development Plan 2001–11 18.8 Philippines National Calamity Fund 2005 12.8 Russian Federation Fund for prevention and elimination of emergency 2003 687.4 situations Tajikistan Activities for disaster management Annual 5.5 Source: Asian Disaster Reduction Center, country reports (www.adrc.asia). weather events. Since the data on emergency man- tional improvement that accompanies economic agement costs are sparse, the focus is on the role development is also important, through enhanced of socioeconomic development in increasing resil- public sector capability to organize disaster preven- ience to climate change. The analysis builds on tion and relief. empirical work and case studies that have docu- mented the role of socioeconomic development in Other work focuses on political and human devel- reducing vulnerability to climate shocks (see box opment. Albala-Bertrand (1993) identifies political 21 for preliminary findings from two country case marginalization as a source of vulnerability to natural studies on social protection approaches and box 22 disasters. Toya and Skidmore (2005) find a significant on costing social protection interventions under role for education in reducing vulnerability, through climate change). Several studies have focused on better choices in areas ranging from safe construc- the effect of rising income per capita: as commu- tion practices to assessment of potential risks. nities get richer, they have greater willingness and Recently, Oxfam International (2007, p. 1), drawing ability to pay for preventive measures (Horwich on extensive evidence from South Asia, highlights 2000; Tol and Leek 1999 Burton and others 1993; the particular vulnerability of women, who often suf- Kahn 2005). Kahn (2005) finds that the institu- fer greater losses than men in natural disasters: 62 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Box 21 The importance of social protection measures Preliminary findings from the country case studies suggest that social safety nets and other social protection approaches are widely assigned high priority among measures to support pro-poor adaptation to climate change. Participants in scenario development workshops in Bangladesh named extension of citizenship rights to urban slum dwellers (as well as improved coverage of basic ser- vices) as key elements of their future vision. Preferred social protection interventions include both protective measures (safety nets, cash transfers) and productive measures (livelihoods, asset protection, attention to natural resources and agriculture). Safety net programs, when designed to address climate hazards, should include investments in risk preparedness and response systems, with attention to gender issues in disaster mitiga- tion. And they should include investments in the construction of community-level physical assets, such as water storage and land management systems. Harmonization and coordination among actors involved in disaster risk management, social protection, and longer term development are considered important. Both the Productive Safety Net Program (Ethiopia) and National Rural Employ- ment Guarantee Act (NREGA) in India (see box 22), for example, have elements that can be adapted to address climate risks. NREGA, in particular, has been shown to reduce distress migration by half in drought-affected sample villages. Nature does not dictate that poor people, or This approach offers considerable co-benefits women, should be the first to die. Cyclones because female education has a much broader do not hand-pick their victims. Yet, history sphere of potential influence than as a direct invest- consistently shows that vulnerable groups ment in emergency preparedness. As the develop- end up suffering from such events dispropor- ment literature has shown for many years, educating tionately …. In the 1991 Bangladesh cyclone, young women is a major determinant of sustainable for example, four times more women died development. A disaster prevention approach that than men …. Disasters are therefore an issue focuses on investment in female education there- of unsustainable and unequal development fore has a broader expected social rate of return that at all levels …. justifies the exercise, even if the expected benefits from reduced disaster vulnerability are overstated A logical inference from these studies is that (though more likely the opposite is true). empowering women through improved education is critical for reducing household vulnerability to Variations in projected climate, socioeconomic, and weather-related disasters. This would also be con- demographic variables produce wide disparities in sistent with the extensive literature on the power- outcomes for required female schooling and associ- ful effect of female education on community-level ated costs by 2050 (table 23), even among countries social capital and general welfare measures such as in the same region. At the country and regional lev- life expectancy (World Bank 2001). els, neither climate scenario dominates in all cases. The wet scenario (NCAR) generates higher risk-neu- Accordingly, the estimate of adaptation costs high- tralizing expenditure on female schooling in some lights the importance of female education and countries and regions; the dry scenario (CSIRO) is empowerment in reducing risks of weather-related more costly in others. South Asia requires the high- loss (see box 23 for methodology). The cost anal- est expenditure in both scenarios, followed on aver- ysis considers two key issues: How many addi- age by Sub-Saharan Africa and East Asia and Pacific tional young women would have to be educated to and then more distantly by the other regions. neutralize the increased vulnerability to extreme weather events resulting from climate changes? At both regional and global levels, the scale is large And how much would it cost? for the requisite increases in female education The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 63 expenditure. By mid-century, neutralizing the cost of $12–$15 billion annually. For the period as impact of extreme weather events requires educat- a whole, additional expenditures total about $300 ing an additional 18–23 million young women at a billion. Time-discounting, even at modest rates, Box 22 Costing social protection interventions under climate change The livelihoods of many of the rural poor in developing countries are highly dependent on climate. Yet the people who are most vul- nerable to climate change are often least able to adapt because of low asset holdings and poor access to information. Social protec- tion instruments, such as cash- and food-for-work programs and microinsurance, can provide vital external support for adaptation to climate change. Among previous studies of the costs of adaptation, only Human Development Report 2007/2008 included any estimates of likely social protection costs, finding that an additional $40 billion a year would be required by 2015 to strengthen social protection programs and scale up aid in other key areas (UNDP 2007). While costing the impact on social protection programs for all developing countries was not feasible under this study, an illustrative costing exercise was conducted to examine the likely impact of climate change on the financial viability of social protection programs in Bangladesh, Ethiopia, India, and Malawi. The EACC climate, GDP, and popu- lation projections were used to calculate potential participation rates and costs in 2015 and 2030 for scaling up programs to the national level. Sensitivity analysis was conducted to understand the relationship between assumptions (such as poverty rates, rural- urban population shares) and cost and participation outcomes. Findings were mixed. In some cases, climate change was projected to lead to an increase in the numbers of program participants and overall program costs, while in other cases projected economic growth reduced the need for social protection and lowered operating costs. Results for cash and food transfer programs such as Bangladesh’s Primary Education Stipend Program, Ethiopia’s Productive Safety Nets Program, and India’s National Rural Employment Guarantee Act suggest that development could reduce or stabilize social protection costs by 2030 as the number of poor people requiring assistance drops (see table). These findings are strongly dependent on income distribution assumptions and on how distribution may be expected to change with GDP growth. Stubborn pockets of poverty may remain even as GDP rises and, in combination with increased frequency and severity of climate hazards, could boost demand for social protection. Projected impact of climate change on illustrative social protection programs Impacts with EACC growth projections and Impacts with EACC growth projections and Country and program significant reductions in rural poverty significant increases in rural poverty Ethiopia, Productive Safety Nets While substantial resources are needed to pro- Numbers of beneficiaries and total costs of Program vide social protection in 2015, total beneficia- the program nearly double between 2015 and ries and costs are only slightly higher in 2030 2030 because of lower agricultural productiv- ity and greater incidence of droughts and floods (Diao and others 2005) India, National Rural Employment For the most part, income growth outpaces Numbers of rural poor and costs of the pro- Guarantee Act population growth, resulting in smaller num- gram increase between 2007 and 2015 but bers of rural poor and lower program costs in decline subsequently 2015 and 2030 than in 2007 Source: Economics of Adaptation to Climate Change study team. Analysis of selected microinsurance programs (the BASIX index-based microinsurance program in Andhra Pradesh, India, and Malawi’s rainfall-based index insurance product for maize farmers) suggests that the programs could become insolvent if projected increases in the frequency and severity of extreme weather events materialize. This would occur because of strong covariate risk and increased likelihood of extremes of droughts and flooding (Hochrainer and Linnerooth-Bayer 2009). Any long-run change in the frequency or severity of such hazards means that the risks can no longer be priced on the basis of the historical record, thus likely precluding an insurance-based solution. Social protection programs play a vital role in helping the poorest and most vulnerable to climate change deal with its consequences. Yet the projected increase in intensity of floods and droughts is likely to hurt the finan- cial viability of many such programs, at least in the near term. Further research to understand the full implications of climate change on social protection should be a priority. 64 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Box 23 Extreme weather events methodology To address the question of how much it would cost to reduce household vulnerability to weather-related disasters by empowering women through improved education, a model of weather-related impact risk is estimated using panel data for 1960–2002. Use of panel data allows for clearer interpretation of results, because it absorbs many sources of potentially misleading cross-sectional cor- relation into estimated country effects. The need for lengthy time series limits the estimation variables to a sparse set, however. The study employs fixed effects estimation of risk equations that link losses from floods and droughts to three determinants: weather events that increase potential losses, income per capita, and female education. Separate equations are estimated for the risk of death from floods, the risk of being affected by floods, and the risk of being affected by drought (the data are too sparse to support estima- tion for death from droughts). As in the other sector analyses, the analysis combines estimated risk equations with projections of economic growth, population growth, and changes in primary and secondary schooling. The same three scenarios are developed: a baseline with socioeconomic development but without climate change, and two scenarios with the same baseline development path but with alternative weather paths—a wet (NCAR) and a dry (CSIRO) scenario. For each scenario, the associated changes in the risks of death from floods and being affected by floods or droughts are calculated. Then, using the worst-case risk, the increase in female schooling that would neutralize this additional risk is calculated. The results are multiplied by expenditures per student to estimate the total education investment required to neutralize the additional weather risk posed by climate change. The approach here is conservative in that it is unlikely to underestimate the required investment and even imparts a strong upward bias. First, the cost assessment is based on general preparedness through increased education, rather than more narrowly targeted investment in emergency preparedness. Second, cost calculations are based on worst-case risk scenarios, which require the greatest increase in schooling to neutralize. (Extreme wet and dry scenarios are both worst-case scenarios for extreme weather, because they generate the greatest number of floods and droughts.) Third, only projected increases in vulnerability are included, not decreases. (An alternative would be a net impact analysis for a wet climate scenario that subtracts lower expected losses from drought from higher expected losses from flooding.) Finally, the results for the two model scenarios are not averaged, which would neutralize their extreme signals. substantially reduces the value of these expendi- The costs are high, at approximately equal to cur- tures, but the basic result stands: in developing rent official development assistance (OECD 2008). countries, neutralizing the impact of worsening The highest costs are in East Asia and Pacific, fol- weather over the coming decades will require edu- lowed closely by Latin America and the Caribbean cating large numbers of young women at a cost that and then Sub-Saharan Africa. The dry scenario, will steadily escalate to several billion dollars annu- CSIRO, requires lower adaptation costs overall ally. However, there will also be other gains on the and in all regions but South Asia. The lower total margin from investing in education for millions of costs under CSIRO reflect lower costs for infra- young women, adding to the benefits. structure, health, and extreme weather events than under NCAR, more than compensating for higher costs for water supply and flood protection and Consolidated results agriculture. Total adaptation costs calculated by the gross sum method average $10 billion a year Overall, the study estimates the costs of adaptation more than by the other two methods (the insig- to climate change in developing countries at $75– nificant difference between the X-sum and net $100 billion a year over 2010–50, depending on sum figures is largely coincidence). Countries that the aggregation rule used (see section 3), and the appear to benefit from climate change in the water climate scenario—NCAR (wetter) or CSIRO (drier; supply and flood protection sector, especially in table 24). The costs of adaptation are roughly $80– East Asia and Pacific and South Asia, drive this $90 billion for the X-sum aggregation method. difference. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 65 Table 23 Average annual cost of adaptation for extreme weather events—climate change—neutralizing costs of female education and additional numbers of female students, by region, 2010–50 Category East Asia and Europe and Latin America and Middle East and Sub-Saharan and year Pacific Central Asia Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario Total ($ billions at 2005 prices, no discounting) 2010 0.45 0.17 0.58 0.04 0.30 0.24 1.78 2020 1.15 0.54 1.43 0.11 0.89 0.76 4.88 2030 1.48 0.82 1.34 0.26 2.00 1.18 7.08 2040 1.95 0.98 1.55 0.50 3.96 1.83 10.77 2050 2.98 1.76 1.58 1.08 5.49 2.49 15.38 Additional primary school students (thousands) 2010 872 214 619 46 990 981 3,722 2020 1,561 459 929 101 1,961 2,422 7,433 2030 1,130 375 700 135 2,960 3,038 8,338 2040 820 311 526 181 3,752 3,383 8,973 2050 780 345 407 244 3,539 2,967 8,282 Additional secondary school students (thousands) 2010 1,276 313 959 93 1,020 974 4,635 2020 1,984 561 1,928 205 2,024 2,508 9,210 2030 1,635 561 1,687 259 3,139 4,262 11,543 2040 1,554 429 1,445 312 4,056 6,481 14,277 2050 2,307 447 1,032 372 3,681 7,053 14,892 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario Total ($ billions at 2005 prices, no discounting) 2010 0.38 0.13 0.45 0.07 0.60 0.20 1.83 2020 1.00 0.38 1.15 0.19 1.77 0.64 5.13 2030 1.53 0.47 0.70 0.37 3.37 1.13 7.57 2040 2.38 0.54 0.25 0.65 4.64 1.90 10.36 2050 0.90 0.59 1.09 1.01 6.16 2.59 12.34 Additional primary school students (thousands) 2010 1,100 200 465 114 2,264 800 4,943 2020 1,423 419 555 269 4,354 1,847 8,867 2030 990 301 412 255 5,129 2,117 9,204 2040 768 216 200 232 4,470 2,038 7,924 2050 241 148 365 219 4,277 1,708 6,958 Additional secondary school students (thousands) 2010 1,237 246 597 147 2,603 880 5,710 2020 2,580 436 1,486 318 5,277 2,258 12,355 2030 2,681 359 833 339 7,143 2,843 14,198 2040 3,367 265 644 322 6,040 3,311 13,949 2050 1,315 156 703 323 5,357 3,488 11,342 Source: Economics of Adaptation to Climate Change study team. 66 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 24 Total annual costs of adaptation for all sectors, by region, 2010–50 ($ billions at 2005 prices, no discounting) East Asia and Europe and Latin America Middle East and Sub-Saharan Cost aggregation type Pacific Central Asia and Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario Gross sum 28.7 10.5 22.5 4.1 17.1 18.9 101.8 X-sum 25.0 9.4 21.5 3.0 12.6 18.1 89.6 Net sum 25.0 9.3 21.5 3.0 12.6 18.1 89.5 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario Gross sum 21.8 6.5 18.8 3.7 19.4 18.1 88.3 X-sum 19.6 5.6 16.9 3.0 15.6 16.9 77.6 Net sum 19.5 5.2 16.8 2.9 15.5 16.9 76.8 Source: Economics of Adaptation to Climate Change study team. Note: The gross aggregation method sets negative costs in any sector in a country to zero before costs are aggregated for the country and for all devel- oping countries. The X-sums net positive and negative items within countries but not across countries and include costs for a country in the aggregate as long as the net cost across sectors is positive for the country. The net aggregate measure nets negative costs within and across countries. Not surprising, both climate scenarios show costs period, from $57 billion a year in 2010–19 to $95 increasing over time (table 25). Under the NCAR billion by 2040–50. Under the NCAR scenario, scenario, annual adaptation costs are $73 billion there is little variation in costs over the 40-year during 2010–19, rising 45 percent over the next 30 period in East Asia and Pacific and Latin America years to reach $106 billion in 2040–50. Under the and the Caribbean. Costs grow most rapidly in the CSIRO scenario, growth is more rapid, through Middle East and North Africa, rising 1.6-fold over from a lower base, rising 67 percent over the entire the four decades. Table 25 Total annual costs of adaptation for all sectors, by region and period, 2010–50 (X-sums, $ billions at 2005 prices, no discounting) East Asia and Europe and Latin America and Middle East and Sub-Saharan  Period Pacific Central Asia Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR, wettest scenario 2010–19 22.7 6.5 18.9 1.9 10.1 12.8 72.9 2020–29 26.7 7.8 22.7 2.0 12.7 17.2 89.1 2030–39 23.3 10.8 20.7 3.0 13.5 19.2 90.5 2040–49 27.3 12.7 23.7 5.0 14.3 23.2 106.2 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario 2010–19 16.4 3.9 11.6 2.4 11.9 10.3 56.5 2020–29 20.1 4.7 13.1 2.6 17.5 13.3 71.3 2030–39 20.9 6.4 20.2 3.0 17.7 20.0 88.2 2040–49 21.0 7.6 22.8 3.9 15.3 24.1 94.7 Source: Economics of Adaptation to Climate Change study team. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 67 A key finding is that adaptation costs decline as middle-income group is much smaller, and these a percentage of GDP over time, suggesting that countries have more infrastructure to protect. countries become less vulnerable to climate change as their economies grow (table 26). There are con- The EACC estimates fall at the upper end of the siderable regional variations, however. Adaptation UNFCCC (2007) estimates—the study clos- costs as a percentage of GDP are highest in Sub- est in approach to this one—though not as high Saharan Africa, in large part because GDP is lower as the costs suggested by a recent critique of the in the region. Percentages remain stable in Europe UNFCCC study by Parry and others (2009) (table and Central Asia and the Middle East and North 28 and box 24). Three methodological differences Africa and fall sharply in all other regions. limit the comparability of the two studies, how- ever: this study uses a consistent set of global cli- The distribution of costs across low-, lower mid- mate models to link climate change to impacts dle-, and upper middle-income countries (based on and adaptation costs, whereas the UNFCCC study incomes in 2008) shows that adaptation costs are uses many different models; this study uses socio- fairly evenly divided across the three income groups, economic projections under the Intergovernmen- particularly under the NCAR scenario (table 27). tal Panel on Climate Change (IPCC) A2 scenario Low-income countries have higher costs than mid- (see box 4), whereas the UNFCCC uses A1B and dle-income countries under the CSIRO scenario. B1 scenarios; and this study explicitly separates the costs of development from those for adaptation, Adaptation costs as a percentage of GDP are high- whereas the UNFCCC study assumes instead that est in the low-income countries (see table 27), but climate change accounts for 25 percent of the total they are not lowest in the upper middle-income costs of development and adaptation. countries, as might be expected. This is in part because China is in the lower middle-income The major difference between the estimates is group and grows very fast over 2010–40. The upper the sixfold increase in the cost of coastal zone Table 26 Total annual costs of adaptation as a share of GDP, by region and period, 2010–50 (X-sums, percent, no discounting) East Asia and Europe and Latin America and Middle East and Sub-Saharan  Period Pacific Central Asia Caribbean North Africa South Asia Africa Total National Centre for Atmospheric Research (NCAR), wettest scenario 2010–19 0.19 0.11 0.30 0.08 0.20 0.70 0.22 2020–29 0.15 0.11 0.27 0.06 0.16 0.68 0.19 2030–39 0.09 0.12 0.19 0.07 0.12 0.55 0.14 2040–49 0.08 0.11 0.16 0.08 0.09 0.49 0.12 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario 2010–19 0.13 0.08 0.20 0.10 0.23 0.57 0.17 2020–29 0.11 0.07 0.17 0.12 0.25 0.52 0.16 2030–39 0.08 0.07 0.18 0.07 0.17 0.56 0.14 2040–49 0.06 0.07 0.16 0.06 0.09 0.50 0.11 Source: Economics of Adaptation to Climate Change study team. 68 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes management and defense under the EACC study. mates, including maintenance costs, and inclusion This difference reflects several improvements to the of costs of port upgrading and of risks from both earlier UNFCCC estimates: better unit cost esti- sea-level rise and storm surges. Table 27 Total annual costs of adaptation, by country income groups and decade, 2010–50 (X-sums, at 2005 prices, no discounting) Low income Lower middle income Upper middle income Total Amount Share of GDP Amount Share of GDP Amount Share of GDP Amount Share of GDP Period ($ billions) (percent) ($ billions) (percent) ($ billions) (percent) ($ billions) (percent) National Centre for Atmospheric Research (NCAR), wettest scenario 2010–19 26.2 0.39 25.2 0.16 21.4 0.19 72.8 0.22 2020–29 33.6 0.33 30.0 0.13 25.4 0.17 89.0 0.19 2030–39 34.2 0.23 28.2 0.09 28.2 0.15 90.6 0.14 2040–49 39.3 0.18 34.4 0.08 32.5 0.14 106.2 0.12 Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario 2010–19 23.4 0.35 17.4 0.11 15.6 0.15 56.5 0.17 2020–29 30.7 0.34 22.6 0.11 15.7 0.13 71.2 0.16 2030–39 36.4 0.27 28.6 0.09 17.9 0.12 88.2 0.14 2040–49 39.2 0.18 29.0 0.07 23.2 0.11 94.7 0.11 Source: Economics of Adaptation to Climate Change study team. Table 28 Comparison of adaptation cost estimates by the United Nations Framework Convention on Climate Change study (2007), Parry and others (2009), and the Economics of Adaptation to Climate Change study, by sector ($ billions) Economics of Adaptation to Climate Change study (in 2005 prices, no discounting) United Nations Framework Commonwealth Scientific Convention on National Centre for and Industrial Research Climate Change Parry and others Atmospheric Research Organization (CSIRO), Sector (2007) (2009) (NCAR), wettest scenario driest scenario Infrastructure 2–41 18–104 29.5 13.5 Coastal zones 5 15 30.1 29.6 Water supply and flood protection 9 >9 13.7 19.2 Agriculture, forestry, fisheries a 7 >7 7.6 7.3 Human health 5 >5 2 1.6 Extreme weather events — — 6.7 6.5 Total 28–67 — 89.6 77.7 Source: UNFCCC (2007), Parry and others (2009), and Economics of Adaptation to Climate Change study team. a The baseline provision of rural roads up to 2050 used to estimate costs of adaptation is adjusted to account for the additional length of rural roads consistent with the baseline projections for road investment. This adjustment reduces the investment in rural roads included in the cost of adaptation for agriculture by about 80–85 percent for the two climate scenarios. The adjustment for these overlaps amounts to $2.0–$2.2 billion a year averaged over the full period. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 69 Box 24 Critique of the United Nations Framework Convention on Climate Change estimates by Parry and others (2009) A recent critique of the United Nations Framework Convention on Climate Change (UNFCCC 2007) estimates of adaptation costs by Parry and others (2009) argues that the estimates may be too low because some sectors (ecosystems, energy, manufacturing, retailing, and tourism) are not covered, some sectors are not fully covered, estimates for climate proofing infrastructure stocks do not account for the need to climate proof the adaptation deficit, and residual damages (impacts remaining after adaptation) are not counted. Agriculture, forestry, and fisheries. Parry and others (2009) suggest that UNFCCC estimates in these sectors are low because they underestimate costs to maintain irrigation capacity under climate change and do not account for residual damage (a study of the wheat crop in Australia found residual damage costs to be about 20 percent of total damages). The EACC estimate for these sectors is even lower than the UNFCCC estimate. Water supply. Parry and others (2009) argue that the UNFCCC estimate is an underestimate because it does not account for the costs of managing increased flood risk, maintaining water quality standards, and supporting in-stream economic and environmental use or consider residual damages and operating costs. Parry and others also critique the UNFCCC study for failing to use hydrologic mod- els to estimate changes in reservoir capacity. The EACC analysis of water supply and flood protection avoids most of these shortfalls and is, consequently, higher. Infrastructure. Parry and others argue that low- and middle-income countries have a large infrastructure deficit and that the costs of climate proofing this additional infrastructure must be included in the adaptation costs. Parry and others estimate the additional costs at $16–$63 billion a year. The bulk of the estimates for the infrastructure sector in the EACC study are for observed levels of in- frastructure. But even after closing the adaptation deficit by allowing for an optimal level of infrastructure the EACC estimates remain much lower, at $30 billion under the wetter NCAR scenario and $14 billion under the drier CSIRO scenario. Ecosystem services. The UNFCCC estimates do not include ecosystem services. Parry and others define the costs for ecosystem servic- es as the costs of expanding and protecting terrestrial protected area networks so that they represent 10 percent of each country’s land area, costs of marine protected areas covering 30 percent of total area of the seas, and costs of biodiversity conservation in a wider matrix of landscapes. This approach to costing adaptation for ecosystem services would suggest that the development deficit should be part of the adaptation costs, an approach not used by the EACC. Instead, in the EACC estimates, some ecosystem services are covered in other sectors. Another difference is the higher costs of adaptation study includes malnutrition under the health sec- for water supply and flood protection under the tor, the EACC study includes it under the agricul- EACC study, particularly for the drier climate sce- ture sector. nario, CSIRO. This difference is explained in part by the inclusion of riverine flood protection costs The infrastructure costs of adaptation in the under the EACC study. Also pushing up the EACC EACC study fall in the middle of the UNFCCC study estimate is the study’s comprehensive sector range because of two contrary forces. Pushing up coverage, especially inclusion of the cost of adapta- the EACC estimate is the more detailed coverage tion to extreme weather events. of infrastructure. Previous studies estimated adap- tation costs as the costs of climate proofing new On the other hand, adaptation costs in the human investment flows and did not differentiate risks or health sector are lower in the EACC study than in costs by type of infrastructure. The EACC study the UNFCCC study, in part because inclusion of extended this work to estimate costs by types of the development baseline reduces the number of infrastructure services—energy, transport, water additional cases of malaria, and thereby adaptation and sanitation, communications, and urban and costs, by some 50 percent by 2030 under the EACC social infrastructure. Pushing down the EACC study. Part of the difference is also explained by dif- study estimate are measurements of adaptation ferences in sectoral coverage: while the UNFCCC against a consistently projected development 70 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes baseline and use of a smaller multiplier on base- Uncertainty about climate projections line investments than in the previous literature, based on detailed analysis of climate proofing, The analysis of adaptation costs is based on two cli- including adjustments to design standards and mate scenarios, the wetter NCAR and the drier maintenance costs. On average, the EACC study CSIRO, in an attempt to capture some of the uncer- derives a multiplier of 1.6 percent while the previ- tainty about future climate conditions. But these ous literature applied multipliers as high as 8 per- are only two global climate models among all the cent. The UNFCCC study uses an upper bound of IPCC Fourth Assessment Report (AR4) models 0.6 percent. archived at phase 3 of the Coupled Model Inter- comparison Project (CMIP3) for the A2 scenario. The scenarios are the wettest and driest of the cli- Sensitivity analysis mate models that provide the minimum and max- imum temperatures required for modeling the While climate scientists can speak with con- agriculture and infrastructure sectors. While pro- viction about general global trends of climate viding a range of estimates, the two scenarios alone change, there is a high degree of uncertainty do not give a sense of the impact of uncertainty in about the extent and timing of the impact of cli- climate projections on cost estimates. mate change on individual economies and socio- economic groups, how these groups will respond, An analysis that draws on all the IPCC AR4 mod- what the benefits and costs of planned adapta- els archived at CMIP3 for the A2 scenario for all tion measures will be, and how these factors will sectors was beyond the time and resource con- change over time. straints of this study. A limited Monte Carlo anal- ysis was conducted for the infrastructure sector Three broad types of uncertainty that affect the and provides some sense of the potential impact estimation of the costs of adaptation presented in of uncertainty about climate outcomes. The anal- this report were assessed using sensitivity analysis: ysis finds that a small number of countries face enormous variability in the costs of adapting to • Uncertainty about future climate outcomes. climate change given the uncertainty about the How might the estimates have differed had extent and nature of climate change. Managing alternative global climate models been used to this risk will need to be a key policy concern in project climate conditions? these countries. • Uncertainty about the development baseline. What if a different future were to evolve? The distributions of the climate variables for each • Uncertainty about the structure of the models grid cell and country used in the Monte Carlo anal- and the parameters used. ysis were based on the means and standard devia- tions of projections of monthly temperatures and In addition, it is possible that actual patterns of log precipitation for 2040–59 and 2080–99 gener- climate change might affect the aggregate rate ated by the global climate models analyzed by the and distribution of economic growth and how Massachusetts Institute of Technology Joint Cen- countries respond to climate change through ter for this study. For simplicity, the distributions of technological advances or the design of future climate outcomes assume a high degree of spatial economic policies. These issues are outside the correlation within countries but zero correlation scope of this study. between countries. This highlights uncertainty for The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 71 individual countries, while recognizing the effect of tainty is that the development baseline grows expo- risk pooling at a larger scale. nentially over time. Alternative assumptions about population and economic growth have only a Distributions of delta-P costs as a percentage of slight impact on estimates of the cost of adapta- base infrastructure costs by region and period were tion in 2010–19, so the margins of error associated obtained by calculating region/period totals for with the development baseline are not very impor- each climate scenario as percentages of base costs tant in the immediate future. But these margins of for the region/period and calculating the percen- error grow over time, so the discussion focuses on tiles and means of the resulting distributions (table estimates of the costs of adaptation for 2040–50, 29). The results indicate that South Asia faces by which rely on economic and population forecasts far the greatest uncertainty. While the median cost for 2050. of adaptation is 0.5 percent of base infrastructure costs, the 95th percentile is 11.9 percent, or nearly The United Nations publishes alternative popu- 25 times the median. For other regions, the 95th lation projections that rely on different assump- percentile is only 2.3–4.8 times the median. The tions about the decline of fertility in developing risk for South Asia as a consequence of unfavorable countries. The variation in population forecasts climate outcomes appears quite extreme and war- for developing countries in 2050 is approximately rants investigation. +/–14 percent for the alternative fertility assump- tions. The United Nation’s central projection has The regional average cost predicted from the consistently been revised downward over the last NCAR model falls between the median and the two decades as fertility rates have fallen faster than mean of the ensemble (Monte Carlo) regional aver- anticipated. Thus, the plausible range of uncer- ages for the 26 climate models for the A2 sce- tainty might be +/–10 percent. The range of uncer- nario (see table 29). The CSIRO model average falls tainty for growth in GDP per capita is larger. The slightly below the 25th percentile of the ensemble economic models used to generate the baseline average. Thus, the NCAR and CISRO models pro- GDP projection have a range of –26 percent to +40 vide a reasonable range of adaptation costs. percent for global GDP in 2050 using the medium fertility population projection. The variation for developing countries is even larger—from –40 per- Uncertainty about the development baseline cent to +50 percent—so the range of variation in total GDP might be –45 percent to +75 percent, a A key contribution of this study is its attempt to huge margin of uncertainty. These errors are com- separate the costs of adaptation from those of pounded by the confidence intervals of projections development by defining a development baseline. of demand as functions of population and GDP per But here, too, the study assumes just one future capita. On this basis, it is very difficult to calculate development path. How would the costs of adap- potential margins of error in the estimates of the tation change with a different development path? costs of adaptation. The basic elements of the development baseline are growth in population, GDP per capita, and The sensitivity of adaptation cost estimates in agri- urbanization, which drive the demand for food, culture was explored using a 10 percent increase investment in infrastructure, benefits of protect- in per capita GDP relative to the baseline projec- ing coastal zones, and so on and thus determine tions and a 10 percent increase in population (table the costs of adaptation. One element of uncer- 30). Across all developing countries, a 10 percent 72 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 29 Delta-P costs for infrastructure as a percentage of base infrastructure costs for the two global climate models used in the Economics of Adaptation to Climate Change study and Monte Carlo simulations of all models, by region and period, 2010–50 (percent) Results of Monte Carlo model simulations NCAR, 95th Period and region wettest CSIRO, driest Mean 5th percentile 25th percentile Median 75th percentile percentile 2010–19 East Asia and Pacific 1.60 0.73 1.30 0.09 0.36 0.65 1.72 4.04 Europe and Central 0.44 0.23 1.02 0.36 0.54 0.75 0.95 2.74 Asia Latin America and 0.87 0.68 2.90 0.89 1.47 2.13 3.86 7.69 Caribbean Middle East and North 1.01 0.67 1.09 0.30 0.43 0.57 1.03 3.19 Africa South Asia 1.71 0.63 4.01 0.04 0.17 0.36 1.48 15.80 Sub-Saharan Africa 1.32 0.84 2.57 0.97 1.64 2.22 3.20 6.09 2020–29 East Asia and Pacific 1.79 0.64 1.36 0.14 0.38 0.75 1.89 4.15 Europe and Central 0.50 0.31 1.68 0.63 0.93 1.23 1.95 3.99 Asia Latin America and 1.11 0.67 3.06 1.19 1.71 2.34 4.07 7.46 Caribbean Middle East and North 1.08 0.63 1.23 0.42 0.56 0.83 1.31 3.16 Africa South Asia 2.21 0.64 3.47 0.06 0.22 0.44 1.64 13.95 Sub-Saharan Africa 2.08 1.00 2.43 1.03 1.62 2.17 2.93 5.38 2030–39 East Asia and Pacific 1.72 0.67 1.26 0.17 0.40 0.81 1.71 3.66 Europe and Central 1.02 0.37 1.72 0.69 1.02 1.48 2.08 3.49 Asia Latin America and 1.27 0.58 2.77 1.11 1.61 2.19 3.61 6.49 Caribbean Middle East and North 1.07 0.64 1.13 0.45 0.65 0.81 1.16 2.78 Africa South Asia 2.18 1.20 2.89 0.06 0.28 0.50 1.55 11.91 Sub-Saharan Africa 2.70 1.15 2.16 0.97 1.49 1.98 2.59 4.42 2040–49 East Asia and Pacific 1.84 0.71 1.13 0.15 0.40 0.74 1.49 3.11 Europe and Central 1.09 0.49 1.29 0.62 0.82 1.15 1.48 2.45 Asia Latin America and 1.49 0.58 2.32 0.95 1.36 1.88 2.96 5.27 Caribbean Middle East and North 1.04 0.81 0.93 0.45 0.59 0.70 0.95 2.08 Africa (continued on next page) The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 73 Table 29 (continued) Delta-P costs for infrastructure as a percentage of base infrastructure costs for the two global climate models used in the Economics of Adaptation to Climate Change study and Monte Carlo simulations of all models, by region and period, 2010–50 (percent) Results of Monte Carlo model simulations NCAR, 95th Period and region wettest CSIRO, driest Mean 5th percentile 25th percentile Median 75th percentile percentile South Asia 2.11 1.79 2.38 0.11 0.31 0.53 1.33 9.90 Sub-Saharan Africa 3.23 1.38 1.86 0.89 1.34 1.72 2.21 3.59 Full period East Asia and Pacific 1.76 0.69 1.23 0.16 0.41 0.75 1.65 3.57 Europe and Central 0.80 0.37 1.45 0.61 0.89 1.21 1.64 3.01 Asia Latin America and 1.24 0.61 2.68 1.05 1.53 2.10 3.51 6.44 Caribbean Middle East and North 1.05 0.70 1.06 0.42 0.58 0.74 1.09 2.63 Africa South Asia 2.09 1.20 2.92 0.08 0.27 0.48 1.52 11.94 Sub-Saharan Africa 2.57 1.15 2.14 0.96 1.48 1.93 2.56 4.43 Period mean 1.58 0.79 1.91 0.54 0.86 1.21 1.99 5.34 Source: Economics of Adaptation to Climate Change study team. Note: The analysis draws on all the IPCC AR4 models archived at phase 3 of the Coupled Model Intercomparison Project (CMIP3) for the A2 scenario. Delta-P cost is the adaptation cost computed as the additional cost of constructing, operating, and maintaining baseline levels of infrastructure services under the new climate conditions projected by the two global climate models. increase in per capita GDP under the baseline East and North Africa of about 3.5 percent. A 10 results in a 1.4 percent overall decline in the num- percent increase in population growth has a much ber of malnourished children, with the greatest larger, and negative, effect on the number of mal- declines in East Asia and Pacific and the Middle nourished children, which rises by about 8 percent, Table 30 Percentage change in number of malnourished children with a 10 percent increase in GDP per capita and population growth, by region and climate scenario, 2010–50 Climate East Asia and Europe and Latin America and Middle East and Sub-Saharan scenario South Asia Pacific Central Asia Caribbean North Africa Africa Total 10 percent increase in GDP per capita NCAR, wettest –0.8 –3.5 –0.3 –0.2 –3.5 –1.7 –1.4 CSIRO, driest –0.8 –3.5 –0.3 –0.2 –3.6 –1.7 –1.4 10 percent increase in population NCAR, wettest 5.2 5.9 5.0 5.7 10.0 11.9 7.9 CSIRO, driest 5.2 6.0 5.1 5.7 10.2 11.9 7.9 Source: Economics of Adaptation to Climate Change study team. 74 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes with the greatest increases in the Middle East and on the estimates of the costs of adaptation as a per- North Africa and Sub-Saharan Africa. centage of GDP for 2010–19; however, the impact increases over time. Under the NCAR scenario with A more robust sensitivity test considers how the EACC development baseline projection, the much the costs of adaptation increase or decrease overall cost of adaptation falls from 0.22 percent of as a percentage of GDP at higher and lower eco- developing world GDP in 2010–19 to 0.12 percent nomic and population baselines. For most sectors in 2040–50 (see table 26). With a range of uncer- and especially overall, the cost of adaptation as a tainty for aggregate GDP of –45 percent to +75 share of GDP falls as GDP rises (see, for exam- percent, trend projections indicate that the associ- ple, tables 26 and 27, which show that this effect ated costs of adaptation would range from 0.16 per- is stronger than any increase in the impact of cli- cent of GDP in 2040–50 (low economic growth) to mate change over time). Three factors account for 0.09 percent of GDP in 2040–50 (high economic this relationship: growth), with a central value of 0.12 percent. • Adaptation has large fixed costs that are sub- stantially independent of future levels of GDP Model and parameter uncertainty and population, particularly those for pro- tecting populated coastal zones. The analysis All sector analyses rely on large numbers of of coastal protection allows for residual dam- model assumptions and parameters that feed into ages, which increase with population and GDP the estimation of the cost of adaptation. Some per capita, but this is a small fraction of the examples: total cost and is limited by the option of pro- viding more extensive protection. Maintenance • Infrastructure. Dose-response relationships of existing infrastructure that is not adapted to linking changes in climate variables to changes changed climate conditions is also a fixed cost in design standards and average costs of con- that diminishes over time. struction, changes in operating efficiency and • The income and population elasticities of costs under different ambient conditions, base- demand for infrastructure, food, and water line construction and maintenance costs. are well below one, so that higher aggregate • Coastal zones. Unit costs of building dikes or GDP does not translate into proportionately undertaking beach nourishment, exposure of higher costs of investing in or operating fixed coastal zones to flooding and permanent inun- assets. dation, relationships between aggregate GDP • The relationships between the development and the decision to protect segments of coast. baseline and the costs of adapting to climate • Water supply and flood protection. Runoff change for health and extreme weather events curves, the unit costs of building additional operate to reduce the costs of adaptation as water storage and river flood defenses, and the GDP per capita increases. Higher population backstop cost of alternative ways of meeting could weaken their relationship somewhat, demand for water. but the overall direction of change is a strong • Agriculture. Elasticities of agricultural pro- downward trend in the cost of adaptation. duction to investments in research, irriga- tion improvements, and rural roads; impact In summary, uncertainty about the development of changes in trade margins; substitution in baseline is not likely to have an important impact demand between food products. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 75 Some variables, such as unit costs, affect the esti- and select the one with the best performance in mates of adaptation costs in a linear manner, so infrastructure investment as the most efficient. The that increasing one or more unit costs by 10 per- development deficit is measured as the difference cent will increase the associated costs by the same between actual levels of infrastructure and pre- percentage. However, almost all sectors include dicted levels derived from frontier regressions that strongly nonlinear elements. For infrastructure, fit the outer envelope of infrastructure stocks given the costs of adaptation for many assets incorpo- the values of exogenous variables. These frontier rate step functions so that, for example, the aver- regressions define the baseline projections used in age cost of constructing and maintaining paved calculating the costs of adaptation. roads increases with each 3°C increase in maxi- mum temperature or 100 millimeter increase in The difference between the two approaches to total precipitation. Such nonlinearities mean that it defining the development baseline is that the base- is difficult to estimate the sensitivity of adaptation line without the adaptation deficit starts with costs to model and parameter uncertainty without lower initial stocks of infrastructure but may imply detailed investigations using Monte Carlo or sim- greater investment in constructing new infrastruc- ilar techniques. Such work was not feasible within ture in the future than the baseline with the adap- the time and resources available for this study, and tation deficit. On the other hand, the baseline with it remains a matter for further research. the adaptation deficit assumes a higher initial stock of infrastructure, which must be maintained and One additional form of model uncertainty was replaced over time, but it may imply lower invest- examined for the infrastructure sector. The sectoral ment in additions to the stock of infrastructure in analyses in this section are based on a definition of future years. Depending on the relative costs of the development baseline that starts from current adaptation for existing stocks and new investments, levels of infrastructure provision, rather than some either approach might yield higher total costs of higher level that includes an adjustment for the adaptation. adaptation deficit. If it is assumed (as it was in the sectoral analyses) that countries are currently allo- The costs of adaptation adjusted for the adaptation cating their resources efficiently, neither underin- deficit are consistently higher than those derived vesting nor overinvesting in infrastructure, there is from actual investment decisions, in total and in no adaptation deficit and the development baseline each decade to 2050 (table 31). Under the NCAR can be based on current levels of infrastructure. scenario and over the entire 40-year period, adap- If, however, it is assumed that countries should be tation costs are 23 percent higher adjusting for the investing more or less in infrastructure, and less or adaptation deficit than are those based on actual more in some other sector of the economy, then an investment decisions. Under the CSIRO scenario, adaptation deficit exists. This deficit is incorporated this difference rises to 26 percent. These higher into the analysis by calculating adaptation costs for costs arise because the extra costs of maintaining a higher level of infrastructure in each period. and replacing a larger initial stock of infrastruc- ture outweigh the higher costs of construction for This deficit can only be approximated. One way is a larger investment program in later periods, even to compare countries of similar levels of income without discounting. 76 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes Table 31 Annual delta-P costs of adaptation for infrastructure, actual investment and investment adjusted for the adaptation deficit, by period, 2010–50 (X-sums, $ billions at 2005 prices, no discounting) Commonwealth Scientific and National Centre for Industrial Research Organization Atmospheric Research (NCAR), wettest scenario (CSIRO), driest scenario Adjusted for adaptation Adjusted for adaptation Period Actual investment deficit Actual investment deficit 2010–19 15.9 20.9 7.8 11.3 2020–29 24.2 31.6 9.2 13.7 2030–39 33.8 43.3 14.2 20.7 2040–49 44.0 55.6 22.9 31.5 Average 29.5 37.9 13.5 19.4 Source: Economics of Adaptation to Climate Change study team. Note: Delta-P cost is the adaptation cost computed as the additional cost of constructing, operating, and maintaining baseline levels of infrastructure services under the new climate conditions projected by the two global climate models. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 77 Section 6. Key Lessons FIGURE 4 Development greatly lowers the number of people killed by oods and a ected by oods and droughts, The sectoral estimates of adaptation costs presented 2000–50 in this report point to a number of lessons. A key Killed by Floods (Per Million) lesson is that adaptation to a 2°C warmer world will 0.7 NCAR Static be costly—and it will be even more costly if coun- Historical 0.6 tries fail to take mitigation measures to avoid even CSIRO Static greater warming and other climate change. 0.5 0.4 NCAR Development Development is imperative… 0.3 CSIRO Development 0.2 Development is adaptation, and it must remain 2000 2010 2020 2030 2040 2050 a global imperative. Not only does development A ected by Floods make economies less reliant on climate-sensitive 0.0045 NCAR Static sectors, such as agriculture, but by increasing levels of incomes, health, and education, it expands the Historical capacity of households to adapt, and by improving 0.0035 CSIRO Static institutional infrastructure, it enhances the ability of governments to assist. NCAR 0.0025 Development Development dramatically reduces the numbers CSIRO Development of people killed by floods and affected by floods 0.0015 2000 2010 2020 2030 2040 2050 and droughts, quite apart from the impact of cli- mate change (figure 4). If development is held con- A ected by Droughts stant at 2000 levels, the number of people killed by 0.0055 CSIRO Static floods increases over time under the NCAR (wet- test) scenario and decrease under the CSIRO (dri- Historical est) scenario. Allowing for development between NCAR Static 2000 and 2050 greatly reduces the numbers of peo- 0.0045 CSIRO ple killed under both scenarios. The findings are Development similar for the number of people affected by floods NCAR Development and droughts. 0.0035 2000 2010 2020 2030 2040 2050 In the health sector analysis, allowing for devel- Source: Economics of Adaptation to Climate Change study team. opment reduces the number of additional cases of malaria, and thereby adaptation costs, by more than half by 2030 and more than three-quarters by 2050. Development must be inclusive, however, to have these effects. And development can also increase The greater the baseline level of development in vulnerabilities: the more developed the country, each period, the smaller is the impact of climate the greater the value of infrastructure and personal change and the smaller are the costs of adaptation. property at risk from climate change and therefore 78 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes the greater the cost of climate proofing such assets. Though adaptation is costly, costs can be reduced However, these costs decrease with development as a percentage of GDP. The clearest opportunities to reduce the costs of adaptation are in water supply and flood protec- tion. Almost every developed country has experi- …but not simply development as usual enced what can happen when countries fail to shift patterns of development or to manage resources Adaptation will also require a different kind of in ways that take account of the potential impacts development—breeding crops that are drought and of climate change. Often, the reluctance to change flood tolerant, climate proofing infrastructure to reflects the political and economic costs of chang- make it resilient to climate risks, reducing overca- ing policies and (quasi-) property rights that have pacity in the fisheries industry, accounting for the underpinned decades or centuries of development. inherent uncertainty in future climate projections Countries that are experiencing rapid economic in development planning, and others. growth have an opportunity to reduce the costs associated with the legacy of past development by Consider water supply. Adapting to changing con- ensuring that future development takes account of ditions in water availability and demand has always changes in climate conditions. been at the core of water management. Tradition- ally, though, water managers and users have relied Here are just a few examples of opportunities to on historical experience when planning. Water reduce the costs of adaptation in the water supply supply management has concentrated on meeting and flood protection sector: increasing water demand, and flood defense mea- sures have assumed consistency in flood recurrence • The costs of coastal protection assume that periods. These assumptions no longer hold under the proportion of nonagricultural GDP pro- climate change. Water management practices and duced in the coastal zone of each country does procedures for designing water-related infrastruc- not change, thus justifying a gradual increase ture need to be revised to account for future cli- in the share of coastline that is protected. If mate conditions (see box 25 for an example at the instead countries adopted a policy of protect- local level). Similarly, dikes and other coastal pro- ing existing developed areas while prohibit- tection measures will need to be built in anticipa- ing any further development or increase in the tion of rising sea levels. proportion of the coastline that is protected, Box 25 Local knowledge and ownership in water storage: the Kitui sand dams in Kenya Kitui District, a semiarid region 135 kilometers east of Nairobi, has highly erratic and unreliable rainfall, with two rainy seasons providing 90 percent of the annual rainfall. Historical analysis of meteorological data shows that climate change has already affected Kitui District. Since 1990, Sahelian Solution Foundation, a local nongovernmental organization, has been assisting local communities in building more than 500 small-scale (3–50 meters wide) sand dams to store water in artificially enlarged sandy aquifers. Sand dams are small concrete structures built in ephemeral rivers to store excess rainfall for use during periods of drought. This old technique differs from traditional dams by storing water within the sand and gravel particles, which accumulate against the dam wall. The sand prevents high evaporation losses and contamination. Since the start of the project more than 67,500 people in Kitui have gained better access to safe drinking water, at an average invest- ment of less than $35 a person, through community use of local knowledge about water to cope with droughts. The increased water availability and the time saved have brought positive social and economic changes, especially in agriculture. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 79 future costs of adaptation would be much public sector, and it assumes limited or no change lower. in technology, except in the agriculture sector anal- • Similar considerations apply to development in ysis. But the boundary between public and pri- river floodplains, though it is easy to contem- vate (autonomous) adaptation is almost infinitely plate going further to relocate assets that may flexible. So long as governments and the pub- be at risk of future flooding. lic sector ensure that incentives for innovation, • Economists and others regularly urge the investment, and private decisions reflect the scar- adoption of mechanisms for managing water city of resources once the impact of climate change resources that recognize the scarcity value of is taken into account, experience demonstrates raw water. This advice is almost invariably that the costs of adaptation may be dramatically ignored. The reasons for the poor management reduced by a combination of technical change and of water resources are varied and deeply embed- private initiative. ded in political and social systems. But the costs of misallocation of water resources will escalate even without climate change and could be over- Uncertainty remains a challenge whelming under conditions of climate change. A large share of the costs of adaptation in water The inherent uncertainty in climate projections supply and flood protection could be avoided by makes climate-resilient development planning a adopting better management policies. challenge. While the science is clear on general • A similar observation can be made for the global trends of climate change, current climate sci- use of water in municipal and industrial sec- ence can provide little guidance to public invest- tors. Demand for such water is not price inelas- ment in specific countries or sectors, with the tic, yet average and marginal water tariffs tend exception of sea-level rise. to be well below the long-run marginal cost of necessary infrastructure and ignore the scarcity This study has estimated the cost of adaptation value of water. under 2 (of 26) global climate models associated with the A2 scenario of the Intergovernmental While the scale of adaptation costs for water sup- Panel on Climate Change (IPCC) Special Report on ply and flood protection means that the potential Emissions Scenarios (SRES; see box 4). The costs savings from better policies are particularly large, were estimated as though the countries knew with other sectors also suffer from the misallocations of certainty what the climate outcome would be. This resources that result from failures to adopt sensible is clearly not the case. policies. The costs of adaptation in transport and electricity can be reduced, perhaps substantially, by Two lessons about uncertainty have emerged in this pricing services to reflect the true cost of the scarce study. First, country-level data for climate plan- resources used in providing them. In the reverse ning do not exist. Results for individual countries direction, the estimates of the costs of adaptation vary so widely for current climate models that cli- for agriculture are much lower than would emerge mate scientists agree that the results cannot be used had an assumption of partial or complete agricul- for making country-level decisions. This implies tural or food self-sufficiency been imposed. that climate adaptation must be limited to robust measures such as education and climate-related For good practical reasons, this study focuses on research. For durable climate-sensitive investments, the costs of adaptation that are likely to fall on the a strategy is needed that maximizes the flexibility to 80 The CosT To Developing CounTries of ADApTing To ClimATe ChAnge—new meThoDs AnD esTimATes incorporate new climate knowledge as it becomes and insure. Countries will select among these available. Hedging against varying climate out- options, depending on specific investment deci- comes, for example by preparing for both drier and sions and their level of risk aversion. wetter conditions for agriculture, would raise the cost of adaptation well above the estimates here. Since climate change is gradual, designing for lim- ited or no change in climate conditions while wait- Second, a few climate models predict extremely ing for better information might save money today high adaptation costs for a few countries. A small but will likely result in high future costs for main- number of countries face enormous variability in tenance or earlier replacement of assets if climate the costs of adapting to climate change under cur- conditions are worse than anticipated. Prepar- rent conditions of uncertainty about the extent and ing for the worst might not be that expensive if nature of climate change. Preliminary Monte Carlo the cost of adjusting design standards to accom- analysis (see section 5) for the infrastructure sector modate future climate conditions is relatively suggests that 5 percent of countries will incur costs small, as is the case for many infrastructure assets. of more than 92 percent of base costs of installed Insurance is more complicated, because uncer- infrastructure in the worst 5 percent of climate out- tainty about climate change also involves regional comes. The important lesson is not the magnitude shifts in temperature and rainfall. What might be of the costs of adaptation under the majority of cli- large uncertainties for individual countries might mate scenarios, but rather the possible impact of become much smaller when the costs of adaptation the worst-case climate scenarios on a small number are pooled, particularly across regions. A funding of countries that face extreme costs of adaptation. mechanism that permits the reallocation of funds across regions as better information is collected There are three ways to deal with this uncertainty: about the actual outcome of climate change would wait for better information, prepare for the worst, provide a basis for pooling risks across countries. The globAl reporT of The eConomiCs of ADApTATion To ClimATe ChAnge sTuDy 81 References Diaz, R.J., and R. Rosenberg. 2008. “Spreading Dead Zones and Consequences for Marine Ecosys- Acemoglu, D., S. Johnson, and J.R. Robinson. tems.” Science 321 (5891): 926–29. 2001. 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