GREENHOUSE GAS EMISSIONS CONTROL
IN THE FORESTRY SECTOR
EME*EM
Todd M. Johnson and Julian Lampietti
with Lars Blomkvist and Xu Deying
November 1994






CHINA
Issues and Options in Greenhouse Gas Emissions Control
Greenhouse Gas Emissions Control
in the Forestry Sector
SUBREPORT NUMBER 6
by
Todd M. Johnson, Environmental Economist, The World Bank
Julian Lampietti, Consultant, The World Bank
Lars Blomkvist, Senior Forester, SGS Silviconsult
and
Xu Deying, Professor, Forest Ecology and Environment Institute,
Chinese Academy of Forestry
November 1994
Supported by the Global Environment Facility



The views expressed herein are those of the authors and do not necessarily
represent those of the World Bank.
Copyright 1994
Additional copies of this report may be obtained from
The World Bank
Industry and Energy Division
China and Mongolia Department
East Asian and Pacific Regional Office
1818 H Street, NW
Washington, DC 20433
OTHER SUBREPORTS IN THIS SERIES:
Estimation of Greenhouse Gas Emissions and Sinks in China, 1990, August 1994. Report 1.
Energy Demand in China: Overview Report, February 1995, forthcoming. Report 2.
Energy Efficiency in China: Technical and Sectoral Analysis, August 1994, Report 3.
Energy Efficiency in China: Case Studies and Economic Analysis, December 1994. Report 4.
Alternative Energy Supply Options to Substitute for Carbon-Intensive Fuels, December 1994.
Report 5.
Greenhouse Gas Control in the Agricultural Sector, September 1994. Report 7.
Valuing the Health Effects of Air Pollution: Application to Industrial Energy Efficiency
Projects in China, October 1994. Report 8.
Potential Impacts of Climate Change on China, September 1994. Report 9.
Residential and Commercial Energy Efficiency Opportunities: Taiyuan Case Study,
September 1994, Report 10.
Pre-Feasibility Study on High Efficiency Industrial Boilers, August 1994. Report 11.



FOREWORD
This report is one of eleven subreports prepared as inputs to the United Nations
Development Programme (UNDP) technical assistance study, China: Issues and Options in
Greenhouse Gas Emissions Control, supported by the Global Environment Facility and
executed by the Industry and Energy Division, China and Mongolia Department, of the
World Bank. On the Chinese side, overall coordination for the project was managed by the
National Environmental Protection Agency (NEPA), while the Chinese Academy of
Forestry participated in the research for this subreport.
This report considers the effect that forest management and tree planting has on
China's net carbon dioxide emissions. It assesses the potential and net costs of carbon
sequestration under various planting scenarios. Missions visited China in November 1992
and June 1993 for work on the scope of the study and the design of the forestry models. A
major review meeting was held in Washington, DC in November 1993 to discuss the
results and implications of the modeling work and the overall findings and conclusions.
The forestry report was drafted and edited by Todd M. Johnson and Julian Lampietti with
major contributions on the modeling and the final conclusions provided by Lars Blomkvist
and Xu Deying. The authors would like to thank the Chinese Academy of Forestry in
Beijing, Hari Eswaran from the US Department of Agriculture, Stephen Boyce from Duke
University, and Keith Openshaw, a consultant to the World Bank, who prepared a
background report and offered significant help with the conclusions of this study.



ii
CURRENCY EQUIVALENTS
1 US$ = 4.7 Chinese Yuan (1990)
WEIGHTS AND MEASURES
hectare =104 M2 = 2.47 acres
1 ton fuelwood (air dry) = 0.54 tce
ABBREVIATIONS AND ACRONYMS
C            - carbon
CO2          - carbon dioxide
FGHY         - fast-growing high-yield forestry plantations
GEF          - Global Environment Facility
GHG          - greenhouse gas
IRR          - internal rate of return
MAI          - mean annual increment
mt           - million (metric) tons
NAP          - National Afforestation Project
NEPA         - National Environmental Protection Agency of China
NFPA         - National Forest Planning Agency
NPV          - net present value
OECD         - Organization for Economic Cooperation and Development
UNDP         - United Nations Development Programme



iii
CONTENTS
1. FORESTS AND GLOBAL CLIMATE CHANGE ..........................................1
2. BACKGROUND ..........................................                2
A. FORESTRY IN CHINA .........................................2
Forest resources .........................................2
Wood demand ..........................................                4
Afforestation .........................................               4
Fast-growing high-yield (FGHY) programs ..........................................5
Management and production in Chinese forests ......................................... 5
B. ORGANIC CARBON ASSESSMENT .........................................7
Woody biomass ...........................................7
Soil carbon ..........................................                8
3. MODELING CARBON SEQUESTRATION .......................................... 9
A. NATIONAL MODEL ...........................................9
Structure of the model ..............................9
Uncertainty and use limitations ........................... 10
National model scenarios ........................... 11
Results of the national model ........................... 12
B. FORESTRY PLANTATION MODELS: FINANCIAL AND ECONOMIC ANALYSIS 14
Types of plantations ............................. 14
Results of the financial analysis .............................      15
4. DISCUSSION AND CONCLUSIONS ............................. 20
5. REFERENCES .............................. 22
6. APPENDIX A: NATIONAL MODEL ............................. 24
7. APPENDIX B: PLANTATION MODEL RESULTS ...................................... 25



iv
LIST OF TABLES
TABLE 1. REGIONS DEFINED ..............................................................  2
TABLE 2. FORESTED AND POTENTIAL FOREST LAND IN 1988, (MILLION HA) ................... 3
TABLE 3. AGE PROFILE OF CHINA'S FORESTS IN 1988, (MILLION HA) ............................ 4
TABLE 4. WOODY BIOMASS (MILLION METRIC TONS, AIR DRY) .................................... 7
TABLE 5. AVERAGE SOIL CARBON TO ONE METER DEPTH .......................................... 8
TABLE 6. PLANTING ASSUMPTIONS (MILLION HECTARES PER YEAR) ............................. 9
TABLE 7. SENSITIVITY ANALYSIS .............................................................. 10
TABLE 8. MEAN ANNUAL INCREMENT (CUBIC METERS PER YEAR) .......... ................... 1 1
TABLE 9. CUMULATIVE AREA PLANTED UNDER THREE SCENARIOS (MILLION HECTARES) ... 11
TABLE 10. RANGE OF ESTIMATES FOR TOTAL SEQUESTERED CARBON (MILLION TONS) ....... 12
TABLE 11. STEMWOOD HARVESTED BY END PRODUCT (MILLION CUBIC METERS) ...... ....... 12
TABLE 12. STANDING STOCK BY AGE CLASS (MILLION CUBIC METERS) ......................... 13
TABLE 13. ANNUAL CARBON BALANCE (MILLION TONS) ................... ...................... 13
TABLE 14. PLANTATION SCENARIOS ('000 HECTARES PER YEAR) ............................... 15
TABLE 15. INTENSIVE PLANTATIONS: FINANCIAL ANALYSIS AND SEQUESTRATION COSTS.. 16
TABLE 16. EXTENSIVE PLANTATIONS: FINANCIAL ANALYSIS AND SEQUESTRATION COSTS. 17
TABLE 17. FUELWOOD PRODUCTION FROM FUELWOOD AND .................................... 17
TABLE 18. CARBON SEQUESTRATION BY PLANTATIONS, 1990-2020 (MILLION TONS C) ..... 18
LIST OF FIGURES
FIGURE 1. CHINA'S FIVE REGIONS ............................................................... 2
FIGURE 2. FORESTED AND POTENTIAL FOREST LAND AS A PERCENT OF TOTAL LAND AREA . . .3
FIGURE 3. SOIL CARBON LEVELS ..............................................................   8



v
EXECUTIVE SUMMARY
i.    Through afforestation projects, the planting of timber and fuelwood plantations, and
improved management of open forests, it is possible to store carbon in trees and soil and
thus reduce net GHG emissions in China. Carbon sequestration is maximized by planting
high-yield and fast-growing species on good land, under good growing conditions, and by
applying scientific management. If part of the production of fuelwood can be substituted
for coal, for instance, in direct substitution or in power generation, the contribution of the
forestry sector in China to net CO2 emission reduction would be even larger.
ii.   Two models are developed to study carbon sequestration in China's forests: (a) a
national model to predict the forest carbon balance, and (b) a plantation model to provide
information on the financial costs and benefits of forest management schemes. Both models
are simulated for 30 years, starting in 1990.
iii.  The analysis of tree planting in China shows that a moderately successful large-
scale afforestation program could sequester a cumulative total of 2.2 to 4.6 billion tons of
carbon in woody biomass and soil over a thirty year period, or an average of 116 million
tons carbon (mtC) per year. Under a highly successful scenario, the amount of carbon
sequestered in the year 2020 would be 221 mtC. For comparison, China's GHG emissions
in 1990 from all sources are estimated at 800 mtC. To achieve this level of carbon
sequestration from the forestry sector, China would need to increase forested land by 4-5
million hectares per year between now and the year 2020, extend the use of fast-growing
high-yield plantations, and broadly disseminate advanced silviculture techniques. This
level of planting would increase the percentage of forested land in China from about 13
percent in 1990 to more than 20 percent by the year 2020. Although fuelwood plantations
do not sequester much carbon on a net basis, they can make a contribution to GHG
reduction by substituting regenerable biomass for fossil fuels.
iv.   A net cost analysis of carbon sequestration from forestry development finds that the
following types of plantations in China are financially and economically attractive on a life-
cycle basis even if GHG benefits are not considered: (i) intensively-managed fast-growing
high-yield (FGHY) timber plantations on good land in most parts of China, (ii)
extensively-managed timber plantations in South and Southwest China, (iii) improved open
forest management regimes in South China, and (iv) intensively-managed FGHY fuelwood
plantations in South and Southwest China.
v.    Afforestation and forestry management practices that have the potential for
maximizing carbon sequestration at the lowest net cost should be the focus of government
support. While State Forest Farms must play a major role in afforestation work in China,
private sector involvement and funds will be needed. Policies to encourage both public
and private investment in the forestry sector are needed in China, including improvements
in rural capital markets, further price reform, clarification of legal rights, and liberalization



vi
of foreign trade and investment policies. Technical assistance or technology transfer can
also be important to further expand China's fast-growing high-yield plantation program,
and to improve silviculture techniques, the efficiency of wood harvesting and milling,
nursery management, and forestry research and extension.



1. FORESTS AND GLOBAL CLIMATE CHANGE
1.1   Increasing atmospheric concentrations of carbon dioxide, methane, nitrous oxide,
and chloroflurocarbons cause changes in the earth's surface temperature. Carbon dioxide is
the largest contributor to this change. Forests are prominent in the global carbon cycle and
in the exchange of carbon between terrestrial ecosystems and the atmosphere (Tans et al.
1990 and Dale et al. 1991). Forest vegetation and forest soil account for 60 percent of the
organic carbon stored on the Earth's land surface (Schlesinger and Waring, 1985). The
potential for using forestry to sequester atmospheric carbon has been extensively
investigated (Dixon et al. 1991, and Moulton and Richards 1990), including work on
China by one of the authors (Xu 1993, 1993a).
1.2   Forests are both a sink and a source of carbon. Trees take up carbon from the
atmosphere to build their structure and maintain their physiological processes and they
store carbon in their woody biomass and release carbon through respiration and
decomposition. Forest soils absorb carbon from decomposing biomass; they store carbon in
organic matter, and they discharge it through respiration. Young forests rapidly accumulate
carbon in stemwood and soil. Mature forests are generally in equilibrium, with carbon
uptake equaling carbon release. The pool of carbon held in forests can be maintained by
reducing deforestation and it can be raised by improving forest management and increasing
afforestation.
1.3   The storing of carbon in woody biomass and soils --carbon sequestration-- can be a
cost-effective means of reducing net GHG emissions in developing countries. 1 The key to
low-cost carbon sequestration in developing countries is to take advantage of the financial
and social benefits from forestry development. Under the right conditions, multi-use
afforestation projects, the planting of timber and fuelwood plantations, and the
management of open forests in China can yield positive financial returns, meaning that the
cost of carbon sequestration from these projects is low.
1 Net GHG emissions is the sum of all emission sources minus the amount of carbon that can be
captured and stored in plant biomass or soils.



2
2. BACKGROUND
A. FORESTRY IN CHINA
2.1   In China, "forest land" often refers to administrative control of the land and can
refer to land with trees and land without trees but available for planting. Forest land is
therefore best separated into two categories: (a) forested land, and (b) potential forest land.
Forested land has at least 30 percent crown cover, but includes forest fallow. Potential
forest land contains degraded forest with less than 30 percent crown cover, and all lands
designated for forestry purposes by the government.
2.2   China's forests can be separated into five regions (Figure 1). The following
discussion uses these regional definitions. The largest of these regions is the Northwest,
followed by the North, South, Northeast, and Southwest.
Figure 1. China's five regions
NE Nj       . Region      Provinces
_Jn               , '1. North                  Hebei, Shanxi, Anhui,
r     t-            N w - \ ,'                   Henan, Shandong, Inner
t-1  NW  . '' '; -  -' /--t-¢ >   Mongolia
NW 
3. Northeast  Liaoning, Jilin,
Heilongjiang
2. Northwest  Xinjiang, Tibet, Gansu,
,->Sa            s                     Qinghai, Ningxia, Shaanxi
~ -r:,   ' /5. South             Jiangxi, Jiangsu, Zhejiang,
ki W  bn              Fujian, Hubei, Hunan,
SW            o 500 4O    .            Guangdong, Guangxi
4.Southwest  Guizhou, Sichuan, Yunnan
Source: Chinese Academy of Forestry,
1993
Forest resources
2.3   China is deficient in forest resources. China currently has about 131 million
hectares of forested land, up from around 119 million hectares in 1988 (Table 2). Still,
forests account for only 13.6 percent of the land area of China. In per capita terms, forest
resources amount to only 0. 11 hectares per capita, less than one-sixth the world average.
Standing volume of wood is about 11 billion cubic meters (mi3), equivalent to about 9.5 m3
per capita, far below the world average of 66 m3 per capita. Natural forests account for
about three-quarters of the forested area in China and 95 percent of the standing wood



3
volume. Most natural forests are located in the Northeast provinces of Jilin, Liaoning, and
Inner Mongolia, and in the Southwest provinces of Sichuan and Yunnan (Table 2). The
North, Northwest, and Southwest all have less than 9 percent forest cover (Figure 2a).
Excellent potential forest land is located in the South, Southwest, and Northeast. The
government has identified the comparative advantage offered by the South's tropical
climate, targeting it as the principal potential forest region (Figure 2b). By the late 1980s,
the stock of mature and over-mature forests amounted to about 2.6 billion m3, of which
only about half was commercial. Evidence from many sources indicates that the stock of
natural commercial forests is rapidly being depleted. The computer model constructed for
this study, described in detail below, shows that the resources of mature forest would be
depleted within ten years at current exploitation rates.
Table 2. Forested and potential forest land in 1988, (million ha)
gegions            Total   North  Northeast  Northwest  South   Southwest-
Area               950     95     195        284         145    231
Forested land       119    6      36         16         41      20
Potential forest land  130  14    26         19         39      31
Source: Xu, 1993
Figure 2. Forested and Potential forest land as a percent of total land area
a. Forested land, 1988  ''                  b. Potential forest land, 1988  1  I
Percentoflandarea
20-290%
10.19
I 5.9%
km
0 500 1000
2.4    A forest census for China from 1984 to 1988 found a declining forest area,
diminishing growing stocks, and a poorer quality of timber.2 A repercussion of
deforestation is that 73 percent of China' s timberlands are under 40 years old (Table 3).
The declining stock of near mature and mature trees signals an impending shortage of large
diameter timber. This problem is particularly acute in the South, where only 14 percent of
the trees are over 40 years old.
2 Chinese Ministry of Forestry.



4
Wood demand
2.5   China is the third largest consumer of forest products in the world, and the demand
for wood products has been expanding with the development of the economy. Current
wood consumption is in the range of 300 million m3 per year, about half of which is
industrial roundwood, one-third is fuelwood, and the remainder is used for rural
construction. In 1992, China imported $1.2 billion worth of wood products, comprising
4.8 million m3 of logs, 1.0 million m3 of lumber, 1.2 million m3 of plywood, and
miscellaneous other wood products (World Bank, 1994). Important non-timber forest
products include significant quantities of furs and skins, fruits, resins, fungi, wild honey,
medicines, aphrodisiacs, oils, sandalwood, bamboo, and rattan ware. During the 1980s,
the consumption of forest resources exceeded the annual increase in growing stock by some
20 million m3 (World Bank, 1994).
Table 3. Age )rofile of China's forests in 1988, (million ha and re&*onal percent)
Regions                 Country   North  Northeast  Northwest  South  Southwest
Young (1-20 years)      47        32%    35%        32%        50%    32%
Middle-age (21-40 years)  40      37%    35%        37%        35%    24%
Near-mature (41-60 years)  11     13%    9%         13%        7%     12%
Mature (61-80 years)     14       12%    16%        12%        5%     19%
Over mature (8 1-1I00 years) 6    6 %    5 %        6 %        2 %    13%
Source: Xu, 1993
Afforestation
2.6   Because of the shortage of forest resources in China, and the growing gap between
the supply and demand for wood products, China has instituted the largest afforestation
program in the world. Between 1984-1988, China planted an average of 3.25 million
hectares per year, with the net increase in forested land amounting to around 0.65 million
hectares per year. In 1989 and 1990, the area of planting exceeded 5 million hectares per
year, with the net increase surpassing 2 million hectares per year. Besides timber and
fuelwood plantation forests, China has also initiated a large-scale protective afforestation
program in North China and has designated some 3 million hectares of open forests,3
mostly on steep slopes, to be closed for forest development. If China continues to increase
its forested area at the rate of the past five years, by the end of the century the area of the
country covered by forests would exceed 15 percent.
2.7   Environmental benefits of afforestation. Non-market goods and services
produced by forests are watershed values and ecological processes. Watershed values
include erosion control, flood reduction, and regulation of stream flows. One of the most
3 Open forests are defined as forests with 30 percent or less of forest canopy.



5
acute economic damages caused by excessive deforestation is reservoir siltation. Ecological
processes include the fixing and cycling of nutrients, soil formation, and the cleansing of
air and water. Global non-market benefits from Chinese forests include carbon -
sequestration and biodiversity habitat.
Fast-growing high-yield (FGHY) programs
2.8   In the past, Chinese plantation forests have had low survival rates and low
productivity largely due to poor management and the use of low quality lands. Since the
mid-1980s a new fast-growing high-yield (FGHY) afforestation program has been initiated
in China. This program relies on (i) planting on good quality sites, (ii) improved genetic
materials and seedling preparation, and (iii) detailed silviculture prescriptions for planting,
tending and harvesting. Tree species are selected which can meet minimum growth rates
under given soil and climatic conditions. Among the most common FGHY species in
China are larch (Larix kaempferi), Chinese fir (Cunninghamia), poplar (Populus
tomentosa), pine (Pinus massoniana, Pinus elliotii, Pinus taeda), eucalyptus (Eucalyptus
spp.), and paulownia (Pawlonia). More than one-quarter of the plantations established in
China since 1985 have been FGHY plantations.
2.9   Barriers to large-scale FGHY forestry development. While there are more than
200 million hectares of land theoretically available in China for forestry development,
there are other competing claims for these lands, including agriculture, animal husbandry,
and urban and industrial development. Secondly, much of the land available for forest
development in China is of poor quality and inappropriate for intensive forestry
plantations. Some types of forestry development, including fuelwood plantations and open
forest management, are typically financially viable only in southern China, whereas, much
of the total land available for forestry development is in the North and Northwest.
Management and production in Chinese forests
2.10 Forests in China are managed by state forest farms, collectives, and individuals.
Although the majority of land is controlled by state forest farms, much of this land is
contracted to collectives and individual households, who provide labor and inputs. The
quality of management by collectives and individuals is generally low, since they have had
limited access to advanced silviculture techniques and since most face financial constraints.
In the 1980s roughly one-quarter of total forested land was transferred from the state to
households as part of the household responsibility system. While land tenure relations
were improved, household forest farms continue to be characterized by low productivity
and minimal adoption of improved silviculture techniques.
2.11  Production forests. China's production forest consists of both natural and man-
made stands. There are about 7 billion cubic meters of mature natural timber stands in
China. The stocking density of timber stands is low due to over-exploitation. Average
growing stock is 70-75 cubic meters per hectare, which is far below the 90-100 cubic
meters per hectare typical of European forests. Natural forest includes conifers (70



6
percent), deciduous species (20 percent), and a mix of the two. Spruce (Picea spp.), larch,
and fir dominate the conifer stands. Common deciduous species include oak (Quercus spp.)
and birch (Betula spp.).
2.12 Plantation forests. Plantations account for approximately 25 percent of China's
forest land. The government encourages plantations to help meet fuelwood, timber, and
pulpwood demand. Plantation growing stock is also low, averaging between 10 and 30
cubic meters per hectare. Preferred species for intensively managed plantations include
larch, poplar, paulownia and pine in the northern regions, and fir, pine, and eucalyptus in
the southern regions. Extensively managed plantation species include birch, spruce, and
oak in the northern regions and oak, pine, and fir in the southern regions.
2.13 Planned harvesting. China's production statistics distinguish four harvesting
categories: (a) in-the-plan, (b) outside-the-plan, (c) fuelwood, and (d) illegal. Planned
harvesting is the responsibility of the state forest bureaus. These bureaus harvest a quota
based on the National Forest Planning Agency (NFPA) production schedule. The NFPA
plans future production with a formula that includes the volume of timber harvested in-the-
plan and outside-the-plan in previous years, estimated fuelwood consumption, and the
change in Gross National Product.
2.14 Outside-the-plan, illegal, and fuelwood harvesting. There is considerable
uncertainty in the volumes of outside-the-plan harvesting, illegal felling, and fuelwood
collection. Government officials acknowledge that outside-the-plan harvesting is
considerably higher than planned production, particularly for fuelwood. A 1989 survey of
rural energy use in China estimated that fuelwood consumption was about 140 mtce, or 50
higher than the officially reported annual fuelwood harvest. Of the total fuelwood, only
about 10 percent is produced by dedicated fuelwood plantations with the remainder coming
from other plantations and from non-forest trees.
2.15  Protection forests. Forests designated for environmental purposes are separated
into two categories in China: (a) protection forest, and (b) forest preserves. Protection
forests cover approximately 8 million hectares (World Resources Institute, 1992), and play
an important role in land reclamation, erosion control, desert stabilization and other
environmental benefits. According to some experts, the survival rate of protection forests
has been less than 50 percent because they are heavily pruned for firewood (Richardson,
1990). China's forest preserves cover another 8 million hectares and provide habitat to
many unique and endangered species. The forest preserves serve four purposes: (a)
conservation, (b) scientific research, (c) production, and (d) tourism.
2.16 Wood processing. Processing occurs at big state mills and small stand-alone mills.
The state mills are part of integrated wood industries that include the state forest bureaus.
Stand-alone mills are usually associated with village forest farms and specialized
households. State mill utilization of stemwood in China is low, averaging only about 70
percent. By contrast, in well-developed milling operations in other countries, 90 percent of
stemwood can be utilized. The difference comes from using the slash and milling wastes to



7
make artificial board, as fuel for mill operation, or for electricity generation. Wastage in
Chinese mills comes from leaving logs exposed in yards and heaping rather than stacking
sawnwood. Few mills in China have drying kilns and there is rarely any secondary
treatment of wood products. Hardwoods and softwoods are often processed with the same
saws, speeds, and settings, leading to poor product quality. Volume recovery is reportedly
as low as 55 percent (Richardson, 1990). Furthennore, most of the mills were not designed
with a view to handling their waste. Since the late 1980s, increasing prices for wood
products has helped to improve the recovery rate of state processing mills. In comparison
to the state sector, stand-alone mills tend to be more efficient, recovering 70-75 percent of
volume (Richardson, 1990). Village based mills are adept at cutting low-grade logs to
service local industries. They are also located in areas where their waste is readily
disposable.
B. ORGANIC CARBON ASSESSMENT
Woody biomass
2.17 Forests are the largest store of organic carbon of in China. The preliminary
assessment of woody biomass presented in Table 4 indicates that 85 percent of above and
below ground woody biomass is held by forests. The above-ground woody biomass
growing stock is 10 to 11 billion tons, and the below-ground growing stock is 5 to 5.5
billion tons.4 Each year this growing stock produces an additional 655 million tons of
biomass.
Table 4.-Woodyr biomass (million metric tons, air dry)
Land use               Total          Cropland  Forests  Rangeland   Other
Area (million ha)      960            146        182     400        231
A/g growing stock /1   10,340-11,005  684-977   9,426    40-80      210-522
B/g growing stock /2   5,280-5,503    342-489   4,713    20-40       105-261
A/g annual growth      555-595        51-74     491      2-4         11-26
B/g annual growth      185-198        17-24      164     1-1         3-9
A/g annual growth leafy  693-743      63-92     614      2-5         14-32
tissue
Notes: 1) A/g = above ground
2) B/g = below ground
Source: Openshaw, 1993
4 This estimate is based on a total forest area of 182 million hectares which is 40 percent higher
than the area used in other estimates.



8
Soil carbon
2.18 Soil organic carbon plays an important role in the assessment of total forest carbon.
Figure 3 indicates soil carbon content is lower in the tropical and subtropical climate of the
South, where decomposition occurs rapidly, than it is in the temperate climate of the
Northeast, where decomposition occurs slowly. Figure 3 presents estimates of the
maximum soil carbon level in the five regions. Accumulation of soil carbon is higher on
undisturbed land, such as mature grassland and forest land, than it is on cropland. Soil
carbon accumulates proportionally to tree growth and reaches equilibrium after 50 years.
Table 5. Average soil carbon to one
Figure 3. Soil carbon levels             meter depth
Region      Area (million  Equilibrium
ha)          carbon level
..........................................................,,,,,,,,,,,,,,,,,,.(to. .a )
Country     950          101
<---)<9Sl      <              ~~~~~~~North  95         ill
t  ,i  341  Northeast  195       341
>n   'I     <r%4      z~~~~~~ 102-111
%  60a72  Northwest  284         60
-'s          0 500 IOM    South      145          102
Southwest  231          72
Source: US Department of Agriculture, Soil
Conservation Service, 1993



9
3. MODELING CARBON SEQUESTRATION
3.1   If recent afforestation efforts in China can be maintained, the area of forested land
would increase from about 13 % in 1990 to 17% by the turn of the century. It was
assumed that China could increase the forested area by about 45 million hectares, or 4.5
million hectares per year during the 1990s. At the same time, planting must also include
the reforestation of areas clearfelled for timber production, which currently amounts to
approximately 2.6 million hectares per year. Therefore, a total of 7 million hectares of
land should be planted each year. Given the magnitude of such tree planting, this was
taken as the high planting scenario. Two other scenarios -- 75% and 50% of the 7 m ha
per year goal -- were also used in the modeling of afforestation and carbon sequestration.
(Table 6)
Table 6. Planting assumptions (million hectares prear)
Scenario  Reforestation of   Incremental   Incremental natural  Total area
clear-cut areas    plantations   regeneration (open
forests)
Low       2.62               1.34           0.89               4.85
Medium    2.62               2.01           1.34               5.97
High      2.62               2.68           1.79               7.09
3.2   Two computerized models have been developed for analyzing the potential for
carbon sequestration in China's forests: (a) a national model that predicts standing volume,
age class structure, and forest carbon balance, and b) plantation models for assessing the
costs and benefits of forestry planting and net costs of carbon sequestration. Both models
are simulated for 30 years, beginning in 1990, with the planted or managed areas based on
the scenarios given in Table 6.
A. NATIONAL MODEL
3.3   The National model has two sinks and five sources of atmospheric carbon. The
sinks are the biomass and the soil. The sources are sawlogs, pulpwood, fuelwood, soil on
clearfelled land, and decaying slash and waste material. A diagram of the model is
provided in Appendix A.
Structure of the model
3.4   The core of the National model is a forest area divided into five age classes. Forest
growth is represented by movement of land through these age classes. Standing volume is
calculated by multiplying the area in each age class by the average stand age and the mean



10
annual increment. Demand for wood products was estimated by taking FAO forestry
resource data (from 1979-1990) and regressing it against population and GDP per capita,
and then extrapolating future years using population and GDP projections from the China
GHG Model (China: Issues and Options in Greenhouse Gas Emissions Control, Summary
Report, 1994). An algorithm based on demand projections determines the area of
timberland harvested each year. The algorithm starts in the oldest age class and works its
way downward, stopping before entering the youngest age class. A percentage of soil
carbon is released immediately after harvest. All harvested land re-enters the youngest age
class after a three year delay. Government planting objectives are represented by equal
increments of new land entering the youngest age class. Soil carbon absorption follows the
S shaped pattern of tree growth. The volume of soil carbon absorbed is equal to the
difference between the initial and equilibrium carbon levels.
Uncertainty and use limitations
3.5    Limited data and uncertainties in the carbon absorption and release process required
testing the model's sensitivity to a range of parameter estimates (Table 7). The most
inconstant parameters are the initial and equilibrium soil carbon levels, and the duration of
soil carbon absorption. Soil carbon absorption has a significant effect on the total amount
of carbon sequestered after 30 years. According to model results, it will by then represent
about one-third of total absorption by the forestry sector. Greater resources should be
dedicated to assessing the soil carbon parameter if the model is to be used for further
analysis.
Table 7. Sensitivit analysis
Parameter                Parameter      Percent change in     Total carbon sequestered
estimnate .......pFarmeter estimate  after. 30yeas(ilo    tons)
...................................................................... . ................. ..............................................................   .......  ................................................................................................
Volume of soil carbon         30             base case                    4.2
absorbed (tons per            40              + 33%                       4.5
hectare)                      50               +66%                       4.9
Duration of soil carbon       50             base case                    4.2
absorption (years)            25              - 50%                       5.5
100             + 100%                      3.3
3.6    Construction of a carbon sequestration model for China requires extensive specific
information on and about the relationship and interactions of the forest system components.
Many factors, such as weather and fire, are not incorporated into the model because they
are exogenous and can not be predicted. Primary information on some endogenous factors,
such as soil carbon absorption, was unavailable. Therefore the model is created largely
from secondary data, and where necessary, best guess estimates are made. Nonetheless,
the model provides an illustration of important and already noticeable trends and tendencies
in Chinese forestry: the imbalance between yields and fellings, the rapid depletion of



11
mature stock, and the risk of not only raw material shortage but also net GHG emissions
from forestry unless a sizable and sustained plantation program is maintained.
3.7   Assumptions. Several assumptions were made to facilitate model construction.
Assumptions that significantly effect results are: (a) harvesting in progressively younger
age classes as the timber supply is exhausted, (b) planting equal areas of new forest each
year, (c) replanting 100 percent of clearfelled forest, and (d) projecting demand from
production rather than consumption. Harvesting is likely to occur in several age classes at a
time. The area planted is prone to change as success rates vary and new technology is
introduced. Replanting is apt to shift with available resources and government incentives.
Basing projections on production understates demand because it does not take into account
unreported and illegal felling or imports.
National model scenarios
3.8   The forest's carbon sequestration performance is largely dependent on forest
management and planting programs. Six scenarios are developed to model the impact of
forest management regimes and planting programs on carbon sequestration.
3.9   Forest management. Replacement of natural stands with man-made and managed
tree stands effects the forest's growth rate. These interventions influence the species,
planting density, and age of the forest. This effect is incorporated in the model by changing
the mean annual increment. Three management scenarios are developed: (a) low growth,
(b) medium growth, and (c) high growth. Table 8 illustrates the progressive change in
mean annual increment under increasingly intensive management.
Table 8. Mean annual increment (cubic meters per Lear) ...... _
Scenario   Age class  Year 0  Year 5   Year    Year I Year      Year    Year
._______  __________  _______  __10  15  20  25     30
Low       Young   . 2.1      3.3      4.4     5.2     5.9     6.5     6.5
growth   Middle-age   3.8      3.8     3.8     3.8     3.8     4.8     5.5
................ ........ .................... ........  ....................................   .. ..............  ,.................... ......... .......................
Medium      Y          21      3.8     4.9     58      64       6.5     6.5
growth   Middle-age   3.8      3.8     3.8     3.8     5.1     6.0     6.5
High      Young      2.1      4.2     5.4     6.2     6.5     6.5      6.5
growth  I Middl   e    38      3.8     3.8     3.8     54      6.3     6.8
3.10  Forest planting. China's ambitious planting program has met with varied success
due to poor conditions and a lack of incentives. Planting survival rates have ranged from
100 percent to less than 50 percent. Three scenarios are modeled: (a) low success (50
percent of goal), (b) medium success (75 percent of goal), and (c) high success (100
percent of goal). Table 9 provides a summary of the area planted under each alternative.



12
Table 9. Cumulative area plnted under three scenarios (million hectares)
Survival rate          1990   2000    2010  2020
Low success (50%)        0    22     43    65
Medium success (75%)     0     32    65    97
High success (100%)      0    43     86    130
3.11  Baseline parameters. A set of baseline parameters are chosen to emulate existing
conditions in China's forests. Unless otherwise stated, these parameters are used in all
simulations. These are: (a) "low growth," (b) "medium success", and (c) 30 tons of soil
carbon is absorbed per hectare over the course of 50 years. Under these conditions 4.2
billion tons of carbon is sequestered after 30 years.
Results of the national model
3.12 The combined results from the management and planting scenarios are presented in
Table 10. The total volume of carbon sequestered after 30 years ranges from 2.2 billion
tons to 7 billion tons. The greatest amount of carbon is sequestered under conditions of
high growth and high planting success, and the least amount of carbon is sequestered under
low growth and low success.
Table 10. Range of estimates for total        on (mlion tons)
Scenarios                         2000    2010    2020
...................................................................................................................................I...............................
Low growth & low success           861    1,295  2,243
Medium growth & medium success    1,277   2,388  4,653
Hi !h_growth_&h. hsuccess         1,723   3,395   7,014
3.13 The volume of stemwood harvested and the standing stock of timber will increase in
the next decade. By 2020, 550 million cubic meters of stemwood will be harvested per
year, of which 50 percent will be used for sawlogs, 30 percent for pulpwood, and 20
percent for fuelwood (Table 11).
Table 11. Stemwood harvested-b_ end product (million cubic meters)
Product      1990   2000    2010   2020
Total         209    273    389    550
Sawlogs      125    160    216    268
Pulpwood     16     30     72     161
Fuelwood     68     83     101    121
3.14  By 2020, the planting and reforestation program will more than double China's
stemwood from 12 to 28 billion cubic meters (Table 12). Harvesting and replanting
combine to change the age structure of the forest. In 1990, 38 percent of timber reserves
consist of mature and over-mature stands. After 30 years, only 6 percent of reserves are



13
mature and over-mature. The dramatic decrease in older age tree stands foreshadows a
shortage of large diameter timber and a loss of old growth habitat.
Table 12. Stann stock by age class (million cubic meters)
Age class      1990    2000    2010    2020
Total         11,960  16,140  20,490   27,740
Young          970    2,834    4,630   5,948
Middle-age    4,345   5,151    6,359   11,130
Near-mature   2,127   4,573    6,771   8,987
Mature        3,503   3,425    2,623   1,607
Over-mature   1,015    156      105     67
3.15 Sinks and sources. The annual atmospheric carbon uptake and release by the
model's two sinks and five sources is presented in Table 13. Biomass is the most important
sink in determining the carbon balance of China's forests, accounting for over 85 percent
of sequestration. Soil becomes an increasingly important carbon sink. Slash decomposition
and soil carbon release are the largest sources of carbon. By 2020 sawlogs, pulpwood, and
fuelwood account for almost equal proportions of emissions, with the proportion of sawlog
carbon release increasing beyond the 30 year simulation horizon.
Table 13. Annual carbon balance (million tons)
Carbon sinks and sources  1990  2000  2010   2020
Sinks                    148   238    281    429
Biomass                  148   209    204    305
Soil carbon               0     29     77    124
Sources                  30    117    182    266
Sawlogs                   0     6      19     32
Pulpwood                  1     5      11     26
Fuelwood                 19     23     28     33
Soil on harvested land    0     32     43     58
Biomass                  10     51     81    117



14
B. FORESTRY PLANTATION MODELS:
FINANCIAL AND ECONOMIC ANALYSIS
3.16 A number of studies of the costs of carbon sequestration through tree planting and
modified forestry practices have reinforced the perception that the net costs of carbon
sequestration by the forestry sector are positive.5 Such studies have generally calculated
the cost of carbon sequestration as the total costs of tree planting -- purchasing or renting
land, establishing, and maintaining trees -- divided by total carbon sequestration (in
biomass and soil). What have not generally been considered are the direct economic
benefits from tree planting; i.e., revenues from the sale of timber products (sawlogs,
pulpwood, fuelwood), social benefits from reducing deforestation, and environmental
benefits such as erosion control and habitat protection. While the regular thinning and
harvesting of timber plantations can result in lower overall carbon sequestration than if the
forests are left untouched, the financial benefits from use of forestry products are crucial to
the success of afforestation programs, particularly in developing countries.
3.17  This analysis considers the net cost of carbon sequestration from tree planting and
modified forestry practices in China, whereby the private financial benefits are subtracted
from the costs. Financial tables, which include the costs of establishment, maintenance,
harvesting, and reforestation, and the benefits from sales of sawlogs, pulpwood, and
fuelwood, have been prepared for intensive, extensive, and fuelwood plantations, and for
the improved management of open forests.6 To calculate the cost-effectiveness of carbon
sequestration, the net present value of each respective project is divided by the discounted
carbon sequestered in living biomass and in the soil.
Types of plantations
3.18 For the financial analysis of various plantation programs, the scenarios of new
"incremental plantations" (Table 6) were subdivided into three categories: (a) intensively
managed plantations, (b) extensively managed plantations, and (c) fuelwood plantations.
In 1990, 3.67 million hectares were closed for natural regeneration; this is referred to here
as open forest management.
3.19 Intensively managed plantations refer to the planting of fast-growing species, such
as Chinese fir, masson pine, larch, paulownia, poplar, and eucalyptus. Such plantations
would be established with the objective of maximizing biological production and financial
5 See for example, Moulton, R.J. and K.R. Richards, Costs of Sequestering Carbon Through
Tree Planting and Forest Management in the United States, US Department of Agriculture Forest
Service, December 1990.
6 Financial data for the intensive plantations is taken from the National Afforestation Project
(NAP), which has received financial and technical assistance from the World Bank.



15
returns and would be grown on the most productive forestry lands and have the highest
growth rates and the highest costs.
3.20 Extensively managed plantations refer to naturally occurring species, such as oak,
birch, spruce, fir and various pine species. These plantations would be managed as
commercial forests but with much longer rotations and much lower costs than intensive
plantations. The MAI is assumed to be much lower than for the intensive plantations
because of poorer land quality and fewer inputs.
3.21 Fuelwood plantations are dedicated, fast-growing regenerable species, such as
locust and eucalyptus, grown with the intention of maximizing biomass production and
financial returns.. It should be noted that some fuelwood is produced from thinnings of
other plantations and on open forests. The area of fuelwood plantations (medium scenario)
is taken from the 1991-95 five-year plan target (2.6 million hectares, or 520,000 ha/yr),
while the proportion of intensive and extensive plantations is based on the current situation
(40/60) as reflected in government forestry statistics.
3.22 Open forest management is the management of open forests to improve growth rates
and protection against illegal felling or other activities which damage trees or soil. Some
timber and fuelwood would be available from these lands through selective thinning and
removal of dead or dying trees.
Table 14. Plantation scenarios ('000 hectares per year)
Scenario  Intensively   Extensively   Fuelwood     Total
managed       managed      plantations  incremental
plantations   plantations                plantations
Low       280           710           350          1,340
Medium    420           1,070         520          2,010
High      538           1,360         780          2,680
Source: Joint study team, China GHG Study. See Table 6 for total planting.
Results of the financial analysis
3.23 Intensively managed plantations. Table 15 shows that all but one of the intensive
timber plantations have rates of return exceeding 12%, and thus provide carbon
sequestration at negative cost. Based on the most recent (1993) prices for timber products,
and even the substantially lower prices prevailing in 1990, 10 of the 12 intensive plantation



16
species yielded internal rates of return (IRR) above the target rate (12 percent).7 The
World Bank has recently appraised similar FGHY plantations as part of a forestry project
in 16 provinces in China, and has estimated the average rate of return for such plantations
at 18.1 percent.8 One of the reasons for the relatively high rates of return for all of the
intensive plantations is that real wages are not assumed to rise very much due to the
continued existence of large amounts of rural surplus labor.
Table 15. Intensive  antations: financial analysis and sequestration costs
Species/MAI                      NPV (12%) IRR     $/t C02
1   Larch/14                         801        16.3%  -1.76
2   White Poplar/11                  711        24.8%  -6.56
3   Yunnan Pine/16                   4455       23.5%  -5.72
4   Masson Pine/14                   6720       22.0%  -4.88
5   Chinese Fir/16                   424        25.2%  -10.74
6   Chinese Fir/18                   7361       26.2%  -11.29
7   Eucalyptus/20                    230        45.9%  -8.95
8   Larch/10                         4          12.2%  -0.07
9   Table Pine/6                    -430        1.1%   1.61
10  Italian Poplar/22                2340       45.9%  -21.96
11  Paulownia/20                     96         36.6% -11.81
12  White Poplar/10                  548        23.5%  -6.38
3.24 Extensively managed plantations. While not nearly as cost-effective as intensive
plantations, extensively managed plantations as a whole, and many individual species, also
yield positive economic returns. Table 16 shows that only three of the ten extensive
plantation models yielded rates of return above 12 percent. The lower yields are offset by
lower costs, resulting in an overall rate of return of more than 12%. The models that
yielded positive net present values were Chinese fir, masson pine, and Yunnan pine
growing in South and Southwest China.
7 One of the reasons for the relatively high rates of return is that real labor costs are
assumed to remain low due to future macroeconomic projections carried out under the
China Greenhouse Gas Study showing continued surplus labor in China well into the 21st
century.
8 The World Bank, Staff Appraisal Report, China: Forest Resource Development and Protection
Project, May 1994.



17
Table 16. Extensive plantations: financial analysis and sequestration costs
Species/MAI                 NPV (12%)     IRR      $/t
1   Oak/7                         -797        4.1%    0.66
2   Birch/l l                      -478       8.4%     0.29
3   Oak/8                         -937        5.6%    0.62
4   Yunnan Pine/12                1000       14.9%    -0.59
5   Masson Pine/14                5481       23.1%    -3.89
6   Chinese Fir/14                9241       26.4%    -8.95
7   Table Pine/3                  -1395      negative  1.98
8   Birch/5                        -99        1.7%    0.95
9   Spruce/5                      -1306      negative  1.54
10  Oak/5                        -1134      negative  1.10
3.25 Fuelwood plantations. The Chinese government has promoted fuelwood
plantations in order to reduce the adverse impact of fuelwood collection on natural forests
and timber plantations. Nearly two-thirds of fuelwood production would come from
fuelwood plantations, and one-third from thinnings and removal of dead or dying wood
from other plantations. In contrast to other plantations, the production of fuelwood is not
financially viable at official prices prevailing on current state-owned fuelwood plantations
(30-50 Y/t). However, the true market price or opportunity cost of fuelwood is probably
double this amount based on the cost of collection or compared with other fuels. At 100
Y/t, which is roughly the fuel equivalent price of coal in the regions reviewed minus the
difference in fuel combustion efficiency, fuelwood production exceeds the 12 percent rate
of return target in South and Southwest China.
Table 17. Fuelwood production from fuelwood and
other plantations, high scenario (mt air dry wood)
Type of Plantation        Thousand       Offtake in      Percent
hectares      year 2020
planted/yr
Fuelwood                     780            176          64%
Intensively managed          535             34          12%
Extensively managed          1365            27          10%
Open forest management       1790            40          14%
Total                       4470            277         100%



18
3.26 If all of the fuelwood produced under the high scenario could be substituted for
coal, 112 mt of carbon could be reduced, which is equivalent to 16% of China's 1990 CO2
emissions.
3.27 Open forest management. It is possible to improve the growth rates of existing
open forests by applying better silviculture techniques and by protecting the forests against
destructive felling and encroachment. Some timber and fuelwood would be available from
these lands through selective thinning and removal of dead or dying trees. Based on the
financial analysis, improved open forest management is typically commercially viable only
in South China.
3.28   Sensitivity analysis. The most important variable influencing the rate of return of
the plantation projects is the price of forest products (sawlogs, smallwood, pulpwood,
fuelwood). The most recent price information for fast-growing species in intensive
plantations, collected as part of the National Afforestation Project, has been used in the
plantation models. Over the past five years, timber prices throughout the country have
increased substantially as the government has eased price controls on "in-plan" timber
harvests and as a growing percentage of "above-plan" timber harvests have been sold at
market prices. In order to reflect the move to market prices for forestry products in China,
the most recent (1993) prices for timber products have been used. Even at the substantially
lower prices prevailing in 1990, most intensive plantation species have IRRs above the
target rate of return (12%). The exceptions are the species used primarily for pulp --
eucalyptus, larch, and table pine -- since pulp prices have not increased nearly as rapidly in
China as prices for sawlogs and smallwood.
Table 18. Carbon sequestration by plantations, 1990-2020 (million tons C)
Type of Plantation                        Scenario
Low           Medium        High
Intensively managed plantations    419            630         803
Extensively managed plantations   1,181          1,777       2,266
Fuelwood plantations               141            208         312
Open forest management             630            949         1,267
TOTAL                           2,370           3,564    4,648



19
3.29 The policy implications of the net versus gross cost analyses are significant. For
instance, Xu (1993)9 calculated the gross costs of carbon sequestration for China using the
Moulton and Richards methodology and concluded that the least-cost measure was
management of open forests in Southwest China, where the MAI was high and the costs of
labor and other inputs were low. By contrast, under the net cost approach, open forest
management does not meet the target rate of return (12%) in most regions of the country
and in no region is open forest management as attractive in financial terms as intensive
plantations.
9 Xu, Deying, Economic Analysis and Forestry Options for Mitigating Global Climate Change: A
Chinese Case Study, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China,
1993.



20
4. DISCUSSION AND CONCLUSIONS
4.1    By instituting a massive afforestation program, China could reduce net GHG
emissions by about 10 percent in 2020 compared to the Baseline GHG Scenario. 10 To
achieve this level of carbon sequestration, China would have to increase forested land by 4-
5 million hectares per year between now and the year 2020, extend the use of fast-
growing, high-yield plantations, and broadly disseminate advanced silviculture techniques.
This level of planting would increase the percentage of forested land in China from about
13 percent in 1990 to more than 20 percent by the year 2020. Although fuelwood
plantations do not sequester much carbon on a net basis, they can contribute to GHG
reduction by producing biomass, a substitute for fossil fuels. Utilizing wood and forest
residues grown on a sustainable basis to generate power is an effective way to reduce
GHGs by both replacing coal and increasing carbon sequestered on forest stands.
4.2    A net cost analysis of carbon sequestration from forestry projects found that four
types of plantations in China are financially and economically attractive on a life-cycle
basis even if GHG benefits are not considered. By contrast, gross cost analyses done in the
US and elsewhere conclude that least-cost sequestration forestry projects are ones that
minimize total costs, even when the forestry projects in question are not commercial. 11
Specifically, the following afforestation and forestry management practices have been
identified as having the greatest potential for cost-effective reduction in net carbon
emissions in China: (a) the planting of fast-growing, high-yield (FGHY) timber
plantations on good quality land, (b) the establishment of certain multiple-use protection
forests, (c) the planting of high-yield fuelwood plantations on good sites, particularly in
southern China, and (d) improved management and supplemental planting of open forests,
also predominantly in southern China. Although fuelwood plantations themselves do not
provide significant carbon sequestration, they can significantly reduce carbon emissions by
limiting destructive cutting of natural forests and by substituting fuelwood for coal and
other fossil fuels, either in direct use or for power generation.
4.3    Despite the potential within China's forestry sector for carbon sequestration, the
modeling also points out the growing difficulties that China will have in meeting the
10 See Summary Report, China: Issues and Options in Greenhouse Gas Emissions Control,
December 1994, Chapter 2, for a description of the Baseline GHG Scenario.
11 For instance, Xu calculated the gross costs of carbon sequestration for China using the
Moulton and Richards methodology and concluded that the least-cost measure was management of
open forests in Southwest China, where the mean annual increment was high and the costs of labor
and other inputs were low. By contrast, under the net cost approach, open forest management does
not meet the target rate of return (12%) in most regions of the country and in no region is open
forest management as attractive in financial terms as intensive plantations. Xu, Deying, Economic
Analysis and Forestry Options for Mitigating Global Climate Change: A Chinese Case Study,
Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China, 1993.



21
demand for mature timber over the coming decade. Mature forests are being diminished at
a rapid rate in China and despite the massive afforestation efforts that have been underway
in the country, by the turn of the century there will be insufficient mature trees available
from the afforested areas. Measures to reduce the impending gap between the supply and
demand for mature timber include the liberalization of imports, increased efficiency of
harvesting and milling, and the adoption of technologies to use smaller diameter timber for
various wood products such as plywood and particle board.
4.4   The priority afforestation programs for carbon sequestration are different than the
priorities for other environmental reasons such as erosion control, watershed management,
or biological diversity. The objective of carbon sequestration is to amass the most carbon
in standing biomass and in the soil as possible at the lowest cost. Therefore, afforestation
and forestry management practices that have the potential for maximizing carbon
sequestration at the lowest net cost should be the focus of government support.
4.5   Given the limited public resources available in China to support forestry
development and the growing demand for forest products in the country, China should
encourage private investment (both domestic and foreign) in commercial timber and
fuelwood forestry projects. Policy measures that can accelerate forestry development in
China include: (a) improvements in capital markets, (b) further price reform, and (c)
clarification of land-tenure rights. Improvements in capital markets, including equal access
to credit, is needed to allow individuals and firms to borrow for long-term forestry
projects. The reform of timber prices in the past several years has helped to encourage
private sector investment; further reform of logs and wood product prices and the removal
of international trade barriers would improve allocation of wood products in China. Land
rights are another important aspect of forestry development; national and local
governments in China need to provide legal assurances to individuals or groups that they
can secure the gains of forestry development in the distant future or will be able to transfer
those rights to others.
4.6    The government can promote more cost-effective development and management of
priority afforestation projects through technology transfer, demonstration, and technical
assistance. Among the areas of greatest significance are the improvement of (a) growing
stock, including genetic improvement, seed supply, and plant propagation systems; (b) site
management, including site identification and classification, fertilization, and weed control;
and (c) stand management, including tree spacing, thinning and pruning. Human resource
capacity building is needed in the areas of silviculture and nursery management, forestry
research and extension, market analysis, and afforestation model design.



22
5. REFERENCES
China: Issues and Options in Greenhouse Gas Emissions Control, Summary Report.
Report of a Joint Study Team from the National Enviromnental Protection Agency of
China, the State Planning Commission of China, the World Bank, and UNDP. December
1994.
Dale, V.A., R.A. Houghton, and C.A.S. Hall. 1991. "Estimating the Effects of Land Use
Change on Global Atmospheric C02 Concentrations." Canadian Journal of Forest
Research 21(1):87-90.
Dixon, R. K., P. E. Schroeder, and J. K. Winjum, (eds.). 1991. Assessment of Promising
Forest Management Practices and Technologies for Enhancing the Conservation and
Sequestration of Atmospheric Carbon and Their Costs and the Site Level. EPA/600/3-
91/067. Washington: US Environmental Protection Agency, Office of Research and
Development.
Openshaw, K. 1992. China: Organic Carbon Assessment and Sequestration Potential.
Draft report. The World Bank, Washington, D.C.
Repetto, R., and M. Gills, (eds.). 1988. Public Policies and the Misuse of Forest
Resources. Press Syndicate of the University of Cambridge, New York, New York.
Richardson, S.D. 1990. Forests and Forestry in China. Island Press, Washington, D.C.
Schlesinger, W. H., and R. H. Waring. 1985. Forest Ecosystems: Concepts and
Management. Academic Press, Inc., San Diego, California.
Sharma, N.P (ed.). 1992. Managing the World's Forests. Kendall/Hunt Publishing
Company, Dubuque, Iowa.
Tans, P.P., I.Y. Fung, and T. Takahashi. 1990. "Observational Constraints on the Global
C02 Budget." Science 247: 1431-1438.
The World Bank. 1994. Staff Appraisal Report. China: Forest Resource Development and
Protection Project, Report No. 12762-CHA. Washington, D.C.
The World Bank. 1990. Staff Appraisal Report. China National Afforestation Project,
Report No. 8487-CHA. Washington, D.C.
The World Bank. 1992. China Environmental Strategy Paper. Report No. 9669-CHA.
Washington, D.C.



23
The World Bank/UNDP/Bilateral Aid Energy Sector Management Assistance Program.
1989. Activity Completion Report: County-level Rural Energy Assessments, A Joint Study
of ESMAP and Chinese Experts. Report No. 101/89. Washington, D.C.
The World Resources Institute. 1992. World Resources 1992-1993: A Guide to the Global
Environment. Oxford University Press, New York, New York.
Xu Deying. 1993, Economic Analysis and Forestry Options for Mitigating Global Climate
Change: A Chinese Case Study, Research Institute of Forestry, Beijing, China.
Xu, Deying. 1993a. China's Forests, C02 Emissions and Related Strategies. Draft report.
The World Bank, Washington. D.C.



24
6. APPENDIX A: NATIONAL MODEL
FOREST SYSTEM
SINKS OF                                                   SOURCES OF
ATMOSHERIC CARBON      | NEW LAND                           ATMOSPHERIC CARBON
ATMOSHERIC CARBONRS 
l1l 2l0                                 SAWLOGS   l
SOIL               2140 YEARS      -     >               | PULP&PAPER]
BIOMASS1-6 YEAR            .ON*                       FUELWOOD
BIOMASS               J                    |   FCELLETIONR l
| 61-80 YEARS                            FELUT
|  s   l                     | ~~~~~~DECAY&



7. APPENDIX B: PLANTATION MODEL RESULTS
Appendix Table B.1 Intensively Managed Plantations: summary sheet for all species;
calculation of accumulated carbon in woody biomass and soil;
calculation of net (economic) cost per ton of carbon (C02 basis)
sequestered.
Appendix Table B.2 Extensively Managed Plantations: summary sheet for all species;
calculation of accumulated carbon in woody biomass and soil;
calculation of net (economic) cost per ton of carbon (C02 basis)
sequestered.
Appendix Table B.3   Fuelwood Plantations: summary sheet for all species; calculation of
accumulated carbon in woody biomass and soil; calculation of net
(economic) cost per ton of carbon (C02 basis) sequestered;
summary table by species and region of NPV, IRR $/t C02, MAI
assumptions, and carbon sequestered.
Appendix Table B.4   Open Forest Management: summary sheet for all species;
calculation of accumulated carbon in woody biomass and soil;
calculation of net (economic) cost per ton of carbon (C02 basis)
sequestered; summary table by species and region of NPV, IRR $/t
C02, MAI assumptions, and carbon sequestered.






Appendix Table B.1 Intensively Managed Plantations
CHINA GREENHOUSE GAS STUDY                PLANTATION MODULE              INTENSIVELY MANAGED PLANTATIONS
SUMMARY SHEET, par I                                          AREA DISTURBUTON PER REGION AND SPECIES
(PROPORTIONS)
TOTAL AREA PLANTED, '000 HA PER YEAR                                       REGION:        1          2         3          4         5
SCENARIO 1             990.000                                           PROPORTION              0.1848864  0.2426109  0.2986429  0.1154451  0.1584146       1
SCENARIO 2             1490.000  CHOOSE| 1900.000|            SPECIES                 ROT/MAI
SCENARIO 3             1900.000                             I LARCH                   20/14          0.802                                           0.1482789
2 WHITE POPLAR            15/11          0.198                                           0.0366075
MANAGEMENT, % OF AREA                  3 YUNNAN PINE             20/16                    0.726                                  0.1761355
INTENSIVE            EXTENSIVE                   4 MASSON PINE             20/14                     0.189     0.608                       0.2274284
REGION I       24.68                75.32                   5 CHINESE FIR             20/16                    0.052                                 0.0126158
REGION 2       26.12                73.88                   6 CHINESE FIR             20/18                               0.372                      0.1110952
REGION 3       43.72                56.28                   7 EUCALYPTUS              7/20                     0.002       0.02                      0.0064581
REGION 4       26.56                73.44                   8 LARCH                   20/10                                          0.0S      0.231  0.042366
REGION 5        8.16                91.84                   9 P. TABLAEFORMIS         30/6                                          0.576      0.282  0.1111693
10 ITALIAN POPLAR (V)      10/22                                         0.351            0.0405212
11 PAULOWNIA               10/20                                         0.022            0.0025398
12 WHITE POPLAR            15/10                    0.031                          0.487  0.0846689
1.000     1.000      1.000     0.999      1.0L0
1.000
NATIONAL SUMMARY
YEAR                                                        I          2           3          4         5          6         7          8         9         10         11        12        13         14        15
YEARS (1990-2020)                                        1990          1           2          3         4          5         6          7         8          9      2000          1         2          3         4
LOGS, '020 CU M                                             0         0            0          0         0          0       455        455       512       2168      2168       2278      2278       3159      5396
SMALLWOOD, '000CU M                                         0         0            0          0         0          0         0          0        196      1838       1838      2004      2004       2857      4157
FUELWOOD, '0D0 TON                                          0         0            0          0         0          0        36         36        177       719       719        832       832       1373       1890
CARBON STORED IN WOODY BIOMASS, MILLION TONS                3          8           16        27        41         57        76         97       121        146        173       203       236        270       304
EXPENSES, 'OD0 000 YUAN                                   735        791         843        884       904        923       974        961       1044      1326       1375      1421       1440      1613       1817
REVENUES - EXPENSES                                       -735      -791         -843      -884       -904      -923       -868      -888       -789        89        40        164       144        547      2019
REVENUES                                                    0         0            0          0         0          0        106       106       247       1407       1407      1576       1576      2226      3975
ACCUMULATED CARBON IN SOIL, MILLION TONS                    0         0             1         2         4          5         8         10        13         16        20         23        27         32        37
TOTAL CARBON IN WOODY BIOMASS AND SOIL (MT)                 3          9           17        29        44         62         83       107        134       162        193       226        263       301        341
NET COST/TON C02 REDUCED                       -8.84     Y/ton
1990 shadow exchange raw (Y/S)     5.5      -1.61      S/ton



Appendix Table B.1 Intensively Managed Plantations
CHINA GREENHOUSE GAS STUDY                   PLANTATION MODULE                INTENSIVELY MANAGED PLANTATIONS
SUMMARY SHEET, part2
AREA DISTPJBUItON PER REGIONAND SPECIES
IN 000 HA ACCORDING TO THE SELECTED SCENARIO
REGION:         I          2           3          4          5         TOTAL                         REGION      INCREMENT
PER SP.
SPECIES
I LARCH                              69.530956          0      0.000       0.000      0.000     69.531 B                               1       1162
2 WHITE POPLAR                       17.165997          0       0.000      0.000      0.000      17.166 C                              2       1822
3 YUNNAN PINE                                0  87.412532       00.0       0000       0.000     87.413 D                               3       3872
4 MASSON PINE                                0  22.756155     150.831      0.000      0.000     173.587 E                              4        705
5 CHINESE FIR                                0  6.2609527       0.000      0.000      0.000      6.261 F                               5        218
6 CHINESE FIR                                0          0      92.285      0.000      0.000     92.285 G
7 EUCALYPTUS                                 0  0.2408059       4.962      0.000      0.000      5.202 H
8 LARCH                                      0          0      0.000       2.913      5.673      8.586 1
9 P. TABLAEFORMIS                            0          0       0.000     33.557      6.926     40.483 J
10 ITALIAN POPLAR (V)                         0          0      0.000      20.449      0.000     20.449 K
I PAULOWNIA                                  0      0.000      0.000       1.282      0.000      1.282    GRAND TOTAL,
12 WHITE POPLAR                           0.000      3.732      0.000       0.000     11.961     15.694    INTENSIVELY MANAGED
PLANTATIONS
TOTAL PER REGION                      86.697    120.403    248.077     58.200      24.561                          537.937
TOTAL        NPV        IRR
16         17         18          19         20         21         22         23          24         25         26         27          28         29         30              (CO2 basis)
5          6          7           8          9       2010          11         12         13         14          15         16         17         18          19       2020
5396       5396       5396        5396      65642      66097      66097       66097      66097      66097      66097       66097      66552      66610      73964       73964     849868
4157       4157       4157        4157      20006      20006      20006       20006      20D06      20006      20006       20006      20006      20203      22901       22901     277584
1890       1890       1890        1890      12550      12586      12586       12586      12586      12586      12586       12586      12622      12769      14054       14054     168324
341        381        423        468         471        474        482         491        504        519        536         556        578        603        626         650       2385       2129
1951       1969       1987       2005        7989       8536       8460       8614        8646       8662       8678       8694        8740       8604       9532       9651      129769      14099
1965       1947       1930        1913      36530      36001      35964      35929       35896      35880      35864      35849       35833      35828      38503      38381     439590       23259      23.3%
3484       3484       3484        3484      44086      44682      44682      44682       44682      44682      44682      44682       44788      44929      48372      48372      569884      37239
42         47         53          59         65         72         79          86         93        101        109         117        126        134         144        153        561        501
383        428        476         527        536        546        560         577        597        620        645         673        704        738        769         803       2945       2630



Appendix Table B.2 Extensively Managed Plantations
CHINA GREENHOUSE GAS STUDY               PLANTATION MODULE              EXTENSIVELY MANAGED PLANTATIONS
SUMMARY SHEET                                                AREA DISnIBUTION PER REGION AND SPECIES
(PROPORTIONS)
TOTAL AREA PLANTED, '000 HA PER YEAR                                    REGION:        1         2         3         4          5
SCENARIO I             990.00                                          PROPORTION           0.1848864  0.2426109  0.2986429 0.1154451  0.15U4146       1
SCENARIO 2            1490.000   CHOOSE    1900.000          SPECIES              ROT/MAI
SCENARIO 3            1900.000                             1 OAK                  40n            0.500                                           0.0924432
2 BIRCH                40/11          0.500                                           0.0924432
MANAGEMENT, % OF AREA                  3 OAK                  40/8                     0.514                                 0.124702
INTENSIV EXTENSIVE                     4 YUNNAN PINE          30/12                    0.486                                0.1179089
REGION I NE              24.68     75.32                   5 MASSON PINE          25/14                                0.5                       0.1493215
REGION2 S                26.12     73.88                   6 CHINESEFIR           25/14                                0.5                       0.1493215
REGION 3 SW              43.72     56.28                   7 P. TABLAEFORMIS      40/3                                            0.9            0.1039006
REGION 4 N               26.56     73.44                   8 BIRCH                40/5                                            0.1            0.0115445
REGION5 NW                8.16     91.U4                   9 SPRUCE               60/5                                                      0.5  0.0792073
10 OAK                  60/5                                                      0.5  0.0792073
1.000     1.000      1.000     1.000     1.000
1.000
NATIONAL SUMMARY
YEAR      (t)                                              1         2          3         4          5         6         7         8          9        10        I1         12        13        14         15
YEARS (19902020)                                         1990         1         2         3          4         5         6         7          8         9      2000          I         2         3          4
LOGS, '0S0 CU M                                            0         0          0         0         0          0         0         0          0         0         0          0         0         0       7577
SMALLWOOD, 'ODO CU M                                       0         0          0         0          0         0         0         0          0         0         0          0         0         0       6730
FUELWOOD, '0S0 TON                                         0         0          0         0         0          0         0         0          0         0         0          0         0         0       1257
CARBON STORED IN WOODY BIOMASS, MILLION TONS               5         15        30        50         75       105       141       181        226       276       331        391       457       527        594
EXPENSES, 'OO000OYUAN                                    1265      1371      1471       1559      1608      1657      1707       1755      1799      1842       1885      1928      1972      2015       2803
REVENUES-EXPENSES                                       -1265     -1371     -1471      -1559     -1608     -1657      -1707     -1755     -1799     -1842      -1885     -1928     -1972      -2015      5090
REVENUES                                                   0         0          0         0          0         0         0         0          0         0         0          0         0         0       7892
ACCUMULATED CARBON IN SOIL, MILLION TONS                   0          1         3         6         10        15        21        28         35        44        53         64        75        87        100
TOTAL CARBON IN WOODY BIOMASS AND SOIL (MT)                5         16        33        56         85       120       161       208        261       320       385        455       532       614        694
NET COST/TON C02 REDUCED                      -1.29     Y/ton
1990 shadow exchange rae (Y/S)     5.5     -0.23      S/ton



Appendix Table B.2 Extensively Managed Plantations
CHINA GREENHOUSE GAS STUDY                   PLANTATION MODULE                 EXTENSIVELY MANAGED PLANTATIONS
AREA DIS7RTB UTON PER REGION AND SPECIES
IN 000 HA ACCORDING TO THE SELECTED SCENARIO
REGION:         1          2           3          4          5      TOTAL
PER SP.
SPECIES                                                                                                                     REGION     INCREMENT
I OAK                                132.29365          0      0.000       0.000      0.000     132.294 B                              1       2381
2 BIRCH                              132.29365          0       0.000      0.000      0.000     132.294 C                              2       3366
3 OAK                                        0   174.00419      0.000      0.000      0.000     174.004 D                              3       4471
4 YUNNAN PINE                                0   164.52536      0.000      0.000      0.000     164.525 E                              4        515
5 MASSON PINE                                0          0     159.672      0.000      0.000     159.672 F                              5        1382
6 CHINESE FIR                                0          0     159.672      0.000      0.000     159.672 G
7 P. TABLAEFORMIS                            0          0       0.000    144.979      0.000     144.979 H
8 BIRCH                                      0          0       0.000     16.109      0.000      16.109 1
9 SPRUCE                                     0          0       0.000      0.000     138.214    138.214 J
10 OAK                                        0          0       0.000      0.000    138.214     138.214 K
TOTAL
EXTENSIVELY MANAGED
PLANTATIONS
TOTAL PER REGION                     264.587    338.530    319.345     161.087    276.427                          1359.976
TOTAL        NPV        IRR
16         17          18         19         20         21         22          23         24         25         26          27         28         29         30          31  (CO2basis)  (at 12%)
5          6           7          8          9       2010          11         12         13         14          15         16         17          18         19       2020
7577       7577        7577       7577      26078      26078      26078       26078      26078      59509      59509       59509      59509      59509       86107      86107     638035
6730       6730       6730        6730      13097      13097       13097      13097      13097      22139      22139       22139      22139      22139      28753       28753     267332
1257       1257       1257        1257       4015       4015       4015        4015       4015      12367      12367       12367      12367      12367       15945      15945     120086
666        743         826        913        986       1064        1147       1236       1329       1394        1465       1541       1621       1707        1775       1848       6775       6049
2846       2889       2932        2975       4498       4543       4580        4616       4652       8647       8993        9055       9117       9166       11525      11722     129392       17536
5047       5003       4960        4917      10834      10788       10752      10716      10680      37399      37053       36991      36929      36879      50803       50606     341613       9576       16.1%
7892       7892       7892        7892      15332      15332       15332      15332      15332      46046      46046       46046      46046      46046       62328      62328     471005      27112
114        129        145         161        178        196        215         234        255        276        298        320         344        368        393         418       1533       1368
781        872         970       1074       1164       1260        1362       1470       1584        1670       1763       1861       1965       2075        2167       2266       8308       7418



APPENDIX TABLE B.3 FUELWOOD PLANTATIONS
CHINA GREENHOUSE GAS STUDY                PLANTATION MODULE               FUELWOOD     PLANTATIONS
SUMMARY SHEET, par I                                                                            AREA DISTRIBUTION PER REGION AND SPECIES
(PROPORTIONS)
TOTAL AREA PLANTED, '000 HA PER YEAR                                       REGION:        1         2          3          4         5
SCENARIO I              350.000                                           PROPORTIONS            0.1848864  0.2426109  0.2986429  0.1154451  0.1584146        1
SCENARIO 2              520.000   CHOOSE     780.000        reg. SPECIES             ROT/MAI
SCENARIO 3              780.000                               I LOCUST               3/8,5 TIHA      1.000                                            0.1848864
LESPEDEZA
2 ALNUS                 3/12,5                    1.000                                  0.2426109
CASSIA
3 - CENTE   OAK                 3/12,5                                0.56                         0.16724
COEROSPONDIAS
3-SOUTH    EUCALYPTUS           3/22,5                                0.44                       0.1314029
ACACIA
4 LOCUST                2/ 8,5                                             1             0.1154451
AMORPHA
5 ELAEAGNUS             3/6,5                                                         1 0.1584146
HIPPOPHAE
1.000      1.000     1.000      1.000      1.000
1.000
Cumulative Area Planted ('000 ha)                          780       1560       2340       3120      3900       4680       5460      6240       7020       7800      8580       9360      10140      10920     11700
YEAR       (t)                                                1         2          3         4          5          6         7          8          9         10         11        12         13         14        15
YEAR (199D-2020)                                           1990         1          2         3          4          5         6          7          8          9      2000          1          2         3          4
LOGS, '000 CU M                                              0          0          0         0          0          0         0          0          0         0          0          0          0         0          0
SMALLWOOD, W      CU M                                       0          0          0         0          0          0         0          0          0         0          0          0          0         0          0
FUELWOOD, '000 TON                                           0          0      17597      17597     17597      35195      35195     35195      52792      52792     52792      70389      70389     70389      87987
CARBON STORED IN WOODY BIOMASS, MILLION TONS                 3          8          8         10        15         15         18        23         23         25        30         30         33        38         38
EXPENSES, '000D0YUAN                                       1020      1165       1825      2055       2199       2860       3090      3234       3894       4124      4265       4921       5942      6086       6746
REVENUES - EXPENSES                                        -793      -905       -735       -913      -1025      -855      -1033      -1145      -975      -1153      -1262     -1089      -1882      -1994      -1824
REVENUES                                                     0          0        673        673       673       1346       1346       1346      2019       2019      2019       2691       2691       2691      3364
CARBON STORED IN SOIL, O00D OD TON                           0          1          2         3          6          8         12        15         20         25        30         36         42        49         56
TOTAL CARBON IN WOODY BIOMASS AND SOIL (MT)                  3          8          9         13        21         23         29        38         42         50        60         66         75        86         94
NET COST/TON C02 REDUCED                       39.32
1990 shadow exchange rate (Y/$)     5.5       7.15



APPENDIX TABLE B.3 FUELWOOD PLANTATIONS
CHINA GREENHOUSE GAS STUDY                   PLANTATION MODULE                 FUELWOOD PLANTATIONS
SUMMARYSHEE, pot 2
AREA DISRIBUIION PER REGION AND SPECIES
IN 000 HA ACCORDING TO THE SELECTED SCENARIO
REGION:         I          2           3          4          5      TOTAL
PER SP.
SPECIES                                                                                                          REGION      INCREMENT
I LOCUST                    t44.211      0.000       0.000      0.000      0.000     144.211                                 1       1442
LESPEDEZA                   0.000      0.000      0.000      0.000       0.000      0.000                                 2       2649
2 ALNUS                       0.000     189.237      0.000      0.000       0.000    189.237                                 3       4389
CASSIA                      0.000      0.000      0.000       0.000      0.000      0.000                                 4        855
3 - CENTE    OAK                       0.000      0.000     130.447      0.000      0.000     130.447                                5         890
COEROSPONDIAS               0.000      0.000      0.000       0000       0.000      0.000
3- SOUTH   EUCALYPTUS                  0.000      0.000     102.494      0.000      0.000     102.494
ACACIA                      0.000      0.000      0.000 0.000            0 .000     0.000
4 LOCUST                      0.000      0.000       0.000     90D047      0 000      90.047
AMORPHA                    0.000       0.0D0      0.000      0.000       0.000      0.000
5 ELAEGNUS                    0.000      0.000       0.000      0.000     123.563            GRAND TOTAL,
HIPPOPHAE                   0.000      0.000      0.000      0.000       0.000            FUELWOOD
PLANTATIONS
TOTAL PER REGION          144.211    189.237    232.941     90.047     123.563                           780.000                                                              TOTAL         NPV         IRR
12480      13260       14040      14820      15600       16380      17160      17940      18720       19500      20280      21060       21840      22620      23400       24180   (C02 basis)
16         17          18         19         20         21          22         23         24          25         26         27          28         29         30          31
5          6           7          8          9        2010         11          12         13         14         15          16         17         18          19       2200
0          0           0          0          0           0          0          0           0          0          0          0           0          0           0          0              0
0           0          0          0          0           0          0          0           0          0          0          0           0          0           0          0              0
87987      87987      105584     105584      105584     123182     123182     123182      140779     140779     140779      158376     158376     158376      175974     175974        2727591     348367
40         45          45         48         53          53         55         60          60         63         68         68          70         75          75         78            285        254
6976       7121        7781       8011       8155        8816       9046       9186        9843      10863      11007       11668      11898      12042       12702      12932         211473      30280
.2002      -2114       -1944      -2122      -2234      -2064       -2242      -2351      -2178      -2971       -3083      .2913      -3091       -3203      -3033       -3211         -58348      -9995 NEGATIVE
3364       3364        4037       4037       4037        4710       4710       4710       5383        5383       5383       6056        6056       6056        6729       6729         104295      13321
64         72          81         90         100        110        120         131        143        155        167         179        193        206         220        234            859        767
104        117         126        138        152         162        175        191        203         217        234        247         263        281        295         312           1143       1021



APPENDIX TABLE B.3 FUELWOOD PLANTATIONS
Fuelwood Plantations                                            Carbon Sequestered
NPV (12%)      IRR    $/t C02        MAI       Biomass      Soil      Total
SPECIES                                                 cm/ha (gr)   '000 tC
1 (NE)                LOCUST
LESPEDEZA                  -2638    #NUM!          2.04         10      14753      57191       71944
2 (SW)                ALNUS
CASSIA                      -229    #NUM!          0.28         14       1805      44090       45895
3 - (S) CENTER          OAK
COEROSPONDIAS              -1795    #NUM!          1.96         14      20551      30393       50944
3- (S) SOUTH          EUCALYPTUS
ACACIA                      -1238   #NUM!          1.45         25      23592      23880       47472
4 (N)                 LOCUST
AMORPHA                    -1669    #NUM!          2.08         10       8751      35711       44462
5(NW)                 ELAEGNUS
HIPPOPHAE                  -2427    #NUM!          2.64          7       8191      42877       51068
Total Average                                                                                 77642      234142     311784



APPENDIX TABLE B.4 OPEN FOREST MANAGEMENT
CHINA GREENHOUSE GAS STUDY                       PLANTATION MODULE                    OPEN FOREST MANAGEMENT
SUMMARY SHEET, part I                                                                                         AREA DISTRIBUTION BY REGION
(PROPORTIONS)
TOTAL AREA ESTABLISHED, '000 HA PER YEAR                                              REGION:           1          2            3           4           5
SCENARIO I                   890.000                                                  PROPORTIONS             0.171061528 0.293077443 0.386487752 0.071462007 0.077911271            1
SCENARIO 2                  1340.000    CHOOSE      1790.003             REGION                   MAI
SCENARIO 3                  1790.000                                               1                     2.53           1                                                   0.171061528
2                     3.21                       1                                       0.293077443
AREAS AVAILABLE, '000 HA
REGION                I        3289                                                3                     3.20                                   1                           0.386487752
2        5635
3        7431                                                4                     2.20                                                1              0.071462007
4        1374
5        1498                                                5                     3.53                                                            1 0.077911271
19227
1.000       1.000        1.000       1.000       1.000
YEAR        (t)                                                        1           2           3           4            5           6           7           8            9          10          I1          12           13          14          15
YEARS (1990-2020)                                                   1990           1           2           3            4           5           6           7            8           9        2000            1           2           3           4
LOGS, '000 CU M
SMALLWOOD, '000 CU M                                                   0           0           0           0            0           0           0           0           0            0           0           0            0           0        6789
FUELWOOD, 'OODTON                                                      0           0           0           0            0           0           0           0           0            0           0           0            0           0        7113
CARBONSTOREDINWOODYBIOMASS,MILLIONTONS                                 2           5          11           18          27          38          51          65           82         100         120         141          165         190         211
EXPENSES,'O000     YUAN                                             188         224         260         295          331         367         403         439          474         510         537         564          591         618         908
REVENUES - EXPENSES                                                 -188        -224        -260        -295         -331        -367        -403        -439        -474         -510        -537        -564        -591         -618        1267
REVENUES                                                              0            0           0           0           0            0           0           0           0            0           0           0           0            0        2174
ACCUMULATEDCARBONINSOIL,MILLIONTONS                                    0           1           4           8           14          21          29          38          48           60          73          87          102         119         136
TOTrAL CARBON IN WOODY BIOMASS AND SOIL (MT)                           2            7          15          26          41          59           79         103         130          160         193         228         267         309          346
NET COST/TON C02 REDUCED                               -0.04        Y/ton
1990 shabw exchange rate (Y/5)            5.5       -0.01         S/ton



APPENDIIX TABLE B.4 OPEN FOREST MANAGEMENT
CHINA GREENHOUSE GAS STUDY                          PLANTATION MODULE                      OPEN FOREST MANAGEMENT
SUMMARY SHEET, part 2
AREA DISTRIBUTION BY REGION
IN 0S0 HA ACCORDING TO THE SELECTED SCENARIO
REGION:            1            2            3            4            5      TOTAL                                   REGION       INCREMENT                 AREA          Increment per ha
PER SP.                                              000 cu m                  000 ha       planted
1                                306.200        0.0S0        0.000        0.0D0        0.000      306.200                                       1          775               306.2001352        0.433
2         1684               524.6086233         0.941
2                                  0.0S0      524.609        0.000        0.000        0.000       524.609                                      3         2442               691.8130754         1.364
4          281                t27.9169917        0.157
3                                  0.0S0        0.000      691.813        0.0S0         0.000      691.813                                      5          307                139.4611744        0.171
5489.012144                       1790  3.06648731
4                                  0.000        0.0S0        0.0S0       127.917       0.000       127.917
5                                  0.0D0        0.0D0        0.000        0.000       139.461      139.461
GRAND TOTAL,
OPEN FOREST
MANAGEMENT
TOTAL PER REGION               306.200      524.609      691.813      127.917      139.461                                1790.000                                                                     TOTAL          NPV           IRR
(C02 basis)
16           17           18           19           20           21           22           23           24           25            26           27           28           29           30           31
5            6            7            8            9         2010           11            12           13           14           Is           16            17           18           19         2200
0
7191         7191         7191         7191         7191         7191         7191         7191          7191        17555        18169        18169        18169         18169        18169        18169       198071
7534         7534         7534         7534         7534         7534         7534         7534          7534        19194        19884        19884        19884         19884        19884        19884       213413
234          259          285          314          344          377          411          446          484           513          543          575          609          645           683          722         2648         2364
952          979         1006         1033         1060         1087         1113          1140         1167         1605         1632         1659         1686         1712          1739         1766        28043         4029
1222         1195         1168         1142         1115         1088         1061         1034         1007         3931          3904         3878         3851         3824         3797         3770         32455          149        12.4%
2174         2174         2174         2174         2174         2174         2174         2174         2174          5536         5536         5536         5536         5536          5536         5536        60498         4178
154          174          194          216          238          262          286          311          338          365           393          422          451          482          513          545          1999         1785
388          432          480          530          583          638          697          758           822          877          936          997         1061          1127         1196         1267        4647         4149



APPENDIX TABLE B.4 OPEN FOREST MANAGEMENT
Open Forest Management                                                   Carbon Sequestered
NPV (12%)       IRR     $/t C02          MAI        Biomass        Soil        Total
REGION                                                                         '000 tC
1 NE                  -151         8.7%         0.03        2.53       115105       176037      291141
2 SW                   -52        11.4%         0.01         3.21      216869        88470      305339
3 S                    498        15.3%        -0.06         3.53      314500       116667      431167
4 N                     -88        7.0%         0.04         2.20       36242        78443       114685
5 NW                   -57         9.4%         0.03         2.20       39512        85522      125035
Summary                          149        12.4%        -0.01                   722227       545138     1267366