GUIDEBOOK This guidebook contains a step by step description of actions necessary for urban growth scenarios modeling. It aims at helping future implementers to identify the resources and time needed for the activities that lead to a successful outcome. This Guidebook is part of the Consultancy Urban Growth Scenarios Model and Sustainable Urban Expansion for the Hashemite Kingdom of Jordan. Funded by the Korean Green Growth Trust Fund, through the World Bank. Glossary Glossary Acronyms Base year is the present year, or the year with the latest available CEP Clients’ engagement process information. Defining a base year is highly relevant in CDP Capacity development process scenario modeling because it represents a startup-point for the forecasting process. UGS Urban Growth Scenarios Horizon is a selected year in the future in which scenarios take OKEV Overseas Knowledge Exchange Visit year place. Defining a horizon year is key to avoid bias when comparing scenarios. The definition of a horizon year strongly depends on the availability of historical data. Normally, the range between the base year and the horizon year is equal or less than the range of the historical data. Indicators are numeric values which describe the conditions and issues of a city. Indicators simplify the evaluation, monitoring and communication of the status of a city and are key for integrated urban planning. Indicators can be used to assess how a city is (or will be) dealing with specific urban concerns. Policy allow decision makers to test the application of a project, levers instrument or public policy in a computer model. By activating or deactivating a lever, stakeholders can visualize the potential impact of implementing an action in a simulation platform. Possible are projects, instruments or public policies which local solutions stakeholders envision as potential alternatives to deal with urban concerns. Possible solutions can be a detailed plan or a conceptual idea. When their implications are modeled they are called policy levers. Scenarios are “possible future conditions” that can be projected using statistical models and spatial data. Developing scenarios helps forecast what a city will be like in the future. To do so, practitioners analyze historical data and identify the key factors that led the city to its present conditions. Urban are the most significant problems that a city faces. These concerns “challenges” can be derived from different sources of information, such as literature review, benchmark comparison and interviews with experts. In the present study, urban concerns are strongly based on the perspective of local stakeholders. Urban are planning tools that facilitate the understanding of various growth possible outcomes related to specific urban policies. These scenarios policies might include transport or infrastructure investment plans, land use changes and housing policies, among others. Scenarios contribute to an efficient communication of urban initiatives. They rely on indicators, which provide a “common language” based on numerical data and represent a consistent, transparent and systematic approach to urban concerns. 1. Introduction 5 1.1. Objectives 6 GUIDEBOOK INDEX 1.2. Information display 2. Preliminary activities 2.1. Planning 7 8 8 2.2. Defining team roles 11 2.3. Analyzing the context 12 3. Client engagement process 14 3.1. Introduction and first contact 15 3.2. Collaboration and information exchange 20 Introduction Preliminary Client Capacity Technical 3.3. Dissemination 24 activities engagement development description 4. Capacity development process 31 process process 4.1. Module 1 32 Technical Planning Introduction Module 1 4.2. Module 2 37 Objectives details and first contact 5. Technical description 45 Defining Collaboration Urban growth Information 5.1. Technical details 46 & information Module 2 scenario display team roles exchange methodology 5.2. Urban growth scenario methodology 47 Analyzing Dissemination 6. Annexes 53 the context 6.1. Annex 1: General information required 54 6.2. Annex 2: Survey example 55 6.3. Annex 3: Handbook 56 6.4. Annex 4: Training session description 71 6.5. Annex 5: Exercise example – Diagram 73 6.6. Annex 6: Agenda for the Overseas 74 Knowledge Exchange Visit to Korea 6.7. Annex 7: Models 76 6.8 Annex 8: Indicators methodology 84 7. Bibliography 107 Introduction 1.1.Objectives 1 1.2. Information display 1. Introduction The urban growth scenario methodology facilitates the understanding of various possible outcomes related to specific urban policies. This methodology analyzes the performance of a 1.1. Objectives forecast scenario in a variety of indicators, calculated from the characteristics of the city. The indicators’ results can be improved by implementing local government policies or projects (policy levers); a mix of these policy levers brings different results presented as scenarios. This guidebook presents the guidelines to apply the urban growth scenario methodology in The scenarios provide a platform to assess the benefits and drawbacks of a certain combination different contexts in terms of working with of policy levers. The scenarios are displayed in a web based application. Having this visualization country counterparts. tool is particularly useful to align different views and build consensus on policy priorities. Counterparts' engagement The document has three specific objectives: This methodology is part of the undergoing efforts carried out by the World Bank to support strategy local governments in developing sustainable urban planning strategies. The methodology has been applied to countries as diverse as Jordan, Indonesia, Côte d’Ivoire and Mexico. A description Describe the client engagement of the methods can be found in chapter 5 of this guidebook and in the document Urban Growth process Model and Sustainable Urban Expansion for the Hashemite Kingdom of Jordan Final Report. The present guidebook is based on the engagement process and the policy dialog experience in Jordan and the countries where the methodology has been implemented. Several examples are Suggest a capacity development used throughout this guidebook to illustrate this implementation in a variety of situations and to process describe the work with country counterparts. Working with government counterparts is essential to learn about the context, to collect data Offer the technical details of and to meet the local priorities and expectations. Moreover, the methodology must be owned by adapting the methodology, the stakeholders, and the outcomes should be useful to the local decision-making process. according to a country context, policy issues and data Since mutual learning and collaboration is crucial, these proceedings are strongly based on availability. experience and knowledge exchange. This approach is fostered by two parallel processes: 1) client engagement, and 2) a capacity development. 6 The CEP proposes three different activities promoting collaboration, a locally-owned methodology, and information exchange. The CDP aims at reinforcing certain skills by two learning modules; it also includes an OKEV to have an in-depth learning experience about the possibilities of taking informed decisions. 1.2. Information display The information included in this guidebook aims at helping your planning, implementation and assessment of the methodology adaptation. The information structure promotes a clear and agile reading. Every activity or module in the guidebook has a description of the following features: Objectives: Resources: What do we want to accomplish What do we need for this activity? (such with this activity? as tools, information, visual support, etc.) Audience: Expected outcomes: This guidebook is nourished by Who are the counterparts Which products will we have when this the experience of adapting the participating? activity is completed? methodology in Jordan and other countries. You will find Methods: General recommendations: these examples displayed in How do we achieve the What do we need to consider, in general boxes like this one. terms, to achieve this activity? objectives? Besides these features, the modules in the CDP include goals; which are the activities or tasks that the attendees will be able to perform after a module is completed. You will find specific tips According to the objectives, the following chapters present the preliminary activities to start throughout the guidebook. the UGS modeling, the local CEP, the CDP and the technical aspects to consider while adapting the methodology. 7 Preliminary activities 2.1. Planning 2 2.2. Defining team roles 2.3. Analyzing context Stakeholder mapping 2. Preliminary activities Before working with local counterparts, it is important to carry out certain activities to foster collaboration and knowledge exchange: ⚙ You need to have a plan. If the host country is abroad, you will need to plan according to the number of possible fields trips. ⚙ The team will perform particular roles while working with counterparts, you need to define these activities before starting the knowledge exchange process. JORDAN ⚙ You require context background to present the UGS modeling to stakeholders and to Our early planning showed we could invest establish the first contact. available resources to create a webpage as repository of meetings, workshops and training sessions materials. The webpage also provided 2.1. Planning online registration for people attending the main events, and a general survey at the end of To anticipate obstacles and opportunities we suggest reading this guidebook entirely before each session. starting your working plan. Even though all the recommendations, activities and methods displayed in this guidebook are flexible; reading it will give you some ideas to adapt the urban growth modeling methodology to the city or country you are working on. Elaborate a working plan. Depending on the available time and resources, we suggest defining the dates for the CEP and CDP activities in relation to the main deliverables. Also, it is important to have a list of the required data for each stage, as well as a list of the human and material resources. It will be easier to define these after adjusting the guidelines offered in this document to the specific UGS modeling characteristics. 9 Example of a working plan. The timeline is based on the Jordan’s UGS modeling. A typical process would take between 6 and 12 months. Knowledge and experience exchange Visit Visit Visit Visit 1 2 3 4 Preliminary activities APRIL MAY JUNE JULY AUG. SEPT. OCT. NOV. DEC. Introduction & Meetings with Urban concerns and first contact decision makers possible solutions (validation) Meetings with Follow Policy levers definition 0 stakeholders up meetings Dissemination National Data gathering 1 meetings Workshop Module 1 Module 2 Methods development 2 Training Training session 1 & 2 session 1 Scenario development 3 Overseas Knowledge Results dissemination 4 Exchange Visit 0 Data set, material & sources 3 Validation report Draft Methodology Final Comprehensive 1 report 4 report Preliminary Growth 2 Model report 10 2.2. Defining team roles The UGS modeling requires a multi-disciplinary team with expertise in several domains. The profiles of the task team members should include experience in urban planning, urban economy, environmental studies, architecture or civil engineering and computer science. At least one member of the task team should have field experience in research methodologies (qualitative and quantitative). Carrying out the activities demands certain roles from the task team. These roles can be Language can be a strong barrier. performed by one or more members; and they can vary – or even not be necessary – depending Besides the translation support from the on the activity: local representative, working with a translation company throughout the UGS The strategist monitors, notes and modeling facilitates the communication The team leader promotes and creates direct dialogs with the registers issues that require more process. The local representative can stakeholders and knows UGS attention, identifies meetings that help deciding which company to select. modeling at a very detailed level. require follow-up, creates links Nevertheless, make one or two between stakeholders, and maps proofreading tests to ensure the results out interests and conflicts. are as expected. The local representative has wide The secretary records all meetings Some team members should have knowledge on the country’s context and shares the notes with all the moderation skills to help planning and and speaks the local language. This team members and with the implementing the CDP. member of the team identifies the stakeholders. The secretary also key stakeholders and helps setting makes a photographic record, and up the meetings. Also, this member organizes the meetings and training is able to communicate the UGS sessions logistics. main concepts and methodology. 11 2.3. Analyzing the context Besides the documentation on the social, economical and environmental characteristics of the cities, we recommend having background knowledge about the policy context. Before starting, we suggest answering the following questions: ⚙ How does the political structure work? ⚙ Which are the key institutions and stakeholders to involve in the UGS modeling? ⚙ Which is their position towards the UGS modeling objectives? ⚙ Which institutions own the information we need? ⚙ What are the main development interests of the key stakeholders? ⚙ Which is the best way to approach a policy dialog? ⚙ Which is the cultural/social code for meetings? Stakeholder mapping We suggest to identify the relevant institutions and actors’ roles. A stakeholders map recognizes the persons or group of persons whose support is needed to carry out the UGS modeling or that could give an interesting opinion about it. To create this map you need to identify individuals, groups or institutions that could influence or that could be influenced by the UGS modeling. We suggest to make a diagram Example of an organization structure map. This with these actors’ priority, as well as the level of impact in the UGS modeling at a technical mapping helps understanding the nature of an level (involvement). organization and its relationship with other institutions. Source: KGGTF Knowledge Exchange. 12 In the following diagram, we present a generic example of this actors map. At the Decision top left, you find the institutions/actors makers Ministry of Urban Planning with a high level of decision. These Minister stakeholders need to be informed and Ministry of Housing Ministry of Energy engaged but probably do not need Minister Minister technical details. At the right bottom, you see the stakeholders with a high level of Ministry of Public Works Ministry of Transportation involvement but with a low level of Minister Minister decision-making. Municipality Municipal Planning Mayor Department Priority Director Acknowledge the interest of the key stakeholders, the ideas they are averse Ministry of Urban Planning to, and their relationship with other Planning engineer actors. This can be crucial to define the GIS Department Ministry of Transportation best way to approach them and gain Head of Department Mobility engineer their support. Department of Statistics GIS Department Head of Department Traffic engineer Municipal Parks and Gardens Department of Statistics Head of Department Statistic Engineer Technical groups Potential data Potential providers Involvement owners of the tool 13 Client engagement process Introduction and 3 first contact Collaboration and information exchange Dissemination Meetings with decision makers National Workshop 3. Client engagement process The active participation and collaboration with country counterparts is a key factor for the success of the UGS modeling. This strategy includes three activities to promote knowledge and experience exchange with local stakeholders. 3.1. Introduction and first contact This activity is a first approach to present the UGS methodology and to learn about the stakeholders’ interests and concerns related to the city’s planning. The task team recognizes the data availability and defines further follow-up meetings with key stakeholders. JORDAN Objectives The task team had four meetings with • Present the urban growth modeling methodology to local stakeholders. Jordanian local authorities in 1) Greater • Define clear communication channels for future data collection. Amman, 2) Zarqa and Russeifa, 3) Greater • Understand local stakeholders main interests and concerns for urban planning. Mafraq and 4) Greater Irbid Municipality. • Identify relevant initiatives and projects from local, national and international institutions. Meetings were also held with the National Ministries of Planning, Municipal Affairs, Transportation, and with a local consultant Audience firm. • Urban planning, infrastructure, and transport representatives, among other national ministries or Local stakeholders shared their main urban government departments. planning concerns. This first contact helped to • Local authorities (at municipal level). understand Jordanian cities’ context and to • Local consultants and private sector representatives. establish new channels of communication. • International cooperation agencies with similar initiatives within the city or the country. 15 Methods The suggested number of participants is up to 8. Nevertheless, it is advisable to Meetings (recommended number is up to 8 stakeholders). These meetings have two main consider that meetings can vary in size parts. The first one is dedicated to the UGS modeling presentation. The second part is used to with short notice. gather the participants’ general impressions and to identify local government projects or public policies related to the city’s urban concerns. We suggest a sequence of activities for these meetings: 1. Introduce the meeting, the institutions and the participants collaborating with the task team. Emphasize the support from local institutions and the importance of the collaborative work. JORDAN 2. Make a presentation (25 minutes maximum) including objectives, scope, methodology and In Jordan, it was helpful asking local expected results. counterparts about the ideal features or a. Objectives must make sense to the participants; if possible ask them to read the characteristics they wanted for their city. objectives from the slide(s) and give some minutes to discuss them. These answers were used as references while b. Make sure that, after the methodology explanation, the participants have enough presenting the policy levers. For example, one time to ask some questions about it. answer to the first trigger question was: “A c. Share the intention of integrating a technical committee to follow-up the UGS city without traffic”. When local counterparts modeling and to learn about the methodology. Identify the persons interested in this claimed that the improvement of the public idea to make a formal invitation in the near future. transport system is not relevant because of 3. To collect information from the stakeholders, we suggest engaging participants by posing the country’s mindset or the country’s way of three trigger questions (give some examples of the urban concerns already identified by your life, the task team explained how investing in team). high quality public transportation has proven a. How would you describe the change you wish for your city? Ask them to share their to reduce urban congestion. answer in no more than five words. For example “a connected city”, “a cleaner city”, “a safer city” etc. b. Which are the top five urban concerns about your city? Ask them to share according Note that the trigger questions are only to the order of priority. suggestions. You will decide which are 4. The answers can be collected in different ways, we describe three of them in the following the best questions to present, depending paragraphs. At the end of each one the conclusions, main thoughts and ideas are recorded. on your context analysis and the rapport you have with the stakeholders. 16 5. Encourage participants to comment and discuss. This allows you to identify the context of the ideas presented, as well as the controversial opinions or topics. Discussion are useful to identify the benefits and drawbacks of the different ideas, as well as the actors defending one idea and the actors promoting another ideas. 6. We recommend to have a break at this moment; participants can mingle and the task team integrates a final list of urban concerns. JORDAN 7. After the break, present this list of urban concerns and ask stakeholders about projects or The importance of context while collecting plans addressing them. You can ask questions like: information. Some of the stakeholders expressed a. Which are the – ongoing or future – projects or public policies related to the main there was a “fear of development”. It was until they urban concerns? elaborated the idea, adding some context, that we b. Is there a budget assigned for this project? understood the origin of this fear. In Jordan, the law c. Is it part of a published Program? establishes the right to claim ownership of treasury 8. Share with the stakeholders the list of data required and the format in which this information lands when proven that it has been under their use should be presented (an example of this list in Annex 2). Additionally of being familiarized and care for a certain amount of years. So, people are with the nature of the data, stakeholders can advise which institutions or stakeholders will scared of losing this right and build their own house, provide this information. as they are not able to buy one. 9. Ask stakeholders if they have any further questions 10. Make final conclusions and thank the stakeholders for their presence. Difference of opinions. Actors involved in the recent creation of parks were defending the importance of There are several ways to collect this information: creating big, open public spaces. Other actors (mainly female actors) argued that the location of those parks are not useful because they are not located Establish an open discussion among participants. In a round table arrangement pose each near the most populated areas of the city. They trigger question and let them answer one by one. The moderator promotes respect during the claimed that a better solution is to have small parks conversation and writes the answers on a board where everybody can see the results. in proximity of people. From this discussion we discovered two different policy levers: 1) Few big Ask the participants to use cards. In a round table arrangement, ask the attendees to write down parks 2) Smaller parks distributed close to their ideas in cards. This is a silent activity with a specific lapse of time (1 minute is enough). residents. Afterwards, ask them to share their answers with the person next to them, couples can have a discussion (2 to 3 minutes) about their thoughts on the trigger question. When the time is up, one member of the couple shares the highlights of the conversation (in 1 minute). The moderator writes the answers in a board where everybody can see the results. 17 Use Metaplan1, which is a proven and effective method to reach a shared understanding among a group of people. Metaplan is a structured way to get consensus and it is time efficient with larger groups of people. Room arrangement. For the round table: attendees and members of the task team are seating facing each other (as shown in figure 3); this helps to create a dialog among counterparts. For the ABIDJAN Metaplan: participants are seating forming a U shape, the moderators and the pinboard are at the In Côte d’Ivoire, the Urban Master Plan of front (as shown in figure 3). Greater Abidjan helped to start off the discussion from a set of projects that were Metaplan Round table already well known by the local authorities; and this helped to the scenarios definition. Therefore, if the city is working on a development or urban master plan, these meetings are useful to get information about it. Also, local counterparts can share the new strategies they are willing to include to update and complement the original plan. Business cards may appear unnecessary, nevertheless consider that in certain countries, it is a well- appreciated gesture. At these meetings, we recommend showing how the visualization tool works (a demo in case theirs is not Attendees ready). This helps the stakeholders to understand the use of the information Members of task team they provide, and to have a better Figure 3. Recommended arrangement for meetings idea of the expected outcomes. 1. For further information: Metaplan, Basic Techniques, Metaplan LLC. http://resources.metaplan.de/wp-content/uploads/2017/04/Metaplan_Basiswissen_engl.pdf 18 Resources • Attendance list or a digital registration system. • Visual presentation to introduce the UGS modeling. • Computer and screen. Having visual support is advisable; some • A recorder. countries participants are grateful when they can • USB cards to deliver the presentation and the list of required data. take some information with them. If that is the • Consider bringing a mobile Wi-Fi hotspot to avoid internet dependency. case, it is more likely that participants will share the information with their peers. Expected outcomes Printing out: In some cases, it is helpful • Stakeholders information to nourish the actors’ map. to have infographics printed out. Visual • Contact information of all the participants. support will enhance stakeholders • List of sentences describing the expected changes for their city. analysis and comprehension. • List of prioritized urban concerns. • List of projects and public policies related to the urban concerns and key persons to follow up. Technical committee: Throughout these meetings, we suggest to form a technical committee. The members of this group are representatives of different government departments, and they are in constant communication with the task team to follow up, share specific data, and learn technical details to implement the methodology. This committee is a suitable group to attend the CDP modules because this will promote greater engagement towards the UGS modeling. 19 3.2. Collaboration and information exchange This activity increases the collaboration and the knowledge exchange with stakeholders. Through follow-up meetings, the task team encourages a better understanding about the Since it is not always possible to gather methodology and about the importance of the collected data. Key stakeholders learn about the the data during the first meeting, plan evolution of the UGS modeling and validate the information. to have enough time ahead for follow up meetings. It is more effective to When planning these meetings, consider reinforcing the collaboration with the technical collect and validate information in committee to increase their engagement. these meetings than asking the stakeholders to send it afterwards. Objectives • Validate the policy levers identified by the task team. • Collect specific information to estimate indicators. • Reinforce the lessons learned regarding the methodology and develop further according to The objectives do not need to be the stakeholders’ interest. addressed all at once in each meeting. They depend on the needs identified by Audience the task team and also on the audience attending. Technical and non-technical stakeholders that are essential to develop the policy levers. The specific audience will depend on the context and on the concerns and projects previously identified for the city. An example of sectors involved is: In some cases, new stakeholders will start • Urban development and urban planning. taking part in the process unexpectedly. • Building, transportation, infrastructure, public works and services. Make sure you are ready to give a brief • Water resource management. version of the first presentation at any • Climate change adaptation. moment. • Economic development, industrial and tourism industry. • Non-profit organizations and advocacy groups. 20 Methods Follow-up meetings (recommended number is up to 4 stakeholders). It is advisable to start these meetings with a brief version of the UGS modeling presentation. This version includes an It is important to be sensible to any rivalry additional section on the changes stakeholders wish for their city, along with the urban concerns between municipalities, departments or and the policy levers the task team identified. It is important to validate this information with ministries. While presenting the information, them. it is relevant to include examples for each city or to use a generic example. We suggest a sequence of activities for this session: 1. Introduce the meeting, the institutions and the participants collaborating with the task team. Emphasize the local institutions supporting the UGS modeling and the importance of the collaborative work. Consider showing a preliminary version of 2. Make a presentation (20 minutes maximum) including brief introduction to the UGS modeling, the visualization tool to validate the work a description of the change the stakeholders described at the first stage, a list of the urban made by the task team. concerns and the policy levers resulting from the task team analysis. 3. Explain the importance of the data, emphasizing that the information availability define the results accuracy. 4. Share with the stakeholders the list of data required and the format in which this information should be presented (an example of this list is presented in Annex 1). Additionally of being familiarized with the nature of the data, stakeholders can advise which institutions or persons can provide this information. 5. Ask the stakeholders for detailed information from a particular sector or government department. If it is pertinent, ask them to be part of the UGS modeling by opening new channels of communication in their area. 6. Before ending the meeting, ask the stakeholders if they can copy the data in an USB card or similar. Make sure, that all information is readable and in the appropriate format 7. If needed, set up another follow-up meeting with the same stakeholders or with someone in their team to get the required data. It is possible to share again the list of required data. 8. Ask stakeholders if they have any further questions. 9. Make final conclusions and thank the stakeholders presence. 21 Room arrangement. Attendees and members of the task team are seating facing a computer (as shown in figure 4); this is helpful to analyze the information and to work with the visualization tool. Verify that everyone in the task team knows the gathered data and the information that still needs to be collected. A shared document in a cloud-based platform can be helpful for this task. Follow-up meetings might take more time than expected. Consider that some meetings will be cancelled or that the objectives will not be reached the first time. Figure 4. Recommended arrangement for follow-up meetings 22 Resources • Attendance list or a digital registration system. • Visual presentation to introduce the UGS modeling. • Computer or laptop. • A recorder. • USB cards to deliver the presentation and the list of required data. • USB card to take away data from the stakeholders . • Consider bringing a mobile Wi-Fi hotspot to avoid internet dependency. Expected outcomes • Specific data to estimate the indicators. • A validated list of policy levers. • New channels of communication with departments or ministries. 23 3.3. Dissemination The purpose of this activity is presenting results (preliminary and final) and to bring awareness and engagement. This is done by different methods: 1. Individualized meetings with decision-makers from key decision makers, and a 2. National Workshop at the end of the UGS modeling. 3. Additional meetings with the technical committee, as the ones described in section 3.2 (optional). Meetings with decision-makers JORDAN In Jordan, the key ministries where the The purpose of these meetings is to share the results with decision-makers from key Ministry of Planning and International Affairs, ministries. Presenting the preliminary and final results allows you to discuss the main findings, the Ministry of Municipal Affairs and the identify which policy levers should be developed into the future and draft possible paths for Ministry of Public Woks and Housing. them, which is the overall objective of the scenarios modeling. Objectives It is possible to bring together • Discuss the scenarios’ results and their implications. stakeholders with similar concerns. For • Identify high impact policy levers that can be developed into the future. example, the department of water, • Increase the engagement and commitment of decision-makers, by being informed. sanitation, and electricity can participate • Reach consensus about the what will be presented in the National Workshop. in one meeting. Another one can be with representatives from transport and Audience urban planning. • Decision-makers from key ministries such as the Interior Ministry, Ministry of Infrastructure, and Ministry of Urban Planning and Development. 24 Methods Meetings with decision makers (up to 4 stakeholders). These meetings should start with a presentation of the results and the visualization tool (preliminary or final). Participants can work with the visualization tool and learn about the scenarios. Afterwards, a discussion about the results’ implications and future steps is recommended. Resources • Visual presentation to present results. • Visualization tool. • Computer or laptop. • A recorder. • USB cards to deliver the presentation. • Consider bringing a mobile Wi-Fi hotspot to avoid internet dependency. Expected outcomes • List of required modifications (when presenting preliminary results). • List of high impact policy levers that can be taken into further development. • Agreed take-aways that will be disseminated. • Synergy among a diversity of stakeholders’ opinions. 25 National Workshop It is convenient to have some information printed out to help participants following This workshop presents UGS modeling to a larger audience and shows the collaborative work the presentation. Some infographics can between the local government and the task team. This workshop is a favorable moment to share be available at each table. the implications of the urban growth scenarios methodology, emphasizing the importance of informed decision on urban planning. Depending on the conclusions reached with the key stakeholders, the National Workshop can be used also as the platform to introduce the future steps. Room arrangement. We recommend having a cocktail setting (as shown in figure 5). Unlike an auditorium setting, this arrangement promotes a more collaborative process. Dissemination events can vary greatly according to the needs of the UGS modeling and the characteristics of the country. For example, in Jordan the National Workshop was held in Amman during the third visit, to present the main findings of the OKEV and the preliminary results. In Mexico, due to the extension of the country, 32 workshops were held to disseminate the final results for 37 metropolitan areas. Figure 5. Recommended arrangement for national workshops 26 Objectives • Assemble stakeholders to present final results. • Assemble stakeholders to validate final results. • Share the methodology and tool with stakeholders. • Promote collaboration to reach urban planning consensus. JORDAN Audience The National Workshop held in Jordan was • National ministries or government departments. divided in two parts: 1) the general presentation • Local authorities. of the project and the results, 2) the • Private sector. presentation of the experiences and thoughts • Research centers and academia. from a group of delegates that went to Korea in • Technical stakeholders working with the task team. an OKEV. The workshop was from 9:00 to • International cooperation agencies. 14:00, with a coffee break at noon, and lunch after the final Questions & Answers session. During the coffee break, attendees had the Methods opportunity to visualize the preliminary results through a dynamic website tool created The national workshop is a large event where all stakeholders are invited to learn the specifically for the event. results and share their thoughts about it. The number of attendees will depend on each UGS modeling. We suggest to choose an unbiased venue to have it. During the National Workshop, we suggest emphasizing the following key ideas: The main activity of the workshop is the results’ presentation from the task team, • To understand the rationale of the urban growth scenarios methodology, think about however a brief intervention from the how you would make a decision at a personal level. A possibility is that you would assess attendees is helpful to keep them all options you have and try to imagine the future with each one of them. This is exactly engaged. For example, you can ask them what a scenarios modeling methodology does in terms of urban planning. to describe their city in two or three • The methodology has been part of the CDP with local stakeholders and they can adapt it words. Later on it will be easy to link the to the country’s needs. This is important because projects, priorities, technology, etc. tend policy levers to the reality they described. to change, and the project will need to fit the new needs. 27 • The scenarios allow us to communicate, in an effective way, the best combination of policy levers. • Collaboration and cooperation is fundamental for a better urban planning and projects implementation. • Reaching consensus is crucial to move towards an organized and sustainable growth. Resources • Attendance list or a digital registration system. • Preliminary or final results presentation. A digital registration system is useful • Visualization tool. to record and process information in • Computer or laptop. an agile and homogeneous way. • A recorder. • A mobile Wi-Fi hotspot. • Coffee break and lunch if planned. • Survey. Expected outcomes • Consensus over different observations and comments. • Extension of the user’s network. • Synergy among a diversity of stakeholders opinions. 28 General recommendations for carrying out the CEP meetings. Before: During: After: ⚙ Organize and plan your activity in ⚙ Make sure that everybody sign up for the ⚙ Debrief with your team. advance. Respect the stakeholders activity. If possible, verify their contact ⚙ Make sure you have the main ideas from planning by sending the invitations information is complete. each meeting in a document and share with enough time. ⚙ Mention the objectives before starting an your notes with stakeholders and the ⚙ Know the attendees’ profile to activity, and make sure you have a checklist of members of the task team. recognize what kind of information the expected outcomes. ⚙ Send the materials (or further they can provide to the UGS ⚙ Make sure you record all opinions drawn up information if asked) the same day if you modeling. during the meetings and the dissemination can. This will promote your audience to ⚙ Designing the presentation. The activities. stay engaged. more visual elements the better. ⚙ Recognize the importance of repetition. Avoid the excess of text and let the Stakeholders will have a deeper understanding images have their own narrative to of the methodology if they listen to the key explain the UGS modeling. concepts and the main ideas more than once. ⚙ Check on advance the availability ⚙ Make sure that during the presentation you of all the devices and elements mention that this is a collaboration work needed for the meeting: projector, between the task team and the city. Highlight projection screen, microphone (if that the UGS modeling aims at their city needed), laptop, adaptors, improvement. electricity plugs, and USB card. ⚙ Before leaving a meeting, make sure ⚙ Make sure you have an attendance participants know how to get in contact with list or a digital registration system the task team. The distribution of business ready before the meetings. cards is an effective way and it gives the opportunity to have a couple of minutes to talk to each participant. ⚙ Make contact with new stakeholders willing to share information still required for the UGS modeling. 29 General recommendations for carrying out the National Workshop: Before: After: ⚙ Integrate the invitation list. Make sure that all stakeholders are ⚙ Make the required modifications resulting from the invited, and remember to invite the local press. stakeholders’ suggestions. ⚙ Have a detailed agenda to share with all the members of the ⚙ Additionally to sending the materials, you can also send task team, the local representatives and other people working a small survey to have the participants’ assessment on on the logistics of this day. the methodology and on the tool (we include an ⚙ Define the venue where the workshop is taking place and check example of this survey in Annex 2). availability. ⚙ Make sure to send the presentation and the results to ⚙ Send a “save the date” email, at least two weeks in advance. all the participants. ⚙ Send the invitations to the workshop one week in advance and a reminder two days before the workshop. ⚙ Check if a translation service is required. ⚙ In case the event takes more than two hours consider having a coffee break; if it takes all morning consider inviting stakeholders to lunch. ⚙ It is advisable to invite local stakeholders (working in the UGS modeling) to make part of the presentation. Their voices empowers local actors and reinforces the sense of collaboration. ⚙ Prepare an attendance list or a digital registration system before the National Workshop. 30 Capacity development process 4 4.1. Module 1 Two training sessions 4.1. Module 2 One training session Overseas Knowledge Exchange Visit 4. Capacity development process How to use and maintain the UGS model The counterparts’ engagement and the CDP are performed at the same time, as parallel processes. The stakeholders attending the meetings described before can also be part of the following plan. The best scenario is that the technical committee is already formed, and it is participating in the CDP activities from the beginning. This committee is expected to be in charge of managing, maintaining and updating the tool in the future. The CDP comprises two modules. Each one has learning objectives that lead to a group of expected outcomes. Since the learning concepts are in a progressive sequence, we recommend respecting the order. Nevertheless, the moment to implement them depends on the context and on the task team time, resources, and observations. 4.1. Module 1 The first module is an introduction to the importance of using the urban growth modeling methodology to create consensus and to make informed decisions. It introduces the key concepts of the methodology, as well as some of the indicators’ calculations. Learning objectives Audience In Jordan and in Abidjan, this module was conducted in two sessions of 4 hours each. • Recognize why urban planning Technical staff in charge of managing and updating the tools, policy levers, indicators, and tool in the future. They could work in the following scenarios are useful for informed sectors: Attendees should have solid bases on • Urban development and urban planning, building. urban planning and minimum decision making. • Transportation, infrastructure and basic services. knowledge on geographic information • Understand and practice some of • Water resource management. systems, demographics and geography. the indicators’ calculations. • Climate change adaptation. • Economic development, industrial and tourism industry. 32 Methods This module is delivered by two training sessions; we suggest a duration of 3 to 4 hours for each session. They can be conducted in one or two days depending on availability of time and resources. Contents of the module include theory analysis and practical exercises. This is important to ensure that attendees can apply concepts and methods to real urban problems. The first training session The recommendation for the first session is to guide the participants to recognize the benefits and possibilities of the methodology; we also propose to present the rationale of some of the calculations and to guide participants to practicing them. JORDAN Indicators’ exercise for the training sessions To explain how the variables relate to the local context, we create a Handbook that describes held in Amman. The goal of the exercise was some of the indicators’ calculations. This handbook might be useful to create an exercise for this to understand the rationale of the proximity session (you can find it in Annex 3). indicators. Participants were asked to identify the BRT stations proximity for the city’s The main concepts for this session are: population. To do so, they had a map showing • Input variables - Information availability and transformation. the localization of BRT stations, also the map • Expansion models. had the distribution of the population in a • Indicators’ calculations. grid. Participants were asked to create a on the map (800 m). Having the buffers, they We suggest a sequence of activities for this session: counted the population for each square in the 1. Introduce the UGS modeling, the institutions and the participants collaborating with the task grid and calculate the total population in team. proximity to the amenity. This result was 2. Make a presentation of the main concepts (25 minutes maximum). divided by the city’s total population to know 3. Ask participants to share their thoughts and ideas on the contents presented. the percentage of people close to the BRT 4. Continue with the presentation of the main concepts (25 minutes maximum). stations. 5. Present the exercise you prepared and guide participants in the calculation of the indicators you chose. 6. Review the exercise with them and open a Q & A session. 7. Make final conclusions. Refer to some of the ideas the participants mentioned during the session. 33 Planning a training session will depend on several factors: the number of participants, the Despite that the agenda will depend on time availability, the resources, the specific objectives, etc. Accordingly, we suggest to make a the specific UGS modeling characteristics, training session description. This description specify each activity, its objective, the contents we want to suggest a possible agenda for and the description, the person in charge of the activity, as well as the time, materials and the activities proposed in this training resources required (we present an example in Annex 4). session. Activities Minutes This detailed plan is an effective tool to prepare all materials and contents for the session and Introduction to the session and introduction of participants 30 to ensure that all of the task team members know what to do and when. Also, with this Contents’ presentation 25 planning it will be easy to have your session agenda ready to share with the participants. Activity to promote participants input 10 Contents’ presentation 25 20 We suggest some key ideas to be introduced during this session. They might help to drive the Questions and answers discussion to the importance of the methodology and to explain certain concepts. Break 20 Exercise presentation 10 1. Scenarios modeling help us to understand how our city will look in the future if we make Exercise performance 30 certain changes, or how it would look if we continue with the present trend. Exercise review 15 2. Think about: How do you make personal decisions? It is probable that you will try to Questions and answers 15 imagine the future with each one of your choices. The scenarios modeling methodology Final thoughts and closure 10 does that, in terms of urban planning. This training session agenda considers a group of 12 to 15 persons. 3. A tool to visualize these results makes the decision-making process easier. It helps to reach agreements and to take informed decisions. 4. You may ask: If it is so great, why is it that we have not used this methodology before? Parallel processing allows us to make calculations in a way that it was not possible before; we can get results in a shorter period of time. Also, cooperation and collaboration projects like this enables us to have opportunities to exchange knowledge and experience. 5. The accuracy of the results depends on the data availability and in our capacity to transform the information to the required formats. 6. Indicators: Calculating indicators is not new for stakeholders; even though it is important to make sure they understand the methods and to promote the creation of their own indicators. 34 The second training session This session reviews the concepts of policy levers and scenarios. These concepts are used while working with a preview of the urban growth scenarios tool for their city. The main concepts for this session are: • Policy levers. • Scenarios. For this session, we suggest a sequence of activities. 1. Introduce the session and resume the final thoughts of the previous one. 2. Present the main concepts of the session. 3. Explain success stories to illustrate the implementation of a combination of policy levers. 4. Present the visualization tool with the policy levers and scenarios for their city. 5. Guide participants to use the visualization tool in pairs. 6. Ask participants to share their ideas and questions about the tool. 7. Ask participants to create an example of how the methodology works by proposing new indicators and policy levers appropriate to the local context. 8. Review the exercise with them and open a Q & A session. 9. Make final conclusions. Refer to some of the ideas the participants mentioned during the The suggested agenda of the last training session. session can be easily adapted to this one. 10. Ask participants to answer a survey to have feedback on the first module. We suggest some key ideas to be introduced during this session: 1. Having certain indicators allow us to assess the city performance in terms of your urban concerns; the policy levers help you to improve those indicators’ results. 2. You can create your own scenarios by turning on and off the policy levers. Demo tools. If the preview of the 3. Scenarios give us a method to communicate integrated solutions and help us to create visualization tool for this city is not ready, consensus among stakeholders. When pursuing funding for a project, it is helpful to you can use other country’s tool to help demonstrate with numerical evidence that your project will improve more than one indicator. participants to understand the basic 4. When presenting examples, consider sharing cases that relate to their urban concerns. principles of the methodology. 5. The purpose of these training sessions is that participants can access to all calculation methods and to give them freedom to create their own. 35 Goals Between modules it is important to enable an open communication with Upon completion of this module, attendees will be able to: the technical committee, in case they 1. Explain the importance of urban planning tools. have further questions or doubts 2. Describe the following concepts: input variables, indicators, expansion models, scenarios about the UGS modeling. and policy levers. 3. Recognize local input variables and indicators. 4. Calculate a diversity of indicators. 5. Recognize international examples of solutions to specific urban concerns. 6. Test demo tools and understand the basic principles of the methodology. 7. Propose locally appropriate policy levers and scenarios. 8. Use each of the concepts’ methodology appropriately. 9. Recognize combination of policy levers to alleviate specific urban concerns. Resources • Visual presentations. • Material for the exercises. • Infographics. • Demo tools. • Feedback survey. Expected outcomes At the end of this module attendees are able to explain why urban planning tools, indicators and scenarios are useful for informed decision making. They recognize the difference between urban concerns and policy levers, and they explain the main concepts by creating an example of their own. 36 4.2. Module 2 Learning objectives Using urban planning tools and indicators to analyze public policies and urban projects. Audience The technical committee should be integrated at this point. The audience should be the same participating in module 1. JORDAN Keeping the audience. A steady audience Methods throughout the CDP modules can be difficult. It is possible that participants will come and This module is delivered by one training session and an OKEV. Contents of the training session go, but there will be interested people that include theory analysis and practical exercises. The overseas visit is a knowledge exchange will commit. This is what we experienced in experience, in which the technical committee visits another country to learn about their Jordan, there was a group of technical staff solutions to certain urban concerns. that participated in every visit. However, it is advisable to try to incentivize Training session participants by presenting all the benefits of having scenarios to make informed decisions. We suggest a 4 hours training session. The recommendation for this training session is that stakeholders create (with information they have) new indicators for the local context. Also, this session is intended to guide the participants to use the final versions of their country’s tool and to be able to present the scenarios’ results as a way to bring in consensus. 37 Room arrangement. We recommend having one or more tables in a U shaped setting (as shown in figure 6). This arrangement promotes collaboration among participants as well as attention to the presentation. Figure 6. Recommended arrangement for the training sessions 38 The main concepts for this session are: • The creation of new indicators. • The tools’ usage. • The tool’s results presentation to create consensus. For this session, as in Module 1, we suggest an agenda. Remember this is only To accomplish the learning objectives, we suggest asking the participants to complete few a general idea of the time distribution, you tasks before the session. Send them the latest version of the tool and ask them to: will need a specific plan for your session. 1. Turn on and off the existing policy levers on the tool. Activities Minutes 2. Think about: How would you use the tool for your professional projects? Introduction to the session and main thoughts of 30 3. Choose one project you want to move forward. previous session 4. Use the tool to prepare a communication strategy to create consensus among your peers Tool usage and participants input 20 and other stakeholders. Activity in pairs 30 We suggest a sequence of activities for this session: Presentation in pairs and comments from peers 40 1. A brief introduction with the main conclusions of the previous training session is helpful to Break 20 start working in the same ideas. Exercise presentation 10 2. The task team gives an introduction of the final version of the tool. 3. Participants share their ideas about the benefits and drawbacks using the tool for their Exercise performance 40 professional projects. Results’ socialization 30 4. Participants work in pairs (maximum three persons) to elaborate only one strategy to Questions and answers 20 communicate the scenario that drives their projects. This will help to promote a Final thoughts, closure and survey 20 collaboration process among departments. 5. Each couple present their communication strategy (no more than 5 minutes per This training session agenda considers a group of 12 to 15 person presentation) and receive constructive criticism from their peers. 6. Stakeholders explain, from their perspective, the following questions: a. What other indicators will you include in the tool? b. What is the required information to develop those indicators? c. Which policy levers will affect those indicators performance? d. Which would be the calculation methods for those indicators? 39 7. The stakeholders present the results for these 4 questions in diagram (Annex 5 is an example of the expected result for the diagram). There is time to socialize the results. 8. This session will be also important to solve questions or doubts the technical staff has about working with the methodology and the tool in the future. 9. Consider a final survey on the CDP. For this session, as in Module 1, we suggest an agenda. Remember this is only a general idea of the JORDAN time distribution, you will need a specific plan for your session. Overseas Knowledge Exchange Visit The OKEV to Korea. Local counterparts from the 5 different cities in Jordan integrated a The OKEV is an in-depth learning experience to inspire key stakeholders to promote innovation delegation that traveled to Korea. This visit’s in their city’s planning. The geographical location and agenda for this activity depend on the main goal was to understand the reasons specific needs and resources (Annex 6 is the agenda of the OKEV from Jordan to Korea). This is an behind the recent urban policies in Korea and to effective activity to promote a vivid understanding of the possible changes in a city or a country compare with their country’s reality. when informed decisions are taken. This experience played a meaningful role in the This activity requires significant planning.2 It is important to consider hosts and visitors CDP; as Mohammed Zawahreh, Head of the objectives and expectations to plan the pertinent field visits to reach the goals. These goals will Local Development Unit of Zarqa Municipality depend on the ideas, skills, concepts or practices you wish to reinforce through this experience. expressed when talking about his experience in To plan the OKEV we recommend to define the following: Korea: • The visit’s goal. • Main interests of the visitors. “The most effective way to learn about • Main interests of the hosts. something is to go and see it”. • Logistical preparation such as travel expenses, participants’ visas, location and structure of the visit. All delegates learned about the significant • Translation services (if required). changes Korea accomplished in a few years, by • Clear communication channels with visitors and hosts. committing to specific goals; they learned • Agenda of each day of the visit. about several sustainable solutions to problems that are similar to those they have in Consider a daily wrap-up meeting. We suggest having constant communication with the visitors Jordan. to have a sense of their experience. 2. More information about planning an Overseas Knowledge Exchange Visit at World Bank, The Art of Knowledge Exchange [1]. 40 The advantages of an OKEV are the following: After the visit, the delegates presented their take away at the National Workshop. This • Participants can see and experiment the implementation of a specific combination of policy presentation was relevant as a manifestation of levers. all the new knowledge they had acquired. Also, • This experience will bring awareness on the benefits that the urban growth methodology their statements gave a local vision of all the can provide to their practice on planning. positive impacts that are possible by reaching • This kind of knowledge exchange encourages a more open minded behaviour towards consensus and by taking informed decisions certain changes on the cultural mindset. about the urban planning of their cities. • It is possible that the participants of the technical committee conceived themselves as a group; which would help to have a sense of collaboration on the OKEV. In the following paragraphs we present some of • The final national workshop is a interesting opportunity for the stakeholders to disseminate the experiences the Jordanian delegates shared their new knowledge, and inspire peers and fellow citizens. during the national workshop: In Korea, a project to rehabilitate a landfill was implemented; there were nine companies involved in the design, the supervision and implementation of the project. Which increased the green areas in Seoul, as well as the water quality. Ammal, Russeifa Municipality In Korea they listed all the challenges to know what they wanted. They started to think together, as a group, they fought together to have a comprehensive database that will benefit everyone in Korea. Now they have an online service operational. Rowieda, Greater Amman Municipality. Improve public transportation is an important project for Irbid. In Korea, people used to suffer much more than what we are suffering now. 41 The main challenges were pollution, traffic jams Goals (because of an increase in vehicles). There was also an increase on costs and time wasted on traffic Upon completion of this module, attendees will be able to: jams, measured by the hours needed to get to work • Create new calculation methods based on specific local needs. places. Then, an integrated system was proposed • Propose appropriate dissemination strategies for the tool. that solved several of those problems. • Share new and rich experiences from another city or country regarding urban planning. Reham, Irbid Municipality There is something that greatly affected me, the Resources role of open and public spaces. Now, here in Jordan children don’t have open spaces and this creates • Visual presentations. violence and extreme attitudes. (...) [in Korea] They • Infographics. decided to have a pedestrian passage, I walked • Printed exercises. along that passage and there I could see old • Final tools and datasets. persons, young people, and different ways of life. • OKEV logistics. You can tell this people is happy and capable of have a feeling of happiness, they are at ease, they don’t care of the religion of other, is a big space Expected outcomes called humanity. To reach that level of interaction, as humans when worrying become non-existent, we At the end of this module attendees will be able to use urban planning tools and scenarios to solve need spaces where we can let out our pressure and specific problems in the local context and to communicate different scenarios. They will anger, where we can be tolerant and calm and understand the basic processes for updating and managing the tools. peaceful. We need governors based on accountability, we need to push this forward. Mohammed, Zarqa Municipality. What I’ve learned is that Seoul managed to develop and improve from a simple idea: good plans. With the leadership of the King we have a good strategy. We would like to do the same. Ameer, Mafraq Municipality 42 General recommendations for carrying out the training sessions Before: During: After: ⚙ Plan your session. Write an agenda for the day (to share ⚙ Introduce yourself and your partners with you. it is ⚙ Debrief with your team. with participants) and prepare the session’s description. also important that every participant share their name ⚙ Send the materials (or further information ⚙ Prepare your visual materials. A presentation with all the and occupation. if asked) the same day if you can. This will contents (remember to avoid the excess of text), and ⚙ An “ice-breaker” activity helps to build community promote your audience to stay engaged. some infographics or general information printed out. among attendees; which encourages stakeholders to ⚙ Develop the exercise. It is important to let the participate through the session. participants use the information learned. Thus, it is ⚙ Share the objectives and the day’s agenda with your important to create one or two exercises to help them audience. practice. In case you decide to include an exercise in the ⚙ An introduction of the UGS modeling is always useful. day’s agenda, practice on it with your team the day Even if you think is repetitive, people is always grateful before to check that you have the right and sufficient to remember the objectives and highlights of the UGS materials. Also, while performing the exercise, let them modeling. be creative resolving the calculations; that flexibility will ⚙ If you decide to have an exercise, write the directions help them to understand the method. and put them where everyone can see them (project ⚙ Remember your audience profile. The information them is a paperless solution). should include technical details. The first stage of the ⚙ Remember to ask questions along your presentation to CEP is useful to recognize the stakeholders’ knowledge make sure the key concepts are understood. on GIS and mapping, and then prepare the training ⚙ Repeat the importance of the information they gave sessions accordingly. you, and the way they helped to collect this ⚙ Examples are very important. Include study cases in your information. presentation and use as many examples as you can. ⚙ Remember to promote the participants input, and use Adding international solutions to urban concerns they their thoughts and ideas to set down the main recognize for their country is a useful resource to realize concepts. the importance of these tools. ⚙ Feedback from attendees helps assessing if all ⚙ Check on advance the availability of all the devices and concepts and methods were delivered appropriately. elements needed for the meeting: projector, projection This is performed along the presentation with screen, microphone (if needed), laptop, adaptors, questions to the audience, but it is also possible with a electricity plugs, and USB card. final survey with some general questions about the ⚙ Prepare an attendance list or a digital registration main concepts. This is important to ensure that the system before the training sessions. tools will be useful and appropriate to the local context. 43 General recommendations for carrying out the OKEV Before: During: After: ⚙ Identify the OKEV’s goal. ⚙ Invite all participants to a morning briefing ⚙ Identify roles for your team members: ⚙ Debrief with visitors and promote sharing every day. take-aways. logistics, communication with visitors, ⚙ Provide a role or task to every participant. materials, technical details. ⚙ Debrief with your team to know how to For example, the documentation of a improve your next OKEV. ⚙ Select the candidates by identifying the certain subject or a presentation in the host motivations and interests related to the main ⚙ Send follow-up materials (or further country. information if asked). goal. ⚙ Pay attention to the visitors’ expectations ⚙ Identify the visitors’ needs and expectations. ⚙ Prepare your report. by focusing on real solutions to their urban ⚙ Identify the hosts’ needs and expectations. concerns. ⚙ Establish the different subjects of interest to ⚙ Respect the agenda. review during the visit, for example, data ⚙ While visiting sites promote that everybody availability, affordable housing, transport. listens and participates. ⚙ Share the communication channels you will ⚙ Document the entire process. be using and create an emergency protocol in ⚙ Have a daily meeting to express impressions case someone is not able to get in contact and questions. with the task team. ⚙ Identify the main organizations and institutions to make contact and visit during the OKEV. ⚙ Make contact with the organizations and institutions you would like to encounter. ⚙ Make sure all administrative formalities are done, such as transportation, hotels, visas, vaccinations, currency. ⚙ Prepare the OKEV’s materials such as daily agenda, presentations, and supplementary documentation. 44 Technical description 5.1. Technical details 5 5.2. Urban growth scenario methodology 5.1. Technical details Collecting local data can be a hard task. In some cases, information is incomplete, or it needs a lot of time and effort to be generated or transformed into a suitable format. The urban growth scenarios need spatial information to acknowledge the urban characteristics that determine the environmental, social and economic indicators results. Therefore, it is recommended to obtain all the information in geographic information systems (GIS) formats, like .shp files, and compile it in spatial databases in PostgreSQL or similar. If the data is obtained in JORDAN tables, like .csv, be sure they contain a georeferenced location per each entry of the table, for example the latitude and longitude or the geometry in WKT or WKB format. Another option is to Collecting data in Jordan took 110 follow up have an id or code to relate each entry to a corresponding shp file, for example the census code meetings. Data gathering and processing to link the number of housing units per block with the geometry of each block in a shp file. represented two thirds of the total time. A large number of the output indicators estimated through the urban growth scenarios relay on Census data was obtained at neighborhood data disaggregated at block level or a pixel of maximum 250x250 m, therefore it is important to level. Only the neighborhoods’ geometry was request it in this way since the early moments. For example, it is not possible to estimate the delivered in shp file; population, housing and percentage of the population that lives 700m or less away from a park if we only know the employment data was provided in spreadsheets population at municipal level. If only aggregated data is available, consider time and resources to with the neighborhood code. The first step was process it and downscale it. to compile a shp with all the information related to each neighborhood. Then, the data As we are modeling growth scenarios for specific cities, all the data inputs should come from the was downscaled to a grid of 250x250 m using local context. In case official local data is not available, or the information provided is not of use, the built-up area information provided by the indirect evidence-based estimation methods can be used. For example, layers like Gross Domestic Global Human Settlement Layer. This provided Product estimation using Nighttime Lights from the National Oceanic and Atmospheric the scale needed to calculate indicators like Administration (NOAA) or the Global Human Settlement Layers from the European Commission, proximity to urban amenities or the energy can be combined to estimate population proximity to sources of employment. consumed for transportation. Negotiating the information delivery can be a demanding process, it should not be underestimated. 46 5.2. Urban growth scenarios methodology The methodology used in this study involves urban growth scenario modelling. This methodology was designed to provide key information for city managers and simplify their decision-making process. This is done by forecasting how stakeholders’ present decisions might impact the city’s future conditions. The scenarios provide a platform for understanding how integrated solutions across varying levels of government and different sectors could be successful. Additionally, they help various actors understand their interdependency, creating a consensus among a wide range of JORDAN stakeholders. The overall objective of the UGS modeling for Jordan was to compare the environmental, social The performance of each scenario is measured on the basis of a variety of indicators, which are and economic impacts of different urban growth calculated from the characteristics of the city (input variables). For example, indicators such as paths for five Jordanian cities to guide the proximity to public transport and job proximity depend on the population density, the public identification, preparation and implementation of transport system, and the employment density across the city. The Figure below depicts the sustainable urban investment projects. The cities conceptual framework of the scenario modelling. included in the study were Greater Amman Indicators Municipality, Greater Irbid Municipality, Greater Input variables Energy consumption Mafraq Municipality, Russeifa Municipality, and Public transit network Zarqa Municipality. Employment density Infrastructure cost For this UGS modeling, the base year is 2015 and the horizon year is 2030. Population density Public space proximity Pedestrian infrastructure Water consumption Land value SCENARIO Land consumption Urban form Job proximity Urban development plans Infrastructure costs GHG emissions Water demand Public transport proximity 47 The current year, or the year with the latest available information, is referred to as the base year, and the forecasted year is called the horizon year. For this project, the base year is 2015 and the horizon year is 2030. The first step is to model a Business-as-usual (BAU) scenario. This scenario forecasts the future characteristics of the city if the past repeats itself, using machine-learning algorithms. Such algorithms utilize statistical spatial data to determine the drivers of urban expansion and predict JORDAN which areas have a high probability of becoming urban in the horizon year [2]. The detailed methodology can be read in Annex 7: Models. The main policy levers tested for Jordanian cities Alternative scenarios can be created to assess what will probably happen if certain interventions were those that can control land use and urban take place. These interventions can range from investment projects like public transportation expansion. Programmatic algorithms were used systems, to changes in housing policy, urban planning instruments, or building construction to model how and where the population will codes. These interventions are known as policy levers, as they trigger changes in the settle in the horizon year according to the performance of the city. maximum housing densities allowed in the Master Plans and the policies that prioritize All data processing and indicator calculations were carried out using Urban Performance, a tool settling in specific areas or housing typologies. developed as a part of this project by CAPSUS SC and Urban Planning Technology SA de CV. Urban Performance is based on open source software PostgreSQL, PostGIS, and Python. Other levers related to transportation and urban infrastructure, as well as efficiency and clean Urban growth scenario modelling is developed in six main stages. As described throughout this energy measures, were then combined with the Guidebook, the urban concerns of each city are discussed and analyzed in close coordination land use patterns to create the main scenarios with local stakeholders to identify the indicators that best assess the performance of each city. for analysis. Local stakeholders also provide information about interventions they are planning, which are modelled as policy levers to create different scenarios. A series of meetings and workshops with government officials and technical specialists are designed with this objective (the timeline of these is presented in page 10). Each stage of the UGS modeling is described in the following sections. 48 Stage 1 - Identify urban concerns and possible solutions The objective of the first stage was to identify the main urban concerns for each city and the possible solutions to these problems in order to define the indicators that best reflect how the possible solutions tackle the urban concerns. JORDAN A series of workshops with the city officials are developed to present the objectives, scope, and The urban concerns repeatedly suggested during the workshops were related to road congestion, solid waste limitations of the project. The meetings conclude with working sessions in which local management, energy consumption and generation, stakeholders complete and improve preliminary lists of urban concerns and indicators previously accessibility to parks and schools, and pollution sources drafted by the core team from a literature review. like the phosphate piles in Russeifa and artisanal workshops in Mafraq. An initial list was drafted after the Based on the workshops, a final list is defined by selecting only elements that met the following first set of workshops and crafted with the stakeholders criteria: during the second set of workshops and meetings. 1. An urban concern can be abstracted into and measured by one or more indicators. Local authorities expressed their interest in the location 2. The effects of possible solutions can be abstracted into one or more policy levers. of parks and public open spaces in relation to the 3. All indicators and policy levers can be modelled because either: population; therefore, proximity to this type of urban a) data from local, regional or national sources is available, amenities was added as an indicator. For this Jordan, b) data from international sources can be adapted, or proximity to worship places was added, recognizing their c) reasonable assumptions can be made. importance in the daily life of most Jordanians. Furthermore, indicators such as population density and Indicators vacant housing rate have been integrated to reflect Urban indicators are numeric values that describe the conditions and issues of a city. Indicators current problems of the housing market in Jordan. simplify the evaluation, monitoring, and communication of the status of a city and are key for integrated urban planning. Artisanal industries such as stone cutters, and industrial waste such as the phosphate waste piles in Russeifa, were identified as sources of air pollution; thus, it was The list of indicators is defined in terms of assessing the sustainability of each scenario and necessary to measure the percentage of the population tailored to the urban concerns specific to each city. Indicators such as water consumption, exposed to these hazards. Bearing in mind that energy consumption, and GHG emissions measure the environmental aspect of sustainability, investment and maintenance costs can be an and the social sphere is covered by indicators such as proximity to schools, jobs, health facilities, overwhelming burden for local governments, and other urban services. infrastructure costs and the cost of municipal services are also included as indicators. 49 An example of a full list of indicators can be found in the following Table, and a description of each is provided in Annex 8. You can also find graphical explanations of the calculation methods in the Indicator Units Handbook (Annex 3). Land consumption [km2] Population density [population/km2] GHG emissions [kgCO2eq/capita*annum] Energy consumption [kWh/capita*annum] Infrastructure costs [JD] Municipal services costs [JD] Water consumption [m3/capita*annum] Job proximity [%] Public transport proximity [%] School proximity [%] Public space proximity [%] Sports facility proximity [%] Worship place proximity [%] Health facility proximity [%] Public building proximity [%] Cultural space proximity [%] Exposure to hazards [%] Index cards for each indicator can be found in Annex 9. They contain a description of the indicator, the calculation methods and equations, units, and the information sources used in Jordan. To help understanding how the information is used, Annex 3 (page 62 of this Guidebook) includes a graphical representation of the databases and information gathered to calculate the indicators described. The information needed to build them is shown at the top of the image, and the information used at the bottom. 50 Stage 2 – Policy levers definition Possible solutions to the urban concerns identified in stage 1, including projects and public policies suggested by the local actors, must be analyzed and structured into policy levers that can change the city’s path of development. These policy levers are defined in coordination with the local stakeholders and complemented with international experience, creating new levers or enriching those identified with local counterparts. The advantages and disadvantages of each policy lever are assessed based on the previously discussed indicators. Each policy lever has at least two options: one for current conditions (marked as lever 0) and a second for the planned changes or proposals (lever 1, 2, and so on). This allows researchers to compare the effects of turning the lever on/off. For instance, a lever on solid waste management will include the possible improvements a city can make in the sector. The level 0 would consider that the city remains with the existing infrastructure. The level 1 could be to create a new transfer station and the level 2 could include two new transfer stations. To promote a better understanding on the relationship among the urban concerns and the policy levers, Annex 10 explains the urban development issues addressed by each policy lever and indicate which levers were evaluated in the UGS developed for five Jordanian cities. 51 Stage 3 – Data gathering The third stage focused on collecting, validating, organizing, and integrating data in a single platform. Information is gathered from several government offices. This task depends on constant communications with local stakeholders and a demanding process of data homogenization, downscaling, and merging. It could be a cumbersome task in the absence of an up-to-date database, at the Ministry level and at the Municipal level. As an added benefit, this project can help the municipalities with creating their own databases, in addition to delivering a set of useful planning tools. A single, integrated database is developed for each city. It is important to mention that to ensure precision of the scenarios, special attention need to be given to both quantity and quality of information. Outputs from Stage 1 and the integration of data in a single platform provides a realistic perspective for the definition of indicators and scenarios. As an example, Annex 11 presents the information and sources encompassed in the final databases for the UGS in Jordan. Stage 4 – Methods development Stage four focus on developing accurate methods to calculate each indicator. The calculation methods are defined in line with the policy levers identified by the stakeholders. For example, to estimate the energy savings from replacing public lighting bulbs with LED bulbs, the key variable in the calculation method is the percentage of light bulbs that are LED. However, to reflect how much energy will be needed to illuminate the new streets that will be built by 2030, the method should also consider the number of streets as one variable that could change depending on how much the city grows in each scenario. In other words, it is necessary to identify the variables that would turn each policy lever on and off, and to design the calculation method based on such variables. 52 It is also important to reflect the possible drawbacks of the policy levers. For example, creating a transfer station in the solid waste collection system can reduce the volume of diesel consumed by the collection trucks, but the new transfer station will consume energy to operate. Therefore, it is important to have both aspects in the calculation method of the energy consumption indicator. The calculation method of each indicator is documented in the Annex 8 to ease future replication. Stage 5 - Scenario development The scenarios are representations of possible futures that take into consideration how current decisions will change the future of the city. Scenarios are created by combining one or more policy levers. There can be as many scenarios as the number of policy lever combinations. A Base Scenario is created according to the conditions of the base year (extension of the urban footprint, urban population distribution, existing public transportation routes, schools, parks, clinics, etcetera). Indicators for this base scenario are calculated using the methods defined in stage 4. Also, a business-as-usual (BAU) scenario is created to use as a baseline to compare with more ambitious scenarios. The BAU scenario assumes that the city’s future growth will repeat its past growth patterns. The scenario assumes that urban services or landmarks will be built in a similar proportion and distribution as in the last urban growth period. The scenario uses machine learning algorithms to forecast the urban expansion for the horizon year. These methods learn from the land use changes of the past to predict the non-urban areas that are likely to become JORDAN urban in the future. Urban growth in this scenario is not restricted by natural reserves or land uses; therefore, if human settlements have occurred in unzone areas in the past, the model The last urban growth period considered to replicates this trend. The resulting scenario represents what will happen if the public policies create the BAU scenario for the UGS in Jordan that have shaped the past remain unchanged. Annex 7 describes the methodology utilized to was from 2000 to 2015. model the urban expansion used in the BAU scenario. 53 Alternative scenarios can be developed using the Population Settlement Model described in the aforementioned Annex (7) and combining the policy levers defined in stage 2. It is advisable to model at least two alternative scenarios: i) a Moderate Scenario modeling urban growth according to the current Master Plan and combining it with the policy levers mentioned by the local actors; and ii) a Vision Scenario that models a compact development of the cities and the policy levers that yield the highest benefits. To read more about how the scenarios are defined, go to Annex 12, which describes the scenarios modelled for 2030 for each Jordanian city. Stage 6 - Results dissemination Findings are communicated to policymakers and other stakeholders during the workshops and follow-up meetings. It is useful to hand out databases, a comprehensive report, and dissemination materials to local counterparts for the continuation of urban studies based on this methodology. Based on the present Guidebook, it is advisable to organize and implement a series of training sessions with key members of the Municipal and National governments. For this purpose, it is JORDAN useful to use the The Urban Growth Scenarios Handbook, which is a graphical explanation of the general methodology and the calculation methods of the main indicators. Also, National Dissemination Workshops are recommended to socialize preliminary and final findings. A project brief and a short video were prepared as dissemination materials. Also, an online results visualization tool was created to display the scenarios’ results. The dissemination materials and the visualization tool are accessible via the website: http://jordan.capitalsustentable.com.mx/ 54 Annexes 6 Annex 1: General information required All data must be delivered in .shp format and at the smallest analysis scale available (block or similar). Category Data Transport Public transport routes and/or stops, shape files or table with coordinates Transport Average expenditure per household in transportation Jobs Economic units location & number of jobs per economic unit Services Services location (schools, health facilities, religious buildings, markets, parks & open spaces) Walkability Pedestrian infrastructure (existence of walkways, public lighting, pedestrian crossings, average size of urban blocks) Population Census at block level (population, population by age group, housing units, vacant housing units, habitants per housing unit) Land Land use changes historical information 1990-2000-2015 Population Land registry & records (plots, no. stories, renting cost) Informal housing Informal housing (number and location of informal housing) Hazards Location of hazardous areas (polluted water bodies, air-polluting industries, garbage burning sites) and implications Energy Houses: baseline consumption of energy per year per housing unit, efficiency programs or building codes Transport: Lighting: Types of street light bulbs, number of street lights or distance between light poles Water Annual city consumption in the city, percentage of water lost through leakages, baseline consumption of water per year per housing unit, efficiency programs or building codes, energy required to supply one cubic meter of water GHG emissions National emissions inventories and electricity mix Costs Infrastructure construction costs (primary, secondary and tertiary roads, water & sewage networks, public lighting) and maintenance Solid waste management Solid waste volume and costs for the municipality Revenues Municipal revenues statistics and description (land tax calculation) 56 Annex 2: Survey example 57 Annex 3: Handbook 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 Annex 4: Training session description Participants profile: Technical team from different ministries and departments from municipalities in charge of following up the Urban Growth Scenarios modeling for their city. Activity Objective Contents Description Person in charge Schedule Time Materials & Resources To write down names and Participants will fill the format with their Registration contact of participants personal information. Daniela 9:30 20 min. Registration CAPSUS will present the workshop objectives as Carmen Objectives well as the agenda of the day. To Present the workshop Ricardo Visual presentation What is CAPSUS? Introduction objectives, the agenda, CAPSUS will present the company and personal 10:00 10 min. CAPSUS and the participants. Who from CAPSUS? R&C&D information. Participants will be asked to present themselves with name, institution and job title. Who are the participants? All the participants To present the project UGS modeling UGS modeling basics Video 10:10 5 min. Video objectives and the work done introduction in Jordan until now To present the objectives and CAPSUS will present the objectives (and UGS modeling Objectives Carmen 10:15 5 min Visual presentation the work done in Jordan until expectations) of the Scenarios of Urban Growth introduction now for Jordan. CAPSUS will present the importance of creating Methodology To remember the main Scenarios value scenarios for decision making in urban planning; Carmen 10:20 10 min. Visual presentation presentation concepts of the methodology also the importance and advantages of sustainable planning. CAPSUS will explain the input variables, where this information comes from, and how it is used To understand the input Input variables to create base and to create the horizon year (expansion model). Input variables variables regarding the base horizon year The importance of the scenarios is explained in Carmen 10:30 15 min. Visual presentation and the forecasted year terms of the forecasted year. An example will be presented. Indicators show urban CAPSUS will explain that this scenario can be performance results in aspects measured in a variety of indicators, for example To understand how the such as energy consumption, the public transport network input variable can Indicators: a glance forecasted year scenario can be infrastructure cost, water be measured by the public transport proximity Carmen 10:45 10 min. Visual presentation measure by several indicators consumption, job proximity, GHG and the job proximity indicators. CAPSUS will emissions, among others. show some other examples. Input variables for To present Jordan's expansion Databases and information Challenges using and transforming the available Carmen 11:00 10 min. Handbook Jordan databases availability data. CAPSUS will explain the importance of the To understand some of the Indicators: in detail indicators Indicators examples indicators and show some of the calculations to Daniela 10:55 5 min. Handbook get the results. Participants will calculate the energy transport Handbook /Printed exercise, To calculate one or two of the Activity 1 indicators How to calculate indicators? proximity / Schools proximity / lightning Carmen / Ricardo 11:10 60 min sharpies, vellum paper, consumption. Printed exercise. paperclips. BREAK 12:10 30 coffee 73 Input from the To express ideas about how How to create a better city? How to improve these indicators? How to build Ricardo 12:40 15 min. Visual presentation a better city? How to build a more sustainable participants to create a better city city? Assistants give their input Policy levers are the local government projects and public polices related to the urban CAPSUS will explain that local government Understanding policy To comprehend the policy concerns identified in the city. projects and public policies can modify the Ricardo 12:55 10 min. Visual presentation levers lever concept They are analyzed and structured input variables and therefore the indicators as actions that can change future change to better results. development paths. In pairs or in groups of 3, participants will suggest and propose a policy lever for their cities. They will need to explain the reasons behind their selection. To do so, they will need To analyze the relationship to do an assessment of their proposition; to do Activity 2 between urban concerns and How to choose a policy lever? this they will need to answer questions such as: Daniela 13:05 25 min. Sheets of paper and pens policy levers Why is this policy lever important? How do you decide this was an important policy lever? Which indicators will this policy lever affect? They will share their results with the entire group (2 minutes per group). CAPSUS will show the different indicators' results by mixing different policy levers. This To compare the scenarios mix shows how urban planning is a How to create new scenarios from Policy levers and results by choosing different multidisciplinary activity. The results from one Carmen 13:30 15 min. Results' slides (maps) the integration of different policy scenarios policy levers to create levers and to compare them indicator affected by expansion (for example scenarios transport proximity) has also impact in other indicator such as schools proximity, or hospitals proximity. To discuss the importance of Scenarios results / the results in terms of Results will be presented. It is important to How the scenarios help to take working together to plan a remember that it is always better to work in Carmen 13:45 10 Tool's visualization conclusion more organized and decisions multidisciplinary and intersectoral projects. sustainable city To thank participants and CAPSUS will thank all participants and the Carmen & Closure institutions ministries that made possible the workshop / Ricardo 13:55 10 min. Link to survey Next steps / Survey 74 Annex 5: Exercise example - Diagram Change of 30% Policy lever Public lighting to LED STREET Summation of the Summation of the AREA OF TOTAL quantity of primary, length of primary, LIGHTING OF THE secondary and THE CITY secondary, tertiary per square tertiary and POPULAT kilometer of city. pedestrian roads. Number of hours a day ION Total number of bulbs Input that the street lighting used for street lighting works of the led bulbs used Voltage variabl Number of led bulbs Voltage of the common for street lighting es used for street lighting bulbs used for street lighting Total number of bulbsNumber of led bulbsVoltage of the common x Number of led bulbs Voltage of the led Number of hours a day - used for street lighting x bulbs used that + for street lighting bulbs used for street lighting used for street lighting used xthe street lighting works for street lighting Formula Summation of the Summation of quantity of x the length of x AREA OF primary, primary, THE CITY secondary and secondary, tertiary per tertiary and square kilometer TOTAL OF THE pedestrian POPULATION of Energy city. = ((tot_bulb-num_led)*volt_bulb+num_led*volt_led) lighting roads. *hours_day*365 / (prim_road_km+sec_road_km+ter_road_km+ped_road_km) * (prim_road_km2+sec_road_km2+ter_road_km2)*footprint_km2/tot_pop Indicator ENERY ASSOCIATED TO PUBLIC 75 LIGHTING Annex 6: Agenda for the Overseas Knowledge Exchange Visit to Korea Travel Arrival Logistics: Arrive by Oct 22 (Sun) and start the exchange visit from Oct 23 (Mon) Organized by geographic travel areas: until Oct 27 (Fri); All the delegation members leave on Oct 28 (Sat). Zone A: Seoul Official Exchange Visit Dates: Oct 23-27, 2017 Zone B: Capital Region (Incheon, Gyyeonggi Province) Zone C: Sejong & Daejeon Hotel: Millennium Hilton Hotel, Seoul DATE Sun, Oct 22 Mon, Oct 23 Tue, Oct 24 Wed, Oct 25 Thur, Oct 26 Fri, Oct 27 Sat, Oct 28 ZONE Zone A&B Zone A Zone C Zone A & B Zone A Zone A Zone A&B TRANSPORT Walk, Bullet Train, BRT, Airport Limousine Walk, Bus Walk, Bus Walk, Bus Rental Bus Airport Limousine MODE Rental Bus Arrival time TBC (9:00 -11:00) Meet at Lobby by 7:00 AM (9:30 - 11:00) (9:30 - 12:00) Meet at Lobby Hotel Check-out Introductory Meeting Transport: Walk or Bus to LX SMG / SI / SUSA by 9:00 AM Hotel Check-in Venue: Hilton Hotel Train Stationà Take Venue: LX in Seoul Venue: tbc Transport: Rental Bus Departure time TBC • Introduction of Bullet Train to Osong • Introduction of LX • (Strategic Development) (10:00 - 11:45) participants, KGGTF Station à Take BRT to (history and role) Seoul 2030 Master Plan KLID & week schedule Sejong Gov’t Complex • Importance of land- • History of SMG’s Urban Venue: Sangam DMC • Public Sector (10:00 - 12:00) registration for Growth Management • KLID introduction Institutional MOLIT development • (Communication) Public regarding local Structure in Korea Venue: Sejong Gov’t • Working with local & Service Announcement governance and smart • Relevant Green Complex national government methods and learnings city development Morning Growth Video Clips • Evolution of affordable for land registry • Seoul’s International perspective (Cheonggye Stream housing policy in Korea • Discussion Cooperation • Discussion Restoration & etc.) • Implementation of • Discussion • KLID CERT control National Housing Policy (11:15 – 12:00) center Transport: Bus in Korea (Happiness Site Visit: Citizen Service Housing and Bogeumjari Center (tbc) Housing case) Land registration system • Discussion actual application experiencing Lunch Lunch Lunch w MOLIT (tbc) Lunch Lunch Lunch 76 Meet at Hotel (2:15 - 3:45) (1:30 – 2:30) (2:00 – 4:00) (1:30 - 2:30) Lobby 4:00 PM Sangam DMC (SMG) Site Visit: LH Sejong LH / Smartium SMG TOPIS Additional Bi-lateral Green Growth • District Exhibition Hall • Role of LH in Briefing on Seoul’s meetings or internal Walking Tour: redevelopment case • Intro to LH infrastructure Transport information meeting (tbc) • Briefing on Sejong Smart management system Cheonggye into media-ICT development in Korea Stream industry cluster City Development • Korea’s Newtown (2:45 -5:00) Restoration Site • Integration of ICT in • Discussion development SMG / SH / SI / SUSA and surrounding urban development • Discussion Venue: tbc area (3:00 - 5:00) • Public Housing and case (4:00 -5:30) LHI (5:00 PM) in Seoul • Site Visit: Nanjido • Overview of LH & LHI Site Visit: Hanam • Urban Redevelopment After now Haneul Park • Overview of Korea’s urban Newtown Urban Service Case in Seoul (Old Landfill site) development history and Complex noon • Transformation of policy • Tour & briefing of Hanam waste dump site into • Overview of Korea’s environment facility ecological park housing policy and land complex (waste water policy treatment, waste • Overview of Korea’s urban recycling center, etc.) (4:00 PM) redevelopment policy • How to change the Internal Wrap-up • Discussion perception of Meeting + Dinner traditionally NIMBY • Share reflections of Transport: Rental Bus back facility during new town the week to Seoul development phase • Discussion KGGTF Hosted: Dinner Group Dinner Free Free Free Free Closing Dinner 77 Institution Summary Acronym Full Name of Organization Type of Organization City or Region MOLIT Ministry of Land, Infrastructure and Transport National Government Sejong LX Korea Land and Geospatial Informatix Corporation Public Corporation (national level) Seoul or Metropolitan Region LH Korea Land and Housing Corporation Public Corporation (national level) Gyeonggi Province (Bundang) LHI Land & Housing Institute (LH) Public Corporation (national level) Daejeon Korea Local Information Research & Development KLID Public Think-Tank Seoul Institute SMG Seoul Metropolitan Government Local Government Seoul SI Seoul Institute Public Think-Tank Seoul SH Seoul Housing Corporation Public Corporation (city level) Seoul SUSA Seoul Urban Solutions Agency Public Corporation (city level) Seoul SEOUL, Transport Operations & Information Seoul TOPIS Local Government Service UOS University of Seoul Public University Seoul 78 Annex 7: Models Expansion models The growth modeling methods recommended are Random Forests, Extratrees and Logistic Regression with regularization. The models work through machine learning algorithms and are considerably robust and complex. The models are based on the trends in the change of historical density and land use. The input variables of the models were adjusted to each city, according to the specific characteristics of their urban environment. In this way, the projections consider the specific characteristics of each city. Urban growth projection models are not new, in fact, some of these processes were conceptualized in the 40s and since then they have been used by different authors in a variety of environments to estimate patterns of urban expansion. Some examples of recent studies are Kamusoko et al. (2015) in Harare, Zimbabwe [2]; Mustafa et al. (2017) Wallonia, Belgium [3]; Wang et al. (2017) in North Brabant, The Netherlands [4] and Shafizadeh-Moghadam et al. (2017) in Tehran and Isfahan, Iran [5]. 79 Random Forest. The Random Forest method is made up of a collection of decision trees, which are used to control the variance. This method can be described as a set (collection) of models that use aggregated sampling bootstraps to construct different decision trees, to later combine these models in a final classification. The Random Forest method has several advantages: they can handle many variables, they are quickly trained, they do not require distribution assumptions like the rest of the methods, they are generally robust in the treatment of outlier data and noise, and they provide a way to calculate the importance that each variable has in the model. Extratrees. The Extratrees method is a variant of the Random Forest classifier [6] that uses the complete sample in each step with random decision limits (variables). Some advantages of Extratrees, compared to Random Forest, are that it represents a lower computational cost, the randomization makes the limits of each decision smoother and the use of fewer variables in each tree avoids overfitting. Logistic Regression The Logistic Regression method allows to predict the outcome of a dependent variable (categorical) based on a series of independent variables. In general terms, it allows to model the probability of an event that occurs as a function of other factors. To reduce the possibility of overfitting, a Ridge and Lasso regularization process was integrated. The Logistic Regression method allows to identify the variables that are significant for a particular model. What the Random Forest, Extratrees and Logistical Regression methods all have in common, is that they use a series of observations of land use change over three moments in time. They also depend on a series of explanatory variables that can be described as those conditions that influenced the change in the observations. These models “learn” about the tendencies that are seen and “train” to predict the change in land use in the future. From this training, they predict the possible changes in future land use. Data sources Some of the most frequently used explanatory variables include proximity to urban centers, roads and metro stations [7] or proximity to built-up areas, roads, industrial centers, schools, universities, hospitals, airports, downtown area of the city, topographic characteristics, per capita income, altitude, average slope and population density [2]. 80 In order to make results comparable among cities, global data sources with similar temporal information were used. The data sources used in this work are: Built-up Grid: Data contain an information layer on built-up presence as derived from Sentinel1 image collections. • Source: Global Human Settlements [8]. • Temporality: 1990, 2000 and 2014. • Format: Raster with a 250 by 250 meters pixel resolution. Population Grid: Generated using census data combined with built-up index and aerial weights to generate the spatial distribution expressed as the number of people per cell. • Source: Global Human Settlements [9]. • Temporality: 1990, 2000 and 2015. • Format: Raster with a 250 by 250 meters pixel resolution. Digital Elevation model (DEM): From the GTOPO30, which is a global digital elevation model (DEM) with a horizontal grid of 1 square kilometer. GTOPO30 was derived from several raster and vector sources of topographic information. With the elevation model, a raster file with slopes in percentage was generated, which considers the maximum difference between each cell to its adjacent cells. • Source: U .S. Geological Survey ’s Center for Earth Resources Observation and Science (EROS) [10]. • Temporality: 1996. • Format: Raster with a 1000 by 1000 meters pixel resolution. Gross Domestic Product distribution: Gross Domestic Product spatial distribution derived from night lights satellite data. • Source: National Oceanic and Atmospheric Administration (NOAA) [11]. • Temporality: 1995, 2000 and 2013. • Format: Raster with a 1000 by 1000 meters pixel resolution. Highways • Source: Open Street Maps. • Temporality: starting from 2008. • Format: lines geometry. 81 Geolocations: airports, schools, universities, worship places and hospitals. • Source: Open Street Maps. • Temporality: starting from 2008. • Format: points geometry. Water Bodies: Provides a base map for the lakes, seas, oceans, large rivers, and dry salt flats of the world. • Source: Esri Data and Maps [12]. JORDAN • Format: polygons geometry. Definition of urban The three models for the five Jordanian cities were There are no standard criteria to define an urban area, but many definitions include elements like population size and estimated using the data density, economic activity, level of infrastructure, or a combination of them. sources and definition of urban mentioned in this For this project, an adaptation to the harmonized urban cluster defined by the European Commission [13] was used, section. The resulting urban where a cell is considered urban if: expansion predictions are shown in the document 1. The maximum value of built-up is greater or equal than 40%. Urban Growth Models and 2. The mean value of the population is greater or equal than 75 people per 0.16 km2. Sustainable Urban Expansion 3. The total number of people in adjacent cells is greater or equal than 5,000. for the Hashemite Kingdom of Jordan Final Report (Section 4.4). 82 Population settlement modeling Different urban growth scenarios can be created according to how the population projected for 2030 will settle. If no specific measures are taken, the population can be expected to occupy the urban expansion predicted with the urban growth models explained in the previous section. But the urban expansion can be modified by the land uses and densities indicated by the city’s Master Plan. Or, if an urban contention policy is enforced by the government, a settlement could be concentrated within the current city boundaries. To envision these different growth scenarios, a second model was built to predict where will the incoming population settle. The definition of these scenarios is done through three policy levers: a settlement lever, a vacant housing lever, and a master plan lever. The settlement lever directs where settlement should occur first, using priority polygons. The model allocates population in each priority polygon until it is full, doing the same in each polygon until the models reach the population projected for 2030. It has three options: • 0 where the incoming population occupies the predicted urban expansion polygon; • 1 where infill close to jobs and public transportation is prioritized, first within the current boundaries of the city, and then in the urban expansion polygon, and • 2 where the first priority polygon is the predicted urban expansion but within the zoned areas in the Master Plan, the second priority polygon is the complete Master Plan, and the last one is the un-zoned areas within the municipality boundary. Option 0 was used for the Business as usual Scenario (BAU), option 1 for the Vision Scenario and option 2 for the Moderate Scenario. The quantity of new population that the model allocates in each polygon is based on the maximum number of housing units allowed by the Master Plan (max_hu), the existing number of housing units (hu), the existing number of inhabitants (population), and the average number of inhabitants per housing unit (hu_size). Only a fraction (i) of the maximum number of housing units allowed is used, in this project i = 95%, assuming 5% will remain un-built, as shown in the following equation. 83 When there is no defined maximum number of housing units, because there is no Master Plan or it is an un-zoned area, a maximum number is assumed (assumed_hu), as shown in the following equation. The second policy lever involved in the population settlement model aims at reducing the vacant housing rate to a maximum of 8%. When the vacant housing lever is on, this means its value equals 1, the model will allocate population first in the vacant houses within the city and then it will continue with the priority polygons process described above. When it is o , its value equals 0, no population is allocated in vacant units, the process enters directly to the priority polygons. The master plan lever models changes done to the land use or building norms, i.e. a new or modified Master Plan. This is modeled by introducing a different set of values for max_hu. The new urban footprint of the city (Footprint) is calculated as the current footprint (existing) plus the expansion areas (new), as shown in the following equation. Expansion areas are defined as the areas that had no population in the base year and that do have population at the end of the modeling process. Areas inside the existing city boundaries, that had a 2 fold increase in their population are added up into the Infill area (as shown in the following equation), to recognize that their infrastructure carrying capacity has to be upgraded. The following figure depicts a graphical representation of the flow diagram of the population spatial distribution process described in this section. 84 Pop to allocate= projected population BEGIN Increment between the base year and the horizon year max_hu I = 80% For each square: hu Population = Population + (I * max_hu-hu) * hu_size assumed_hu LEVER For each square, if max_hu = NULL: Reduce vacant Population = Population + housing rate is ON (assumed_hu-hu) * hu_size hu Vacant housing Distribute population in existing vacant housing units Footprint expansion STEP 1 LEVER Job Settlement of EXIT new population Transit Footprint base STEP 1 STEP 2 Distribute Job population in Footprint base polygon 1 STEP 3 Transit Footprint base STEP 4 Note: A square refers to each of STEP 2 Footprint base the analysis points, inside the city Distribute population in polygon 2 and outside it. Population refers to the number of inhabitants living in that square in the base scenario. The maximum number STEP 5 STEP 3 Job of housing units that can be built Distribute population in Footprint expansion in the square according to the polygon 3 Master Plan is called max_hu, STEP 6 and it is multiplied by a fraction Transit called i. hu is the number of Footprint STEP 4 Distribute expansion existing housing units in the population in square. hu_size is the average polygon 4 STEP 7 Footprint number of inhabitants per expansion housing unit. If the square is STEP 8 outside the Master Plan, it has no STEP 5 Political max_hu and a maximum number Distribute boundary of housing units is assumed, NO population in polygon 5 Area called assumed_hu. Update the urban footprint area and calculate the infill area Footprint = existing + new areas Infill area = sum of area where population had a 2 fold increase END 85 Annex 8: Indicators methodology Land consumption. The amount of land predicted to change from natural habitats or agricultural uses into urban human settlements between the base year and the horizon year, measured in square kilometers. Population density. The number of inhabitants per built-up area, expressed as inhabitants per square kilometer. GHG emissions. The average GHG emissions released annually per capita related to energy consumed for public lighting, municipal water supply, solid waste collection, electricity in dwellings, and commuting (public transportation and private vehicles). Emissions are measured as the total kilograms of carbon dioxide equivalent emitted per person per year. Energy consumption. Energy consumption. The total average amount of energy consumed per person per year for public lighting, municipal water supply, solid waste management, electricity in dwellings, and commuting by public transportation and private vehicles. Energy consumption is expressed as total kilowatt hours of energy consumed per person per year. The energy consumption indicator is the addition of 5 sub-indicators: • Energy consumption for commuting [kWh/capita*annum]: The total average amount of energy consumed per person per year for commuting within the city via public transportation or private vehicle. • Energy consumption for water distribution [kWh/capita*annum]: The per capita annual amount of energy required to supply the volume of water demanded by the city’s dwellings. The calculation considers the energy embedded in water treatment and distribution, as well as water losses due to municipal network leakages. • Energy consumption for public lighting [kWh/capita*annum]: The annual average amount of energy consumption for public lighting per person. • Energy consumption for solid waste collection [kWh/capita*annum]: The average per capita amount of energy consumed annually by the solid waste management system of the city, including collection, transportation, and energy consumed in the landfill and transfer stations. • Energy consumption for dwellings [kWh/capita*annum]: Average annual housing electricity consumption per capita. The calculation is not connected to household income; only the city’s average electricity consumption is taken into consideration. 86 Infrastructure costs. The total investment required to build the roads, water network, sewer network, public lighting, and electricity grids for the square kilometers that the city will expand, and the investment required to increase the capacity of the existing networks where the urban population will have a twofold increase. It is measured as the total Jordanian dinars (JD) required to invest between the base year and the horizon year. The Net Present Value is not taken into consideration; all costs used in the calculation are from the base year. The infrastructure costs indicator is the addition of 2 sub-indicators: • Infrastructure costs for urban expansion (expansion) [JD]: The total cost to build the roads and water, sewage, public lighting, and electricity networks within the km2 that the city is estimated to grow. • Infrastructure costs for upgrading existing capacity (infill) [JD]: The total cost to upgrade the water, sewage, and electricity networks within the areas of the existing city that are estimated to experience a twofold increase in their population. Water consumption. The total average volume of water consumed per capita in the city’s households in one year. The calculation is not connected to household income; only the city’s average water consumption is taken into consideration. Job proximity. The percentage of the population that lives within 1,000 m from areas in the city with high job density. Public transport proximity. The percentage of the population that lives within walking distance of a public transportation station. Walking distance is considered 800 m for structured transportation systems like a Bus Rapid Transit (BRT) or subway, and 300 m for buses and similar modes. School proximity. The percentage of the population that lives within a radius of 700 m from an elementary school. Public space proximity. The percentage of the population that lives within a radius of 700 m from a public space or park. 87 Sports facility proximity. The percentage of the population that lives within a radius of 1,000 m from a sports facility. Worship place proximity. The percentage of the population that lives within a radius of 1,000 m from a Mosque, Church, Synagogue, or other place of worship. Health facility proximity. The percentage of the population that lives within a radius of 1,500 m from a hospital, clinic, or doctor. Public building proximity. The percentage of the population that lives within a radius of 2,000 m from the city’s town hall or a public service office. Cultural space proximity. The percentage of the population that lives within a radius of 1,000 m from a cultural facility, community center, library, social facility, or theatre. Exposure to hazards. The percentage of the population that is exposed to hazardous pollutants from living near human-made stationary sources of pollution. Pollutant concentrations are not measured, only proximity. All proximity indicators are calculated by creating a buffer of the corresponding radius around the All proximity indicators are calculated by buildings being analyzed, then adding up the population that lives within that radius. Due to technical creating a buffer of the corresponding constraints, distances are not measured using the street networks. radius around the facilities being analyzed, then adding up the population that lives within that radius. Due to Figure 2.3 is a graphical representation of the databases and information gathered to calculate the technical constraints, distances are not selected indicators. Indicators are shown on the right side of the image and the information needed to measured using the street networks. build them is on the left. 88 Annex 9: Index cards Land consumption Description. Amount of land predicted to change from natural habitats or agricultural uses into urban human settlements. Measurement units. Square kilometers [km2] Methodology. Land consumption (land_consumption_km) is calculated as the difference between the city footprint in the horizon year (fp_horizon) and the footprint in the base year (fp_base). The city footprint refers to the total built-up area of a city, including streets, open space and inner vacant land. Urban footprint for the horizon year is estimated using artificial neural networks based on orography, roads, built-up area, population and employment historical data, using at least two points in time (e.g. years 2000 and 2015). The number of years between these two points in the past determines how far into the future can the forecast go; for example, if 2015 is the base year, and information from 15 years before 2015—Year 2000—is available, then the forecast can go as far as 15 years after the base year 2015—year 2030. Calculation. land_consumption_km = fp_horizon - fp_base Sources. • Built-up area: Developed by CAPSUS as explained in chapter 2.8 89 Population density Description. Number of inhabitants per built-up area, expressed as inhabitants per square kilometer. Measurement units. Inhabitants per square kilometers [pop/km2] Methodology. The population density (pop_dens) is calculated by dividing the total number of inhabitants (tot_pop) by the built- up area of the city (footprint_km2). Calculation. pop_dens = tot_pop / footprint_km2 Sources. • Population: Population and housing census 2015 and projections by the Department of Statistics and the Housing and Urban Development Corporation (HUDC) [2, 33]. • Built-up area: Developed by CAPSUS as explained in chapter 2.8 Desirable range. According to the studies Better Neighborhoods: Making higher density work [38], Compact Sustainable Communities [39] and Towards a strategy of Transport Oriented Design for Mexico City [40], recommended urban densities range between 80 to 110 housing units per hectare (15,000 to 35,000inhabitants per km2). 90 GHG emissions Description. Average per capita greenhouse gases emissions released annually related to the energy consumed for public lighting, municipal water supply, solid waste management, electricity in dwellings and commuting (public transportation and private vehicles). Measurement units. Kilograms of CO2eq per person per year [kgCO2eq/capita/annum] Methodology. Annual per capita GHG emissions (ghg_tot) are the result of multiplying annual energy consumption per person by the carbon factor of each type of energy. Carbon factors refer to the amount of CO2eq released by unit of energy consumed. For electricity consumption, the carbon factor (carbon_factor_elect) is specific to the national energy mix. Gasoline (carbon_factor_gasoline) and diesel (carbon_factor_diesel) carbon factors are used to estimate emissions from the consumption of fuels in transportation. The types of energy considered are: electricity for public lighting (energy_lighting), electricity for water supply (energy_water), electricity for housing units (energy_buildings), energy for solid waste collection, transportation and final disposal (energy_swaste) and energy for commuting (energy_gasoline and energy_diesel). The carbon electric factor (carbon_factor_elect) is calculated by dividing the electric emissions (elec_emi) between the total electricity generated in the country (gen_tot) plus the total electricity imported in the country (imp_tot). The electric emissions (elec_emi) value is calculated by adding the emissions of the energy generated in the country (gen_emi) plus the emissions from the energy imported to the country (imp_emi). To calculate the emissions of the energy generated in the country (gen_emi) is necessary to make a calculus adding the generation of each type of energy multiplied by the emissions factor of each type of energy: steam energy generation (ste_gen) is multiplied by the steam energy emissions (ste_emi), plus the diesel powered gas turbine generation (gdie_gen) multiplied by the diesel powered gas turbine emissions (gdie_emi), plus the natural gas powered gas turbine electric generation (gnat_gen) multiplied by its emissions (gnat_emi), plus the heavy fuel oil powered diesel engine electric generation (hfo_gen) multiplied by its emissions (hfo_emi), plus 91 the natural gas powered diesel engine electric generation (dnat_gen) multiplied by its emissions (dnat_emi), plus the diesel engine electric generation (die_gen) multiplied by its emissions (die_emi), plus the electric generation of hydropower units (hyd_gen) multiplied by its emissions (hyd_emi), plus the eolic electric generation (win_gen) multiplied by its emissions (win_emi), 105 plus biogas plants electric generation (bio_gen) multiplied by its emissions (bio_emi), plus combined cycle electric generation (com_gen) multiplied by its emissions (com_emi), plus the existing generation of solar energy (sol_gen) plus the calculation of new solar power plants (capacity of the solar plant (sol_cap) multiplied by the efficiency of the plant (sol_eff) and by the hours of sun that the plant receives every year (sol_hours)) multiplied by 365 and by the emissions of solar electric generation (sol_emi). The emissions of the imported energy (imp_emi) are calculated by subtracting the generation of the new solar power plants (capacity of the solar plant (sol_cap)) multiplied by the efficiency of the plant (sol_eff) and by the hours of sun that the plant receives every year (sol_hours) from the total energy imported in the country (imp_tot), all multiplied by the imported energy emissions factor (imp_fact). Carbon_factor_diesel and carbon_factor_gasoline are constant values assumed from the national average. Calculation. ghg_tot=(energy_water+energy_lighting+energy_buildings)*carbon_factor_elect + energy_gasoline* carbon_factor_gasoline + (energy_diesel+energy_swaste)*carbon_factor_diesel carbon_factor_elect=(elec_emi/(gen_tot+imp_tot))/1000000 elec_emi=gen_emi+imp_emi gen_emi=(ste_gen*ste_emi)+(gdie_gen*gdie_emi)+(gnat_gen*gnat_emi)+(hfo_gen*hfo_emi)+(dnat_gen*dnat_ emi)+(die_gen*die_emi)+(hyd_gen*hyd_emi)+(win_gen*win_emi)+(bio_gen*bio_emi)+(com_gen*com_emi)+((s ol_gen+((sol_cap/1000)*(sol_eff/100)* (sol_hours*365))*sol_emi) imp_emi=(imp_tot-((sol_cap/1000)*(sol_eff/100)* (sol_hours*365)))*imp_fact Sources. • Electricity generation in Jordan obtained from the National Electric Power of Jordan [41] • Emissions factors per type of generation obtained from the IPCC [42] • Efficiency of solar plant of 80% [43] • Sun hours that Jordan receives in average [44] 92 Energy consumption Description. Total average energy consumed per person during a year for public lighting, municipal water supply, solid waste management, electricity in dwellings and commuting by public transportation and private vehicles. The solid waste management energy consumption involves collection, transportation to transfer stations and final disposal sites, transference, and final disposal in landfill (if applicable). Measurement units. Kilowatts hour per person per year [kWh/capita/annum] Methodology. The indicator energy_consumption embraces the energy consumed by the city’s population for commuting (energy_transport), for the electricity they consume in their homes (energy_buildings), to supply the water they consume (energy_water), for public lighting (energy_lighting), and to manage the solid waste produced by the city (energy_swaste). Each of these consumptions is explained as one indicator in the next charts. Calculation. energy_consumption=energy_water+energy_lighting+energy_swaste+ energy_buildings+energy_transport Energy consumption for commuting Description. Total average energy consumed per person during a year for commuting within the city, by public transportation or private vehicle. Measurement units. Kilowatts hour per person per year [kWh/capita/annum] 93 Methodology. Energy consumption associated with transportation (energy_transport) is calculated by adding the energy consumed by type of fuel available in transportation vehicles in the city (energy_diesel and energy_gasoline) divided by the total population(tot_pop). The overall consumption in the city, by type of fuel, is the sum of the energy consumed in all the analysis points in the city. The energy associated to transportation by fuel type in each analysis point was calculated by multiplying the costs incurred in each type of fuel (transport_cost_diesel and gasoline) per person, by the population in the analysis point, by a factor that converts them to energy. This factor combines the diesel and gasoline calorific value (diesel_cv and gasoline_cv) and the diesel and gasoline density (gasoline_density and diesel_density). The transport cost associated to each type of fuel was calculated by multiplying the transport (transport_cost) by the fraction each type of transport represents of the whole array (gasoline and diesel_transp_frac). Transport costs were calculated per each analysis point by applying a linear multivariable regression modelIed with expenditure and income data from Mexico. The model’s resulting units are costs incurred per household per trimester in Mexican pesos. As the units desired are the local currency per person per year, the result is multiplied by 4 trimesters in a year, the exchange rate to the desired currency (JDMXN_exrate), average inflation of the Mexican Peso from the date the model was developed until the current date (avge_inflation), and divided by average household size in the city (hu_size). Calculation. energy_transport=(sum(energy_dieseli)+sum(energy_gasolinei))/tot_pop energy_diesel=sum(energy_dieseli)/tot_pop energy_gasoline=sumenergy_gasolinei)/tot_pop energy_dieseli=popi*transport_cost_dieseli*(diesel_cv/diesel_cost*diesel_density/1000) energy_gasolinei=popi*transport_cost_gasolinei*(gasoline_cv/gasoline_cost*gasoline_density/1000) transport_cost_dieseli=transport_costi*diesel_transp_frac/100 transport_cost_gasolinei=transport_costi*gasoline_transp_frac/100 transport_costi=max(0,[4/JDMXN_exrate*(1+avge_inflation/100)*(620.06+3.06*transit_distance+(19.10)*job_densit y_avge+(0.69)*pop_density_avge+213.09*avge_area+661.16*socioeco_level)]/hu_size) Sources. • Percentages of diesel and gasoline vehicles in Jordan [45] • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. • Diesel and gasoline calorific values and densities [46] 94 Energy consumption for water distribution Description. Per capita annual amount of energy required to supply the volume of water demanded by the city’s dwellings. Water losses due to the municipal network lakages are included in the calculation. Measurement units. Kilowatts hour per person per year [kWh/capita/annum] Methodology. The total annual energy consumption for water distribution (energy_water) is calculated by multiplying the energy needed to supply and distribute one cubic meter of water (water_factor) by the sum of the total volume of water consumed by the city (tot_water * tot_pop) and the water lost through leakages; which is estimated as the multiplication of the kilometres of roads in one square kilometre of the city (prim_road_km2 + sec_road_km2 + ter_road_km2), the square kilometres of the city (footprint_km2) and the volume of water lost by kilometre (loss). This total is then divided by the total population of the city (tot_pop). Calculation. energy_water=water_factor*(tot_water*tot_pop+footprint_km2*(prim_road_km2+sec_road_km2+ter_road_km2)*lo ss)/tot_pop Sources. • Total water consumed by the city [47]. • Loss of water per net length [47]. • Energy consumption of the municipal water grid to supply 1 m3 of water [48]. • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. • Roads: Open Street Maps and Jordan Ministry of Transport spatial registries. • Built-up area: Developed by CAPSUS as explained in chapter 2.8. 95 Energy consumption for public lighting Description. Annual average energy consumption for public lighting per person. Measurement units. Kilowatts hour per person per year [kWh/capita/annum] Methodology. The energy consumption for public lighting (energy_lighting) considers the total number of bulbs in the city (tot_bulb), how many of these are LED bulbs (num_led), the voltage of conventional bulbs (volt_bulb) and LED bulbs (volt_led), the dalily number of hours day that the bulbs are on (h) and 365 days to calculate the annual energy required to illuminate the streets. This number is divided by the total kilometers of primary, secondary and tertiary roads in the city (prim_road_km + sec_road_km + ter_road_km) to obtain the energy required per kilometer of street. As the precise number of kilometers of street that the city will have is uncertain, this number is estimated by multiplying the total built-up area of the city (footprint_km2) by the kilometers of primary, secondary and tertiary roads per square kilometer that the city has in the base year (prim_road_km2 + sec_road_km2 + ter_road_km2). At last, the energy required per kilometer of street is multiplied by the estimated kilometers of street and divided by the total population (tot_pop) to obtain the annual per capita energy consumption for public lighting. Calculation. energy_lighting=((tot_bulbnum_led)*volt_bulb+num_led*volt_led)*hours_day*365/(prim_road_km+sec_road_km +ter_road_km+ped_road_km)*(prim_road_km2+sec_road_km2+ ter_road_km2)*footprint_km2/tot_pop Sources. • LED and common bulbs voltage [49] • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. • Roads: Open Street Maps and Jordan Ministry of Transport spatial registries. • Built-up area: Developed by CAPSUS as explained in chapter 2.8. 96 Energy consumption for solid waste collection Description. Average per capita energy consumed annually by the solid waste management system of the city, including collection, transportation and energy consumed in the landfill and transfer stations. Measurement units. Kilowatts hour per person per year [kWh/capita/annum] Methodology. The energy consumption associated with solid waste management (energy_swaste) embraces the energy consumed in every step the management system: solid waste collection (collection_energy), its transportation to the transfer stations and/or landfills (transport_energy), the energy consumed in the transfer station (TS_energy) and the energy used in the landfill (landf_energy). The result of this sum is divided by the total population (tot_pop). The first step is to calculate the energy used in the collection stage (collection_energy). This includes the efficiency of the collection truck (truck1_ef) in liters of diesel consumed per km, multiplied by the diesel density (diesel_den), the diesel calorific value (diesel_cv) and the total of kilometers traveled in a year, which is estimated by multiplying the kilometers of primary roads per km2 (prim_road_km2) by the percentage of the primary roads that the truck uses (prim_road_fact) plus the kilometers of secondary roads per km2 (sec_road_km2) multiplied by the percentage of the secondary roads that the truck uses (sec_road_fact) plus the kilometers of tertiary roads per km2 (ter_road_km2) multiplied by the percentage of the tertiary roads that the truck uses (ter_road_fact). All the last is multiplied by the number of times the truck collects garbage per week (collections) and multiplied by the weeks of the year. Then, this total is multiplied by the total built-up area (footprint_m3) to obtain the energy used by the truck per year. Additionally, is important to add the energy used by the truck’s compactor system, to calculate this part is necessary to multiply the compactor efficiency in m3 of diesel by m3 of garbage (comp_ef) by the diesel density (diesel_den) and the diesel calorific value (diesel_cv). 97 Then multiply the result by the total population (tot_pop) multiplied by the waste generation per person per day (waste_per) multiplied by 365 days per year, all between the waste density (waste_density). The second stage is the energy used by the waste transport (transport_energy) from the center of the city to the transfer stations and from the transfer stations to the landfill, if there are not transfer stations it is assumed that the transport is from the center of the city to the landfill area. The first part assumes that there are not transfer stations, it includes the efficiency of the collection truck (truck1_ef) converted to m3 per km multiplied by the diesel density (diesel_den) and the diesel calorific value (diesel_cv). Then is multiplied by the total waste volume collected annually (tot_wvol) divided by the capacity of the collection truck (truck1_cap), multiplied by the average of the distances from the center of the city to the landfill or landfills (dist_land). The second part of the calculation assumes one or more transfer stations exist, therefore it is the same than the first part but multiplied by the average of the distances from the center of the city to the transfer stations (dist_ts) and plus the efficiency of the transfer station truck (truck2_ef) converted to m3 per km multiplied by the diesel density (diesel_den) and the diesel calorific value (diesel_cv) and multiplied by the total population (tot_pop), the waste generation per person per day (waste_per), 365 days per year, and divided by the capacity of the transfer station truck (truck2_cap) multiplied by the average of the distances from transfer stations to the landfill (dist_tsland). The third stage is the energy consumed in the transfer stations (TS_energy) which includes the multiplication of the total population (tot_pop) by the waste generated per person per day (waste_per) multiplied by 365 days per year, multiplied by the energy consumed by the waste segregation machinery (energy_tonTS). The fourth and last stage is the calculation of the energy consumed in the landfill. This is obtained by multiplying the total population (tot_pop) by the waste generation per person per day (waste_per) by 365 days per year, divided by the efficiency of the landfill in ton per year (land_ef), all multiplied by the efficiency of the landfill trucks (truck3_ef). 98 Calculation. energy_swaste=(collection_energy+transport_energy+TS_energy+landf_energy)/tot_pop collection_energy=truck1_ef/1000*diesel_den*diesel_cv*(prim_road_km2*prim_road_fact/100+sec_road_km2* sec_road_fact/100+ter_road_km2*ter_road_fact/100)*collections*52*footprint_km2+comp_ef/1000*diesel_de n*diesel_cv*tot_pop*waste_per*365/1000/waste_density transport_energy=(((truck1_ef/1000)*diesel_den*diesel_cv)*(((tot_pop*waste_per*365)/1000))/truck1_cap)*d ist_land)+(((truck1_ef/1000)*diesel_den*diesel_cv)*(((tot_pop*waste_per*365)/1000))/truck1_cap)*dist_ts)+( ((truck2_ef/1000)*diesel_den*diesel_cv)*(((tot_pop*waste_per*365)/1000))/truck2_cap)*dist_tsland) TS_energy=((tot_pop*waste_per*365)/1000))*energy_tonTS landf_energy=(((tot_pop*waste_per*365)/1000))/land_ef)*truck3_ef Sources. • Solid waste generation and efficiencies and capacities of the trucks: Obtained from the cities municipalities. • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. • Roads: Open Street Maps and Jordan Ministry of Transport spatial registries. • Built-up area: Developed by CAPSUS as explained in chapter 2.8. Energy consumption for dwellings Description. Average annual housing electricity consumption per capita. Measurement units. Kilowatts hour per person per year [kWh/capita/annum] 99 Methodology. The annually energy consumed per person in housing units (energy_buildings) reflects the energy savings expected from implementing a Green Building Code in the houses to be built between the base year and the horizon year (HU_new). It is estimated by multiplying the number of housing units existing in the base year (HU_existing) by the average energy consumption per household established as baseline (ener_baseline), plus the multiplication of the new houses (HU_new) by the penetration percentage of the green building code (GBC_pen /100) by the reduced energy consumption per household (GBC_ener), plus the multiplication of the new houses (HU_new) by the percentage that do not implement the green building code (1-GBC_pen/100) by the baseline housing unit energy consumption (ener_baseline). This total volume is then divided by the total population (tot_pop) to obtain the annual housing energy consumption per capita (energy_buildings). The number of new housing units (HU_new) is calculated as the difference between the total number of housing units in the horizon year (HU_tot_h) and the total number of housing units in the base year (HU_tot_b). Calculation. energy_buildings=(HU_existing*ener_baseline+(HU_new*(1GBC_pen/100)*ener_baseline+HU_new*GBC_pen/100 *GBC_ener))/tot_pop HU_existing=HU_tot_b HU_new=HU_tot_h-HU_tot_b Sources. • Energy of equipment: Energy of air conditioner, heater and lighting [44]. • Saving of equipment: Obtained from the USA Environmental Protection Agency (EPA) • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. • Roads: Open Street Maps and Jordan Ministry of Transport spatial registries. • Built-up area: Developed by CAPSUS as explained in chapter 2.8. 100 Infrastructure costs Description. Total investment required to build the roads, water network, sewer network, public lighting and electricity grids for the square kilometers that the city will expand, and the investment required to increase the capacity of the existing networks were the urban population will have a two-fold increase. Measurement units. Jordan dinars [JD]. Methodology. The infrastructure costs indicator is the sum of the investment required to build the infrastructure of the city’s expansion (infrastructure_new_costs) and to upgrade the areas of the city that will increase their population (infrastructure_infill_costs). Calculation. Infrastructure_costs=Infrastructure_new_costs + Infrastructure_infill_costs Infrastructure costs for urban expansion Description. Total costs to build the roads and water, sewage, public lighting and electricity networks of the km2 that the city is estimated to grow. Measurement units. Jordan dinars [JD]. 101 Methodology. Combines the parametric costs to build the infrastructure of one new km2 of city by the total km2 of urban expansion. Infrastructure costs embrace construction costs per kilometer of primary road (cost_prim_road), secondary road (cost_sec_road), tertiary road (cost_ter_road), municipal water network (cost_water), sewage (cost_swge), electric grid (cost_elec) and public lighting (cost_light). Construction of roads considers walkways and road pavement. As the precise number of kilometers of street that the city will have is uncertain, this number is estimated by multiplying the total built-up area of the city (footprint_km2) by the kilometers of primary, secondary and tertiary roads per square kilometer that the city has in the base year (prim_road_km2 + sec_road_km2 + ter_road_km2). This estimate is multiplied by each of the parametric costs to obtain the total infrastructure costs of expanding the city. Calculation. infrastructure_new_costs = ((cost_prim_road * prim_road_km2) + (cost_sec_road *sec_roads_km2) + (cost_ter_road * ter_roads_km2) + ((cost_light +cost_elec+cost_water+ cost_swge) * (prim_road_km2 + sec_roads_km2 + ter_roads_km2))) * land_consumption_km Infrastructure costs for upgrading existing capacity Description. Total costs to upgrade the water, sewage and electricity networks of the areas of the existing city that are estimated to have a two-fold increase in their population. Measurement units. Jordan dinars [JD]. 102 Methodology. Considers costs associated with retrofitting the infrastructure needed to promote infill development. Includes parametric costs of water pipes retrofit (retro_watr), electricity lines retrofit (retro_elec), and sewer infrastructure retrofit (retro_swge) per km2 that needs to be retrofitted to cope with the demand of the new population density. The parametric costs are then multiplied by the number of kilometers of primary, secondary and tertiary roads per square kilometer of city (prim_road_km2 + sec_roads_km2 + ter_roads_km2), and by the amount of total land designated for infill development (infill_area_km2). If the infill area is not indicated by the user, it is calculated as the sum of the areas of all points of analysis that had population since the base scenario (pop0>0) and their population had a two-fold increase or more, i.e. that the population in the scenario of analysis (popi) is twice or more than the population in the base scenario (pop0), which was higher than 0. Calculation. infrastructure_infill_costs=(retro_elec+retro_watr+retro_swge)*(prim_road_km2+sec_roads_km2+ter_roads_km2) *infill_area_km2 infill_area_km2=0.01*sum of area where pop0>0 and popi/pop0>=2 Water consumption Description. Total average volume of water consumed per capita in the households of the city in one year. Measurement units. Cubic meters per person per year [m3/capita/annum] 103 Methodology. The total volume of water consumed annually per capita (tot_water) reflects the water savings expected from implementing a Green Building Code in part of the new houses to be built between the base year and the horizon year (HU_new). It is estimated by multiplying the number of housing units existing in the base year (HU_existing) by the average consumption of water per household established as baseline (HU_water0), plus the multiplication of the new houses (HU_new) by the penetration percentage of the green building code (GBC_pen /100) by the reduced water consumption per household (HU_water1), plus the multiplication of the new houses (HU_new) by the percentage that do not implement the green building code (1-GBC_pen/100) by the baseline housing unit water consumption (HU_water0). This total volume of water is then divided by the total population (tot_pop) to obtain the annual water consumption per capita. The number of new housing units (HU_new) is calculated as the difference between the total number of housing units in the horizon year (HU_tot_h) and the total number of housing units in the base year (HU_tot_b). Calculation. tot_water=((HU_existing*HU_water0)+(HU_new*(1(GBC_pen/100))*HU_water0+(HU_new*(GBC_pen/100)*HU _water1))/tot_pop HU_existing=HU_tot_b HU_new=HU_tot_h-HU_tot_b Sources. • Average water savings per equipment (toilets, showerheads, sinks and washing machine) [50] • Total houses from the Population and housing census 2015 [2]. Job proximity Description. Percentage of the population that lives within a distance of 1,000 meters from the areas of high job density of the city. Measurement units. Percentage [%] 104 Methodology. This indicator identifies the areas of the city that concentrate employment and then quantifies the population that lives close to these areas as a percentage of the total city population. The process is divided in 4 stages: First, job density is quantified for each analysis point within a 250x250 meters grid. Job density (job_density) is measured as the number of jobs in a radius of 1,000 meters divided by the area of that circle, i.e. by 314.16 hectares. Second, a buffer of the maximum distance recommended (max_dist_job) is created from the center of each analysis point with a job density equal or higher than the minimum job density recommended (min_job_density). Third, the population (pop) of all the analysis points contained in the buffer is added up. This is the population that lives close to high job density areas (pop_prox_job). Fourth, this population is divided by the total population of the city (tot_pop) to obtain the percentage of the population that lives close to employment (job_prox). Calculation. job_prox=pop_prox_job/tot_pop pop_prox_job=sumpopif(distance<=max_dist_job) from (job_density>min_job_density) max_dist_job=800m min_job_density=10 jobs per hectare If jobs_lever = 0 job_prox = ( subset(pop_prox_job, footprint_base) + pop_expansion * d_job_prox) / tot_pop Sources. • Number of jobs: Obtained of an estimate of gross domestic product (GDP) derived from satellite data made by the National Oceanic and Atmospheric Administration (NOAA) [36] [30]. • Population: Population and housing census 2015, table 3.1 “Total population” by block or neighborhood [2]. 105 Proximity to public transport Description. Percentage of the population that lives within walking distance from a public transport station. Walking distance is considered to be 800 m for structured transport systems like a BRT or subway, and 300 m for buses and similar. Measurement units. Percentage [%] Methodology. Public transport proximity (transit_prox) is calculated by dividing the population (pop_prox_transit) that lives within the maximum distance recommended to a public transport station (max_dist_transit), by the total population (tot_pop). First, a buffer of the maximum distance recommended (max_dist_transit) is created from the center of each public transport station. Second, the population (pop) of all the neighborhoods or blocks contained in the buffer is added up to obtain the population that lives close to public transport (pop_prox_transit). Third, this population is divided by the total population of the city (tot_pop) to obtain the percentage of the population that lives close to public transport (transit_prox). Calculation. transit_prox=pop_prox_transit/tot_pop pop_prox_transit=sumpopif(distance<=max_dist_transit) If transit_lever=0 transit_prox=(subset(pop_prox_transit,footprint_base)+pop_expansion*d_transit_prox)/tot_pop Sources. • Public transport stations: Municipalities of the cities and Ministry of Transport city registries. • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. Desirable range. 80% to 100% 106 Services proximity Description. Percentage of the population with access to each of the following urban public services and amenities: schools (elementary, secondary or high school), universities, health facilities (clinics and hospitals), nurseries, public buildings, cultural spaces (community centers, libraries, theaters), worship places, markets, sport facilities, and public spaces. One indicator is calculated per each urban service or amenity. Measurement units. Percentage [%] Methodology. One indicator is calculated for each of the following classes of amenity: school, university, health facility, nursery, public building, cultural facility, place of worship, market, sports and public space. The proximity is calculated for each amenity class by dividing the population (pop_prox_ami) that lives within the maximum distance recommended for that type of amenity (max_disti), by the city’s total population (tot_pop). Table A.1 shows the maximum distance considered for each indicator. Table A.1: Classes and maximum distance recommended Class Landmarks Maximum distance School Elementary school, secondary school and high school 700m Health Clinic, doctors, hospital 1500m Public building Public building, town hall 2000m Cultural facility Community center, library, social facility, theater 1000m Place of worship Mosque, Church 1000m Sports Sport field or court, Pitch, swimming pool 1000m Public space Park, garden, public space 700m 107 Calculation. amen_proxi=(pop_prox_ami)/tot_pop pop_prox_ami=sumpopif(distance<=max_disti) If amenity_lever=0 amen_prox=(subset(pop_prox_am,footprint_base)+pop_expansion*d_amen_prox)/tot_pop Municipal service costs Description. Average per capita annual municipal expenditure needed to provide public lighting, potable water, and solid waste collection services and maintenance to the city roads. Measurement units. Jordan dinars per capita [JD/person] Methodology. The annual municipal expenditure in public services per person (municipal_service_costs) is estimated from the energy needed to provide public lighting (energy_lighting) in all the streets of the city multiplied by the cost the municipality pays per each kWh of electricity consumed for public lighting (elighting_cost), plus the energy needed to provide potable water (energy_water) multiplied by the cost the municipality pays per each kWh of electricity consumed for provide potable water (ewater_cost), plus the diesel consumed by the trucks used for solid waste collection and management (energy_swaste) multiplied by the cost of one liter of diesel (diesel_cost), plus the average amount of money that the municipality spends to maintain one kilometer of road (road_maintenance) multiplied by the road kilometers per square kilometer of the city (prim_road_km2+sec_roads_km2+ter_roads_km2), by the built-up area of the city (footprint_km2) and divided by the total population (tot_pop) to obtain the municipal expense per capita. Calculation. municipal_service_costs = energy_lighting*elighting_cost + energy_water*ewater_cost + ( diesel_cost*1000 * (collection_energy+transport_energy) / (diesel_den*diesel_cv) + road_maintenance* (prim_road_km2 + sec_roads_km2 + ter_roads_km2) * footprint_km2 ) / tot_pop Sources. • Population: Population and housing census 2015, table 3.1 “Total population” by neighborhood [2]. • Roads: Open Street Maps and Jordan Ministry of Transport spatial registries. • Built-up area: Developed by CAPSUS as explained in chapter 2.8. • Diesel calorific value and density [46] 108 Exposure to hazards Description. Percentage of the population that is exposed to hazardous pollutants for living in the outreach of human-made stationary sources of pollution. Measurement units. Percentage [%] Methodology. Exposure (hazard_exp) is calculated by dividing the population that lives within the outreach distance (outreach) of a hazardous source of pollution (pop_prox_hazards) by the total population (tot_pop). First, a buffer of the outreach distance (outreach) is created from the center of each human-made stationary source of pollutants. Second, the population (pop) of all the analysis points contained in the buffer is added up to obtain the population exposed to hazards (pop_prox_hazards). Third, this population is divided by the total population of the city (tot_pop) to obtain the percentage of the population that is exposed to hazardous pollutants (hazard_exp). Table A.2 shows the outreach distance per type of hazard. Table A.2: Outreach distance Type of hazard Outreach distance Outreach of sources of suspended particulate 1000m Outreach of water borne hazards 700m Calculation. hazard_exp=(pop_prox_hazards)/tot_pop Sources. • Hazards location obtained from the cities’ municipalities. pop_prox_hazards=sum pop if (distance <= outreach) 109 Annex 10: Policy levers definition for the UGS in Jordan Urban growth The following three policy levers define how the population will settle in the future, and hence, how the urban area will expand: 1. Settlement lever: Defines how the population that is expected to increase by 2030 will settle. It chooses between occupying the modelled urban expansion with no restrictions, settling in the areas planned in the Master Plan, or prioritizing infill in areas close to jobs and public transportation. 2. Vacant housing lever: Reduces the vacant housing rate in the city to 8% by assuming that new inhabitants will occupy the existing empty dwellings. 3. Master plan lever: Changes the land uses and restrictions in the maximum number of housing units allowed in each zone of the city. The five Jordanian cities were assessed using the settlement and vacant housing levers, but the master plan lever was prepared only for Amman. Since Amman is already building the first phase of the BRT, which will travel from east Amman to central areas of the city, the lever aims to analyze the possible effects of increasing the maximum number of housing units allowed along this first BRT corridor. Land use will remain the same, but residential areas will experience a twofold increase in the number of permitted dwellings Table 10.1: Settlement policy levers City Level Policy lever name 0 Settlement in new urbanized areas, expanding the city Amman 1 Settlement near employment and public transportation 2 Settlement according to the Master Plan 0 Settlement in new urbanized areas, expanding the city Irbid 1 Settlement near employment and public transportation 2 Settlement according to the Master Plan 0 Settlement in new urbanized areas, expanding the city Mafraq 1 Settlement near employment and public transportation 2 Settlement according to the Master Plan 110 Russeifa 1 Settlement near employment and public transportation 2 Settlement according to the Master Plan 0 Settlement in new urbanized areas, expanding the city Zarqa 1 Settlement near employment and public transportation 2 Settlement according to the Master Plan Table 10.2: Vacant housing policy levers City Level Policy lever name 0 Keep existing vacant housing rate Amman 1 Reduce vacant housing rate to 8% 0 Keep existing vacant housing rate Irbid 1 Reduce vacant housing rate to 8% Mafraq 0 Keep existing vacant housing rate 1 Reduce vacant housing rate to 8% Russeifa 0 Keep existing vacant housing rate Zarqa 1 Reduce vacant housing rate to 8% 111 Table 10.3: Master plan policy levers City Level Policy lever name 0 Current Master Plan and building norms Amman Modified Master Plan increasing the number of dwellings by 2 1 allowed along the new BRT lines Solid waste management improvements Currently, Jordan generates about 2 million tons of municipal solid waste (MSW), 45,000 tons of industrial waste, and 4,000 tons of medical waste per year. MSW collection coverage is estimated at about 90% in urban areas and 70% in rural areas [6]. The final destination of MSW is divided between recovered and landfilled waste: 7% is informally recovered, 48% is sent to the sole engineered landfill in the country, and 45% is taken to one of the 20 existing dumpsites in Jordan [6]. The total cost of solid waste management in the country is 55 million JD per year. In some Jordanian cities, the waste problem has escalated; this has been caused mainly by urban expansion. In cities such as Amman, Irbid, Mafraq, Zarqa, and Russeifa, the issue of solid waste management is of particular concern due to the lack of collection and transfer stations. The lack of infrastructure has resulted in the collection trucks having to travel longer distances to the dumpsites and the landfill, increasing collection intervals and total management costs. Part of the solution is the construction of transfer stations. These buildings help reduce the distance travelled by each collection truck. This will in turn allow the cities to utilize trucks that carry at least twice the volume carried by the current low capacity trucks. This can potentially reduce management costs and allow for more efficient use of the collection trucks. Another relevant improvement is the creation of new landfills, which would reduce the environmental and public health risks posed by open dumpsites. Although only the technical experts from the Greater Amman Municipality shared specific details of their plans for two new transfer stations, and only Mafraq officials provided information regarding current collections and trips to the dumpsite, all Municipalities expressed their concerns for improving their solid waste management systems. For this reason, relevant policy levers were proposed for the five cities, as shown in Table 2.5. 112 Table 10.4: Solid waste management policy levers City Level Policy lever name 0 Existing landfill and transfer station Amman 1 Two new transfer stations 0 Existing landfill and transfer station Irbid 1 New transfer station Mafraq 0 Existing dumpsite 1 New transfer station and landfill 0 Existing landfill Russeifa 1 New transfer station 0 Existing landfill Zarqa 1 New transfer station Public transportation expansion In Jordan, transportation problems are some of the most challenging to address. The main problems include congestion, an increase in car ownership ratio, road capacity problems, lack of reliable public transportation systems, and an absence of BRT and light and national railway systems. These problems may cause increased travel times, travel costs, air pollution, and accident risks [7]. The solutions mentioned by local counterparts during the second round of workshops focused on increasing the width and capacity of the roads and providing more parking spaces. Several studies, however, have proven that individuals drive more when the stock of roads and parking in their city increases (which is called induced demand), and that this increment in driving offsets the benefits [8–10]. For this reason, the policy levers included in this study focus on measures from the demand side: providing more and better public transportation to reduce the number of individuals riding alone. 113 The policy levers tested in this study include the public transportation expansion plans for Irbid bus routes, the BRT line under construction in Amman, and the planned BRT traveling from Amman to Zarqa. During the first workshop in the Zarqa Municipality, local officials mentioned that the BRT should not end in downtown Zarqa, but should continue to Hashemite University. Therefore, this extension to Hashemite University was included as another lever. In addition, two alternative BRT routes were proposed by this team: one from Zarqa to Amman but through Russeifa, and a BRT line east of Amman. The specific public transportation policy levers used for the five cities included: Table 10.5: Public transportation policy levers City Level Policy lever name 0 Existing transport routes Amman 1 Planned bus routes and BRT line 2 Proposed BRT line in East Amman 0 Existing transport routes Irbid 1 9 Planned bus lines Mafraq 0 Existing transportation routes 0 Existing transportation routes 1 Planned BRT on highway Russeifa 2 Proposed BRT through the city 0 Existing transportation routes 1 Planned BRT on highway Zarqa 2 Continue BRT to University Green building code Until the 1970s, the way of life, urban planning, and building construction in the Arab world followed what would qualify as green practices. Unfortunately, after the oil boom, this trend was reversed due to increased wealth and consumerism in the region [11]. In the context of Jordan, traditional buildings were following the same tendencies as the Arab world. However, due to urbanization and population growth, there was a change in building patterns, land use, zoning, and technology. A shift towards green building concepts and sustainability in the way buildings are designed, constructed, and operated is crucial in minimizing the negative impact on the natural environment, especially given the water and energy constraints of the country. 114 As part of Jordan’s efforts to tackle the water and energy limitations, the Jordan National Building Council developed the “Energy Efficiency in Buildings Code” to improve thermal performance and minimize energy consumption in buildings; in November 2010, the new Green Building Guideline and Rating System of Jordan was approved [12]. The green building guideline and rating system is currently referred to as Jordan’s compulsory Building Code; the challenge now is to enforce the Building Code in all future houses. For this reason, the proposed policy lever tests different percentages of penetration of the Green Building Code, ranging from 0% to 90% of the new houses expected to be built by 2030. It was assumed that a house built according to the Green Building Code would install the following mandatory energy saving technologies: Energy • Efficient light bulbs: 30% energy savings • Heater: 43% energy savings • Air conditioning: 30% energy savings In order to address the water issues, the following water saving technologies that have proven their viability in other developing countries were added: Water • Toilet: 20% water savings • Sink: 40% water savings • Shower head: 60% water savings • Washing machine: 50% water savings If all of the above measures were combined, energy consumption per housing unit would decrease from 12,724 KWh per year to 11,686 KWh per year; additionally, water consumption would decrease from 518m3 per year to 330m3 per year. An extended description of this calculation can be examined in Annex A. The specific green building code policy levers used for the five cities included: 115 Table 10.6: Green building code policy levers City Level Policy lever name 0 Penetration in 0% of new housing units Amman 1 Penetration in 14% of new housing units 2 Penetration in 90% of new housing units 0 Penetration in 0% of new housing units Irbid 1 Penetration in 14% of new housing units 2 Penetration in 70% of new housing units 0 Penetration in 0% of new housing units Mafraq 1 Penetration in 14% of new housing units 2 Penetration in 70% of new housing units 0 Penetration in 0% of new housing units 1 Penetration in 14% of new housing units Russeifa 2 Penetration in 70% of new housing units 0 Penetration in 0% of new housing units 1 Penetration in 14% of new housing units Zarqa 2 Penetration in 70% of new housing units Clean energy generation In 2006, Jordan contributed about 28,717 gigagrams or 28.72 million tons of CO2eq of GHG to the atmosphere, of which 72.9% came from the energy sector, followed by 10.6% from the waste sector and 8.9% from industrial processes. Regarding the energy sector, the subsectors that contributed the most are energy industries (27.6%), transportation (16.4%), and commercial and residential activities (10%) [13]. 116 Moreover, Jordan’s energy sector imports a large amount of oil and natural gas, and even electricity, which poses an enormous challenge in energy security. In recent years, the government has been promoting different measures to tackle this challenge, such as improving the efficiency of energy consumption and using renewable energy. Regarding the use of renewable energy, the government expects PV solar self- generation projects with electric power in homes and government institutions, banks, hotels, and hospitals to rise to 125 MW by 2020 [13]. Local counterparts from Amman expressed the city’s plans to have 16 MW in solar generation capacity, Irbid expects a 16 MW solar plant, and Zarqa anticipates a 15 MW solar plant. These plans have been added as policy levers in this study, as they affect the national energy mix and hence its GHG emissions. It was assumed that the added solar generation replaces the same amount of electricity imported. In addition, the effect of a 10 MW solar plant was tested for Mafraq and Russeifa. The specific policy levers used for the five cities included: Table10.7: Clean energy policy levers City Level Policy lever name 0 Do not increase solar power Amman 1 Increase solar power in 16 MW Irbid 0 Do not increase solar power 1 Increase solar power in 16 MW Mafraq 0 Do not increase solar power 1 Increase solar power in 10 MW Russeifa 0 Do not increase solar power 1 Increase solar power in 10 MW Zarqa 0 Do not increase solar power 1 Increase solar power in 15 MW 117 Efficient public lighting In Jordan, almost all households are served by fully or partially lit roads; on average, only 7% of the households are not served by lit roads [14]. Jordan consumes 337 GWh of electricity each year in street lighting alone, which represents 2% of the total electricity consumed [15]; thus, reducing this form of consumption is an important action for Jordan. The main improvement in public lighting consumption is the replacement of common street light bulbs with LED bulbs. This change can reduce electricity consumption by almost 58% [16], generating economic, electricity, and GHG savings. The five cities in this study mentioned that they had plans to replace all or a portion of their light bulbs; however, in this study, the policy lever tested for all cities was based on changing 100% of the street light bulbs to LED. The specific public lighting policy levers used for the five cities included: Table 10.8: Public lighting policy levers City Level Policy lever name 0 Changing to LED 50% of total light bulbs Amman 1 Changing to LED 100% of total light bulbs 0 Changing to LED 6% of total light bulbs Irbid 1 Changing to LED 100% of total light bulbs 0 Changing to LED 0% of total light bulbs Mafraq 1 Changing to LED 100% of total light bulbs 0 Changing to LED 0% of total light bulbs Russeifa 1 Changing to LED 100% of total light bulb 0 Changing to LED 0% of total light bulbs Zarqa 1 Changing to LED 100% of total light bulbs 118 Reduce hazards Air and water pollution continues to receive a great deal of attention worldwide due to its negative impacts on human health. Several studies reported significant correlations between air pollution and certain diseases, including shortness of breath, sore throat, chest pain, nausea, asthma, bronchitis, and lung cancer [17]. Also, water pollution can propitiate diseases, especially when water is contaminated with heavy metals [18]. In Jordan, there is a present concern about air pollution from cement and stone cutting industries and river contamination from wastewater. To diminish the effects of such pollution, some Jordanian cities have taken or plan to take some measures according to the type of contamination (airborne or waterborne). For artisanal industries, cities like Irbid, Mafraq, and Zarqa aim to enforce regulations or relocate the sources out of the city. Water contamination is much more difficult to control. In Russeifa and Zarqa, for example, a contaminated section of the Zarqa River passes by; the cities are aiming for a complete cleaning of the Zarqa river, and hope to generate a public space for people to gather [19]. In addition, Russeifa is concerned about other sources of pollution such as the phosphate piles generated by a mining company and the former landfill land [20]. The city wants to remove the phosphate piles and clean the former landfill soil to prevent any risks for the population. The policy lever considered in Irbid, Mafraq, and Zarqa was the control of artisanal industry air pollution. In Russeifa, the policy lever tested was the cleaning of phosphate lands and landfill soils. A lever modelling the recovery of the Zarqa River was also added in Russeifa and Zarqa. The specific hazard control policy levers used for the four cities included: Table 10.9: Hazards control policy levers City Level Policy lever name 0 Existing artisanal industry Mafraq 1 Control artisanal industry air pollution 0 Existing phosphate lands, polluted Zarqa River, and former landfill 1 Clean Phosphate lands, and landfill Russeifa 2 Clean Zarqa River, phosphate lands, and landfill 0 Existing artisanal industry and polluted Zarqa River 1 Control artisanal industry air pollution Zarqa 2 Clean Zarqa River and control artisanal industry air pollution 119 Public space The accessibility of people to urban services and facilities is an important component of the quality of life in a city [21]. In particular, public spaces have a central role, both physically and functionally, in urban planning and development. Urban theorists point out their significant role as one of the principal components of a healthy urban setting. Moreover, public spaces increase a sense of community when intensive social interactions take place in these areas. As is stated by many urban theorists, public spaces, such as neighborhood parks or community gardens, are one of the major elements that define the city’s unique attraction points. Furthermore, the importance of public spaces was examined during the first round of workshops, specifically in Russeifa and Zarqa, where an intense discussion took place. Some of the attendants questioned the impact of recently built large parks that were not located in proximity to the most populated areas of the city. From this experience and later meetings with local counterparts, several options for new parks were defined as policy levers for both cities. These included small but widely distributed parks in Russeifa, creating large parks in the ex-phosphate landsand in the former landfill, two parks at two specific points along the Zarqa River, and a linear park along the fully restored Zarqa River. In the city of Irbid, the policy lever embraces the parks that are already planned by the municipality. For Mafraq, the parks marked in the Master Plan were considered as one policy lever, but also local officials shared the idea of building a linear park in the former railway. The specific public space policy levers used for the five cities included: Table 10.10: Public spaces policy levers City Level Policy lever name Amman 0 Existing landmarks 0 Existing landmarks Irbid 1 Planned Parks 0 Existing landmarks Mafraq 1 Planned parks and railway linear park 120 0 Existing landmarks 1 Planned parks 2 Parks in ex-phosphate lands, landfill and planned parks Russeifa Zarqa River linear park, park in ex-phosphate lands and 3 planned parks 0 Existing landmarks in Open Street Maps 1 Two parks along River Zarqa and planned parks Zarqa 2 Zarqa River linear park and planned parks 121 Annex 11: Information and sources used in the final databases of the UGS in Jordan • Total population, total number of housing units, and total number of vacant housing units by neighborhood – Population and Housing Census 2015, Department of Statistics. • Population projections for the Kingdom by 2030 – Population projections 2015- 2050, Department of Statistics. • Public transportation routes (bus, service and collective taxi) – Municipalities and Ministry of Transport city registries. • Job density as an estimate from the gross domestic product (GDP) derived from satellite data, National Oceanic and Atmospheric Administration (NOAA). • Location of schools, health facilities, cultural facilities, places of worship, sport facilities and public spaces – Municipalities. • Primary, secondary, tertiary and pedestrian roads – Ministry of Transport. • Average water consumption per housing unit – Jordan Water Sector Facts and Figures 2015, Ministry of Water and Irrigation, Miyahuna Business Plan 2013- 2017. • Total electricity generation – National Electric Power of Jordan. • Emissions factors per type of generation – IPCC. • Construction cost of electric, water and sanitation networks – Public Works Departments within each Municipality. • Characteristics of the solid waste management system and the public lighting - Public Works Departments within each Municipality. 122 Annex 12: Scenarios modelled for five Jordanian cities More than five scenarios for 2030 were modelled for each Jordanian city. The scenarios for the Jordanian cities were defined by modelling a business-as-usual scenario (BAU scenario) and alternative scenarios that combine the policy levers mentioned in Annex 10. Two alternative scenarios were created by combining the three urban growth policy levers described in Annex 10. The Master Plan scenario assumes that no human settlements will occur outside of the zoned areas and the current building code restrictions. The Compact growth scenario models what would happen if the construction of new housing units is prioritized close to employment and public transportation, and a policy to reduce the vacant housing rate to 8% is enforced. Annex 7 describes in detail how urban growth is modelled for these scenarios. A Moderate scenario and a Vision scenario were created by blending the rest of the policy levers described in Annex 10 with the Master Plan and Compact growth scenarios, respectively. The Vision scenario takes some of the policy levers to a more ambitious level; for example, it simulates having a mandatory Green Building Code instead of the voluntary code from the Moderate scenario. Apart from these urban scenarios created for the forecasted year, a Base scenario represents the situation in 2015. The following paragraphs express the definition of each scenario. Figure 12.1 shows a graphical representation of the five scenarios for 2030, and figures 12.2, 12.3, 12.4, 12.5, and 12.6 summarize the policy levers that form the main scenarios for each city. 123 Figure 12.1 Five scenarios for the UGS in Jordan 124 Base scenario. Current conditions of the city by the year 2015. The boundaries of what is considered an urban area are defined in this scenario. It summarizes the population, employment density, landmarks, and other characteristics of the city in the base year. BAU scenario. Possible conditions by 2030 if the city expands according to historical growth patterns and new population occupies the urbanized areas. This scenario uses machine learning algorithms to forecast the urban expansion for the horizon year. These methods learn from the land use changes of the past to predict the non-urban areas that are likely to become urban in the future. Master Plan scenario. Possible conditions by 2030 if urban growth happens according to the Master Plan: New population settles according to historical growth patterns but within the zoned areas indicated in the Master Plan. If the maximum densities of the Master Plan are reached, settlement occurs in un-zoned areas within the municipality boundary. Moderate scenario. Possible conditions by 2030 if urban growth happens according to the Master Plan, the public transportation system grows according to current plans, parks included in the Master Plan are built, all public lighting uses LED bulbs, the Green Building Code is enforced in 14% of the new houses, solid waste transfer stations are built as well as solar farms with 10 MW to 16 MW of generating capacity, artisanal industry air pollution is controlled, and the ex-phosphate lands and former landfill in Russeifa are cleaned. Compact growth scenario. Possible conditions by 2030 if infill close to jobs and public transportation is prioritized, and the maximum housing densities indicated in the Master Plan are respected. If the maximum housing densities are reached, expansion takes place; otherwise, no new land is consumed. The vacant housing rate is reduced to 8%, assuming that the new population will occupy a portion of the existing vacant dwellings in the city. Vision scenario. Possible conditions by 2030 if the city follows compact growth (as in the Compact growth scenario); alternative BRT routes are built in Amman, Zarqa, and Russeifa in addition to the planned public transportation routes; planned parks are finished; the Zarqa River is fully cleaned and turned into a linear park in Russeifa and Zarqa; all public lighting uses LED bulbs; the Green Building Code is enforced in 70 to 90% of new houses; solid waste transfer stations are built, as well as solar farms with 10 MW to 16 MW of generating capacity; artisanal industry air pollution is controlled; and the ex-phosphate lands and former landfill in Russeifa are cleaned, along with the Zarqa River. 125 Figure 12.2 Scenarios for Amman Figure 12.3 Scenarios for Irbid Figure 12.4 Scenarios for Mafraq Figure 12.5 Scenarios for Russeifa 126 Figure 12.6 Scenarios for Zarqa 127 Bibliography 7 [1] Kumar Shoba and Loenard Aaron, The Art of Knowledge Exchange, A [8] Martino Pesaresi, Daniele Ehrilch, Aneta J. 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