Public Disclosure Authorized REIMAGINING CENTRAL ASIAN CITIES FOR A RESILIENT AND Public Disclosure Authorized LOW-CARBON FUTURE Public Disclosure Authorized Public Disclosure Authorized Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan © 2024 The World Bank Group 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org This work is a product of the staff of The World Bank Group with external contributions. “The World Bank Group” refers to the legally separate organizations of the International Bank for Reconstruction and Development (IBRD), the International Development Asso- ciation (IDA), the International Finance Corporation (IFC), and the Multilateral Invest- ment Guarantee Agency (MIGA). The World Bank Group does not guarantee the accuracy, reliability, or completeness of the content included in this work, or the conclusions or judgments described herein, and accepts no responsibility or liability for any omissions or errors (including, without limitation, typographical errors, and technical errors) in the content whatsoever or for reliance thereon. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank Group concerning the legal status of any territory or the endorsement or acceptance of such boundaries. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the organizations of the World Bank Group, their respective Boards of Executive Directors, and the governments they represent. The contents of this work are intended for general informational purposes only and are not intended to constitute legal, securities, or investment advice, an opinion regarding the appropriateness of any investment, or a solicitation of any type. Some of the orga- nizations of the World Bank Group or their affiliates may have an investment in, provide other advice or services to, or otherwise have a financial interest in, certain of the com- panies and parties named herein. Nothing herein shall constitute or be construed or considered to be a limitation upon or waiver of the privileges and immunities of any of the organizations of The World Bank Group, all of which are specifically reserved. Rights and Permissions The material in this work is subject to copyright. Because The World Bank Group en- courages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given and all further permissions that may be required for such use (as noted herein) are acquired. The World Bank Group does not warrant that the content contained in this work will not infringe on the rights of third parties and accepts no responsibility or liability in this regard. All queries on rights and licenses should be addressed to World Bank Publica- tions, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; e-mail: pubrights@worldbank.org. Attribution—Please cite the work as follows: World Bank. 2024. Huang, Chyi Yun; Eisenberg, Ross Marc; Velasco, Guillermo. Reimagining Central Asian Cities For A Resilient and Low-Carbon Future (English). Washington, DC: World Bank. REIMAGINING CENTRAL ASIAN CITIES FOR A RESILIENT AND LOW-CARBON FUTURE Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan Content Foreword 14 Acknowledgements 15 Abbreviations 16 Executive Summary 23 Context 23 Impetus of Study and Diagnostic Framework 24 Key Findings: Current Urbanization Situation in Central Asia 27 Way Forward to Achieve Resilient and Low-Carbon Cities 28 1 Introduction 33 Regional Context 33 Policy and Institutional Context 36 Rationale and Scope of Study 38 2 Urban and Spatial Profiles of 48 Cities 41 Macro Assessment Methodology 41 Key Findings on the Current Urbanization Situation in Central Asia 44 Regional Takeaways 79 3 Urban Growth Scenarios for 2050 in Five Cities 83 4 Lessons Learned from the Deep- Dive Analysis 99 5 Key Recommendations 103 Dimension 1: Livable Green Cities 105 Dimension 2: Easy Access to Infrastructure and Services 109 Dimension 3: Adapt to Natural Hazards and Climate Risks 112 Dimension 4: Mitigate Greenhouse Gas Emissions and Environmental Concerns 115 Dimension 5: Enhanced Access to Jobs 121 References 122 Appendixes 126 Figures Figure ES.1 Diagram Summarizing the Methodology Used 24 Map ES.1 CARL-Cities Study Areas 25 Figure ES.2 Modeling of Urban Growth Scenarios 26 Figure ES.3 Summary of Selected Indicators and Results from Scenario-Modeling 30 Figure 1.1 Urban Population in Central Asia 33 Figure 1.2 Urban Population Projections for Central Asia 34 Figure 1.3 Urban Population Projections in Central Asia, by Country 35 Table 1.1 Climate Change Commitments by Country 37 Map 2.1 CARL-Cities Study Areas 41 Map 2.2 Example Study Area: Almaty, Kazakhstan 42 Table 2.1 Set of Indicators for the Macro Assessment 43 Figure 2.1 Same Density in Two Different Urban Forms 44 Map 2.3 Urban Footprint Growth Between 1990-2020 in Nukus (UZB) 45 Figure 2.2 Urban Footprint Growth 1990-2020 46 Map 2.4 Figure 2.10 Population Density, Ashgabat (TKM) 47 Emission of Particulate Matter PM10 in the Urban Areas 63 Figure 2.3 Figure 2.11 Population Density in the Region 48 Emission of Particulate Matter PM2.5 in the Urban Areas 64 Table 2.2 Figure 2.12 Spatial Patterns Classification 49 GHG Emissions by Sector for Central Asia 65 Map 2.5 Figure 2.13 Examples of Spatial Development in Central Asia 50 GHG Emissions by Sector Per Country 66 Map 2.6 Figure 2.14 Leapfrog Urban Dispersion in Astana (KAZ) Greenhouse Gas Emissions Within the Functional (Fractal Degree 1.53) 50 Urban Areas 68 Map 2.7 Figure 2.15 Periurban Continuous Growth in Atyrau (KAZ) Average Annual Growth of Economic Activity (Fractal Degree 1.82) 51 Between 2012 and 2021 70 Figure 2.4 Map 2.12 Urban Dispersion in Central Asia 52 Change in Economic Activity from 2012 to 2021 in Turkestan (KAZ) 71 Figure 2.5 Urban Expansion Projections in CA (Based on SSPs) 53 Figure 2.16 Share of Population Living Within Economic Activity Clusters 72 Map 2.8 Quantity of Urban Amenities Within Walking Distance in Map 2.13 Oral (KAZ) 54 Job Concentration in Osh (KGZ) 73 Figure 2.6 Photo 2.1 Share of Population with Access to Urban Amenities 55 Trolleybus in Bishkek (KGZ) 74 Map 2.9 Figure 2.17 Urban Green Areas in Semey (KAZ) 57 Urban Mobility Infrastructure in CA Cities 75 Map 2.10 Map 2.14 Area Exposed to the UHI Effect in Temirtau (KAZ) 57 Accessibility to Bus Stops and Bicycle Parking in Samarkand (UZB) 76 Figure 2.7 Urban Green Areas Per Capita 58 Photo 2.2 E-Scooters as A Micromobility Alternative in Central Asia 77 Figure 2.8 Population Exposed to the UHI Effect 59 Figure 2.18 Intersection Density in CA Cities 78 Map 2.11 Area Exposed to Floods in Kyzylorda (KAZ) 60 Figure 3.1 Cities Selected for the Deep-Dive Analysis 83 Figure 2.9 Population Exposure by Type of Hazard 61 Figure 3.2 Figure 4.1 Deep-Dive Analysis: Modeling Urban Growth Scenarios 84 Summary of Selected Indicators and Results from Scenario Modeling 100 Table 3.1 Set of Indicators for the Deep-Dive Analysis 85 Figure 5.1 Key Recommendations and Actionable Items in Figure 3.3 Five Key Dimensions 103 Comparison of Projected Urban Expansion 87 Photo 5.1 Figure 3.4 AHURP Construction progress in Ulaanbaatar, Comparison of Projected Population Density 88 Mongolia 108 Figure 3.5 Photo 5.2 Expected Proximity Levels to Health Care Facilities 89 La Quebradora Park, Mexico City 114 Figure 3.6 Photo 5.3 Expected Proximity to Educational Facilities 89 Little Sugar Creek, Charlotte, North Carolina 115 Figure 3.7 Photo 5.4 Expected Proximity Levels to Public Spaces 90 Photovoltaic System for Residential Use 119 Figure 3.8 Photo 5.5 Expected Proximity Levels to Bus Stops 91 Jakarta Old Town, Kota Tua 120 Figure 3.9 Flood Hazard Exposure 92 Figure 3.10 UHI Hazard Exposure 92 Figure 3.11 Comparison of Projected Per Capita GHG Emissions 93 Figure 3.12 Comparison of Projected Per Capita PM2.5 Emissions 94 Figure 3.13 Comparison of Projected Water Consumption 95 Figure 3.14 Comparison of Projected Share of Wastewater Treatment 95 Figure 3.15 Estimated Solid Waste Collection Coverage 96 Figure 3.16 Estimated Share of Basic Infrastructure Costs 97 Figure 3.17 Estimated Capital Investment Costs for Implementing Recommended Interventions 97 Foreword Acknowledgements Building Resilient and Low-Carbon Cities in Central Asia: The Central Asia Regional Study on Resilient and Low-carbon Cities (CARL-Cities/ Study) was conducted by a core team led by Chyi-Yun Huang: Giuseppe Rossitti, A Pathway to a Sustainable Future and a Livable Planet Madina Nizamitdin, Faridun Sanginov, Marcus Lee, Tolkun Jukusheva, Rosanna Nitti, Mohamed Nada, Ildus Kamilov, and Manjusha Rai, with input from Oraz Sultanov, Kirtan Chandra Sahoo, Elena Strukova Golub, Susanna Dedring, Larissa Jenelle Duma, Saltanat Zhakenova, Aigerim Nurmakhanova, Antonio Nunez, and Dmitry Petrin. In a time when the clarion call for sustainability resonates across the globe, the focus on building resilient low-carbon The study received extensive technical support from the City Resilience Program cities has never been more pressing. Central Asia, with its unique challenges and opportunities, has embarked on a (CRP), and full participation by its team,. led by Robert William Pilkington and Ross transformative journey toward a sustainable future. The Reimagining Central Asia Cities for A Resilient and Low-Carbon Marc Eisenberg, with Leah Musenero and Danielle Monsef Abboud. Key diagnostics, Future (CARL-Cities) study presents an integrated approach that sheds light on the path to achieving this vision. spatial analysis, and scenario modeling were conducted by the team from Capsus, led by Guillermo Velasco with Bardo Salgado, Paul Cota, Andrea González, Antares Cities are pivotal in the global climate response, with the potential to contribute up to 40 percent of the emission reductions Velázquez, Dinorah León, Fátima Viquez, Jorge Márquez, Ricardo Ochoa and Socorro required to limit global warming to 1.5 degrees Celsius. Recognizing this immense potential, the CARL-Cities study Román, in association with the team from Juru, led by Khabibullo Negmatullaev with delves deep into the urbanization landscape of the Central Asia region, analyzing the patterns, trends, and challenges Ilia Gusev, Aigerim Urazgaliyeva, Amangul Ovezberdyyeva, Rustam Abdurazzakov, faced by its medium to large cities. The aspiration to cultivate cities that are both resilient and low-carbon is not merely Takhmina Turdialieva, Atai Samyibek and Abubakr Safarzoda. Administrative support an ambition; it is a necessary evolution. In the face of climate change and its myriad challenges, the strategies outlined was provided by Carine Ter-Alopova, Navruza Aliqulova, Aigerim Alpkarina, Ainura here offer a beacon of hope and a guide for action. They reflect a deep understanding of the unique challenges faced by Sydykova, Zhanna Amire, Rosa Alieva, and Elena Klementyeva. Central Asian cities, as well as the universal principles that underpin sustainable urban development. The team benefitted greatly from comments and advice received from peer reviewers The findings of the CARL-Cities study highlight the urgent need for decisive policy actions and concrete implementation Joanna Masic, Axel Baeumler, Victor Vergara, Paola Agostini, Xueman Wong, as well mechanisms at the subnational level. This study emphasizes the importance of engaging local stakeholders and fostering as excellent contributions from Ellen Hamilton, Urvashi Narain, and Jane people-centered urban planning and design. By promoting compact growth, appropriate densification, and people- Olga Ebinger. oriented urban forms, cities can free up resources that would otherwise be associated with unnecessary expansion, and create livable environments that enhance the quality of life for their residents. It also underscores the significance The study was prepared under the guidance and support of Indu John-Abraham, Andrei of investing in green infrastructure and nature-based solutions to mitigate the impacts of natural hazards as well as the Mikhnev, Naveed Hassan Naqvi, Ozan Sevimli, Marco Mantovanelli, Jean-Francois need to improve urban mobility and public transport, and decarbonize energy systems to significantly reduce emissions. Marteau, and the overall leadership of Christoph Pusch, Tatiana Proskuryakova and Sameh Naguib Wahba. This document is a call to action for policy makers, urban planners, industry leaders, and citizens alike. It is an invitation to embark on a collective journey toward a future where cities are not only the heartbeats of economic vitality but also The team is deeply grateful to the numerous government officials, technical experts, bastions of ecological harmony and resilience. and local stakeholders from the five Central Asian countries - Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan—as well as the five cities–Almaty, As we embark on this transformative journey, let us embrace the opportunities that lie ahead. By adopting ambitious Bishkek, Dushanbe, Namangan, and Shakhrisabz—for their active participation in yet achievable goals, we can build cities that not only mitigate climate change but also enhance the well-being and consultations, generous sharing of information, and their valuable insights. quality of life for all residents. Together, we can create a future in which Central Asia’s cities lead the way in sustainable development, setting an example for the world to follow. The study is made possible through the funding support of the City Resilience Program (CRP), the Climate Support Facility (CSF), and the Europe and Central Asia (ECA) Cities and Climate Change Program, under the Sustainable Urban and Sameh Naguib Wahba Regional Development (SURGE) multi-donor trust fund (MDTF). Regional Director, Sustainable Development Europe and Central Asia Region World Bank CSF Climate Support Facility Abbreviations DeHSt German Emissions Trading Authority ECA Europe and Central Asia region AHURP EDGAR Affordable Housing and Resilient Urban Renewal Project Emissions Database for Global Atmospheric Research AQI ESA Air Quality Index European Space Agency BAU ETS Business as Usual Emission Trading System BRT EV Bus Rapid Transit Electric vehicles CA FUA Central Asia Functional urban area CARL-Cities Gcal Central Asia Regional Study on Resilient and Low-carbon Cities giga calorie CCS GCAP Carbon Capture and Storage Green City Action Plan CH4 GDP Methane Gross domestic product CHP GEDS Combined heat and power Green Economy Development Strategy CHPP GFDRR Combined heat and power plant Global Facility for Disaster Reduction and Recovery CNG GFW Compressed natural gas Global Forest Watch CO2 GHG Carbon dioxide Greenhouse gas emissions CO2e GHS-FUA carbon dioxide equivalent Global Human Settlements Functional Urban Areas CRP GHSL City Resilience Program Global Human Settlement Layer GIS kWh Geographic information system Kilowatt hour GWh LCR Gigawatt hours Land consumption rate ha LEZ Hectare Low emission zone NDC LNG Nationally Determined Contributions Liquefied natural gas INDC LPG Intended Nationally Determined Contributions Liquefied petroleum gas inh LST Inhabitant Land surface temperature IPCC LULUCF Intergovernmental Panel on Climate Change Land use, land-use change, and forestry ISPU m Air Pollution Standard Index (Indeks Standar Pencemar Udara) Meter JRC MDTF Joint Research Centre Multi-donor trust fund KAZ MtCO2e Kazakhstan Megatonnes of carbon dioxide equivalent KGZ MW Kyrgyz Republic Megawatt kgCO2eq MWp Kilogram of carbon dioxide equivalent Megawatt-peak km N 2O Kilometer Nitrous oxide km2 NBS Square kilometer Nature-based solution KML NDVI Keyhole Markup Language Normalized Difference Vegetation Index KMZ NDS-2040 Keyhole Markup Language Zipped National Development Strategy 2018-2040 kWp NGO Kilowatt-peak Non-governmental organization NOAA TKM National Oceanic and Atmospheric Administration Turkmenistan NTL TOD Nighttime lights Transport-oriented development OECD tpa Organization for Economic Co-operation and Development tons per annum OSM TWh Open Street Maps Terawatt hours PGA UGA Peak ground acceleration Urban green area PGR UHI Population growth rate Urban heat island PM10 US-EPA particulate matter 10 microns Environmental Protection Agency of the United States of America PM2.5 USSR particulate matter 2.5 microns Union of Soviet Socialist Republic POI UZB Point of interest Uzbekistan PV VIIRS Photo voltaic Visible Infrared Imaging Radiometer Suite SEP WSUD Stakeholder engagement plan Water Sensitive Urban Design SFRARR WTE Strengthening financial resilience and accelerating risk reduction in waste-to-energy SME μm Small and medium sized enterprises microns SSP Shared Socioeconomic Pathways SURGE Sustainable Urban and Regional Development SWOT Strengths, weaknesses, opportunities, and threats TJK Tajikistan Context Executive summary Climate mitigation is a crucial issue in Central Asia (CA), where Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan rely heavily on carbon-based energy. For example, Kazakhstan’s energy sector accounts for country in CA to establish an emissions trading scheme. 78 percent of its emissions (OECD 2019). Central Asian Since 2019, Uzbekistan has focused on climate adaptation cities are among the world’s most polluted, especially in and renewable energy investment through key policy winter, due to coal and low-quality fuel use for heating. reforms. However, many strategies are ambitious but lack These countries have some of the highest greenhouse concrete implementation mechanisms, especially at the gas (GHG) emissions per unit of GDP globally, driven subnational level, where action is most needed. by energy-subsidized heavy industry, inefficient public buildings, and challenging geography with sparse Cities are pivotal in climate response, capable populations and cold climates. of achieving up to 40 percent of the emission reductions needed to limit global warming to 1.5 degrees Celsius Climate adaptation holds critical importance (C40 and ARUP 2016). Urban areas must lead climate for CA, a region highly vulnerable to natural change mitigation by reducing emissions and carbon disasters. Over the past two decades, 90 floods and 56 footprints. Simultaneously, cities can bolster adaptation earthquakes have affected 2.5 million people and caused and resilience by hazard-resistant infrastructure, over $1.5 billion in damages (Scaini 2022). Annually, improving institutional risk preparedness, developing these natural disasters cost CA countries between $3.5 long-term risk reduction strategies, and diversifying billion and $4.2 billion (World Bank 2023). Global warming access to climate adaptation funding. Additionally, urban is expected to worsen these issues, leading to more climate initiatives offer significant local cobenefits, further extreme heat, water scarcity, longer droughts, increased incentivizing action. storm variability and intensity, glacial melt, deforestation, and soil erosion, underscoring the need for integrated adaptation and resilience solutions. CA countries have taken steps toward resilient and inclusive growth, but local actions are needed. The Kyrgyz Republic, Tajikistan, and Uzbekistan have included resilience and climate vulnerabilities in their nationally determined contributions (NDCs). Kazakhstan aims for carbon neutrality in electricity and heat production by 2060, and is the first _______________________________ 1 See Global Flood Database. 2 Earthquakes with a Richter magnitude size above 6.3 based on the SFRARR Earthquake Catalogue. Source: CAPSUS, 2023, Shakhrisabz [Photograph] 22 23 Impetus of the Study, and Diagnostic Framework The Central Asia Regional Study on Resilient The study began by creating urban and spatial This study is a novel attempt to analyze the and Low-carbon Cities (CARL-Cities/Study) profiles for 48 cities, followed by a detailed is an innovative attempt to systematically analysis of five cities to project future patterns and trends of urbanization in medium understand urbanization and its potential scenarios and inform policy decisions (figure to large cities in Central Asia. It encompasses in CA. It analyzes urban growth trends in medium to ES.1 and map ES.1). It developed practical technical a broad range of parameters, and employs an large cities using comprehensive parameters and an evidence-based approach to promote green and resilient proposals for potential investment projects aligned with identified policy levers, providing cities with a strategic evidence-based approach to outlining strategic urban environments. The study enhances knowledge of advantage in achieving environmental goals. The process directions and actions for fostering green and local challenges and identifies actionable steps for cities across the five countries to develop low-carbon, climate- included extensive stakeholder consultations, workshops, and exchanges at national and subnational levels in all resilient urban development. resilient cities and regions. five countries. Figure ES.1 Diagram Summarizing the Methodology Used Map ES.1 CARL-Cities Study Areas Central Asia Region Small < = 250,000 inh Development of urban profiles for 48 Medium > 250, 000 inh < 1 million inh cities in terms of urban development, Large > = 1 million inh GHG emissions, and exposure to natural hazards. 1 Deep-dive analysis Kazakhstan 2 of five cities. Uzbekistan Kyrgyz Republic Methodology Identification of Main 2.1 Concerns and policy levers in collaboration with key Turkmenistan Tajikistan local stakeholders. While conditions differ among the five study 2.2 countries of Kazakhstan (KAZ), the Kyrgyz Republic (KGZ), Tajikistan (TJK), Definition of Future Turkmenistan (TKM), and Uzbekistan 2.4 2.3 Urban Growth Scenarios. The CARL-Cities Study Areas The selection of the study areas for the Macro Assessment (UZB), several common patterns prevail across the region, these include: includes all the 48 urban areas with population above 150,000 Elaboration of technical inhabitants and is based on the Global Human Settlements • Rapid urbanization Identification of potential analysis of 2 investment Functional Urban Areas (GHS-FUA) dataset, which delineates • Urban expansion investments projects. projects in each the commuting area of the local workforce in a given urban • Uneven densification selected city. area. Leveraging the FUA dataset allows the assessment to • Limited access to urban services have a common criterion across the region for every city in • Uneven economic development every country. A Micro Analysis was also conducted for the cities • High greenhouse gas emissions of Almaty, Bishkek, Dushanbe, Namangan and Shakhrisabz. • Climate hazards Source: CARL-Cities 2024. Source: CARL-Cities 2024. 24 25 The study conducted a comprehensive urban quantitative, qualitative, and spatial data to inform This report summarizes the study’s key findings and and spatial analysis for 48 urban areas in policy and decision-making. It compared two urban recommendations. The following background analysis Central Asia, identifying key urbanization and growth scenarios for 2050: No-Intervention and Vision, and technical resources produced through the study climate-related characteristics. It assessed which depict potential future outcomes for the cities complement the report: urban development across five main dimensions: urban based on the proposed policy levers, including policy form, urban services and amenities, urban environment, measures and investments. economic activity, and urban mobility. These urban areas, Diagnostic report on urban and spatial profile of 48 cities (complemented each with over 150,000 residents, comprise about 32.1 The analysis contrasted the two scenarios 1 by derived spatial data for each city, and associated appendixes on the methodology and percent of the region’s population3. The study leveraged on potential outcomes like GHG emissions, data sources). international databases to create a standardized vulnerability to natural hazards, service accessibility, measurement framework, allowing easy comparisons and sustainable urban development, emphasizing the Country summaries for each of the five CA countries, based on their urban and spatial across cities in the five Central Asian countries. impact of local decisions aligned with green growth. This 2 profiles. modeling aims to guide future policy and investment To explore pathways to a resilient and low- decisions. Consultations with key country and city Individual city reports capturing deep-dive analysis and scenario modeling carbon future, the study modeled scenarios stakeholders led to the selection of two climate mitigation 3 for the five selected cities--Almaty, Bishkek, Dushanbe, Namangan, and Shakhrisabz--and for 2050 in five cities: Almaty, Bishkek, and adaptation projects for each of the five cities, with associated appendixes on the methodology and data sources. Dushanbe, Namangan, and Shakhrisabz preliminary technical analysis conducted for these ten (figure ES.2). This in-depth analysis used potential investments. Technical analysis reports of proposed investments and urban solutions 4 for each of the ten potential investment projects. Figure ES.2 Modeling of Urban Growth Scenarios SCENARIO Within each city, the deep dive assessment encompasses the modeling development and analysis of Key Findings: Current Urbanization Situation in Central Asia two urban growth scenarios: ‘No-intervention’ and ‘Vision’ scenarios. Findings from the CARL-Cities study reveal a CA’s urban areas largely display unsustainable region that is experiencing a steady rise in spatial expansion patterns. Fifty-eight percent of urbanization while facing immense climate- the areas studied show a “leapfrog” development pattern, related challenges. While conditions differ among the while 39 percent are characterized by fragmented five countries studied, several common patterns prevail development. These types of urban expansion leave across the region. These include rapid urbanization, underused land and promote a dispersed, disconnected, urban expansion, uneven densification, limited access to and distant city structure. urban services, uneven economic development, a high level of greenhouse gas (GHG) emissions, and climate CA’s cities are economic drivers, but the hazards. economic growth rates vary considerably. Annual growth of economic activity for the 48 cities was Central Asia (CA) is urbanizing, and its cities 2.42 percent, with 64 percent of them experiencing some are expanding rapidly. The 48 urban areas studied growth. The largest cities observed an average growth No intervention The ‘No-intervention’ Vision scenario The ‘Vision scenario’ assumes grew by an average of 36.3 percent between 1990 and ranging from 3.9 percent to 4.5 percent per annum. assumes that no significant that all expected population 2020, with large urban areas growing at a faster rate than change will be made on growth will be accommodate the rest, both in terms of population and physical extent. Most of the urban areas in CA have critically urban policy and considers within the current urban footprint These large settlements account for almost half of urban low access to urban services, and amenities investments in basic due to densification strategies. infrastructure for expanding This scenario also incorporates land consumption in the region. In addition, the urban such as health and education facilities, the urban footprint. key urban policy measures and areas in CA have relatively low population density, with public spaces, sports, and cultural venues. capital investments. 25 percent of the studied areas experiencing a reduction The average share of the population in CA with walking in population density. accessibility to urban amenities is limited. Only 6.8 Source: CARL-Cities 2024. _______________________________ _______________________________ 4 The urban areas were classified based on its population into small cities (under 250,000 inhabitants), medium cities (between 250,000 and 3 Based on Population, total | Data for 2020. 1,000,000 inhabitants), and large cities (more than 1,000,000 inhabitants). 26 27 percent of the citizens are close to health clinics, 16.5 green areas. The cities analyzed in this report annually planning. Energy efficiency in buildings, industries, life, and redirect savings to sustainable projects. Nature- percent close to schools, 8 percent to public spaces, contribute a per capita average of 11.7 tons of CO2 eq and transport systems offers significant savings, while based solutions and resilient infrastructure are crucial for 8 percent to sports facilities, and 3 percent to cultural per capita (in GHG emissions) and 3.1 kg of PM10 (air cleaner energy solutions can reduce air pollutants and mitigating climate impacts like floods and UHI effects. centers. pollution). In addition, the cities studied have insufficient GHG emissions. These findings offer valuable insights for policymakers green areas. Most of the 48 CA cities have a very low and urban planners to guide cities toward sustainability Cities in CA face serious climate and provision of green areas, with a regional average of 7.6 Effective urban planning and strategic and resilience. environmental challenges. They are exposed m2 per capita, less than half the European average of investment in green infrastructure and nature- to natural disasters, urban heat, and air pollution. The 18.2 m2 per capita. based solutions are essential for adapting study reveals that 75.6 percent of the population is to climate impacts. Cities can reduce flooding located within an earthquake-prone area; 17 percent Cities offer major opportunities for achieving and landslide risks by limiting development in high-risk is exposed to the urban heat island (UHI)5 effect; 2.5 national emissions reduction commitments. areas and using appropriate construction methods and percent is at risk of being impacted by pluvial flooding; For instance, the city of Almaty (KAZ) plays a relevant technologies. Increasing green spaces and implementing 3.5 percent is at risk of being impacted by fluvial role in achieving the country’s carbon reduction passive building designs can mitigate urban heat island flooding; and 1.1 percent of the urban population could commitments. Kazakhstan has pledged to reduce its effects, especially in vulnerable areas. Nature-based be affected by landslides. Most of these natural hazards GHG emissions by 15 percent by the end of 2030 without solutions and green infrastructure are crucial for flood are exacerbated by climate change. significant international assistance. Achieving net-zero management and ecosystem conservation. emissions in Almaty alone could fulfill nearly 60 percent Engaging local stakeholders is vital for successful green CA cities contribute significantly to GHG and of the country’s reduction commitment. urban development. This study’s workshops, held with air pollutants, and they lack sufficient urban subnational and city officials helped validate and refine our understanding of the primary challenges and the viability of proposed solutions. These interactions Way Forward to Achieve Resilient and Low-Carbon Cities highlighted local concerns affecting residents’ quality of life, such as private vehicle use, energy production, waste management, public transport, and modernizing essential services and infrastructure. The green policies and investments proposed for these urban areas could reduce their GHG The study’s recommendations findings for led addressing to tailored urban emissions by half on average, and with similar or and climate challenges in the five selected cities. These recommendations include policies less costs than in a business as usual scenario. and projects to create livable, green cities; enhance access to infrastructure and amenities; adapt to and mitigate natural and climate impacts; and improve job A resilient, low-carbon future in CA cities can commitment and potential costs of achieving carbon accessibility. While broadly applicable across Central be achieved without significant additional neutrality. Asian cities, these recommendations are grounded in financial resources but through decisive policy local context and international best practices, providing interventions and strategic investments in Urban areas should pursue compact growth a roadmap for transitioning to a low-carbon, resilient sustainable infrastructure. Savings from compact and strategic densification to reduce costs, future. urban growth can significantly offset costs to achieve enhance quality of life, and achieve low- low-carbon, resilient development. Scenario modeling carbon development. Compact vertical development The CARL-Cities study shows that cities can (figure ES.3) shows similar capital investment costs for and strategically placed infrastructure can avoid the achieve a resilient, low-carbon future through both scenarios but vastly different benefits. For the five high costs of urban expansion while improving access smart urban policies and investments cities, the vision scenario could reduce GHG emissions to public services. This requires robust urban planning, without straining finances. By adopting compact by an average of 58 percent by avoiding costs related to people-centered design, effective development control growth, strategic densification, energy efficiency, cleaner urban sprawl and inefficient resource use. Almaty’s Vision and enforcement, as well as cross-sectoral interventions technology, and expanding green public transportation, scenario aims for net-zero emissions, demonstrating the such as integrating land use with urban transport cities can reduce GHG emissions, improve quality of _______________________________ 5 UHI was defined as those area with a temperature higher than 2 degrees above the annual average surface temperature. 28 29 Figure ES.3 Summary of Selected Indicators and Results from Scenario-Modeling Source: CARL-Cities 2024. Kazakhstan Almaty Kyrgyz Republic Bishkek Tajikistan Dushanbe Uzbekistan Namangan Uzbekistan Shakhrisabz 30 31 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 1 Introduction Regional Context Central Asia (CA) is characterized by its exacerbated issues like insufficient public transportation, landlocked geography, its post-soviet congestion, inefficient energy use, environmental economy, and the geopolitical significance degradation, and urban sprawl. of its neighbors. Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan all lack access Population growth in CA is strong but uneven to oceanic routes and they border Russia, China, (figure 1.1). Uzbekistan is the most populous with Afghanistan, and Iran (Dabrowski and Batsaikhan 2017). 34.9 million people, followed by Kazakhstan (19 million), The region’s cities were planned during the Soviet era to Tajikistan (9.7 million), Kyrgyz Republic (6.6 million), meet national economic needs, leading to single-focus and Turkmenistan (6.1 million) (UN DESA 2022). The cities (residential, manufacturing, etc.) that now face region’s population of 78 million in 2022 is expected to diversification challenges. Recent urban growth has grow to 102 million by 2050 (UN DESA 2018). Figure 1.1 Urban Population in Central Asia Population (millions) Turkmenistan Kazakhstan Uzbekistan Tajikistan Kyrgyz Republic 34,915 9,750 6,118 6,694 19,003 Source: United Nations, Department of Economic and Social Affairs, Population Division 2022. Population growth in the region has been Although this shows a positive trend, it is still below the driven by steady urbanization, with 49 percent urbanization rates of Latin America and the Caribbean of the population now living in urban areas, (82 percent), China (64 percent), and Europe (75 primarily in large cities6. The urban population has percent). The region also has many small and medium- grown from 9 million in 1970 to 38 million in 2022 and sized cities, a legacy of its rural, agrarian, and industrial is expected to reach 60 percent by 2050 (figure 1.2). economy planned around monofunctional cities. _______________________________ 6 The urban areas were classified based on population into small cities (under 250,000 inhabitants); medium cities (between 250,000 and 1,000,000 inhabitants); and large cities (more than 1,000,000 inhabitants). Source: CAPSUS, 2023, Namangan [Photograph] 32 33 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 1.2 Urban Population Projections for Central Asia Figure 1.3 Urban Population Projections in Central Asia, by Country Urban population projections for Kazakhstan Urban population projections for Kyrgyz Republic 100 25 20 7.5 Population [millions] Population [millions] 75 15 5.0 Population [millions] 10 2.5 50 5 0 0.0 1975 2000 2025 2050 1975 2000 2025 2050 Year Year 25 Rural population Urban population Rural population Urban population Urban population projections for Tajikistan Urban population projections for Turkmenistan 8 15 0 1975 2000 2025 2050 6 Population [millions] Population [millions] 10 Rural population Urban population 4 Source: United Nations, Department of Economic and Social Affairs, Population Division 2022. 5 2 The Central Asian countries are urbanizing at different rates (figure 1.3). In 2020, Kazakhstan and Turkmenistan had the highest urban populations at 0 0 57 and 53 percent, respectively, projected to reach 70 and 1975 2000 2025 2050 1975 2000 2025 2050 Year Year 68 percent by 2050. Tajikistan, while strongly urbanizing, Rural population Urban population Rural population Urban population will remain predominantly rural, increasing from 25 to 43 percent urban by 2050. Similarly, Uzbekistan’s urban population is estimated to be 49 percent, while the Urban population projections for Uzbekistan Kyrgyz Republic is estimated to be 37.8 percent urban, with most residents in rural areas by 2050. 40 Population [millions] 30 20 10 0 1975 2000 2025 2050 Year Rural population Urban population Source: United Nations, Department of Economic and Social Affairs, Population Division 2022. 34 35 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Policy and Institutional Context Table 1.1 Climate Change Commitments by Country Central Asian countries are implementing 2022-2026” strategy calls for climate change adaptation long-term sustainability measures by setting measures but provides no specifics. Tajikistan’s 2030 climate-resilient targets within national Strategy views climate change through an environmental Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan development frameworks. As part of their Intended quality lens and calls for adaptation measures. Target reduction Target reduction of Target reduction of Target reduction Target reduction GHG Nationally Determined Contributions (INDCs), they have of 15%–25% of of 20% of GHG emissions per unit of Objective 16%–43% of GHG 50%–70% of GHG greenhouse gas (GHG) set emission reduction goals (table 1.1)7. Kazakhstan Central Asian countries prioritize mitigation emissions by 2030 emissions by 2030 emissions by 2030 emissions in 2030 GDP by 35% by 2030 aims to reduce GHG emissions between 15 (unconditional in key sectors like energy, construction, A 15% reduction in Target reduction of 20% target) and 25 percent (conditional target) by 2030 and transportation, and waste management. The GHG emissions by A 16.63% and 15.97% Not to exceed 60–70% of GHG emissions in Unconditional reduction in GHG 2030 compared to the achieve carbon neutrality in electricity and heat production energy sector, particularly in Uzbekistan and Kazakhstan, December 31, 2030, of emissions from Not defined target emissions by 2025 and business as usual (BAU) compared to the 1990 levels by 2030 2030, respectively scenario relative to 2010 by 2060. The Kyrgyz Republic targets a 16 percent is a major focus due to its high carbon emissions. Efforts base year emission levels (unconditional target) and 43 percent (conditional target) include transitioning to low-carbon energy sources and A 25% reduction in Target reduction of Not to exceed 50–60% reduction by 2030. Tajikistan aims for a 30-40 percent expanding renewables like wind, solar, and biogas. Conditional GHG emissions by 2030. 43.62% of greenhouse of emissions from 1990 Not defined Not clearly defined target Subject to international gas emissions under the levels by 2030 (unconditional) reduction by 2030 from 1990 levels, with Since 2019, Uzbekistan has enacted policy reforms for investment BAU scenario by 2030 a conditional goal of halving emissions. Uzbekistan plans climate adaptation and renewable energy investment. Base year 1990 1990 1990 2010 2010 to reduce GHG emissions per unit of GDP by 35 percent Kazakhstan introduced an emission trading system (ETS) Period 2021 - 2030 2025 - 2030 2018 - 2030 2020-2030 2020-2030 from 2010 levels by 2030. Turkmenistan commits to a 20 in 2013 to curb GHG emissions in energy, industry, and -Energy -Energy -Energy -Industry -Agriculture, -Industrial processes and percent reduction from 2010 levels by 2035. oil and gas sectors (German Emissions Trading Authority Strategic -Agriculture -Forestry and other -Industry and construction -Energy product use (PPPU) sectors -Agriculture -Industrial processes -Waste types of land use -Agriculture 2017). However, sectoral documents often prioritize (mitigation) -Land-Use Change -Transport -Agriculture **Industrial processes -Waste -Forestry and other -Forestry and Urban planning in CA is integrated into national socioeconomic development and environmental quality -Forestry and use of products land uses biodiversity **Waste -Waste development documents. There are no standalone over climate change, and specific sectoral mitigation national urban plans, except in Kazakhstan, which has targets with quantifiable metrics are often lacking, limiting frameworks like the “National Project of Strong Regions,” progress tracking and resource optimization. Market- Source: National INDCDs. (Kyrgyz Republic 2021; Republic of Kazakhstan 2016; Republic of Tajikistan 2021; Republic of Turkmenistan the “Law on Agglomerations Development,” and the spatial based mitigation mechanisms remain largely unexplored. 2016; Republic of Uzbekistan 2021). development forecast until 2030. The Kyrgyz Republic’s urban targets are part of its National Development Adaptation efforts focus on enhancing environmental quality. Tajikistan’s Midterm Development Empowering subnational governments would Strategy 2040. Tajikistan, Turkmenistan, and Uzbekistan resilience in water, agriculture, energy, and Program until 2025 and the Kyrgyz Republic’s National enhance their ability to address climate give less prominence to urban planning in their national transportation sectors due to the region’s Development Program until 2026 also lack concrete change effectively. Limited engagement of urban plans. Uzbekistan created an Urbanization Agency and vulnerability to climate change. The agricultural climate resilience targets. Without national-level green areas in promoting a green, sustainable agenda poses a began developing an urbanization strategy, but the work and water sectors are prioritized due to threats from development agendas, city governments cannot commit challenge in aligning subnational and national objectives. was suspended in 2020, and the agency was disbanded. droughts and diminishing water flows, impacting food to low-carbon and climate-resilient objectives. Local governments, not involved in decision-making, and water security. Consequently, all of the countries lack guidance on translating national plans into local The climate change policy planning process incorporate this priority into their national documents. The In Central Asia, national climate strategies programs and have limited control over city planning and in Central Asia is supported by national Kyrgyz Republic and Tajikistan, reliant on hydropower, often overlook the roles of subnational management. strategies, plans, and policies. Key documents emphasize water and energy sector adaptation. Tajikistan authorities like regions and cities. National include national development strategies, national also focuses on adapting transportation infrastructure documents rarely specify urban or regional responsibilities Institutional strengthening and local capacity- adaptation policies, sectoral development strategies, and due to its mountainous geography. for adaptation, mitigation, and funding. Cities and regions building are critical for developing low-carbon, green economy programs. However, these documents typically lack the administrative and financial capacity resilient cities in Central Asia. While some local often include limited climate change considerations. For National development plans and strategies for independent low-carbon development. Exceptions policies align with national objectives, many lack specific example, Kazakhstan’s “Kazakhstan-2050” strategy aims often lack specific climate-related targets. include larger cities with special administrative status, targets and measurable goals for climate resilience and to transition to a low-carbon economy but lacks specific Uzbekistan’s subnational programs align with the such as Almaty and Astana in Kazakhstan, which have green development. Enhancing the integration of climate- details. The Kyrgyz Republic’s National Strategy until 2040 New Uzbekistan Development Strategy, which lacks the autonomy to set ambitious climate targets due related goals into existing frameworks and developing includes climate change adaptation measures with a focus climate targets. Kazakhstan’s plans link to the National to greater financial resources. The Kyrgyz Republic new instruments for local sustainability actions are on environmental quality. Uzbekistan’s “New Uzbekistan Development Plan until 2025, focusing mainly on grants subnational authorities administrative autonomy essential. Collaboration among national and subnational _______________________________ but maintains financial dependence on the central entities, innovative sustainable urban planning, and 7 There can be two types of targets within an INDC: conditional and unconditional. Unconditional targets are emission reduction targets that a government. strategic investments are crucial for achieving a low- country commits to achieving regardless of any external assistance. They represent the country’s own domestic efforts to reduce emissions. Condi- tional targets are emission reduction targets that a country commits to achieving if they receive international support. This support can come in carbon, resilient urban future in Central Asia. various forms, such as financial aid, technology transfer, or capacity building. 36 37 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future Rationale and Scope of the Study The Central Asia Regional Study on Resilient A deep-dive analysis was conducted on and Low-Carbon Cities (CARL-cities) is a Almaty (KAZ), Bishkek (KGZ), Dushanbe (TJK), novel attempt to systemically understand Namangan (UZB), and Shakhrisabz (UZB) to urbanization and its potential in Central Asia. examine policy options and interventions. It sheds light on the urban growth trajectories and trends This analysis used quantitative, qualitative, and spatial in medium-to-large cities in CA, examined through a data, along with local stakeholder engagement. Scenario set of comprehensive parameters, and provides an modeling estimated the potential benefits of key project evidence-based approach to charting a path and taking investments through 2050, comparing a No Intervention actions toward developing green, resilient cities. scenario and a Vision scenario.9 The No Intervention scenario identifies the strengths and weaknesses of the This study explores the challenges and status quo, while the Vision scenario estimates the effects solutions for low-carbon, climate-resilient of climate change mitigation and adaptation measures. urban development at the subnational level in This modeling serves as a basis for further discussion Central Asia (CA). Understanding these challenges and policy development. is essential for creating effective strategies to support sustainable urban development in the region. The study identifies potential actions based on common urban development concerns: natural hazards, carbon intensity, social infrastructure, and environmental issues. Addressing these challenges can help CA cities transition to low-carbon, climate-resilient development and enhance urban planning and sectoral capacity with a long-term climate change vision. The report presents key findings from urban and spatial profiles of 48 cities in the region and insights from in-depth assessments of five selected cities. The macro-level analysis provides an overview of these 48 urban areas, identifying strengths and major concerns, and mapping them spatially. The assessment focused on five dimensions: urban form, urban services and amenities, urban environment, economic activity, and urban mobility. The analyzed cities, each with a population over 150,000, represent about 32.1 percent of the CA region’s total population8. _______________________________ 8 Based on Population, total | Data for 2020. 9 The Vision scenario presents two distinct approaches: Cost-Efficient and Net Zero. The Cost-Efficient scenario, implemented in Bishkek, Dushanbe, Namangan, and Shakhrisabz, focuses on maximizing environmental and social impact within constrained budgets. This approach prioritizes strategic urban policies and investments that reduce GHG emissions while improving local living conditions. In contrast, the Net Zero scenario, adopted by Almaty, sets ambitious goals for achieving net-zero emissions. This requires more transformative policies and a high level of investment. 38 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 2 Urban and Spatial Profiles of 48 Cities This section summarizes findings from patterns, disaster risks, and greenhouse gas (GHG) the urban and spatial profiles of 48 urban emissions. It built a spatial profile for each study areas across five Central Asian countries, area to understand urban growth trajectories, current identifying key urbanization and climate- characteristics, and trends in urban form, environment, related characteristics. The macro assessment mobility, access to amenities, and economic activity. focused on urbanization, development trends, growth Macro Assessment Methodology The CARL-Cities Study Areas The study areas for the macro assessment criterion across the region, focusing on labor markets were selected using the Global Human rather than political or administrative boundaries. Settlements Functional Urban Areas (GHS- The region has 104 functional urban areas, mostly in FUA) dataset (Schiavina et al. 2019) , which 10 Uzbekistan and Kazakhstan. All areas with populations defines urban areas based on local workforce over 150,000 were included, resulting in 48 study areas. commuting patterns . Leveraging the Functional 11 Map 2.1 shows their locations. Urban Areas (FUA) dataset ensures a consistent Map 2.1 CARL-Cities Study Areas Central Asia Region Small < = 250, 000 inh Medium > 250,000 inh < 1 million inh Large > = 1 million onh Kazakhstan Uzbekistan Kyrgyz Republic Turkmenistan Tajikistan Source: CARL-cities 2024 based on Schiavina et al. 2019. _______________________________ 10 According to the OECD, a functional urban area (FUA) consists of a city and its commuting zone, where the latter represents the area of influence of the city in terms of labor market flows. 11 As commuting and local unit boundaries are not available in most countries, the GHS-FUA estimates the FUA based on a probabilistic model trai- ned with actual OECD FUA boundaries. The GHS-FUA uses spatial building blocks instead of local administrative units. Source: CAPSUS, 2023, Bishkek [Photograph] 40 41 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Table 2.1 Set of Indicators for the Macro Assessment Topic Indicator Description Map 2.2 shows a sample study area in Kazakhstan, connected to the city core. Using the FUA ensures an 1.1 Urban This indicator refers to the total built-up area of a city or urban area, including illustrating how the FUA aligns with the urban footprint accurate understanding of urban dynamics and identifies Footprint streets, buildings, open space, infrastructure, and urban amenities. and administrative boundaries. The FUA extends beyond relevant externalities in the city’s surroundings. Population density considers the number of people or inhabitants per square these boundaries to include all urban areas functionally 1 1.2 Population kilometer. The population density is calculated by dividing the total number of Density Urban Form inhabitants by the total FUA area. Map 2.2 Example Study Area: Almaty, Kazakhstan This indicator measures the fragmentation level of the urban footprint of 1.3 Settlement settlements and includes the classification of urban development patterns. Legend Fragmentation Urban settlement fragmentation is the lack of continuity and contiguity of the urban footprint, resulting in built-up area patches or islands. FUA contour Regional boundaries (ADM 1) 2 2.1 Proximity to Accessibility is measured as the percentage of the population living within urban the coverage area12 of urban facilities and amenities. One subindicator is District boundaries (ADM 2) Urban services and amenities calculated for each of the following categories of urban facilities: Health, Urban footprint amenities and facilities Education, Public Spaces, Sports, Financial, and Culture. This indicator will examine the area of greenery in the urban areas from 3.1 Urban satellite imagery and compare it with Open Street Maps (OSM) public green Greenery area data features to estimate the total surface of the study area’s greenery. The resulting area will be divided by the total population to estimate the square meters of urban green area per person. This indicator estimates the percentage of the population living within UHI zones. 3.2 UHI 3 UHI are defined as those areas that are warmer than their surrounding areas13. Urban 3.3 Exposure The percentage of people residing within areas prone14 to pluvial flooding, environment to Natural earthquakes, and landslides. The indicator is calculated by dividing the number Hazards of inhabitants that live within the hazard risk zone by the total population. This indicator estimates CO2, CH4, N2O, and F-gas emissions expressed in 3.4 Greenhouse Gas Emissions CO2 equivalent (CO2e) as a proxy for the annual average greenhouse gas emissions. 3.5 Particulate The emissions per capita of PM2.5 and PM10 will serve as a proxy measure of Matter air pollution. The indicator is calculated by dividing the total amount of PM2.5 Emissions and PM10 emissions by the total settlement population. The economic activity indicator is calculated as the average annual change 4.1 Economic in nighttime Lights (NTL) between 2012 and 2021. This metric provides an Activity estimate of economic activity within the settlements based on the intensity of 4 Change artificial lights captured by satellite imagery during nighttime hours. Source: CARL-cities 2024 based on Schiavina et al. 2019. Economic Activity The job/housing balance indicator is the share of the study area population 4.2 Job/Housing living in economic hotspots, defined as the zones within the study area with Macro Assessment Indicators Balance high economic activity. This indicator uses nighttime light emissions (NTL) as a proxy measure of economic activity15. The study evaluates the current performance such as health clinics, schools, public spaces, sports 5.1 Proximity to Accessibility is captured as a proxy through the percentage of the population of 48 cities using indicators and data from facilities, and cultural centers, was also measured. 5 bus stops and international databases, providing a standard The urban environment was assessed using indicators living within the coverage area16 of urban structured public transportation. bicycle parking framework for comparison. Due to data limitations, for greenery, the UHI effect, hazard exposure, GHG Urban Mobility 5.2 Intersection The intersection density is calculated by dividing the number of street the base year for each indicator ranges from 2012 to emissions and particulate matter emissions. Economic Density intersections within the FUA by the built-up area of the settlement. 2023, often requiring multiple data sources. The macro activity was evaluated through changes in nighttime assessment covers five focus areas: urban form, urban lights and jobs/housing balance. Urban mobility was Source: CARL-cities 2024. _______________________________ services and amenities, urban environment, economic assessed based on accessibility to structured public 12 Area accessible on foot within a specified distance from urban amenities, such as a school, park, or public transit station. The distance thresholds vary for each type of urban amenity, as defined in appendix A. activity, and urban mobility (table 2.1). Urban form transportation and intersection density. Appendix A 13 UHIs were defined as zones within the study area exhibiting a land surface temperature (LST) exceeding the local average by at least 2°C. indicators include urban footprint and land consumption, provides detailed information on each focus area, 14 Appendix A provides more detail on the definition of risk-prone areas. population density, and settlement fragmentation. including indicators, data sources, base year, units, and 15 The results of the 48 study areas show a weak correlation of 0.32 between the job/housing balance and population density. 16 The area that is accessible on foot within a specified distance from bus stops and bicycle parking stations. The distance thresholds vary for bus Accessibility to social infrastructure and public services, calculation methods. stops and bicycle parking, as defined in appendix A. 42 43 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Key Findings on the Current Urbanization Urban Footprint 1990 to 2020, large cities (over one million inhabitants) Situation in Central Asia Cities in CA have expanded rapidly. Between expanded by 244 km² (44.7 percent), medium-sized 1990 and 2020, the built-up area of analyzed urban cities (250,000 to one million people) by 159 km² Urban Form settlements grew by an average of 36.3 percent, (29.1 percent), and small cities (150,000 to 250,000 consuming 545 square kilometers (km2). Major people) by 143 km² (26.2 percent). The most significant Urban form is crucial: distant, dispersed, are key to identifying its sustainability challenges and changes occurred in the Kyrgyz Republic (52.2 expansions were in Nukus, UZB (112.4 percent), and disconnected cities face significant opportunities (figure 2.1). percent), Turkmenistan (47.6 percent), and Kazakhstan Shymkent, KAZ (109.8 percent), Dashoguz, TKM, and sustainable development challenges and (38.2 percent), surpassing the regional average. In Astana, KAZ (both 91.7 percent), and Oral, KAZ (67.6 require more resources for daily operations. Sustainable and efficient urban development Uzbekistan and Tajikistan, urban expansion increased percent). The least expansion occurred in Temirtau, Mobility issues are pronounced due to greater distances is more cost-effective. A compact, connected city by 31.2 percent and 25.7 percent respectively. KAZ (6.5 percent), Bukhara, UZB (8.6 percent), Semey, and dispersed populations, making public transport more uses resources efficiently due to shorter travel distances KAZ (10.6 percent), and Gijduvan and Urgench, UZB expensive and less efficient. Residents spend more time and economies of agglomeration. From a public budget Urban expansion in CA cities varies (both 15.5 percent) (see map 2.3 and figure 2.2). and energy reaching destinations, increasing pollution perspective, city expenses correlate with the built-up significantly, correlating with city size. From and congestion. Low-density cities also have higher area size, while income correlates with population. If a per capita demands for energy, land, and resources. city’s size grows faster than its population, expenses will Map 2.3 Urban Footprint Growth Between 1990-2020 in Nukus (UZB) For example, ten families in single-family homes outpace income, potentially causing fiscal imbalance. consume more resources than in an apartment complex. Unfortunately, many urban areas in CA exhibit such Therefore, a city’s urban form and development type unsustainable sprawl patterns. Figure 2.1 Same Density in Two Different Urban Forms Legend FUA contour Regional boundaries (ADM 01) District boundaries (ADM 02) Urban footprint 2020 Urban footprint FUA 1990 Urban footprint FUA 2020 Source: GHS-POP R2022A Schiavina et al. 2022. Source: CARL-cities 2024. 44 45 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.2 Urban Footprint Growth 1990-2020 Population Density Without policy interventions, some CA cities Nukus Appropriate population density benefits may lose their density advantage. Population Shymkent sustainable development by enabling efficient trends vary by country: Tajikistan had mixed results (half Dashoguz resource use, reducing energy consumption, of the cities increasing in population density and half Astana and increasing access to amenities and losing it), Kazakhstan saw a density decline in 61 percent Oral public transportation. The average population of urban areas, and the Kyrgyz Republic experienced Jizzax density of the 48 analyzed urban areas is 1,594 decreases in all analyzed settlements. Conversely, Bishkek inhabitants per square kilometer. Larger cities tend to Turkmenistan and Uzbekistan showed positive trends, Ashgabat attract more residents, with significant density increases with all Turkmenistan cities and 76 percent of Uzbek Aktobe between 1990 and 2020: large settlements gained an cities increasing in density in recent decades (see map Fergana average of 2,486 people per square kilometer, medium- 2.4 and figure 2.3). Osh sized settlements gained 372, while small settlements Jalal-Abad saw a decrease of 723. Oral and Petropavl (KAZ) had Almaty the lowest densities, while Dushanbe (TJK), Bishkek Kostanay (KGZ), and Tashkent (KAZ) had the highest. Navoiy Andijan Oskemen Map 2.4 Population Density, Ashgabat (TKM) Namangan Taldykorgan Quva Khujand Atyrau Study Area Aktau Mary Petropavl Qarshi Termez Karaganda Regional average: 36.2% Shahrisabz Tashkent Taraz Samarkand Khiva Kyzylorda Turkestan Kokand Yangikurgan Legend Turtkul FUA contour Dushanbe Regional boundaries (ADM 01) Katta−Kurgan Legend District boundaries (ADM 02) Denov Total extent [km2] Country Urban footprint 2020 Pavlodar 50 Kazakhstan Turkmenabat Population density (inh/Ha) 100 Kyrgyz Republic Urgench Gijduvan 150 Tajikistan Semey Turkmenistan 200 Source: Pesaresi, et al. 2015; GHS-POP R2022A Schiavina et al. 2022. Bukhara Uzbekistan Temirtau 0 30 60 90 120 Source: GHS-POP R2022A Schiavina et al. 2022. 46 47 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.3 Population Density in the Region Settlement Fragmentation Dushanbe Urban areas in CA exhibit unsustainable spatial Bishkek expansion. The average fractal degree17 of 1.7 indicates Tashkent dispersed urban growth with leapfrog and scattered Ashgabat development (table 2.2 and maps 2.5 to 2.7).18 About Almaty 58.3 percent of urban areas show leapfrog development, Osh 39.6 percent have scattered19 development, and only 2.1 Shymkent percent display continuous peri-urban expansion. Andijan Aktau Table 2.2 Spatial Patterns Classification Turkestan Jalal-Abad Spatial Pattern Fractal Degree Description Kokand In this type of development, the urban footprint exhibits minimal voids Termez or empty spaces. Compact urban development is a direct outcome Kyzylorda of expanding or consolidating built-up areas primarily within the pre- Khujand Compact21 1.9 - 2 existing and established urban footprint. The compact urban footprint Namangan often emerges as a consequence of infill expansion, where new Astana development takes place within the available spaces in the urban Kostanay core without increasing the overall urban extent (Sun et al. 2013). Fergana This form of urban development occurs when the urban footprint Taldykorgan Peri-Urban expands outward from the consolidated urban area, specifically Yangikurgan Continuous 1.81 - 1.9 within its periphery. It represents a contiguous expansion of the Aktobe Growth settlement. Study Area Pavlodar Bukhara Scattered development is typified by a fragmented, diffuse, and Samarkand dispersed pattern of urban expansion. This urban growth expands Dashoguz beyond the boundaries of the consolidated urban footprint. Scattered Scattered development refers to an urban growth pattern where Katta−Kurgan Growth 1.715 - 1.81 new or existing urban areas and constructions are spread out and Nukus are not contiguous with the existing consolidated urban footprint. Shahrisabz In scattered development, the dispersion of built-up areas takes Urgench on the appearance of isolated, individual small patches scattered Denov across the study area. Gijduvan Atyrau Leapfrog development is characterized by a discontinuous urban Semey fabric, marked by isolated built-up patches or “islands” that stand Leapfrog 0 - 1.715 apart from the urban core. This type of development is commonly Khiva associated with settlements located at a considerable distance from Karaganda existing urban areas. Qarshi Jizzax Source: CARL-cities 2024. Categories adjusted based on Suárez-Meaney et al. 2022. Quva Oskemen Legend _______________________________ Navoiy 17 The fractal degree measures the filled and empty space within the study area, compared to a simple geometric shape, such as a square. The City Size Country Turkmenabat urban footprint is categorized as a filled area, while land with no built-up surface is considered “empty” space. This value quantifies the dispersion of Kazakhstan the urban settlement’s footprint. Mary Large Regional average: Kyrgyz Republic 18 Leapfrog development shows a discontinuous urban fabric characterized by isolated built-up patches or “islands” that are separated from the urban Turtkul 1594 inh/km2 core. This type of development is typically identified as settlements far away from existing ones. Temirtau Medium Tajikistan 19 Scattered development is characterized by a discontinuous, diffuse, and dispersed fragmentation of the urban footprint. Taraz Turkmenistan 20 This pattern is characterized by an expansion next to the existing settlements or urban centers. This spatial development is consolidated in the Small Uzbekistan surrounding functional area. Petropavl 21 In this context, the term compact should not be confused with the compact city approach. During the calculation of this indicator, it was observed Oral that settlements with high fractal degrees, which are typically considered compact cities, often display a significant level of confetti-like urban disper- 0 1000 2000 3000 4000 5000 sion, as observed in Tashkent. In such cases, the level of dispersion is so pronounced that it becomes difficult to differentiate between vacant urban land and farmland. Therefore, the compactness described by this indicator primarily refers to the observed homogeneity in the shape of the urban Source: Pesaresi, et al. 2015; GHS-POP R2022A Schiavina et al. 2022. Higgs, C. et al. 2021. area and should not be directly associated with the compact city approach. 48 49 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Map 2.5 Examples of Spatial Development in Central Asia Map 2.7 Periurban Continuous Growth in Atyrau (KAZ) (Fractal Degree 1.82) Source: World Pop, 2023. Map 2.6 Leapfrog Urban Dispersion in Astana (KAZ) (Fractal Degree 1.53) Legend FUA contour Regional boundaries (ADM 01) District boundaries (ADM 02) Urban footprint 2020 Source: GHS-POP R2022A Schiavina et al. 2022. The urban development model in CA leads Overall, urban expansion and population to a resource-intensive region with negative growth in CA are increasing at similar rates, medium- and long-term impacts. Urban expansion which is uncommon in most developing cities. scenarios based on Shared Socioeconomic Pathways This trend maintains density and supports sustainable (SSPs) indicate a growing land demand in the coming urban development. However, large variations are years (figures 2.4 and 2.5). SSPs, used in the IPCC’s observed for each city. sixth assessment report, help understand how societal choices affect land use and GHG emissions, and how to achieve the Paris Agreement goals. Legend FUA contour Regional boundaries (ADM 01) District boundaries (ADM 02) Urban footprint 2020 Source: GHS-POP R2022A Schiavina et al. 2022. 50 51 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.4 Urban Dispersion in Central Asia Figure 2.5 Urban Expansion Projections in CA (Based on SSPs) Atyrau Osh Quva Mary Khiva Tashkent Yangikurgan 20 Termez Qarshi 2 Jalal-Abad Thousand km Taldykorgan Almaty Jizzax Kyzylorda 15 Kostanay Kokand Ashgabat Fergana Bukhara Namangan Turkestan 10 Gijduvan 2020 2030 2040 2050 Study Area Petropavl Legend Bishkek Scenario ssp1 ssp2 ssp3 ssp4 ssp5 Khujand Shahrisabz Navoiy Source: Calculations based on Gao and O’Neil 2020. Aktau Karaganda Taraz Urban Services and Amenities Turkmenabat Dashoguz Proximity to social infrastructure and public Accessibility to Urban Amenities Katta_Kurgan services affects trip length and quality of and Services Oral life. Key destinations typically include job centers, Most urban areas in CA have severely limited Dispersed Compact Samarkand schools, markets, parks, health clinics, sports facilities, access to essential services and amenities. Dushanbe Legend and cultural venues. Close amenities increase access Health clinics, schools, parks, sports venues, and Urgench Country and reduce the need for motorized transport, lowering cultural centers are distant for most residents. Average Andijan Kazakhstan congestion, pollution, and GHG emissions. accessibility is only 16.5 percent for schools, 6.8 percent Aktobe Kyrgyz Republic for health clinics, 8 percent for parks and sports facilities, Nukus Tajikistan Denov Urban expansion necessitates new and 3 percent for cultural centers22. Bishkek (KGZ) has Turkmenistan Semey infrastructure and services. Without investment, the highest proximity to amenities, followed by Oral Uzbekistan Turtkul access to these amenities may decline, especially in (KAZ) (map 2.8), Semey (KAZ), Ashgabat (TKM), and Fractal Degree areas with decreasing density and sprawl. Building new Taldykorgan (KAZ). These areas scored well in education Shymkent 1.6 Oskemen amenities is costlier and slower than upgrading existing and financial facilities. Temirtau 1.7 ones. Effective urban planning can address growth Pavlodar 1.8 challenges and mitigate negative environmental and Astana social impacts through proper design and management. 1.715 1.810 1.900 2.000 _______________________________ Fractal Degree 22 According to the 20-minute city framework implemented by the Victoria State Government (2022), accessible urban amenities are defined as local health facilities within 800 meters, schools within 800 meters, public spaces within 300 meters, sports facilities within 800 meters, and cultural facilities Source: GHS-BUILT-S R2022A Pesaresi et al. 2022. within 800 meters. 52 53 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Overall, all study areas had low proximity to cultural, • Proximity to cultural spaces is low, Figure 2.6 Share of Population with Access to Urban Amenities sports, and health facilities (figure 2.6). Key findings averaging 3 percent. Bishkek (KGZ) has the Cultural Spaces Financial Services Hospitals Public Spaces Schools Sport Facilities include: highest at 11 percent, followed by Oral (KAZ) at Bishkek • Educational facilities are the most 9.3 percent and Taldykorgan (KAZ) at 8.3 percent. Oral accessible urban amenities, with 16 percent Namangan, Denov, and Yangikurgan (UZB) have Semey of the population living within walking distance. no residents within walking distance of cultural Ashgabat Taldykorgan Bishkek (KGZ) leads with 40 percent of residents amenities. Pavlodar near schools, followed by Ashgabat (TKM) and • Accessibility to sports facilities Petropavl Nukus (UZB) at 33 percent each, and Petropavl averages 6 percent. Bishkek (KGZ) leads Aktobe (KAZ) at 32.4 percent. Lower results were seen in with 22.36 percent, followed by Atyrau (KAZ) Astana Shakhrisabz (UZB) at 2.6 percent, Mary (TKM) at at 17.3 percent and Taldykorgan (KAZ) at 16.4 Dushanbe Almaty 3.1 percent, and Gijduvan (UZB) at 3.4 percent. percent. Gijduvan (UZB) and Shakhrisabz (UZB) Nukus • Walkable access to parks and public have no residents near sports facilities. Kostanay spaces averages 8 percent, with Bishkek Karaganda (KGZ) at 51 percent, Ashgabat (TKM) at 26 Atyrau percent, and Pavlodar (KAZ) at 20 percent. Temirtau Osh Aktau Map 2.8 Quantity of Urban Amenities Within Walking Distance in Oral (KAZ) Urgench Jalal-Abad Legend Bukhara Regional boundaries (ADM 01) Kyzylorda Study Area District boundaries (ADM 02) Oskemen Turkestan Urban footprint 2020 Jizzax Types of amenities within walking distance Turkmenabat Shymkent Tashkent Khujand Dashoguz Fergana Samarkand Turtkul Taraz Andijan Quva Termez Khiva Oral Mean: 3.03 % Mean: 10.85 % Mean: 6.79 % Mean: 8.09 % Mean: 16.53 % Mean: 5.9 % Navoiy Kokand Qarshi Mary Namangan Katta−Kurgan Shahrisabz Denov Gijduvan Yangikurgan 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 Population with Access to Urban Amenities and Services [%] Source: GHS-POP R2022A Schiavina et al. 2022; Open Street Maps. Source: GHS-POP R2022A Schiavina et al. 2022; Open Street Maps. 54 55 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Map 2.9 Urban Green Areas in Semey (KAZ) Urban Environment The urban environment was assessed using indicators Urban Greenery for greenery, the UHI effect, hazard exposure, GHG Most cities in CA lack adequate urban green emissions and particulate matter emissions: areas (UGA), averaging only 7.6 square meters • Urban greenery reduces climate hazards, (m2) per capita, 11 m2 below the EU average provides environmental benefits, and increases of 18.2 m2 (Varbova 2022) (figure 2.7). Kazakhstan park accessibility. Green spaces offer recreation, cities fare better, averaging 16.4 m2 per capita, with enhance well-being, and ensure ample per capita Semey (KAZ) at 51.6 m2 (map 2.9). Tajikistan averages green space. They contribute to environmental 6.8 m2, with Dushanbe (TJK) at 12 m2. The Kyrgyz sustainability through climate regulation, shading, Republic averages 3.7 m2, with Bishkek (KGZ) at 4.6 m2. carbon sequestration, pollution mitigation, and Uzbekistan averages 1.7 m2, with Denov (UZB) at 4.8 m2. water filtration. Strategically placed green areas Turkmenistan averages 1.9 m2, with Turkmenabat (TKM) act as natural buffers during floods, absorbing at 2.8 m2. Adequate UGA is crucial for regulating urban excess rainfall. microclimates and reducing the UHI effect. • Urban Heat Island (UHI) analysis helps Legend understand how urbanization increases Urban Heat Island temperatures and heat exposure. According to Approximately 13 percent of the total area and Urban green areas the US-EPA, urbanization causes buildings and 17 percent of the population in the analyzed Regional boundaries (ADM 01) infrastructure to absorb and re-emit solar heat, cities are subject to the UHI effect (figure District boundaries (ADM 02) creating “heat islands” that are hazardous during 2.8)23. Significant variations exist between cities. Urban footprint 2020 heat waves. Urgench (UZB), Turkmenabat (TKM), and Petropavl • Flooding, seismic activities, landslides, (KAZ) have over 45 percent of their populations exposed Source: GHS-POP R2022A Schiavina et al. 2022; GHS-BUILT-S R2022A Pesaresi et al. 2022. Source: CARL-cities 2024. and heat waves expose populations to to UHI, while Yangikurgan has no exposure. (Map 2.10 natural disasters. Climate change and the highlights the situation in Temirtau (KAZ).) In contrast, natural context of CA cities present risks that city nearly a third of the analyzed cities have less than 10 Map 2.10 Area Exposed to the UHI Effect in Temirtau (KAZ) administrations must manage. Understanding percent of their populations living in UHI-prone areas. these risks helps urban planners identify suitable For example, Karaganda (KAZ) is at 1 percent, Kyzylorda areas for expansion, optimal locations for (KAZ) at 2 percent, and Ashgabat (TKM) at 3 percent. amenities, and plan strategic densification. It also Given the steady increase of 0.28°C in average annual air aids civil protection agencies in implementing temperature per decade from 1950 to 2016 (Haag, Jones, preventive measures to reduce disaster risks. and Samimi 2019), and projections indicating greater • Air pollutant emissions pose immediate rises in climate extremes compared to the global average and future problems for CA cities. Urban (Liu et al. 2020), addressing the UHI effect is crucial for activities demand natural resources and mitigating climate vulnerability. generate pollutants, impacting the environment. Particulate matter affects public health, while GHG emissions exacerbate climate change. These pollutants are linked to urban structure and environmental policies. Legend Urban heat island Regional boundaries (ADM 01) District boundaries (ADM 02) _______________________________ Urban footprint 2020 23 The exposed surface area of a UHI is determined by dividing the total area with a land surface temperature (LST) exceeding 2 degrees above the annual average temperature by the total settlement area. The identification of UHI-prone areas uses the yearly average of LST. For further details on the calculation, please refer to appendix A. Source: GHS-POP R2022A Schiavina et al. 2022; Fick and Hijmans 2017; Open Street Maps. 56 57 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.7 Urban Green Areas Per Capita Figure 2.8 Population Exposed to the UHI Effect Semey Urgench Oskemen Turkmenabat Petropavl Petropavl Oral Jalal-Abad Pavlodar Khiva Aktobe Namangan Kostanay Turtkul Dushanbe Bukhara Temirtau Oskemen Atyrau Temirtau Almaty Tashkent Karaganda Semey Astana Katta−Kurgan Denov Andijan Bishkek Navoiy Tashkent Taraz Jizzax Samarkand Nukus Aktau Taraz Khujand Osh Termez Jalal-Abad Kokand Turkmenabat Pavlodar Study Area Taldykorgan Dushanbe Study Area Bukhara Mary Urgench Gijduvan Navoiy Oral Ashgabat Denov Shahrisabz Bishkek European Union average: 18.2 m²/inh Termez Fergana Khujand Qarshi Mary Taldykorgan Fergana Almaty Turkestan Kostanay Regional average: Regional average: 17.64% Samarkand Jizzax 7.6 m²/inh Shymkent Aktobe Quva Osh Dashoguz Turkestan Qarshi Astana Khiva Atyrau Kokand Shahrisabz Legend Legend Kyzylorda Quva Namangan Country Dashoguz Country Kazakhstan Nukus Kazakhstan Andijan Katta−Kurgan Kyrgyz Republic Shymkent Kyrgyz Republic Aktau Tajikistan Ashgabat Tajikistan Gijduvan Turkmenistan Kyzylorda Turkmenistan Turtkul Uzbekistan Karaganda Uzbekistan Yangikurgan Yangikurgan 0 10 20 30 40 50 60 0 20 40 60 Urban Green Areas per capita [m2/inh] Population exposed to Urban Heat Islands [%] Source: GHS-POP R2022A Schiavina et al. 2022; GHS-BUILT-S R2022A Pesaresi et al. 2022. Source: GHS-POP R2022A Schiavina et al. 2022; Fick and Hijmans 2017; Open Street Maps. 58 59 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Exposure to Natural Hazards percent), Aktau (KAZ) (0.86 percent), Karaganda (KAZ) Figure 2.9 Population Exposure by Type of Hazard CA cities are highly exposed24 to natural (2 percent), and Pavlodar (KAZ) (2.22 percent), less Earthquake Fluvial flood Landslides Pluvial Flood hazards, including earthquakes, landslides, than 3 percent of the population is exposed to natural Dushanbe and floods (figure 2.9). Earthquakes are the hazards, with flooding being the most significant. Almaty dominant hazard due to the collision of the Eurasian and Shymkent Indian plates. Floods are the second most prevalent, Earthquakes are a major threat, with 75.6 Bishkek Shahrisabz especially in mountainous areas and alluvial plains. percent of the population in the studied Tashkent Urban areas near the mountains of Tajikistan and the urban areas living in earthquake-prone Turkmenabat Kyrgyz Republic are at high risk for landslides. zones. In Tajikistan, the Kyrgyz Republic, and Samarkand Uzbekistan, 95 percent, 91 percent, and 78 percent of Jalal-Abad Northern and central cities have less exposure the population, respectively, live in earthquake-prone Fergana to natural hazards. Only about 10 percent of the areas. In Turkmenistan and Kazakhstan, the figures are Namangan Taldykorgan analyzed urban areas have very low exposure. In 52 percent and 28 percent. Andijan Turkestan (KAZ) (0.58 percent), Nukus (UZB) (0.73 Jizzax Osh Map 2.11 Area Exposed to Floods in Kyzylorda (KAZ) Quva Semey Navoiy Yangikurgan Termez Oskemen Denov Study Area Khiva Urgench Taraz Kokand Qarshi Ashgabat Khujand Gijduvan Katta−Kurgan Turtkul Bukhara Dashoguz Kyzylorda Astana Oral Petropavl Aktobe Kostanay Legend Mary Atyrau Flood-prone areas Mean: 58.04% Mean: 3.74% Mean: 0.48% Mean: 1.68% Temirtau Regional boundaries (ADM 01) Pavlodar Karaganda District boundaries (ADM 02) Aktau Urban footprint 2020 Nukus Turkestan 0 25 50 75 100 0 10 20 0 2 4 6 8 0 2 4 6 Source: GHS-POP R2022A Schiavina et al. 2022; World Bank 2022. Population Exposed to Hazards [%] _______________________________ 24 Exposure is defined as the percentage of people residing within areas prone to natural hazards such as pluvial flooding, earthquakes, and landsli- Source: GHS-POP R2022A Schiavina et al. 2022; World Bank 2022. des. This is calculated by dividing the number of inhabitants living within the hazard-prone areas by the total settlement population. Earthquake-prone areas are those that would be affected by strong shaking, and have a peak ground acceleration (PGA) of 9.2 percent. Fluvial and pluvial flood-prone areas are those where the water depth could reach up to 0.5 meters. Landslide-prone areas are those that showed a 30 percent landslide susceptibili- ty, representing a medium-level risk. 60 61 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 In Dushanbe (TJK), Osh (KGZ), and Almaty PM10 and PM2.5 pollutants, at 0.3 and 0.2 kg Figure 2.10 Emission of Particulate Matter PM10 in the Urban Areas (KAZ), landslides are the second major threat per capita, respectively. Other cities with low levels Temirtau after earthquakes, affecting 8.27 percent, 7.53 of pollutant emissions included Navoiy (UZB), (0.36 kg Aktau percent, and 3.61 percent of the population, respectively. PM10 and 0.2 kg PM2.5 per capita), and Namangan (UZB), Aktobe Other urban areas have less than 2 percent of the Andijan (UZB), and Kokand (UZB), with almost 0.4 kg Petropavl population exposed to landslides, which are more likely PM10 and 0.3 kg PM2.5 per capita, each. The urban areas Pavlodar during spring and summer due to increased rainfall and of Aktau (KAZ) and Temirtau (KAZ) have almost 30 times Oral extreme weather events from climate change. more PM10 emissions per capita than the area with the Astana Karaganda lowest emissions (Katta-Kurgan (UZB)). Oskemen Kyzylorda (KAZ) (map 2.11), Semey (KAZ), Taldykorgan Turkmenabat (TKM), and Astana (KAZ) have Manufacturing and energy for the construction Kostanay the highest flood exposure, with 27.3 percent, sector are the major contributors to the Taraz 18.47 percent, 18.22 percent, and 14.73 percent of emission of particulate matter in the analyzed Shymkent the population affected, respectively. Other cities with cities. Figure 2.12 and Figure 2.13 indicate that in 2015, Almaty significant exposure include Oral (KAZ) (9.82 percent), the manufacturing sector was responsible for nearly Semey Petropavl (KAZ) (9.36 percent), and Oskemen (KAZ) 45 percent of PM10 and 49 percent of PM2.5 emissions. Kyzylorda (7.33 percent). These results pertain to fluvial floods, as Emissions from the construction sector accounted for the Osh pluvial flood exposure in CA was generally not significant. second-most significant source, with 37 percent of PM10 Atyrau and 38 percent of PM2.5 emissions. Turkestan Dushanbe (TJK) is the most vulnerable Bishkek settlement in the region (World Bank 2022). Between 1990 and 2015, the region Fergana Khujand In Dushanbe (TJK), almost the entire urban population experienced a decrease in the total emission Study Area Dushanbe (98 percent) is susceptible to earthquakes, while of primary particulate matter. In the last Jalal-Abad approximately 8 percent is exposed to landslides, 6 decade, total PM2.5 and PM10 emissions decreased by Dashoguz percent to fluvial floods, and 3 percent to pluvial floods. approximately 15.5 and 22 percent, respectively27. This Gijduvan After Dushanbe (TJK), the three settlements with the downward trend is not common in all cities since some Quva highest cumulative share of the population exposed to urban areas actually increased their particulate matter Mary natural hazards are Almaty (KAZ), Shymkent (KAZ), and emissions. For instance, Aktau (KAZ) recorded the highest Turkmenabat Bishkek (KGZ). growth in emissions, with PM10 and PM2.5 increasing by Denov 120 percent and 109 percent, respectively. Astana (KAZ) Turtkul Particulate Matter Emissions25 also recorded a notable increase in emissions, with PM10 Bukhara Regional average score: 3.1 kg PM10/inh Forty percent of the analyzed cities have a and PM2.5 rising by 65.8 and 59 percent. Termez high proportion of per capita emissions of Khiva particulate matter (figure 2.10 and 2.11). From 1990 to 2015, the agriculture, fuel Tashkent Urgench According to the EDGAR database (Monforti et al. 2021), production, and construction sectors recorded Jizzax Temirtau (KAZ) had the highest level of air pollution a significant increase in air pollutants. Shahrisabz intensity in the region26. This urban area generated 10.4 Agriculture witnessed a staggering surge, amplifying Sector Nukus and 8.5 kg per capita of PM10 and PM2.5, respectively, its particulate matter emissions nearly twentyfold. Qarshi Agriculture followed by Aktau (KAZ) (9 kg PM10 and 7.7 kg PM2.5), Likewise, emissions resulting from fuel-related activities Samarkand Aviation experienced a substantial uptick of 300 percent, while the Energy for buildings and Aktobe (KAZ) (8.2 kg PM10 and 7 kg PM2.5). Ashgabat Farming energy consumption associated with construction also Yangikurgan Fuel exp and production Manufacturing Among the analyzed settlements, Katta- rose by 125 percent over the period. Kokand Metals production Kurgan had the lowest relative emissions of Andijan Minery Other Namangan Power industry _______________________________ Navoiy Transport 25 While this indicator is useful for assessing the emission of air pollutants, it is important to note that it is not an air quality index. An Air Quality Index Waste Katta−Kurgan (AQI) considers both the concentration of pollutants in the air and the potential health risks those pollutants pose to the population. 0 3 6 9 12 26 The analysis only considers emissions produced within the functional urban area. In addition, large-scale biomass burning with savannah burning, forest fires, and sources and sinks from land use, land-use change, and forestry (LULUCF) are excluded. Windblown dust is also not considered. PM10 Emissions per capita per sector 2015 [kg PM10/inh] 27 The analysis only considers emissions produced within the functional urban area. In addition, large-scale biomass burning with savannah burning, forest fires, and sources and sinks from land use, land-use change, and forestry (LULUCF) are excluded. Windblown dust is also not considered. Source: Monforti 2021. 62 63 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.11 Emission of Particulate Matter PM2.5 in the Urban Areas Greenhouse Gas Emissions In Kazakhstan, the electricity and heat sector contributed Temirtau CA’s greenhouse gas (GHG) emissions 43 percent of emissions, and construction 13 percent. Aktau increased by 5 percent from 1990 to 2019. In Uzbekistan, the electricity and heat sector and Aktobe Figure 2.12 shows regional CO2 emissions rising from agriculture each contributed about 30 percent and 20 Petropavl 617 MtCO2e in 1990 to 645 MtCO2e in 2019, despite a percent, respectively. In Tajikistan, agriculture was the Pavlodar dip in the mid-late 90s. However, figure 2.13 indicates primary source at 39 percent, with electricity and heat, Oral varying trends among CA countries. Kazakhstan saw a construction, and industrial processes collectively at 30 Astana drop in emissions followed by an increase from 1999 percent. In the Kyrgyz Republic, buildings contributed Karaganda to 2013, then fluctuating levels. The Kyrgyz Republic 42 percent and agriculture 36 percent. In Turkmenistan, Taldykorgan and Tajikistan experienced a significant decline before fugitive emissions comprised 46%, followed by the Oskemen 1995, stability until around 2010, and then a gradual electricity and heat sector at 16 percent. Kostanay increase. Uzbekistan’s GHG emissions fluctuated from Taraz 1990 to 2019, ending slightly higher. Turkmenistan Overall, Turkmenistan and Kazakhstan Shymkent Almaty consistently increased its emissions, reaching about exhibit the highest carbon intensity within Semey 160 MtCO2e by 2019. the region. Data for 201528 reveals that Turkmenistan Kyzylorda and Kazakhstan emitted around 35.2 MtCO2e and Atyrau The increase in national GHG emissions is 14.6 MtCO2e per capita, respectively. Uzbekistan, the Turkestan mainly due to the energy sector, which accounted Kyrgyz Republic, and Tajikistan showed a lower carbon Osh for 31% of emissions in 2018, with the electricity and intensity, below the regional average of 11.8 MtCO2e. Bishkek heat sector generating 202 MtCO2e (Climate Watch In those countries it was estimated at 5, 2.6, and 1.4 Jalal-Abad Historical database). Emission sources vary by country. MtCO2e, respectively. Khujand Jalal-Abad Study Area Gijduvan Figure 2.12 GHG Emissions by Sector for Central Asia Quva Fergana Dashoguz Dushanbe 600 Mary Denov Turtkul Turkmenabat Bukhara Khiva Regional average 400 Tashkent score: 2.53 kg PM2.5/inh Termez Sector Jizzax Agriculture Urgench Building Shahrisabz Electricity/Heat Nukus Sector Fugitive Emissions Qarshi Agriculture 200 Aviation Industrial Processes Samarkand Energy for buildings Land−Use Change and Forestry Yangikurgan Farming Andijan Fuel exp and production Manufacturing/Construction Manufacturing Other Fuel Combustion Namangan Metals production Kokand Minery Transportation Other Waste Ashgabat 0 Power industry Navoiy Transport Katta−Kurgan Waste 1990 2000 2010 2020 0.0 2.5 5.0 7.5 10.0 PM2.5 Emissions per capita per Sector 2015 [kg PM2.5/inh] Source: Climate Watch 2022. _______________________________ Source: Monforti 2021. 28 Calculations based on Climate Watch and World Population Prospects. 64 65 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.13 GHG Emissions by Sector Per Country More than half of the analyzed settlements 1990 to 91.6 percent in 2019, while coal and natural gas have GHG emissions exceeding the ECA shares decreased. Kazakhstan Kyrgyz Republic regional benchmark. Figure 2.14 shows that 300 30 about 65 percent of the analyzed urban areas recorded Despite advancements in renewables, CA’s carbon emissions surpassing the Europe and Central electricity and heat generation heavily relies Asia (ECA) average of 6.7 tCO2e per capita. In 2015, on fossil fuels. Combined heat and power plants 200 20 Aktau (KAZ) had the highest per capita emissions at (CHPs) and household heating practices primarily use 53.3 tCO2e, followed by Temirtau (KAZ) with 48 tCO2e, coal, with major plants shifting towards natural gas. In and Karaganda (KAZ) with 40 tCO2e. Conversely, urban Turkmenistan, 99 percent of electricity generation relies 100 10 areas in Tajikistan and the Kyrgyz Republic had the on natural gas, and in Uzbekistan, it accounts for 85 lowest GHG per capita emissions. Dushanbe (TJK) percent29. recorded the lowest at 1.29 tCO2e, followed by Khujand 0 (TJK) with 1.29, Jalal-Abad with 1.8, and Bishkek (KGZ) In 2019, the region generated about 98.8 0 with 2.8 tCO2e. TWh of electricity from natural gas. Uzbekistan led with 54 percent of the region’s natural gas-based Tajikistan Turkmenistan The waste and fuel production sectors show electricity, followed by Turkmenistan (25 percent) the highest increases in CO2 emissions. and Kazakhstan (20 percent). Most hydropower 150 According to Monfortu et al. (2021), the fuel production infrastructure is in Kazakhstan, the Kyrgyz Republic, 15 sector recorded the highest increase in GHG emissions, and Tajikistan (UNECE 2007). The Kyrgyz Republic and rising from 49.5 tCO2e per capita in 1990 to 98.7 in Tajikistan generate 91-93 percent of their electricity from 100 2015. The waste sector followed with a 22 percent hydropower but face critical shortages in winter due to 10 increase in per capita emissions compared to 1990 reduced river flow, a situation likely worsened by climate levels. The farming, aviation, and agriculture sectors change. This results in insufficient electricity, and leads 50 also experienced significant growth (8.8, 8.7, and 7.3 to widespread energy shortages, a situation that might 5 percent respectively) between 1990 and 2015. be exacerbated in the future due to climate change (Times of Central Asia 2024)30. 0 Energy Mix in Central Asia 0 Electricity generation in the region increased 1990 2000 2010 2020 by 66 percent over the last two decades, from Uzbekistan 91.5 TWh in 2000 to 228.7 TWh in 2019. Despite this 200 growth, the region remains heavily dependent on fossil fuels. From 1990 to 2019, about 75 percent of electricity 150 was generated from natural gas (38 percent) and coal (34 percent). By 2019, natural gas’s share rose to 42.9 percent, an increase of 26.7 TWh. 100 Renewable energy production increased by 25 50 percent between 1990 and 2019, accounting for 22.3 percent of electricity generation (51 TWh). In 2019, hydropower dominated, producing 49 0 TWh (96 percent), while solar and wind contributed 1990 2000 2010 2020 minimally, generating 0.83 TWh (1.63 percent) and 0.70 TWh (1.39 percent), respectively. The Kyrgyz Republic transitioned from carbon-based to renewable electricity, Agriculture Electricity/Heat Industrial Processes Manufacturing/Construction Transportation Sector with hydroelectric power rising from 63.48 percent in Building Fugitive Emissions Land−Use Change and Forestry Other Fuel Combustion Waste _______________________________ Source: Climate Watch 2022. 29 See IEA Energy Statistics Data Browser. 30 Climate scientists predict that the flow of Kyrgyzstan’s main river will decrease by 15–50 percent after 2030. That means the already low water levels in Kyrgyzstan’s largest reservoirs could become even lower. 66 67 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.14 Greenhouse Gas Emissions Within the Functional Urban Areas Economic Activity Aktau Temirtau The region’s economy is transitioning from a decrease of -1.1 percent annually. Turkestan (KAZ) Karaganda centrally planned model to an open market, had the highest average increase in economic activity Pavlodar accelerating urbanization. Economic growth has with an annual growth rate of 17 percent, followed Petropavl increased over the last two decades due to commodity- by Oral (KAZ) at 10 percent and Kyzylorda (KAZ) at Aktobe based strategies, such as exporting hydrocarbons and 9.5 percent. About 10 percent of the settlements had Oskemen minerals like oil, natural gas, aluminum, gold, cotton, limited growth, with annual rates below 2 percent. Taraz Astana and other metals. The share of agriculture in the (KAZ), Jizzax (UZB), and Shakhrisabz (UZB) had the Dashoguz regional economy has declined, with the unweighted lowest growth rates at 0.7 percent, 0.8 percent, and 1 Mary average share of agriculture, forestry, and fishing in percent, respectively. Mary (TKM), Dashoguz (TKM), Taraz GDP dropping from 33 percent in 1990 to 14 percent and Temirtau (KAZ) recorded negative annual rates of Oral in 201931. 3.7, 3.6, and 3.5 percent. Turkmenabat Almaty The relationship between economic growth Kostanay Atyrau and urbanization in CA is not linear. In Shymkent predominantly rural countries like the Kyrgyz Republic Taldykorgan and Tajikistan, urbanization is slow, while in Kazakhstan Semey and Uzbekistan, it is slightly declining (Baeumler et Kyzylorda al. 2021). However, the region’s large and medium- Fergana sized cities are experiencing faster population growth Ashgabat than those in other regions, such as Eastern Europe, likely due to improved job opportunities and amenities Study Area Gijduvan Quva resulting from the economic shift from agriculture to Turtkul industry, commerce, and services (Restrepo et al. 2017). Nukus Regional average Economic Activity Change Turkestan score: 11.7 ton CO2e/inh Qarshi Bukhara Nighttime lights-based economic activity in Denov CA shows positive change, with the largest Shahrisabz cities being the main economic drivers. Termez However, economic activity growth is uneven. From Khiva 2012–21, the average annual growth of economic Urgench activity, measured using nighttime lights (NTL)32 as a Osh proxy for the 48 cities, was 2.42 percent. Samarkand Jizzax There are significant disparities: 64 percent of the cities saw growth, while 36 percent Namangan ECA average Sector Andijan score: 6.7 ton CO2e/inh experienced a decline. Major cities like Almaty Kokand Agriculture Aviation (KAZ), Dushanbe (TJK), Bishkek (KGZ), and Tashkent Tashkent Energy for buildings (UZB) had average annual growth rates of 3.9 to 4.5 Yangikurgan Farming Navoiy Fuel exp and production percent, while in Ashgabat (TKM), it increased by 2 Manufacturing percent. An exception is Astana (KAZ), which saw a Katta−Kurgan Metals production Bishkek Minery Other _______________________________ Jalal-Abad Power industry 31 See Agriculture, forestry, and fishing, value added (percent of GDP) | Data. Khujand Transport 32 Nighttime light (NTL) serves as a proxy indicator for economic performance in regions where data availability is limited as noted by (Barzin et al. Waste Dushanbe 2022). Research in this field has consistently demonstrated correlations between NTL emissions and several economic variables, including establi- 0 10 20 30 40 shment and employment density. NTL is a useful tool for estimating subnational GDP levels and economic density (McCord and Rodriguez-Heredia GHG per capita 2015 (ton CO2 e/inh) 2022), although its accuracy diminishes when measuring year-on-year growth rates. NTL can still be used to predict GDP at the subnational level, but it is important to acknowledge its limitations, as other studies reveal that NTL is not the best proxy to estimate productivity in terms of wage incomes Source: Monforti 2021; Global Forest Watch 2018; GHS-POP R2022A Schiavina et al. 2022. (Mellander et al. 2015). 68 69 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.15 Average Annual Growth of Economic Activity Between 2012 and 2021 Map 2.12 Change in Economic Activity from 2012 to 2021 in Turkestan (KAZ) Turkestan Kyzylorda Oral Nukus Khujand Aktobe Khiva Shymkent Navoiy Taldykorgan Urgench Petropavl Osh Bukhara Samarkand Dushanbe Bishkek Tashkent Almaty Legend Kokand Termez Regional boundaries (ADM 1) Atyrau District boundaries (ADM 2) Kostanay Study Area Urban footprint Semey Economic activity change 2012-2021 Aktau Yangikurgan Denov Shahrisabz Source: NOAA, Earth Observation Group (Elvidge et al. 2021). Jalal-Abad Ashgabat Regional average: 22.9% Gijduvan Job/Housing Balance lowest proportions are in Temirtau (KAZ) at 2.9 percent, Taraz The job/housing balance in CA cities is low, Tashkent (UZB) at 7.8 percent, and Almaty (KAZ) at 7.9 Jizzax with only about 19 percent of the population percent (figure 2.16). Quva living near job opportunities , far below 33 Oskemen the recommended 60 percent (UN-Habitat City size does not impact the job/housing balance in Turtkul Fergana 2023) (figure 2.16). Nationally, aggregated results CA. In large settlements, 23 percent of the population Katta−Kurgan show Tajikistan having the highest job/housing balance lives in high economic activity areas, while medium Astana at 31 percent, followed by the Kyrgyz Republic at 30 and small settlements have 19 percent and 17 percent, Andijan percent. In Turkmenistan, 20 percent of the population respectively. These findings indicate that CA cities have Pavlodar Legend lives within economic clusters, while Kazakhstan and monofunctional areas and large peripheral populations, Qarshi Uzbekistan have lower shares at 16.6 percent and with high economic activity concentrated in central areas Country Karaganda Kazakhstan 17.3 percent, respectively. At the city level, Dushanbe and minimal activity in the outskirts. Improvement could Namangan Kyrgyz Republic (TJK), Bishkek (KGZ), and Osh (KGZ) have the highest come from supporting affordable inner-city housing, Temirtau Tajikistan shares of people living within economic clusters, with promoting mixed-use developments, and encouraging Turkmenabat Turkmenistan 43.7 percent, 40 percent, and 31 percent, respectively, economic activities in residential areas. Dashoguz Mary Uzbekistan although this still fall short of international standard. The 0 50 _______________________________ Economic Activity Growth 2012−2021(%) 33 The definition of the economic clusters is based on the distribution of the employment concentration within the study areas. The employment concentration combines data on build-up area, population density, nighttime lights, vegetation intensity (NDVI), existing water bodies, and points of Source: Annual Time Series of Global VIIRS Nighttime Lights Derived from Monthly Averages NOAA, Earth Observation Group interest (OSM). Thus, economic clusters are identified as areas with employment concentration exceeding 3 standard deviations. All regions below (Elvidge et al. 2021). this cut-off value were not considered economic clusters. For further details, please refer to appendix A. 70 71 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.16 Share of Population Living Within Economic Activity Clusters Map 2.13 Job Concentration in Osh (KGZ) Dushanbe Bishkek Osh Aktau Petropavl Pavlodar Turtkul Dashoguz Termez Shymkent Fergana Katta−Kurgan Kostanay Kokand Kyzylorda Semey Denov Jalal-Abad Oral Namangan Mary Legend Samarkand Regional boundaries (ADM 1) Study Area Turkmenabat Andijan District boundaries (ADM 2) Oskemen Urban footprint Nukus Job concentration in Osh Khujand European Union average: 60% Urgench Bukhara Qarshi Source: GHS-POP R2022A Schiavina et al. 2022; GHS-BUILT-S R2022A Pesaresi et al. 2022; Open Street Maps. Ashgabat Karaganda Urban Mobility Quva Taldykorgan Efficient, sustainable cities reduce travel Public Services and Amenities, as mobility also reflects Astana Regional average: 18.7% distances and times by ensuring adequate the level of public services available. Gijduvan Yangikurgan density, balanced private and public services, Khiva and nearby urban amenities. They implement Accessibility to Bus stops and Jizzax efficient public transportation and nonmotorized Bicycle Parking Taraz alternatives on a well-connected street network. Motorized transport, whether private Shahrisabz Legend Compact cities with a mix of population density, vehicles or public transportation, dominates Turkestan Country amenities, jobs, services, and sustainable mobility urban mobility in this region. Despite structured Navoiy Kazakhstan systems lower transportation time and cost, reducing high-capacity public transportation options like trolleys Atyrau Kyrgyz Republic negative environmental and social impacts. and natural gas buses, most people use low-capacity, Aktobe Tajikistan highly polluting options such as old private vehicles Almaty Turkmenistan Proximity to transportation systems, urban accessibility, or public minivans called Marshrutkas (photo 2.1). Tashkent Uzbekistan Temirtau and interconnection density can assess a city’s mobility This is due to factors like narrow, poor-quality roads in 0 20 40 60 profile. When data on travel time, cost, and environmental low-density areas, the spatial distribution of jobs and Population living in economic hubs [%] impact are unavailable, these indicators can predict social infrastructure, insufficient high-capacity transport Source: GHS-POP R2022A Schiavina et al. 2022; GHS-BUILT-S R2022A Pesaresi et al. 2022; Open Street Maps. mobility challenges. This section presents results for the coverage, and low fuel costs (Yang 2019). first two indicators, while the third is discussed under 72 73 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Photo 2.1 Trolleybus in Bishkek (KGZ) Figure 2.17 Urban Mobility Infrastructure in CA Cities Bicycle Parking Stations Bus Stops Oral Bishkek Ashgabat Astana Petropavl Almaty Semey Aktobe Kostanay Karaganda Nukus Turkestan Temirtau Oskemen Dushanbe Shymkent Turkmenabat Tashkent Atyrau Aktau Bukhara Taldykorgan Study Area Pavlodar Samarkand Dashoguz Navoiy Source: © CARLCities / World Bank. Further permission required for reuse. Turtkul Urgench Khiva Most urban areas in CA have insufficient The bicycle parking indicator shows very Osh access to public transportation, with only low accessibility34 across all urban areas, Yangikurgan 7 percent of the population living within with fewer than 1 percent of the population Kyzylorda walking distance of bus stops. However, there having walking access to bicycle parking. Fergana are significant differences among cities. Oral (KAZ), Nukus (UZB) and Bishkek (KGZ) have the highest rates Taraz Bishkek (KGZ), and Ashgabat (TKM) have the best at 0.47 percent, followed by Dushanbe (TJK) at 0.3 Jizzax Jalal-Abad access, with an estimated 29.7, 25.4, and 24.7 percent percent. Tashkent (UZB) and Astana (KAZ) have only Khujand of their populations living close to bus stops. In contrast, 0.08 and 0.2 percent, respectively. Nearly 66 percent Mean: 0.12 % Mean: 7.14 % Kokand Gijduvan, Termez, and Denov in Uzbekistan have less of the settlements lack bicycle parking facilities within Shahrisabz than one percent proximity (0.05, 0.05, and 0.04 percent, walking distance. Mary respectively), and Quva (UZB) was the only settlement Namangan with no bus stops within walking distance. Qarshi Andijan Katta−Kurgan Termez Gijduvan Denov 0.0 0.1 0.2 0.3 0.4 0.5 0 10 20 30 Population with Access to Urban Amenities and Services [%] Source: GHS-POP R2022A Schiavina et al. 2022; Open Street Maps. _______________________________ 34 According to the Institute of Transportation and Development Policy’s transit-oriented development (TOD) standard, bicycle parking is considered accessible if it is within a distance of 100 meters. 74 75 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Map 2.14 Accessibility to Bus Stops and Bicycle Parking in Samarkand (UZB) Photo 2.2 E-Scooters as A Micromobility Alternative in Central Asia Legend Regional boundaries (ADM 1) District boundaries (ADM 2) Urban footprint Source: CARL-Cities / World Bank. Further permission required for reuse. Accessibility to bus stops Source: GHS-POP R2022A Schiavina et al. 2022; Open Street Maps. Intersection Density intersections/km², respectively. The highest densities are Most cities in the region have dense street in Astana (KAZ) with 353 intersections/km², Ashgabat grids that promote walkability and enable (TKM) with 290, Atyrau (KAZ) with 264, Aktobe (KAZ) fluent movement in multiple directions. with 263, and Oskemen (KAZ) with 251 intersections/ About 70 percent of the analyzed urban areas have an km². The lowest densities are in Yangikurgan (UZB) with intersection density35 above the international benchmark 23 intersections/km², Denov (UZB) with 29, Gijduvan of 100 intersections/km² (figure 2.18). Kazakhstan (UZB) with 38, Termez (UZB) with 41, and Kokand (UZB) and Uzbekistan cities have high intersection densities, with 43 intersections/km². These findings suggest that averaging 259 and 130 intersections/km², respectively. the urban structure in most cities is adequate for walking, The Kyrgyz Republic, Turkmenistan, and Tajikistan biking, and small-scale electric scooters (photo 2.2). cities have lower densities, with 191, 158, and 184 _______________________________ 35 The intersection density was calculated by dividing the number of intersections and the built-up area. 76 77 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 2.18 Intersection Density in CA Cities Regional Takeaways Astana Ashgabat The CARL-Cities study shows that cities infrastructure, services, employment, and efficient land Atyrau in this region have not yet realized their use. These challenges lead to negative environmental Aktobe full economic, social, and environmental impacts, such as higher greenhouse gas emissions from Oskemen potential. Common patterns across the five construction and transport. Urban growth also negatively Petropavl countries include rapid urbanization, urban expansion, affects access to essential amenities and public green Taldykorgan uneven densification, limited access to services, spaces, increasing exposure to the UHI effect. Karaganda uneven economic development, high greenhouse gas Taraz emissions, and climate hazards. CA cities are economic drivers, but growth Nukus trends vary, and they have not reached their Temirtau Kostanay Central Asia is urbanizing rapidly. Between full potential. From 2012-21, the average annual Aktau 1990 and 2020, the population in the 48 urban areas growth of economic activities in the 48 cities was 2.42 Almaty studied grew by an average of 36.3 percent. A third of percent, measured by nighttime lights as a proxy. Oral these areas saw population growth above 60 percent, However, 64 percent of the cities are growing, while Semey while only 16 percent experienced a decline. This 36 percent are in decline. The largest capitals (Almaty, Pavlodar growing urban population increases the demand for Dushanbe, Bishkek, and Tashkent) show favorable Kyzylorda infrastructure and services. growth, ranging from 3.9 percent to 4.5 percent per Bishkek annum, except for Astana (KAZ), which saw a decrease Jalal-Abad CA’s urban areas have relatively low population of -1.1 percent annually. Qarshi density, averaging 1,593 inhabitants per Dushanbe Turkestan square kilometer. Densities range from 782 in The job/housing balance38 in CA cities is Study area Navoiy Oral (KAZ) to 4,256 in Dushanbe (TJK), compared to extremely low, with only about 19 percent of Shymkent 9,068 in Barcelona. Between 1990 and 2020, 58% of the population living near job opportunities, Jizzax urban areas saw density increases, while 42% saw far below the recommended 60 percent. Even Samarkand decreases. The most significant decreases were in the in the best-performing cities like Dushanbe (TJK), Dashoguz Kyrgyz Republic, where all its cities witnessed declining Bishkek (KGZ), and Osh (KGZ), only 30-43 percent of Osh density, and Kazakhstan where it is 60 percent. the population is within economic clusters. This reflects Bukhara the monofunctional land use in CA cities. Improving the Quva Urban areas in CA are expanding rapidly, job/housing balance could be achieved by promoting Tashkent though less so than in Europe, Asia, and Africa affordable inner-city housing, mixed-use developments, Mary Turkmenabat (He et al. 2019. ). From 1990 to 2020, the studied 36 and encouraging complementary activities within Katta−Kurgan urban areas expanded by an average of 36.3 percent, economic hubs. Khiva consuming 546 square kilometers of land. Large urban Turtkul areas drove this expansion, accounting for nearly half Most cities in the region have dense street Fergana of the region’s land consumption and growing faster in grids that promote walkability and multi- Khujand both population (1.9 percent annual growth) and urban directional movement. About 70 percent of the Urgench footprint (1.2 percent annual land consumption). analyzed urban areas have an intersection density Andijan Legend above the international benchmark of 100 intersections Shahrisabz International Benchmark: Country The urban areas of CA exhibit unsustainable per square kilometer (UN-Habitat 2023). Kazakhstan Namangan 100 intersections/km2 Kazakhstan spatial expansion patterns. About 58.3 percent Kokand and Uzbekistan have high intersection densities, while Kyrgyz Republic Termez show leapfrog development, 37 39.6 percent have the Kyrgyz Republic, Turkmenistan, and Tajikistan Tajikistan Gijduvan fragmented development, and only 2.1 percent display have lower densities. Most urban areas have moderate Turkmenistan Denov continuous peri-urban expansion. This significant accessibility to bus stops, with Oral (KAZ) performing Uzbekistan Yangikurgan expansion heightens challenges in providing access to best at 29.7 percent of its population living close to bus 0 100 200 300 _______________________________ Intersection density [intersections/km2] 36 Based on the United Nations Definition of Regions. 37 Leapfrog development shows a discontinuous urban fabric characterized by isolated built-up patches or “islands” that are separated from the urban Source: Open Street Maps. core. This was measured by estimating the fractal degree of the settlement’s urban footprint. 38 This refers to the share of population residing in the study areas who are living within economic clusters. 78 79 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future stops. However, access to bicycle parking is much lower across CA’s urban areas. Almost all studied urban areas have critically low access to urban services and amenities such as health and education facilities, public spaces, and cultural venues. The regional average accessibility to educational facilities is 16.5 percent, to health facilities is 6.7 percent, and to public spaces is only 8 percent. Most of the 48 CA cities have very low provision of urban green areas, averaging 7.6 square meters per capita compared to the European average of 18.2 m². This shortage negatively impacts the environment, increases vulnerability to heat islands, and lowers the quality of life. CA cities face significant climate and environmental challenges, including natural disasters, UHI effects, and air pollution. They are prone to earthquakes (58 percent), landslides (0.4 percent), fluvial floods (3.7 percent), and pluvial (1.7 percent) floods. About 17 percent of the population is exposed to the UHI effect. The average GHG emissions per capita in CA cities is high, at 11.7 tons CO2e, 42 percent higher than the European and Central Asian average of 6.7 tons CO2e. The main contributors are the power industry, manufacturing, energy for buildings, and fuel production. Turkmenistan and Kazakhstan have the highest carbon intensity in the region. 80 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 3 Urban Growth Scenarios for 2050 in Five Cities This section provides a thorough analysis quantitative, spatial, and qualitative methods to support of policy options and interventions for five evidence-based policymaking (figure 3.1). The findings Central Asian cities—Almaty, Bishkek, for each modeled indicator are presented, along with Dushanbe, Namangan, and Shakhrisabz—to results for all five cities, supported by maps and graphs. promote low-carbon and climate-resilient A subsection on actionable recommendations highlights development. The cities were assessed using the expected outcomes from proposed investments. Figure 3.1 Cities Selected for the Deep-Dive Analysis Kazakhstan Kyrgyz Republic Tajikistan Uzbekistan Almaty Bishkek Dushanbe Namangan Urban Urban Urban Urban footprint 2020 footprint 2020 footprint 2020 footprint 2020 Kazakhstan Kyrgyz Republic Tajikistan Uzbekistan Uzbekistan Almaty Bishkek Dushanbe Namangan Shahrisabz Urban Urban Urban Urban Urban footprint 2020 footprint 2020 footprint 2020 footprint 2020 footprint 2020 Source: CARL-cities 2024. Two urban growth scenarios are compared: reduce natural hazard exposure, and promote a No Intervention scenario and a Vision sustainable urban development. These policy levers scenario (figure 3.2). The analysis highlights the were developed through a participatory process with benefits of using policy levers to mitigate emissions, local authorities and stakeholders to address critical Source: CAPSUS, 2023, Almaty [Photograph] 82 83 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 issues in the five cities39. The growth scenarios, Local budgets, varying by city, were defined based on The performance of each scenario was indicators of the macro assessment, new categories were created using a combination of policy levers, simulate the total investment needed for basic infrastructure measured using several indicators (table 3.1), incorporated to assess energy consumption, solid waste possible futures by modeling the effects of proposed in new urban areas, including roads, water networks, which are numeric values describing the present or future collection service coverage, drinking water consumption, policies. Each scenario considers historical evolution, sewage systems, public lighting, and electricity grids. conditions of an urban area in a given year. Indicators and estimated capital investment costs. These additional current conditions, expected changes, and the cities’ simplify the evaluation and monitoring of urban areas indicators provide a better understanding of the current commitment to reducing emissions by 2050. Almaty’s Vision scenario examines the cost and are crucial for integrated urban planning. They were state of the cities and the impact of proposed policies of achieving net-zero emissions through used to assess city performance on various topics in both and investments. The analysis contrasted the scenarios The proposed Vision scenario for Bishkek, ambitious policies and investments. The the No Intervention and Vision scenarios. Additionally to across these benchmarks. Dushanbe, Namangan, and Shakhrisabz Net-Zero scenario serves as a roadmap, exploring aims to deliver significant benefits through the policies and substantial investments required Table 3.1 Set of Indicators for the Deep-Dive Analysis strategic interventions without burdening to transform Almaty into a carbon-neutral city. By Key Key local budgets. The “No Intervention” scenario serves analyzing investments in renewable energy and efficient Dimension Objective Policy Levers Specific Actions as a benchmark to compare potential gains from strategic infrastructure, this scenario illustrates Almaty’s potential Develop and implement urban planning and investments against a business-as-usual approach. to achieve its net-zero emissions goal. People-centered design guidelines for compact and people-oriented urban design urban forms. Figure 3.2 Deep-Dive Analysis: Modeling Urban Growth Scenarios Promote infill growth and contiguous peri-urban growth. Sustainable Encourage appropriate densification through updating SCENARIO Within each city, the deep dive assessment encompasses the 1 Livable and urban growth urban plans and guidelines. modeling development and analysis of Urban Form green cities Establish urban limits where appropriate. two urban growth scenarios: Prevent construction and urban development in hazard- ‘No-intervention’ and ‘Vision’ scenarios. prone areas. Land use planning Update relevant building and construction codes to be for resilience seismic and climate-resilient. and equity Promote affordable housing in central areas. Be sensitive and respond to market forces while safeguarding the public interest. Adopt Transit-Oriented Approach (TOD) Redevelop and repurpose brownfield sites and underutilized plots. 2 Facilitate the construction and upgrade of housing units Urban regeneration in well-served areas and neighborhoods. Urban and multifunctional Transform single-use public buildings into services and amenities community facilities multifunctional community buildings. Create a network of cultural and sports facilities. No intervention The ‘No-intervention’ Vision scenario The ‘Vision scenario’ assumes Improve coverage and access to quality health care assumes that no significant that all expected population services. change will be made on growth will be accommodate Establish public spaces and buildings as shelters and urban policy and considers within the current urban footprint Easy access disaster response centers. investments in basic due to densification strategies. to infrastructure infrastructure for expanding This scenario also incorporates and services Create and maintain safe paths for children and adults the urban footprint. key urban policy measures and Low-carbon to walk and bike to schools and other urban amenities. capital investments. personal mobility Build complete streets for a better walking and cycling experience. 3 Source: CARL-Cities 2024. Urban Efficient public Update and expand the public transportation network. mobility transport Decarbonize public transportation. E-mobility Invest in charging stations for electric vehicles. Gradually disincentivize the use and ownership of private vehicles. _______________________________ 39 Each city developed a tailored set of solutions, encompassing various policy levers and investments. For a comprehensive breakdown of these city-specific strategies, please refer to appendix C – Individual City Reports. 84 85 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Key Key Dimension Objective Policy Levers Specific Actions Urban Form Restore and enhance urban green areas and nature in public spaces. Urban Footprint the No Intervention scenario assumes no measures Green infrastructure and nature-based Increase access to consolidated urban green areas Efforts to contain urban expansion and to control sprawl, leading to significant ecosystem solutions of at least 0.5 hectare within a 5-minute walk from implement strategic densification will degradation from converting nonurban land. Adapt to natural residential areas. promote efficient resource use and hazards and sustainable development while reducing In Bishkek, proposed policies could control urban climate risks Build pollutant-specific wastewater treatment plants in industrial parks. nonurban land consumption. Figure 3.3 compares sprawl effectively, potentially minimizing 86 percent Wastewater Modernize and rehabilitate water and sewage projected urban expansion in kilometer square for of urban expansion compared to the No Intervention management infrastructure. the five cities under two scenarios. Under the Vision scenario, resulting in substantial infrastructure cost 4 Explore replacing or complementing gray water and scenarios, urban footprint growth is projected to be lower savings. Shakhrisabz could see a 68 percent reduction waste infrastructure with green ones. in all cities compared to the No Intervention scenario. in urban expansion. Dushanbe and Almaty are projected Urban environment Implement and update building regulations and norms This is due to stringent guidelines and regulations in the to reduce urban expansion by 54.5 and 46.5 percent, Mitigate GHG Energy and Net Zero and Cost-Efficient scenarios that control urban respectively. Namangan could reduce urban sprawl by to meet energy-efficient standards. emissions and water efficiency Incentivize the purchase and use of green appliances. sprawl and promote densification. Consequently, most 36 percent, but its overall projected expansion remains environmental new population growth will occur within the current urban the largest among the five cities, potentially leading to concerns Efficient heating Decarbonize cooking and heating systems in residential footprint, minimizing outward expansion. In contrast, higher infrastructure costs. provision buildings. Promote the installation of renewable microgrid Figure 3.3 Comparison of Projected Urban Expansion Renewable energy technology in residential units and commercial buildings. 800 760 Modernize the CHP plants within cities to efficiently transition from coal to natural gas as the main fuel Decarbonize the source. power industry 600 Invest in carbon capture and storage in the manufacturing and industry sectors. 487 Effective solid Consolidate municipal waste management. 400 waste management Implement integral “Waste-to-Energy’’ facilities. km2 Develop local emission inventories of criteria air Enhanced air 283 pollutants and GHGs. pollution control 200 231 Invest in an automatic pollution monitoring network. Establish a vehicle verification program. 151 93 13 105 97 Incentivize mixed-use densification projects in existing 30 5 urban areas and consolidated neighborhoods. 0 Enhanced Mixed-use and Almaty Bishkek Dushanbe Namangan Shakhrisabz Economic Promote new residential developments to allocate access to jobs densification activity 25-30 percent of the constructed area to nonresidential No intervention scenario 2050 Vision scenario 2050 uses (and job-generating uses). Source: CARL-cities 2024. Based on Urban Performance modeling. Source: CARL-cities 2024. A detailed description of each indicator, calculation method, and source can be found in appendix A Individual City Reports and Urban Performance Methods. Population Density Namangan and Shakhrisabz see the highest increases Implementing strategic densification and at 36 percent each, followed by Dushanbe with nearly urban containment policies will lead to more 30 percent. Bishkek has the highest density under the efficient use of urban space (figure 3.4). The Vision scenario, with a 27 percent increase, while Almaty Vision scenario projects increased population density experiences a 20 percent increase. in all five cities compared to the No Intervention scenario, especially in those with currently low densities. 86 87 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 3.4 Comparison of Projected Population Density Figure 3.5 Expected Proximity Levels to Health Care Facilities 8,000 80.0 6,000 60.0 Population share [%] inhabitants / km² 4,000 40.0 2,000 20.0 0 0.0 Almaty Bishkek Dushanbe Namangan Shakhrisabz Almaty Bishkek Dushanbe Namangan Shakhrisabz No Intervention scenario 2050 Vision scenario 2050 No Intervention scenario 2050 Vision scenario 2050 Source: CARL-cities 2024. Based on Urban Performance modeling. Source: CARL-cities 2024. Based on Urban Performance modeling. Urban Services and Amenities Figure 3.6 Expected Proximity to Educational Facilities 20.0 Health Care Facilities Educational Facilities Expanding reachable health care facilities Investing in new schools and educational improves access to medical services, centers improves residents’ access to basic 15.0 fostering a healthier community. Figure 3.5 education and vocational training. Figure 3.6 shows the projected increase in the population living shows the projected increase in the population living Population share [%] near hospitals or clinics in the five cities under the Vision near these facilities across the five cities under the scenario. Compared to the No Intervention scenario, the Vision scenario, nearly doubling compared to the No 10.0 Vision scenario offers a significant improvement, with an Intervention scenario. average 46 percent increase in proximity to health care facilities due to new investments. Strategically locating schools in densely 5.0 populated neighborhoods bridges the gap in Investing in well-located social infrastructure, educational access. Namangan shows the most especially in densely populated areas, greatly significant improvement, with access increasing 1.6 0.0 enhances accessibility. Almaty leads in improved times from a low 2.4 percent. Bishkek and Shakhrisabz Almaty Bishkek Dushanbe Namangan Shakhrisabz access, with nearly three-quarters of the population also see significant progress, with both cities projected No Intervention scenario 2050 Vision scenario 2050 having convenient access to hospitals and clinics, to double the population living near schools compared almost double the coverage of the No Intervention to the No Intervention scenario, greatly enhancing Source: CARL-cities 2024. Based on Urban Performance modeling. scenario. Bishkek, Namangan, and Dushanbe also show educational opportunities for residents. significant progress, with improvements of 93 percent, 87 percent, and 78 percent respectively. Shakhrisabz is expected to see more modest progress due to its low density and scattered urban pattern. 88 89 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Public Spaces the recreational access gap. Namangan shows Figure 3.8 Expected Proximity Levels to Bus Stops Strategic investment in new public areas the most substantial improvement, with accessibility 80 can create vibrant spaces that empower increasing more than 11 times. Dushanbe and communities and foster economic and Shakhrisabz are projected to more than double the cultural development. Figure 3.7 shows that the number of residents living near parks, with Dushanbe 67 Vision scenarios project a significant increase in the seeing a twofold increase and Shakhrisabz a 1.5- 60 population living near parks and open spaces across the fold increase. This significantly enhances recreational Population share [%] five cities, with nearly 60 percent more residents having opportunities, fostering a healthier and more vibrant 47 easy access compared to the No Intervention scenario. urban environment. 40 44 39 Prioritizing well-located public spaces in 30 densely populated neighborhoods closes 20 24 18 Figure 3.7 Expected Proximity Levels to Public Spaces 2 4 7 60.0 0 Almaty Bishkek Dushanbe Namangan Shakhrisabz No intervention scenario 2050 Vision scenario 2050 Source: CARL-cities 2024. Based on Urban Performance Modeling. 40.0 Population share [%] Urban Environment Exposure to Hazards the Vision scenario reduces this to 0.2 percent, a 95 20.0 Reducing exposure to climate-related hazards percent decrease. Shakhrisabz and Namangan also can be achieved through nature-based show significant progress, with reductions of 52 percent solutions and resilient urban expansion. In the and 69 percent, respectively. Dushanbe and Almaty No Intervention scenario, exposure to natural hazards see more modest improvements of 29 percent and 20 is projected to increase due to settlements in hazard- percent. These improvements highlight the effectiveness 0.0 prone areas and lack of preventive investment. Figures of nature-based solutions and resilient urban planning, Almaty Bishkek Dushanbe Namangan Shakhrisabz 3.9 and 3.10 show that all five cities project a decrease including green areas, corridors, reflective roofs, and No Intervention scenario 2050 Vision scenario 2050 in population at risk under the Vision scenario. Flood overall resilient practices in mitigating UHI exposure. Source: CARL-cities 2024. Based on Urban Performance Modeling. exposure is reduced by implementing nature-based solutions to retain excess rainwater and discouraging Greenhouse Gas Emissions Urban Mobility development in hazard-prone areas. The UHI effect is A strategic commitment to reducing mitigated by nature-based solutions and reflective roofs. greenhouse gas (GHG) emissions through a Proximity to Bus Stops and the development of an inner-city bus rapid transit Bishkek exemplifies the benefits of minimizing flood multisectoral approach can significantly cut Investing in strategic public transportation (BRT) corridor. Shakhrisabz and Dushanbe also show risk, reducing the population in flood-prone areas from local emissions. Figure 3.11 shows the projected corridors improves accessibility. Figure 3.8 significant improvements. Shakhrisabz is expected to see 5.6 percent to 0.7 percent under the Vision scenario. reductions under the Vision scenario, with Almaty and shows that proposed investments in new infrastructure an 80 percent increase in accessibility, while Dushanbe Dushanbe and Almaty also show significant progress, Namangan seeing the largest decreases of 88 percent and public transportation corridors are estimated to is projected to improve by almost 60 percent. These with reductions of 53.3 percent and 32.6 percent, and 73 percent, respectively, compared to the No enhance accessibility to bus stops by an average of expansions target areas currently lacking sufficient respectively. Shakhrisabz can halve its flood-exposed Intervention scenarios. Dushanbe is projected to reduce 45 percent across the five cities. Namangan stands public transport options. Bishkek and Almaty would population, while Namangan sees a reduction from 2.1 emissions by nearly 64 percent, while Shakhrisabz out with a projected 22-fold increase in accessibility experience improvements of 51 percent and 20 percent, percent to 1.5 percent. and Bishkek show more moderate reductions of 30 under the Vision scenario, due to investments in respectively. While these gains are more modest, they percent and 25 percent. Almaty aims for net-zero GHG key corridors connecting surrounding villages (Uyci, still represent significant steps toward enhanced public Bishkek leads in combating urban heat, achieving the emissions, targeting a nearly 90 percent reduction Unkhayat, and Turakurgan) to major activity centers transportation accessibility. most significant reduction under its Vision scenario. In under the Vision scenario. Remaining emissions would the No Intervention scenario, 5.3 percent of Bishkek’s be offset through nature-based solutions and market population is expected to live in UHI-prone areas, but mechanisms. The strategy includes investments in 90 91 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 3.9 Flood Hazard Exposure Figure 3.11 Comparison of Projected Per Capita GHG Emissions 10.0 6,000 8.0 kgCO eq per capita per year 4,000 Population share [%] 6.0 4.0 2,000 2.0 0.0 0 Almaty Bishkek Dushanbe Namangan Shakhrisabz Almaty Bishkek Dushanbe Namangan Shakhrisabz No Intervention scenario 2050 Vision scenario 2050 No intervention scenario 2050 Vision scenario 2050 Source: CARL-cities 2024. Based on SFRARR Population Layer and Hazard Maps (Scaini 2022). Source: CARL-cities 2024, Based on Urban Performance Modeling. Figure 3.10 UHI Hazard Exposure Particulate Matter Emissions40 of 42 percent and 37 percent, respectively. These Local efforts to shift urban transportation, improvements represent substantial steps toward cleaner 80 power generation, buildings, and waste air and lower-carbon development. 29.2 management away from fossil fuels can significantly reduce PM2.541. Policies and Energy Consumption 24.4 investments in energy-efficient buildings, improved public The five selected cities can reduce their 22.7 60 transportation, low-carbon energy sources, and carbon energy consumption by an average of Population share [%] 19.6 capture technologies in the power industry42 can decrease one-third through strategic densification, 16.1 particulate matter emissions. Figure 3.12 shows that the distributed photovoltaic systems, and stricter 14.0 Vision scenarios43 could reduce PM2.5 emissions by an energy efficiency standards for buildings and 11.9 average of 66 percent compared to the No Intervention appliances. Almaty and Namangan have the greatest 20 scenarios, leading to a healthier environment. potential, with projected reductions of 38 percent and 62 percent, respectively, reaching 6,601 kWh and 1,753 5.3 Almaty and Namangan are projected to kWh per capita annually. These improvements result 3.7 0.2 achieve the most significant declines in PM2.5 from a policy toolkit and investment package focusing on 0 emissions, with reductions of 97 percent compact urban growth, walkability, and reduced reliance Almaty Bishkek Dushanbe Namangan Shakhrisabz and 98 percent, respectively. This translates to on diesel vehicles. Stricter energy efficiency standards for No intervention scenario 2050 Vision scenario 2050 decreases from 4,425 tons to 97 tons annually in Almaty, buildings and appliances are crucial. Almaty will benefit Source: CARL-cities, 2024. Based on SFRARR Population Layer and Hazard Maps (Scaini 2022). and from 1,249 tons to 14 tons annually in Namangan. from renewable energy investments, while Namangan’s Shakhrisabz is projected to reduce emissions by 54 energy demand reduction will be driven by enforcing clean urban mobility, reduced energy consumption, percent, while Dushanbe and Bishkek show reductions green building codes and standards. comprehensive solid waste management, and local solar energy generation. Without intervention, Almaty would produce 5,478 kgCO2eq per capita, but the Vision _______________________________ 40 Since there is no local emission inventory, this estimation is based on the EDGAR database. scenario aims to reduce this to 637 kgCO2eq per capita 41 This indicator measures the amount of air pollutants sent to the atmosphere; it is not a measurement of air quality (concentration). before offsets. 42 The model considered an incineration waste-to-energy (WtE) plant with a capacity of 40,000 tons per annum (tpa) (Namrata Joshi 2021). 43 Including public lighting, wastewater treatment, water supply, household electricity and heating, public transportation, private vehicle commuting, and solid waste management. 44 This section examines the energy consumption of public lighting, wastewater treatment, water supply, household electricity, public transportation, private vehicle commuting, and solid waste management. 92 93 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 3.12 Comparison of Projected Per Capita PM2.5 Emissions Figure 3.13 Comparison of Projected Water Consumption 6,000 80 142 142 143 143 4,000 60 Population share [%] PM . /annum 75 75 2,000 20 52 52 47 26 0 0 Almaty Bishkek Dushanbe Namangan Shakhrisabz Almaty Bishkek Dushanbe Namangan Shakhrisabz No intervention scenario 2050 Vision scenario 2050 No intervention scenario 2050 Vision scenario 2050 Source: CARL-cities 2024, Based on Urban Performance Modeling. Source: CARL-cities 2024, Based on Urban Performance Modeling. Water Consumption Solid Waste Management Figure 3.14 Comparison of Projected Share of Wastewater Treatment Implementing and enforcing water-saving Renovating the collection truck fleet and 100 standards for buildings and household densifying neighborhoods can improve waste appliances could reduce Almaty’s water coverage and reduce emissions (figure 3.15). consumption by nearly half by 2050. Under the The solid waste collection indicator measures the Net Zero scenario (figure 3.13), per capita consumption proportion of waste effectively collected by a city. The 75 Share of wastewater treated [%] is projected to drop from 47,000 liters to 26,000 liters Vision scenario aims to enhance solid waste management annually, a 44 percent decrease. This results in an annual by modernizing truck fleets and densifying strategic savings of approximately 21,350 liters per capita. Without areas, significantly improving collection coverage and 50 these interventions, water consumption would remain reducing emissions. Almaty, Namangan, and Dushanbe much higher. provide compelling examples. Almaty could increase collection coverage from 17 percent to 100 percent with 25 Wastewater Treatment 180 new low-carbon trucks. Namangan could achieve The Vision scenario anticipates strategic 100 percent collection by expanding its fleet with 48 new improvements in wastewater treatment trucks, up from 44.5 percent. Dushanbe is projected to across Central Asian cities. Figure 3.14 shows reach 100 percent coverage, up from 68 percent, under 0 Almaty Bishkek Dushanbe Namangan Shakhrisabz that only Namangan and Shakhrisabz increase their the Vision scenario. No intervention scenario 2050 Vision scenario 2050 treatment capacity compared to the No Intervention scenario, thanks to key investments in wastewater Source: CARL-cities 2024, Based on Urban Performance Modeling. treatment plants. Namangan’s treatment capacity could increase by 61 percent, allowing it to treat 58 million cubic meters of wastewater annually, up from 36 percent in the No Intervention scenario. Shakhrisabz would also see significant improvements, with new plants treating 58 percent of its wastewater, or 48 million cubic meters per year. These investments would enhance environmental performance and reduce energy use, yielding cost savings and minimizing environmental impact. 94 95 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Figure 3.15 Estimated Solid Waste Collection Coverage Figure 3.16 Estimated Share of Basic Infrastructure Costs 100 8,000.0 75 6,000.0 Millions of USD Percentage [%] 50 4,000.0 25 2,000.0 0 0.0 Almaty Bishkek Dushanbe Namangan Shakhrisabz Almaty Bishkek Dushanbe Namangan Shakhrisabz No intervention scenario 2050 Vision scenario 2050 No intervention scenario 2050 Vision scenario 2050 Source: CARL-cities 2024, Based on Urban Performance Modeling. Source: CARL-cities 2024, Based on Urban Performance Modeling. Budget Figure 3.17 Estimated Capital Investment Costs for Implementing Recommended Interventions 20,000 Basic Infrastructure Costs Capital Investment Costs The Vision scenario’s promotion of compact The Vision scenario focuses on capital- urban development results in substantial intensive interventions in energy, cost savings and additional funds for social transportation, and urban sectors to achieve 15,000 infrastructure (figure 3.16). Basic infrastructure long-term sustainability goals (figure 3.17). costs are projected to be 43 percent higher on average These costs include specific policy interventions beyond Millions of USD under the No Intervention scenario compared to the Vision basic infrastructure. For example, Almaty’s goal of carbon 10,000 scenario. This means basic infrastructure consumes 68 neutrality by 2050 requires an estimated $15.79 billion percent of the local budget under No Intervention, but investment ($16.65 billion with offsets), with renewable only 25 percent under the Vision scenario. This shift not energy initiatives comprising 44 percent, urban infill 9 5,000 only delivers environmental benefits but also frees up percent, and energy efficiency measures 7 percent. significant capital for other strategic initiatives. Bishkek and Shakhrisabz would achieve the most significant cost Similar trends are seen in other cities. savings, with potential reductions of up to 86 percent Bishkek’s Vision scenario prioritizes infill development 0 Almaty Bishkek Dushanbe Namangan Shakhrisabz and 68 percent, respectively. Dushanbe, Almaty, and and public transportation, allocating 90 percent of the No intervention scenario 2050 Vision scenario 2050 Namangan also see substantial savings, with reductions budget to these areas. Dushanbe’s interventions in of 54.5, 46.6, and 45.5 percent, respectively. infill development, public transportation, and energy Source: CARL-cities 2024, Based on Urban Performance Modeling. efficiency account for 86 percent of its budget. Namangan allocates 40 percent of its resources to urban retrofit and renewable energy. In Shakhrisabz, the focus is on energy efficiency, wastewater treatment, and emissions control, which make up 67 percent of the budget. 96 97 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 4 Lessons Learned from the Deep- Dive Analysis The deep-dive analysis revealed that Different Interventions for each city’s path to low-carbon, resilient Common Challenges development is shaped by its unique context and resource management. A comparative While cities share common urban concerns, analysis of five cities showed both commonalities and the impact on development varies, differences, offering valuable lessons. Integrating these necessitating different priorities based on insights helps understand current conditions, potential each city’s unique situation. For example: future scenarios, and derive key takeaways for the region. Bishkek faces challenges from a carbon- These lessons can guide policy recommendations, intensive power industry and rapid urban aiding in navigating urban development complexities expansion, straining infrastructure and services. and fostering sustainable growth. Shakhrisabz struggles with energy scarcity and high building-related GHG emissions, Common Challenges and impacting power demand and contributing to Shared Realities climate change. Dushanbe has significant transportation- The deep-dive analysis identified common related carbon challenges, with heavy reliance challenges in all five cities, including on fossil fuels causing high GHG emissions and unsustainable urbanization, high carbon intensity, air air pollution. pollution, vulnerability to natural hazards, and limited Namangan deals with limited green urban access to social infrastructure. These issues result areas and high residential energy demand in traffic congestion, longer commutes, loss of natural emissions. habitats, high GHG emissions, poor air quality, and social inequalities. Policies and investments emphasize low- carbon and renewable energy generation but Compact urban development offers a solution vary by city context. For instance: to these challenges. It reallocates resources from Bishkek focuses on retrofitting CHP1 and expansion costs to sustainable interventions, reducing using gas, with investments in distributive hazard exposure and improving access to urban renewable sources. amenities and public services. For example, nature- Dushanbe prioritizes carbon capture and based solutions like green corridors can mitigate floods storage technologies, with future solar power and heat effects, while efficient public transportation considerations. reduces reliance on motorized vehicles. Shakhrisabz emphasizes solar grid upgrades, storage solutions, and phasing out carbon Another key lesson is the need for specialized energy sources. urban data. The lack of standardized and complete Almaty integrates solar technologies to reduce data hampers reliable insights and effective policies. reliance on fossil fuels, aiming for net-zero Improving urban data infrastructure is essential for emissions by 2050. accurate monitoring, identifying improvement areas, Namangan and Shakhrisabz focus on and anticipating future trends, enabling evidence-based energy efficiency in residential areas and decision-making for low-carbon, resilient urban planning. renewable investments. Source: CAPSUS, 2023, Almaty [Photograph] 98 99 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Urban growth scenarios also differ: Almaty adopts a net-zero scenario aiming for The other cities adopt a cost-efficient These tailored approaches highlight the importance of diversifying energy sources to achieve cleaner, more net-zero emissions by 2050, incurring higher scenario, using current budgets and savings from context-specific interventions for effective and sustainable sustainable practices. Figure 4.1 summarizes the key costs but yielding significant benefits. compact growth for sustainable improvements. urban development, enhancing energy efficiency, and differences in results yield between the two scenarios. Figure 4.1 Summary of Selected Indicators and Results from Scenario Modeling Kazakhstan Almaty Kyrgyz Republic Bishkek Tajikistan Dushanbe Uzbekistan Namangan Uzbekistan Shakhrisabz 100 101 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 5 Key Recommendations This section builds on the study’s findings to propose infrastructure access, natural hazards, GHG emissions, recommendations addressing regional and urban and environmental concerns. The recommendations are challenges, aiming to achieve ambitious objectives. organized by key objectives (table 5.1): These challenges include urban development, 1 Becoming livable and green cities 2 Improved access to infrastructure and services 3 Adapting to natural hazards and climate risks This section also highlights best Mitigating GHG emissions and practices from Central Asia and 4 environmental concerns globally, demonstrating how these recommendations can be implemented. 5 Enhanced access to jobs By combining local needs with international best practices, it aims to guide and support low-carbon, resilient urban development in the region. Figure 5.1 Key Recommendations and Actionable Items in Five Key Dimensions Key Key Dimension Objective Policy Levers Specific Actions Develop and implement urban planning and People-centered design guidelines for compact and people-oriented urban design urban forms. Promote infill growth and contiguous peri-urban growth. Sustainable Encourage appropriate densification through updating 1 Livable and urban growth urban plans and guidelines. Urban Form green cities Establish urban limits where appropriate. Prevent construction and urban development in hazard- prone areas. Land use planning Update relevant building and construction codes to be for resilience seismic and climate-resilient. and equity Promote affordable housing in central areas. Be sensitive and respond to market forces while safeguarding the public interest. Adopt Transit-Oriented Approach (TOD) Redevelop and repurpose brownfield sites and 2 underutilized plots. Easy access Urban regeneration Facilitate the construction and upgrade of housing units Urban to infrastructure and multifunctional services and in well-served areas and neighborhoods. and services community facilities amenities Transform single-use public buildings into multifunctional community buildings. Source: CAPSUS, 2023, Uzbekistan [Photograph] 102 103 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Key Key Key Key Dimension Objective Policy Levers Specific Actions Dimension Policy Levers Specific Actions Objective Create a network of cultural and sports facilities. Incentivize mixed-use densification projects in existing 2 Urban regeneration Improve coverage and access to quality health care 5 urban areas and consolidated neighborhoods. Enhanced Mixed-use and Urban and multifunctional services. Economic Promote new residential developments to allocate access to jobs densification services and community facilities Establish public spaces and buildings as shelters and activity 25-30 percent of the constructed area to nonresidential amenities Easy access disaster response centers. uses (and job-generating uses). to infrastructure and services Create and maintain safe paths for children and adults Source: CARL-Cities 2024. Low-carbon to walk and bike to schools and other urban amenities. personal mobility Build complete streets for a better walking and cycling experience. 3 Urban Efficient public Update and expand the public transportation network. Dimension 1: Livable Green Cities mobility transport Decarbonize public transportation. The development of cities in the region should Invest in charging stations for electric vehicles. E-mobility Gradually disincentivize the use and ownership of embrace compact urban growth. private vehicles. Urban development in the region should the Kyrgyz Republic, and Kazakhstan. Extensive low- Restore and enhance urban green areas and nature in promote adequate population density density development increases infrastructure costs by Green infrastructure public spaces. and access to public services and social an average of 60 percent. Therefore, local authorities and nature-based Increase access to consolidated urban green areas solutions of at least 0.5 hectare within a 5-minute walk from infrastructure. Currently, many Central Asian cities should encourage compact urban development, focusing Adapt to natural residential areas. face rapid urbanization and inefficient land use, leading on dense populations and walkable neighborhoods near hazards and to low-density development. This issue is particularly basic services and jobs, accessible by nonmotorized, climate risks Build pollutant-specific wastewater treatment plants in severe in medium and small-sized cities in Tajikistan, clean transport options. industrial parks. Wastewater Modernize and rehabilitate water and sewage management infrastructure. Urban data is essential for developing effective evidence-based 4 Explore replacing or complementing gray water and policies to promote low-carbon, resilient urban development. waste infrastructure with green ones. Urban environment Cities in Central Asia need to improve evidence-based decision-making, and implementing Implement and update building regulations and norms Mitigate GHG Energy and data production, management, and use to targeted policies. Developing local emission inventories to meet energy-efficient standards. emissions and water efficiency Incentivize the purchase and use of green appliances. accurately assess performance and deliver for GHG emissions and air pollutants (such as their environmental effective policies. The study’s findings and types, quantities, and sources) is essential for crafting concerns Efficient heating Decarbonize cooking and heating systems in residential proposals rely on the best available, though often limited, effective strategies and public policies for healthy, low- provision buildings. information. Establishing robust city data infrastructure is carbon development. Promote the installation of renewable microgrid crucial for managing urban data systematically, supporting Renewable energy technology in residential units and commercial buildings. Modernize the CHP plants within cities to efficiently Suggested specific actions (SAs) for livable and green cities include: transition from coal to natural gas as the main fuel Decarbonize the source. power industry Invest in carbon capture and storage in the 1 People-Centered Urban Design manufacturing and industry sectors. SA1. Develop and implement efficiency, and balanced streetscapes. Effective solid Consolidate municipal waste management. guidelines for compact, dense, By creating people-oriented urban design waste management Implement integral “Waste-to-Energy’’ facilities. and people-oriented urban forms, guidelines, cities in CA can ensure ensuring better quality of life and that new developments--whether new Develop local emission inventories of criteria air Enhanced air pollutants and GHGs. compatibility with existing neighborhoods. construction or the renewal of existing pollution control Invest in an automatic pollution monitoring network. Strategies include investing in critical infrastructure-- promote adequate Establish a vehicle verification program. infrastructure, promoting higher urban densification, sustainability, and social density, mixed land use, energy development in the long term. 104 105 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 2 People-Centered Urban Design 3 Land-Use Planning for Resilience and Equity SA2. Promote infill and contiguous spaces, public transportation access, and SA8. Balance housing market SA9. Adopt a Transit Oriented peri-urban growth. Expanding a city’s infrastructure resilience. These guidelines forces with public interest to Development (TOD) approach. urban footprint requires funds for new should promote a mandatory framework ensure equitable access to housing and Cities should develop new housing infrastructure and increases travel time. for citywide implementation and foster promote economic development. Cities within walking distance of transit stations Cities should utilize unused or underused evidence-driven decision-making in should prioritize affordable housing in new and create transport hubs in dense land within or near the city with good urban planning. developments and integrate regulatory neighborhoods. Affordable housing near access to social infrastructure, public measures. Key actions include: (i) using transit benefits low-income households services, goods, and jobs. This approach SA4. Establish urban limits to market-based solutions like inclusionary by providing access to jobs, education, saves budgetary resources and improves control sprawl and protect natural zoning and PPPs for affordable housing and services, and increases return on environmental performance in Central areas providing ecosystem projects; (ii) encouraging development investment for local governments in Asian cities.Promote infill growth and services. Tailor containment boundaries in both low-income and mixed-income transit infrastructure. contiguous peri-urban growth. to each city’s unique circumstances, as areas to prevent segregation and existing regulations may differ. Local promote social cohesion; (iii) establishing SA3. Encourage appropriate governments should periodically review a regulatory framework that promotes densification by updating urban and adjust these boundaries to protect public participation in housing provision; plans and guidelines. Strategic significant areas and allow for peri-urban and (iv) involving communities and the densification aims to increase urban growth. Regulations could prohibit land- private sector in decision-making for new density sustainably, enhancing the city’s use changes or construction permits housing developments. livability, sustainability, and resilience. Key outside the urban perimeter. elements include energy efficiency, green 3 Land-Use Planning for Resilience and Equity Regional Best Practices SA5. Prevent construction in for impacts like increased temperatures Kazakhstan’s national efforts to Tajikistan’s Green Economy hazard-prone areas by addressing and rising sea levels; (iii) conducting risk promote agglomeration development and Development Strategy (GEDS) 2023-2037 urban sprawl. This region is highly assessments to identify hazard-prone support urban priorities are commendable. and Dushanbe’s Green City Action Plan vulnerable to earthquakes, floods, areas and design local responses; (iv) This includes investing in infrastructure, (GCAP) promote sustainable development and landslides. Unplanned expansion investing in capacity-building programs connectivity, and strategic densification and empower local agencies. increases risk. Urban growth in Central to train construction professionals; and to combat urban sprawl. The Green City Asia should consider natural risk factors. (v) fostering public awareness and Action Plan (GCAP) for Almaty 2022 Uzbekistan emphasizes the role Strategies include increasing fines for engagement on the importance of updated exemplifies sustainable urban growth, of cities in environmentally conscious illegal construction and establishing a building codes. aligning with national goals and addressing socioeconomic development through public-private monitoring system where climate change and resilience. the Green Economy Transition Strategy the private sector receives a percentage SA7. Promote affordable housing 2019-2030 and the Green Economy of the fines. in new residential developments The Kyrgyz Republic uniquely and Green Growth Transition Program and central areas to ensure inclusive incorporates a vision for green cities in its 2030. These frameworks aim to enhance SA6. Update relevant building economic development and adequate long and midterm national development urban environmental sustainability and and construction codes to be housing for all. This policy aims to plans. The next step is to create local decentralize power to support sustainable seismic and climate-resilient. mitigate gentrification and reduce rental urban planning documents for cities and growth, providing a pathway for the This action minimizes disaster risks and prices, providing housing for low-income towns. sustainable development of cities by 2050. ensures urban infrastructure safety and residents. By encouraging densification sustainability. Key strategies include: (i) and accessible social services, cities can ensuring building codes withstand seismic enhance spatial justice in the region. forces; (ii) integrating climate resilience 106 107 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Dimension 2: Easy Access to Infrastructure and Services International Best Practice: Ulaanbaatar, Mongolia (AHURP) To increase livability and reduce carbon intensity, cities in CA should The Affordable Housing and Resilient Urban resilient ecodistricts with low-carbon affordable improve accessibility to social infrastructure and urban amenities. Renewal Sector (AHURP) project in Mongolia housing. Designed with community input, these aims to enhance Ulaanbaatar’s climate resilience neighborhoods will offer accessible services and Over 90 percent of Central Asian city Cities could also improve access to by investing in low-cost urban infrastructure, amenities. Housing units will cater to diverse residents lack convenient access to public transportation and nonmotorized public facilities, and social housing (photo 5.1). incomes: 15 percent for social green housing, 55 urban amenities like parks and healthcare alternatives. The macro assessment reveals a By developing self-sufficient ecodistricts in city percent for affordable green housing, and 30 percent facilities, increasing carbon emissions from significant lack of accessibility to public transportation, subcenters, AHURP seeks to improve urban quality for market-rate green housing. AHURP plans to build commuting. Local authorities could address this by with only 7 percent of residents living near a bus stop. and reduce traffic congestion. 10,000 housing units in a 100-hectare area between increasing urban amenities and social infrastructure, Local governments could promote sustainable mobility 2022 and 2027, increasing density in new ger areas upgrading existing facilities, and promoting their use by expanding the public transportation network, adding The project will transform climate-vulnerable and providing housing, social infrastructure, and in well-served areas. New facilities should be built in new routes, and enhancing infrastructure like right-of- and polluting ger districts 45 into climate- public services to low- and middle-income families. underserved areas, and existing ones modernized. way lanes. Redesigning streets to prioritize walking Improving the built environment for safer walking and cycling safety, balancing space for pedestrians Photo 5.1 AHURP Building Site in Ulaanbaatar, Mongolia and cycling, and increasing population density near and vehicles, and providing protected pedestrian and amenities, will reduce energy consumption and transport cycling infrastructure will encourage healthier, low- emissions while enhancing accessibility. carbon transportation options. The specific actions suggested for achieving the key objective of easy access to infrastructure and services are: 4 New Social Infrastructure SA10. Redevelop and repurpose SA12. Transform single-use public brownfield sites and underused buildings into multifunctional urban plots by promoting mixed- community spaces. Most Central use development and creating Asian residents lack convenient access to more public spaces. Facilitate urban amenities and social infrastructure. building permits in central areas and Cities should extend the hours of public provide economic and fiscal incentives facilities and integrate compatible for infill development and renovation activities within them. This will improve projects that comply with local green accessibility, strengthen community ties, building codes. and reduce social service costs. Adapt existing buildings to accommodate various SA11. Facilitate the construction activities, such as libraries, community Source: Asian Development Bank. (2024). and upgrading of housing in centers, and childcare facilities. well-served neighborhoods. Local authorities could invest in revitalizing SA13. Create a network of these areas by upgrading basic services cultural and sports facilities to and infrastructure, improving public promote cohesive, resilient, and inclusive buildings and spaces, and increasing communities. Cities could invest in energy- and water-efficient housing units. constructing or upgrading community centers, public parks, and shared spaces. These investments strengthen social ties and increase the city’s social capital. _______________________________ 45 “Ger” districts are residential areas in Mongolia. They usually consist of parcels with one or more detached traditional mobile dwellings or gers (hence the name) and are usually informal and in the peri-urban areas of cties. 108 109 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 4 New Social Infrastructure 7 E-Mobility SA14. Improve coverage and SA15. Designate public spaces SA20. Invest in charging stations SA21. Gradually disincentivize access to quality health care and buildings as shelters and for public and private electric private vehicle use and ownership services. The assessment reveals disaster response centers. To vehicles (EVs) to reduce GHG to promote sustainable urban spatial injustice in proximity to health enhance city resilience and ensure quick emissions and improve air quality in CA mobility. Measures could include facilities. Creating new facilities is disaster response, these shelters should cities. Transitioning from fossil-fueled to congestion pricing, car-free zones, essential, but their location is critical. be disaster-resistant and capable of electric vehicles can significantly lower vehicle-emissions fines, and increased Focus on building medical centers and autonomous operation, providing safe the carbon footprint. Key strategies parking fees. Reducing private vehicle use clinics in densely populated areas far refuge and serving as coordination points include promoting subsidies for charging decreases traffic congestion and carbon from existing public health facilities. for relief efforts. infrastructure, exploring public-private emissions. Ensure sustainable alternatives This will enhance health outcomes and partnerships (PPP) for installation like public transportation, cycling, and improve spatial equality. and maintenance, and providing fleet pedestrian pathways are available, conversion incentives for private vehicles, enhancing social equity by providing businesses, taxi companies, and public affordable transportation for all residents. 5 Low-Carbon Personal Mobility transportation agencies. SA16. Create and maintain safe SA17. Build complete streets to walking and biking paths to enhance walking and cycling. While schools and urban amenities. many cities support active mobility, local Enhancing street and sidewalk safety authorities should design environments International Best Practice: Open Schools in Tirana, Albania46 improves access to public facilities and that promote nonmotorized transport, supports social mobility. This could be especially near public transportation Tirana’s innovative Open Schools program and revitalize suburban areas. By opening public achieved by widening sidewalks, adding stations and social infrastructure (within transforms educational facilities into vibrant schools beyond traditional hours, Open Schools crosswalks, planting trees, providing 1,000 meters). This involves redesigning community hubs. These spaces function as integrates education into residents’ lives. The plan shade, and installing traffic calming streets to allocate safe spaces for walking traditional schools on weekdays and become envisions 17 new schools by 2030, starting with measures and lighting. Safe routes and cycling, creating safe cycle parking, accessible to the community on evenings, three in Don Bosko, Köder-Kamëz, and Shqiponja, encourage walking and biking, reduce and bike lanes, and protecting pedestrian weekends, and holidays, serving as recreational inaugurated in 2021. These schools offer canteens, air pollution, and lower GHG emissions. and cycling infrastructure from motorized areas, meeting places, and emergency shelters, multipurpose halls, libraries, and sports facilities, Implement road safety measures around traffic. fostering community life. accessible from both inside and outside the these facilities and public spaces. buildings. The Tirana 2030 masterplan incorporates this concept to address the city’s growing population 6 Efficient Public Transport SA18. Update and expand the SA19. Decarbonize public public transportation network. transportation. Cities could adopt Efficient options like trolleybuses and energy-efficient, low-emission vehicles buses are well-known in Central Asia. to reduce fossil fuel dependency, GHG To attract more riders, cities should emissions, and air and noise pollution. prioritize funding to expand coverage and Modernize bus fleets to battery-electric, implement transport-priority corridors. hydrogen, or natural gas units. For electric This will reduce traffic congestion, air vehicles, reduce the carbon intensity of pollution, and GHG emissions. the national grid by introducing pollution controls, cleaner fuels, and renewable energy sources. _______________________________ 46 See Stefano Boeri Architetti – Open Schools | Tirana. 110 111 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Dimension 3: Adapt to Natural Hazards and Climate Risks 9 Wastewater Management To enhance resilience against climate-driven hazards, cities can leverage the power of nature-based solutions and adopt resilient SA24. Build pollutant-specific enhance local sewage systems and build urban development practices. wastewater treatment plants new treatment facilities. in industrial parks. Industrial Cities should prevent construction in hazard- Additionally, supporting green roofs, white roofs, and wastewater requires different treatment SA25. Modernize and rehabilitate prone areas, as the region is vulnerable to vertical gardens can further reduce heat absorption. than household waste. Cities in CA water and sewage infrastructure. earthquakes, floods, and landslides. Unplanned could form public-private partnerships These systems are essential for expansion increases the number of vulnerable people. CA cities should prioritize climate-smart to develop these facilities, funded by community well-being and public health. To ensure resilient development, cities must prioritize policies to protect public health and reduce wastewater fees on industries and higher Cities in this region struggle to meet urban planning with hazard risk assessments. GHG emissions. They face challenges like air taxes or fines for untreated discharges. demand due to outdated Soviet-era Additional measures include early warning systems, quality, water pollution, and flood exposure. While Investing in advanced monitoring infrastructure and urban sprawl. Aligning retrofitting existing structures in moderate-risk areas, local governments have strategies to mitigate these technologies will ensure accurate urban containment measures with water and developing a risk atlas to identify unsuitable areas issues, most lack a climate change vision. For example, measurement of wastewater quantity and infrastructure retrofits can help prioritize for urbanization. Kazakhstan plans to introduce natural gas and electric quality. Fees, taxes, and fines based on areas for improvement and allocate buses, Uzbekistan aims for 80 percent electric or natural discharge volume and pollutant content resources efficiently, allowing for the Cities can improve resilience to weather gas-powered public transit by 2030, the Kyrgyz Republic will incentivize sustainable practices. repair and upgrade of existing networks events by expanding multifunctional green targets 80 percent of urban passenger volume with Revenue from these measures could to handle increased demand. spaces , 47 reducing exposure to UHI and these vehicles, and Tajikistan promotes electric vehicles flooding. Implementing green corridors and reducing to reach a 55 percent share by 2037. However, these heat absorption in built-up areas are key strategies. Local investments focus on reducing pollutant emissions authorities could invest in tree trenches along sidewalks rather than specific GHG reductions. Cities that design and roads, and revitalize underused plots and degraded climate-smart policies can better protect public health, Regional Best Practices public spaces with vegetation and water features reduce carbon intensity, and build resilience. to manage stormwater and regulate temperature. Most countries in the region have set Regional climate change frameworks ambitious targets for urban environment promote a low-carbon, resilient approach and risk management. The Kyrgyz Republic’s in CA cities. All countries participate in the The specific actions suggested for achieving the key objective of adapting to National Development Strategy 2018-2040 (NDS- Sendai Framework for Disaster Risk Reduction natural hazards and climate risks are: 2040) guides policy and investments, emphasizing and aim to incorporate its principles into domestic the expansion of green areas to mitigate climate policies. Transboundary cooperation, such as the 8 Green Infrastructure and Nature-Based Solutions (NBS) change risks. Uzbekistan’s New Uzbekistan Regional Center for Emergency Situations and Development Strategy 2022-2026 coordinates with Disaster Risk Reduction (CESDRR) established SA22. Restore and enhance urban like tax-increment financing, carbon every region in the country and set city-level urban by Kazakhstan and the Kyrgyz Republic, supports green areas and nature in public bonds, and value-capture taxes. environment targets, including planting millions of regional resilience. Continuing these frameworks will spaces. Environmental degradation trees to improve air quality. significantly aid the region’s resilient pathway. negatively impacts biodiversity, SA23. Ensure access to urban ecosystem services, and public health. green areas of at least 0.5 Cities could increase access to green hectares within a 5-minute walk areas and restore degraded spaces with from residential areas. These green native species to counteract the UHI spaces offer social and environmental effect. To fund these efforts, cities could benefits, including flood management, seek national and international green temperature regulation, biodiversity funds, public income, and public-private sheltering, air quality improvement, soil partnerships, and evaluate instruments protection, and water runoff prevention. _______________________________ 47 According to WHO (2017) the population should be able to access consolidated urban green areas of at least 0.5 hectare within a 5-minute walk from residential areas. 112 113 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 International Best Practice: La Quebradora Park, Iztapalapa, Mexico City Photo 5.3 Little Sugar Creek, Charlotte, North Carolina La Quebradora (Vargas Lara 2018) is a 4-hectare benefiting up to 28,000 residents. It increases public public park in one of Mexico City’s densest districts, space per capita from 1.1 to 2.9 m2, improves water offering cultural and recreational activities (photo capture and infiltration, and reduces flood hazards 5.2). The park addresses water management issues in surrounding streets. The park features a skate like drinking water scarcity, flood hazards, sinking park, swimming pool, basketball courts, open-air ground, and reduced aquifer recharge. Using gym, and multifunctional classrooms. It includes Water Sensitive Urban Design (WSUD), the park a wastewater treatment plant, bioswales for water captures rainwater and infiltrates it into the aquifer, demand, and solar panels for electricity. Photo 5.2 La Quebradora Park, Mexico City Source: Institute for Transportation Research and Education. (2015). Little Sugar Creek Greenway Urban Section Pedestrian Downtown [Graphic]. Licensed under CC by 2.0. Integrating green infrastructure in this dense urban The transformation began in 2002 with the removal area faced challenges like property acquisition, of the concrete cap, followed by replanting native business relocation, flood-resilient design, and vegetation and restoring creek banks. These efforts freeway proximity. Ecologically, the main goal was brought back wildlife and changed community to restore the creek’s health, requiring robust public perception, with residents valuing the creek’s beauty involvement through stakeholder interviews and and ecological benefits. The project’s success relied community open houses. on public-private partnerships. Dimension 4: Mitigate Greenhouse Gas Emissions and Environmental Concerns Low-carbon development requires clean local energy generation, and a set of energy-efficiency measures in existing residential buildings. Source: © Elprimoshere, Licensed under CC0 1.0 Universal. Achieving low-carbon urban development coal-fired CHP plants. To reduce emissions, the region requires transitioning to clean local energy could decrease reliance on solid fuels and increase sources. Analyses show the power industry is a clean energy production, such as solar, wind, hydro, and International Best Practice: Little Sugar Creek, Charlotte, North Carolina (USA) major carbon emitter, responsible for nearly one-third geothermal power. Additional measures include investing of regional emissions. In cities like Aktau, Osh, and in renewable energy, setting incentives for distributed The Little Sugar Creek Greenway (LandDesign n.d.) thousands of visitors monthly. The waterfront has Temirtau, 48 power generation emissions can exceed 50 generation, and implementing abatement technologies. spans 800 acres and serves as a vital city corridor seen significant retail and residential growth, creating percent of their carbon footprint. This is mainly due to (photo 5.3). Completed in 2012, this multifunctional picturesque landscapes. Once a neglected and green space connects neighborhoods, parks, polluted waterway, Little Sugar Creek’s transformation civic facilities, schools, and open areas, attracting began in 1990 by Mecklenburg County. _______________________________ 48 EDGAR data (Monforti Ferrario et al. 2021) reveals that the power industry is a significant contributor to carbon emissions in Aktau (71 percent), Osh (65 percent), and Temirtau (64 percent). 114 115 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Energy-efficient strategies and local green Net Zero scenario and 23 percent under a Cost-Efficient building codes can significantly reduce carbon scenario. Carbon emissions could decrease by up to and air pollutant emissions. By updating building 31% with strong retrofitting efforts, while fine particulate 10 Energy and Water Efficiency regulations to meet energy-efficient standards, local matter could drop by 56 percent under the Net Zero SA27. Incentivize the purchase refrigerators, washing machines, dryers, governments can lower per capita GHG and particulate scenario. To achieve these reductions, it is essential to and use of green appliances energy-efficient stoves, LED light bulbs, matter emissions from the construction sector. Analysis improve insulation, phase out polluting fuels, and adopt through rebates and tax breaks and smart thermostats. Slow adoption shows potential reductions in air pollution and carbon modern heating and cooling technologies. to make them more affordable hinders energy goals and increases emissions, with PM2.5 emissions decreasing by 14-97 and attractive, accelerating the GHG emissions; thus, incentivizing green percent and GHG emissions by 2-40 percent. Cities in To curb transportation-related CO2 emissions, transition to sustainable energy appliances complements other energy- CA could enforce higher energy-efficiency standards CA cities should prioritize sustainable efficiency. Prioritize high-efficiency efficient and low-carbon initiatives. for buildings and appliances, and incentivize energy- transportation by reducing the use of diesel efficient technologies in existing buildings through fiscal and gasoline-fueled vehicles. This can be incentives and grants. Governments could also partner achieved through regulations limiting these vehicles, 11 Efficient Heating with international financing institutions and banks to promoting low-carbon public transport, and encouraging offer green mortgages for environmentally efficient SA28. Decarbonize cooking and Upgrade heating systems to energy- non-motorized modes of transport. Key actions housing and buildings. heating systems in residential efficient alternatives like heat pumps, include limiting obsolete vehicle imports, conducting buildings by focusing on which can significantly reduce emissions environmental checks on public transport, phasing out Decarbonizing residential cooking and combined renovations of building when paired with low-carbon electricity. older vehicles, and offering incentives for low-carbon heating is crucial for low-carbon development. envelopes and heating systems. For cooking, update equipment and electric vehicles. Additionally, promoting public This involves renovating building envelopes to improve Enhance insulation of windows and regulations and consider programs for transport can involve implementing low-emission and insulation and upgrading heating systems to modern, doors to minimize heat loss in winter improved stoves, fuel switching (coal to car-free zones, expanding public transport infrastructure, energy-efficient alternatives like heat pumps and eco- and reduce cooling needs in summer. gas if feasible), and better solid fuels. and developing safe pedestrian and cycling paths. friendly stoves. These measures reduce heat loss, lower Analysis shows that reducing motorized vehicle use energy demand, and cut air pollutants. Analysis shows and expanding public transport, combined with strategic that retrofitting heating technology and using energy- densification, can significantly cut commuting-related 12 Renewable Energy efficient stoves can reduce annual household energy greenhouse gas emissions. SA29. Promote renewable for buildings, social facilities, and street consumption per capita by up to 30 percent under the microgrid technology in residential lights. This transition reduces carbon and commercial buildings. Access intensity, promotes community resilience, to clean, reliable electricity is essential diversifies energy sources, and lowers The specific actions suggested for achieving the key objective of Mitigating for economic development and quality GHG emissions. Cities can offer economic GHG Emissions and Environmental Concerns are: of life. Implement distributed renewable incentives and capacity-building programs solutions like photovoltaic panels on roofs to accelerate this shift. and facades to generate solar energy 10 Energy and Water Efficiency SA26. To reduce per capita GHG existing buildings, cities can incentivize 13 Decarbonization of the Power Industry emissions in the construction energy-efficient technologies and sector, cities should implement low-scale renewable energy systems SA30. Modernize CHP plants in Invest SA31. in carbon and update building regulations to through fiscal incentives and grants. cities to transition from coal capture and storage (CCS) in meet energy-efficient standards. Additionally, governments can partner to natural gas. Cities in CA face manufacturing and industry. This includes enforcing higher energy- with international financing institutions power sector pollution but lack control Incorporating CCS technologies can efficiency standards for buildings and and banks to offer lower-rate green over operations. National governments significantly reduce GHG emissions household appliances, as well as new mortgages for environmentally efficient should modernize CHP plants to boost by capturing CO2 at the source and commercial and office buildings. For housing and buildings. efficiency and cut emissions. Additionally, preventing its release. This involves CA can expand renewable energy, both capturing, compressing, and securely utility-scale and distributed, and invest in storing CO2 in carbon sinks. carbon capture and storage where fuel substitution isn’t feasible. 116 117 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Regional Best Practices 14 Effective Solid Waste Management Central Asian countries are committed to buildings and developed “green” technical passports SA32. Consolidate municipal SA33. Implement “Waste-to- reducing energy intensity. Kazakhstan aims for construction. waste management to mitigate Energy” facilities as part of a low- for a 30 percent reduction by 2030 and 50 percent environmental degradation, improve carbon waste management strategy. Use by 2050, while Uzbekistan targets a 30 percent Transportation strategies promote public health, and enhance resource biodigesters to treat organic material and reduction by 2030. The Kyrgyz Republic aims for a electric vehicles and invest in charging efficiency. In CA, challenges include capture biogas for generating electricity 4.5 percent reduction by 2023.49 All countries plan to infrastructure. Kazakhstan considers natural incomplete collection, inadequate landfill and heat in areas with significant reduce energy consumption in housing, public, and gas and electric buses, Uzbekistan aims for 80 space, and insufficient recycling systems. biodegradable waste. Assess and define industrial sectors by introducing resource-efficient percent electric or natural gas public transport Cities need to develop infrastructure for the best technological options suited to technologies, reducing transmission and distribution by 2030, the Kyrgyz Republic targets 80 percent waste collection, treatment, and recycling. each city’s local context. losses, and enhancing building energy efficiency. clean-powered public transport in major cities, and Addressing these needs will help mitigate Tajikistan promotes electric vehicles for both private GHG emissions through sorting and Energy efficiency in housing and and public use. Most countries offer tax and fee recycling, waste-to-energy solutions, and infrastructure is a priority for Central benefits on electric vehicle imports, boosting their pollutant control at disposal sites. Asian countries. Kazakhstan leads in building popularity. Tajikistan is implementing an electric taxi energy efficiency, setting clear consumption targets, project, the Kyrgyz Republic is considering electric encouraging retrofitting, and enhancing subnational official vehicle fleets, and Kazakhstan is expanding 15 Enhanced Air Pollution Control control and monitoring. The Kyrgyz Republic electric vehicle infrastructure in large cities. has introduced energy efficiency certification for SA34. Develop local emission contingency programs for extreme inventories of criteria air pollution, and protect public health. In pollutants and GHGs. These reports many cities, these networks are essential list all sources of pollutants in an area, for air quality and public health initiatives. International Best Practice: Green Mortgage Program, Mexico detailing types, amounts, and sources. Mexico’s Green Mortgage Program, initiated by program achieves nearly one ton of CO2e savings This data informs public policies to SA36. Establish a vehicle Infonavit, offers extra loans at lower rates for per household annually, with monthly savings of $13, improve air quality and monitor progress. verification program with mandatory purchasing energy- and water-efficient homes (photo seven cubic meters of water, and over 200 kWh. Major metropolitan areas should regularly inspections for private cars, motorcycles, 5.4). It includes incentives for developers and is linked Recently, private banks in Mexico have implemented monitor GHGs and air quality, updating trucks, and buses to test safety and to public subsidies and housing credit rules. The similar programs to promote efficient homes. inventories at least every two years. emissions. This will reduce highly polluting vehicles and improve urban air quality. Photo 5.4 Photovoltaic System for Residential Use SA35. Invest in an automatic The program could be linked to initiatives pollution monitoring network. like “day without a car” or ecozones. These systems help identify air quality Design the policy to reward low-carbon issues, track policy performance, and technologies (hybrids, electric, natural pinpoint pollutant sources and their gas) and discourage high-carbon options interaction with weather. They support through fines, use restrictions, and evidence-based policy design, inform enforcement. the public about air quality, activate Source: © CAPSUS. Used with the permission of CAPSUS. Further permission required for reuse. _______________________________ 49 At the time of writing, there was no report available on the achievement of this goal. 118 119 Reimagining Central Asian Cities for a Resilient and Low-Carbon Future June 2024 Dimension 5: Enhanced Access to Jobs International Best Practice: Low-Emission Zone, Jakarta, Indonesia Mixed-Use Development Is Key for Thriving Low-Carbon Cities A Low-Emission Zone (LEZ) restricts high-emission • Reduce the number of vehicles on the road. vehicles to reduce air pollution, improve air quality, • Protect the physical structures and historical Central Asian cities should prioritize jobs, and foster entrepreneurship. Prioritizing mixed-use and promote public transportation and low-emission character of Kota Tua. mixed-use development to improve job development and compact growth strategies increases transport. Jakarta’s LEZ, implemented in Kota Tua • Improve air quality. access, shorten commutes, and reduce proximity to job centers and reduces vehicle-kilometers on February 8, 2021, covers 14 hectares with six • Create a more pleasant and healthy carbon emissions. Currently, these cities have traveled. Policy interventions include zoning reforms to closed road sections. Only pedestrians, cyclists, environment for residents and visitors. monofunctional urban areas with few residents near job incentivize mixed-use developments and programs to public transportation, residents, and vehicles with • Encourage people to use public transportation centers. Integrating residential areas with workplaces, support entrepreneurship and start-ups. low-emission stickers are allowed. The LEZ aims to and walk more, which will help reduce traffic shops, and amenities can attract businesses, create limit traffic and protect the cultural heritage of the and air pollution. old town, as part of the Kota Tua Old City master The specific actions suggested for achieving the key objective of access to plan. It includes the following strategies: jobs are: Photo 5.5 Jakarta Old Town, Kota Tua 16 Accessible Jobs 17 Land Use Planning SA37. Incentivize mixed-use SA38. Encourage new residential densification in urban areas by developments to allocate 25- offering tax breaks, density bonuses, 30 percent of the constructed quick permitting, and public real estate area to nonresidential (and job- assets. These incentives encourage generating) uses. This mix promotes developers to invest in energy-efficient sustainable development by enabling buildings and renovations. This strategy walking to destinations and reducing promotes infill development, reducing service provision costs. According to UN- carbon intensity and climate vulnerability. Habitat (2023), this strategy is effective Code amendments can support new but may need local adjustments. Cities buildings with commercial ground floors should use regulations and economic and residential upper floors, enhancing incentives, like property tax breaks for sustainability. Densely mixed-use mixed-use buildings, to bring jobs and neighborhoods foster interaction, reduce services closer to residents. commuting times, promote diversity, and lower GHG emissions. Source: © Hari W. Agung. Licensed under CC by-SA 2.0 Attribution-Share alike 2.0 Generic. Due to improvements in air quality, safety, and social inclusion, Jakarta plans to expand the LEZ to other areas. The Kota Tua LEZ improved the Air Pollution Standard Index (ISPU) from 58 to 49 points. Authorities aim for full pedestrianization and integrated public transportation access by 2027.50 _______________________________ 50 DKI Jakarta Governor Special Climate Envoy Team. (2021). Jakarta Climate Resilient City. Best Practices Compilation 2021. Jakarta. 120 121 German Emissions Trading Authority. 2017. Measure for Economic Activity?” PLOS ONE 10 References “Emissions Trading in Kazakhstan: Recommen- (10): e0139779. dation for Cap Setting.” German Environment https://doi.org/10.1371/journal.pone.0139779 Agency; Dessau-Roßlau. https://www.dehst.de/SharedDocs/downloads/ Monforti Ferrario, F., M. Crippa, D. Guizzardi, M. EN/publications/country-study-kazakhstan. Muntean, E. Schaaf, E. Lo Vullo, E. Solazzo, J. pdf?__blob=publicationFile&v=2. Olivier, and E. Vignati. 2021. EDGAR v6.0 Green- house Gas Emissions AHURP. The Third Annual Progress Report C40 and ARUP. 2016. Deadline 2020: How Cities Ghofrani, Z., V. Sposito, and R. Faggian. 2016. (http://data.europa.eu/89h/97a67d67-c62e-4826- (2023). Incorporating Quarterly progress for Oct- Will Get the Job Done. New York. Designing Resilient Regions by Applying Blue- b873-9d972c4f670b) [dataset]. Dec 2023 (49169-002 MON: Ulaanbaatar Green https://www.c40.org/wp-content/uploads/2021/07/ Green Infrastructure Concepts. 493–505. Affordable Housing and Resilient Urban Renewal Deadline_2020.pdf. https://doi.org/10.2495/SC160421. Namrata Joshi. 2021. “Waste-to-Energy.” Fact Sector Project (AHURP)). Green Climate Fund. sheet. ICLEI Local Governments for Sustainability https://www.greenclimate.fund/document/ulaan- Dabrowski, M. and U. Batsaikhan. 2017. “Central Haag, I., P.D. Jones, and C. Samimi. 2019. “Cen- e.V.; Bonn. baatar-green-affordable-housing-and-resilient-ur- Asia at 25.” Policy brief, Bruegel, Brussels. tral Asia’s Changing Climate: How Temperature ban-renewal-project-ahurp-0 and Precipitation Have Changed Across Time, OECD (Organisation for Economic Co-operation EBRD (European Bank for Reconstruction and Space, and Altitude.” Climate 7 (10) : 123. and Development). 2019. Sustainable Infrastruc- Akimat of Almaty City. 2022. Green City Action Development). 2019. “Kashkadarya Oblast Was- https://doi.org/10.3390/cli7100123. ture for Low-Carbon Development in Central Asia Plan for the City of Almaty. tewater Modernization Project Feasibility Study.” and the Caucasus: Hotspot Analysis and Needs Nontechnical Summary, EBRD, London. He, C., Z. Liu, S. Gou, Q. Zhang, J. Zhang, and Assessment, Green Finance and Investment. Albarrán Márquez, Alejandro. 2014. “Sisevive-Eco- L. Xu. 2019. “Detecting Global Urban Expan- Paris. https://doi.org/10.1787/d1aa6ae9-en. Casa – Sistema de Evaluación de la Vivienda EBRD (European Bank for Reconstruction and sion over the Last Three Decades Using a Fully Verde.” Presentation for Infonavit, March 6, 2014. Development). 2021. “Namangan Regional Water Convolutional Network.” Environmental Research Republic of Kazakhstan. 2013. Green Economy https://www.gob.mx/cms/uploads/attachment/ And Wastewater Project.” Project Summary Do- Letters 14 (3): 034008. Transition Concept of Kazakhstan. Astana. file/84276/SISEVIVECONUEE.pdf. cument, EBRD, London. https://doi.org/10.1088/1748-9326/aaf936. https://adilet.zan.kz/rus/docs/U1300000577. https://www.ebrd.com/work-with-us/projects/ Angelini, S. 2010. Environmental Issues in Central psd/51032.html Kyrgyz Republic. 2021. Intended Nationally De- Republic of Kazakhstan. 2016. Intended Nationa- Asia. Venice International University. termined Contributions. Kyrgyz Republic. lly Determined Contributions. Elvidge, C. D., M. Zhizhin, T. Ghosh, F.-C. Hsu, Barzin, S., P. Avner, J. Rentschler and N. O’Clery. and J. Taneja. 2021. “Annual Time Series of Glo- Land Design. n.d.. “: Little Sugar Creek Greenway Republic of Tajikistan. 2021. Intended Nationally 2022. Where Are All the Jobs? A Machine Learning bal VIIRS Nighttime Lights Derived from Monthly – Return to Nature Yields Returns in the Commu- Determined Contributions. Approach for High Resolution Urban Employment Averages: 2012 to 2019.” Remote Sensing 13 (5): nity.” LandDesign (blog), n.d. Prediction in Developing Countries. World Bank; 922. https://landdesign.com/project/little-su- Republic of Turkmenistan. 2016. Intended Natio- Washington, DC. https://doi.org/10.3390/rs13050922. gar-creek-greenway/. nally Determined Contributions. Baeumler et al., 2022. Green, Low Carbon and European Commission. Joint Research Centre. Liu, Y., X. Geng, Z. Hao, and J. Zheng. 2020. Republic of Uzbekistan. 2021. Intended Nationally Climate Resilient Prishtina. World Bank; Washing- 2022. GHSL Data Package 2022: Public Release “Changes in Climate Extremes in Central Asia Determined Contributions. ton, DC. GHS P2022. Publications Office. Under 1.5 and 2 °C Global Warming and Their https://data.europa.eu/doi/10.2760/19817. Impacts on Agricultural Productions.” Atmosphere Restrepo et al., 2017. Cities in Eastern Europe DLR/EOC Land Surface Dynamics. 2019. World 11 (10): 1076. and Central Asia: A Story of Urban Growth and Settlement Footprint (WSF) Evolution—Land- Gao, J. and O’Neill, B.C. 2020. Mapping global https://doi.org/10.3390/atmos11101076. Decline. World Bank; Washington, DC sat-5/-7—Global [TIF]. urban land for the 21st century with data-driven https://download.geoservice.dlr.de/WSF_EVO/#de- simulations and Shared Socioeconomic Pa- McCord, G. C., and M. Rodriguez-Heredia. 2022. Salokhiddinov, A., R. Boirov, M. Ismailov, S. tails thways. Nat Commun 11, 2302 (2020). “Nightlights and Subnational Economic Activity: Mamatov, P. Khakimova, and M. Rakhmatullae- https://doi.org/10.1038/s41467-020-15788-7 Estimating Departmental GDP in Paraguay.” va. 2020. “Climate Change Effects on Irrigated Donkor, F. K., and K. Mearns. 2021. “Clean Ener- Remote Sensing 14 (5): 1150. Agriculture: Perspectives from Agricultural Pro- gy Solutions and Sustainable Development.” In Gao, J., and M. Pesaresi. 2021. “Downscaling https://doi.org/10.3390/rs14051150. ducers in Eastern Uzbekistan.” IOP Conference Affordable and Clean Energy by W. Leal Filho, SSP-Consistent Global Spatial Urban Land Series: Earth and Environmental Science 612 (1): A. Marisa Azul, L. Brandli, A. Lange Salvia, and Projections from 1/8-degree to 1-km Resolution Mellander, C., J. Lobo, K. Stolarick, and Z.Mathe- 012058. T. Wall (Eds.), 144–152). Springer International 2000–2100. Scientific Data 8 (1): 281. son. 2015. “Night-Time Light Data: A Good Proxy https://doi.org/10.1088/1755-1315/612/1/012058. Publishing. https://doi.org/10.1038/s41597-021-01052-0. https://doi.org/10.1007/978-3-319-95864-4_123. Scaini, C. 2022. “Central Asia Exposure La- UN DESA (United Nations Department of Econo- World Bank. 2023. Earthquake and Flood Risk yers—Population. Regional Layer of Residential mic and Social Affairs). 2022. World Population Assessment in Central Asia. World Bank Group: Buildings in Central Asia Developed as Part of the Prospects 2022: Summary of Results. UN DESA, Washington, DC. Strengthening Financial Resilience and Accele- New York. https://documents.worldbank.org/en/pu- rating Risk Reduction in Central Asia Program. blication/documents-reports/documentde- World Bank Global Facility for Disaster Reduction UNECE (United Nations Economic Commission tail/099559109182313173/idu05865efa50d- and Recovery; Washington, DC. for Europe. 2007. “Dam Safety in Central Asia: 14c04efd0b20a0ead793a1fcf9. Capacity-Building and Regional Cooperation.” Schiavina, M., A. Moreno-Monroy, L. Maffenini, Water Series No. 5 ECE/MP.WAT/26. Yang, Y. 2019. “Toward safer, cleaner, and more and P. Veneri. 2019. GHS-FUA R2019A - GHS convenient public transport in Central Asian ci- Functional Urban Areas, Derived from GHS-UC- UN-Habitat (United Nations Human Settlements ties.” World Bank blog, July 31, 2019. DB R2019A, (2015), R2019A. [dataset]. Programme). 2023. My Neighbourhood. UN-Habi- https://blogs.worldbank.org/en/transport/toward- http://data.europa.eu/89h/347f0337-f2da-4592- tat; Nairobi. safer-cleaner-and-more-convenient-public-trans- 87b3-e25975ec2c95. https://unhabitat.org/my-neighbourhood. port-central-asian-cities. Schiavina, M., S. Freire, and K. MacManus. 2022. Varbova, A. 2022. Ex-Ante Assessment of the Zhao, P., B. Lü, and G. D. Roo. 2011. “Impact of GHS-POP R2022A - GHS Population Grid Multi- Thematic Area “Greening Cities” Under the Urban the Jobs-Housing Balance on Urban Commuting temporal (1975-2030) [dataset]. European Com- Agenda for the EU. European Commission; Brus- in Beijing in the Transformation Era.”Journal of mission, Joint Research Centre (JRC). sels. Transport Geography 19 (1): 59–69. https://doi.org/10.2905/D6D86A90-4351-4508- https://www.urbanagenda.urban-initiative.eu/sites/ https://doi.org/10.1016/j.jtrangeo.2009.09.008. 99C1-CB074B022C4A. default/files/2022-10/EAA%20Report%20Gree- ning%20Cities.pdf. Suárez-Meaney, T., H.D. Reséndiz López, J. Arriaga Carbajal, and L. Chías Becerril. 2022. “La Vargas Lara, Raquel. 2018. “Primera obra water medición de la dimensión fractal en las ciudades, smart en México: Parque hídrico ‘La Quebrado- una aproximación para conocer su eficiencia en ra’.” IKI Alliance Mexicico, October 4, 2018. movilidad.” In La interdisciplina en el estudio de https://iki-alliance.mx/primera-obra-wa- la forma urbana, 59–75. Universidad Autónoma ter-smart-en-mexico-parque-hidrico-la-quebrado- Metropolitana. Unidad Azcapotzalco. División de ra/. Ciencias y Artes para el Diseño. https://doi.org/10.24275/uama.9205.9210. WHO (World Health Organization). 2017. Urban Green Spaces: A Brief for Action. World Health Sun, C., Z. Wu, Z. Lv, N. Yao, and J. Wei. 2013. Organization: Geneva. “Quantifying Different Types of Urban Growth and the Change Dynamic in Guangzhou Using Mul- World Bank. 2019. Uzbekistan—Irrigation and ti-Temporal Remote Sensing Data.” International Drainage Interventions to Support the Agriculture Journal of Applied Earth Observation and Geoin- Sector. Independent Evaluation Group, Project formation 21: 409–417. Performance Assessment Report.134622. https://doi.org/10.1016/j.jag.2011.12.012. World Bank. 2020. Financing Climate Action in The Times of Central Asia. 2024. “Climate Chan- Central Asia. A Survey of International and Local ge Threatens Kyrgyzstan With Potential Energy Investments. Crisis.” March 11, 2024. https://zoinet.org/wp-content/uploads/2020/10/ https://timesca.com/climate-change-threa- CA-climate-finance-en.pdf tens-kyrgyzstan-with-potential-energy-crisis/. World Bank. 2022. “Strengthening Financial Resi- UN DESA (United Nations Department of Econo- lience and Accelerating Risk Reduction in Central mic and Social Affairs). 2018. World Urbanization Asia Program (Draft Version).” Global Facility for Prospects: The 2018 Revision. UN DESA, New Disaster Reduction and Recovery York. https://www.gfdrr.org/en/program/SFRARR-Cen- tral-Asia. Appendixes Appendix A: Macro-Assessment Report with Methodology and References Appendix B: Five City Reports Appendix C: Institutional Full Gap Analysis Appendix D: Summary Fact Sheet Appendix E: Technical Analysis Report on Proposed Investments for the Five Cities Appendix F: Country-Level Summaries With Relevant Recommendations Reimagining Central Asian Cities for a Resilient and Low-Carbon Future REIMAGINING CENTRAL ASIAN CITIES FOR A RESILIENT AND LOW-CARBON FUTURE Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan 128