Socio-Economic Impacts of Urban Energy Policies on CO₂ Emissions: A Systematic Literature Review

Socio-Economic Impacts of Urban Energy Policies on CO₂ Emissions: A Systematic Literature Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Socio-Economic Impacts of Urban Energy Policies on CO₂ Emissions: A Systematic Literature Review Hari Prasad Ghimire, Warangkana Jutidamrongphan, Saroj Gyawali This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8283710/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In this systematic literature review (SLR), the effects of socio-economic urban energy policies on CO₂ emission levels are discussed. Any energy policy enacted at the city level aimed at mitigating greenhouse gases is considered crucial, as it contributes to emissions reduction and is particularly important for the fastest-growing cities in the developing world. However, these policies are associated with socio-economic impacts that are not easily discernible. The effects of these policies on economic costs and benefits, social equity, public health, and changes in behavior are incorporated and compared in the review. This review synthesizes evidence from 46 peer-reviewed studies published between 2015 and 2024, revealing that most research has concentrated on Asian megacities, while evidence from Africa and Latin America remains limited, indicating a significant geographical imbalance in the literature. However, the evidence base remains geographically imbalanced, with most studies drawn from Asian megacities and very limited representation from Sub-Saharan Africa, Latin America, or Central and Eastern Europe. This imbalance constrains the generalizability of findings and underscores the need for more geographically inclusive research. It is emphasized that although such policies are environmentally beneficial, they initially entail high costs, have implications for social equity, and require changes in behavior. Additionally, harmonization between the environmental dimensions of policy and socio-economic factors is necessary to foster sustainable city development policies. The findings point to the following directions for future research and policy: a) More comprehensive models must be incorporated to examine the variety of socio-economic effects; b) The relative efficiency of different policy mixes across sectors and contexts should be investigated; c) Greater attention should be paid to addressing the role of stakeholder engagement in the construction and implementation of effective and equitable policies. Key information that can be of use to policymakers is offered, ensuring that urban energy policies are developed to maximize benefits that meet the needs of the population while averting conceivable implications. Urban Energy Policies CO₂ Emissions Socio-Economic Impacts Sustainable Urban Development Environmental Policy Figures Figure 1 Figure 2 Figure 3 Figure 4 Highlights • Out of 46 studies on urban energy policies, their socio-economic impacts were analyzed. • Among the urban policies examined are energy efficiency, renewables and plans for transport. • The most important aspects in this area are related to costs, how equitable the change is, public health and influence on human behavior. • Country-specific details are highlighted in the comparison of Global North and South concepts. • Recommends different stakeholders should participate and adapt their actions to improve the energy system in cities. 1. Introduction Climate change, driven largely by energy-related CO₂ emissions, remains one of the most urgent global challenges of the 21st century. Urban areas consume more than two-thirds of the world’s energy and generate most emissions, making cities critical areas for climate mitigation. Consequently, urban energy policies ranging from renewable energy deployment and building efficiency measures to sustainable transport planning and market-based instruments play a decisive role in shaping both environmental and socio-economic outcomes. For instance, studies in Jiangxi and Nanchang, China demonstrate how industrial and urban energy policies shape CO₂ trajectories (Jia et al., 2018 ; Xiuhui & Raza, 2022 ). Similar evidence from Europe and Latin America highlights the diversity of socio-economic outcomes. While numerous studies evaluate the technical and environmental effectiveness of such policies, the socio-economic consequences including distributional equity, affordability, health outcomes, and behavioral change—have received comparatively less systematic attention. These dimensions are particularly important for ensuring that urban transitions are not only environmentally sustainable but also socially inclusive and economically viable. To address this gap, this study applies to SLR of 46 peer-reviewed articles published between 2015 and 2024. The review synthesizes findings across diverse urban contexts, comparing experiences in the Global North and South as well as megacities and secondary cities. This review seeks to better understand the relationship between policy design and governance contexts to the effectiveness and equity of urban energy transitions by concentrating on socio-economic trade-offs and co-benefits. Three goals guide the review, (1) to categorize urban energy policies to lessen CO₂ emissions, (2) to determine their socio-economic effects in economic, social, health and behavioral aspects, and (3) to determine how the effects vary across regions to impact policy efficacy. The following section briefly outlines the key urban energy policies and how they contribute towards mitigating against CO₂ emissions. 1.1 Overview of Urban Energy Policies and CO₂ Emissions Urban energy policies are a heterogeneous collection of tools expected to mitigate CO₂ emissions in cities through the reconfiguration energy production, consumption, and mobility patterns. It is possible to identify four broad categories of these policies: energy efficiency policies, renewable energy policies, urban transport and planning policies, and market-based regulatory policies. These two are related to the environmental and socio-economic outcomes and the international level case study proves that they are efficient and trade-offs. The goals of energy efficiency policies are to reduce energy demand through technological and behavioral improvements. Retrofitting the current stock of buildings, appliance efficiency, and smart grid infrastructure are the most common answers (Longo et al., 2018 ; Fields et al., 2023 ). In a high-scale residential retrofit in Istanbul two positive effects were observed: household energy expenditure was reduced and indoor air quality was enhanced at the expense of high start-up expenses that were not affordable to low-income population (Batur et al., 2019 ). The same cost-optimisation models are implemented in Switzerland to maximize the performance of urban buildings and minimise long-term emissions and balance the trade-offs between the economy (Yazdanie et al., 2017 ). Renewable energy policies encourage the use of low-carbon sources of energy including solar, wind and biomass in urban systems. In this instance, the normative schemes are feed-in tariffs or capital subsidies or community-based microgrids (Prasad et al., 2021 ). Renewable adoption policies in Brazil produced regional sources of income and opportunities to reduce poverty but were not expanded due to the lack of funds (Chiquetto et al., 2022 ). Similarly, African solar micro grids have not solely delivered clean energy to inadequately electrified locations and workplaces but also brought about co-benefits in energy equity and employment (Fields et al., 2023 ). However, the distribution of subsidies may only amplify the inequalities between rich and poor populations unless allocated in a reasonable way (Castro-Verdezoto et al., 2024 ). Urban planning policies and transport policies respond to the large proportion of emissions due to mobility by supporting sustainable transportation modes and compact urban forms. They may be congestion charges, bus rapid transit (BRT), bicycle riding, land-use planning (Horak et al., 2022 ; Liu et al., 2022 ). Not only the London Congestion Charging Scheme was not creating the CO₂ emissions caused by the traffic jams: the scheme was literally earning the municipal monies as well, though the scheme is aligned with the equity issues (e.g. the scheme will more strongly discriminate against the poorer commuters than against the wealthier ones), also in the scheme (Horak et al., 2022 ). An example of how a low cost and high efficiency public transit system can provide effects on both an emission reduction and a mobility equity and social inclusion benefit was the TransMilenio BRT system in Bogotá, Colombia (Pan et al., 2020 ). The fact that the planning that involves the bicycle infrastructure must be also regarded as a part of the intention to intensify the process of development of the transport infrastructure should also be seen as indicative of the fact that the health co-benefits could also be applied to the improvement of the efficiency of the policy in question (Pan et al., 2020 ). The aim of the market-based and regulatory instruments is to internalize the external costs of carbon and encourage change in behavior. These are the trading program and the carbon tax, use vehicle ticket (Hassan and Lee, 2015 ; Wang et al., 2022 ). In China, the success of the fee-charging models to minimize the CO₂ emission in city transportation depended on the ability of the institutions to enact them (Wang et al., 2022 ). Similarly, another illustration within the context of carbon pricing, the case of the European Union, which is a subset of the broader policy platform of the EU Green Deal, demonstrates the mobilization of regulatory tools that can help in integrating the activity of the city level with the commitments of the international climate process and the establishment of funds that can be reinvested in programs of social equity (Elkhatat and Al-Muhtaseb, 2024 ). 1.2 Importance of Understanding Socio-Economic Impacts The socio-economic factors of the urban energy policies on the CO₂ emissions are addressed because it is necessary due to some reasons (Batur et al., 2019 ; Chen et al., 2022 ; Gouldson et al., 2018 ). These implications will help policymakers recognize possible obstacles to actual implementation of such policies like financial restrictions, social opposition, and ignorance (Batur et al., 2019 ; Huang et al., 2023 ; Liu et al., 2019 ). One of them is high-cost and low-income earner or marginalized policies which cannot be integrated conveniently since such policies are very difficult to follow (Horak et al., 2022 ; Kilian et al., 2022 ; Natividade-Jesus et al., 2019 ). The identification of these issues leads to the development of a more effective policy to achieve social, economic, and environmental targets and objectives (Chi et al., 2023 ; Longo et al., 2018 ; Riadh, 2022 ). An assessment of socio-economic implications of policies regarding urban energy can help identify the benefits that were not necessarily evident at the outset, like enhanced efficiency, social health, employment, social inclusion, and environmental issues (Chen et al., 2022 ; Liu et al., 2022 ; Mahoney et al., 2022 ). Probably, these benefits can also increase the degree of acceptance and adoption of policies by the population (Chen et al., 2022 ; He et al., 2023 ; Pan et al., 2020 ). The evaluation of such effects is fundamental to how the policies of urban energy will look in the future (Elkhatat and Al-Muhtaseb, 2024 ; Prata et al., 2015 ; Xiuhui and Raza, 2022 ). Unless socio-economic factors are properly addressed, the policies can lead to adverse effects with regards to socio-economic factors and, in fact, become self-defeating in their intent and aim (Hassan and Lee, 2015 ; Truong et al., 2022 ; Wan and Li, 2023 ). On the other hand, more sustainable and resilient cities are more likely when policies are designed with a focus on socio-economic impacts (Horak et al., 2022 ; Scorza and Santopietro, 2024 ; Yigitcanlar and Kamruzzaman, 2018 ). Thus, the existing and possible socio-economic impacts of urban energy policies should be articulated to help formulate and implement policies in the future (Fulton et al., 2017 ; Palermo et al., 2020 ; Yazdanie et al., 2017 ). The socio-economic relationship has a wide range of related co-benefits and trade-offs, so it is crucial to perform a systematic study of the impacts of urban energy policies on CO₂ emissions (Chen et al., 2022 ; Elkhatat and Al-Muhtaseb, 2024 ; Szymczyk et al., 2021 ). This type of analysis is essential to the creation of effective and reasonable policies that embody the intended sustainable energy policy actions (Horak et al., 2022 ; Liu et al., 2019 ; Yang and Zheng, 2023 ). In the systematic literature review, a range of research questions defined relates to urban energy policies and its socio-economic effects on CO₂ emissions (Gouldson et al., 2018 ; Sousa and Costa, 2022 ; Zhao et al., 2023). This review aims to examine the socio-economic effects of urban energy policy on CO₂ emissions based on various major objectives. The initial stage of the SLR is to analyze the energy policy of the cities, its development, application, and performance under different conditions (Hassan and Lee, 2015 ; Pan et al., 2020 ). During the second stage, the study examines the direct impacts of these urban energy policies on CO₂ emissions and how the policy influences the reduction of greenhouse gas emissions in cities (Batur et al., 2019 ; Jia et al., 2018 ; Liu et al., 2019 ). The third stage examines the socio-economic factors of these policies and measures their effects on economic cost, social equity, and population health and behavior (Brilhante and Klaas, 2018 ; Gouldson et al., 2018 ). And finally, the changing socio-economic impact on the environment and, in this instance, on CO₂ emissions are reviewed, and here the dimension of the interaction of socio-economic determinants and environmental performances is observed (Horak et al., 2022 ; Huang et al., 2023 ). Overall, the SLR is to find out how the eco-friendly urban energy policy can focus on the socio-economic development and environmental sustainability to shape policy priorities in the future (Elkhatat and Al-Muhtaseb, 2024 ; Mahoney et al., 2022 ). The review is one of the earliest studies to map out systematically the socio-economic aspects of urban energy policies on the regional level and thus provides answers that other reviews have failed to capture. 2. Methodology This systematic literature review aims to review and evaluate the socio-economic impacts of urban energy policies on CO₂ emissions. Following the guidelines on the methodology used in this type of research, the current review is based on the PRISMA checklist that includes guidelines to conduct systematic reviews when reporting primary research studies to reduce the risk of bias, maximize reliability, and improve the exhaustiveness of the review. It consists of a literature search procedure, as well as the definition of inclusion and exclusion criteria and data retrieval, and study analysis. Figure 1: PRISMA 2020 flow diagram of the study selection process. As shown in Fig. 1, while 260 records were initially retrieved, only 46 met the inclusion criteria. This sharp reduction highlights the limited research attention specifically devoted to the socio-economic impacts of urban energy policies compared to the larger body of technical or environmental studies. 2.1 Search Strategy Table 1 presents the databases and keyword combinations used, ensuring transparency and reproducibility. Table 1 Keywords and Search Terms Used in Database Searches Database Search items Number of articles Scopus urban AND energy AND policies AND CO₂ AND emissions AND socio-economic AND impacts AND climate AND change AND mitigation AND energy AND efficiency AND renewable AND energy AND urban AND planning AND sustainable AND cities AND PUBYEAR > 2015 AND PUBYEAR < 2024 AND ( LIMIT-TO ( DOCTYPE, "ar" ) ) AND ( LIMIT-TO ( LANGUAGE, "English" ) ) 128 Google Scholars "Urban Energy Policies" AND "CO₂ Emissions" AND "Socio-Economic Impacts" ("Urban Energy Policies" OR "City Energy Strategies") AND ("CO₂ Emissions" OR "Carbon Emissions" OR "Greenhouse Gas Emissions") AND ("Socio-Economic Impacts" OR "Economic Impacts" OR "Social Impacts") ("Climate Change Mitigation" AND "Urban Energy Policies") AND ("Socio-Economic Impacts" OR "Social Equity" OR "Public Health") ("Energy Efficiency" OR "Renewable Energy") AND ("Urban Areas" OR "Cities") AND ("Socio-Economic Impacts" AND "CO₂ Emissions") 102 Science Direct "Urban Energy Policies" AND "CO₂ Emissions" AND "Socio-Economic Impacts" "Urban Energy Policies" OR "CO₂ Emissions" AND "Socio-Economic Impacts" "Energy Efficiency" AND "Renewable Energy" AND "Socio-Economic Impacts" AND "Urban Areas" 30 Table 1 outlines the search strategy across Scopus, Google Scholar, and ScienceDirect. Approximately half of the retrieved studies originated from Scopus, reflecting reliance on a leading citation database. However, integrating Google Scholar and ScienceDirect broadened the scope to include interdisciplinary and applied studies, reducing the risk of database bias and strengthening comprehensiveness. Figure 2: Selected Number of Publication per year. Figure 2 shows a sharp increase in publications after 2018, peaking between 2020 and 2022, which coincides with the adoption of the Paris Agreement and the SDGs. This trend underscores the timeliness of conducting this review, as socio-economic dimensions have only recently begun to receive systematic attention. Figure 3 highlights geographical imbalance, with most studies from Asia and few from Africa/Latin America. This bias limits generalizability and shows the need for broader studies. Such geographical concentration not only represents a methodological limitation but also influences the transferability of findings to other regions. For instance, policies tested in Asian megacities may not translate well to smaller cities in Africa or Latin America. This limitation reinforces the need for more geographically inclusive studies, as highlighted in Section 3.4 . 2.2 Inclusion and Exclusion Criteria To ensure that the articles selected for this review were relevant, high-quality, and aligned with the research objectives, the following inclusion and exclusion criteria were applied: Inclusion Criteria : Articles published between 2015 and 2024. Peer-reviewed journal articles in English. Studies focusing on urban energy policies aimed at reducing CO₂ emissions. Articles discussing the socio-economic impacts of these policies, including economic, social equity, public health, and behavioral aspects. Studies relevant to climate change mitigation and sustainable urban development. Exclusion Criteria : Excluded any articles which are not in English or which have been published after 2014 or before 2025. Articles that are not published in peer reviewed journals including op-ed articles, editorial commentaries, and conference proceedings. Papers that avoid examination of socio-economic effects and confine themselves to description of the technical specifications of energy policies. Research articles which were poorly supported by data or are irrelevant to socio-economic effects of urban energy policies. All studies were screened independently by two reviewers to minimize bias, and disagreements were resolved by consensus. To ensure methodological rigor, the Critical Appraisal Skills Programme (CASP) and Joanna Briggs Institute (JBI) checklists were applied to assess study quality, clarity of objectives, methodological soundness, and relevance to the review question. 2.3 Data Extraction and Analysis Data extraction was conducted using a structured template that captured key study characteristics, including title, authors, year of publication, study objectives, methodological approach, and principal findings. In addition to thematic coding, each study was assessed for strength of evidence using a three-tier scale (high, medium, low), based on methodological rigor, data robustness, and sample size. This ensured that the synthesis reflects both the quality and depth of available evidence. Beyond bibliographic information, special attention was given to identifying the socio-economic consequences reported in each study. To ensure analytical consistency, extracted information was systematically coded into four thematic categories of socio-economic impacts: (1) economic costs and benefits, such as infrastructure investment, energy savings, and employment effects; (2) equity and social inclusion, including issues of affordability, energy poverty, and distributive justice; (3) public health outcomes, such as air quality improvements, indoor comfort, and active mobility co-benefits; and (4) behavioral and lifestyle change, including shifts in transport habits, energy consumption practices, and cultural acceptance of low-carbon policies. This thematic coding allowed for cross-comparison of diverse studies and facilitated the identification of patterns and trade-offs across different policy contexts. The analysis combined qualitative synthesis of themes with quantitative mapping of study distribution. For instance, while frequencies of policy types and regions were recorded to illustrate overall trends, greater emphasis was placed on the substantive content of findings and their socio-economic implications. This mixed approach enabled the review to move beyond describing methodological metrics and instead highlight the interplay between urban energy policies, their socio-economic impacts, and resulting implications for policy effectiveness. By adopting this coding and synthesis strategy, the review ensures that the discussion is grounded in both the breadth of evidence (across 46 studies) and the depth of insights into how different policy instruments affect economic, social, health, and behavioral outcomes. 3. Result and Discussion 3.1 Types of Urban Energy Policies Aimed at Reducing CO₂ Emissions Urban energy policies can be broadly categorized into three types: such policies as energy efficiency policies, renewable energy policies and urban planning and transportation policies. Energy Efficiency Policies are intended health promotion and energy saving technologies, building renovation, efficient appliances in urban environments (Szymczyk, Şahin, Bağcı, & Kaygın, 2021 ). Renewable Energy Policies are mostly concerned with the promotion of the usage of renewable energy systems including; solar, wind and bio mass within the built environment in urban areas (Olabi et al., 2023 ). Finally, Urban Planning and Transportation Policies are aimed at making enough efforts on the sustainable urban planning, public transportation, and non-motorized transport in order to decrease the energy demand and corresponding emission (Truong, Trencher, & Matsubae, 2022 ). They are commonly executed via policy frameworks that involve legal concepts, monetary rewards and penalties, and information policy initiatives in order to realize those CO₂ emission goals on a population level. Table 2 Study by analyzed regions, models and techniques used by authors and year (n = 46) Reference (Author, Year) Analyzed Region Models/Technique used (Szymczyk, Şahin, Bağcı, & Kaygın, 2021 ) Multi-Country or Global Economic Growth and CO₂ Emission Management Model (Tang, K., & Yang, G. ,2023) China Digital Infrastructure Impact Model (Truong, N., Trencher, G., & Matsubae, K. ,2022) Thailand Socio-Technical Lock-In Model (Ucal, M., & Xydis, G. ,2020) Greece Techno economic Analysis Model (UNDP, 2016) Multi-Country or Global Quantification Analysis Model (Castro-Verdezoto et al., 2024 ) Ecuador Socio-Economic Implication Analysis Model (Wan, F., & Li, J. ,2023) China Responsibility Allocation Model (Wang, H., Shi, W., Xue, H., He, W., & Liu, Y. ,2022) China Fee-Charging Policy Evaluation Model (Wu, J., Feng, Z., & Tang, K. ,2021) China Decomposition Analysis (Wu, J., Zuidema, C., & de Roo, G. ,2022) China Climate Policy Integration Model (Xie, Y., & Zhang, M. ,2023) China Spatial Spillover Effects Model (Xiuhui, J., & Raza, M. Y. ,2022) Pakistan Carbon Mitigation Model (Yang, F., et al. ,2023) China Dynamic Benchmark System Model (Yang, J., & Zheng, X. ,2023) China Spatiotemporal Distribution Model (Yazdanie, M., et al. ,2017) Switzerland Cost Optimization Model (Ye, C., & Ming, T. ,2023) China Carbon Emissions Control Strategy Model (Yigitcanlar, T., & Kamruzzaman, M. ,2018) Multi-Country or Global Smart City Policy Analysis Model (Hassan, A. M. & Lee, H. ,2015) Multi-Country or Global Land Use Policy (Horak, D. et al. ,2022) Multi-Country or Global Spatio-temporal urban energy system modeling (Huang, X. et al. ,2023) Multi-Country or Global Socioeconomic analysis (Hunter, G. W. et al. ,2018) Italy Case study (Jia, J. et al. ,2018) China Driver analysis (Natividade-Jesus et al., 2019 ) Portugal Integrated methodology (Palermo et al., 2020 ) Multi-Country or Global Climate change mitigation assessment (Pan et al., 2020 ) Sweden Urban development policy interaction model (Papa et al., 2016 ) Multi-Country or Global Spatial planning model (Batur, Bayram, & Koc, 2019 ) Istanbul Impact assessment model (Brilhante, O., & Klaas, J. ,2018) Multi-Country or Global Green city performance measurement (Chen et al., 2022 ) China Impact assessment of energy transition policy (Chiquetto et al., 2022 ) Brazil Saptial Analysis Model (Liu, J. et al. ,2022) Multi-Country or Global Transport and Renewable Energy Model (Liu, X. et al. ,2019) Multi-Country or Global Scenario Simulation (Mahoney, K. et al. ,2022) Multi-Country or Global CompeSA Framework (Gouldson, A., Sudmant, A., Khreis, H., & Papargyropoulou, E. ,2018) Multi-Country or Global Systematic Review (Hashemizadeh, A., Bui, Q., & Zaidi, S. A. H. ,2022) Multi-Country or Global Energy Consumption Models (Scorza, F., et al. ,2024) Multi-Country or Global Sustainable Energy and Climate Action Plan (SECAP) (Sousa, C., et al. ,2022) Multi-Country or Global Joint Diffusion of EVs with Renewables (Elkhatat & Al-Muhtaseb, 2024 ) Multi-Country or Global Comparative Policy Analysis (Fields et al., 2023 ) Kenya Evidence-Based Policymaking (Fulton et al., 2017 ) Multi-Country or Global Mitigation Pathways (Prasad, S. et al., 2021 ) Multi-Country or Global Energy Policy Models (Prata, J. et al., 2015 ) Multi-Country or Global Urban Planning Models (Riadh, A.-D., 2022 ) United Arab Emirates Smart City Models (Kilian et al., 2022 ) Switzerland Spatial analysis (Akbari, F., Mahpour, A., & Ahadi, M. R. ,2020) Iran System dynamics approach (Mott MacDonald ,2022) Multi-Country or Global Energy Sector Review and Recommendations Note : “UNDP (2016)” corresponds to the United Nations Development Programme’s Human Development Report 2016: Human development for everyone , which provided the quantification framework referenced in this table. Table 2 shows most studies use quantitative models, with fewer qualitative methods. This bias underrepresents equity and health impacts. Most studies rely on quantitative modeling approaches such as econometric analysis and scenario modeling, while only a smaller share use qualitative case studies. This indicates that the evidence base is dominated by technical assessments, with relatively fewer contributions analyzing socio-economic trade-offs in depth. The dominance of quantitative modeling highlights the technical orientation of current research. While such methods capture emissions reduction potential, they often underrepresent equity, health, and behavioral outcomes. This methodological bias explains why socio-economic trade-offs remain comparatively underexplored. This imbalance directly connects to the second objective of this review, which is to assess socio-economic impacts. Because most existing studies rely on technical models, non-technical impacts such as equity and behavior remain underexplored, leaving a critical gap in the evidence base that this SLR addresses. This framework illustrates the interaction between four categories of urban energy policies (efficiency, renewables, transport, and market instruments) and their socio-economic impacts, which include economic costs/benefits, social equity, public health, and behavioral change. These impacts collectively shape the overall effectiveness of policy interventions, emphasizing that socio-economic dimensions are central to achieving sustainable and equitable urban decarbonization. 3.2 Socio-Economic Impacts of Urban Energy Policies Urban energy policies influence societies in diverse ways that extend beyond emission reductions. The reviewed studies highlight four major dimensions of socio-economic impacts: economic costs and benefits, equity considerations, public health effects, and behavioral change. Economic impacts arise from both the costs of policy implementation and the potential for long-term benefits. For example, in Brazil, renewable adoption policies created local employment opportunities and demonstrated potential for poverty alleviation, but their long-term effectiveness was constrained by financing challenges (Chiquetto et al., 2022 ). In China, fee-charging and responsibility allocation models achieved measurable reductions in CO₂ emissions, but their success depended heavily on strong institutional enforcement, which may not be replicable in weaker governance systems (Wang et al., 2022 ). Social equity impacts are among the most contested outcomes. London’s congestion pricing scheme successfully reduced emissions and traffic congestion but disproportionately burdened low-income commuters who lacked affordable alternatives (Horak et al., 2022 ). In India, rooftop solar subsidy programs supported middle-income households but largely excluded marginalized groups, raising questions about distributive justice and policy inclusivity (Castro-Verdezoto et al., 2024 ). Health effects relate closely to the quality of air and urban conditions. In Stockholm, expanding cycling infrastructure and mass transit not only reduced transport-related CO₂ emissions but also delivered significant public health benefits through improved air quality and active mobility (Pan et al., 2020 ). Similarly, residential interior energy-efficiency retrofits added comfort to indoor environments and reduced the respiratory health risks associated with the low indoor air quality in Istanbul (Batur et al., 2019 ). Behavioral effects are associated with changes in consumption, movement and lifestyle patterns. It might also include congestion pricing in London that assisted commuters to shift to alternative transport options and integrated mobility planning in Stockholm that assisted cultural shifts to sustainable transport patterns in the long term (Horak et al., 2022 ; Pan et al., 2020 ). These illustrations show that behavioral acceptance can be critical in determining the sustainability of policy results. Collectively, these instances demonstrate that socio-economic effects are determinants of the acceptance, effectiveness and long-term viability of urban energy policies. Unless these policies are approached with costs, distributional effects, and behavioral responses in mind, they are less likely to succeed, and those that do use both equity and health as co-benefits have a higher possibility of success (Gouldson et al., 2018 ; Horak et al., 2022 ). The socio-economic impacts of urban energy policies are diverse and can be classified into several key areas: Table 3 Key Socio-Economic Impact Areas of Urban Energy Policies Key Areas Description Economic Costs and Benefits High capital costs for infrastructure and technology, initial high costs for consumers and municipalities, but long-term economic gains through reduced energy costs, employment generation, and energy diversification. Social Equity and Inclusion Low-income groups face affordability issues with energy-efficient investments, potential deepening of energy poverty, and risk of social imbalance through displacement or gentrification. Public Health Impacts Reduction of CO₂ emissions leads to improved public health; active transportation like cycling and walking enhances cardiovascular health. However, urban intensification may increase local pollution exposure. Behavioral and Lifestyle Changes Policies aim to influence public behavior towards sustainable energy consumption and transportation, though societal practices and cultural habits may resist these changes. Table 3 summarizes economic, equity, health, and behavioral effects. It is dominated by economic and equity issues and underexplored by health and behavior. Of the studies reviewed, more than 40 per cent focused on economic or equity aspects, less than 20 per cent focused on health outcomes, and less than 10 per cent focused on behavioural change. This difference casts into sharp relief lapses of evidence. 3.3 Influence of Socio-Economic Impacts on Policy Effectiveness Socio-economic impacts of urban energy policies are strong mediators of their effectiveness. Policies with apparent economic, equity, and health co-benefits tend to have social approval and are more likely to be long-term sustained, whereas those with disproportional burdens are often met with opposition (Gouldson et al., 2018 ; Horak et al., 2022 ). These dynamics are described in case evidence. The most widespread policies in Brazil as have already influenced the poverty situation and directly affected the provision of work in the region, and they were right in the long term (Chiquetto et al., 2022 ). Rather, the London congestion pricing was already tested over time on traffic and emission reduction and was and had been habitually criticized, not only through the prism of equality and equity but also of proportionality (Horak et al., 2022 ). In Stockholm, the incorporation of health and equity aspects in transport planning, e.g., via cycling networks and development of public transport, enhanced effectiveness and social acceptance by providing several co-benefits (Pan et al., 2020 ). Similarly, Istanbul residential retrofits concerning energy efficiency is enhanced to indoor air quality and a reduced emission, but cost more because they had to be restricted solely to subsidies (Batur et al., 2019 ). In addition to individual policy outcomes, comparative evidence demonstrates that effectiveness is highly mediated by governance capacity as well as regional context. In cities with high income like Stockholm, good institutional structures allowed policies to deal with equity and health thus being more accepted by the people. By contrast, weaker governance and resource endowed cities like Delhi and Istanbul were challenged by having to maintain a balanced result even after emission cuts were realised. The experience of the BRT system in Bogotá, Latin America, proved that the level of emissions, as well as social equity of a certain locality, could be improved jointly and that in Brazil, the projects with renewable energy were funded primarily because they could alleviate poverty (Chiquetto et al., 2022 ). The above-mentioned cross-regional differences justify the conclusion that the success of any policy is determined more by the quality of governance and socio-economic environment (Gouldson et al., 2018 ; Elkhatat and Al-Muhtaseb, 2024 ). To further synthesize the findings, Table 4 summarizes the key socio-economic impacts associated with different categories of urban energy policies. This matrix highlights the trade-offs and co-benefits across economic, equity, health, and behavioral dimensions. Table 4 Socio-Economic Impacts of Urban Energy Policy Types (Synthesis of 46 Studies) Policy Type Economic Costs/Benefits Social Equity Impacts Public Health Effects Behavioral/Lifestyle Shifts Energy Efficiency (e.g., building retrofits, efficient appliances) High upfront costs; long-term savings on energy bills; job creation in retrofitting industries Risk of energy poverty if low-income groups cannot afford upgrades Reduced indoor air pollution; improved comfort Encourages energy-saving practices in households Renewable Energy (e.g., solar, wind, biomass) Large capital investment; energy diversification; new employment opportunities May widen inequality if subsidies favor wealthier households; equity gains if community-based schemes adopted Reduced emissions → better air quality Promotes adoption of distributed energy and prosumer culture Transport & Urban Planning (e.g., public transit, cycling, congestion pricing) Infrastructure costs; reduced congestion → long-term productivity gains Risk of gentrification/displacement (congestion pricing); equity gains from affordable public transport Active transport improves cardiovascular health; reduced exposure to car emissions Encourages modal shift toward sustainable mobility Market-based & Regulatory Instruments (e.g., fee-charging, carbon pricing, land use regulation) Generates municipal revenue; incentivizes innovation Risk of regressive effects unless revenues recycled to vulnerable groups Reduced fossil fuel use improves urban air quality Alters consumption patterns toward cleaner energy/services Table 4 compares socio-economic impacts by policy type. Efficiency raises affordability issues, renewables risk inequality, transport policies improve health but risk gentrification. 3.4 Limitations While this review synthesizes 46 peer-reviewed studies on the socio-economic impacts of urban energy policies, several limitations should be acknowledged: Geographical bias: Most studies originate from East and Southeast Asia, with limited representation from Sub-Saharan Africa, Latin America, and Central/Eastern Europe. This uneven distribution constrains the global generalizability of the findings. Variation in methodological quality: Although systematic screening and critical appraisal tools (CASP and JBI) were applied, differences in study design and methodological rigor across the included literature limit comparability of results. Publication and language bias: The review emphasizes published, English-language journal articles, which may exclude relevant policy reports or studies in other languages. Simplification of complex trade-offs: The synthesis highlights broad trends but cannot capture the full complexity of socio-economic trade-offs at the local level. These limitations underscore the need for more geographically diverse and methodologically consistent research to strengthen evidence for policy formulation. 4. Conclusion and Policy implications The literature review was conducted in a systematic manner to synthesize existing evidence on the socio-economic effects of urban energy policies implemented between 2015 and 2024. The analyses show that although policies promoting energy efficiency, renewable energy, sustainable transport, and market-based solutions have made a significant contribution to reducing CO₂ emissions. These include short-term economic costs, distributional injustices, and disproportionate burdens on vulnerable groups. At the same time, many policies generated important co-benefits, such as improved public health from cleaner air, the creation of green jobs, and shifts toward more sustainable consumer behavior. Aligning these socio-economic dimensions with environmental objectives is therefore essential to ensure long-term effectiveness and public legitimacy. This review highlights that the impacts of urban energy policies vary across regions and socio-economic contexts. In developed countries such as those in Europe, initiatives like the London congestion charge and stringent building efficiency codes have successfully combined emission reductions with revenue generation for sustainable mobility. In China, large-scale low-carbon city pilot programs demonstrate how integrated policy frameworks can drive industrial restructuring, though social equity challenges remain. In Latin America, participatory renewable energy initiatives and urban transit systems, such as Bogotá’s Bus Rapid Transit (BRT), have improved both environmental outcomes and social inclusion. In Sub-Saharan Africa, community-based solar microgrids stand out as niche solutions that enhance energy access while supporting local employment and reducing carbon dependency. These diverse experiences underline that there is no “one-size-fits-all” pathway: policies must be designed and adapted according to regional realities. Developing cities face financial and institutional constraints but also possess opportunities for leapfrogging directly to cleaner, decentralized energy systems. Developed cities, by contrast, can leverage existing infrastructure and governance capacity to implement large-scale efficiency and integration measures. Future research should therefore expand coverage of underrepresented regions such as Sub-Saharan Africa and Central and Eastern Europe, while incorporating systematic assessments of equity, health, and behavioral impacts into policy evaluations. Such comparative insights will help policymakers craft targeted, evidence-based interventions that maximize climate benefits while ensuring fairness and inclusiveness in the global transition to sustainable urban development. Declarations Author Contribution H.P.G. conceived and designed the study, developed the search strategy and review protocol, conducted database searches, screened studies, extracted and analyzed data, and drafted the main manuscript text. W.J. contributed to the conceptual framing and methodology, advised on the review protocol, supported interpretation of the findings, and critically revised all sections of the manuscript. S.G. assisted with database searches, screening and data extraction, prepared summary tables and figures, and contributed to writing the sections on urban energy policy instruments and socio economic outcomes. All authors reviewed and approved the final version of the manuscript. Acknowledgement The authors thank the Faculty of Environmental Management, Prince of Songkla University, for academic support. We also thank colleagues at Everest Center for Research and Development Partners, Nepal, for constructive comments during the design of the review protocol. We are grateful to friends and research assistants who supported database searches, article screening, and data extraction. The views expressed in this article are those of the authors and do not necessarily reflect the views of their institutions. Data Availability Research data are derived from previously published studies identified through the systematic literature review. 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05:29:53","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161870,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8283710/v1/41eb367751a17b04f378728f.html"},{"id":97672632,"identity":"12431a7c-f2d7-4e0d-b660-9cbdcd7bb4f3","added_by":"auto","created_at":"2025-12-08 09:38:31","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":99997,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePRISMA 2020 flow diagram of the study selection process.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8283710/v1/87ae2c18b1b075d6a2537403.jpg"},{"id":97648474,"identity":"73fc4a9c-0903-41ba-a309-96236d82407b","added_by":"auto","created_at":"2025-12-08 05:29:53","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69568,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSelected Number of Publication per year.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8283710/v1/9d5d1f44685406661b88cc7c.jpg"},{"id":97648478,"identity":"d6d83430-eee1-4999-bcc9-2eac89a20bde","added_by":"auto","created_at":"2025-12-08 05:29:53","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70062,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePublished articles by Country of origin\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8283710/v1/58e0ad35ba4fff09a4ea76ff.jpg"},{"id":97648476,"identity":"3dc5acbb-2e50-4137-a43b-94470c770718","added_by":"auto","created_at":"2025-12-08 05:29:53","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":66577,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFramework linking urban energy policies, socio-economic impacts, and policy effectiveness.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8283710/v1/103740c71a1515316e7b5fb0.jpg"},{"id":97678859,"identity":"531a05be-896b-4799-a020-9cc89e58bded","added_by":"auto","created_at":"2025-12-08 09:56:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1293571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8283710/v1/719b81b3-4613-44b6-b2ad-d125a4e4a55d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Socio-Economic Impacts of Urban Energy Policies on CO₂ Emissions: A Systematic Literature Review","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; Out of 46 studies on urban energy policies, their socio-economic impacts were analyzed.\u003c/p\u003e\u003cp\u003e\u0026bull; Among the urban policies examined are energy efficiency, renewables and plans for transport.\u003c/p\u003e\u003cp\u003e\u0026bull; The most important aspects in this area are related to costs, how equitable the change is, public health and influence on human behavior.\u003c/p\u003e\u003cp\u003e\u0026bull; Country-specific details are highlighted in the comparison of Global North and South concepts.\u003c/p\u003e\u003cp\u003e\u0026bull; Recommends different stakeholders should participate and adapt their actions to improve the energy system in cities.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eClimate change, driven largely by energy-related CO₂ emissions, remains one of the most urgent global challenges of the 21st century. Urban areas consume more than two-thirds of the world\u0026rsquo;s energy and generate most emissions, making cities critical areas for climate mitigation. Consequently, urban energy policies ranging from renewable energy deployment and building efficiency measures to sustainable transport planning and market-based instruments play a decisive role in shaping both environmental and socio-economic outcomes. For instance, studies in Jiangxi and Nanchang, China demonstrate how industrial and urban energy policies shape CO₂ trajectories (Jia et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Xiuhui \u0026amp; Raza, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similar evidence from Europe and Latin America highlights the diversity of socio-economic outcomes.\u003c/p\u003e\u003cp\u003eWhile numerous studies evaluate the technical and environmental effectiveness of such policies, the socio-economic consequences including distributional equity, affordability, health outcomes, and behavioral change\u0026mdash;have received comparatively less systematic attention. These dimensions are particularly important for ensuring that urban transitions are not only environmentally sustainable but also socially inclusive and economically viable.\u003c/p\u003e\u003cp\u003eTo address this gap, this study applies to SLR of 46 peer-reviewed articles published between 2015 and 2024. The review synthesizes findings across diverse urban contexts, comparing experiences in the Global North and South as well as megacities and secondary cities. This review seeks to better understand the relationship between policy design and governance contexts to the effectiveness and equity of urban energy transitions by concentrating on socio-economic trade-offs and co-benefits. Three goals guide the review, (1) to categorize urban energy policies to lessen CO₂ emissions, (2) to determine their socio-economic effects in economic, social, health and behavioral aspects, and (3) to determine how the effects vary across regions to impact policy efficacy. The following section briefly outlines the key urban energy policies and how they contribute towards mitigating against CO₂ emissions.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 \u003cb\u003eOverview of Urban Energy Policies and CO₂ Emissions\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eUrban energy policies are a heterogeneous collection of tools expected to mitigate CO₂ emissions in cities through the reconfiguration energy production, consumption, and mobility patterns. It is possible to identify four broad categories of these policies: energy efficiency policies, renewable energy policies, urban transport and planning policies, and market-based regulatory policies. These two are related to the environmental and socio-economic outcomes and the international level case study proves that they are efficient and trade-offs.\u003c/p\u003e\u003cp\u003eThe goals of energy efficiency policies are to reduce energy demand through technological and behavioral improvements. Retrofitting the current stock of buildings, appliance efficiency, and smart grid infrastructure are the most common answers (Longo et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fields et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In a high-scale residential retrofit in Istanbul two positive effects were observed: household energy expenditure was reduced and indoor air quality was enhanced at the expense of high start-up expenses that were not affordable to low-income population (Batur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The same cost-optimisation models are implemented in Switzerland to maximize the performance of urban buildings and minimise long-term emissions and balance the trade-offs between the economy (Yazdanie et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRenewable energy policies encourage the use of low-carbon sources of energy including solar, wind and biomass in urban systems. In this instance, the normative schemes are feed-in tariffs or capital subsidies or community-based microgrids (Prasad et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Renewable adoption policies in Brazil produced regional sources of income and opportunities to reduce poverty but were not expanded due to the lack of funds (Chiquetto et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, African solar micro grids have not solely delivered clean energy to inadequately electrified locations and workplaces but also brought about co-benefits in energy equity and employment (Fields et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the distribution of subsidies may only amplify the inequalities between rich and poor populations unless allocated in a reasonable way (Castro-Verdezoto et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUrban planning policies and transport policies respond to the large proportion of emissions due to mobility by supporting sustainable transportation modes and compact urban forms. They may be congestion charges, bus rapid transit (BRT), bicycle riding, land-use planning (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Not only the London Congestion Charging Scheme was not creating the CO₂ emissions caused by the traffic jams: the scheme was literally earning the municipal monies as well, though the scheme is aligned with the equity issues (e.g. the scheme will more strongly discriminate against the poorer commuters than against the wealthier ones), also in the scheme (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). An example of how a low cost and high efficiency public transit system can provide effects on both an emission reduction and a mobility equity and social inclusion benefit was the TransMilenio BRT system in Bogot\u0026aacute;, Colombia (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The fact that the planning that involves the bicycle infrastructure must be also regarded as a part of the intention to intensify the process of development of the transport infrastructure should also be seen as indicative of the fact that the health co-benefits could also be applied to the improvement of the efficiency of the policy in question (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe aim of the market-based and regulatory instruments is to internalize the external costs of carbon and encourage change in behavior. These are the trading program and the carbon tax, use vehicle ticket (Hassan and Lee, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In China, the success of the fee-charging models to minimize the CO₂ emission in city transportation depended on the ability of the institutions to enact them (Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, another illustration within the context of carbon pricing, the case of the European Union, which is a subset of the broader policy platform of the EU Green Deal, demonstrates the mobilization of regulatory tools that can help in integrating the activity of the city level with the commitments of the international climate process and the establishment of funds that can be reinvested in programs of social equity (Elkhatat and Al-Muhtaseb, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Importance of Understanding Socio-Economic Impacts\u003c/h2\u003e\u003cp\u003eThe socio-economic factors of the urban energy policies on the CO₂ emissions are addressed because it is necessary due to some reasons (Batur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gouldson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These implications will help policymakers recognize possible obstacles to actual implementation of such policies like financial restrictions, social opposition, and ignorance (Batur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). One of them is high-cost and low-income earner or marginalized policies which cannot be integrated conveniently since such policies are very difficult to follow (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kilian et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Natividade-Jesus et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The identification of these issues leads to the development of a more effective policy to achieve social, economic, and environmental targets and objectives (Chi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Longo et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Riadh, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAn assessment of socio-economic implications of policies regarding urban energy can help identify the benefits that were not necessarily evident at the outset, like enhanced efficiency, social health, employment, social inclusion, and environmental issues (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mahoney et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Probably, these benefits can also increase the degree of acceptance and adoption of policies by the population (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; He et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe evaluation of such effects is fundamental to how the policies of urban energy will look in the future (Elkhatat and Al-Muhtaseb, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Prata et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Xiuhui and Raza, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Unless socio-economic factors are properly addressed, the policies can lead to adverse effects with regards to socio-economic factors and, in fact, become self-defeating in their intent and aim (Hassan and Lee, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Truong et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wan and Li, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). On the other hand, more sustainable and resilient cities are more likely when policies are designed with a focus on socio-economic impacts (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Scorza and Santopietro, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yigitcanlar and Kamruzzaman, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Thus, the existing and possible socio-economic impacts of urban energy policies should be articulated to help formulate and implement policies in the future (Fulton et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Palermo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yazdanie et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe socio-economic relationship has a wide range of related co-benefits and trade-offs, so it is crucial to perform a systematic study of the impacts of urban energy policies on CO₂ emissions (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Elkhatat and Al-Muhtaseb, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Szymczyk et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This type of analysis is essential to the creation of effective and reasonable policies that embody the intended sustainable energy policy actions (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yang and Zheng, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In the systematic literature review, a range of research questions defined relates to urban energy policies and its socio-economic effects on CO₂ emissions (Gouldson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sousa and Costa, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao et al., 2023).\u003c/p\u003e\u003cp\u003eThis review aims to examine the socio-economic effects of urban energy policy on CO₂ emissions based on various major objectives. The initial stage of the SLR is to analyze the energy policy of the cities, its development, application, and performance under different conditions (Hassan and Lee, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). During the second stage, the study examines the direct impacts of these urban energy policies on CO₂ emissions and how the policy influences the reduction of greenhouse gas emissions in cities (Batur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jia et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The third stage examines the socio-economic factors of these policies and measures their effects on economic cost, social equity, and population health and behavior (Brilhante and Klaas, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gouldson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). And finally, the changing socio-economic impact on the environment and, in this instance, on CO₂ emissions are reviewed, and here the dimension of the interaction of socio-economic determinants and environmental performances is observed (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Overall, the SLR is to find out how the eco-friendly urban energy policy can focus on the socio-economic development and environmental sustainability to shape policy priorities in the future (Elkhatat and Al-Muhtaseb, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mahoney et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The review is one of the earliest studies to map out systematically the socio-economic aspects of urban energy policies on the regional level and thus provides answers that other reviews have failed to capture.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Methodology","content":"\u003cp\u003eThis systematic literature review aims to review and evaluate the socio-economic impacts of urban energy policies on CO₂ emissions. Following the guidelines on the methodology used in this type of research, the current review is based on the PRISMA checklist that includes guidelines to conduct systematic reviews when reporting primary research studies to reduce the risk of bias, maximize reliability, and improve the exhaustiveness of the review. It consists of a literature search procedure, as well as the definition of inclusion and exclusion criteria and data retrieval, and study analysis.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 1: PRISMA 2020 flow diagram of the study selection process.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;1, while 260 records were initially retrieved, only 46 met the inclusion criteria. This sharp reduction highlights the limited research attention specifically devoted to the socio-economic impacts of urban energy policies compared to the larger body of technical or environmental studies.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Search Strategy\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the databases and keyword combinations used, ensuring transparency and reproducibility.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKeywords and Search Terms Used in Database Searches\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDatabase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSearch items\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of articles\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScopus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eurban AND energy AND policies AND CO₂ AND emissions AND socio-economic AND impacts AND climate AND change AND mitigation AND energy AND efficiency AND renewable AND energy AND urban AND planning AND sustainable AND cities AND PUBYEAR\u0026thinsp;\u0026gt;\u0026thinsp;2015 AND PUBYEAR\u0026thinsp;\u0026lt;\u0026thinsp;2024 AND ( LIMIT-TO ( DOCTYPE, \"ar\" ) ) AND ( LIMIT-TO ( LANGUAGE, \"English\" ) )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGoogle Scholars\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\"Urban Energy Policies\" AND \"CO₂ Emissions\" AND \"Socio-Economic Impacts\"\u003c/p\u003e\u003cp\u003e(\"Urban Energy Policies\" OR \"City Energy Strategies\") AND (\"CO₂ Emissions\" OR \"Carbon Emissions\" OR \"Greenhouse Gas Emissions\") AND (\"Socio-Economic Impacts\" OR \"Economic Impacts\" OR \"Social Impacts\")\u003c/p\u003e\u003cp\u003e(\"Climate Change Mitigation\" AND \"Urban Energy Policies\") AND (\"Socio-Economic Impacts\" OR \"Social Equity\" OR \"Public Health\")\u003c/p\u003e\u003cp\u003e(\"Energy Efficiency\" OR \"Renewable Energy\") AND (\"Urban Areas\" OR \"Cities\") AND (\"Socio-Economic Impacts\" AND \"CO₂ Emissions\")\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScience Direct\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\"Urban Energy Policies\" AND \"CO₂ Emissions\" AND \"Socio-Economic Impacts\"\u003c/p\u003e\u003cp\u003e\"Urban Energy Policies\" OR \"CO₂ Emissions\" AND \"Socio-Economic Impacts\"\u003c/p\u003e\u003cp\u003e\"Energy Efficiency\" AND \"Renewable Energy\" AND \"Socio-Economic Impacts\" AND \"Urban Areas\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the search strategy across Scopus, Google Scholar, and ScienceDirect. Approximately half of the retrieved studies originated from Scopus, reflecting reliance on a leading citation database. However, integrating Google Scholar and ScienceDirect broadened the scope to include interdisciplinary and applied studies, reducing the risk of database bias and strengthening comprehensiveness.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 2: Selected Number of Publication per year.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFigure 2 shows a sharp increase in publications after 2018, peaking between 2020 and 2022, which coincides with the adoption of the Paris Agreement and the SDGs. This trend underscores the timeliness of conducting this review, as socio-economic dimensions have only recently begun to receive systematic attention.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e highlights geographical imbalance, with most studies from Asia and few from Africa/Latin America. This bias limits generalizability and shows the need for broader studies. Such geographical concentration not only represents a methodological limitation but also influences the transferability of findings to other regions. For instance, policies tested in Asian megacities may not translate well to smaller cities in Africa or Latin America. This limitation reinforces the need for more geographically inclusive studies, as highlighted in Section \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e3.4\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e\u003cp\u003eTo ensure that the articles selected for this review were relevant, high-quality, and aligned with the research objectives, the following inclusion and exclusion criteria were applied:\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion Criteria\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eArticles published between 2015 and 2024.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePeer-reviewed journal articles in English.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStudies focusing on urban energy policies aimed at reducing CO₂ emissions.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eArticles discussing the socio-economic impacts of these policies, including economic, social equity, public health, and behavioral aspects.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStudies relevant to climate change mitigation and sustainable urban development.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExclusion Criteria\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eExcluded any articles which are not in English or which have been published after 2014 or before 2025.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eArticles that are not published in peer reviewed journals including op-ed articles, editorial commentaries, and conference proceedings.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePapers that avoid examination of socio-economic effects and confine themselves to description of the technical specifications of energy policies.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eResearch articles which were poorly supported by data or are irrelevant to socio-economic effects of urban energy policies.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eAll studies were screened independently by two reviewers to minimize bias, and disagreements were resolved by consensus. To ensure methodological rigor, the Critical Appraisal Skills Programme (CASP) and Joanna Briggs Institute (JBI) checklists were applied to assess study quality, clarity of objectives, methodological soundness, and relevance to the review question.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data Extraction and Analysis\u003c/h2\u003e\u003cp\u003eData extraction was conducted using a structured template that captured key study characteristics, including title, authors, year of publication, study objectives, methodological approach, and principal findings. In addition to thematic coding, each study was assessed for strength of evidence using a three-tier scale (high, medium, low), based on methodological rigor, data robustness, and sample size. This ensured that the synthesis reflects both the quality and depth of available evidence. Beyond bibliographic information, special attention was given to identifying the socio-economic consequences reported in each study.\u003c/p\u003e\u003cp\u003eTo ensure analytical consistency, extracted information was systematically coded into four thematic categories of socio-economic impacts: (1) economic costs and benefits, such as infrastructure investment, energy savings, and employment effects; (2) equity and social inclusion, including issues of affordability, energy poverty, and distributive justice; (3) public health outcomes, such as air quality improvements, indoor comfort, and active mobility co-benefits; and (4) behavioral and lifestyle change, including shifts in transport habits, energy consumption practices, and cultural acceptance of low-carbon policies. This thematic coding allowed for cross-comparison of diverse studies and facilitated the identification of patterns and trade-offs across different policy contexts.\u003c/p\u003e\u003cp\u003eThe analysis combined qualitative synthesis of themes with quantitative mapping of study distribution. For instance, while frequencies of policy types and regions were recorded to illustrate overall trends, greater emphasis was placed on the substantive content of findings and their socio-economic implications. This mixed approach enabled the review to move beyond describing methodological metrics and instead highlight the interplay between urban energy policies, their socio-economic impacts, and resulting implications for policy effectiveness.\u003c/p\u003e\u003cp\u003eBy adopting this coding and synthesis strategy, the review ensures that the discussion is grounded in both the breadth of evidence (across 46 studies) and the depth of insights into how different policy instruments affect economic, social, health, and behavioral outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Result and Discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Types of Urban Energy Policies Aimed at Reducing CO₂ Emissions\u003c/h2\u003e\u003cp\u003eUrban energy policies can be broadly categorized into three types: such policies as energy efficiency policies, renewable energy policies and urban planning and transportation policies. Energy Efficiency Policies are intended health promotion and energy saving technologies, building renovation, efficient appliances in urban environments (Szymczyk, Şahin, Bağcı, \u0026amp; Kaygın, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Renewable Energy Policies are mostly concerned with the promotion of the usage of renewable energy systems including; solar, wind and bio mass within the built environment in urban areas (Olabi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Finally, Urban Planning and Transportation Policies are aimed at making enough efforts on the sustainable urban planning, public transportation, and non-motorized transport in order to decrease the energy demand and corresponding emission (Truong, Trencher, \u0026amp; Matsubae, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). They are commonly executed via policy frameworks that involve legal concepts, monetary rewards and penalties, and information policy initiatives in order to realize those CO₂ emission goals on a population level.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStudy by analyzed regions, models and techniques used by authors and year (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReference (Author, Year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnalyzed Region\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModels/Technique used\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Szymczyk, Şahin, Bağcı, \u0026amp; Kaygın, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEconomic Growth and CO₂ Emission Management Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Tang, K., \u0026amp; Yang, G. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDigital Infrastructure Impact Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Truong, N., Trencher, G., \u0026amp; Matsubae, K. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThailand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSocio-Technical Lock-In Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Ucal, M., \u0026amp; Xydis, G. ,2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGreece\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTechno economic Analysis Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(UNDP, 2016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuantification Analysis Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Castro-Verdezoto et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEcuador\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSocio-Economic Implication Analysis Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Wan, F., \u0026amp; Li, J. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResponsibility Allocation Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Wang, H., Shi, W., Xue, H., He, W., \u0026amp; Liu, Y. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFee-Charging Policy Evaluation Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Wu, J., Feng, Z., \u0026amp; Tang, K. ,2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecomposition Analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Wu, J., Zuidema, C., \u0026amp; de Roo, G. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClimate Policy Integration Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Xie, Y., \u0026amp; Zhang, M. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatial Spillover Effects Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Xiuhui, J., \u0026amp; Raza, M. Y. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePakistan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCarbon Mitigation Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Yang, F., et al. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDynamic Benchmark System Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Yang, J., \u0026amp; Zheng, X. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatiotemporal Distribution Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Yazdanie, M., et al. ,2017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSwitzerland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCost Optimization Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Ye, C., \u0026amp; Ming, T. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCarbon Emissions Control Strategy Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Yigitcanlar, T., \u0026amp; Kamruzzaman, M. ,2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSmart City Policy Analysis Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hassan, A. M. \u0026amp; Lee, H. ,2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLand Use Policy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Horak, D. et al. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatio-temporal urban energy system modeling\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Huang, X. et al. ,2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSocioeconomic analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hunter, G. W. et al. ,2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCase study\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Jia, J. et al. ,2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDriver analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Natividade-Jesus et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePortugal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntegrated methodology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Palermo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClimate change mitigation assessment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSweden\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUrban development policy interaction model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Papa et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatial planning model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Batur, Bayram, \u0026amp; Koc, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIstanbul\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eImpact assessment model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Brilhante, O., \u0026amp; Klaas, J. ,2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGreen city performance measurement\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eImpact assessment of energy transition policy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Chiquetto et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrazil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSaptial Analysis Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Liu, J. et al. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTransport and Renewable Energy Model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Liu, X. et al. ,2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eScenario Simulation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Mahoney, K. et al. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompeSA Framework\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Gouldson, A., Sudmant, A., Khreis, H., \u0026amp; Papargyropoulou, E. ,2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSystematic Review\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hashemizadeh, A., Bui, Q., \u0026amp; Zaidi, S. A. H. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnergy Consumption Models\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Scorza, F., et al. ,2024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSustainable Energy and Climate Action Plan (SECAP)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Sousa, C., et al. ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eJoint Diffusion of EVs with Renewables\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Elkhatat \u0026amp; Al-Muhtaseb, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eComparative Policy Analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Fields et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKenya\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEvidence-Based Policymaking\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Fulton et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMitigation Pathways\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Prasad, S. et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnergy Policy Models\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Prata, J. et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUrban Planning Models\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Riadh, A.-D., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnited Arab Emirates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSmart City Models\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Kilian et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSwitzerland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatial analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Akbari, F., Mahpour, A., \u0026amp; Ahadi, M. R. ,2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIran\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSystem dynamics approach\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Mott MacDonald ,2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulti-Country or Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnergy Sector Review and Recommendations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: \u0026ldquo;UNDP (2016)\u0026rdquo; corresponds to the United Nations Development Programme\u0026rsquo;s \u003cem\u003eHuman Development Report 2016: Human development for everyone\u003c/em\u003e, which provided the quantification framework referenced in this table.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows most studies use quantitative models, with fewer qualitative methods. This bias underrepresents equity and health impacts. Most studies rely on quantitative modeling approaches such as econometric analysis and scenario modeling, while only a smaller share use qualitative case studies. This indicates that the evidence base is dominated by technical assessments, with relatively fewer contributions analyzing socio-economic trade-offs in depth. The dominance of quantitative modeling highlights the technical orientation of current research. While such methods capture emissions reduction potential, they often underrepresent equity, health, and behavioral outcomes. This methodological bias explains why socio-economic trade-offs remain comparatively underexplored. This imbalance directly connects to the second objective of this review, which is to assess socio-economic impacts. Because most existing studies rely on technical models, non-technical impacts such as equity and behavior remain underexplored, leaving a critical gap in the evidence base that this SLR addresses.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis framework illustrates the interaction between four categories of urban energy policies (efficiency, renewables, transport, and market instruments) and their socio-economic impacts, which include economic costs/benefits, social equity, public health, and behavioral change. These impacts collectively shape the overall effectiveness of policy interventions, emphasizing that socio-economic dimensions are central to achieving sustainable and equitable urban decarbonization.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Socio-Economic Impacts of Urban Energy Policies\u003c/h2\u003e\u003cp\u003eUrban energy policies influence societies in diverse ways that extend beyond emission reductions. The reviewed studies highlight four major dimensions of socio-economic impacts: economic costs and benefits, equity considerations, public health effects, and behavioral change.\u003c/p\u003e\u003cp\u003eEconomic impacts arise from both the costs of policy implementation and the potential for long-term benefits. For example, in Brazil, renewable adoption policies created local employment opportunities and demonstrated potential for poverty alleviation, but their long-term effectiveness was constrained by financing challenges (Chiquetto et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In China, fee-charging and responsibility allocation models achieved measurable reductions in CO₂ emissions, but their success depended heavily on strong institutional enforcement, which may not be replicable in weaker governance systems (Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSocial equity impacts are among the most contested outcomes. London\u0026rsquo;s congestion pricing scheme successfully reduced emissions and traffic congestion but disproportionately burdened low-income commuters who lacked affordable alternatives (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In India, rooftop solar subsidy programs supported middle-income households but largely excluded marginalized groups, raising questions about distributive justice and policy inclusivity (Castro-Verdezoto et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHealth effects relate closely to the quality of air and urban conditions. In Stockholm, expanding cycling infrastructure and mass transit not only reduced transport-related CO₂ emissions but also delivered significant public health benefits through improved air quality and active mobility (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, residential interior energy-efficiency retrofits added comfort to indoor environments and reduced the respiratory health risks associated with the low indoor air quality in Istanbul (Batur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBehavioral effects are associated with changes in consumption, movement and lifestyle patterns. It might also include congestion pricing in London that assisted commuters to shift to alternative transport options and integrated mobility planning in Stockholm that assisted cultural shifts to sustainable transport patterns in the long term (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These illustrations show that behavioral acceptance can be critical in determining the sustainability of policy results.\u003c/p\u003e\u003cp\u003eCollectively, these instances demonstrate that socio-economic effects are determinants of the acceptance, effectiveness and long-term viability of urban energy policies. Unless these policies are approached with costs, distributional effects, and behavioral responses in mind, they are less likely to succeed, and those that do use both equity and health as co-benefits have a higher possibility of success (Gouldson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe socio-economic impacts of urban energy policies are diverse and can be classified into several key areas:\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey Socio-Economic Impact Areas of Urban Energy Policies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKey Areas\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEconomic Costs and Benefits\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh capital costs for infrastructure and technology, initial high costs for consumers and municipalities, but long-term economic gains through reduced energy costs, employment generation, and energy diversification.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Equity and Inclusion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow-income groups face affordability issues with energy-efficient investments, potential deepening of energy poverty, and risk of social imbalance through displacement or gentrification.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic Health Impacts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReduction of CO₂ emissions leads to improved public health; active transportation like cycling and walking enhances cardiovascular health. However, urban intensification may increase local pollution exposure.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBehavioral and Lifestyle Changes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePolicies aim to influence public behavior towards sustainable energy consumption and transportation, though societal practices and cultural habits may resist these changes.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes economic, equity, health, and behavioral effects. It is dominated by economic and equity issues and underexplored by health and behavior. Of the studies reviewed, more than 40 per cent focused on economic or equity aspects, less than 20 per cent focused on health outcomes, and less than 10 per cent focused on behavioural change. This difference casts into sharp relief lapses of evidence.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Influence of Socio-Economic Impacts on Policy Effectiveness\u003c/h2\u003e\u003cp\u003eSocio-economic impacts of urban energy policies are strong mediators of their effectiveness. Policies with apparent economic, equity, and health co-benefits tend to have social approval and are more likely to be long-term sustained, whereas those with disproportional burdens are often met with opposition (Gouldson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese dynamics are described in case evidence. The most widespread policies in Brazil as have already influenced the poverty situation and directly affected the provision of work in the region, and they were right in the long term (Chiquetto et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Rather, the London congestion pricing was already tested over time on traffic and emission reduction and was and had been habitually criticized, not only through the prism of equality and equity but also of proportionality (Horak et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Stockholm, the incorporation of health and equity aspects in transport planning, e.g., via cycling networks and development of public transport, enhanced effectiveness and social acceptance by providing several co-benefits (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, Istanbul residential retrofits concerning energy efficiency is enhanced to indoor air quality and a reduced emission, but cost more because they had to be restricted solely to subsidies (Batur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition to individual policy outcomes, comparative evidence demonstrates that effectiveness is highly mediated by governance capacity as well as regional context. In cities with high income like Stockholm, good institutional structures allowed policies to deal with equity and health thus being more accepted by the people. By contrast, weaker governance and resource endowed cities like Delhi and Istanbul were challenged by having to maintain a balanced result even after emission cuts were realised. The experience of the BRT system in Bogot\u0026aacute;, Latin America, proved that the level of emissions, as well as social equity of a certain locality, could be improved jointly and that in Brazil, the projects with renewable energy were funded primarily because they could alleviate poverty (Chiquetto et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The above-mentioned cross-regional differences justify the conclusion that the success of any policy is determined more by the quality of governance and socio-economic environment (Gouldson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Elkhatat and Al-Muhtaseb, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo further synthesize the findings, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the key socio-economic impacts associated with different categories of urban energy policies. This matrix highlights the trade-offs and co-benefits across economic, equity, health, and behavioral dimensions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-Economic Impacts of Urban Energy Policy Types (Synthesis of 46 Studies)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolicy Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEconomic Costs/Benefits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSocial Equity Impacts\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePublic Health Effects\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBehavioral/Lifestyle Shifts\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnergy Efficiency (e.g., building retrofits, efficient appliances)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh upfront costs; long-term savings on energy bills; job creation in retrofitting industries\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRisk of energy poverty if low-income groups cannot afford upgrades\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReduced indoor air pollution; improved comfort\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEncourages energy-saving practices in households\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRenewable Energy (e.g., solar, wind, biomass)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge capital investment; energy diversification; new employment opportunities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMay widen inequality if subsidies favor wealthier households; equity gains if community-based schemes adopted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReduced emissions \u0026rarr; better air quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePromotes adoption of distributed energy and prosumer culture\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransport \u0026amp; Urban Planning (e.g., public transit, cycling, congestion pricing)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInfrastructure costs; reduced congestion \u0026rarr; long-term productivity gains\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRisk of gentrification/displacement (congestion pricing); equity gains from affordable public transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eActive transport improves cardiovascular health; reduced exposure to car emissions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEncourages modal shift toward sustainable mobility\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarket-based \u0026amp; Regulatory Instruments (e.g., fee-charging, carbon pricing, land use regulation)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGenerates municipal revenue; incentivizes innovation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRisk of regressive effects unless revenues recycled to vulnerable groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReduced fossil fuel use improves urban air quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAlters consumption patterns toward cleaner energy/services\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e compares socio-economic impacts by policy type. Efficiency raises affordability issues, renewables risk inequality, transport policies improve health but risk gentrification.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Limitations\u003c/h2\u003e\u003cp\u003eWhile this review synthesizes 46 peer-reviewed studies on the socio-economic impacts of urban energy policies, several limitations should be acknowledged:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e Geographical bias: Most studies originate from East and Southeast Asia, with limited representation from Sub-Saharan Africa, Latin America, and Central/Eastern Europe. This uneven distribution constrains the global generalizability of the findings.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eVariation in methodological quality: Although systematic screening and critical appraisal tools (CASP and JBI) were applied, differences in study design and methodological rigor across the included literature limit comparability of results.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePublication and language bias: The review emphasizes published, English-language journal articles, which may exclude relevant policy reports or studies in other languages.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSimplification of complex trade-offs: The synthesis highlights broad trends but cannot capture the full complexity of socio-economic trade-offs at the local level.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThese limitations underscore the need for more geographically diverse and methodologically consistent research to strengthen evidence for policy formulation.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Conclusion and Policy implications","content":"\u003cp\u003eThe literature review was conducted in a systematic manner to synthesize existing evidence on the socio-economic effects of urban energy policies implemented between 2015 and 2024. The analyses show that although policies promoting energy efficiency, renewable energy, sustainable transport, and market-based solutions have made a significant contribution to reducing CO₂ emissions. These include short-term economic costs, distributional injustices, and disproportionate burdens on vulnerable groups. At the same time, many policies generated important co-benefits, such as improved public health from cleaner air, the creation of green jobs, and shifts toward more sustainable consumer behavior. Aligning these socio-economic dimensions with environmental objectives is therefore essential to ensure long-term effectiveness and public legitimacy.\u003c/p\u003e\u003cp\u003eThis review highlights that the impacts of urban energy policies vary across regions and socio-economic contexts. In developed countries such as those in Europe, initiatives like the London congestion charge and stringent building efficiency codes have successfully combined emission reductions with revenue generation for sustainable mobility. In China, large-scale low-carbon city pilot programs demonstrate how integrated policy frameworks can drive industrial restructuring, though social equity challenges remain. In Latin America, participatory renewable energy initiatives and urban transit systems, such as Bogot\u0026aacute;\u0026rsquo;s Bus Rapid Transit (BRT), have improved both environmental outcomes and social inclusion. In Sub-Saharan Africa, community-based solar microgrids stand out as niche solutions that enhance energy access while supporting local employment and reducing carbon dependency.\u003c/p\u003e\u003cp\u003eThese diverse experiences underline that there is no \u0026ldquo;one-size-fits-all\u0026rdquo; pathway: policies must be designed and adapted according to regional realities. Developing cities face financial and institutional constraints but also possess opportunities for leapfrogging directly to cleaner, decentralized energy systems. Developed cities, by contrast, can leverage existing infrastructure and governance capacity to implement large-scale efficiency and integration measures.\u003c/p\u003e\u003cp\u003eFuture research should therefore expand coverage of underrepresented regions such as Sub-Saharan Africa and Central and Eastern Europe, while incorporating systematic assessments of equity, health, and behavioral impacts into policy evaluations. Such comparative insights will help policymakers craft targeted, evidence-based interventions that maximize climate benefits while ensuring fairness and inclusiveness in the global transition to sustainable urban development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eH.P.G. conceived and designed the study, developed the search strategy and review protocol, conducted database searches, screened studies, extracted and analyzed data, and drafted the main manuscript text. W.J. contributed to the conceptual framing and methodology, advised on the review protocol, supported interpretation of the findings, and critically revised all sections of the manuscript. S.G. assisted with database searches, screening and data extraction, prepared summary tables and figures, and contributed to writing the sections on urban energy policy instruments and socio economic outcomes. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the Faculty of Environmental Management, Prince of Songkla University, for academic support. We also thank colleagues at Everest Center for Research and Development Partners, Nepal, for constructive comments during the design of the review protocol. We are grateful to friends and research assistants who supported database searches, article screening, and data extraction. The views expressed in this article are those of the authors and do not necessarily reflect the views of their institutions.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eResearch data are derived from previously published studies identified through the systematic literature review. The datasets generated and analyzed in this study, including the study screening log and data extraction matrix, are not publicly available because they are based on copyrighted third party publications, but they are available from the corresponding author on reasonable request. No new raw data were collected from human participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkbari, F., Mahpour, A., \u0026amp; Ahadi, M. R. (2020). 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Does smart city policy lead to sustainability of cities? \u003cem\u003eLand Use Policy\u003c/em\u003e, \u003cem\u003e73\u003c/em\u003e, 49\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landusepol.2017.12.013\u003c/span\u003e\u003cspan address=\"10.1016/j.landusepol.2017.12.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Urban Energy Policies, CO₂ Emissions, Socio-Economic Impacts, Sustainable Urban Development, Environmental Policy","lastPublishedDoi":"10.21203/rs.3.rs-8283710/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8283710/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this systematic literature review (SLR), the effects of socio-economic urban energy policies on CO₂ emission levels are discussed. Any energy policy enacted at the city level aimed at mitigating greenhouse gases is considered crucial, as it contributes to emissions reduction and is particularly important for the fastest-growing cities in the developing world. However, these policies are associated with socio-economic impacts that are not easily discernible. The effects of these policies on economic costs and benefits, social equity, public health, and changes in behavior are incorporated and compared in the review. This review synthesizes evidence from 46 peer-reviewed studies published between 2015 and 2024, revealing that most research has concentrated on Asian megacities, while evidence from Africa and Latin America remains limited, indicating a significant geographical imbalance in the literature. However, the evidence base remains geographically imbalanced, with most studies drawn from Asian megacities and very limited representation from Sub-Saharan Africa, Latin America, or Central and Eastern Europe. This imbalance constrains the generalizability of findings and underscores the need for more geographically inclusive research. It is emphasized that although such policies are environmentally beneficial, they initially entail high costs, have implications for social equity, and require changes in behavior. Additionally, harmonization between the environmental dimensions of policy and socio-economic factors is necessary to foster sustainable city development policies. The findings point to the following directions for future research and policy: a) More comprehensive models must be incorporated to examine the variety of socio-economic effects; b) The relative efficiency of different policy mixes across sectors and contexts should be investigated; c) Greater attention should be paid to addressing the role of stakeholder engagement in the construction and implementation of effective and equitable policies. Key information that can be of use to policymakers is offered, ensuring that urban energy policies are developed to maximize benefits that meet the needs of the population while averting conceivable implications.\u003c/p\u003e","manuscriptTitle":"Socio-Economic Impacts of Urban Energy Policies on CO₂ Emissions: A Systematic Literature Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 05:29:48","doi":"10.21203/rs.3.rs-8283710/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"074c2f75-1750-43ff-826a-c028b5a88591","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T05:29:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 05:29:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8283710","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8283710","identity":"rs-8283710","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}