Energy Policy Development Research Articles

The Evolution of U.S. Republican and Democratic Party Approaches to Climate Agenda: Late 1990s to 2023

The article focuses on analyzing the reasons behind the differing approaches of the Republican and Democratic parties to the issue of climate change. Party positions on this matter significantly influence the development of economic and energy policies in the U.S. Furthermore, the U.S.'s involvement in international efforts to combat global warming is also shaped by the power dynamics between these parties in the presidential administration and Congress. These stances directly impact other vital aspects of U.S. economy and politics, particularly in areas such as energy and Washington's role in international endeavors to achieve net-zero emissions. The climate agenda has become a significant point of contention in EU-US relations, a topic that holds particular relevance today. The findings of the study indicate an increasing partisan divide on the climate agenda, signifying deepening divisions in American society as the 2024 presidential election approaches.

MECHANISMS AND MEASURES FOR THE DEVELOPMENT OF ENERGY SOURCES IN ALGERIA IN LIGHT OF SUSTAINABLE DEVELOPMENT

Objective: The aim of this study is to examine the sustainable use of energy sources in Algeria, focusing on the need to improve the efficiency of managing non-renewable resources in light of increasing global energy consumption and its environmental impacts. Given that Algeria heavily relies on non-renewable energies, the research addresses the importance of enhancing the sustainability of these sources to align with global development goals. Theoretical Framework: The theoretical framework discusses the role of energy in global economies, particularly emphasizing the environmental challenges posed by non-renewable energy sources. It explores concepts related to sustainable development, resource management, and the importance of aligning national energy policies with global sustainability standards. Methodology: The study utilizes a comprehensive review of existing literature and energy consumption data in Algeria. It assesses current resource management practices, explores policy frameworks, and identifies opportunities for improving energy efficiency and sustainability. The methodology includes both qualitative and quantitative analyses to provide a holistic understanding of the issue. Findings: The results indicate that Algeria's heavy reliance on non-renewable energy sources necessitates immediate action to improve resource management efficiency. The study highlights key areas where policy improvements can lead to more sustainable use of energy, ultimately contributing to long-term economic and environmental stability. Research, Practical & Social Implications: The study has significant implications for energy policy development in Algeria, offering insights into how the country can better manage its non-renewable energy resources. Practically, it suggests actionable strategies for improving energy efficiency and aligning with global sustainability goals. Socially, the research emphasizes the importance of addressing energy consumption patterns to reduce environmental harm and ensure sustainable development. Originality/Value: The value of the study lies in its focus on Algeria, providing context-specific insights into sustainable energy management. It highlights the urgent need for improving the efficiency of non-renewable resource use in a country that heavily depends on such sources, while offering practical recommendations for policy makers to foster sustainable development in the energy sector.

Changes in the Global Structure of Energy Consumption and the Energy Transition Process

The global energy transition represents a pivotal aspect of the pursuit of sustainable development and the reduction of greenhouse gas emissions. The objective of this study was to examine the dynamic relationships between global primary energy consumption and the consumption of individual energy sources (nuclear, oil, coal, natural gas, renewables) from 2011 to 2023. To examine both long-run and short-run relationships between variables, advanced econometric methods were employed, including the Johansen cointegration test and the Vector Error Correction Model (VECM). Furthermore, an Index of Sustainable Energy Transformation (ISTE) was devised to quantify the advancement of the transition to low-carbon energy sources. The analysis confirms the existence of long-term equilibrium relationships between global primary energy consumption and the consumption of individual energy sources. The analysis revealed that renewable energy consumption exerts a considerable influence on primary energy consumption, both in the short and long term. The ISTE index demonstrated a notable increase over the period of 2011 to 2023, indicative of advancement in the global energy transition. The results confirm the existence of a stable long-term equilibrium between global primary energy consumption and the consumption of individual energy sources. The observed increase in the ISTE index indicates progress towards low-carbon energy sources, which has important implications for energy policy and sustainable development. The results can support policymakers in monitoring the progress of the energy transition and shaping policies to accelerate the development of renewable energy sources.

Evaluating Energy Consumption in Residential Buildings in Qatar: A Case Study on Compounds

The global urgency to cut carbon emissions and pollution is clear. Qatar, rich in fossil fuels, is shifting towards sustainability to reduce carbon emissions. This paper analyzes the energy consumption patterns in residential buildings in Qatar, categorizing them by size and ownership, and establishing energy benchmarks for each building type, offering insights to guide energy efficiency policies. By examining the building size and ownership, the study helps establish benchmarks, supporting Qatar’s sustainability goals in reducing carbon emissions. The study was conducted from 1 January 2019 to 31 December 2021, utilizing data from the Qatar General Electricity and Water Corporation (KAHRAMAA). A total of 172,796 residential buildings were analyzed, with data on building characteristics and demographic information incorporated into the analysis. A quantitative analysis revealed that the building size, ownership, and demographics significantly impact energy consumption, guiding efficiency strategies. The ownership and floor area significantly impact energy consumption. A strong positive correlation (R = 0.97) was found between energy consumption (kWh) and the total built area (m2). The patterns of energy use varied across different residential building types. The findings highlight the importance of considering the ownership and building size in energy efficiency policies. Identifying specific energy use patterns supports the development of targeted strategies. This research offers valuable data on residential energy consumption in Qatar, providing a foundation for energy benchmarks. These benchmarks can guide policy decisions and strategies to enhance energy efficiency and promote sustainability in the residential sector. This study uniquely connects the ownership and building size with energy consumption patterns in Qatar, supporting the development of effective energy policies and contributing to global sustainability goals.

Sustainable development goals and environmental performance: Exploring the contribution of governance, energy, and growth

This study investigates the impact of renewable and non-renewable energy consumption, governance quality, and economic growth on environmental sustainability across frontier, emerging, and developed economies from 2001 to 2021. The Environmental Performance Index (EPI) and Sustainable Development Goals (SDGs) are environmental sustainability measures. The study addresses potential endogeneity issues through advanced econometric techniques and explores the differential impacts of energy sources, governance structures, and economic factors on environmental performance. The findings reveal significant variations in how these factors influence environmental sustainability across frontier, emerging, and developed economies. The results demonstrate a positive relationship between renewable energy consumption and governance quality with environmental sustainability, while non-renewable energy consumption exhibits a negative association. Economic growth emerges as a crucial factor influencing both environmental performance and the advancement of SDGs. This research contributes to the expanding literature on environmental sustainability by presenting a comprehensive analysis of its determinants across different economic contexts. The findings provide valuable insights for policymakers, underscoring the importance of tailored approaches to energy policy, governance reforms, and economic development strategies in the pursuit of environmental sustainability goals.

Assessing dynamics of urban solar PV power generation using grid divisional method

The assessment of solar energy potential and urban density has become a crucial prerequisite for urban sustainable development. However, two significant challenges persist: the high computational cost associated with assessments across large urban areas and the lack of detailed rooftop information for each building. This study aims to integrate solar photovoltaic (PV) systems in urban environments of varying built density in an Indian city and assesses the solar energy potential (SEP) using grid divisional method and simulations. The methodology involved extracting, filtering and developing a 2.5 D model with GIS using the open buildings dataset, followed by simulations of grid-connected PV systems using PV-Sol. The results demonstrated the dynamics in correlation of SEP and grid morphology indicators, with built density and roof area showing a strong positive relation. The financial analysis resulted in average payback period of 8–10 years. The study also highlighted significant CO2 emission reductions, with thermal power plants generating 26,982 tons/kWh compared to just 1,513 tons/kWh for solar power. The findings demonstrate the financial viability and environmental benefits of PV adoption in urban areas, offering crucial insights for sustainable energy planning and policy development.

Public perception and policy development in the transition to renewable energy

The transition to renewable energy is essential for addressing climate change and ensuring a sustainable future. This paper explores the critical role of public perception in shaping the development and implementation of renewable energy policies. It examines the historical evolution of public attitudes toward energy, the factors influencing public perception, and the impact of public support or opposition on policy outcomes. Additionally, the paper reviews current policy frameworks and highlights the challenges policymakers face in balancing public opinion with political, economic, and environmental goals. Public engagement emerges as a key factor in successful policy implementation, with examples from various countries illustrating how public involvement has influenced energy transitions. Finally, the paper discusses future trends in public perception and offers recommendations for policymakers to better align public opinion with the goals of renewable energy transitions. The findings underscore the importance of integrating public perception into policy development to achieve a successful and inclusive energy transition.

Options for environmental regulation policy under China's carbon peaking target: Energy supply policy or carbon tax policy?

China plans to achieve the carbon peaking target by 2030 and will maybe implement a series of environmental regulation policies, primarily including energy supply policy (such as coal consumption constraint and non-fossil energy development) and carbon tax policy. This paper simulates these policies using a computable general equilibrium model. The simulation results indicate that carbon tax policy has a finite impact on the economy, the emissions reduction effect is also limited and carbon tax policy alone is insufficient to achieve China's 2030 carbon peaking target. The coal consumption constraint policy has a good emissions reduction effect, but is not conducive to economic growth. The non-fossil energy development policy can increase energy supply and promote economic growth, but the emissions reduction effect is inadequate. In general, the simultaneous implementation of the coal consumption constraint and non-fossil energy development policies could not only achieve the carbon peaking goal, but also narrow the energy gap and reduce pressure on economic growth. However, it is notable that if carbon tax policy and energy supply policy are implemented simultaneously, the emissions reduction effect of carbon tax policy would be significantly reduced; therefore, it is likely that no carbon tax will be levied in China.

WITHDRAWN: The impact of renewable energy development on regional carbon emission reduction: Based on the spatio-temporal analysis of 30 provinces in China

The development of renewable energy has become an important means for the world to cope with climate change, ensure energy security and protect the ecological environment. Using the panel data of 30 provinces in China from 2013 to 2021, this paper used the mediating effect model and the spatial Durbin model (SDM) to explore the mechanism and spatial effects of renewable energy development on carbon emission reduction. The results show that: (1) The results of mechanism analysis show that renewable energy development reduces carbon intensity by improving energy structure, promoting industrial structure optimization and industrial structure upgrading. (2) Renewable energy development can not only reduce the local carbon intensity, but also have a positive spillover effect on the carbon intensity of neighboring regions. (3) Further analysis shows that renewable energy development has a dynamic effect on carbon emissions. The heterogeneity analysis shows that compared with the Yellow River basin, renewable energy development significantly influences carbon emission reduction in the Yangtze River Economic Belt region. Energy-rich areas fall into the "resource curse", which makes renewable energy development’s carbon emission reduction effect not significant. This paper has certain reference significance for promoting reasonable decomposition between regions and formulating renewable energy development policies.

Development path for China's mega-large urban agglomerations based on the water-energy-food nexus

The Beijing-Tianjin-Hebei (BTH) mega-large urban agglomeration of China (CMUA) has significantly contributed to Chinese socioeconomic development. However, it faces severe shortages in the supply to meet the increasing demand of water, energy, and food resources (WEF). In order to safeguard the resource security of CMUA-BTH and the synergistic development of cities, and to compensate for the lack of dynamic analysis between urban agglomerations and WEF in previous studies. In this study, a coupled CMUA-WEF simulation model is developed based on the system dynamics approach. The model not only studies the three elements of WEF, supply and demand, but also conducts a comparative analysis of the three regions of BTH, and designs a total of four scenarios based on the possibility of future development, so as to facilitate the depiction of the trend of the WEF supply and demand system under different scenarios, and to provide theoretical basis for the government to formulate effective policy. The results show that: (1) Regarding demand, the aggregate demand for energy, food and water in the BTH will increase by about 3–5 times, 3 times, and 2 times, respectively, from 2000 to 2050, among which the total demand for energy will increase most significantly. In contrast, the variation of local resource supply side is small, which leads to the deterioration of resource security. (2) The risk of water shortage is the greatest in resource security, with less than 30% self-sufficiency in water security in all three regions. (3) Scenario analysis for CMUA-BTH indicates that “choking flow” (S3) yields more pronounced effects compared to “open source” (S2), and therefore adhering to the reduction of food waste, promoting energy-saving technologies, and intensifying water-saving measures can effectively reduce the risk of water shortages in the three regions. Optimal resource security in S4 increases Hebei's water pressure by 1.5%, alleviates Beijing's pressure by 7.3%, and the implementation of the Xiongan New Area and the new energy development policy can help realize the synergistic development of BTH and the inter-regional linkage.

The rise in female consciousness contributes to advancing household energy transition: Evidence from Chinese households

Gender is an indispensable dimension, gender equality and empowering all women are core elements in transitioning to sustainable energy. However, current research on how female consciousness impact energy fairness remains insufficient. To fill this gap, utilizing data from the China Family Panel Studies (CFPS), encompassing 16,000 households and 43,147 respondents, we explore how female consciousness influences energy transition. The findings reveal that a rise in female consciousness contributes to advancing household energy transition, particularly in eastern and urban areas where this effect is more pronounced. Further moderating effect analyses indicate that improved levels of female education and heightened female income further enhance the effective utilization of female awareness in driving household energy transition. The study not only deepen our understanding of the relationship between female consciousness and energy transition but also provide a scientific basis for developing energy policies promoting gender equality in developing countries, thus fostering global gender equality and sustainable energy development.

Life cycle climate performance of photovoltaic power plant for Turkey’s solar power conditions

ABSTRACT In this study, a solar power plant with an output power of 10 kW AC was designed according to the Turkish Electricity Legislation. Silicon-based photovoltaic modules were used in the design. The solar power plant’s annual and lifetime electricity generation was calculated for 81 provinces of Turkey. The study contributes significantly to the literature by evaluating the environmental impacts of energy sources in a more realistic way. According to the electricity generation calculations, the power plant in Trabzon generates a minimum of 13,037 kWh of electricity per year. In comparison, the power plant in Antalya generates a maximum of 18,562 kWh. Over the plant’s life, Antalya will generate 464,040 kWh of electricity and Trabzon will generate 325,929 kWh. The life cycle climate performance technique was used to understand the environmental impacts during the installation phase, and these values were determined to be 5759 kgCO2. Emission values from electricity generation vary between 0.01241 and 0.01767 kgCO2 per kWh. These data provide a comprehensive assessment of the environmental impacts of solar power plants. This study contributes to the literature by investigating the potential and environmental effects of solar energy in different regions of Turkey in detail. In particular, presenting the emission values of electricity generation from photovoltaic systems for each province provides valuable data that can be used in shaping energy policies and developing environmental strategies. This unique study will provide a scientific basis for planning and implementing solar energy investments in Turkey and contribute significantly to developing energy policies and environmental strategies.

The alleviating effect of household distributed photovoltaics on multidimensional relative poverty in rural areas

Relative poverty represents a major obstacle to China's rural revitalization efforts and necessitates enhanced policy support. This study aims to investigate the impact of household distributed photovoltaic (HDPV) on relative poverty conditions. Based on 337 questionnaire data from Jiujiang City, Jiangxi Province in 2022, we construct a multidimensional relative poverty index using the Alkire-Foster method to assess the level of relative poverty. We employ fixed-effects models and mediation models to evaluate the effectiveness of HDPV in alleviating relative poverty. The results indicate that HDPV reduce the multidimensional relative poverty level of rural residents by approximately 0.058, demonstrating that installing HDPV can significantly alleviate multidimensional relative poverty. This effect is primarily achieved through increased investment in children's education. Additionally, we find that the alleviation effect varies by income level, with lower-income households experiencing greater improvements compared to higher-income households. Specifically, HDPV reduce the poverty level of the low-income group by approximately 0.0969, while the high-income group saw a reduction of about 0.0313. The findings of this study enrich the research on relative poverty in China by revealing the poverty-alleviating attributes of HDPV. It provides support for the development of renewable energy and regional development policies and has practical significance for advancing photovoltaic building integration.

Monthly electricity consumption data at 1 km × 1 km grid for 280 cities in China from 2012 to 2019

High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method’s accuracy showed significant improvements, with determination coefficients (R2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies.

Advancing Nuclear Energy Forecasting: Exploring Regression Modeling Techniques for Improved Accuracy

The urgent requirement for sustainable and dependable energy sources has stimulated an increased fascination with precisely forecasting nuclear energy generation. This work utilizes sophisticated regression modeling approaches, namely XGBoost, to predict nuclear energy generation by leveraging economic indices such as Gross Domestic Product (GDP). Each model’s prediction accuracy has been evaluated by examining historical data on nuclear energy output and GDP from various locations. Here, measures such as mean squared error (MSE) and coefficient of determination (R2) to analyze their effectiveness have been used. The results of this study demonstrate that the XGBoost model outperforms standard regression approaches, showing greater R2 values and lower MSE scores. Furthermore, the consequences of these discoveries for the development of energy policy offer possible directions for future study in energy forecasting. This study provides useful insights for energy planners and policymakers, enabling a more profound comprehension of the complex relationship between economic indicators and nuclear energy generation.

Optimal energy storage configuration to support 100 % renewable energy for Indonesia

This study presents a renewable energy (RE) optimization study to model the pathway to achieve 100 % carbon abatement, focussing on options for storage, using Indonesia's national electricity grid as a case study. Utilizing the PLEXOS energy simulation tool, the study covers the period 2021–2045. It employs an optimization of cost minimization function approach, encompassing investment, operation, maintenance, and unserved energy. The study integrates various components, including electricity supply and demand, transmission, renewable sources, and energy storage, while considering operational, build, and renewable energy target constraints. A range of scenarios are explored, varying in RE targets, battery capacities, and whether to include open-cycle gas turbines. The key novelty of this study is considering multiple versions of battery storage, with different options for the number of hours of storage. The findings indicate that higher RE targets lead to increased total installed nameplate capacity, with a significant portion from battery storage. In the early phases, batteries with 2-hour of capacity prioritized for short-term needs. As the focus shifts to more extended targets, batteries with a 4-hour capacity are recognized as more cost-effective and become the predominant choice. Over time, the least-cost strategy evolves to incorporate 10-hour capacity batteries to meet long-term energy storage requirements. To achieve a 100 % RE target by 2045, it is estimated that alongside every 100 MW of wind and solar capacity, there should be a corresponding 42 MW of energy storage. However, interpretations of these findings must consider the limited temporal resolution, uncertainties in demand and cost, and challenges related to grid inertia from energy storage, which may affect the stability and feasibility of the proposed solutions. This research offers crucial insights for energy policy and infrastructure development in renewable energy and storage system implementation.

AI-Enhanced lifecycle assessment of renewable energy systems

As the global push towards renewable energy intensifies, it becomes imperative to comprehensively assess the environmental impacts and sustainability of renewable energy systems throughout their operational lifecycle. Traditional lifecycle assessment (LCA) methods, while useful, often fall short in handling the complex, dynamic data associated with renewable energy systems. This study explores the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance lifecycle assessments of wind, solar, and green hydrogen energy systems, aiming to provide more accurate, efficient, and comprehensive evaluations. AI-driven LCA models leverage extensive datasets from various stages of the lifecycle of renewable energy systems, including raw material extraction, manufacturing, installation, operation, maintenance, and decommissioning. By employing ML algorithms, these models can identify patterns and relationships within the data, predict potential environmental impacts, and provide insights into sustainability performance over time. The research focuses on developing and validating ML models that incorporate diverse data inputs such as material usage, energy consumption, emissions, and waste generation. These models are trained using historical data from multiple renewable energy projects and are capable of adapting to new data inputs, ensuring continuous improvement in assessment accuracy. Key findings demonstrate that AI-enhanced LCA models significantly improve the precision and depth of environmental impact assessments. For wind energy systems, ML models help in predicting turbine lifespan and maintenance needs, thereby optimizing resource use and minimizing environmental footprints. In solar energy systems, AI techniques assist in forecasting degradation rates and energy yield, contributing to more sustainable design and operation. For green hydrogen production, ML models optimize the electrolysis process and assess the overall sustainability of hydrogen supply chains. The integration of AI in LCA facilitates real-time monitoring and dynamic adjustments, ensuring that renewable energy systems operate at peak sustainability. This approach not only enhances the environmental performance of individual systems but also supports strategic decision-making in renewable energy deployment and policy development. In conclusion, the application of AI and ML techniques in lifecycle assessment offers a transformative approach to evaluating the environmental impact and sustainability of renewable energy systems. This research underscores the critical role of advanced analytics in advancing the global transition to sustainable energy and calls for further exploration and adoption of AI-driven LCA methodologies. Keywords: Machine Learning, Renewable Energy Systems, Environmental Impact, Sustainability, AI-Enhanced Lifecycle.

The analysis of electricity consumption in Kazakhstan

The energy sector is a fundamental element of the economic structure of any state, determining its sustainability, competitiveness and ability to innovate. In this context, Kazakhstan, which has significant reserves of hydrocarbons, energy sources and renewable properties, finds itself at the crossroads of solving issues of energy policy, innovation and sustainable development. The electricity sector is a priority resource necessary to maintain the economic security of the country. This is relevant due to the rapid growth of industrial production and demography in order to maintain increasing demand and increase electricity generation in the country. The purpose of this scientific work is focused on the economic analysis of electricity generation and consumption, as well as the identification of shortcomings and the proposal of recommendations to ensure the sustainable development of the energy sector in Kazakhstan. Using the scientific method of analysis, the study aims to identify trends that determine the level of electricity consumption in the country, as well as to offer recommendations for the sustainable and effective development of this industry. The article is a valuable contribution to strengthening and modernizing the energy system of the country. The results of the research are: the current state of Kazakhstani energy sector is revealed against the background of anti-Russian sanctions, increased energy prices and global uncertainty; a comparative analysis of electricity production is carried out; an economic assessment of primary and final energy consumption from 2015 to 2023 was carried out; the reasons for changes in electricity generation and consumption from the perspective of industrial and consumer demand growth were substantiated; shortcomings were revealed and proposals were made to improve the development and consumption of electricity in the republic. The results obtained have significant potential to initiate certain transformations in the energy sector of Kazakhstan. The article is a scientific work contributing to the development of theory and practice in the field of energy in Kazakhstan. This research contributes to the further development of energy consumption and improvement of the country's energy infrastructure, ensuring its sustainability and competitiveness in the long term.

The Impact of Renewable Energy Development on Regional Carbon Emission Reduction: Based on the Spatio-Temporal Analysis of 30 Provinces in China.

The development of renewable energy has become an important means for the world to cope with climate change, ensure energy security, and protect the ecological environment. Using the panel data of 30 provinces in China from 2013 to 2021, this study used the mediating effect model and the spatial Durbin model (SDM) to explore the mechanism and spatial effects of renewable energy development on China's regional carbon emission reduction. The results show that: (1) Renewable energy development can help to reduce carbon emission intensity. (2) The results of mechanism analysis show that renewable energy development reduces carbon intensity by improving energy structure, promoting industrial structure optimization, and industrial structure upgrading. (3) The development of renewable energy can not only reduce the local carbon intensity but also have a positive spillover effect on the carbon intensity of neighboring regions. (4) Further analysis shows that the long-term effect of renewable energy development on carbon emissions is greater than the short-term effect. At the same time, the heterogeneity analysis shows that compared with the Yellow River basin, the development of renewable energy has a significant carbon emission reduction effect in the Yangtze River Economic Belt region. Energy-rich areas fall into the "resource curse", which makes the carbon emission reduction effect of renewable energy development not significant. This paper has certain reference significance for promoting reasonable decomposition between regions and formulating renewable energy development policies.

Addressing environmental justice in clean energy policy: Comparative case studies from the United States and Nigeria

This paper explores the intersection of environmental justice and clean energy policy through a comparative analysis of case studies from the United States and Nigeria. Environmental justice, defined as the fair treatment and meaningful involvement of all people in environmental decisions, is increasingly recognized as a critical aspect of transitioning to clean energy systems. By examining clean energy policies and initiatives in both countries, this study aims to identify successes, challenges, and lessons learned in addressing environmental justice considerations. In the United States, the analysis focuses on federal and state-level clean energy policies, assessing their impact on marginalized communities and efforts to promote equity in access to clean energy resources. Similarly, in Nigeria, attention is given to government-led clean energy initiatives and their implications for environmental justice, particularly in rural and underserved areas. Through a comparative lens, this paper highlight’s common themes and divergent approaches to addressing environmental justice in clean energy policy between the two countries. It identifies opportunities for cross-country collaboration and knowledge sharing to advance equitable and sustainable energy transitions globally. The findings underscore the importance of integrating environmental justice principles into clean energy policy development and implementation, with recommendations provided for policymakers and stakeholders to promote inclusivity, fairness, and community engagement in shaping the future of clean energy.