Climate Change Mitigation Measures Research Articles

An evaluation of the Africa-CORDEX Regional Climate Model's performance in simulating air temperatures and precipitation in the Melka-Wakena Catchment, Southeast Ethiopia

Understanding climate science is essential for effective policy development, adaptation, mitigation, and risk management. Given the inherent limitations in climate models, this study evaluates the performance of CORDEX Africa regional climate models to simulate precipitation and temperatures over the Melka-Wakena catchment. To accomplish this, the performance evaluation utilizes techniques such as multi-metric weighted ranking to select top-1 (best individual model), specific multi-model ensembles (top-N ensemble), multi-model ensemble, and average hybrid (top-N ensemble with MME) approaches at various temporal scales. Also, Taylor diagrams and empirical cumulative distribution functions are other useful elements for model comparison visualization. This study finds that, top-3 ensemble (for temporal scale tasmin, monthly pr), top-7 ensemble (monthly and seasonal tasmax), average hybrid (top-1 with MME (daily pr and tasmax), HadGEM2ES_RACMO22T for seasonal and yearly pr), and HadGEM2ES_RCA4 for yearly tasmax) are preferable, with weighted scores of 0.29, 0.44, 0.22, 0.20, 0.35, 0.40, 0.39, 0.33, 0.45, 0.25, and 0.33, respectively. In short, RCA4 and RACMO22T efficiently mimic air temperatures and precipitation in the Melka-Wakena catchment. While ensemble approaches are generally more resilient and possible, single-best-performing model approaches can be quite effective for long-term periods. Finally, these studies have an important implication for improving climate change assessment, adaptation, and mitigation measures.

Quantifying food security and mitigation risks consequential to climate change impacts on crop yields

Abstract Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the IMAGE integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison (GGCMI) of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as Agriculture, Forestry and Other Land Use (AFOLU) emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.

Quantifying the Carbon Reduction Difference Based on Households' Willingness to Transform Their Lifestyles from the Micro Perspective

Cities are gathering places for residents, industries, and energy consumption, and the carbon emissions generated by urban residents' consumption are becoming increasingly prominent. Under the "dual carbon" goal, how to effectively guide the transformation of urban households' lifestyles and achieve consumption side carbon reduction has become an important issue. Based on questionnaire surveys and face-to-face interviews in the main districts of Hangzhou, the total amount and component of household consumption carbon reduction potential in Hangzhou were calculated by adopting a carbon emission coefficient model, and the relevant factors influencing various types of household consumption behaviors and carbon reduction potential were analyzed through virtual regression models and binary logistic regression. Our results showed that the consumption carbon reduction potential of different groups of residents in the four dimensions of food, clothing, housing, and transportation was significantly different, and electricity consumption had significant direct and indirect impacts on household consumption behaviors and carbon reduction potentials. Age and income were the key factors leading to significant differences in the carbon reduction potential of household consumption. Economic interests and environmental emotional factors were the main factors that affected the transformation of residents' family lifestyle, and their strengths and weaknesses were different. Personal habits, demonstration effects of surrounding people, time costs, etc., were the main reasons affecting residents' willingness to transform their lifestyles. The findings therefore had important implications for climate change mitigation and policy measures associated with lifestyle. On the premise of ensuring stable economic development and improving the well-being of residents, differentiation guides the lifestyle choices of community residents providing reference for better realization of the "double carbon" goal.

6.F. Scientific session: Understanding the impact of climate change on health: the latest reports from EEA and NPHIs

Abstract Climate change poses a significant threat to human life and wellbeing worldwide. Extreme weather events like heatwaves, storms or floods can have adverse impacts on health, as can many other factors influenced by climate change, such as allergens, UV radiation and vector-borne diseases. In order to support the action needed to protect and promote health and wellbeing, many National Public Health Institutes (NPHIs) aim to keep relevant stakeholders informed on the scientific evidence of the impacts of climate change on health. Reports that synthesise the evidence can help in the development of suitable and health-relevant climate change adaptation and mitigation measures. In this workshop, European Environment Agency assessments on climate and health are presented, including the European Climate Risk Assessment Report and recent outputs of the European Climate and Health Observatory. Next, three NPHIs introduce their recent national reports on the impact of climate change on health, sharing lessons learned and valuable insights into their content, process and reception, highlighting similarities and differences. The workshop will feature presentations by NPHIs from the United Kingdom (UK Health Security Agency), Germany (Robert Koch Institute), and the Netherlands (National Institute for Public Health and the Environment) as well as the European Climate and Health Observatory. The perspective of the European Climate and Health Observatory offers Europe-wide insights as a provider of tools and knowledge that support actions from NPHIs and other health actors. Our aim is to highlight the value of such reports, and inform and inspire NPHIs and other stakeholders that may be considering the publication of similar reports. The format of the workshop will be informative and interactive, with opportunity for Q&A, discussion, and engagement with the audience. By showcasing the recent reports, the workshop aims to increase awareness of climate change as a public health issue and establish NPHIs as key climate actors. Furthermore, it aims to highlight the importance of having a national, up-to-date evidence base to drive climate measures and enhance resilience. Key messages • National evidence-based reports on climate change and health are a useful tool for informing health-relevant climate change adaptation and mitigation measures. • Through the public health functions of surveillance, monitoring, responding and evaluating, NPHIs play a crucial role in collating and assessing the evidence on the health effects of climate change.

Ensuring sustainable impact of the national report on climate change and health in Germany 2023

Abstract Issue/problem The Robert Koch Institute recently coordinated a status report on climate change and health for Germany, detailing the current and future impact of climate change on health through 14 chapters. Description of the problem A central aim was to ensure the report’s long-term impact and public health value. Essential areas of focus have therefore been stakeholder-specific communication and establishing a network of experts for continued scientific exchange. Results The publication of the report as peer-reviewed articles has served to reach the scientific community. Another target group are public health practitioners and decision makers at subnational levels, who can contribute towards climate change mitigation and adaptation measures relevant to health, as recommended in the report. This latter group was reached through various methods and formats of science communication, including conferences aimed at the public health sector, through target-group oriented podcasts, social media engagement and digital town hall discussions. Following publication, the experts involved in writing, reviewing and using the report were invited to establish a network in order to support long-term scientific exchange and collaborations and in turn ensure the report’s sustainable impact and value. Lessons Through follow-up evaluations, the reception of the report and the further communication needs of this target group were analysed. A major lesson was to include the insights of public health practitioners more systematically and at an earlier stage in any future reports. As for the establishment of a network, a survey amongst the authors and other experts showed what this group considers the goals of this network: creating synergies and connections with existing initiatives and providing a platform for further exchange, especially amongst researchers addressing similar questions, such as the efficacy of mitigation and adaptation measures, from different angles. Key messages • Local public health practitioners are important stakeholders for climate change and health for ensuring public health impact. • The expertise in the network will support continued scientific exchange on climate change and health and thus ensure the national report’s sustainability.

Do impoverished regions benefit from climate change mitigation measures? Evidence from the Forest Carbon Sink Project in China

ABSTRACT Forests play a crucial role in achieving global climate change mitigation goals. The Forest Carbon Sink Project (FCSP) was initially proposed by the Clean Development Mechanism under the Kyoto Protocol, aiming to address externalities in climate governance through ecological compensation mechanisms. For impoverished regions, the FCSP is more attractive than the mandatory administrative approaches to forest protection. This Currently, due to the lack of empirical research, there is still debate in the academic community about whether the FCSP can produce overall positive economic benefits in poor areas. Based on panel data from 634 impoverished counties in China from 2002 to 2019, this study attempts to address this issue using a multi-period Difference-in-Differences (DID) model. The results demonstrate that, compared to non project counties, the implementation of the FCSP led to an increase in actual GDP and per capita GDP of 8.40% and 11.10% in project counties, respectively. That is, the FCSP can expand the economic scale while also promoting economic growth of project counties. The results of the dynamic model show that the economic benefits generated by the FCSP in these counties are long-term and sustainable. Based on the results of theoretical analysis and mechanism testing models, this study concludes that the FCSP generates short-term economic benefits through capital investment. It generates long-term economic benefits by improving the productivity of the primary industry labour force, increasing the level of fixed asset construction, and optimizing the industrial structure in poverty-stricken counties. Additionally, this study also conducted a heterogeneity analysis. In summary, this study concludes that the FCSP is a climate change mitigation measure worthy of promotion in impoverished regions.

Heatwave Intensifications in Armenia: Evidence From Temporal and Spatial Analysis of Observational Data Over the Last Decades

ABSTRACTIncreasing temperatures cause the weather to become more severe. Studying how heatwaves (HWs) impact individual heat exposure and susceptibility is vital for building climate change mitigation and adaptation measures. So, this study explores the impact of HWs on individual heat exposure and susceptibility. The assessment was based on the highly complex topographic region contribution to HWs in the Republic of Armenia (RA) using data from 16 meteorological stations for the extended warm season (May–September). We developed a regional HW catchment program to estimate the HW indices' responses to climatic change and to present them in terms of topography changes. The Mann–Kendall (MK) test was used to determine the statistical significance of the trends for 10 distinct HW indicators using linear and exponential trends along with graphical interpretations. This study reveals a large‐scale, significant increasing trend in annual maximum temperatures (Tmax) and observed HWs over the period 1955–2019. The rising temperature is accompanied by an increase in HW indices, particularly at low altitudes up to 1250 m above sea level (ASL), where the main population centres and national crop production are concentrated. According to our classification, the above‐mentioned areas have faced extreme and severe increases in HW intensity, covering more than 60% of the country's territory. Moreover, not only the intensity and frequency have been identified but the HW period extension as well. This extreme increase has been found in the low‐lying highly populated and intensively cultivated areas, such as in the Ararat valley. These results have implications for future climate assessments, adaptation strategies, agriculture and public health in Armenia. The development of targeted mitigation measures and adaptation strategies informed by these findings is essential for addressing the escalating challenges posed by HWs in the region.

Analysis of Technology for Mitigation of The Effects of Climate Change on Buildings in Kaloum (Guinea-Conakry)

Information and communications technologies (ICTs) can, in a number of ways, contribute to meeting the requirements of the three main pillars of the Bali Action Plan, which was developed at the thirteenth Conference of the Parties in December 2007. These pillars concern enhanced action on adaptation, concerted action to reduce greenhouse gas (GHG) emissions and climate change mitigation measures. ICTs can support these actions and address the climate change issues that all countries (and particularly developing countries) face. ICTs can also be used to mitigate the influence of other sectors on GHG emissions and to help countries adapt to climate change.

Spatio-temporal tendencies of urban land surface temperature on the Andean piedmont under climate change: A case study of Metropolitan Lima, Peru (1986–2024)

The increase in land surface temperature (LST) in megacities has contributed to global warming due to poor urban planning and high population concentration. This study analyzes spatio-temporal trend patterns of LST in the city of Metropolitan Lima, Peru, during the summers of 1986–2024. The Mann-Kendall tests and the Theil-Sen Slope method were used to analyze the spatio-temporal trends of LST, relating R2 and the Mann-Kendall p-value of the annual average LST in each district. A hierarchical cluster analysis was performed to group districts according to their average yearly LST. Urban heat islands were identified based on basin configuration and distance to the sea at 1 km intervals. The results reveal a significant increase in LST (p < 0.001) related to El Niño-Southern Oscillation phenomena, in addition to urban growth and land cover change. The significant positive trend of LST showed a heterogeneous distribution in all districts. The districts were grouped into three clusters with statistically significant differences in LST (p < 0.001), spatially configured radially from the sea to the foot of the Andes, up to 1179 m a.s.l. Urban heat islands did not correlate with significant positive trends in basins. Still, they showed a considerable increase in LST in areas of high economic activity, including dense commercial, industrial, and residential areas. This information is crucial to managing climate change adaptation and mitigation measures and contributing to sustainable urban planning focused on the population's well-being.

The local cooling potential of land restoration in Africa

Land restoration is becoming increasingly popular as a climate change mitigation and adaptation measure. It is suggested that resulting vegetation changes can impact the local surface temperature through biophysical processes such as albedo warming and evaporative cooling. Yet, the potential effect of land restoration on the local surface temperature in Africa remains uncertain. In this study, we use Terra MODIS time series of vegetation, albedo, and land surface temperature to determine vegetation-temperature relationships at a continental scale. We show that vegetation-albedo and vegetation-temperature relationships do not only vary spatially across Africa but also temporally over different time scales, with strong cooling effects in semi-arid environments. Furthermore, we predict that land restoration can decrease local land surface temperature by around 0.2 Kelvin on average. This study gives a more detailed insight into where future land restoration provides additional positive climate impacts, and where land restoration may instead warm the local environment.

Advancing forest carbon stocks’ mapping using a hierarchical approach with machine learning and satellite imagery

Remote sensing of forests is a powerful tool for monitoring the biodiversity of ecosystems, maintaining general planning, and accounting for resources. Various sensors bring together heterogeneous data, and advanced machine learning methods enable their automatic handling in wide territories. Key forest properties usually under consideration in environmental studies include dominant species, tree age, height, basal area and timber stock. Being proxies of stand productivity, they can be utilized for forest carbon stock estimation to analyze forests’ status and proper climate change mitigation measures on a global scale. In this study, we aim to develop an effective machine learning-based pipeline for automatic carbon stock estimation using solely freely available and regularly updated satellite observations. We employed multispectral Sentinel-2 remote sensing data to predict forest structure characteristics and produce their detailed spatial maps. Using the Extreme Gradient Boosting (XGBoost) algorithm in classification and regression settings and management-level inventory data as reference measurements, we achieved quality of predictions of species equal to 0.75 according to the F1-score, and for stand age, height, and basal area, we achieved an accuracy of 0.75, 0.58 and 0.56, respectively, according to the R2. We focused on the growing stock volume as the main proxy to estimate forest carbon stocks on the example of the stem pool. We explored two approaches: a direct approach and a hierarchical approach. The direct approach leverages the remote sensing data to create the target maps, and the hierarchical approach calculates the target forest properties using predicted inventory characteristics and conversion equations. We estimated stem carbon stock based on the same approach: from Earth observation imagery directly and using biomass and conversion factors developed for the northern regions. Thus, our study proposes an end-to-end solution for carbon stock estimations based on the complexation of inventory data at the forest stand level, Earth observation imagery, machine learning predictions and conversion equations for the region. The presented approach enables more robust and accurate large-scale assessments using limited annotated datasets.

Climate Change Effects and Mitigation Measures in Uttarakhand Himalayas Region

One of the biggest environmental issues affecting the world's natural ecosystems is climate change. Based on the literature that is currently accessible, this article offers a succinct summary of how the Uttarakhand Himalayan Mountains' agriculture, water, and 15.61% forest are affected by climate change. Numerous research have been conducted on a variety of Himalayan ecosystem-related topics, but only a small number of local studies have been published that address factors connected to climate change. This is mainly because there is a dearth of organized and targeted data on the subject. Thus, the qualitative analysis shows that in order to meet the demands of research on many elements of climate change impacts, mitigation, and adaptation, it is imperative to strengthen the climate data gathering network. Over the last four decades, this region has been found in soil water content reduce, total precipitation and run-off, land-used change due to urbanization that are challenges for both community and government to mitigate and adaptation.

Understanding Global Climatic Shifts- A Comprehensive Review

Climate change, spanning from tropical regions to polar zones, represents a significant and persistent alteration in weather patterns, posing a grave threat to all sectors of the global economy. This review seeks to shed light on the variability that is comprehensively eroding the sustainability of various sectors. The uniqueness of this review lies in its thorough synthesis of the most recent research and insights into global climatic changes, offering a holistic perspective that covers the causes, manifestations, impacts, and potential remedies to tackle this intricate issue. While numerous studies have delved into different facets of climate change independently, this review integrates diverse viewpoints from climate science, ecology, economics, and social sciences to provide a nuanced comprehension of the multifaceted challenges of climatic shifts. Furthermore, a discussion on the intricate relationship between climate change and other global crises, such as food security, water scarcity, and social inequality, underscores the interconnected nature of these challenges and the significance of integrated solutions. Additionally, the review has furnished valuable insights into potential adaptation and mitigation strategies to confront the challenges of climate change. Recent events like the coronavirus outbreak indicate that climate change exacerbates the issue of antimicrobial resistance, posing a new threat to human health through the proliferation of resistant microorganisms. Moreover, the global tourism faces significant setbacks when climate change renders previously popular destinations less attractive. This review offers a detailed assessment of climate change mitigation and adaptation measures tailored to specific sectors mentioned above while considering the associated economic implications. Prioritizing efforts to mitigate the impacts of climate change is imperative, necessitating a global endeavor to address its catastrophic effects and safeguard global sustainability.

Dryland self-expansion enabled by land-atmosphere feedbacks.

Dryland expansion causes widespread water scarcity and biodiversity loss. Although the drying influence of global warming is well established, the role of existing drylands in their own expansion is relatively unknown. In this work, by tracking the air flowing over drylands, we show that the warming and drying of that air contributes to dryland expansion in the downwind direction. As they dry, drylands contribute less moisture and more heat to downwind humid regions, reducing precipitation and increasing atmospheric water demand, which ultimately causes their aridification. In ~40% of the land area that recently transitioned from a humid region into a dryland, self-expansion accounted for >50% of the observed aridification. Our results corroborate the urgent need for climate change mitigation measures in drylands to decelerate their own expansion.

Modelling climate change impacts on lake ice and snow demonstrates breeding habitat decline of the endangered Saimaa ringed seal

Snowdrifts on lake ice provide vital breeding habitats for the endangered Saimaa ringed seal. In this study, a lake ice model of Watershed Simulation and Forecasting System (WSFS-Ice) was developed for improved estimation of ice and snow conditions in Lake Saimaa during the pupping season of the Saimaa ringed seal. The WSFS-Ice model is based on energy balance, enabling reliable estimation of the ice cover evolution in current and future climate. In addition, a simple snowdrift model was used to simulate formation of snowdrifts, which are essential for the seals breeding success in Lake Saimaa. The model was calibrated against ice thickness, ice type and snow depth measurements. According to our results based on climate scenarios with intermediate representative concentration pathway (RCP4.5), the breeding habitat of the Saimaa ringed seal is significantly deteriorating during the twenty-first century. The mean depth of the snowdrifts is projected to decrease approximately to half from the 1981–2010 to 2070–99 period and at the same time the ice-covered period is reduced by one and a half months. During the mildest winters the ice cover is projected to melt even before the pupping season has ended. The results highlight the importance of climate change mitigation and active conservation measures to enhance seal population growth, enabling it to survive in a changing climate.

Investigating the impact of climate variables on the organic honey yield in Turkey using XGBoost machine learning.

The Turkish organic honey industry, a major player in the global market, faces challenges due to climate fluctuations. Understanding the influence of climate factors on honey production is vital for sustainable farming and economic stability. This study uses a machine learning approach with the XGBoost algorithm to analyze temperature, wind, humidity, precipitation and surface pressure over a 20-year period from 2004 to 2023. The results show that these factors significantly impact organic honey production, with temperature, wind, humidity, precipitation and surface pressure having effects of 41.20%, 26.50%, 12.47%, 11.42% and 8.41%, respectively. Sensitivity analysis reveals the model's sensitivity to even minor fluctuations in these variables. The results of this research underscore the necessity of integrating climate change mitigation and adaptation measures into agricultural policies and beekeeping practices. This study showcases the practical application of machine learning in deciphering the intricate relationship between climate change and the production of crops, emphasizing the importance of data-driven decision-making to guarantee long-term sustainability and financial stability in the sector. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Climate Change Litigation: General Perspectives and Emerging Trends

Abstract This article provides an overview of the historical and current landscape of climate change litigation, highlighting its transformative impact on public perceptions and governmental policies globally. Ground-breaking cases have compelled States to adopt more ambitious greenhouse gas reduction targets, whilst emphasising a rights-based approach to climate change mitigation and adaptation measures. In fact, strategic climate change litigation is gaining momentum and is likely to continue in volume and importance. This allows for the targeting of a wider range of actors, not least within the private sector, which in turn can pose financial risks to fossil fuel firms. The article also discusses certain emerging trends in the context of climate change litigation, as well as the potential for a shift towards personal responsibility and inter-state arbitration in 2024. It concludes that climate change litigation emerges as a powerful strategy, capable of influencing policy, ensure accountability, and drive systemic change towards climate justice for present and future generations.

Integrating Spatiotemporal Analysis of Land Transformation and Urban Growth in Peshawar Valley and Its Implications on Temperature in Response to Climate Change

Examining the interconnected dynamics of urbanization and climate change is crucial due to their implications for environmental, social, and public health systems. This study provides a comprehensive analysis of these dynamics in the Peshawar Valley, a rapidly urbanizing region in Khyber Pakhtunkhwa, Pakistan, over a 30-year period (1990–2020). A novel methodological framework integrating remote sensing, GIS techniques, and Google Earth Engine (GEE) was developed to analyze land use/land cover (LULC) changes, particularly the expansion of the built-up environment, along with the land surface temperature (LST) and heat index (HI). This framework intricately links these elements, providing a unique perspective on the environmental transformations occurring in the Peshawar Valley. Unlike previous studies that focused on individual aspects, this research offers a holistic understanding of the complex interplay between urbanization, land use changes, temperature dynamics, and heat index variations. Over three decades, urbanization expanded significantly, with built-up areas increasing from 6.35% to 14.13%. The population surged from 5.3 million to 12.6 million, coupled with significant increases in registered vehicles (from 0.171 million to 1.364 million) and operational industries (from 327 to 1155). These transitions influenced air quality and temperature dynamics, as evidenced by a highest mean LST of 30.30 °C and a maximum HI of 55.48 °C, marking a notable increase from 50.54 °C. These changes show strong positive correlations with built-up areas, population size, registered vehicles, and industrial activity. The findings highlight the urgent need for adaptive strategies, public health interventions, and sustainable practices to mitigate the environmental impacts of urbanization and climate change in the Peshawar Valley. Sustainable urban development strategies and climate change mitigation measures are crucial for ensuring a livable and resilient future for the region. This long-term analysis provides a robust foundation for future projections and policy recommendations.

Study on the Evolution of Spatial and Temporal Patterns of Carbon Emissions and Influencing Factors in China

Abstract: Industrialization has increased global carbon emissions, necessitating effective climate change mitigation measures. China, the most populous developing nation, faces the challenge of strategizing emissions to meet national carbon neutrality objectives. However, research on specific regions’ carbon emissions drivers and causal factors is limited, particularly across prefectural-level cities. This study estimates the spatial and temporal patterns of carbon emissions across China’s prefectural cities and utilizes both OLS regression and stepwise regression models to analyze the impact of various factors influencing carbon emissions in these cities. Results reveal the following: (1) The country’s overall 20-year carbon emissions continue to grow from 3020.29 Mt in 2001 to 9169.74 Mt in 2020, with an average annual growth rate of 5.71%; the eastern region has seen a gradual deceleration in emissions, whereas the western region continues to experience an increase. Carbon emissions in cities within each subregion consistently rise. (2) Carbon emissions in Chinese prefectural-level cities exhibit strong spatial autocorrelation and clustering (Z &gt; 1.96, p &lt; 0.05), with hot spots primarily in the eastern coastal areas and cold spots in the northwest to southwest regions. (3) Economic and demographic factors significantly increase carbon emissions, while climate and urbanization effects are more complex and variable. Economic growth and population increase are the most significant influencing factors, but regional variances exist in carbon emissions determinants in subregional prefectural cities. These insights provide valuable insights into national emission dynamics at the prefectural level, providing a theoretical basis for enhancing carbon emission strategies across various jurisdictions.

Conceptualizing Climate Law in India

Abstract This article highlights the importance of differentiating between environmental law and climate law in India, and, in doing so, analyses what counts as climate law in that country. It identifies three overarching approaches (trickle-down; Environmental Impact Assessment as climate law; and human rights law and climate change) that the current literature adopts to study and analyse climate law in India. We argue that none of these approaches comprehensively covers climate change mitigation measures adopted in this country. We propose an alternative approach to the analysis of climate law in India, which we call ‘administrative layering’. Accordingly, we outline a three-step process to identify and conceptualize climate law in India.