Combat Climate Change Research Articles

THE ROLE OF DIGITAL TECHNOLOGIES IN ADDRESSING TODAY'S GLOBAL CHALLENGES

The significance of the study is due to the crucial role that technology plays in solving many of the global problems faced by the modern world. The impact of technology in addressing these issues not only provides insight into current and future challenges, but also offers viable solutions to overcome them. Harnessing technology can create a more sustainable, just and prosperous world for all. The aim of the study is to conceptualise how digital technologies can be used to address the world's pressing global issues. The study focuses on international experience in tackling these global issues through the use of digital technologies by business leaders. Specifically, the research examines digital technologies as a powerful tool for addressing global challenges, while emphasising the need for careful and balanced implementation that takes into account environmental, social and economic factors. Study objectives include the following: (1) to study the role of digital technologies in solving modern global problems; (2) to identify ways to accelerate technological innovation in the field of environmental protection; and (3) to justify the responsibility of business leaders for environmental protection and solving modern global challenges. Digital technologies such as artificial intelligence, blockchain, the Internet of Things (IoT) and big data have become an integral part of modern society and have a significant impact on solving global problems such as combating climate change. Artificial intelligence, in particular, is crucial for predicting climate change, optimising the use of resources and improving the efficiency of energy production. The study highlights the experiences of leading countries that are using technology as a key element in addressing global challenges, offering innovative solutions to problems that once seemed insurmountable. The paper concludes that the potential of modern technologies is key to addressing today's global challenges, emphasising the need to integrate innovative solutions into national policies and development strategies. The study offers recommendations for further integration of digital technologies into various spheres of public life to effectively address these issues.

Analyzing trend and forecasting of temperature and rainfall in Shimla district of Himachal Pradesh, India using non-parametric and bagging REPTree machine learning approaches

The changing pattern of climate variables has caused extreme weather events and severe disasters, especially in mountainous regions. Such events have a detrimental impact on resources, environment and society. Thus, it has become imperative to examine the trends and forecasts of meteorological variables using a scientific modelling approach. This study investigates temperature and rainfall trends using the modified Mann-Kendall test and Sen's slope estimator between 1980 and 2021. A Bagging-REPTree machine learning model was utilized for forecasting temperature and rainfall trends for the next 30 years (2022–2051) to understand the temporal dynamics in Shimla district of the Indian Himalayan state. The mean absolute percentage error, mean absolute error, root mean squared error and correlation coefficient were determined to assess the effectiveness and precision of the model. The findings revealed that the frequency of intense rainfall in the district has increased during the monsoon season (June–September) from 1980 to 2021. Significant trends were found in annual rainfall, maximum, minimum and mean temperatures while rainfall during the winter, summer and post-monsoon seasons has shown a declining trend. The forecast analysis revealed a significant trend for rainfall during the monsoon season and an increasing trend in the maximum temperature has been observed during the winter and summer seasons. The analysis has provided sufficient evidence of variability and uncertainty in the behavior of meteorological variables. The outcome of the study may help in devising suitable adaptation and mitigation strategies to combat climate change in hilly regions. The methodology adopted in the study may help in the future progression of the research in different geographical regions for trend and climate forecasting.

Do ICT and green technology matter in sustainable development goals?

AbstractThe desire for development in developed and developing countries has caused difficulties in realizing environmental goals. For this reason, initiatives such as Sustainable Development Goals have been taken to balance economic growth and environmental goals. Recent research from a sustainable development perspective has shown that skilled human capital, green technology, and ICT play an essential role in the sustainable management of natural resources. In this context, the present study aims to reveal the impact of natural resource rent, economic complexity, human development, green technological innovation, and ICT on ecological footprint. It also focuses on the moderating role of green technological innovation and ICT in the relationship between natural resource rent and ecological footprint. The findings show that natural resources and ICT are the causes of environmental degradation in G7 countries, whereas economic complexity, human development, and green technological innovation improve environmental quality. It has also been discovered that ICT and green technological innovation have a moderating role in the natural resources of G7 countries. In E7 countries, natural resource rent and economic complexity increase environmental degradation, whereas human development, ICT, and green technological innovation contribute to environmental quality. Causality findings are similar in both country groups. The findings show that synergies between SDG‐4 and SDG‐13 in G7 and E7 countries can help achieve climate action sustainably and effectively. Moreover, achieving SDG 13 in E7 countries requires interactive policies to achieve SDG‐12 and SDG‐17. Achieving SDG‐8 and SDG‐17 targets in G7 countries can contribute to combating climate change.

BAs/BlueP van der Waals heterostructures for photovoltaic and thermoelectric applications

The advancement of novel energy materials, encompassing photovoltaic and thermoelectric materials, assumes paramount significance in ameliorating the energy crisis and proactively combating climate change. The BAs/BlueP van der Waals heterostructure (vdWH), characterized by its outstanding optical absorption properties, high power conversion efficiency (PCE), and excellent thermoelectric performance, offers novel insights into the advancement of materials for photonic and thermoelectric applications. We have engineered a vdWH by combining BAs and BlueP, and conducted a comprehensive investigation of its electronic, optical, and thermoelectric properties. The BAs/BlueP vdWH demonstrates excellent thermodynamic and kinetic stability with type I band alignment, facilitating rapid interlayer electron-hole recombination. The remarkable optical absorption capability within the visible and ultraviolet (UV) spectral regions, coupled with an outstanding power conversion efficiency reaching up to 22.35 % under strain, firmly establishes the potential for utilization in photovoltaic conversion applications. At 1000 K, the significant ZT value (1.25) and high thermoelectric conversion efficiency (19.45 %) provide the theoretical foundation for its application in the field of thermoelectrics.

Molecularly Woven Cationic Covalent Organic Frameworks for Highly Selective Electrocatalytic Conversion of CO2 to CO.

Coupling carbon capture with electrocatalytic carbon dioxide reduction (CO2R) to yield high-value chemicals presents an appealing avenue for combating climate change, yet achieving highly selective electrocatalysts remains a significant challenge. Herein, two molecularly woven covalent organic frameworks (COFs) are designed, namely CuCOF and CuCOF+, with copper(I)-bisphenanthroline complexes as building blocks. The metal-organic helical structure unit made the CuCOF and CuCOF+ present woven patterns, and their ordered pore structures and cationic properties enhanced their CO2 adsorption and good conductivity, which is confirmed by gas adsorption and electrochemical analysis. In the electrocatalytic CO2R measurements, CuCOF+ decorated with extra ethyl groups exhibit a main CO product with selectivity of 57.81%, outperforming the CuCOF with 42.92% CO at the same applied potential of 0.8 VRHE. After loading Pd nanoparticles, CuCOF-Pd and CuCOF+-Pd performed increased CO selectivity up to 84.97% and 95.45%, respectively. Combining the DFT theoretical calculations and experimental measurements, it is assumed that the molecularly woven cationic COF provides a catalytic microenvironment for CO2R and ensures efficient charge transfer from the electrode to the catalytic center, thereby achieving high electrocatalytic activity and selectivity. The present work significantly advances the practice of cationic COFs in real-time CO2 capture and highly selective conversion to value-added chemicals.

Characteristics and Emerging Trends in International City Negotiations

The article examines key features, main directions, and current trends in international negotiations between subnational territorial units using the example of cities. In today’s world, where the global political system is undergoing epochal change, the international activities of non-governmental and subnational actors, including their participation in international negotiations, have intensified. One of the key features of international city negotiations is that they occur mainly in a multilevel and multilateral format. This is due to the hybrid nature of cities, which are both state and non-state entities. The balance of power between cities and states in international relations depends on factors such as the degree of autonomy granted to sub-national units by the central government, as well as the level of economic and political influence held by cities. Sometimes, the position of a city may differ significantly from that of the state it belongs to. At the international level, there are several specialized institutions and mechanisms that allow cities to coordinate their positions and develop common approaches. These include the World Association of United Cities and Local Authorities, the World Assembly of Local and Regional Authorities, and the Metropolis Association. The main topics of today’s multilateral negotiations between cities include combating climate change, ensuring protection from natural disasters, promoting the rights of migrants and other displaced people, and fostering innovation in urban environment and governance. In contrast, bilateral negotiations between cities, based on the institution of sister cities, focus more on the humanitarian, scientific, educational, and cultural spheres of cooperation. Finally, current trends in international city negotiations include the increasing use of digital technologies and the geographical reorientation of Russian cities’ partnerships towards the countries of the “global majority.”

Breaking the CO2 Gridlock: Can Renewables Lead the Way for the OECD?

The use of low-carbon energy in power grids is essential for minimizing negative effects on the environment. Energy consumption causes environmental damage to the OECD’s economy. This study aims to investigate the effect of energy consumption, population, and GDP on CO2 emissions using panel data from 17 OECD countries over the period 2000–2023. We use regression approaches, such as partial least squares and principal components, to study the effects of GDP, urban and total population, oil and nuclear use, renewable energy, and industrialization on CO2 emissions. The regression process in this study reduces the data to a two-dimensional representation using a stochastic model and estimation techniques. The findings of this empirical investigation indicate that the United States, Canada, France, Germany, Italy, Korea, Mexico, and the United Kingdom exhibit higher levels of primary energy consumption in comparison to value-added sectors, renewable–geothermal energy, and nuclear energy. We determined the effects of CO2 emissions, GDP, and energy consumption by considering these as the most significant elements. This has made it possible to reduce CO2 emissions by focusing one’s attention and energy on the development of novel technologies, the use of renewable energy sources, and the execution of strategic plans. Attracting increasing attention are technological shifts that deliver enormous quantities of clean energy to combat climate change. Findings from this study can help environmentalists and policymakers better understand the role of structural change and energy consumption processes in the globalization process.

Perceptions, Tensions, and Contradictions in Timber Construction: Insights from End-Users in a Chilean Forest City

The study addresses the underutilisation of wood in construction in Chile, particularly given the country’s robust forestry sector. The research investigates perceptions, tensions, and contradictions among end-users regarding timber construction in Valdivia, a city with a mixed forestry industry. Methods included a comprehensive survey of 96 households across various socioeconomic clusters, utilising descriptive and exploratory statistical analyses. Key findings reveal persistent negative perceptions about wood’s durability, fire resistance, and maintenance costs. However, positive aspects, such as lower construction costs and adequate thermal comfort, were also noted. Surprisingly, concerns were raised about wood’s environmental impact, including deforestation and its role in combating climate change, contrasting with the material’s known ecological benefits. The study concludes that these perceptions are deeply influenced by ideological and sociopolitical factors, suggesting that mere marketing strategies may not suffice to alter public opinion. Instead, a collaborative effort involving public policy, industry advancements, and transparent scientific communication is essential to promote the benefits of timber construction and address the entrenched biases.

The Application and Evaluation of the LMDI Method in Building Carbon Emissions Analysis: A Comprehensive Review

The Logarithmic Mean Divisia Index (LMDI) method is widely applied in research on carbon emissions, urban energy consumption, and the building sector, and is useful for theoretical research and evaluation. The approach is especially beneficial for combating climate change and encouraging energy transitions. During the method’s development, there are opportunities to develop advanced formulas to improve the accuracy of studies, as indicated by past research, that have yet to be fully explored through experimentation. This study reviews previous research on the LMDI method in the context of building carbon emissions, offering a comprehensive overview of its application. It summarizes the technical foundations, applications, and evaluations of the LMDI method and analyzes the major research trends and common calculation methods used in the past 25 years in the LMDI-related field. Moreover, it reviews the use of the LMDI in the building sector, urban energy, and carbon emissions and discusses other methods, such as the Generalized Divisia Index Method (GDIM), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Interpretive Structural Modeling (ISM) techniques. This study explores and compares the advantages and disadvantages of these methods and their use in the building sector to the LMDI. Finally, this paper concludes by highlighting future possibilities of the LMDI, suggesting how the LMDI can be integrated with other models for more comprehensive analysis. However, in current research, there is still a lack of an extensive study of the driving factors in low-carbon city development. The previous related studies often focused on single factors or specific domains without an interdisciplinary understanding of the interactions between factors. Moreover, traditional decomposition methods, such as the LMDI, face challenges in handling large-scale data and highly depend on data quality. Together with the estimation of kernel density and spatial correlation analysis, the enhanced LMDI method overcomes these drawbacks by offering a more comprehensive review of the drivers of energy usage and carbon emissions. Integrating machine learning and big data technologies can enhance data-processing capabilities and analytical accuracy, offering scientific policy recommendations and practical tools for low-carbon city development. Through particular case studies, this paper indicates the effectiveness of these approaches and proposes measures that include optimizing building design, enhancing energy efficiency, and refining energy-management procedures. These efforts aim to promote smart cities and achieve sustainable development goals.

A Sustainable Future : The Importance and the Development of Sustainable Finance In the 21st Century

The environmental problems that have emerged along with rapidly increasing global warming in recent years have made the concept of sustainability an important issue in the world in general. This fact has been largely effective in increasing the sensitivity of businesses and leading corporations to the environmental problems. This situation has led businesses to implement environmental friendly policies and invest in these areas, both interms of efficient use of natural resources and minimizing the damage to the environment. With the increasing global warming, climate change has recently become one of the most important problems in the world, and many countries have started to make efforts to reduce the risk of climate change. The inadequacy of environemental measures taken so far has necessitated the search for solutions in different areas regarding this issue. In this sense, financial institutions also contribute to climate awareness by following environmental policies in their activities and developing products that prioritize the environment. The concept of sustainable finance has led to the development of various financial products and to the development of financing projects aimed at protecting the environment. While the concept of sustainable finance is perceived as the responsibility of public authorities, the private sector has also been included in the process with the Sustainable Development Goals in the UN 2030 Agenda. There is no doubt that sustainable banking and finance practices, especially the implementation of sustainability practices by banks and other corporations in developing countries will contribute to the development of these countries considerably. In this study, it is aimed to draw attention to the global climate crisis, to emphasize the relationship between finance and the environment, and to contribute to the increase of applications in this field in the world by introducing green financing tools. One of the important functions of sustainable finance against the climate crisis is the evolution of companies funded within the scope of ESG criteria into a production process that tends to be sensitive to carbon emissions, as well as acquiring social and governance sensitivity. In this way, an economic process can be carried out on the axis of environmental and social awareness. In addition to combating climate change, it can be an important supporter in achieving the Sustainable Development Goals.

Analysis of the drivers and barriers influencing artificial intelligence for tackling climate change challenges

PurposeFacilities management (FM) organizations are pivotal in enhancing the resilience of buildings against climate change impacts. While existing research delves into the adoption of digital technologies by FM organizations, there exists a gap regarding the specific utilization of artificial intelligence (AI) to address climate challenges. This study aims to investigate the drivers and barriers influencing the adoption and utilization of AI by South African FM organizations in mitigating climate change challenges.Design/methodology/approachThis study focuses on South Africa, a developing nation grappling with climate change’s ramifications on its infrastructure. Through a combination of systematic literature review and an online questionnaire survey, data was collected from representatives of 85 professionally registered FM organizations in South Africa. Analysis methods employed include content analysis, Relative Importance Index (RII), and Total Interpretative Structural Modeling (TISM).FindingsThe findings reveal that regulatory compliance and a responsible supply chain serve as critical drivers for AI adoption among South African FM organizations. Conversely, policy constraints and South Africa’s energy crisis emerge as major barriers to AI adoption in combating climate change challenges within the FM sector.Originality/valueThis study contributes to existing knowledge by bridging the gap in understanding how AI technologies are utilized by FM organizations to address climate challenges, particularly in the context of a developing nation like South Africa. The research findings aim to inform policymakers on fostering a conducive environment for FM organizations to harness AI in fostering climate resilience in built assets.

Factors influencing farmers' intention to participate in the voluntary carbon market: An extended theory of planned behavior

Carbon sequestration in agricultural soils is essential for sustainable agriculture, contributing to the achievement of the Sustainable Development Goals and combating climate change. The Voluntary Carbon Market (VCM), designed to encourage farmers to implement sequestration practices, is a recent innovation in Europe, in contrast to the well-established American system. Consequently, there is limited understanding of farmers' intentions to participate. The study analyzes farmers' willingness to participate in VCM and the influencing factors through the Extended Theory of Planned Behavior (ETPB). For this purpose, data were collected from 241 Italian farmers located in the Sicily region and the partial least squares structural equation model (PLS-SEM) was applied. The results show that Attitude, Perceived Behavioral Control and Knowledge of VCM have a statistically significant influence on farmers' intention to participate in VCM. In contrast, Subjective Norms and Perceived Environmental Risk do not have a statistically significant influence. Our findings suggest that farmers' intention is strongly influenced by confidence in their capabilities and knowledge of the topic. This should guide policymakers and practitioners to offer extension services and technical assistance, helping farmers understand the potential of the VCM. Indeed, limited knowledge is a major barrier to participation in this initiative.

Spatial effects of renewable and fossil energy consumption on the ecological footprint for the EU Countries.

This study examines the spillover of pollution among the 26 European Union (EU) countries from 1995 to 2020. In order to quantify pollution spillovers among the countries, we estimated the Environmental Kuznets Curve (EKC) using spatial econometric methods. Our research is unique in that it investigates ecological footprint spillovers for EU countries. This study also considers the direct and indirect effects of renewable and fossil energy consumption and globalization on environmental degradation in EU countries. The empirical results favor the validity of the EKC hypothesis. Our results support the presence of positive and significant ecological footprint spillovers among EU countries. Our spatial estimates also reveal the significant spillover impact of explanatory variables on the ecological footprint. The ecological footprint of the local country is declining owing to the consumption of renewable energy in neighboring countries. Furthermore, the fossil energy consumption of the local and neighboring countries has a positive impact on the ecological footprint. Evidence obtained from our spatial estimates provides useful insights to policymakers in developing appropriate environmental policies to combat climate change.

A Co-production system of cement and methanol: Unveiling its advancements and potential

Both the cement and methanol sectors face increasing pressure to reduce their carbon emissions to combat climate change. Coupling the production process can provide economic and environmental benefits when implementing breakthrough technologies in these industries. The advantages and application potential of the co-production system need to be assessed quantitatively in long-term decarbonization pathways. This study proposes a co-production system of cement and methanol that capitalizes on strong complementarity through bidirectional material flow. Multi-regional planning models are established to evaluate the spatiotemporal deployment of low-carbon technologies, including coupling technologies. The results demonstrate that the co-production system can achieve a 6.6% higher emissions reduction and a 21.2 % lower production cost of clinker by 2060 compared to implementing breakthrough technologies separately. The co-production routes may be widely distributed across China by 2060, accounting for 24.1 % of clinker output and 54.7 % of methanol output. Introducing coupling technologies can influence the industrial layout and trade patterns of China's cement and methanol sectors, carrying policy implications for the deployment of low-carbon technologies.

Is climate change awareness a predictor of anxiety among nursing students?: A cross-sectional study

BackgroundDetermining the climate change anxiety and awareness of student nurses, who will provide health services in various parts of the world after the borders are removed, is important in combating climate change. ObjectivesThe study aims to assess whether nursing students' climate change awareness is a predictor of climate change anxiety. DesignThis research adopts a descriptive cross-sectional study design. ParticipantsThe population of the study consisted of a total of 562 students studying in the nursing department of a state university. 419 students were included in study. MethodsData were gathered from 419 students enrolled in the nursing department of a university during the fall semester of 2022–2023, employing online questionnaires via Google Forms from January to March 2023. The research instrument comprised three parts: a Descriptive Information Form developed in line with the literature, the Global Climate Change Awareness Scale, and the Climate Change Anxiety Scale. SPSS 20.0 software was used for data analysis. The study obtained ethical committee approval, institutional permissions, and participant consent. ResultsFindings indicated that nursing students' mean Global Climate Change Awareness Scale total score was 59.06 ± 15.78, Climate Change Anxiety Scale total score was determined to be 21.27 ± 8.75. A moderate positive relationship was identified between global climate change awareness and climate change anxiety levels among nursing students (r = 0.304, p < 0.05). Furthermore, the study revealed that the participants' awareness of global climate change served as a predictor for their anxiety levels. ConclusionThe climate change awareness of nursing students significantly influences their levels of anxiety related to climate change. Integrating climate change awareness into nursing education is quite important and necessary. This can empower future nurses to be more prepared and effective in a changing world.

Green entrepreneurship: Opportunities and challenges for the transition to a circular economy in Togo, West Africa

The traditional linear economic model, characterized by extraction, production, consumption, and waste disposal, has increasingly exposed its limitations, particularly in the depletion of natural resources and the acceleration of global warming, which are critical global issues. These challenges inherent in the linear economy have prompted a shift towards a circular economy. This study analyzes the opportunities and challenges for transitioning to a circular economy through green entrepreneurship among 29 environmentally friendly entrepreneurs in Togo, West Africa. The descriptive analysis of the results revealed that green entrepreneurs are mainly motivated by economic factors, such as job creation and business opportunities, which take precedence over environmental motivations. However, they face significant challenges, including a lack of access to appropriate financing and complex administrative procedures that affect their growth. It is essential to develop themselves, provide specific support by alleviating bureaucratic obstacles to access to finance, and meet economic and environmental goals from green entrepreneurship. In addition, it's important to advocate for pro-environmental behavior among the general public and to support research and development to increase understanding of the advantages of promoting environmentally friendly entrepreneurship for sustainable development while combating climate change. Mainstreaming gender into circular economy policies design and implementation for sustainable development is crucial due to the low representativeness of women in green entrepreneurship. These measures will strengthen Togo's economic resilience while enabling the transition to a circular economy, thus aligning financial objectives with environmental preservation in pursuing green entrepreneurship.

Technology Focus: Offshore Facilities (September 2024)

Offshore wind power involves generating electricity from wind farms located at sea. Because wind speeds are generally higher offshore than on land, these farms produce more electricity for the same amount of installed capacity. Both wind and solar energy are renewable and do not emit carbon, which helps reduce dependence on fossil fuels such as oil and gas. The papers synopsized in this year’s Offshore Facilities feature cover a breadth of related subjects that will be critical to the future of the industry. Automation in the offshore oil and gas industry makes production safer, faster, and more efficient. It reduces human error, improves quality control, and allows real-time monitoring of operations. Machine learning improves offshore industries by enhancing safety, efficiency, and sustainability It tracks and predicts environmental changes, such as oil spills or marine life patterns, aiding in better environmental management and response. Remotely operated vehicles are used in offshore operations to inspect, maintain, and repair underwater infrastructure; the offshore industry uses 3D video imaging technology to provide detailed real-time images of the underwater environment. Corrosion in offshore environments occurs because of factors such as seawater, sea salts, temperature, salinity, and moisture. It is crucial to monitor corrosion because it can lead to major structural failures. Hydrogen can be produced offshore using renewable energy sources such as wind and solar, which do not emit greenhouse gases and help combat climate change. Supply-chain logistics boost efficiency by cutting costs, removing unnecessary steps, and speeding up product delivery. An efficient supply chain can lead to higher revenue, lower operational costs, and better overall performance. Decommissioning is the final stage of an oil or gas project and involves significant technical, economic, social, and environmental challenges. It is a lengthy, costly, and complex process that must be carefully planned and managed to avoid serious problems. Several ideas have come to the surface that show innovative ways to repurpose a decommissioned platform or ways to cut the cost of decommissioning. Recommended additional reading at OnePetro: www.onepetro.org. SPE 217706 Dynamic Simulation of Riser-Gas Handling With a Fixed-Choke Constant Outflow by Zhaoguang Yuan, SLB, et al. OTC 35092 Reducing Carbon Footprint by Using Fiber-Reinforced Polymers in FPSOs by S. Eves, NOV, et al. OTC 35393 Challenges and Approaches to Solutions for Green Decommissioning and Recycling of Offshore Facilities by Carlos Alberto Machado, American Bureau of Shipping, et al.

High-resolution Standardized Precipitation Evapotranspiration Index (SPEI) reveals trends in drought and vegetation water availability in China

Understanding vegetation water availability can be important for managing vegetation and combating climate change. Changes in vegetation water availability throughout China remains poorly understood, especially at a high spatial resolution. Standardized Precipitation Evapotranspiration Index (SPEI) is an ideal water availability index for assessing the spatiotemporal characteristics of drought and investigating the vegetation-water availability relationship. However, no high-resolution and long-term SPEI datasets over China are available. To fill this gap, we developed a new model based on machine learning to obtain high-resolution (1 km) SPEI data by combining climate variables with topographical and geographical features. Here, we analyzed the long-term drought over the past century (1901–2020) and vegetation-water availability relationship in the past two decades (2000–2020). The century-long drought trend analyses indicated an overall drying trend across China with increasing drought frequency, duration, and severity during the past century. We found that drought events in 1901–1961 showed a larger increase than that in 1961–2020, with the Tibetan Plateau showing a significant drying trend during 1901–1960 but a wetting trend during 1961–2020. There were 13.90% and 28.21% of vegetation in China showing water deficit and water surplus respectively during 2000–2020. The water deficit area significantly shrank from 2000 to 2020 across China, which is dominated by the significant decrease in water deficit areas in South China. Among temperature, precipitation, and vegetation abundance (LAI), temperature is the most important factor for the vegetation-water availability dynamics in China over the past two decades, with high temperature contributing to water deficit. Our findings are important for water and vegetation management under a warming climate.

Assessing China's energy transition pathway: Insights from the synergistic effects of key drivers

China's energy transition is a pivotal component of global efforts to combat climate change. This study identifies the synergistic effects of key factors driving this transition, including social-technology-economic, policy, investment, governance indicators. Asymmetric nexus impacts are explored by using quantile-on-quantile regression (QQR) method. Further, the synergistic effects of key drivers on China's energy transition are examined by model 1–4. The findings show that reconciling the tradeoffs of reducing coal emissions and promoting clean energy are crucial for China's energy transition. Urban growth, environmental taxes, financial development, and strong environmental governance and institutional quality significantly support these efforts, but show different synergistic effects scenarios. These findings also reinforce the need for a more inclusive response to China's energy sustainability challenges, in particular, coordinated policies and strategies in coal-reliant industrial sectors are critical for a successful energy transition.

Carbon Border Adjustment Mechanism (CBAM) Implementation on Reducing Emission in the ASEAN Energy Sector

Abstract In the context of global efforts to combat climate change and transition towards a low-carbon economy, the European Union (EU) has introduced the Carbon Border Adjustment Mechanism (CBAM) as part of its ambitious Green Deal. This mechanism aims to address carbon leakage from high-emitting industries and ensure fair conditions for European industries. The ASEAN region, as highlighted in the 7th ASEAN Energy Outlook (AEO7) study, is projected to experience a substantial increase in greenhouse gas (GHG) emissions, reaching 6,704 Mt CO2-eq by 2050 compared to a baseline scenario of 1,815 Mt CO2-eq in 2020. Consequently, ASEAN has recognized the urgency to earnestly reduce its emissions in response to the global push for carbon neutrality. The implementation of CBAM by the EU has prompted many countries, including ASEAN Member States (AMS) exporting goods to the EU and beyond, to consider the adoption of CBAM policies. This study examines the potential implications of CBAM for the emission reduction in high-emitting industries in ASEAN (such as cement, iron and steel, aluminum, fertilizers, and electricity generation). The findings indicate that the implementation of CBAM may result in higher product prices for these industries, as they will be required to account for the climate footprint of their manufacturing activities through additional fees. However, it also presents an opportunity for emission reductions within these industries by incentivizing the adoption of renewable energy sources to mitigate their carbon footprint during manufacturing processes. To effectively respond to the implementation of CBAM, the region should adopt three key strategies: 1) active participation in and implementation of carbon pricing mechanisms, 2) increased investments in low carbon technologies, and 3) establishment of strategic partnerships to enhance trade relations between the EU and ASEAN.