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Green innovation is important and beneficial for the green development of enterprises. The development of digital technology could improve the asymmetry of information and affect the enterprise's financing modes. Currently, a definitive conclusion about the relationship between the digital transformation and green technology innovation has not reached. Additionally, studies have not yet fully explored the impact pathways of corporate digital transformation on green innovation through corporate financing modes. To fill this void, this study collected data of Chinese A-share listed companies from 2010 to 2020. The empirical analysis results showed that digital transformation significantly enhanced enterprises' green innovation abilities. Furthermore, mediating models were utilized to explore how enterprise financing modes mediate the impact of digital transformation on the enterprise green innovation. Results indicated that through internal financing and bank loans as "bridges", digital transformation promoted enterprise green innovation. However, digital transformation did not have a significant impact on enterprise green innovation through venture capital. Moreover, heterogeneity analyses revealed significant differences among different groups of enterprises. This study expands the research field related to digital transformation and enterprise green innovation by providing empirical evidence to uncover the impact of digital transformation on enterprise green innovation. Findings of this study contribute not only to enterprise managerial decision-makers to better leverage digital transformation through corporate financing to accelerate green innovation, but also to government policymakers to design policies to stimulate enterprise green innovation. • Firstly, our paper empirically examines and validates the impact of digital transformation on enterprise green innovation again by using empirical data of biggest development counties, i.e., China. • Secondly, our paper combines enterprise digital transformation, financing modes, and green innovation within the same framework to study the "bridge" role of financing modes between digital transformation and enterprise green innovation. • Thirdly, Thirdly, heterogeneity analyses were carried out, the results of the different enterprises groups are significant different. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

The impact investing literature largely focuses on private equity investing and overlooks the investments made through debt financing that actually dominate the market. To address this research gap, this paper investigates whether impact financing is associated with financial benefits. By using COVID-19 as an exogenous shock to China's stock market, this paper applies fixed effects panel data analysis with a difference-in-differences research design to provide robust empirical outcomes. The results reveal those financial institutions that better integrated environmental impacts into their financing process experienced positive stock return changes in response to the shock. This study answers the question of how well an impact scales. The findings suggest that impact financing is an effective model, as the impacts incorporated in the debt can be scaled up compared to impact investing funds with low volumes. Impact financing has enormous potential for financial institutions to engage in the green transition since they can derive pecuniary utility while delivering environmental impacts. The revelation of financial benefits also contributes to overcoming the lack of knowledge about impact financing and helps to remove the barriers that advance industry growth. • This paper studies whether impact financing is associated with financial benefits. • Financial firms that better integrate environmental impact in financing have positive stock return changes during COVID-19. • Financial firms can derive pecuniary utility from pursuing impact financing. • The findings suggest that impact financing can be an effective model to bring impact to a substantial scale. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

Enhancing the green economy efficiency (GEE) is crucial for building a sustainable economy. How can the rapidly advancing digital transformation contribute to this process? The paper empirically examines the direct and spatial spillover effects of digital transformation on cities' GEE in China. This study utilizes the National E-commerce Pilot City (NEPC) policy as a quasi-natural experiment of regional digital transformation and employs the staggered difference-in-differences (DID) method with heterogeneous effects. The findings reveal that (i) implementing the NEPC policy significantly increases urban GEE by 2.6%, corresponding to a 16% increase in the mean of GEE. This effect is particularly pronounced in non-resource-based cities and cities with high Internet penetration. (ii) The mechanism test shows that the pilot policy positively affects GEE by promoting green structural transformation, enhancing green innovation, and strengthening public environmental concerns. (iii) The study highlights a positive spatial spillover effect of the NEPC policy on the GEE of nonpilot cities. (iv) The adoption of the NEPC plays a pivotal role in advancing energy use and carbon emission efficiency. This paper expands the existing knowledge on the green development effects of the digital economy while offering valuable policy insights for building an "Inclusive Green Economy". [Display omitted] • The staggered differences-in-differences method is employed to examine the direct and spatial spillover effects of NEPC on cities' GEE in China. • This paper uses NEPC as a quasi-experiment for digital transformation. • NEPC significantly improves green economic efficiency by 2.6%. • Green structural transformation, innovation, and environmental concerns are main channels. • Positive spillover effect of NEPC on green economy efficiency in non-pilot cities. [ABSTRACT FROM AUTHOR]

Building a marine ecological security shelter (MESS) has become the main strategy to adapt marine ecological threats in China. As China's marine policy lacks a robust framework document, it is necessary to consider whether the policy system can effectively support the construction of MESS. However, the linkage between the construction measures of MESS and related policies is not clear. Therefore, the purpose of this paper is to clarify the concept of MESS and its connection with policy, by adopting the policy content analysis method to analyze the evolution process of MESS-related policy system. The legislative shortcomings and implementation obstacles of the MESS-related policy system are then summarized and discussed. The results show that from 1981 to 2021 the MESS-related policy system has been continuously improved. However, the policy system's support and guarantee capacity for building MESS still needs to be improved. (1) Due to the lack of basic laws and special laws, the coordination among governance subjects and among policies lacks legislative guarantee. (2) The construction of MESS continues the inter-regional and inter-department administrative barriers in collaborative governance of marine environment. To establish an effective collaborative governance model, it is essential to improve the governance structure and mechanism. (3) The government-led governance pattern faces the problem of mechanism failure. The command and control instrument accounts for more than 82%, and the public and enterprises lack strong policy guarantees to participate in marine governance. (4) The policy system's adaptability to emerging threats must be improved. Marine policies rarely involve emerging threats such as climate change and new pollutants. Meanwhile, the real-time supervision and monitoring mechanism is weak. The real-time supervision is only accounting for about 10%. Generally speaking, as a complex and long-term system engineering, the construction of MESS will inevitably encounter contradictions in politics, culture, and economy. China should deepen the construction of marine ecological civilization and form a governance concept based on ecosystems. Overall, this paper helps to understand the internal connection between MESS and policy comprehensively and provides a new perspective for improving China's marine governance capacity. [Display omitted] • We conduct a content analysis of 403 Chinese marine ecological security policies. • The policy instruments are mainly regulatory but lack flexibility and precision. • The policy implementation lacks assurance for poor governance mechanisms. • The policy system lacks adaptiveness to climate change and new pollutants. • The study provides ideas to enhance climate change adaptation of marine governance. [ABSTRACT FROM AUTHOR]

The proposal of the dual carbon goal and the blue economy in China has sparked a keen interest in carbon emissions reduction from sewage treatment. Carbon accounting in urban sewage plants serves as the foundation for carbon emission reduction in sewage treatment. This paper re-evaluated carbon accounting in the operational processes for urban sewage treatment plants to develop a novel carbon emission evaluation model for anaerobic-anoxic-oxic treatment plants. The results show that the carbon emissions generated by non-carbon dioxide gases far exceed the carbon emissions from carbon dioxide alone. Moreover, the recycling of sewage leads to carbon emissions reduction that offsets the carbon emissions generated during the operation of the sewage plant. Also, the carbon emissions generated by sewage treatment plants are lower than those generated by untreated sewage. The findings and insights provided in this paper provide valuable references for carbon accounting and the implementation of low-carbon practices in urban sewage treatment plants. [Display omitted] • A novel carbon emission evaluation model for AAO treatment plants was proposed. • Mechanical processes generated higher carbon emissions than energy and chemicals. • The determination of direct and indirect emissions of CO 2 from sewage plants. • Sewage recycling can offset carbon emissions from the operation of sewage plants. [ABSTRACT FROM AUTHOR]

Corporate water performance and sustainable development are currently vital focus areas for scholars. Therefore, this paper investigates the experience of Chief Executive Officers (CEOs) with water shortage influences corporate water performance by focusing on listed companies in water-intensive and high-water-risk industries in China between 2014 and 2019. This paper manually collected information relative to the cities and provinces where CEOs grew up to evaluate their early exposure to water shortages. Furthermore, this paper develops an evaluation scale, based on the Enterprise Water Conservation Evaluation Guide (GB/T 7119-2006), to compute the enterprise water management practices scores. These results will constitute the enterprise water performance evaluation score. Moreover, this paper focuses on CEOs who have experienced water resource shortages through a positive impact on the water resource performance of their companies. As for the findings, they demonstrate that CEOs who grew up in regions with higher water scarcity have a more pronounced positive effect on their water shortage experience through corporate water performance. Furthermore, CEO power intensity positively moderates the relationship between the CEO's water shortage experience and corporate water resource performance. Further investigation reveals generational differences in the impact of CEO water shortage experience on company water performance. CEOs, who grew up during periods with a higher incidence of droughts, demonstrate a more significant promoting effect on corporate water performance. To sum up, this study expands the understanding of factors influencing corporate water resource performance and deepens the knowledge of the early life experiences of CEOs. • We construct a set of scales to measure corporate water performance. • We explore the relationship between CEO water shortage experience and corporate water resource performance. • CEO water shortage experience has a positive effect on corporate water performance. • CEO power intensity plays a positive moderating role. [ABSTRACT FROM AUTHOR]

China's double carbon target aims to improve human well-being and sustainable development. Energy transformation welfare performance (ETWP) is the efficiency of energy transition (ET) in enhancing human well-being. ETWP considers both human well-being and sustainable development. Research on its driving force is helpful in achieving the double carbon goal. Thus, this paper used Logarithmic Mean Divisia Index Model, Fixed Panel Regression Model and Grey Relational Analysis Model to analyze China's ETWP from 2006 to 2022 and predicted ETWP of 31 provinces from 2023 to 2030. The results showed that: (1) ETWP had two rising periods in 2006–2014 and 2015–2022. (2) The government's rationalization policy on energy and environment and technological innovation ability were fundamental driving forces for improving ETWP. (3) There were obvious spatial and temporal distinctions in ETWP, and it would bring out different degrees in most areas. Thus, ET should be promoted by improving the ecological environment and resource utilization efficiency; The importance of the role of scientific and technological innovation and policies should be focused on in promoting ETWP; ET policies based on local developments should be formulated and the energy structure should be changed. Figure Geographical map of ETWP from 2014 to 2022. [Display omitted] • The concept of energy transition welfare performance was defined and accounted for. • The driving factors of energy transition welfare performance were assessed. • The spatial differences of energy transition welfare performance was studied. [ABSTRACT FROM AUTHOR]

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading. • We investigate the nexus between transportation facilities and green development. • We employ the double machine learning model to perform quasi-merge regression. • We affirm this positive effect from the micro enterprise level. • We verify the mediation channels of service industry agglomeration and green innovation level. [ABSTRACT FROM AUTHOR]

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO 2 e) in 2000 to 77.568 Mt CO 2 e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively. • GHG emissions from livestock in cities of the YRB continued to rise from 2000 to 2021. • GHG emissions per unit of GDP of livestock shown a downward trend. • Analyzing parameter of factors from spatiotemporal aspect by using GTWR model. • Probability of GHG emission transfer in urban livestock was spatially dependent. [ABSTRACT FROM AUTHOR]

Based on the panel data of 22 inland provinces in China from 2010 to 2020, this study constructs and measures the level of rural ecological environment in China. The impact of the financial performance of green-listed companies on the rural ecological environment and its moderating and threshold effects are analyzed. The following conclusions are drawn: (1) During 2010–2020, China's rural ecological environment shows a trend of "fluctuating-decreasing-rising" with significant regional non-equilibrium characteristics. (2) The financial performance of green-listed companies has a significantly negative impact on rural ecology. This negative impact has a crucial heterogeneous feature, with a more significant negative impact in areas with a higher rural ecological environment index and less substantial performance in regions with a lower rural ecological environment index. (3) There is a significant positive moderating effect of education level and digitalization on the relationship between the financial performance of green-listed companies on the level of rural ecological development. As moderating variables, the digitalization and education level weakens the negative impact of green-listed companies' performance on the ecological environment. The positive impact of the financial performance of green-listed companies on the development level of the rural ecological environment is more vital in areas with higher per capita education levels and digitalization in rural areas. (4) There is a significant threshold effect on the financial performance of green-listed companies on the level of rural ecological development. When the financial performance of green-listed companies exceeds a particular threshold value, the impact of the financial performance of green-listed companies on the development level of the rural ecological environment is significantly positive. Based on the above findings, this paper puts forward corresponding countermeasure suggestions. • From 2010 to 2020, the development level of China's rural ecological environment showed a trend of "fluctuating-decreasing-rising," with noticeable regional differences. • The income level of green-listed companies has a negative impact on the rural ecological environment, and there is regional heterogeneity in this impact. • The rural education and digitalization levels have a positive moderating effect on the ecological environment. • It is found that the impact of green-listed companies on the ecological environment has a threshold effect. [ABSTRACT FROM AUTHOR]

The increasing volume of electronic waste (e-waste) poses significant challenges for efficient collection in China. Despite many measures were taken over the past two decades, the e-waste collection rate was still not high. To this end, the Chinese government issued a new policy, the collection target responsibility (CTR) policy. Under the CTR policy, however, it is essential for participants to know how to share the responsibility of collection and how much reasonable targets are set to ensure the efficiency of the collection models. Therefore, the purpose of this paper is to explore the determination of optimal collection targets and the corresponding performance from the perspective of responsibility sharing to support the successful implementation of the CTR. Firstly, the study focuses on participants including the government, manufacturers, and recyclers, and develops three CTR models, independent collection model, government cost-sharing model, and enterprise collaboration model. Secondly, collection target equations for each model are established by employing dynamic differential game analysis, and corresponding collection performances are derived. Thirdly, through practical case simulations, the evolution of collection performance is dynamically analyzed to determine reasonable collection targets for the three models, as 23.8%, 32.3%, and 34.4%, respectively. The findings highlight the effectiveness of CTR in improving e-waste collection targets and performance, with the highest levels attained when the collection responsibilities are shared by government cost-sharing and enterprise collaboration. This study provides theoretical support for setting reasonable collection targets under CTR, and assists decision-makers in developing targeted CTR implementation measures. • The CTR model frameworks involving the main participants are developed. • Three CTR models are constructed from the perspective of shared responsibility. • The collection target for each CTR model is analyzed and determined. • The performances of CTR models are analyzed and compared. • Differences in the CTR models from cost-sharing and enterprises collaboration are observed. [ABSTRACT FROM AUTHOR]

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening—energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process. • Green innovation resilience can promote energy efficiency. • Early digital economy development can lead to resource grabbing and technology constraints effects. • Pursuing the policy orientation of "digital greening—energy efficient". [ABSTRACT FROM AUTHOR]

Spatial misallocation of resource elements impedes the coordination in regional co-benefit in carbon emission and pollution reduction. Guided by scope economy principles, this study aims to quantifies co-benefits and explores spatial variation patterns to facilitate mutual synergy. The findings offer valuable insights for identifying optimal focus points and shaping targeted collaborative policies. Based on the multi-source provincial panel data spanning 2000 to 2021, this paper quantitatively assesses the co-benefit through the lens of marginal abatement cost. Then, the Dagum Gini coefficient was employed to investigate the disparities at the spatial level. Additionally, geographical detector is introduced to analyze the source of disparities at the factor level. Results indicate: (1) Under joint reduction, the marginal abatement cost reduces by 57.86% and 79.97% respectively, with an overall 68.77% increase in co-benefit fluctuation. (2) Provinces with low co-benefit significantly decreased after 2007, while provinces with high co-benefit concentrated in the northwest, southwest, and east. (3) Overall disparities decreased, east-central regions hold the lowest spatial disparities in co-benefit and east-west hold the most; intragroup differences and supervariable density primarily contributes to the disparity. (4) FDI significantly influence the co-benefit over the past two decades, with spatial disparities influenced by both endogenous and exogenous factors across development stages. • Joint reduction significantly lowers the marginal abatement cost and enhanced co-benefit. • East-central regions holds the lowest spatial disparity in co-benefit and east-west holds the most. • Intragroup disparities and supervariable density primarily contributed to spatial disparity. • The interplay between internal and external factors increasingly influences spatial disparities. [ABSTRACT FROM AUTHOR]

Numerous studies have discussed the economic impacts of the COVID-19 pandemic in recent years. However, the effectiveness and trade-offs of diverse countermeasures still need to be investigated, particularly under the long-term goal of low-carbon transition, which is crucial for understanding the potential impacts of the future public health emergency (PHE) related economic crisis. Given that China still faces big pressures from the potential PHE and carbon neutrality, this paper assesses the effectiveness of policy instruments in restoring the economy and advancing green development after the PHE using the Dynamic Stochastic General Equilibrium framework. Our findings reveal that the PHE imposes more constraints on the economy because of the decrease in productivity on the supply side and in consumption on the demand side. Compared to the other counterparts, the mixed stimulus can overcome the adverse impacts of the PHE while contributing to carbon reduction. Furthermore, all types of low-carbon policies investigated in this study can contribute to carbon reduction at the expense of economic growth. Meanwhile, the carbon tax realizes the target of reducing emissions with the smallest negative impact on economic growth. Thus, we suggest adopting the carbon tax policy as the most effective low-carbon measure to address uncertainties associated with the PHE. • This study explores pathways for advancing economic recovery and green development after the public health emergency. • We develop a scenario-based dynamic stochastic general equilibrium (DSGE) model. • We characterize public health emergency shocks from a supply and demand perspective. • The model introduces different carbon abatement mechanisms. [ABSTRACT FROM AUTHOR]

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change. • Extreme heat increases the likelihood of residents purchasing health insurance. • Each additional day of extreme heat boosts health insurance purchases by 0.3%. • This effect varies among different populations. • Mechanistic analyses indicate extreme heat impacting physical and mental health. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon trading prices using deep learning models can help enterprises understand the operational mechanisms and regulations of the carbon market. This is crucial for expanding the industries covered by the carbon market and ensuring its stable and healthy development. To ensure the accuracy and reliability of the predictions in practical applications, it is important to evaluate the model's robustness. In this paper, we built models with different parameters to predict carbon trading prices, and proposed models with high accuracy and robustness. The accuracy of the models was assessed using traditional survey indicators. The robustness of the CNN-LSTM model was compared to that of the LSTM model using Z-scores. The CNN-LSTM model with the best prediction performance was compared to a single LSTM model, resulting in a 9% reduction in MSE and a 0.0133 shortening of the Z-score range. Furthermore, the CNN-LSTM model achieved a level of accuracy comparable to other popular models such as CEEMDAN, Boosting, and GRU. It also demonstrated a training speed improvement of at least 40% compared to the aforementioned methods. These results suggest that the CNN-LSTM enhances model resilience. Moreover, the practicality of using Z-score to evaluate model robustness is confirmed. • Deep learning by combined CNN-LSTM networks for carbon price forecasting. • Hyperparameter tuning of deep learning models for improving forecast accuracy. • CNN-LSTM models outperform single CNN models and single LSTM models. • Performance metric of deep learning for abrupt changes in carbon price variation. [ABSTRACT FROM AUTHOR]

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals. • The current study analyses the role of green factor productivity in zero carbon transition. • We use 30 chinese provincial datasets from 2005 to 2020. • Energy transition is the most effective channel to improve green total factor productivity. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions. • This paper studies the effects of AI on China's GTFP from internal-structural perspective. • GTFP is decomposed into three internal factors by the global Malmquist index. • AI has positive effect on GTFP through different impacts on internal factors. • Improving resource allocation efficiency is the most critical channel of AI on GTFP. • AI plays a more significant role in promoting GTFP in less developed areas. [ABSTRACT FROM AUTHOR]

A significant milestone in China's carbon market was reached with the official launch and operation of the National Carbon Emission Trading Market. The accurate prediction of the carbon price in this market is crucial for the government to formulate scientific policies regarding the carbon market and for companies to participate effectively. Nevertheless, it remains challenging to accurately predict price fluctuations in the carbon market because of the volatility and instability caused by several complex factors. This paper proposes a new carbon price forecasting framework that considers the potential factors influencing national carbon prices, including data decomposition and reconstruction techniques, feature selection techniques, machine learning forecasting techniques for intelligent optimisation, and research on model interpretability. This comprehensive framework aims to improve the accuracy and understandability of carbon price projections to respond better to the complexity and uncertainty of carbon markets. The results indicate that (1) the hybrid forecasting framework is highly accurate in forecasting national carbon market prices and far superior to other comparative models; (2) the factors driving national carbon prices vary according to the time scale. High-frequency series are sensitive to short-term economic and energy market indicators. Medium- and low-frequency series are more susceptible to financial markets and long-term economic conditions than high-frequency series. This study provides insights into the factors affecting China's national carbon market price and serves as a reference for companies and governments to develop carbon price forecasting tools. • A hybrid carbon price prediction model named FS-CEEMDAN-VMD-GWO-LightGBM is proposed. • Accurately predicted the national carbon price in China using multi-influence factor time series data. • Using a data decomposition and reconstruction strategy, the model's accuracy was improved. • The SHAP algorithm is used to assess the impact of various influencing factors on the fluctuations of carbon prices. [ABSTRACT FROM AUTHOR]

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) plays a crucial role in global energy transformation, and a thorough study of the potential impact of RE on regional carbon emissions is of great significance. This is particularly relevant to China, which needs to clarify its path to carbon reduction. Using the sample data of 30 provinces in China from 2000 to 2021, this paper uses the Granger causality test to verify the causal relationship between carbon emission intensity (CEI) and other factors. It builds a mediation effect model on this basis to explore the direct impact effect and indirect transmission path of renewable energy utilization (REU) on CEI. The results show that REU has a one-way causal relationship with CEI. REU can directly and indirectly reduce CEI by improving social wealth and changing the direction of energy investment. In addition, REU indirectly increases CEI through the transmission paths of investment in the energy industry - social affluence and industrial level-social affluence. The CEI is indirectly reduced through the conduction paths of (social affluence-Urbanization rate), (Investment in the energy industry-Urbanization rate), (Industrial level-Urbanization rate), and (Industrial level-Investment in the energy industry). These conclusions will assist policymakers in exploring targeted pathways for low-carbon power development, providing a reference for strategic and sustainable carbon reduction policies. [Display omitted] • Enrich the view of renewable energy's indirect impact on carbon emissions. • Renewable energy's carbon emission reductions go beyond replacing fossil fuels. • Constructed a mediating effect model between renewable energy and carbon emissions. • Renewable energy can promote or inhibit carbon emissions through various pathways. • Research helps develop more effective renewable energy sustainability strategies. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

Resource-based cities generally face the dual pressures of ecological damage and high carbon emissions. Taking the National Sustainable Development Plan for Resource-Based Cities (NSDP) issued in China as a quasi-natural experiment, this paper for the first time, uses the difference-in-difference method to test the coordinated effect of green expansion and carbon reduction brought by NSDP at the county level using rich remote sensing data. The results show that NSDP has significantly promoted the ecological quality improvement and CO 2 emission mitigation in resource-based cities, and the above coordinated benefits mainly occur in energy, mature, declining, northeastern, and municipal resource-based cities. Through the mechanism analysis, we find that NSDP mainly works by promoting the transformation of industry sector to agriculture, animal husbandry, accommodation and catering, finance, and environment management sectors, which are reflected in output, employment, product yield, land type and land transaction area. Further discussion on the tertiary industry suggests that developing tourism, easing financing constraint and strengthening environment regulation, are the key channels to borne fruit in green expansion and carbon reduction. • Analysis of placed-based policy on resource at the county-level. • Coordinated effects of green expansion and carbon reduction are tested. • Key areas of policy effects are identified. • Industrial structure transformation and its related mechanisms are discussed. [ABSTRACT FROM AUTHOR]

The stabilization of growth and preservation of employment are the primary objectives of the current new economic normal. Investigating whether the low-carbon transition can be an opportunity or a shock for employment expansion in green development requires thorough examination. This study utilizes multi-temporal difference-in-difference (DID) models, analyzing comprehensive panel data from China (2007-2019) to assess the impact of the Low-carbon City Pilot (LCCP) policy on employment at meso-regional and micro-firm levels. Empirical findings robustly reveal that LCCP significantly boosts employment, with average treatment effects of approximately 0.548% and 5.892% at regional and firm scales, respectively. Positive impacts vary based on ownership, location, industry type, and energy consumption within enterprises. Notably, state-owned enterprises, those in the eastern region, engaged in secondary industries, and with high energy consumption experience pronounced positive effects. Mechanism analysis further reveals that LCCP boosts employment via promoting government environmental subsidies and expanding enterprise investment scale to create more jobs. These findings provide policy recommendations for further promoting low-carbon transition and expanding employment to achieve the win-win goal of sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Adapting to climate change is critical to building sustainable and resilient agricultural systems. Understanding farmers' perceptions of climate change has become the key to the effective implementation of climate change adaptation policies. This research draws multidisciplinary attention to how farmers participate in decision-making on adaptation behaviors and provides useful insights for realizing synergies between environmental change and agricultural production. In this work, we conducted a meta-analysis of 63 quantitative studies on Chinese farmers' adaptation to climate change to assess the relationship between motivational factors and adaptation behavior. Our analysis highlights that farmers' perceptions of precipitation changes are often inaccurate; however, other psychological factors, such as perception, experience, and risk attitude, significantly positively impact their adaptation behavior. In addition, different climate regions are the main source of high heterogeneity in inter-study comparisons of climate change perception, and the effect of climate regions may therefore constitute a moderating factor that weakens the positive relationship between climate change perception and adaptive behavior. Furthermore, this study highlights the need to intervene at the household level to enhance farmers' adaptability to climate change, which includes providing support through income diversification, early warning information services, training, assistance, credit, subsidies, and other resources. In the future, research on how perception, experience, and risk interact to affect adaptive behavior should be strengthened., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Globally, forest soils are considered as important sources and sinks of greenhouse gases (GHGs). However, most studies on forest soil GHG fluxes are confined to the topsoils (above 20 cm soil depths), with only very limited information being available regarding these fluxes in the subsoils (below 20 cm soil depths), especially in managed forests. This limits deeper understanding of the relative contributions of different soil depths to GHG fluxes and global warming potential (GWP). Here, we used a concentration gradient-based method to comprehensively investigate the effects of thinning intensity (15% vs. 35%) and nutrient addition (no fertilizer vs. NPK fertilizers) on soil GHG fluxes from the 0-40 cm soil layers at 10 cm depth intervals in a Chinese fir (Cunninghamia lanceolata) plantation. Results showed that forest soils were the sources of CO 2 and N 2 O, but the sinks of CH 4 . Soil GHG fluxes decreased with increasing soil depth, with the 0-20 cm soil layers identified as the dominant producers of CO 2 and N 2 O and consumers of CH 4 . Thinning intensity did not significantly affect soil GHG fluxes. However, fertilization significantly increased CO 2 and N 2 O emissions and CH 4 uptake at 0-20 cm soil layers, but decreased them at 20-40 cm soil layers. This is because fertilization alleviated microbial N limitation and decreased water filled pore space (WFPS) in topsoils, while it increased WFPS in subsoils, ultimately suggesting that soil WFPS and N availability (especially NH 4 + -N) were the predominant regulators of GHG fluxes along soil profiles. Generally, there were positive interactive effects of thinning and fertilization on soil GHG fluxes. Moreover, the 35% thinning intensity without fertilization had the lowest GWP among all treatments. Overall, our results suggest that fertilization may not only cause depth-dependent effects on GHG fluxes within soil profiles, but also impede efforts to mitigate climate change by promoting GHG emissions in managed forest plantations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Particulate matter with an aerodynamic diameter of less than 1 μm (PM 1.0 ) can be extremely hazardous to human health, so it is imperative to accurately estimate the spatial and temporal distribution of PM 1.0 and analyze the impact of related policies on it. In this study, a stacking generalization model was trained based on aerosol optical depth (AOD) data from satellite observations, combined with related data affecting aerosol concentration such as meteorological data and geographic data. Using this model, the PM 1.0 concentration distribution in China during 2016-2019 was estimated, and verified by comparison with ground-based stations. The coefficient of determination (R 2 ) of the model is 0.94, and the root-mean-square error (RMSE) is 8.49 μg/m 3 , mean absolute error (MAE) is 4.10 μg/m 3 , proving that the model has a very high performance. Based on the model, this study analyzed the PM 1.0 concentration changes during the heating period (November and December) in the regions where the "coal-to-gas" policy was implemented in China, and found that the proposed "coal-to-gas" policy did reduce the PM 1.0 concentration in the implemented regions. However, the lack of natural gas due to the unreasonable deployment of the policy in the early stage caused the increase of PM 1.0 concentration. This study can provide a reference for the next step of urban air pollution policy development., Competing Interests: Declaration of competing interest Dear editors, all the authors (Tianqi Shi, Yanran Peng, Xin Ma, Ge Han, Zhipeng Pei, Siwei Li, Huiqin Mao, Xingying Zhang, Wei Gong) declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Education expenditure is essential in mitigating air pollution, but the relationship between education expenditure and air pollution lacks in-depth discussion. Utilizing data at the county level in China during 2007-2021, this study estimates the effect of education expenditure from local governments on air pollution. Our findings demonstrate that education expenditure significantly and negatively affects air pollution, which remains robust after addressing endogeneity. The mechanism analysis presents that education expenditure reduces air pollution through the composition, technique, and income effects. The heterogeneity analysis indicates that the impact of education expenditure exhibits marked regional heterogeneity. Specifically, the role of education expenditure is significant in strong regulation, key, eastern, and central regions. By considering interaction terms, we identify the moderating effects of human capital, economic development, infrastructure construction, and public service for education expenditure. The cost-benefit analysis emphasizes that education expenditure improves social welfare. Our findings can inspire local governments to place more emphasis on air quality and public education expenditure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Maintaining optimal ecological security in the Yangtze River-connected and isolated lake basins is of great significance to national projects involving Yangtze River protection. Ecosystem stability and associated factors are important components of ecological security in these basins. However, few studies have focused on ecosystem stability and its driving factors over long periods in the Yangtze River Basin. In this study, a remote sensing index was used to analyze the spatiotemporal variation in the ecosystem stability of the Dongting Lake Basin (DTL), Poyang Lake Basin (PYL), and the isolated Chaohu Lake Basin (CHL) and Taihu Lake Basin (THL) in the Yangtze River over the period 2000-2022 to determine the potential affecting factors. The results showed fluctuations in the ecosystem stability of the DTL and PYL, while a V-shape was observed for the CHL and THL during the same period; the closer to the lake, the weaker the stability of the ecosystem, especially in the DTL and PYL. Moreover, the ecosystem stability was greater in the DTL and PYL than in the CHL and THL. The spillover effect of anthropogenic activities on the ecosystem stability of the four basins and the direct effect of temperature have the greatest effect on the ecosystem stability. Specifically, the ecosystem stability index for the area around the DTL and PYL decreased with increasing human interference, whereas the opposite was observed in the CHL and THL. The effect of temperature was negative for the ecosystem stability of DTL and PYL and significantly positive for CHL and THL, at a level of 0.01 %. The findings of this study provide significant information for targeted ecological restoration of the Yangtze River Basin., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

China's commitment to attaining carbon neutrality by 2060 has galvanized research into carbon sequestration, a critical approach for mitigating climate change. Despite the rapid urbanization observed since the turn of the millennium, a comprehensive analysis of how urbanization influences urban carbon storage throughout China remains elusive. Our investigation delves into the nuanced effects of urbanization on carbon storage, dissecting both the direct and indirect influences by considering urban-suburban gradients and varying degrees of urban intensity. We particularly scrutinize the roles of climatic and anthropogenic factors in mediating the indirect effects of urbanization on carbon storage. Our findings reveal that urbanization in China has precipitated a direct reduction in carbon storage by approximately 13.89 Tg of carbon (Tg C). Remarkably, urban sprawl has led to a diminution of vegetation carbon storage by 8.65 Tg C and a decrease in soil carbon storage by 5.24 Tg C, the latter resulting from the sequestration of impervious surfaces and the elimination of organic matter inputs following vegetation removal. Meanwhile, carbon storage in urban greenspaces has exhibited an increase of 6.90 Tg C and offsetting 49.70% of the carbon loss induced by direct urbanization effects. However, the indirect effects of urbanization predominantly diminish carbon storage in urban greenspaces by an average of 5.40%. The degree of urban vegetation management emerges as a pivotal factor influencing the indirect effects of urbanization on carbon storage. To bolster urban carbon storage, curbing urban sprawl and augmenting urban green spaces are imperative strategies. Insights from this study are instrumental in steering sustainable urban planning and advancing towards the goal of carbon neutrality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

To cope with global climate risks, promoting energy transformation has become a global consensus. China issued a reform policy in 2010 to promote the convergence of the three major information industries, namely broadcasting and television networks, telecommunications networks and the Internet (TPR policy). However, is the convergence of information industries able to promote energy transition? This study constructs a quasi-natural experimental framework using China's TPR policy as a representative case of industrial convergence. Using city-level panel data between 2003 and 2016 in China and a multi-period difference-in-differences model, this study examines the impact of TPR policy on energy transition. The results show that TPR policy positively contributes to energy transition at a 1% significance level. Extensive robustness tests support this finding. This positive effect is particularly evident in regions with less developed communications infrastructure and stricter environmental regulations. Mechanism analysis suggests that TPR policy promotes energy transition by improving the level of information networks, promoting technological innovation, and optimizing industrial structure. The findings of this paper emphasize the importance of information industry convergence in facilitating energy transformation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Motivating the agricultural industry to engage in digital transformation is a challenge academically and socially. It is of great significance to study the choice of digital transformation mode of agricultural industrial organization and analyze its driving factors for promoting the sustainable development of agricultural industrial organization. This study adopts a bilateral evolutionary game to construct a decision-making model for behavioral decision-making during the digital transformation of the agricultural industry. The contingent-actual logical framework and multiple case studies of Yunnan highland agriculture are used to explore the impact of various factors on behavioral decision-making during the digital transformation of the agricultural industry. Additionally, a simulation analysis is used to verify the validity of the bilateral evolutionary game model. The results demonstrate that: (1) When the agricultural industry chooses "active transformation," behavioral decision-making during the digital transformation of the agricultural industry reaches a Nash equilibrium; (2) transformation costs, industry revenue, and reward and penalty mechanisms are the main driving factors for whether or not the agricultural industry chooses to actively engage in digital transformation; and (3) the probability of active digital transformation increases when agricultural industry organizations obtain higher returns at lower costs. Simultaneously, the higher the government's incentives, the greater the enthusiasm. However, when the penalty is excessive, the digital transformation takes the shape of either passive transformation or forced active transformation. Subsequently, it is necessary to improve the digital transformation planning of the agricultural industry, strengthen this field's cooperation mechanism, and formulate a reasonable reward and penalty system for digital transformation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Microorganisms are essential components of underground life systems and drive elemental cycling between plants and soil. Yet, in the ecologically fragile Loess Plateau, scant attention has been paid to the response of microbial communities to organic carbon (C) chemistry of both leaves and soils under different revegetation conditions, as well as subsequent alternation in their C metabolic functions. Here, Fourier transform infrared (FTIR) spectrum, amplicon sequencing of 16S rRNA and ITS, and temporal incubation with Biolog-Eco 96 plates were combined to explore the vegetative heterogeneity of microbial community properties and metabolic functions, as well as their regulatory mechanisms in three typical revegetation types including Robinia pseudoacacia L. (RF), Caragana korshinskii KOM. (SL), and abandoned grassland (AG). We observed higher bacterial-to-fungal ratios (B: F = 270.18) and richer copiotrophic bacteria (Proteobacteria = 33.08%) in RF soil than those in AG soil, suggesting that microbes were dominated by r-strategists in soil under RF treatment, which is mainly related to long-term priming of highly bioavailable leaf C (higher proportion of aromatic and hydrophilic functional groups and lower hydrophobicity). Conversely, microbial taxa in AG soil, which was characterized by higher leaf organic C hydrophobicity (1.39), were dominated by relatively more abundant fungi (lower B: F ratio = 149.49) and oligotrophic bacteria (Actinobacteria = 29.30%). The co-occurrence network analysis showed that microbial interactive associations in RF and AG soil were more complex and connective than in SL soil. Furthermore, Biolog-Eco plate experiments revealed that microorganisms tended to utilize labile C compounds (carbohydrates and amino acids) in RF soil and resistant C compounds (polymers) in AG soil, which were consistent with the substrate adaptation strategies of predominant microbial trophic groups in different revegetation environments. Meanwhile, we observed greater microbial metabolic activity and diversity advantages in RF vegetation. Collectively, we suggest that besides the nutrient variables in the leaf-soil system, the long-term regulation of the microbial community by the C chemistry of the leaf sequentially alters the microbial metabolic profiles in a domino-like manner. RF afforestation is more conducive to restoring soil microbial fertility (including microbial abundance, diversity, interactive association, and metabolic capacity). Our study potentially paves the way for achieving well-managed soil health and accurate prediction of C pool dynamics in areas undergoing ecological restoration of the Loess Plateau., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Research Question: In the context of global low-carbon emission reduction, how to achieve green and high-quality development has become a major issue for the Communist Party of China (CPC) and the Chinese government recently. Based on the data of China's listed companies from 2013 to 2020, this paper uses Python to implement text analysis of annual reports, and explores the relationship between political acuity and carbon-efficiency synergies (CES) from the perspective of enterprise initiative., Research Findings: We found that (1) political acuity positively affects carbon-efficiency synergies. (2) Increased political acuity can reduce carbon emissions, but the effect on economic efficiency is not obvious. That is, low carbon takes the lead in raising the level of carbon-efficiency synergies. (3) Environmental regulations can positively regulate the relationship between political acuity and carbon-efficiency synergies. (4) Political acuity in southern China, carbon neutral and non-state-owned enterprises (NSOEs) will have a more pronounced effect on carbon-efficiency synergies., Academic Implications: From the perspective of the root causes of political linkages, we find the synergies between formal and informal institutions, and the key factors for policy implementation., Policy Implications: This paper is helpful for enterprises to improve the synergies of emission reduction and efficiency promotion, and has practical implications for the government to promote green and high-quality development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The digital economy (DIE), a new economic form with digitalization at its core, has become an important driving force for promoting regional economy development. In the context of the COVID-19 pandemic, exploring the impact path of the DIE on carbon emission efficiency (CEE) is conducive to giving full play to the "carbon-reduction-and-efficiency-enhancement" role of the DIE, and to promoting the realization the "dual carbon" goal of carbon peak and carbon neutrality. In this paper, the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB) are taken as study areas, the panel Tobit model is used to explore the impact of the DIE on CEE, and the intermediary-effect model and threshold-effect model are constructed to test the intermediary and threshold effects of technological innovation, respectively. The results show that the DIE has a U-shaped nonlinear impact on CEE in both the YRB and the YREB and that the impact has regional heterogeneity. Technological innovation can play a mediating effect between the DIE and CEE, whereas the mediating effect in the YRB is stronger than that in the YREB. Technological innovation has a threshold effect on the DIE to improve CEE, while the threshold value in the YREB is higher than that in the YRB. Furthermore, this paper proposes some suggestions to guide regional low-carbon and sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with ω-order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011-2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments We thank all referees for their constructive advise which helped to improve the completeness and clarity of this paper. This work was supported by Social Science Foundation of Shandong Province (22CSDJ72)., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The trading of carbon emissions is a crucial regulatory method to address environmental pollution issues. This study takes China's carbon emission trading pilot policy established in 2013 as a quasi-natural experiment and uses the DID model to empirically test the urban panel data from 2006 to 2019. The results show that the carbon emission trading pilot policy can effectively reduce urban environmental pollution, and this effect is more noticeable in mid-western cities, northern cities, cities with fewer resources, and large-scale cities. In addition, to address the urban environmental pollution problem through this policy, the government is encouraged to raise its environmental protection awareness and put more effort into the innovation of technology. In general, this study uses carbon emission trading policies from China to confirm that market-based incentive environmental regulation tools can effectively reduce environmental pollution in urban areas. These findings can provide more theoretical support and empirical evidence for the government to use mechanisms of the market to effectively solve pollution problems, improve ecological environment quality, and accelerate the realization of green economy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Wetlands in China's coastal provinces are strategically positioned along migratory flyways for waterbirds, serving as essential habitats and stopover sites due to the expansive land area and abundant wetland resources they offer. This study aimed to introduce a simplified index system to enable rapid assessment and prioritization of unprotected areas for wetlands in China's coastal provinces. A spatial analysis was conducted, combining wetland distribution and existing protected areas data and spatial extent of wetlands extracted by remote sensing data. Results indicate substantial gaps in coverage, covering an area of 108.33 × 10 4  ha, with 76% being natural wetlands. Over half of these gaps are identified as high-value wetlands with significant ecological functions. The uneven distribution of unprotected wetlands reflects a tension between economic development and wetland conservation. Our findings support the expansion of the existing coastal wetland protected areas' coverage, as well as protecting critical habitats in conservation gaps, and establishing of a network-based waterbird protection system. This research contributes to informed decision-making and policy in wetlands' conservation planning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In order to fully understand the carbon emission from different fuels in rural villages of China, especially in the typical atmospheric pollution areas. The characteristics of carbonaceous aerosols and carbon dioxide (CO 2 ) with its stable carbon isotope (δ 13 C) were investigated in six households, which two households used coal, two households used wood as well as two households used biogas and liquefied petroleum gas (LPG), from two rural villages in Fenwei Plain from March to April 2021. It showed that the fine particulate matter (PM 2.5 ) emitted from biogas and LPG couldn't be as lower as expected in this area. However, the clean fuels could relatively reduce the emissions of organic carbon (OC) and element carbon (EC) in PM 2.5 compare to the solid fuels. The pyrolyzed carbon (OP) accounted more total carbon (TC) in coal than the other fuels use households, indicating that more water-soluble OC existed, and it still had the highest secondary organic carbon (SOC) than the other fuels. Meantime, the coal combustions in the two villages had the highest CO 2 concentration of 527.6 ppm and 1120.6 ppm, respectively, while the clean fuels could effectively reduce it. The average δ 13 C values (-26.9‰) was much lighter than almost all the outdoor monitoring and similar to the δ 13 C values for coal combustion and vehicle emission, showing that they might be the main contributors of the regional atmospheric aerosol in this area. During the sandstorm, the indoor PM 2.5 mass and CO 2 were increasing obviously. The indoor cancer risk of PAHs for adults and children were greater than 1 × 10 -6 , exert a potential carcinogenic risk to human of solid fuels combustion in rural northern China. It is important to continue concern the solid fuel combustion and its health impact in rural areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Ecological vulnerability and poverty are interrelated and must be addressed together. The resolution of this issue will help us to meet the challenges during the process of implementing concrete actions for realizing the 2030 UN sustainable development goals (SDGs). Ecological restoration projects (ERPs) can enhance ecosystem services (ESs) while providing policy support for improving people's livelihoods. However, processes and mechanisms of ERPs on the ecological environment and socioeconomic development in poverty-stricken and ecologically fragile areas have rarely been studied. To address these issues, we conducted a comparative analysis on the changes of land use and land cover (LULC), ecosystem services (ESs), and socioeconomic development in Bijie City, a karst rocky desertification area in southwest China, before and after the implementation of ERPs in 2000, as well as the complex relationship between these factors. ERPs have affected LULCs, ESs, socioeconomics, and poverty reduction significantly since 2000. Specifically, the total ecosystem service value (ESV) in the study area has increased by more than 3 times in the past 30 years, with the ESV of tourism services and carbon storage increasing the most, from CNY 0.001 and 337.07 billion in 1990 to CNY 11.07 and 108.97 billion in 2019, respectively. The correlation between ESs is mainly synergistic, while the tradeoff between carbon storage and water yield is in a fluctuating upward trend. LULC conversion of cropland to green, and cropland to water, wetland and shrubs has positive effects on carbon storage and water yield, respectively. During study period, GDP, urbanization increased by over 70 times, 5 times, respectively, whereas poverty population, poverty incidence, and employment rate of various sectors (i.e., agriculture, forest, animal, and fishery, or AFAF) decreased by 96.4%, 97.7%, and 18.24%, respectively. Our findings emphasized that ERPs can effectively help poor and ecologically fragile areas to get out of the poverty trap and achieve the "win-win" goals of ecological and socio-economic sustainable development. These results have profound environmental management references to China and other developing countries around the world in realizing ecological restoration, poverty reduction, and the SDGs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The Chinese government promotes nuclear energy development in the context of mitigating climate change. However, the large-scale development is still facing challenges related to the knowledge gap among the general public and the potential "not-in-my-back-yard" objection. Based on a representative national survey, we analyze Chinese people's knowledge and perceptions of nuclear energy and estimate their willingness-to-accept the potential risks of new nuclear programs in neighborhoods via the Contingent Valuation Method. Generally, more than half of people do not know anything about nuclear energy. The main factors influencing public knowledge are identified, such as the residential distance to existing nuclear power stations and the frequency of internet use. Moreover, approximately 12% of individuals with some knowledge seem to be willing to accept new nuclear power plants in their neighborhoods with no compensation needed. Specifically, the perceptions of nuclear risks and pollution from fossil fuels are significant factors influencing people's acceptance of nuclear energy. Although public knowledge does not directly influence acceptance, more knowledge seems to reduce risk perception and increase benefit perception. The residential distance to exiting nuclear stations has limited effects on people's acceptance of newly planned nuclear programs for those living in the same county with some knowledge. In general, a typical Chinese household is willing to accept USD $5.66 every month or USD $67.97 every year to bear the potential risks of the new nuclear program in neighborhoods. Significant practical implications that can be transferable to other new energy technologies and countries or regions are provided., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

The soil selenium (Se) content and bioavailability are important for human health. In this regard, knowing the factors driving the concentration of total Se and bioavailable Se in soils is essential to map Se, enhance foodstuffs' Se content, and improve the Se nutritional status of humans. In this study, total Se and Se bioavailability (i.e., phosphate extracted Se) in surface soils (0-20 cm) developed on different strata were analyzed in a Se-enriched region of Southwest China. Furthermore, the interaction between the stratum and soil properties was assessed and how did the stratum effect on the concentration and spatial distribution of Se bioavailability in soils was investigated. Results showed that the median concentration of total Se in soils was 0.308 mg/kg, which is higher than China's soil background. The mean proportion of phosphate extracted Se in total Se was 12.2 %. The values of total Se, phosphate extracted Se, and soil organic matter (SOM) in soils increased with the increasing stratum age. In contrast, the coefficient of weathering and eluviation (BA) values decreased. The analysis of statistics and Geodetector revealed that the SOM, stratum, and BA were the dominant controlling factors for the contents and distributions of soil total Se and phosphate extracted Se. This study provided strong evidence that the soil properties that affected the total Se and Se bioavailability were modulated by the local geological background, and had important practical implications for addressing Se malnutrition and developing the Se-rich resource in the study region and similar geological settings in different parts of the globe., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Under the influence of many factors, such as climate change, anthropogenic eutrophication, and the development of aquaculture, the area and frequency of algal blooms have showed an increasing trend worldwide, which has become a challenging issue at present. However, the coupled relationship between nitrous oxide (N 2 O) and algal blooms and the underlying mechanisms remain unclear. To address this issue, 15 N isotope cultures and quantitative polymerase chain reaction (qPCR) experiments were conducted in Zhanjiang Bay during algal and non-algal bloom periods. The results showed that denitrification and nitrification-denitrification were the two processes responsible for the in-situ production of N 2 O during algal and non-algal bloom periods. Stable isotope rate cultivation experiments indicated that denitrification and nitrification-denitrification were promoted in the water during the algal bloom period. The in-situ production of N 2 O during the algal bloom period was three-fold that during the non-algal bloom period. This may be because fresh particulate organic matter (POM) from the organisms responsible for the algal bloom provides the necessary anaerobic and hypoxic environment for denitrification and nitrification-denitrification in the degradation environment. Additionally, a positive linear correlation between N 2 O concentrations and ammonia-oxidizing bacteria (AOB) and denitrifying bacteria (nirK and nirS) also supported the significant denitrification and nitrification-denitrification occurring in the water during the algal bloom period. However, the algal bloom changed the main process for the in-situ production of N 2 O, wherein it shifted from denitrification during the non-algal bloom period to nitrification-denitrification during the algal bloom period. The results of our study will improve our understanding of the processes responsible for the in-situ production of N 2 O during the algal bloom period, and can help formulate effective policies to mitigate N 2 O emissions in the bay., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Extensive outbreaks of harmful algal blooms (HABs) occurred in the Fuchunjiang Reservoir in 2022, a crucial urban drinking water source, coinciding with extreme summer heatwaves. We hypothesize that these heatwaves contributed to HABs formation and expansion. Leveraging Landsat 8 and Sentinel-2 data, we employed clustering and machine learning methods to quantify the HABs distribution and area. Concurrent meteorological and water quality data aided in uncovering the effects of heatwave on HABs. When applying different methods to extract HABs from remote sensing images, random forest (RF) analyses indicated accuracies of 99.3% and 99.8% for Landsat 8 and Sentinel-2 data, respectively, while classification and regression tree (CART) analyses indicated 99.1% and 99.7% accuracies, respectively. Support vector machine (SVM) exhibited lower accuracies (83.5% and 97.4%). Thus RF, given its smaller differences between satellites and high accuracy, was selected for further analysis. Both satellites detected extensive HABs in 2022, with Sentinel-2 recording a peak area of 24.13 km 2 (44.6% of cloud-free water area) on August 11, 2022. Increasing trends with amplified durations were observed for summer heatwaves in Jiande and Tonglu around the Fuchunjiang Reservoir. Notably, these areas experienced extreme heatwaves for 63 and 58 days in 2022, respectively, more than double the 1980-2022 average. From June 1 to October 8, 2022, water temperature peaks significantly coincided with expansive HABs and elevated chlorophyll a (Chl-a) concentration from 4.8 μg/L to 119.2 μg/L during the summer heatwaves. Our findings indicated that the reservoir became more HAB-prone during heatwave events, escalating the drinking water safety risk. These results emphasize the challenges faced by reservoir managers in dealing with climate-induced extreme heatwaves and underscore the urgency for heightened attention from water source management departments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Improving corporate green technology innovation is a key link in achieving green transformation and development. Compared with formal environmental regulations that force companies to carry out green innovation passively, ESG ratings under soft environmental regulations can better stimulate the internal motivation of companies. This study uses the ESG ratings of listed companies published for the first time by SynTao Green Finance as an exogenous impact. Taking China's A-share listed companies from 2011 to 2022 as a research sample, the multi-period differences-in-differences model was used to empirically test the impact of ESG rating soft supervision on corporate green technology innovation. The results show that the impact of ESG rating events as a soft market regulation has a significant positive impact on the improvement of corporate green technology innovation. This conclusion still holds after a series of robustness tests. Meanwhile, enterprise digital transformation plays a positive regulatory role. The heterogeneity test shows that the green technology innovation of state-owned enterprises is more affected by ESG ratings. Mechanism research has found that ESG rating events promote corporate green technology innovation by easing corporate financing constraints and reducing managerial myopia. Further research found that under the influence of the external environment, intensified market competition and increased attention from the capital market are also conducive to the improvement of corporate green technology innovation. This study strengthens the corporate ESG concept under the guidance of green development and provides empirical evidence for promoting corporate green transformation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Anthropogenic reactive nitrogen (Nr) loss has been a critical environmental issue. However, due to the limitations of data availability and appropriate methods, the estimation of Nr loss from rice paddies and associated spatial patterns at a fine scale remain unclear. Here, we estimated the background Nr loss (BNL, i.e., Nr loss from soils without fertilization) and the loss factors (the percentage of Nr loss from synthetic fertilizer, LFs) for five loss pathways in rice paddies and identified the national 1 × 1 km spatial variations using data-driven models combined with multi-source data. Based on established machine learning models, an average of 23.4% (15.3-34.6%, 95% confidence interval) of the synthetic N fertilizer was lost to the environment, in the forms of NH 3 (17.4%, 10.9-26.7%), N 2 O (0.5%, 0.3-0.8%), NO (0.2%, 0.1-0.4%), N leaching (3.1%, 0.8-5.7%), and runoff (2.3%, 0.6-4.5%). The total Nr loss from Chinese rice paddies was estimated to be 1.92 ± 0.52 Tg N yr -1 in 2021, in which synthetic fertilizer-induced Nr loss accounted for 69% and BNL accounted for the other 31%. The hotspots of Nr loss were concentrated in the middle and lower regions of the Yangtze River, an area with extensive rice cultivation. This study improved the estimation accuracy of Nr losses and identified the hotspots, which could provide updated insights for policymakers to set the priorities and strategies for Nr loss mitigation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Enterprise digital transformation (EDT) is a strategic initiative that provides robust support for optimising resource allocation, fosters business innovation, and significantly impacts ecological environment to increase financial performance. This study re-examines the substantial contributions of EDT to climate change mitigation. Drawing on data from Chinese A-share listed companies from 2010 to 2021, we investigated the changes and mechanisms influencing carbon emissions reduction performance (CERP) of enterprises undergoing digital transformation. The empirical results indicate that EDT actively contributes to enhancing the CERP of enterprises, with a more pronounced effect observed in non-polluting industries, state-owned enterprises, and manufacturing companies. Furthermore, empirical findings from mechanism tests reveal that EDT effectively improves the CERP by driving green technological innovation, strengthening industry chain connections, and enhancing capacity utilisation. Finally, within external oversight groups, particularly in government and investor supervision, the enhancement of enterprise CERP is more significant, highlighting the crucial role of external oversight in the EDT process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Municipal solid waste incineration (MSWI) fly ash contains large amounts of Ca, Si, and other elements, giving it the potential to be used as a raw material for cement production. However, fly ash often contains a high content of salts, which greatly limits its blending ratio during cement production. These salts are commonly removed via water washing, but this process is affected by the nature and characteristics of fly ash. To clarify the influence of the ash characteristics on salt removal, a total of 60 fly ash samples from 13 incineration plants were collected, characterized, and washed. The ash characterization and cluster analysis showed that the incinerator type and flue gas purification technology/process significantly influenced the ash characteristics. Washing removed a high percentage of salts from fly ash, but the removal efficiencies varied significantly from each other, with the chlorine removal efficiency ranging from 73.76% to 96.48%, while the sulfate removal efficiency ranged from 6.92% to 51.47%. Significance analysis further revealed that the salt removal efficiency varied not only between the ash samples from different incinerators, but also between samples collected at different times from the same incinerator. The high variance of the 60 ash samples during salt removal was primarily ascribed to their different mineralogical and chemical characteristics. Mineralogical analysis of the raw and washed ash samples showed that the mineralogical forms and proportion of these salts in each ash sample greatly influenced their removal. The presence of less-soluble and insoluble chloride salts (e.g., CaClOH, Ca 2 Al(OH) 6 (H 2 O) 2 Cl etc.) in fly ash significantly affected the chlorine removal efficiency. This study also found that Fe, Mn, and Al in fly ash were negatively correlated with the dechlorination efficiency of fly ash. In summary, the different physical and chemical properties of fly ash caused great discrepancies in salt removal. Consequently, it is suggested to consider the potential impact of the ash source and ash generation time on salt removal to ensure a reliable treatment efficiency for engineering applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)