Does the "Belt and Road Initiative" benefit the environment? Insight from analysis of intra-industry trade in environment goods.

The expansion of the Belt and Road Initiative (BRI) has raised a wide range of concerns about its environmental impact. Therefore, from the perspective of environmental impacts, this study used the two-way fixed effect staggered differences in differences (TWFE Staggered DID) method to examine the impact of the BRI on the Environment Goods (EGs) intra-industry trade (IIT) between China and other Belt and Road (B&R) countries, including a sample of 191 countries, covering the period from 2010 to 2019 for eliminating the impact of COVID-19 and the financial crisis in 2008 and 2009. Because only 135 countries signed a Memorandum of Understanding between 2010 and 2019, this study treated these B&R countries as the study group, and the other 73 countries (non-B&R countries) as the control group. This study described EGs using the 54 6-digit code Environment Goods in Harmonized Commodity Description and Coding System listed in the "APEC LIST OF ENVIRONMENT GOODS" published by the Asia-Pacific Economic Cooperation in 2012, and used the intra-industry trade index proposed by Grubel and Lloyd in 1971 to measuring dependent variable. The research results indicated that the BRI has significantly promoted bilateral EGs IIT. The mechanism test implied that, in addition to direct impacts, the BRI also has indirect impacts by boosting the energy restructuring of B&R countries. These results prove that the BRI has positive impacts on the environment. The heterogeneity test showed that there is a heterogeneous impact depending on the type of IIT, product categorization, B&R countries' income levels, and geographic environment. This study not only gives theoretical and empirical evidence of the positive environmental impacts of the BRI, but also provides practical guidance for the development of EGS IIT between China and B&R countries, thereby contributing to global carbon emissions reduction and environmental governance to some degree.

Accounting for the increasing benefits from scarce ecosystems.

As people get richer, and ecosystem services scarcer, policy-relevant estimates of ecosystem value must rise.

The health and welfare effects of environmental governance: Evidence from China.

Environmental regulations aim to reduce pollution and improve air quality and the health of residents. However, there is a lack of research focusing on the health and welfare effects of low-carbon city pilot policies. In this context, this study takes China's low-carbon city pilot policy as an entry point, focuses on the health effects of public environmental governance, and systematically investigates the effects and mechanisms of low-carbon city development on the health of middle-aged and elderly people by applying the difference-in-differences method. The study finds that low-carbon city (LCC) policy significantly improves the physical and mental health of middle-aged and elderly people, and the main transmission mechanism is the reduction in air pollution and improvement in social capital. These results hold following a series of robustness tests. Furthermore, low-carbon city construction can reduce hospitalization and outpatient costs for people over 45 years old by up to 3 % and 15.5 %, respectively. The findings of this study provide useful policy insights for ensuring sustainable improvement in environmental quality and public health.

Sediment source fingerprints of natural processes and anthropogenic pressures: A contribution to manage the Paraopeba River basin impacted by the B1 tailings dam collapse.

Understanding the origins of sediment transport in river systems is crucial for effective watershed management, especially after catastrophic events. This information is essential for the development of integrated strategies that guarantee water security in river basins. The present study aimed to investigate the rupture of the B1 tailings dam of the Córrego do Feijão mine, which drastically affected the Brumadinho region (Minas Gerais, Brazil). To address this issue, a confluence-based sediment fingerprinting approach was developed through the SedSAT model. Uncertainty was assessed through Monte Carlo simulations and Mean Absolute Error (MAE). Estimates of the overall average contributions of each tributary were quantified for each station and annually during the period 2019-2021. It was observed that the sampling point PT-09, closest to the dam breach, contributed to almost 80% of the Paraopeba River in 2019. Despite the dredging efforts, this percentage increased to 90% in 2020 due to the need to restore the highly degraded area. Additionally, the main tributaries contributing to sediment increase in the river are Manso River "TT-03" (almost 36%), associated with an area with a high percentage of urban land use, and Cedro stream "TT-07" (almost 71%), whose geology promotes erosion, leading to higher sediment concentration. Uncertainties arise from the limited number of available tracers, variations caused by dredging activities, and reduced data in 2020 due to the pandemic. Parameters such as land use, riparian vegetation degradation, downstream basin geology, and increased precipitation are key factors for successfully assessing tributary contributions to the Paraopeba River. The obtained results are promising for a preliminary analysis, allowing the quantification of key areas due to higher erosion and studying how this disaster affected the watershed. This information is crucial for improving decision-making, environmental governance, and the development of mitigating measures to ensure water security. This study is pioneering in evaluating this methodology in watersheds affected by environmental disasters, where restoration efforts are ongoing.

Citizen monitoring in environmental disclosure: An economics perspective.

Criticism is mounting that market-led and state-led initiatives for environmental impact disclosure are too limited in scope and that they rest on too strong assumptions about the quality and impartiality of monitoring and enforcement, with resulting insufficient effect on environmental sustainability. It has been proposed that citizen monitoring may contribute to counteract this void. However, to our knowledge, policy analysis in general and economics in particular has not paid much attention to this role of citizen monitoring. This paper aims to bridge that gap from an economics lens, by exploring the dynamics of disclosing local environmental impact and the potential role of citizen monitoring in environmental policy. To this end, the paper addresses monopolistic versus pluralistic environmental disclosure, letting citizen monitoring represent the latter. The study uses the mining industry as an illustrative case, because of that sector's particular transparency challenges in international value chains, typically with strong negative local environmental impact. It is shown how pluralistic information provision such as citizen monitoring can contribute to incentivizing more reliable information provision, especially in countries with weak state institutions, which is particularly important in the case of high-risk environmental impact. The findings should be of use for shaping environmental policy, providing valuable insights for both policymakers and scholars.

Life expectancy and emission trading scheme: a case study in China.

Life expectancy can reflect both health benefit and implementation cost of climate policy. Nevertheless, little research has quantified the relation between life expectancy and climate policy in literature. In this paper, we attempt to narrow the research gap by studying how life expectancy is related to the Chinese nationwide emission trading scheme (CNETS). To achieve this research target, a Computable General Equilibrium (CGE) model is employed to simulate the operation of the economic system and the policy shock from emission abatement. The CGE model results show that life expectancy is prolonged by GDP but shortened by emissions, and the GDP impact on life expectancy is larger than the emission impact. Climate policy has dual effects on life expectancy because it relieves both negative emission impacts and positive GDP impacts on lifespan; its net effect on life expectancy is positive. Life expectancy positively impacts GDP, and this impact is moderated by climate policy; specifically, climate policy reinforces the positive impact of life expectancy on GDP. Life expectancy minimally affects carbon emissions during climate policy implementation; in other words, it has minimal impacts on emission abatement. These findings imply that climate policy and life expectancy complement each other; the government could implement climate policy to increase lifespan or prolong life expectancy to facilitate policy implementation.

Estimating the water quality index based on interpretable machine learning models.

The water quality index (WQI) is an important tool for evaluating the water quality status of lakes. In this study, we used the WQI to evaluate the spatial water quality characteristics of Dianchi Lake. However, the WQI calculation is time-consuming, and machine learning models exhibit significant advantages in terms of timeliness and nonlinear data fitting. We used a machine learning model with optimized parameters to predict the WQI, and the light gradient boosting machine achieved good predictive performance. The machine learning model trained based on the entire Dianchi Lake water quality data achieved coefficient of determination (R2), mean square error, and mean absolute error values of 0.989, 0.228, and 0.298, respectively. In addition, we used the Shapley additive explanations (SHAP) method to interpret and analyse the machine learning model and identified the main water quality parameter that affects the WQI of Dianchi Lake as NH4+-N. Within the entire range of Dianchi Lake, the SHAP values of NH4+-N varied from -9 to 3. Thus, in future water environmental governance, it is necessary to focus on NH4+-N changes. These results can provide a reference for the treatment of lake water environments.

Balancing growth targets and environmental regulations: An empirical analysis of dual policy impact on corporate environmental responsibility-insights from China.

Balancing economic growth with environmental conservation poses a universal challenge for governments worldwide. This study investigates the intricate interplay between governments' economic-environmental trade-offs and their implementation of policies aimed at promoting Corporate Environmental Responsibility (CER). Given the discretion of Chinese local governments in economic and environmental policy, we take China as a case study. To conduct this research, we first merge critical data on China's economic growth targets and environmental regulations with information on listed enterprises. Then, we employ a "U-shaped" relationship model to examine the impact of these trade-offs on CER implementation. The results reveal that: (1)The effective fulfillment of CER by enterprises is primarily driven by stricter environmental regulations. (2) Economic growth targets can, to some extent, diminish the policy effect of environmental regulations on CER fulfillment. (3)The crowding-out effect of economic growth targets is particularly pronounced within specific subsets of enterprises, including state-owned enterprises, heavily polluting firms, and those facing high profit pressure. These findings imply that when local governments implement contradictory policies, they must consider not only enterprises' political connections and economic contributions but also pay close attention to the survival dilemma of enterprises. This balancing act aims to harmonize conflicting policy objectives. This research deepens the understanding of how institutional and policy frameworks impact enterprise engagement in CER, especially within the context of governments' economic-environmental trade-offs. It sheds light on the strategies employed by China and other emerging economies to effectively leverage contradictory policies to foster sustainable green growth.

Research on the identification and evolution of health industry policy instruments in China.

The application of health industry policies could be discovered more quickly and comprehensively through the automated identification of policy tools, which could provide references for the formulation, implementation, and optimization of subsequent policies in each province. This study applies the Bidirectional Encoder Representation from Transformer (BERT) model to identify policy tools automatically, utilizes Focal Loss to reduce the unbalance of a dataset, and analyzes the evolution of policy tools in each province, which contains time, space, and topic. The research demonstrates that the BERT model can improve the accuracy of classification, that supply and environment policy tools are more prevalent than demand tools, and that policy instruments are organized similarly in four major economic regions. Moreover, the policy's attention to topics related to healthcare, medicine, and pollution has gradually shifted to other topics, and the extent of policy attention continues to be concentrated on the health service industry, with less attention paid to the manufacturing industry from the keywords of the various topics.

Effects of environmental awareness training and environmental commitment on firm's green innovation performance: Empirical insights from medical equipment suppliers.

In recent years, the intensification of global industrialization coupled with the enterprise's production and operating activities have caused pollution, increasing the current environmental pressure. Relevant government departments in China have instituted several stringent measures (environmental protection sensitization and awareness activities, training sessions, and exchange activities targeted towards enterprise managers) to address these rising environmental problems. Though these measures have gained traction over the years, there is a dearth of research on their effectiveness on the green innovation performance of enterprises. To bridge the gap, this research explores the effect of environmental awareness training, knowledge exchange activities, and commitment on green innovation performance with survey data from 285 medical equipment manufacturing companies in China. It further expands the theoretical application of environmental awareness training, commitment, and innovation performance from the lens of the Knowledge-Based View. The findings depict a positive relationship between environmental awareness training and innovation performance. It also finds a mediating influence of environmental commitment in the relationship between environmental awareness training and green innovation performance. Furthermore, environmental knowledge exchange activities positively moderate the relationship between environmental awareness training and environmental commitment. These findings offer valuable insights for the green development of medical equipment manufacturing enterprises and the government to formulate environmental protection policies.

How does the digital economy affect the provincial "zero-waste city" construction? Evidence from China.

The digital economy is playing a crucial effect in the field of environmental governance. Digital and intelligent management is an essential means to fully realize the "zero-waste city" construction. The present paper investigates the impact of digital economy on China's provincial "zero-waste city" construction. The results indicate that digital economy can contribute to "zero-waste city" construction. The digital economy has a positive nonlinear effect on the construction of "zero-waste city," but the marginal effect is diminishing. The digital economy can facilitate "zero-waste city" construction by improving industrial structure upgrading and green technology innovation. Heterogeneity analysis reveals that digital economy contributes to the construction of "zero-waste city" in the eastern and western regions and high-level environmental regulation regions, while this impact is insignificant in the central region and low-level environmental regulation regions. The digital economy exerts the most significant positive influence on waste resource recycling followed by waste final disposal and then waste reduction at the source. These findings underscore the effect of digital economy in fostering "zero-waste city" construction and promoting sustainable waste management. The present study provides new ideas for the "zero-waste city" construction in emerging developing countries such as China.

Enhancing local governments' environmental attention through open government data: evidence from China.

Environmental conservation has ascended to a prominent position on the global agenda, and China, recognizing the urgent need for environmental protection, has implemented nationwide measures. However, varying levels of environmental attentiveness among local governments have resulted in uneven implementation of these national directives across regions. Therefore, it is crucial to investigate the factors that drive local governments' environmental attention. Our study explores the impact of open government data (OGD) on local governments' environmental attention. Utilizing city-level data from 2010 to 2020, we employ a staggered difference-in-differences (DID) model for empirical analysis. The results reveal that OGD significantly and positively influences local governments' environmental attention. This influence is partly attributed to OGD's role in promoting government digitization, mitigating fiscal pressures, and increasing energy demand. Further analysis, including heterogeneity assessments, demonstrates that OGD has a more pronounced positive effect on environmental attention in cities with higher online political participation activity and a larger internet user base. Such empirical insights underscore the imperative for an integrative policy framework that accentuates the refinement of OGD platform in tandem with strategic enhancements in political participatory mechanisms and digital infrastructure investments, thereby fostering robust local environmental stewardship paradigms.

When do climate change legislation and clean energy policies matter for net-zero emissions?

Achieving the global decarbonization goal under global conflicts is becoming more uncertain. Within this context, this article seeks to examine the effects of global environmental management and efforts to achieve this goal. Specifically, it investigates the role of democracy, control of corruption, and civil society participation as mechanisms that moderate the impact of environmental policy and legislation, particularly clean energy policy and climate change legislation (laws and regulations), on carbon emissions in highly polluted countries. The empirical results show that (i) the effects of democracy-clean energy policies and climate change legislation are relatively small in reducing carbon emissions; (ii) the effect of controlling corruption-climate change regulations is strong in reducing emissions, meaning that governments with higher control of corruption are more effective at enacting and executing laws and regulations dealing with environmental challenges which help achieve desirable environmental outcomes; (iii) strong civil society participation helps the execution of clean energy policies and climate change legislation to curb emissions, and (iv) the robustness check also provides strong evidence that higher control of corruption can contribute to the effectiveness of these policies and legislation in reducing carbon emissions. Overall, these findings suggest that the efficiency of well-designed environmental policy and legislation should be supported by a combination of higher civil society participation and greater control of corruption that can efficiently enforce such policies and legislation.

Design and impact assessment of policies to overcome oversupply in China's national carbon market.

China has adopted a national carbon emissions trading market to promote emission reductions, but until now, overallocation of allowances suffer low carbon prices and thus to unfulfilled emission reduction goals. We report a general equilibrium modeling that indicates the flexible compliance and price adjustment mechanism of the carbon market, along with explores the solution to the oversupply of allowances in the China's national carbon market. We find that, under the current policy, the initial loose allowance allocation decreases the overall carbon price, and simultaneously the total amount of banked carbon allowances reaches 4.880 billion tons in 2030, resulting in the level of carbon price cannot achieve NDC (Nationally Determined Contribution) targets. However, by introducing carbon market price adjustment schemes, we observe that the cumulative amount of allowances can effectively reduce, enabling the carbon price rising. Importantly, the amount of the supply of allowances decreases most under the benchmark decrease scenario, which increases the emission reduction pressure of the enterprises from the beginning, leading to the largest economic losses, the price-based adjustment mechanism raises the carbon price to expected level at the minimize economic losses, and the quantity-based adjustment mechanism is more sensitive to policy parameters compared to the price -based adjustment mechanism. These findings offer a promising avenue for selecting cost-effective price adjustment mechanism to improve price mechanism design for national carbon markets.

The sword of damocles: Understanding the carbon abatement effects of top-down environmental management practices -- insights from China's campaign-style governance.

Inspection, standing for top-down environmental management practices, also known as campaign-style governance, is used by central governments to lessen local environmental pollution. However, there is no causal evidence for carbon abatement. Employing staggered difference-in-differences (DiD), I find that inspected cities mitigate carbon intensity and carbon emissions by 3.72% and 2.34%, respectively, with economic significance. Conducting a triple difference strategy, I suggest the channels are the local people's congresses and political consultative conferences' proposals, government attention, environmental regulation, industrial structure, and green innovation. Also, the heterogeneous effects suggest that municipal party secretaries assigned to their birthplace, the older the party standing and age, and those with natural sciences majors, are more conducive to the inspection achieving carbon mitigation. An alternative DiD specification shows that the "look-back" inspection achieves sustained carbon reduction. I support the argument that top-down inspection helps achieve resilience to climate change and reduce greenhouse gas emissions.

Urban energy performance improvement policy selection in China based on policy effect prediction: An analysis from the dimensions of economy, environment and well-being.

The environmental pollution and social well-being issue caused by the huge energy consumption in cities reflect the urgency of improving urban energy performance from multiple dimensions of economy, environment, and well-being. As a result, various countries and cities have promulgated a series of policies. However, the complexity of the policies makes the categories and utilities need to be further clarified, and the diseconomy caused by the lag of policy effect evaluation makes the focus of policy implementation need to be clear in advance. Therefore, based on public choice theory, this research follows the idea of "prior analysis" and takes Chinese cities as the research object. Firstly, the collected energy performance improvement policies of Chinese cities were analyzed and classified by the content analysis method, and the main utilities of all policies and the specific utilities of each category were summarized. Based on the multiple dimensions of urban energy performance research (namely, economy, environment and well-being dimensions), this research summarized the policy utilities that help to improve the urban energy performance of each dimension, and also preset the policy utility values. Secondly, the effect prediction model for urban energy performance improvement policies in each dimension was constructed by Back-propagation (BP) neural network. Thirdly, the energy performance of Chinese cities in 2020 measured by Data Envelopment Analysis method was taken as the benchmark value, and the energy performance of Chinese cities in 2025 measured by the policy effect prediction model was taken as the comparison value. According to the results of performance improvement, the energy performance improvement policies of Chinese cities were selected respectively from the dimensions of economy, environment and well-being. This research shows that: the energy performance improvement policies of Chinese cities mainly include six categories, namely energy conservation and emission reduction policies, energy development policies, ecological environmental policies, fiscal and tax policies, industrial policies and economic and social policies. It is needed to focus on ecological environmental policies, fiscal and tax policies and industrial policies to improve urban energy performance from the economic dimension. For the environmental dimension, the key and priority policies are ecological environmental policies. Compared with the economic dimension, the focus of implementing policies adds economic and social policies in the well-being dimension. In the implementation of policies, the differences of energy performance among cities can be reduced through multi-feature analysis of cities or regions, appropriate adjustment of specific measures and targets, and improvement of digital information management of urban energy performance. This research can effectively help cities clarify which policies require higher implementation intensity and attention before and during policy implementation, thereby maximizing multi-dimensional urban energy performance.

Energy transition and environmental stability prospects for OECD economies: The prominence role of environmental governance, and economic complexity: Does the geopolitical risk matter?

The global increase in temperature and climate change signals the need for humanity to reduce greenhouse gas emissions and to adopt eco-friendly lifestyles. The 2023 United Nations Climate Change Conference (COP28) in the UAE emphasized this, urging nations to commit to the Paris Agreement and pursue a greener, carbon-free future. In recent decades, climate change has become a critical issue, primarily because of the extensive use of fossil fuels and conventional energy resources. Economic growth has led to an increase in energy consumption and widespread environmental damage. The present study empirically explores whether any changes in environmental governance, economic complexity, geopolitical risk, and the interaction term influence energy transition and environmental stability in OECD economies over the period 1990-2021. Novel econometric methods, including Westerlund co-integration and the Method of Moments Quantile Regression (MMQR), are employed to address complexities such as cross-sectional dependency and panel causality. The key findings from the MMQR technique showed a positive link between environmental governance and economic complexity in driving sustainable energy transitions, thus bolstering environmental resilience in OECD countries. However, economic complexity counterbalances environmental stability. Significantly, geopolitical risk acts as a moderating variable, enhancing the effects of governance and complexity on sustainable energy practices and environmental stability. Based on these insights, this study recommends strategic initiatives, including investment in eco-friendly technologies, to fast-track the shift to clean energy and strengthen environmental resilience in OECD countries. These strategies align with the broader objectives of global sustainable development, offering a path towards a greener and more sustainable future.

Spatial disparities and sources analysis of co-benefits between air pollution and carbon reduction in China.

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.

Regional integration policies and urban green innovation: Fresh evidence from urban agglomeration expansion.

Climate change is a non-traditional security crisis affecting the global economy and diplomatic progress. In order to curtail carbon emissions and alleviate the perils of climate change at their roots, urban green innovation (UGI) has emerged as a pivotal technological solution. Using the expansion of the Yangtze River Delta urban agglomeration in China as a case study, this paper develops a quasi-experimental model to analyze the effects of regional integration policies on UGI. The main findings are: (1) Regional integration policies significantly enhance UGI and their impact is more pronounced with the expansion of urban agglomerations; (2) Regional integration policies contribute to the advancement of exploitative green innovation while tending to diminish exploratory green innovation; (3) The green innovation effects (GIEs) created by the expansion of regional integration policies are largely influenced by governmental mechanisms on environmental governance as well as residents' green preferences. Based on these findings, recommendations are put forward to promote UGI from the perspective of policy implementation.