Green finance reallocates capital toward environmentally sustainable activities, yet its real effects on entrepreneurial dynamism in emerging markets remain unclear. This paper examines how green finance affects city-level entrepreneurial dynamism in China, a large emerging-market economy where green finance has expanded rapidly under policy-guided financial development. Using a city-year panel of Chinese cities from 2010 to 2020, we estimate a quadratic two-way fixed-effects model to examine the nonlinear effect of green finance on entrepreneurial dynamism. The estimates reveal a rising-then-falling pattern: green finance promotes entrepreneurial dynamism at low and moderate levels, but its marginal effect declines and turns negative beyond the estimated turning point. Turning-point checks, marginal slope tests, and the Lind-Mehlum test further support this non-monotonic pattern. Mechanism analyses show that green finance operates through an innovation-financing channel and a brown financial lock-in reduction channel. Heterogeneity analyses indicate that the effect varies with financial development, environmental regulation, and resource-based city status. These findings suggest that green finance can foster entrepreneurial dynamism, but only when financial deepening is accompanied by diversified intermediation, transition-finance capacity, and local institutional conditions that prevent allocation rigidity.

Promotion of a fair and low-carbon transition is key to sustainable development. Energy quota trading policies (EQTP) are a crucial experiment in China's energy market reform, but their ability to provide a "dual dividend" of environmental control and income distribution improvement needs additional study. Using 2007-2022 city level statistics and micro-level data from Chinese listed businesses, this analysis treats the EQTP as a quasi natural experiment. A staggered DID model is used to evaluate the EQTP's influence on company and regional labor income share (LS). On average, the EQTP boosts firm-level LS by 2.34 %. Mechanism analysis shows that the "substitution effect" and "output effect" drive this growth. However, city-level study shows that the EQTP has no statistically significant influence on regional LS. To tackle this "micro-macro paradox," the study breaks down LS alterations. The decomposition results demonstrate that the substitution impact inside businesses increases LS most, but negative inter-firm resource allocation and firm exit effects in the aggregation process somewhat counteract this positive effect. Heterogeneity study shows that the EQTP has a greater distributional improvement effect in non-resource-based cities, non-former industrial bases, heavy-pollution industries, and high-tech sectors. This study offers policy ideas for carbon neutrality and factor allocation optimization.

China's large-scale cross-regional population migration has profoundly reshaped regional economic development and energy consumption patterns, thereby intensifying carbon intensity inequality across spatial dimensions. Within China's dual control framework for carbon emissions, understanding the mechanisms underlying carbon intensity inequality carries critical policy implications; however, the role of population migration in driving such inequality remains underexplored. Using panel data from 274 prefecture-level cities over 2008-2017, this study examines how population migration influences carbon intensity inequality through dual perspective of between cities and within cities, while unraveling its operational mechanisms. The findings demonstrate that population migration intensifies carbon intensity inequality both between and within cities, with amplified effects observed in low urban hierarchy, regions west of the Hu-Huanyong Line, and ordinary environmental protection status cities. Mechanistically, population migration exacerbates inequality indirectly through labor market reallocation and technological innovation, while environmental regulation counterintuitively amplifies this effect. Furthermore, significant spatial spillover effects emerge: population inflows into focal cities exacerbate intra-city carbon intensity inequality in neighboring cities. These findings advance our understanding of how migration shapes environmental inequality and provide important policy insights for designing spatially differentiated carbon reduction strategies.

As countries along the Belt and Road pursue green economic transformation, environmental total factor productivity (ETFP) has become a key indicator of green development performance, making the measurement and improvement of ETFP a pressing priority. This study evaluates the ETFP of 41 countries participating in the Belt and Road Initiative (BRI). We introduce a novel framework that combines the Green Luenberger Productivity Index with the Bi-weighted Modified Russell Model (BWMRM), treating carbon emissions as an undesirable output. The results show that although overall ETFP remains relatively low, it exhibits a clear upward trend driven primarily by technological progress and carbon emission reduction efforts. Notably, clean technology innovation contributes more to CO₂ reduction than structural energy adjustments. In addition, the input-output performance of labor exceeds that of capital and GDP, with significant regional disparities across countries. Based on these findings, we propose a four-dimensional policy framework. First, countries should establish a gradient mechanism for low-carbon transitions. Second, policymakers should optimize factor allocation to improve labor skills and the green use of capital. Third, fostering transnational green technology spillovers is essential for enhancing clean energy cooperation. Finally, governments should design differentiated, region-specific emission reduction strategies. Overall, this study provides both theoretical and practical guidance for advancing green development across BRI countries.

Natural gas serves as a bridging fuel in the transition of rural energy systems from coal to renewable energy. However, the transition generates notable economic impacts and unequal welfare effects across income groups. This study develops a regional Computable General Equilibrium (CGE) model with an extended income-expenditure module to evaluate the economic and environmental impacts of rural natural gas adoption in Beijing. The results show substantial reductions in pollutant emissions and improvements in energy efficiency, although the environmental benefits diminish over time. Household energy burdens increase unevenly across income groups, with middle- and higher-income households experiencing elevated burdens for 7–12 years, and low-income households facing more persistent pressures. GDP initially declines but gradually recovers as efficiency improvements emerge and industrial structures adjust. These findings highlight the importance of long-term targeted subsidies and complementary industrial policies in facilitating a sustainable energy transition.

As the economic green transition increasingly relies on frontier digital technologies, whether green finance reform can stimulate corporate artificial intelligence (AI) innovation (CAII) has become an important yet underexplored question. Using China’s Green Finance Reform and Innovation Pilot Zones (GFRIPZ) as a policy shock, we estimate a difference-in-differences model using data from Chinese listed firms over the 2014–2024 period and find that firms exposed to the pilot-zone reform exhibit significantly higher AI innovation. This result remains robust to multiple tests, and heterogeneity analysis shows that the statistical significance of the GFRIPZ effect on CAII is mainly driven by highly financially constrained firms and high-tech firms. The positive effect of the GFRIPZ on CAII is consistent with a credit availability channel, and analyst attention positively moderates the effect of the GFRIPZ on CAII. Our findings extend the literature on green finance reform by showing that it affects not only green outcomes in a narrow sense, but also risky frontier digital innovation within firms.

This study explores the role of corporate social responsibility (CSR) in enhancing environmental justice. We argue that CSR helps mitigate environmental injustice, a responsibility stemming from ethical considerations faced by corporations. Furthermore, building on previous studies that identify income disparity as the key factor contributing to environmental injustice, we find that regional economic growth, poverty alleviation among the rural poor, and the enhancement of political power are the primary channels through which CSR influences environmental justice. An analysis of Chinese listed companies provides evidence supporting our view, revealing a more pronounced mitigating effect of CSR on environmental injustice in non-state-owned, environmentally friendly, and large-scale firms. Notably, this contribution of CSR to environmental justice is more evident in the economically developed eastern region of China, which boasts a high level of marketization and a favorable business environment. This highlights the substantive role of CSR in environmental justice. By incorporating CSR into environmental justice studies, our research makes a meaningful theoretical advancement in understanding corporate ethical responsibilities and offers practical implications.

This paper employs regression discontinuity design (RDD) to scrutinize the influence of air pollution on innovation and entrepreneurship and further explores the underlying mechanisms. The findings indicate that: First, air pollution reduces urban innovation and entrepreneurship. Specifically, a 1% increase in PM2.5 concentration is associated with a decrease of 0.904% in the innovation and entrepreneurship index. Second, all entrepreneurship indicators and innovation metrics are susceptible to air pollution. For innovation in particular, the negative impact on invention patents, a form of substantive innovation, is relatively small. Third, the study further identifies key mechanisms through which air pollution impedes innovation and entrepreneurship, including physical discomfort, weakened social networks, and reduced interpersonal trust. Fourth, sectoral analyses indicate that the negative impact is more pronounced in knowledge-intensive industries. This study highlights the importance of air-pollution control for sustainable economic development.

The roof runoff coefficient (RC) is a key design parameter for roof rainwater harvesting systems (RRHS), traditionally estimated based on standard norms, yet often with limited accuracy. This study systematically investigates the variability of RC under different roof conditions and rainfall scenarios through simulated rainfall experiments and analysis of 116 observed rainfall events. Pearson correlation analysis, response surface methodology (RSM), and linear regression modeling were employed to evaluate the effects of rainfall intensity, roof slope, material, and area. Results indicate that rainfall intensity is the primary controlling factor of RC, with roof slope exerting a secondary but significant influence. A linear regression model based on rainfall depth (H), RC = 0.86 − 0.48 × 0.94H, was established, achieving a high predictive reliability with a Nash-Sutcliffe efficiency coefficient of 0.927. Application of this model in RRHS design optimized the required storage volume by 50.79

BACKGROUND:The new generation of network information technology has become a significant tool to promote public health. The application of information and communication technology (ICT) in the traditional medical industry has changed the medical service model, improved the public medical service system, and provided diversified medical services to the public. OBJECTIVE:This paper discusses the impact of ICT on residents' health, and analyzes the possible heterogeneity impact in different groups and its impact mechanism using the China Family Panel Studies (CFPS) data and a fixed-effects model. METHODS:The ordinary least squares estimation method was adopted to quantitatively identify the impact mechanism of ICT applications on residents' health. Multisource big data were collected, including the CFPS questionnaire (gender, age, marriage status, work status, income level, smoking, sports, and insurance participation), regional economic development, as well as service industry development. The quantitative phase involved conducting in-depth investigation across 25 Chinese provinces. Then, a quantitative analyse-based study empirically tested the effects of internet applications on residents' health by matching macro data and micro survey data. After controlling for these identified factors, the data were tested using ordinary least squares and fixed effect models, with the assistance of STATA version 14 to measure and validate the proposed model. RESULTS:The regression results support the conclusion that ICT can significantly improve residents' health (p < 0.001). After a series of robustness tests through replacing explanatory variables and choosing appropriate exogenous policy shocks, the results still hold. We analyse the possible heterogeneous effects and conclude that the health-promoting effect of ICT is stronger among middle-aged individuals, high-income groups, women, urban residents, unmarried individual, those who engage in sports and non-smokers. CONCLUSIONS:Our study confirms a significant association between ICT applications and residents' health and reveals substantial heterogeneity in this effect. It also provides insights into how to apply internet information to better realise disease surveillance and prevention goals.

Market-based environmental regulation has become an important institutional instrument in transitioning economies, yet its influence on firm-level behaviour remains insufficiently understood. This study examines whether China’s emissions trading scheme (ETS), as a newly established market institution, is associated with changes in corporate carbon behaviour by exploiting the staggered introduction of ETS pilot programmes as a quasi-natural experiment. Using panel data on 2,231 A-share listed firms across 221 Chinese cities from 2001 to 2020, we apply a staggered difference-in-differences (DID) framework, complemented by modern multi-period DID estimators, to examine whether ETS exposure is associated with changes in corporate carbon emissions (CE) and carbon attention (CA). We refer to this disclosure-based measure as carbon attention. CA is measured using a text-based indicator derived from firms’ annual reports, capturing an observable informational and behavioural response to carbon constraints rather than an intrinsic environmental preference. The results indicate that ETS implementation is associated with a statistically significant reduction in CE and a simultaneous increase in firms’ disclosure-based CA. These findings remain directionally similar across event-study tests, placebo experiments, synthetic control methods, and supplementary instrumental-variable checks. The transmission-related analysis provides suggestive association evidence that ETS exposure is accompanied by changes in internal information environments, internal-control and reporting-quality margins, managerial adjustment, profitability, and environmental expenditure. By jointly analysing emissions outcomes and disclosure-based behavioural responses, this study provides firm-level evidence on how market-based institutions are associated with firm-level adjustment along organisational and informational margins in a major developing economy.

Environmental decentralization, as a key institutional arrangement, holds significant potential to enhance corporate ESG performance. This study first proposes a theoretical model to assess the impact of environmental decentralization on corporate ESG performance, drawing on the principal-agent framework and Melitz’s (2003) heterogeneous firm model. Secondly, utilizing panel data from 280 Chinese cities and 2,930 listed firms, this paper explores the effect of environmental decentralization on corporate ESG performance through fixed effects model, staggered Difference-in-Differences, and Heckman’s two-stage model, among others. This research highlights the following main conclusions: First, environmental decentralization significantly enhances corporate ESG performance. Second, environmental decentralization improves corporate ESG performance through mechanisms such as local government environmental incentives, public environmental concern, investor attention, corporate green technology innovation, and corporate information transparency. Third, environmental decentralization exerts differential effects on corporate ESG performance depending on contextual factors.

As China pursues carbon neutrality by 2060, reconciling economic development with stringent climate goals has emerged as a central policy challenge. This study examines how economic growth can be aligned with ambitious decarbonization targets by evaluating the joint effects of emissions trading, coal consumption controls, and green investment incentives. Moving beyond analyses that consider these instruments in isolation, we employ a Computable General Equilibrium (CGE) model to assess their policy synergies. Long-term outcomes from 2020 to 2060 are projected using a hybrid ARIMA-LSTM framework. The results indicate that emissions trading policies exert a significant negative impact on economic output, while appropriate coordination with green finance policies can partially offset these effects. Policy implementation struggles to simultaneously achieve both economic growth and carbon reduction targets. However, it generally accelerates the timeline for phasing out coal. Moreover, controlling coal consumption is essential for achieving carbon neutrality. Policies featuring a lower proportion of auctioned allowances and stringent coal control measures effectively balance economic and environmental benefits.

Financing constraints remain an important barrier to technology-driven green development. Using a provincial panel of 30 mainland Chinese provinces from 2010 to 2023, this paper examines the relationship between technology finance and green development, focusing on green innovation, industrial restructuring, and regional variation. The results show a positive and statistically significant relationship between technology finance and GTFP-based green development. Further tests point to two main channels: green innovation and industrial restructuring. The relationship is stronger in provinces with weaker innovation capacity and in regions located southeast of the Hu Huanyong Line. These findings suggest that technology finance is not merely an additional source of capital. Its effectiveness depends on whether local economies can turn technology-oriented financial resources into green innovation and structural change.

Key digital technology (KDT) serves as a critical technological foundation for advancing pollution reduction and carbon mitigation (PRCM), while increasingly reshaping regional environmental governance capacity. However, the institutional fluctuations and governance uncertainties induced by intensifying climate risks have introduced both challenges and opportunities for the environmental effectiveness of KDT. Drawing on panel data from 276 prefecture-level cities in China between 2011 and 2021, this study investigates the impact of KDT on PRCM synergy across heterogeneous regional contexts. The findings reveal that KDT significantly enhances the degree of PRCM synergy, highlighting its dual environmental benefits. Moreover, climate risks play differentiated moderating roles in this process. Specifically, climate transition risks amplify the PRCM effect of KDT, reflecting the greater marginal adaptability of technological governance under institutional risk scenarios. In contrast, the overall moderating role of climate physical risks is limited. Heterogeneity analysis suggests that under transition risks, KDT possesses compensatory capacities to address institutional uncertainty, whereas under physical risks, its effectiveness is conditioned by regional structural characteristics and governance capacity. Mechanism analysis further demonstrates that KDT influences PRCM synergy through a chain pathway encompassing "source prevention-process control-end-stage blocking." Spatial effect analysis indicates a siphon effect of KDT, with significant negative spillovers on the PRCM synergy of adjacent regions, implying the risk of widening inter-regional disparities in environmental governance outcomes.

Managing climate risks has become a central challenge for rapidly urbanizing economies, yet empirical evidence on the effectiveness of large-scale adaptation policies remains limited. China’s Climate-Adaptive City Pilot Policy (CACP) is evaluated as a nationwide policy intervention to examine how adaptation-oriented governance influences urban climate risk management capacity. Drawing on panel data spanning 2010 through 2022 for 267 Chinese cities, we constructed an entropy-weighted urban ecological resilience (UER) index that proxies the extent to which cities can buffer, adjust to, and rebound from climate-induced risks, and we deployed a difference-in-differences design to gauge policy effectiveness. The empirical results indicate that rolling out the pilot scheme produces a meaningful uplift in cities’ capacity to govern urban climate risk. The effects display substantial heterogeneity across cities, reflecting differences in economic structures, geographic conditions, and governance capacities. Mechanism analyses indicate that the observed improvements may operate through multiple, interconnected pathways, including economic restructuring, energy transition, strengthened environmental governance, and the enhancement of ecological asset values. These pathways jointly reduce exposure to climate-related environmental risks while improving adaptive and recovery capacities. Overall, the findings suggest that climate adaptation policies can function as effective risk governance instruments that generate resilience-enhancing co-benefits. This study provides policy-relevant evidence on how adaptation-oriented urban governance can support climate risk management in rapidly urbanizing contexts.

Black carbon (BC) is a key short-lived climate pollutant and a toxic component of PM2.5. This review synthesizes global BC studies published since 2000 and evaluates its spatiotemporal distribution, source contributions, meteorological drivers, and health risks. The compiled evidence shows high concentrations are mainly found in South Asia and Africa, while low concentrations occur in Europe and North America. South American records were limited in the screened literature, and the apparent lower concentrations in this region may partly reflect sparse monitoring coverage rather than a regionwide low concentration pattern. Source evidence indicates that fossil fuel combustion is often important in urban and industrial regions, whereas biomass burning, residential solid fuel use, open waste burning, wildfire emissions, and agricultural burning can contribute substantially in fire affected and data sparse regions. Meteorological factors, including wind speed, boundary layer dynamics, and precipitation play a crucial regulatory role in the accumulation and removal of BC, driving its seasonal variations. The passive smoking equivalent results indicated that the mean decline in lung function associated with BC in children is approximately three times higher than that associated with low birth weight and cardiovascular mortality equivalents. The human health risk assessment results suggested that the lifetime carcinogenic risk of inhaling BC for adults was approximately 2.2 times that of children and was highest in rapidly industrialized areas and transportation hotspots. We further identified dermal exposure as a neglected pathway. This study provides a scientific basis for future global BC pollution control and public health protection.

Since the onset of economic reforms, the catering industry has been playing a crucial role in China’s economic development. However, due to the outbreak of the COVID-19 pandemic, the Chinese government has implemented strict pandemic prevention policies such as (home quarantine and suspending work and production facilities) leading to losses for a variety of industries, especially catering industry. As the main driving force on the demand side, residents’ willingness to pay for catering can play an important role in the post-pandemic economic recovery. In this study, we employ primary data of 1,072 respondents from an online survey to investigate the impact of influential factors on residents’ demand for catering services. A carefully designed structural equation model with 5 latent variables and 14 observed variables has been employed for data analysis purposes. The empirical results indicate that emotional value and policy norm have significant positive impacts on the residents’ willingness to utilize catering services, while personal perceived risk, catering industry status and economic cost have negative impacts. Based on empirical findings, essential and useful policy recommendations have been suggested in this study.

Forest-climate-economy relationships present critical challenges for climate mitigation in rapidly developing economies. While forests are traditionally viewed as carbon sinks, their effectiveness as tradable carbon products remains difficult to quantify in the near term due to time lags and scale mismatch with energy-driven emissions dynamics. This study examines these relationships in China using data from 30 provinces (from 2000 to 2019). Using LSTM-MLP hybrid models and multispatial Convergent Cross Mapping, we reveal what we term the "forest carbon paradox": despite China's extensive afforestation efforts increasing forest coverage significantly, these initiatives demonstrate limited immediate impact on CO2 emissions and GDP trajectories. Energy consumption variables, particularly electricity and natural gas, consistently emerged as the dominant drivers of both emissions and economic growth, while forest coverage showed minimal predictive power in our models. Causal analysis revealed asymmetric relationships: CO2 emissions strongly influenced forest coverage (0.88) versus weaker reverse effects (0.49), suggesting policy-driven afforestation responses rather than direct ecological feedback mechanisms. These findings highlight the need for paradigm shifts in forest carbon valuation strategies that account for temporal complexities in forest-economy-emissions relationships.