Based on the land use data, natural socio-economic data and carbon emission data of the main urban area of Chongqing, the land use transfer matrix and the PLUS (Patching-generating Land Use Simulation) model were used to analyze the spatial evolution characteristics of urban expansion in the main urban area of Chongqing from 2000 to 2020. The development scenarios of the natural state, urban expansion and ecological protection in 2030 were simulated under the influence of endogenous driving factors. The response relationship between land use change and carbon emissions in the study area from 2019 to 2022 was analyzed based on the Generalized Additive Model (GAM), and the total carbon emissions under the three scenarios were calculated. From 2000 to 2020, the cultivated land in the study area decreased by 928.82km², while the construction land increased by 858.30km². A large amount of cultivated land was transferred to the construction land, and water areas, forest land and grassland underwent in a certain degree of dynamic change. Urban expansion is influenced by a combination of natural and socio-economic factors, with the main driving factors including elevation, distance from water areas and distance from Grade 1roads. External policy-driven factors also have a significant impact on urban expansion. From 2020 to 2030, the main urban area of Chongqing will continue to experience in a rapid urbanization process. The direction of urban expansion will mainly be eastward and westward, while the expansion direction of forest land and grassland will be opposite to that of urban expansion. The impact of changes in land use structure on carbon emissions is mostly nonlinear, and there may be potential threshold areas. Forest land, water and cultivated land show non-linear relationships, while grassland and construction land show linear relationships. Based on the land use structure of three scenarios in the study area in 2030, it is estimated that the carbon emissions of the land use structure in study area of Chongqing in 2030 will be 59.2995million tons of C/a, 62.0677million tons of C/a, and 58.2041million tons of C/a respectively.

In Chongqing's composite ecosystem of Mountains, Rivers, Forests, Farmlands, Lakes, and Grasslands (CEMRFFLG), the embodied carbon of four subsystems (farmland, grassland, forest, and water) was quantified using Multi-Regional Input-Output (MRIO) and Partial Least Squares Structural Equation Modeling (PLS-SEM) approaches. The flows of embodied carbon among these subsystems were analyzed within a metacoupling framework, and their driving mechanisms were systematically explored. The results indicated that: (1) In 2020, embodied carbon of CEMRFFLG subsystems in Chongqing ranked as farmland > grassland >forest > water, with the farmland subsystem accounting for 68.88% of the total; (2) The embodied carbon inflow to the CEMRFFLG of Chongqing was 3.45 times greater than its outflow, exhibiting a distinct net-input characteristic; (3) Direct carbon flows were characterized by inflow and outflow contribution rates from distant systems of 99.28% and 78.82%, respectively, indicating predominance of long-distance transmission. Conversely, embodied carbon flows presented a distinctive structural pattern of "remote inflows and proximate outflows," wherein distant systems contributed 85.61% of inflows and adjacent systems received 91.36% of outflows; (4) Among all factors, the consumption level showed the strongest positive influence on embodied carbon flows of CEMRFFLG, with a path coefficient of 0.845. A comparative analysis of direct and embodied carbon flows provides a scientific basis for optimizing embodied carbon flow reduction strategies in Chongqing's CEMRFFLG, offering significant implications for achieving green development of composite ecosystem patterns.

Based on the input-output method, this study utilized the Eora database to assess carbon emissions and interregional transfer patterns within the manufacturing industry and its sub-sectors across the Belt and Road Initiative (BRI) countries from 2007 to 2017. The structural decomposition analysis was employed to identify the key driving factors underlying changes in embodied carbon emissions, while the effects of five distinct trade-related mechanisms on the embodied carbon emissions within industrial chains of key BRI countries were explored in depth. The results indicate that embodied carbon dioxide emissions within the manufacturing industry along the BRI increased by 25.19% over the study period, while a net emission reduction of 361.09Mt was achieved, reflecting a transition towards a consumption-driven emissions structure. Embodied carbon dioxide emissions within the manufacturing sector have increasingly shifted from mid-end manufacturing industries, such as Petroleum, Chemical and Non-Metallic Mineral Products(C7), Metal Products(C8), and Electrical and Machinery(C9) to downstream sectors, including Agriculture (C1), Food and Beverages (C4), C9, and Construction (C14). In addition, the embodied emission outflows from upstream energy industries, particularly Electricity, Gas and Water (C13), to manufacturing industries such as C4and C9has intensified. Therefore, the development of the manufacturing sector along the BRI needs to place greater emphasis on cross-border collaborative emission reduction across upstream and downstream industries. For the manufacturing industry as a whole in the BRI region, the per capita demand effect was the dominant factor of embodied carbon emissions, contributing an increase of 4323.27Mt, while the emission intensity effect exerted a substantial mitigation influence, reducing emissions by 3199.96Mt. Although the key drivers of embodied carbon emissions differ across major BRI countries, the forward linkage effect universally promotes emissions, while the backward linkage effect suppresses them. This contrast underscores the critical importance of developing green supply chains within international trade networks. Accordingly, this study proposes targeted policy recommendations for the low-carbon transition of the manufacturing industry along the BRI, highlighting the need for differentiated emission reduction strategies tailored to national and sectoral conditions.

Current research on the synergistic reduction of pollution and carbon emissions emphasizes "synergy" while neglecting "effectiveness," limiting a systemic understanding. This study aims to integrate and analyze bibliometric findings, further discussing the connotation and mechanisms of "efficiency enhancement". The results reveal that:(1) Research on synergistic pollution-carbon reduction remains in the early exploratory stage, with hotspots focusing on four phases: quantitative characterization of synergy, implementation pathways, feature analysis and effectiveness evaluation, and benefit assessment;(2) "Effectiveness" refers to the multi-dimensional benefits—environmental, ecological, economic, climatic, social, and health-related—triggered by pollution-and-carbon synergy at the systemic level, manifested as enhanced policy efficiency, reduced societal abatement costs, etc.;(3) The transition from multi-dimensional synergy to multi-dimensional effectiveness hinges on complex systems driven by multi-factor interactions, such as collaborative governance among stakeholders and regional joint prevention or control mechanisms. Future directions include: (i) clarifying the definition and consensus on "efficiency enhancement" to refine the systemic understanding of synergistic pollution-carbon reduction; (ii) investigating the scientific mechanisms linking multi-dimensional synergy to efficiency enhancement, thereby unveiling their intricate relationship.

Using A-share listed companies from 2012 to 2022 as the sample, this study employs the difference-in-differences method to examine the impact of carbon emission trading policies on corporate ESG performance and its underlying mechanisms. The findings reveal that the carbon emission trading policy significantly improves the ESG performance of enterprises in pilot regions. This conclusion remains robust after a series of tests, including parallel trend estimation, placebo tests, changes in the sample period, and propensity score matching. Heterogeneity analysis indicates that the policy has a more pronounced effect on enhancing ESG performance for firms in high-energy-consumption regions and those with larger asset scales, with the most substantial improvement observed in the intersection group of these two categories. Mechanism tests show that the policy promotes ESG performance by encouraging enterprises to increase long-term asset investment, thereby driving technological upgrades and green transformation. Based on these findings, policy recommendations are proposed, including improving the carbon market system, innovating carbon financial products, integrating carbon management into corporate ESG strategies, and strengthening financial incentive mechanisms.

To examine the impact of environmental regulations on corporate green innovation from the perspective of external attention, and to better promote the achievement of the "dual carbon" goal and high-quality economic development, this study took industrial enterprises listed on the Shanghai and Shenzhen A-shares from 2010 to 2022 as research objects, and used the difference-in-differences methodology to empirically analyze the impact of the implementation of the new environmental protection law on green innovation of heavily polluting enterprises. The study found that: (1) The implementation of the new environmental protection law was found to exert a significant inhibitory effect on the green innovation of heavily polluting enterprises, mainly reflected in its impact on the quantity of green innovation (2) From the perspective of the mechanism of external attention, analyst attention, institutional investor attention, and media attention were found to effectively mitigate the negative effects of the new environmental protection law on corporate green innovation (3) The impact of environmental regulations on corporate green innovation was shown to be heterogeneous across firms with different levels of digitalization, financing constraints, industry competition levels, and strategic orientations. The research results provide a new analytical framework and empirical basis for understanding the complex relationship between environmental regulation and corporate green behavior from an integrated "regulation-attention-innovation" perspective, offering implications for guiding corporate green transformation and building a multi-party governance system.

Based on big data retrieval of internet-reported risk incidents in municipal solid waste (MSW) landfills from 2004 to 2022 in China, landfill accident risks were statistically analyzed with a discrete binomial distribution probability mode. The aims were to clarify accident types, occurrence probabilities and trends, identify major risk sources, and propose targeted prevention measures, thereby providing a theoretical basis for landfill risk management. The results showed that a total of 128 MSW landfill accidents were reported, with annual occurrences exhibiting a fluctuating upward trend, peaking in 2021 before declining. The overall probability of landfill accidents was 1.92×10^-2, with the following distribution by type in descending order: environmental pollution incidents (with percentage of 52.34%, with probability of 1.0×10^-2), fires (13.28%, 2.54×10^-3), poisoning (10.16%, 1.95×10^-3), collapses (8.59%, 1.65×10^-3), other accidents (8.59%, 1.65×10^-3), and explosions (7.03%, 1.35×10^-3). Notably, Environmental pollution incidents were identified as the dominant accidents. To mitigate these risks, key measures include ensuring the quality of landfill engineering (such as seepage prevention system, drainage system and cover system et al.), improving leachate treatment facilities, enhancing landfill gas extraction and utilization, strict fire control, monitoring critical zones in real time, establishing emergency response systems, strengthening daily operational safety management, and promoting safety awareness.

The large-scale development of shale gas is vital for enhancing energy security and driving regional economic development, yet systematic studies on the potential pollution risks associated with shale gas extraction activities in karst regions remain scarce. This study, focusing on the Fuling shale gas extraction area in Chongqing, investigates heavy metal concentrations and their spatial distribution in soil and groundwater during April to June 2024. It aims to identify potential sources of heavy metals and assess their environmental impacts. Through source apportionment and pollution risk assessments, the study clarifies the contribution of shale gas extraction to changes in heavy metal concentrations in both soil and groundwater and evaluates the associated pollution risks. The findings reveal that while most heavy metals in the soil and groundwater do not show significant exceedances, slight exceedances of Cd, Pb, and As were observed in the soil. Notably, Ba and Sr exhibited substantial enrichment and high spatial variability, with the average Ba concentration in soil reaching 561mg/kg, nearly twice the regional background level. The pollution indices for Ba, Sr, Cd, and Cu in soil were 3.08, 2.07, 1.42, and 1.21, respectively, indicating that shale gas extraction plays a key role in the accumulation of Ba and Sr in the environment. Furthermore, strong correlations (0.84, 0.78, and 0.76) between Cu, Sr, and Ba in both soil and groundwater suggest a common source for these metals. Source apportionment using APCS-MLR and PMF models revealed that agricultural, natural, shale gas extraction, and industrial sources contributed 17.1%, 28.1%, 15.4%, and 39.4% of the heavy metals in the soil, with shale gas extraction accounting for 50.9% and 47.4% of the Ba and Sr concentrations. In groundwater, shale gas extraction contributed 14.6% of the heavy metal concentrations, with Ba contributing as much as 30.3%. Overall, while the pollution levels in the soil-groundwater system of the Fuling shale gas extraction area are relatively low, the localized enrichment of Ba and Sr presents potential ecological risks. These findings provide a scientific basis for environmental monitoring and risk management of shale gas extraction in karst regions.

The research progress of high background of soil heavy metals related to carbonate rocks was systematically reviewed from the aspects of spatial distribution, element combination, spatial coverage, controlling factors, formation process, and risk characteristics. At present, it was generally believed that the main causation for the formation of this type of high background was the "secondary enrichment" of elements in the weathering process of parent rock, that is, the leaching of major elements, e.g. Ca, caused the relative enrichment of trace elements, e.g. Cd. In this process, iron and manganese minerals played an important role in the in-situ concentration of these elements. From the geographical perspective, the hot and humid climate was conducive to the formation of a higher background content. In general, Cd and other elements in soil developed from carbonate eluvium had the character of "high background with low activity", while in the alluvial areas formed by carbonate weathered materials, high acid soluble state of Cd might have occurred with risks of activation under conditions such as soil acidification. With high spatial variation of soil heavy metals in such areas, especially in the medium and small spatial scales, problems such as differentiation between natural background and anthropogenic pollution, quantitative recognition of relative risks, and development of control measures for environmental management, were required to be solved in the future study.

Quantifying Hg flux in lake systems remains challenging due to the synergistic influences of multiple environmental drivers. To address this, we investigated Changshou Lake, an artificial reservoir situated in a karst region, through an integrated approach that included field sampling, path analysis, and machine learning, to elucidate the mechanisms of Hg flux exchange. The results indicated that Hg flux was jointly regulated by multiple factors via both direct and indirect pathways. Water Hg concentration (0.897), UV radiation (0.463), and solar radiation (0.446) were identified as exerting dominant direct effects on the production of dissolved gaseous mercury (DGM, Hg⁰). In contrast, the influence of wind speed on Hg flux was observed to be stronger through its indirect enhancement of solar radiation (0.252) than through direct diffusion (0.197). A hybrid machine-learning prediction mode [0.9 Gradient Boosting Regression (GBR) + 0.05 Random Forest (RF) + 0.05Support Vector Regression (SVR)] was developed. This model was shown to improve generalization ability and stability while maintaining predictive accuracy, enabling dynamic prediction of Hg flux under the coupling of multiple lake parameters. The approach provides decision support for regional Hg risk assessment and management.