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Current Environmental, Social, and Governance (ESG) rating systems encounter challenges due to their subjectivity, time lag, and inconsistent coverage, which present significant obstacles for investors in the stock market. In contrast, news reporting data, characterized by its objectivity, timeliness, publicity, and sociality, has been a crucial source of quality market information for investors. The potential of ESG-related news as a robust complement to the data sources used in existing ESG rating systems merits further exploration. This study investigates the impact of ESG-related news on the Chinese stock market, with the goal of providing compelling evidence for integrating news media into ESG assessments. By analyzing 32,296 ESG-related news articles covering 3643 companies in the Chinese market from 2015 to 2021, we utilize event study methodology to assess the market's abnormal returns in response to ESG-related news. Our findings suggest a significant market impact from ESG-related news, indicating that investors are increasingly attentive to information pertaining to ESG issues. The study also reveals that different attributes of ESG-related news have diverse effects on the market. Specifically, news with negative sentiments has the most significant impact, and investors demonstrate a stronger reaction to ESG-related news disseminated through unofficial media. Furthermore, the study highlights that enterprise heterogeneity affects the impact of ESG-related news, with companies in the secondary and tertiary industries showing higher sensitivity. Privately-owned enterprises are found to be more influenced by such news compared to state-owned enterprises. This study offers a novel perspective in evaluating corporate ESG performance using news media, proposing a more effective and objective method to assess and manage corporate sustainability in a dynamic market landscape. • Significant impact of ESG-related news on Chinese stock market returns. • Diverse market reactions to varying ESG-related news sentiments and sources. • Stock response differs by company industry and ownership type. • Provides a basis for ESG-related news as a complementary tool in ESG ratings. [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]

Organic pollutants are important harmful components in atmospheric fine particulate matters (PM 2.5), health risks of which varied with temporal and spatial distributions. To clarify the characteristics of atmospheric organic pollution, the concentrations, sources, and human health risks of typical organic compositions in PM 2.5 samples from both industrial and urban areas of Nanjing in eastern China were investigated monthly for a year. Results showed that, the concentrations of PM 2.5 -bound polycyclic aromatic hydrocarbons (PAHs) and n-alkanes were higher in winter and spring than those in summer and autumn. The organic pollution was slightly higher in industrial than urban area, though the PAHs in autumn and the n-alkanes in warm season (summer and autumn) were higher in urban area. With regards to the pollutant sources, the atmospheric PAHs were dominated by motor vehicle exhaust in the urban area, and combined with coal combustion emission in the industrial area. Airborne n-alkanes were mainly from biological source accompanied by fossil fuel combustion in industrial area. The PM 2.5 -bound PAHs indicated higher risks to adults in industrial area than in urban area with the seasonal patterns: winter > spring > autumn > summer. More attention should be paid to the health risks of exposure to organic pollutants accumulated in PM 2.5 during cold season. Controlling vehicle emissions might be the key measure for alleviating atmospheric PAHs and n-alkanes pollution in megacities, while coal purification can be an effective control method in industrial areas. • Organic pollutants are typical harmful components in PM 2.5 • Concentrations, sources, and health risks of PM 2.5 show spatio-temporal patterns. • PAHs and n-alkanes pollution were serious in cold season and industrial area. • Vehicle emission is a key target for alleviating particulate organic pollution. • Coal purification can be an effective pollution control method in industrial area. [ABSTRACT FROM AUTHOR]

Decades of intensifying human activities have caused dramatic changes in land use and land cover (LULC) in the ecologically fragile areas of the Qinghai-Tibet Plateau, which have led to significant changes in ecosystem service value (ESV). Taking the ecologically fragile Sanjiangyuan region of the Qinghai-Tibet Plateau as the research object, we focused on understanding the impact of LULC changes on the Sanjiangyuan's landscape pattern and its corresponding ESV, which was combined with a Markov-Plus model to predict LULC changes in 2030. The results showed: (1) from 2000 to 2020, the LULC of Sanjiangyuan has changed to varying degrees, respectively. In the central and southern regions where animal husbandry is the mainstay activity, the area of grass land converted to bareland had expanded; (2) from 2000 to 2010, the total regional ESV increased sharply. However, the total amount of ESV decreased from 2010 to 2020; (3) the overall ESV in the study area was observed to be trending down and is expected to decrease by approximately 4.25 billion CNY by 2030; (4) the fragmentation and complexity of regional landscape patterns will negatively affect local ecosystem stability and biodiversity. Overall, there is a strong temporal and spatial correlation between LULC and ESV. This study will provide a reference for the local government to provide targeted and sustainable land management policies, thereby promoting the improvement of the Qinghai-Tibet Plateau regional ecology value. • ESV in ecologically fragile areas was affected by human activities. • ESV had strong spatial and temporal differences in Sanjiangyuan region. • Bareland and artificial surface had expanded in Sanjiangyuan region in the past few decades. • LULC combined with landscape index can explain ESV spatiotemporal changes. [ABSTRACT FROM AUTHOR]

A high-resolution nutrient emission inventory can provide reliable and accurate identification of priority control areas, which is crucial for efficient decisions on water quality restoration. However, the inventories widely used in large-scale modeling are usually based on provincial inputs, which induce the challenges of lacking localized parameters and missing localized characteristic when provincial scale inputs are converted to finer scales with the down-scale methods. Based on elaborate investigations and statistical data at the county scale with multi-scale data conversion, the China Emission Inventory of Nutrients (CEIN) was developed with a spatial resolution of a 0.1° grid and sub-basin scales. The Yangtze River Basin was used as a case study to illustrate the potential applications of CEIN. The emissions of total nitrogen (TN) and total phosphorus (TP) of Yangtze River Basin is 0.43 Mt and 0.04 Mt for point sources, 11.09 Mt and 4.64 Mt for diffuse sources in 2017. The hotspot analysis for 2606 sub-basins indicated that cropland is the key source of nutrient emissions, accounting for 58.88% and 79.15% of TN and TP, respectively. Industrial sewage and freshwater aquaculture accounted for 27.39% (TN) and 21.98% (TP) of the point sources, which is substantial due to their direct discharge into surface waters. The current results also reveal that, in contrast to CEIN, the previously used common emission factors based on GDP per capita produced considerable overestimations of 2.37 and 2.65 times the actual TN and TP emissions, respectively. Additional advantages of the CEIN have been demonstrated in identifying priority control areas more accurately with reduced bias and quantifying the effects of policies at much smaller scales. For example, the CEIN helps to distinguish hotspots, which was neglected when identifying sources at the level-III sub-basin scale, and indicates that the management of fractional areas (TN: 16.97%; TP: 13.44%) provides the highest nutrient emissions control (TN: 44.34%; TP: 48.65%) for the entire basin. The evaluation of China's toilet revolution policy demonstrates that achieving equitable access to safe sanitation has resulted in a reduction of 7240 t of TN and 833 t of TP, which is extremely critical for rural water quality and health. [Display omitted] • High-resolution China Emission Inventory of Nutrients (CEIN) is developed with 0.1° grid. • Priority control areas were identified for 2606 sub-basins in the Yangtze River Basin. • Previous emission factors with GDP per capita produced considerable overestimations. • CEIN can quantify effects of policies at much smaller scales with reduced bias. [ABSTRACT FROM AUTHOR]

This study offers an insightful and detailed examination of microplastic pollution in the Huixian karst wetland's groundwater, providing novel insights into the complex interplay of microplastic characteristics and their seasonal dynamics. We meticulously quantified microplastic concentrations, observing significant seasonal variation with values ranging from 4.9 to 13.4 n·L−1 in the wet season and 0.53–49.4 n·L−1 in the dry season. Our analysis pinpoints human activities and atmospheric deposition as key contributors to this contamination. A critical finding of our research is the pronounced disparity in microplastic levels between open wells and covered artesian wells, highlighting the vulnerability of open wells to higher pollution levels. Through correlation analysis, we unearthed the crucial influence of the karst region's unique hydrogeological characteristics on microplastic migration, distinctively different from non-karst areas. The karst terrain, characterized by its caves and subterranean rivers, facilitates the downward movement of microplastics from surface to groundwater, exacerbating pollution levels. Our investigation identifies agricultural runoff and domestic wastewater as primary pollution sources. These findings not only underscore the urgent need for environmental stewardship in karst regions but also provide a crucial foundation for formulating effective strategies to mitigate microplastic pollution in karst groundwater. The implications of this study extend beyond the Huixian karst wetland, offering a template for addressing microplastic pollution in similar ecosystems globally. [Display omitted] • Provides detailed analysis of microplastic types and properties in the groundwater environment of a karst wetland protection area. • Uncovers distinct seasonal patterns in microplastic concentrations in karst underground waters. • Reveals a close link between surface and underground water microplastics in karst ecosystems. • Highlights the need for targeted strategies to mitigate microplastic pollution's environmental and health impacts. • Local residents may be exposed to 27 microplastic particles daily via drinking water. [ABSTRACT FROM AUTHOR]

The environmental pollution of water is one of the problems that have plagued human society. The bimetallic nanoscale zero-valent iron (BnZVI) technology has increased wide attention owing to its high performance for water treatment and soil remediation. In recent years, the BnZVI technology based on the development of nZVI has been further developed. The material chemistry, synthesis methods, and immobilization or surface stabilization of bimetals are discussed. Further, the data of BnZVI (Fe/Ni, Fe/Cu, Fe/Pd) articles that have been studied more frequently in the last decade are summarized in terms of the types of contaminants and the number of research literatures on the same contaminants. Five contaminants including trichloroethylene (TCE), Decabromodi-phenyl Ether (BDE209), chromium (Cr(VI)), nitrate and 2,4-dichlorophenol (2,4-DCP) were selected for in-depth discussion on their influencing factors and removal or degradation mechanisms. Herein, comprehensive views towards mechanisms of BnZVI applications including adsorption, hydrodehalogenation and reduction are provided. Particularly, some ambiguous concepts about formation of micro progenitor cell, production of hydrogen radicals (H ·) and H 2 and the electron transfer are highlighted. Besides, in-depth discussion of selectivity for N 2 from nitrates and co-precipitation of chromium are emphasized. The difference of BnZVI is also discussed. [Display omitted] • A review of the type of contaminants removed by bimetallic nanoscale zero-valent iron (BnZVI) is made. • The different synthesis and modification methods of BnZVI are reviewed. • The influence factors of contaminants removed by BnZVI are reported. • The multiple mechanisms of BnZVI with contaminants are discussed. [ABSTRACT FROM AUTHOR]

Accurately obtaining the pollution sources and their contribution rates is the basis for refining watershed management. Although many source analysis methods have been proposed, a systematic framework for watershed management is still lacking, including the complete process of pollution source identification to control. We proposed a framework for identification and abatement of pollutants and applied in the Huangshui River Basin. A newer contaminant flux variation method based on a one-dimensional river water quality model was used to calculate the contribution of pollutants. The contributions of various factors to the over-standard parameters of water quality sections at different spatial and temporal scales were calculated. Based on the calculation results, corresponding pollution abatement projects were developed, and the effectiveness of the projects was evaluated through scenario simulation. Our results showed that the large scale livestock and poultry farms and sewage treatment plants were the largest sources of total nitrogen (TP) in Xiaoxia bridge section, with contribution rates of 46.02% and 36.74%, respectively. Additionally, the largest contribution sources of ammonia nitrogen (NH 3 –N) were sewage treatment plants (36.17%) and industrial sewage (26.33%). Three towns that contributed the most to TP were Lejiawan Town (14.4%), Ganhetan Town (7.3%) and Handong Hui Nationality town (6.6%), while NH 3 –N mainly from the Lejiawan Town (15.9%), Xinghai Road Sub-district (12.4%) and Mafang Sub-district (9.5%). Further analysis found that point sources in these towns were the main contributor to TP and NH 3 –N. Accordingly, we developed abatement projects for point sources. Scenario simulation indicated that the TP and NH 3 –N could be significantly improved by closing down and upgrading relevant sewage treatment plants and building facilities for large scale livestock and poultry farms. The framework adopted in this study can accurately identify pollution sources and evaluate the effectiveness of pollution abatement projects, which is conducive to the refined water environment management. • A framework of pollution source identification and abatement is proposed. • Contaminant flux variation method was put forward for quantifying contribution. • Water quality scenarios models provide pollution management strategies. • Point source contributes the biggest for ammonia nitrogen and total phosphorus. • Impact from point sources on water quality was greater during the dry season. [ABSTRACT FROM AUTHOR]

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO 3 –N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts. • XGBoost-SHAP uncovers key drivers in semi-arid aquatic integrity evolution. • Innovative integration of XGBoost-SHAP with FCM maps aquatic spatial patterns. • AT dominates the distribution of aquatic biological integrity. • Distinct north-south trends in aquatic biological integrity of semi-arids revealed. [ABSTRACT FROM AUTHOR]

One critical question for water security and sustainable development is how water quality responses to the changes in natural factors and human activities, especially in light of the expected exacerbation in water scarcity. Although machine learning models have shown noticeable advances in water quality attribution analysis, they have limited interpretability in explaining the feature importance with theoretical guarantees of consistency. To fill this gap, this study built a modelling framework that employed the inverse distance weighting method and the extreme gradient boosting model to simulate the water quality at grid scale, and adapted the Shapley additive explanation to interpret the contributions of the drivers to water quality over the Yangtze River basin. Different from previous studies, we calculated the contribution of features to water quality at each grid within river basin and aggregated the contribution from all the grids as the feature importance. Our analysis revealed dramatic changes in response magnitudes of water quality to drivers within river basin. Air temperature had high importance in the variability of key water quality indicators (i.e. ammonia-nitrogen, total phosphorus, and chemical oxygen demand), and dominated the changes of water quality in Yangtze River basin, especially in the upstream region. In the mid- and downstream regions, water quality was mainly affected by human activities. This study provided a modelling framework applicable to robustly identify the feature importance by explaining the contribution of features to water quality at each grid. • A framework is advanced for improving the consistency of water quality attribution. • There was a significant improvement in water quality of the Yangtze River basin. • The contribution of drivers to water quality were evaluated at grid scale. • Air temperature was the main driver for water quality. • Measures to manage river water quality should consider climate warming. [ABSTRACT FROM AUTHOR]

China produces a large amount of industrial effluent with multiple pollutants contained, along with a flourishing economy. This study aims to examine the dynamics between China's industrialization and accompanying environmental pressure based on the gray water footprint (GWF) concept. A newly proposed net GWF (NetGWF) and the decoupling index (DI) are applied to evaluate China's industrial activities during 2002–2015 in different modes considering typical, all, and individual pollutants. The NetGWF dynamics are further quantitatively decomposed into 17 effects of not only commonly assessed drivers but also industrial fixed capital formation, inventory variation, and import, using an advanced dynamic decomposition analysis approach. Results show NetGWF is an effective indicator measuring domestic water pollution stress from industrialization, with NetGWF-AllPlt (estimated using all pollutants) validated to be more reliable and sensitive than NetGWF-COD&NH3N (estimated using Chemical oxygen demand and Ammonia nitrogen). An overall decoupling between China's industrialization and wastewater pollution is identified with most of DIs less than 1.0 caused mainly by decreased (by around 40%) industrial NetGWFs for 2002–2015. Industrial fixed capital formation and export have caused main components of China's industrial GWF, with proportions of 37.3% and 30.8%, respectively, followed by urban household consumption (16.8%). Volatile phenol, Petroleum, and Ammonia nitrogen are recognized as three decisive contaminants to the industrial NetGWFs. Technological development is the dominant contributor (−50%) to decreasing China's industrial NetGWFs, while fixed capital formation (18%) and export (16%) are principal drivers increasing the NetGWFs. Based on these, we expect to provide informative findings for building a pollution-decoupled industrialization. • NetGWF is effective in measuring domestic water pollution stress. • Implies an overall decoupling of industrialization and effluent pollution. • Industrial fixed capital formation and export are main sources of pollution stress. • Volatile phenol, Petroleum, and NH3N are decisive pollutants of NetGWF. • 17 drivers behind evolving industrial NetGWFs are quantitatively examined. [ABSTRACT FROM AUTHOR]