This study establishes a carbon emission reduction measurement model for the secondary ash recycled ceramsite project from the perspective of carbon footprint, combined with the National Certified Voluntary Emission Reduction (CCER) methodology. Taking the 40000 tons/year secondary ash recycled ceramsite project as an example, empirical analysis is conducted to evaluate the project's carbon emission reduction. Based on the analysis of key carbon emission factors, the carbon emission reduction potential of the secondary ash recycled ceramsite project is optimized and evaluated. The results show that the total CO₂e emission reduction of the 40000 tons/year secondary ash slag regenerated ceramsite project in 2023 is 32600 tons, of which the ceramsite production stage contributes to 95% of the emission reduction. From the perspective of carbon footprint analysis, the total annual CO₂e emissions of the project are about 64900 tons, and the processing, production, and raw material acquisition stages are key links in the carbon emissions of the ceramsite project. From the analysis of CO₂ emission source categories, the substitution of solid waste materials such as secondary ash and sludge is the key to carbon reduction in the ceramsite industry. In addition, the priority order of adding solid waste materials is secondary ash, sludge, and waste soil. Regarding the optimization of carbon emission reduction potential, under four low-carbon scenarios of green raw materials, clean power grid, low-carbon transportation, and recycling, the secondary ash regenerated ceramsite project achieved CO₂e emission reductions of 69300, 34200, 35600 and 32800 tons, respectively. Under the green raw material scenario, the ceramsite industry has a carbon emission reduction potential of 9million tons.

To investigate the environmental behavior of organophosphate esters (OPEs) in the surroundings of the electronics industry, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to determine the concentration levels of 18 OPEs in soil, atmospheric, and wastewater samples, which were collected from surrounding areas of typical electronic industry enterprises in Shenzhen. Correlation analysis and principal component analysis (PCA) were applied to identify pollution sources, and the health risk levels of people of different age groups were evaluated. The results indicated that the detection rates of 18 OPEs in various environmental media were found to range between 40.9% and 100.0%. In 34 soil samples, 21 atmospheric samples, and 30 wastewater samples, the mean concentrations of ∑18 OPEs were determined to be 283ng/g (12.2~857ng/g), 4.48×10⁵ pg/m³(3.12×10³~2.95×10⁶ pg/m³), and 1.11×10⁶ ng/L (5.39×10⁵~2.73×10⁶ ng/L), respectively. Tris(2,4-di-tert-butylphenyl)phosphate (AO168=O), tris(4-tert-butylphenyl) phosphate (T4tBPP), tris(2-chloropropyl) phosphate (TCPP), and bisphenol A bis(diphenyl phosphate) (BPADP) were identified as the predominant OPEs across all media. The correlation and principal component analysis (PCA) results demonstrated that OPE contamination in the vicinity of electronic industry enterprises was predominantly influenced by industrial production emissions and traffic-related discharges. Non-carcinogenic and carcinogenic health risks associated with multi-pathway exposure to OPEs in soil and atmospheric media across different age groups were found to remain within acceptable thresholds; however, the health risks posed by long-term cumulative OPE exposure were identified as requiring sustained scientific attention.

This study systematically investigated the synergistic interactions between biochar and the model electroactive microorganism Shewanella oneidensis MR-1 in electron transfer processes through comprehensive electrochemical analyses, kinetic modeling, and electron pathway characterization using chromium(VI)-contaminated soil as the experimental matrix. The biochar-based microbial agents demonstrated effective Cr(VI) bioremediation, with biological reduction mediated by MR-1identified as the predominant mechanism following dual-process kinetics. Optimal remediation performance (96.30% Cr(VI) reduction efficiency) was achieved under conditions of 25mg/kg Cr(VI) contamination, 5% (w/w) biochar-based microbial agents dosage, and 30% soil moisture content. Comparative analysis revealed distinct temporal remediation patterns: adsorption-based biochar-microbial composites exhibited rapid initial Cr(VI) sequestration but limited long-term stability, whereas encapsulation-based formulations showed gradual but sustained reduction capacity. Mechanistic studies demonstrated that biochar functioned as an effective microbial carrier, simultaneously enhancing MR-1proliferation and facilitating extracellular electron transfer from microbial cells to Cr(VI) contaminants through its conductive carbon matrix. Notably, the immobilized system maintained 60.44% reduction efficiency after three operational cycles, highlighting its potential for sustainable in situ remediation of chromium-contaminated soils.

This article constructed a multidimensional urban sprawl measurement index system from the structural dimension, morphological dimension, density dimension, and efficiency dimension. Based on map visualization, standard deviation ellipse, and cold and hot spot analysis, it explored the spatiotemporal characteristics and migration evolution patterns of China's urban comprehensive sprawl from 2005 to 2020. The spatiotemporal geographically weighted model (GTWR) was used to empirically examine the spatiotemporal heterogeneity of the impact of multidimensional urban sprawl on carbon emission intensity. Research shows that: (1) The comprehensive urban sprawl in China exhibited a spatial difference of "high in the east and low in the west", but the urban sprawl in the eastern coastal and northeastern regions has declined in the later stage of the sample. The standard deviation ellipse shows a trend of centripetal clustering, and the center of gravity of the distribution shifts towards the southwest as a whole. The analysis of hot and cold spots presents regional differences of "hot in the east and cold in the west". (2) The overall urban sprawl has a significant impact on carbon emissions, and over time, it plays a positive promoting role in an increasing number of cities. The positive promotion area is mainly concentrated in the central and western regions and coastal areas, while the negative inhibition area is mainly the North China Plain and the Pearl River Delta. (3) There is significant spatiotemporal heterogeneity in the influencing factors of each dimension. In terms of temporal trends, the structural dimension promotes carbon emissions in most cities and its influence increases year by year; The form dimension has shifted from a promoting effect to a inhibiting effect on carbon emissions in most cities; The density dimension and efficiency dimension suppress carbon emissions in most cities, but the density dimension shows a polarization trend year by year, while the influence of the efficiency dimension weakens overall. In terms of spatial distribution, the influence of structural dimension and density dimension is stronger in the southeastern, western, and northeastern regions, while the significant effect of morphological dimension is in the northeastern border and central western regions, and the significant effect of efficiency dimension is in the central and western regions.

Based on the super-efficiency SBM model to measure the carbon emission efficiency (CEE) of China's chemical industry across 30 provinces from 2007 to 2021, this study employs spatial analysis methods and kernel density estimation to characterize the spatiotemporal evolution patterns of CEE at both the national and regional levels. Furthermore, a Tobit regression model is applied to identify its influencing factors. Although the CEE of China's chemical industry exhibited a fluctuating upward trend during the study period, the overall level remained relatively low, with a mean value of 0.629. Moreover, a persistent regional disparity was observed, following the order of eastern China (0.750) > western China (0.584) > central China (0.530). The spatial distribution of CEE ultimately displayed a "southwest-northeast" orientation, with significant shifts in spatial patterns gradually forming a "tripartite balance" structure, though most regions remained at low efficiency levels. Additionally, the mean Gini coefficient was 0.322, indicating substantial spatial heterogeneity overall. The CEE in eastern China surpassed that of the central and western regions, with hypervariable density identified as the primary source of regional disparities. The overall evolutionary trend of CEE in the chemical industry was positive, with interprovincial gaps gradually narrowing. While the trends in eastern, central, and western China were generally favorable, attention should be paid to the increasing divergence in the western region. Industrial agglomeration, energy structure, and economic development level significantly promoted CEE, with the energy structure of the chemical industry having the strongest impact which coefficient is 0.9942. Therefore, the government should prioritize optimizing the energy structure of the chemical industry while fully leveraging the positive effects of industrial agglomeration and regional economic development. Additionally, enhancing interregional collaboration and formulating region-specific policies are crucial for further improving the CEE of the chemical industry.

To address the problems of traditional methods lacking the characterization and assessment of internal environmental risks in chemical industrial parks, having single assessment indicators, and not considering the factor of risk prevention and control capabilities, a refined assessment method for sudden environmental incidents at the scale of chemical industrial parks was proposed based on the grid-based risk analysis method for sudden environmental incidents in administrative regions. This method refines the risk unit grid, optimizes the environmental risk field intensity model, improves the vulnerability standards for environmental risk receptors, and introduces a correction factor representing the level of environmental risk prevention and control. Taking a certain fine chemical industrial park along the Yangtze River in Jiangsu Province as an example, environmental risk assessments were conducted and compared using the original assessment method and the refined assessment method. Compared with the original assessment method, the refined assessment method better characterized the distribution of atmospheric and water environmental risks within the park. The number of people involved in the high-risk and medium-risk areas of the atmospheric environment in the study area increased by 17,000, and the areas of high-risk and high-medium-risk areas of the water environment increased by 0.91% and 9.45% respectively. This method can effectively establish the connection between environmental risk assessments at different scales such as chemical industrial parks and environmental risk enterprises, more accurately identify high-risk enterprise units and environmental receptors, and ensure the safety of the internal population and key water bodies in the park.

This study centers on environmental regulatory policies, employing a two-way fixed effect model to scrutinize their impact, underlying mechanisms, and theoretical implications on new quality productivity enhancement. A U-shaped correlation exists between environmental regulations and the enhancement of new quality productivity. Beyond a critical turning point, a 1% escalation in vertical environmental regulation intensity correlates with a 124.42% augmentation in high-quality economic development. Environmental regulations significantly bolster the advancement of new quality productivity levels in both eastern and western provinces of China. Environmental regulations serve as a catalyst in amplifying the mechanisms fostering new quality productivity, particularly by influencing the "new labor tools" and "new infrastructure" subsystems.

This study analyzed the carbon reduction effect of national green data centers on cities and its mechanism. Then, based on the pilot and construction work of national green data centers, a quasi-natural experiment was constructed. Using the difference-in-differences method and panel data of 283 cities from 2011 to 2022, the carbon reduction effect of national green data centers was empirically analyzed, and its mechanism and heterogeneity were explored. The pilot of national green data centers has a significant carbon reduction effect, with a coefficient of -0.013, which is significant at the 5% statistical level. The pilot of national green data centers significantly reduces the carbon emission intensity of cities. This result remains valid after multiple robustness tests, including parallel trend tests, placebo tests, exclusion of selection bias, exclusion of the impact of other policies, and exclusion of the impact of the epidemic. The pilot of national green data centers can reduce the carbon emission intensity of cities by promoting the development level of the digital industry and the green technological innovation level of the region. The impact of the pilot of national green data centers on the development level of the digital industry and the green technological innovation level is significantly positive at the 1% statistical level, with coefficients of 0.039 and 0.061, respectively. The carbon reduction effect of national green data centers is more significant in non-energy-rich cities, cities with high environmental protection levels, and cities with high information levels. The impact of the pilot of national green data centers on these three types of cities is significantly at least at the 10% statistical level, with coefficients of -0.016, -0.017, and -0.016, respectively. Therefore, efforts should be made to promote the green transformation of data centers and expand the scope of the pilot of national green data centers.

The adaptive resilience of microorganisms is crucial for maintaining the stable operation of Biotrickling filters under intermittent flow interruption. This process is intrinsically related to the ability of microorganism to store active substances as Extracellular Polymeric Substances（EPS）. To elucidate this mechanism, a comparative analysis was conducted on biofilm structural characteristics, EPS compositional variations, and functional group transformations during an operation cycle of Biotrickling filters. The correlation between EPS-mediated stress response mechanisms and microbial activity maintenance/recovery was investigated. The results revealed that the removal of COD and NH₄⁺-N reached（95.56±1.10）% and（87.06±2.08）% respectively in the biotrickling filter operated under intermittent flow. Under the regulation of EPS, the biofilm showed a loose and porous structure. During flow interruption phases, microorganisms activated starvation adaptation strategies by converting carbon sources adsorbed in SB-EPS and metabolizing polysaccharides stored in SB-EPS. The structure integrity of microorganisms was maintained via synergistic effects of hydrophobic functional groups within EPS and polymer bridging interactions. Accordingly, an EPS-mediated stress adaptation system responsive to starvation-recovery alternations was established, enabling sustainable operation of Biotrickling filters.

To clarify the dissolution patterns of pathogenic microorganisms in rainwater runoff, a laboratory-simulated rainfall experiment was conducted to flush soil treated with earthworm castings. Propidium monoazide（PMA）combined with quantitative PCR（qPCR）was used to investigate changes in the abundance of viable fecal indicator bacteria（FIB）. The results exhibited that after rainfall, the concentrations of electrical conductivity, ammonia, nitrate, and total phosphorus（TP）in the mixed soil matrix decreased by 51.34%, 45.20%, 99.09%, and 26.22%, respectively. In runoff water, the concentrations of ammonia, total phosphorus, and chemical oxygen demand（COD）exhibited a trend of initially rising and then falling, with peak values occurring within the first 15minutes. The qPCR quantification results for four fecal indicator bacteria—total coliforms（TC）, fecal coliforms（FC）, Escherichia coli（EC）, and Enterococcus spp（ES）—also displayed a similar trend of increasing and then decreasing. A significant positive correlation was found between the PMA-qPCR results and the culture method（Spearman r=0.723, P<0.001）. The fecal coliform counts in all runoff samples exceeded the limits specified in the "Surface Water Quality Standard"（40000CFU/L）. The study indicates that viable pathogenic microorganisms can be washed into water bodies through rainfall and are widely dispersed during initial runoff, increasing the risk of their environmental transmission.