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Building on the resource-based view (RBV) theory, this paper aims to shed light on how does the implementation of green strategies affect enterprises’ performance. To distinguish the evolution of strategy implementation effect, we adopt a panel estimation strategy and gather data from 3869 listed companies in China from 2008 to 2019. Furthermore, we innovatively use the semi-supervised clustering algorithm to classify the companies according to whether they implement green strategies or not and then discuss long-term and short-term financial effects of implementing green strategies. Our study finds that the implementation of green strategy facilitates a company’s long-term performance but hampers its short-term performance. According to the moderating analysis, a green strategy could negatively impact a company’s financial performance by increasing debt ratios. The findings highlight the importance of implementing green strategies and the obstacles in the process of transforming enterprises to be green.Atmospheric CO2 source and sink is among the most debated issues that have puzzled climate change geochemist for decades. Here, we tested whether heavy metal pollutants in river sediments favor preservation of organic matter through shielding microbial degradation. We measured CO2 emission and extracellular enzyme activities at land-water interface (LWI) of 7 sites along a 285 km main stem of the Ganga River and 60 locations up- and downstream of two contrasting point sources discharging urban (Assi drain; Asdr) and industrial (Ramnagar drain; Rmdr) wastewaters to the river. We found the lowest CO2 flux at Rmdr mouth characterized by the highest concentrations of Cu, Cr, Zn, Pb, Ni, and Cd. The fluxes were relatively higher at locations up- and downstream Rmdr. Substrate induced respiration (SIR), protease, FDAase, and β-D-glucosidase all showed a similar trend, but phenol oxidase and alkaline phosphatase showed opposite trend at the main river stem and Asdr. Sites rich in terrestrially derived organic matter have high phenol oxidase activity with low CO2 emission. The CO2 emission in the main river stem showed curvilinear relationships with total heavy metals (∑THM; R2 = 0.68; p less then 0.001) and TOC (R2 = 0.65; p less then 0.001). The dynamic fit model of main stem data showed that the ∑THM above 337.4 µg g-1 were able to significantly decrease the activities of protease, FDAase, and β-D-glucosidase. The study has implications for understanding C-cycling in human-impacted river sediments where metal pollution shields microbial degradation consequently carbon and nutrient release and merits attention towards river management decisions.Environmentally persistent free radicals (EPFRs) are an emerging class of environmental hazardous contaminants that extensively, stably exist in airborne particulate matter and pose harmful effects on human health. However, there was little research about the sources of EPFRs in actual atmospheric conditions. This study reported the occurrence, characteristics, and sources of EPFRs and polycyclic aromatic hydrocarbons (PAHs) in PM2.5 collected in Dalian, China. The concentrations of PM2.5-bound EPFRs ranged from 1.13 × 1013 to 8.97 × 1015 spins/m3 (mean value 1.14 × 1015 spins/m3). Carbon-centered radicals and carbon-centered radicals with adjacent oxygen atoms were detected. The concentration of ∑PAHs ranged from 1.09 to 76.24 ng/m3, and PAHs with high molecular weight (HMW) were predominant species in PM2.5. Correlation of EPFRs with SO2, NO2, O3, and 12 kinds of PAHs indicated that both fuel (coal and biomass) combustion and photoreaction in atmosphere influenced the concentrations of EPFR. The positive matrix factorization (PMF) model results have shown that the primary sources contributed most of the EPFRs and those of secondary sources had a little proportion. Coal combustion (52.4%) was the primary contributor of EPFRs, followed by traffic emission (22.6%), industrial sources (9.6%), and secondary sources (9.2%) during the heating period, whereas industrial emission (39.2%) was the primary contributor, followed by coal combustion (38.1%), vehicular exhaust (23.5%), and secondary sources (9.6%) during the non-heating period. The finding of the present study provides an important evidence for further study on the formation mechanism of EPFRs in actual atmospheric to control the air pollution.Biochar-harbored zero-valent iron (ZVI/BC) has been extensively used to detoxify hexavalent chromium (Cr(VI)). However, the role played by biochar in promoting electron transfer of ZVI and Cr(VI) reduction was not fully uncovered. Herein, three biomass modeling components (cellulose, hemicellulose, and lignin) and their blends were utilized to synthesize ZVI/BC via co-pyrolysis with hematite. X-ray diffraction analysis showed that hematite was successfully reduced to ZVI in nitrogen ambience. Batch sorption experiment showed that mass ratio (hematite to lignocellulosic component) of 120 is most optimal for reduction of Cr(VI) by ZVI/BCs. ZVI supported by BC derived from cellulose, hemicellulose, and their binary mixture demonstrated better Cr(VI) removal capacity (23.8-38.3 mg g-1) owing to higher ordered and graphitic carbon structure as revealed by Raman spectrum. In addition, lower Tafel corrosion potentials and smaller electrochemical impedance arc radiuses were observed based on electrochemical analysis, suggesting their higher electrical conductivity and faster electron transfer, whereas the BCs derived from lignin and lignin-containing hybrids were not conducive to electron transfer of ZVI due to lower degree of graphitization, thus compromising Cr(VI) removal by ZVI/BC (7.7-17.7 mg g-1). As per X-ray photoelectron spectroscopy analysis, reduction, complexation, and co-precipitation were the main mechanisms for Cr(VI) removal. The present study provided a scientific evidence for screening plant-derived biomass feedstock with high contents of cellulose and hemicellulose and low lignin content to fabricate ZVI/BC to achieve high Cr(VI) removal.The evaluation of soil quality requires the use of robust methods to assess biologically based indicators. Among them, enzyme activities are used for several decades, but there is a clear need to update their measurement methods for routine use, in combining feasibility, accuracy, and reliability. To this end, the platform Biochem-Env optimized a miniaturized method to measure enzyme activities in soils using colorimetric substrates in micro-well plates. The standardization of the method was carried out within the framework of ISO/TC 190/SC 4/WG 4 “Soil quality – Biological methods” workgroup, recommending an inter-laboratory evaluation for the publication of a full ISO standard. That evaluation, managed by the platform, was based on the measurement, in six soils of contrasted physicochemical properties, of the ten soil enzyme activities described in the standard. Eight laboratories were involved in the validation study. Only 2.7% of outliers were identified from the analyses of the whole dataset. The repeatability and reproducibility of the method were determined by computing, respectively, the intra-laboratory (CVr,) and inter-laboratory (CVR) coefficients of variation for each soil and enzyme. HS148 chemical structure The mean CVr ranged from 4.5% (unbuffered phosphatase) to 9.9% (α-glucosidase), illustrating a reduced variability of enzyme activities within laboratories. The mean CVR ranged from 13.8% (alkaline phosphatase) to 30.9% (unbuffered phosphatase). Despite this large CVR noticed for unbuffered phosphatase, the method was repeatable, reproducible, and sensitive. It also proved to be applicable for measuring enzyme activities in different types of soils. These results have been found successful by ISO/TC 190/SC4 and resulted in the publication of ISO 201302018 standard.Based on panel data from 30 provinces in China from 2008 to 2017, this paper constructs a quantile regression econometric model to analyze whether China’s environmental regulation has an impact on export trade and to verify whether the Porter hypothesis has been valid in China in recent years. The results show that in the short term, environmental regulations have a restraining effect on export trade, while in the long run, due to the existence of innovation efficiency, environmental regulations will change from having a restraining effect to a promoting effect on export trade. Strict environmental regulations will reduce the production cost of Chinese products, further improve the export competitiveness of Chinese enterprises, and promote export trade. The empirical results verify the conclusion that the Porter hypothesis is confirmed in China. The following three suggestions are proposed for China’s exports to promote the win-win of China’s green development and export trade promote the realization of international and domestic double circulation, avoid becoming “pollution shelters” and support technological innovation in environmental protection industries.Soil salinization is recognized as a key issue negatively affecting agricultural productivity and wetland ecology. It is necessary to develop effective methods for monitoring the spatiotemporal distribution of soil salinity at a regional scale. In this study, we proposed an optimized remote sensing-based model for detecting soil salinity in different depths across the Yellow River Delta (YRD), China. A multi-dimensional model was built for mapping soil salinity, in which five types of predictive factors derived from Landsat satellite images were exacted and tested, 94 in-situ measured soil salinity samples with depths of 30-40 cm and 90-100 cm were collected to establish and validate the predicting model result. By comparing multiple linear regression (MLR) and partial least squares regression (PLSR) models with considering the correlation between predictive factors and soil salinity, we established the optimized prediction model which integrated the multi-parameter (including SWIR1, SI9, MSAVI, Albedo, and SDI) optimization approach to detect soil salinization in the YRD from 2003 to 2018. The results indicated that the estimates of soil salinity by the optimized prediction model were in good agreement with the measured soil salinity. The accuracy of the PLSR model performed better than that of the MLR model, with the R2 of 0.642, RMSE of 0.283, and MAE of 0.213 at 30-40 cm depth, and with the R2 of 0.450, RMSE of 0.276, and MAE of 0.220 at 90-100 cm depth. From 2003 to 2018, the soil salinity showed a distinct spatial heterogeneity. The soil salinization level of the coastal shoreline was higher; in contrast, lower soil salinization level occurred in the central YRD. In the last 15 years, the soil salinity at depth of 30-40 cm experienced a decreased trend of fluctuating, while the soil salinity at depth of 90-100 cm showed fluctuating increasing trend.Haze pollution is one of the most concerning environmental issues, and controlling haze pollution without affecting economic development is of immense significance. Using the panel data composed of PM2.5 concentration and other data from 278 cities in China between 2003 and 2016, this paper empirically investigates the impact of urban innovation on haze pollution and its transmission mechanism. Based on the fixed effect model, the research finds that increasing urban innovation significantly reduces haze pollution. Even after dealing with possible endogenous problems, the result still holds. Energy consumption and industrial agglomeration are two important transmission channels through which urban innovation affects haze pollution. Furthermore, time heterogeneity analysis shows that the negative effect of urban innovation on haze pollution increases with time. Spatial heterogeneity analysis shows that urban innovation has a more significant mitigation effect on haze pollution in eastern cities than in central and western cities in China.