Contaminant characterization at pesticide production sites in the Yangtze River Delta: Residue, distribution, and environmental risk

Microbial community dynamics and bioremediation strategies for petroleum contamination in an in-service oil Depot, middle-lower Yellow River Basin

This study investigated soil and groundwater contamination at an in-service oil transportation station in the middle-lower Yellow River Basin, China. Spatial analysis combined with 16S rRNA and ITS sequencing revealed localized heavy metal (Cu, Ni, Cd, Pb) and petroleum hydrocarbon (PHs: 15.0 mg/kg) contamination in the oily sewage treatment area, with vertical migration constrained by silty sand layers. Volatile organic compounds (VOCs) primarily originated from oil tank emissions. Groundwater exhibited hydraulic gradient-driven downstream migration of PHs (0.03-0.04 mg/L) and arsenic (1.1-1.5 μg/L). Indigenous microbial communities exhibited redox-stratified functional differentiation: unclassified Comamonadaceae (Proteobacteria) dominated aerobic zones (monitoring well D5), utilizing nitrate for PHs degradation, while Desulfosporosinus (Firmicutes) mediated sulfate-coupled anaerobic alkane degradation and metal immobilization in anoxic zones (D6). Fungal communities featured Trametes (Basidiomycota), facilitating ligninolytic PAH breakdown via peroxidase secretion. Functional prediction (FAPROTAX/FUNGuild) confirmed a synergistic "fungal preprocessing-bacterial mineralization" mechanism. Microbial metabolic plasticity (e.g., nitrogen respiration, photoautotrophy) enabled adaptation to redox fluctuations. Given the site's medium-low risk profile, we proposed a tiered management framework: (1) in situ bioremediation that prioritizes indigenous microbes, (2) hierarchical risk zoning, and (3) dynamic monitoring networks. These strategies align with China's Green Low-Carbon Remediation principles through low-energy microbial technologies. The findings provide a mechanistic basis for balancing industrial operations and ecological health in the Yellow River Basin.

Biodegradation of CAHs and BTEX in groundwater at a multi-polluted pesticide site undergoing natural attenuation: Insights from identifying key bioindicators using machine learning methods based on microbiome data

Groundwater pollution, particularly in retired pesticide sites, is a significant environmental concern due to the presence of chlorinated aliphatic hydrocarbons (CAHs) and benzene, toluene, ethylbenzene, and xylene (BTEX). These contaminants pose serious risks to ecosystems and human health. Natural attenuation (NA) has emerged as a sustainable solution, with microorganisms playing a crucial role in pollutant biodegradation. However, the interpretation of the diverse microbial communities in relation to complex pollutants is still challenging, and there is limited research in multi-polluted groundwater. Advanced machine learning (ML) algorithms help identify key microbial indicators for different pollution types (CAHs, BTEX plumes, and mixed plumes). The accuracy and Area Under the Curve (AUC) achieved by Support Vector Machines (SVM) were impressive, with values of 0.87 and 0.99, respectively. With the assistance of model explanation methods, we identified key bioindicators for different pollution types which were then analyzed using co-occurrence network analysis to better understand their potential roles in pollution degradation. The identified key genera indicate that oxidation and co-metabolism predominantly drive dechlorination processes within the CAHs group. In the BTEX group, the primary mechanism for BTEX degradation was observed to be anaerobic degradation under sulfate-reducing conditions. However, in the CAHs&BTEX groups, the indicative genera suggested that BTEX degradation occurred under iron-reducing conditions and reductive dechlorination existed. Overall, this study establishes a framework for harnessing the power of ML alongside co-occurrence network analysis based on microbiome data to enhance understanding and provide a robust assessment of the natural attenuation degradation process at multi-polluted sites.

Simulation, prediction and optimization for synthesis and heavy metals adsorption of schwertmannite by machine learning

Due to its sea urchin-like structure, Schwertmannite is commonly applied for heavy metals (HMs) pollutant adsorption. The adsorption influence parameters of Schwertmannite are numerous, the traditional experimental enumeration is powerless. In recent years, machine learning (ML) has been gradually employed for adsorbent materials, but there is no comprehensive research on the Schwertmannite adsorbent. In this paper, 27 features and 814 groups of experimental data were used to systematically analyze the adsorption modeling of Schwertmannite first time. The results indicated that the adsorption capacity of Schwertmannite was better predicted by the Random Forest (RF) model (the R2 was 0.874). Then, the RF model was used to analyze the features importance that affects the adsorption of HMs by Schwertmannite. And the importance of Schwertmannite synthesis conditions, Schwertmannite characteristics, adsorption environment, and HMs properties were 11.88%, 30.01%, 48.26%, and 8.19% respectively. Moreover, the synthesis and adsorption conditions of Schwertmannite were predicted and optimized based on RF model, it was predicted that the better synthesis method of Schwertmannite was biological oxidation > Fe2+ oxidation > Fe3+ hydrolysis. Finally, a predictive Graphical User Interface Web Page for Schwertmannite-HMs was developed. We hope that this paper can promote the integration of machine learning and Schwertmannite.

Factors affecting distribution and ecological risk assessment of volatile organic compounds (VOCs) in groundwater of the Huazhou district in northwestern China

Volatile organic compounds (VOCs) pollution in groundwater is a significant global concern. In this study, 26 groundwater samples were collected from the unconfined aquifers in Huazhou District, northwestern China, to assess their distribution characteristics, influencing factors, and ecological risks across various geomorphological settings. The findings revealed 35 VOCs in collected groundwater samples, with aromatic hydrocarbons having the highest detection rate (100%), and the VOCs distribution exhibited significant spatial variations, with the highest VOCs concentration near a chemical plant on the inclined pluvial plain. The lithology and groundwater flow influenced the vertical and lateral transport of VOCs, with concentrations decreasing as the aquifer permeability decreases along the groundwater flow from the inclined pluvial plain to the river. The Mantel test was used to analyze the correlation between VOCs and environmental factors, geochemical analyses indicated that nitrate (NO3-) and sulfate (SO42-) served as electron acceptors in the anaerobic biodegradation of organic pollutants, with bicarbonate (HCO3-) levels increasing as a result of this biodegradation. Additionally, the curved streamline searchlight shaped model (CS-SLM) was applied to identify the primary land use types affecting VOCs content, construction land and cropland were primary land use types affecting VOCs distribution. Finally, the ecological risk assessment indicated the highest risk quotient (RQ) for styrene (0.21), suggesting a manageable risk level. The study emphasizes the complexity of VOCs contamination in groundwater, providing a foundation for targeted mitigation strategies.

Unraveling soil geochemical, geophysical, and microbial determinants of the vertical distribution of organic phosphorus pesticide pollutants

Pesticide contamination has emerged as a global threat to humans. Here, we investigate the soil distribution pattern of organic phosphorus pesticide contamination at a pesticide manufacturing site in northern China, exploring their relationships with soil properties and microbial communities. The concentrations of four organic phosphorus pesticides (i.e., phorate, terbuthion, fenitrothion, and parathion) decreased substantially with soil depths from the surface down to 2 m. However, terbuthion, fenitrothion, and parathion had second-peak concentrations at a depth of 8 m. The concentrations of those organic phosphorus pesticides were negatively correlated with soil water content, but positively correlated with sulfide, pH, and total phosphorus. The distribution patterns of organic phosphorus pesticides closely aligned with that of soil organic matter and clay minerals, especially in the presence of montmorillonite, kaolinite, and chlorite. Various bacterial genera known to degrade organic phosphorus pesticides, such as Flavobacterium, Bacillus, Acinetobacter, Lactobacillus, Pseudomonas, Sphingomonas, and Thiobacillus, were correlated with these pesticides. Since these genera were among the top 50 abundant genera in our samples, they might play a significant role in the degradation of organic phosphorus pesticides. Together, this study unveils previously unrecognized pesticide-soil-microbe interactions, thus providing an important knowledge basis for environmental remediation strategies.

Ecological risk of synthetic phenolic antioxidants: A study based on their spatial distribution in water, sediment, and soil from the Yangtze River Delta, China

Environmental occurrence and risks of novel synthetic phenolic antioxidants (SPAs) remain largely unclear. By using a typical algae (Chlorella pyrenoidosa) as model organism, we evaluated the ecological risks of both traditional and novel SPAs, based on their concentrations in water, sediment, and soil collected from the Yangtze River Delta, China. Detection frequencies (DFs) of 10 novel SPAs were 25-100% in water, 3-100% in sediment, and 0-100% in soil, with geometric means (GMs) of 2700 ng/L, 1270 ng/g, and 2440 ng/g, respectively. For 8 traditional SPAs, DFs were 50-100% (GM: 680 ng/L), 3-100% (534 ng/g), and 47-100% (2240 ng/g) in water, sediment, and soil, respectively. AO3114 was the main pollutant in water, while AO1010 dominated in sediment and soil. Notably, low-molecular-weight SPAs showed migration behavior from sediment to water. Four SPAs (AO626, AO1035, AO1098, and AO1076) showed dose- and time-dependent toxicity on Chlorella pyrenoidosa. As time progressed, sediment-released SPAs became more toxic than those in water. Two SPAs (AO1135 and BHT-Q) posed high risks (RQW > 1) to green algae, daphnia, and fish. The SPA mixture exhibited high risks (RQmix > 1) to these organisms, increasing with the trophic level. This research holds valuable guidance for further SPA risk assessments.

Recent Progress in Molecular Oxygen Activation by Iron-Based Materials: Prospects for Nano-Enabled In Situ Remediation of Organic-Contaminated Sites

In situ chemical oxidation (ISCO) is commonly used for the remediation of contaminated sites, and molecular oxygen (O2) after activation by aquifer constituents and artificial remediation agents has displayed potential for efficient and selective removal of soil and groundwater contaminants via ISCO. In particular, Fe-based materials are actively investigated for O2 activation due to their prominent catalytic performance, wide availability, and environmental compatibility. This review provides a timely overview on O2 activation by Fe-based materials (including zero-valent iron-based materials, iron sulfides, iron (oxyhydr)oxides, and Fe-containing clay minerals) for degradation of organic pollutants. The mechanisms of O2 activation are systematically summarized, including the electron transfer pathways, reactive oxygen species formation, and the transformation of the materials during O2 activation, highlighting the effects of the coordination state of Fe atoms on the capability of the materials to activate O2. In addition, the key factors influencing the O2 activation process are analyzed, particularly the effects of organic ligands. This review deepens our understanding of the mechanisms of O2 activation by Fe-based materials and provides further insights into the application of this process for in situ remediation of organic-contaminated sites.

Response of microbial communities in aquifers with multiple organic solvent contamination: Implications for MNA remedy

The application of Monitored Natural Attenuation (MNA) technology has been widespread, while there is a paucity of data on groundwater with multiple co-contaminants. This study focused on high permeability, low hydraulic gradient groundwater with co-contamination of benzene, toluene, ethylbenzene, and xylenes (BTEX), chlorinated aliphatic hydrocarbons (CAHs), and chlorinated aromatic hydrocarbons (CPs). The objective was to investigate the responses of microbial communities during natural attenuation processes. Results revealed greater horizontal variation in groundwater microbial community composition compared to vertical variation. The variation was strongly correlated with the total contaminant quantity (r = 0.722, p < 0.001) rather than individual contaminants. BTEX exerted a more significant influence on community diversity than other contaminants. The assembly of groundwater microbial communities was primarily governed by deterministic processes (βNTI < -2) in high contaminant concentration zones, while stochastic processes (|βNTI| < 2) dominated in low-concentration zones. Moreover, the microbial interactions shifted at different depths indicating the degradation rate variation in the vertical. This study makes fundamental contribution to the understanding for the effects of groundwater flow and material fields on indigenous microbial communities, which will provide a scientific basis for more precise adoption of microbial stimulation/augmentation to accelerate the rate of contaminant removal.

Ecological Risk Assessment of Three Pesticide Additives in Soil and Application to the Remediation of Contaminated Soil

Pesticide additives (PAs) are auxiliary ingredients added to the pesticide manufacturing and use processes, constituting 1% to 99% of the pesticide and often composed of benzene and chlorinated hydrocarbons. We selected three typical PAs, toluene, chloroform, and trichloroethylene, to evaluate their retention function toxicity and ecological risk in soil. Soil immobilization techniques and aquatic model organisms were used to demonstrate the effectiveness of the immobilized soil method to determine the ecological risk of chemicals. The 48-h median lethal concentrations of toluene, chloroform, and trichloroethylene alone in spiked soil on Daphnia magna were 10.5, 2.3, and 1.1 mg/L (medium, high, and high toxicity, respectively). The toxicity of the three-PA mixtures showed an antagonistic effect. The risk levels of toluene, chloroform, and trichloroethylene in the soil were evaluated as moderate to high, low to high, and high risk, respectively. The toxicity of two pesticide-contaminated sites in the Yangtze River Delta before and after remediation was successfully evaluated by immobilized soil technology. The toxicity of two soil sampling points was reduced from medium toxic to low toxic and no toxic, respectively, after remediation. The results of our study give a rationale for and prove the validity of the aquatic model organisms and soil immobilization techniques in assessing the soil retention functions toxicity of PAs. Environ Toxicol Chem 2024;43:1677-1689. © 2024 SETAC.

Analysis of heavy metal and polycyclic aromatic hydrocarbon pollution characteristics of a typical metal rolling industrial site based on data mining

With the transformation and upgrading of industries, the environmental problems caused by industrial residual contaminated sites are becoming increasingly prominent. Based on actual investigation cases, this study analyzed the soil pollution status of a remaining sites of the copper and zinc rolling industry, and found that the pollutants exceeding the screening values included Cu, Ni, Zn, Pb, total petroleum hydrocarbons and 6 polycyclic aromatic hydrocarbon monomers. Based on traditional analysis methods such as the correlation coefficient and spatial distribution, combined with machine learning methods such as SOM + K-means, it is inferred that the heavy metal Zn/Pb may be mainly related to the production history of zinc rolling. Cu/Ni may be mainly originated from the production history of copper rolling. PAHs are mainly due to the incomplete combustion of fossil fuels in the melting equipment. TPH pollution is speculated to be related to oil leakage during the industrial use period and later period of vehicle parking. The results showed that traditional analysis methods can quickly identify the correlation between site pollutants, while SOM + K-means machine learning methods can further effectively extract complex hidden relationships in data and achieve in-depth mining of site monitoring data.

Green finance reform and application intensity of chemical fertilizer and pesticide: policy evidence from China

The environmental hazards resulting from the excessive application of pesticides and fertilizers have been an inevitable agricultural production issue in various countries around the world. New technologies and policies are constantly trying to improve their application efficiency. This paper utilizes panel data of the provincial level in China from 2009 to 2019 to empirically study the effect of green finance reform policies on the chemical fertilizer application intensity (FAI) and pesticide application intensity (PAI). Standard difference-in-differences (DID), synthetic DID, difference-in-difference-in differences (DDD), and spatial DID models are constructed for specific empirical analysis. The findings can be concluded as follows: (1) A unit of the green finance reform policy reduces FAI by 0.0144 and PAI by 1.7921 by promoting green technology innovation. (2) Government financial extractive capacity hinders the reduction effect of green finance on PAI. (3) Coastal geographical location is conducive to reducing PAI through green finance reform. (4) FAI and PAI show positive spatial autocorrelations, and the influence of green finance reform overflows to surrounding areas. The research results can provide policy references for countries around the world to promote the green development of agriculture and reduce environmental pollution.

Removal of sulfonylurea herbicides with g-C3N4-based photocatalysts: A review

The accumulation of agricultural chemicals in the environment has become a global concern, of which sulfonylurea herbicides (SUHs) constitute a significant category. Solar-driven photocatalysis is favored for removing organic pollutants due to its high efficiency and environmental friendliness. Graphite carbon nitride (g-C3N4)-based materials with superior catalytic activities and physicochemical stabilities are promising photocatalysts. This review describes the g-C3N4-based materials and their uses in the photocatalytic degradation of SUHs or other organic pollutants with similar structures. First, the fundamentals of g-C3N4-based materials and photocatalytic SUHs degradation are discussed to provide an in-depth understanding of the mechanism for the photocatalytic activity. The ability of different g-C3N4-based materials to photocatalytically degrade SUH-like structures is then discussed and summarized based on different modification strategies (morphology modulation, elemental doping, defect engineering, and heterojunction formations). Meanwhile, the effects of different environmental factors on the photocatalytic performance of g-C3N4-based materials are described. Finally, the major challenges and opportunities of g-C3N4-based materials for the photocatalytic degradation of SUHs are proposed. It is hoped that this review will show the feasibility of photocatalytic degradation of SUHs with g-C3N4-based materials.

Natural attenuation of BTEX and chlorobenzenes in a formerly contaminated pesticide site in China: Examining kinetics, mechanisms, and isotopes analysis

Groundwater contamination from abandoned pesticide sites is a prevalent issue in China. To address this problem, natural attenuation (NA) of pollutants has been increasingly employed as a management strategy for abandoned pesticide sites. However, limited studies have focused on the long-term NA process of co-existing organic pollutants in abandoned pesticide sites by an integrated approach. In this study, the NA of benzene, toluene, ethylbenzene, and xylene (BTEX), and chlorobenzenes (CBs) in groundwater of a retired industry in China was systematically investigated during the monitoring period from June 2016 to December 2021. The findings revealed that concentrations of BTEX and CBs were effectively reduced, and their NA followed first-order kinetics with different rate constants. The sulfate-reducing bacteria, nitrate-reducing bacteria, fermenting bacteria, aromatic hydrocarbon metabolizing bacteria, and reductive dechlorinating bacteria were detected in groundwater. It was observed that distinct environmental parameters played a role in shaping both overall and key bacterial communities. ORP (14.72%) and BTEX (12.89%) were the main drivers for variations of the whole and key functional microbial community, respectively. Moreover, BTEX accelerated reductive dechlorination. Furthermore, BTEX and CBs exhibited significant enrichment of 13C, ranging from +2.9 to +27.3‰, demonstrating their significance in situ biodegradation. This study provides a scientific basis for site management.

Hydraulic conductivity and microscopic properties of polyanionic cellulose and microscale zero-valent iron amended sand/bentonite backfills exposed to dichloromethane solution

Leachate comprising organic contaminants such as dichloromethane is frequently discharged into groundwater at contaminated sites and unlined landfills. Soil-bentonite backfills in vertical cutoff walls are extensively employed to contain the flow of contaminated groundwater, thereby safeguarding the downstream groundwater environmental quality and ecosystem. This study presented a comprehensive evaluation of effects of dichloromethane-impacted groundwater on hydraulic conductivity and microscopic characteristics of soil-bentonite backfills amended with polymer namely polyanionic cellulose and microscale zero-valent iron. The results showed the amended backfills exhibited lower hydraulic conductivity than the unamended backfill regardless of the permeant type, i.e., tap water and dichloromethane solution. Scanning electron microscopy coupled with energy-dispersive spectrometry analyses demonstrated that polyanionic cellulose hydrogel could effectively coat sand, bentonite, and microscale zero-valent iron particles, providing protection of bentonite particles against attacks imposed by the dichloromethane and multivalent iron ions, and diminish aggregation of microscale zero-valent iron particles in the amended backfills. X-ray diffraction results indicated there was no intercalation of polyanionic cellulose and microscale zero-valent iron into the montmorillonite platelets of bentonite particles. Based on the Fourier Transform Infrared Spectroscopy Spectra analysis, a new functional group (-CH2) was identified on the polyanionic cellulose amended bentonite particles. The results demonstrated that amendment with polyanionic cellulose and microscale zero-valent iron is a promising approach to improve the performance of soil-bentonite backfills in containing flow of dichloromethane-impacted groundwater.

Harmonizing pesticides environmental quality standards: A fate-pathway perspective

Regulatory agencies worldwide set pesticide environmental quality standards, which are proposed independently in each dependent environmental media rather than across the complete fate route. Thus, lacking the fate-pathway perspective in defining pesticide environmental quality standards might cause undesirable pesticide residue from the upper compartment (e.g., soil) to the lower compartment (e.g., water). This study aimed to harmonize the self-consistency of pesticide environmental quality standards across environmental media via the fate-pathway analysis. The introduced qualitative and quantitative rules defined environmental quality standards of pesticides in six major environmental scenarios in the soil and water system based on related regulatory objectives. Fate factors simulated via USEtox were used to create a preliminary quantitative link between theoretical maximum legal masses of pesticides across environmental compartments. Using chlorpyrifos and 2,4-D as examples, their standard values were comparatively assessed in selected environmental media in China and the United States. According to the investigative findings, missing the respective environmental quality standards of pesticides in the agricultural soil could significantly influence the implementation of those in freshwater. Taking a fate-pathway perspective, the self-consistency test highlighted that defining pesticide environmental quality standards for freshwater was the most challenging task, as the freshwater compartment typically comprises multiple lower environmental compartments with diverse regulatory objectives. Overall, this theoretical study has the potential to illuminate the harmonization of pesticide environmental quality standards throughout the entire environmental fate pathway, ultimately leading to improved regulatory efficiency and communication. Future research should focus on risk-based model implementation, regulatory response evaluation, and legal limit interpretation to better integrate environmental pesticide management under a variety of regulatory goals.

Containment of phenol-impacted groundwater by vertical cutoff wall with backfill consisting of sand and bentonite modified with hydrophobic and hydrophilic polymers

A novel soil-bentonite backfill is proposed for use in vertical cutoff walls to contain phenol in groundwater at contaminated sites. The backfill consists of sand and bentonite modified with tetramethylammonium and carboxymethylcellulose, labeled as STCMB backfill. Flexible-wall permeability and double-reservoir diffusion tests were conducted to investigate the impact of phenol solution on hydraulic conductivity (k), effective diffusion coefficient (D*) and partition coefficient (Kp) of the backfill, respectively. The permeability results showed k of the STCMB backfill decreased by 0.91 times when the permeating liquid was changed from tap water to phenol solution. The diffusion testing results showed that D* values for the STCMB and conventional backfill (labeled as SCB backfill) were 4.0 × 10-10 m2/s and 3.0 × 10-10 m2/s, respectively, whereas Kp values for the STCMB and SCB backfills were 2.0 mL/g and 0.75 mL/g, respectively. The octanol-water partition coefficient model is suitable for estimating Kp for nonpolar organics. Furthermore, a series of solute transport simulations using Pollute V7 program was performed to evaluate the performance of vertical cutoff walls comprising STCMB and SCB backfills in containing phenol in lateral flowing groundwater. Overall, the STCMB backfill has demonstrated superior effectiveness in containing phenol in groundwater.

Machine Learning Modeling Based on Microbial Community for Prediction of Natural Attenuation in Groundwater

Natural attenuation is widely adopted as a remediation strategy, and the attenuation potential is crucial to evaluate whether remediation goals can be achieved within the specified time. In this work, long-term monitoring of indigenous microbial communities as well as benzene, toluene, ethylbenzene, and xylene (BTEX) and chlorinated aliphatic hydrocarbons (CAHs) in groundwater was conducted at a historic pesticide manufacturing site. A machine learning approach for natural attenuation prediction was developed with random forest classification (RFC) followed by either random forest regression (RFR) or artificial neural networks (ANNs), utilizing microbiological information and contaminant attenuation rates for model training and cross-validation. Results showed that the RFC could accurately predict the feasibility of natural attenuation for both BTEX and CAHs, and it could successfully identify the key genera. The RFR model was sufficient for the BTEX natural attenuation rate prediction but unreliable for CAHs. The ANN model showed better performance in the prediction of the attenuation rates for both BTEX and CAHs. Based on the assessments, a composite modeling method of RFC and ANN was proposed, which could reduce the mean absolute percentage errors. This study reveals that the combined machine learning approach under the synergistic use of field microbial data has promising potential for predicting natural attenuation.

Contaminant characterization of odor in soil of typical pesticide-contaminated site with shallow groundwater

Odor emission from the soil of pesticide-contaminated sites is a prominent environmental problem in China, but there are very few researches about the component and spatial distribution of odorous substances in the soil of contaminated sites. In this paper, to investigate the odor pollution condition of an organophosphorus pesticide production site in a city of South China, the odor pollutants in the soil and soil gas were analyzed and the key odor-contributing substances were identified. Besides, the correlation between the concentrations of odorous substances in soil and soil gas was analyzed, and the measured results were compared with the predicted results by the linear model and DED model. An off-line soil gas sampling device was designed to collect the gas emitted from soil because the groundwater level in the site was too shallow to build a soil gas well. The key odor substances were screened from the detection results of soil gas via odor activity value (OAV) analysis, which revealed that the key odorous substances included benzene, ethylbenzene, ammonia, toluene, m,p-xylene, methyl sulfide, dimethyl disulfide, and formaldehyde. Furthermore, the spatial distribution of the odor substances in the soil of the pesticide-contaminated site was closely related to the layout and geologic structure of the site. The odor pollutants in soil were mainly distributed near the phosmet production workshop and the drainage ditch network. As for the deep distribution, the odorous substances were mainly enriched in the silty clay or clay layer (5.6-11 m), followed by the sludge layer (1-3.6 m). Finally, the predicted model (linear model and DED model) analysis suggested that the linear model was more suitable for predicting the concentration of odorous substances in the soil gas with the detection data of soil in this pesticide-contaminated site.

Analysis of soil pollution characteristics and influencing factors based on ten electroplating enterprises

The electroplating industry encompasses various processes and plating types that contribute to environmental pollution, which has led to growing public concern. To investigate related soil pollution in China, the study selected 10 sites with diverse industrial characteristics distributed across China and collected 1052 soil samples to determine the presence of industrial priority pollutants (PP) based on production process and pollutant toxicity. The factors influencing site pollution as well as proposed pollution prevention and control approaches were then evaluated. The results indicate the presence of significant pollution in the electroplating industry, with ten constituents surpassing the risk screening values (RSV). The identified PP consist of Cr(VI), zinc (Zn), nickel (Ni), total chromium (Cr), and petroleum hydrocarbons (C10-C40). PP contamination was primarily observed in production areas, liquid storage facilities, and solid zones. The vertical distribution of metal pollutants decreased with soil depth, whereas the reverse was true for petroleum hydrocarbons (C10-C40). Increase in site production time was strongly correlated with soil pollution, but strengthening anti-seepage measures in key areas can effectively reduce the soil exceedance standard ratio. This study serves as a foundation for conceptualizing site repair technology in the electroplating industry and offers a reference and methodology for pollution and source control in this and related sectors.

Research on the recycling and disposal of Chinese pesticide packaging waste based on evolutionary game theory

This study aims to determine the optimal strategy and driving factors of the critical nodes of pesticide packaging waste recycling by constructing the recycling process of "village collection-town transport-county management." Counties, towns, and villages are the central nodes of collection, coordination, and communication in the recycling process. Their strategy selection and influencing factor analysis are related to the development of recycling. The county processing center, township transit center, and village recycling center were selected to construct a game model, and strategy and parameter assumptions were made to obtain the optimal strategy combination. The results showed that strict supervision, professional transportation and strict implementation are the best strategies for counties, towns and villages, respectively. Simulation analysis confirmed that factors such as cost, reward restricted the strategy selection of each subject. The higher the supervision, transport, and input costs, the lower the enthusiasm of counties, towns, and villages to participate in recycling, respectively. Reasonable control of reward could help each participant choose a stable strategy. The study provided the idea of a pilot before promotion for the government and emphasized the importance of controlling incentive policies and relative costs to improve the recycling process of pesticide packaging waste.

Depth and contaminant-shaped bacterial community structure and assembly at an aged chlorinated aliphatic hydrocarbon-contaminated site

Chlorinated aliphatic hydrocarbons (CAHs) are potentially toxic substances that have been detected in various contaminated environments. Biological elimination is the main technique of detoxifying CAHs in the contaminated sites, but the soil bacterial community at CAH-contaminated sites have been little investigated. Here, high-throughput sequencing analysis of soil samples from different depths (to 6 m depth) at an aged CAH-contaminated site has been conducted to investigate the community composition, function, and assembly of soil bacteria. The alpha diversity of the bacterial community significantly increased with increasing depth and bacterial community also became more convergent with increasing depth. Organohalide-respiring bacteria (OHRB) is considered keystone taxa to reduce the environmental stress of CAHs by reductive dechlorinate CAHs into nontoxic products, increases the alpha diversity of bacterial community and improves the stability of bacterial co-occurrence network. The high concentration of CAHs in deep soil and the stable anaerobic environment make deterministic processes dominate bacterial community assembly, while the topsoil is dominated by dispersal limitation. In general, CAHs at contaminated sites have a great impact on bacterial community, but the CAHs metabolic community acclimated in deep soil can reduce the environmental stress of CAHs, which provides foundation for the monitored natural attenuation technology in CAHs-contaminated sites.