ABSTRACT
In recent years, there has been a notable surge in environmental incidents, including wildfires and chemical releases. Responses to such events have primarily focused on addressing acute and immediate impacts. However, potential long-term health risks have been overlooked. Our proposed framework first advocates for the holistic identification of contaminants, prioritizing persistent organic contaminants determined through both knowledge-based and non-targeted and targeted analysis. We suggest integrating environmental monitoring and modeling approaches to assess the extent and composition of contamination caused by these chemicals. To facilitate swift assessments, we advocate the development of streamlined chemical analysis techniques and dedicated technologies for in situ monitoring of persistent organic chemicals. In addition, we provide an overview of both traditional and state-of-the-art approaches to risk assessment and introduce a three-tier risk assessment framework for evaluating the long-term health risks associated with environmental incidents. We emphasize the importance of in situ soil remediation and coordinated recovery efforts, including effective communication, evacuation, and cleaning plans for affected spaces, which are pivotal for facilitating recovery from environmental incidents. This comprehensive approach fortifies preparedness and recovery strategies, providing a robust framework for managing future environmental crises.
ABSTRACT
The massive production and application of nanomaterials (NMs) have raised concerns about the potential adverse effects of NMs on human health and the environment. Evaluating the adverse effects of NMs by laboratory methods is expensive, time-consuming, and often fails to keep pace with the invention of new materials. Therefore, in silico methods that utilize machine learning techniques to predict the toxicity potentials of NMs are a promising alternative approach if regulatory confidence in them can be enhanced. Previous reviews and regulatory OECD guidance documents have discussed in detail how to build an in silico predictive model for NMs. Nevertheless, there is still room for improvement in addressing the ways to enhance the model representativeness and performance from different angles, such as data set curation, descriptor selection, task type (classification/regression), algorithm choice, and model evaluation (internal and external validation, applicability domain, and mechanistic interpretation, which is key to ensuring stakeholder confidence). This review explores how to build better predictive models; the current state of the art is analyzed via a statistical evaluation of literature, while the challenges faced and future perspectives are summarized. Moreover, a recommended workflow and best practices are provided to help in developing more predictive, reliable, and interpretable models that can assist risk assessment as well as safe-by-design development of NMs.
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The advent of the digital era has transformed E-commerce platforms into critical tools for industry, yet traditional recommendation systems often fall short in the specialized context of the electric power industry. These systems typically struggle with the industry's unique challenges, such as infrequent and high-stakes transactions, prolonged decision-making processes, and sparse data. This research has developed a novel recommendation engine tailored to these specific conditions, such as to handle the low frequency and long cycle nature of Business-to-Business (B2B) transactions. This approach includes algorithmic enhancements to better process and interpret the limited data available, and data pre-processing techniques designed to enrich the sparse datasets characteristic of this industry. This research also introduces a methodological innovation that integrates multi-dimensional data, combining user E-commerce activities, product specifics, and essential non-tendering information. The proposed engine employs advanced machine learning techniques to provide more accurate and relevant recommendations. The results demonstrate a marked improvement over traditional models, offering a more robust and effective tool for facilitating B2B transactions in the electric power industry. This research not only addresses the sector's unique challenges but also provides a blueprint for adapting recommendation systems to other industries with similar B2B characteristics.
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Cleaner heating policies aim to reduce air pollution and may bring about health benefits to individuals. Based on a fixed-effect model focusing on Beijing, this study found that after the onset of air pollution, daily clinic visits, hospitalization days, and hospitalization expenses increased several days after the occurrence of air pollution. These hospitalization changes were observed in males and females and three different age groups. A difference-in-differences (DID) model was constructed to identify the influences of cleaner heating policies on health consequences. The study revealed that the policy positively affects health outcomes, with an average decrease of 3.28 thousand clinic visits for all diseases. The total hospitalization days and expenses tend to decrease by 0.22 thousand days and 0.34 million CNY (Chinese Yuan), respectively. Furthermore, implementing the policy significantly reduced the number of daily clinic visits for respiratory diseases, asthma, stroke, diabetes, and chronic obstructive pulmonary diseases (COPDs).
ABSTRACT
Widely-used C60 fullerene nanoparticles (C60) result in their release into the aquatic environment, which may affect the distribution and toxicity of pollutants such as arsenic (As), to aquatic organism. In this study, arsenate (As(V)) accumulation, speciation and subcellular distribution was determined in Danio rerio (zebrafish) intestine, head and muscle tissues in the presence of C60. Meanwhile we compared how single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), graphene oxide (GO) and graphene (GN) nanoparticles alter the behaviors of As(V). Results showed that C60 significantly inhibited As accumulation and toxicity in D. rerio, due to a decrease in total As and monomethylarsonic acid (MMA) and As(V) species concentrations, a lower relative distribution in the metal-sensitive fraction (MSF). It was attributed that C60 may coat As(V) ion channels and consequently, affect the secretion of digestive enzymes in the gut, favoring As excretion and inhibiting As methylation. Similarly, MWCNTs reduced the species concentration of MMA and As(V) in the intestines, low GSH (glutathione) contents in the intestine. Due to the disparity of other carbon-based nanomaterial morphologies, SWCNTs, GO and GN exhibited the various effects on the toxicity of As(V). In addition, the possible pathway of arsenobetaine (AsB) biosynthesis included migration from the intestine to muscle in D. rerio, with the precursor of AsB likely to be 2-dimethylarsinylacetic acid (DMAA). The results of this study suggest that C60 is beneficial for controlling As(V) pollution and reducing the impact of As(V) biogeochemical cycles throughout the ecosystem.
Subject(s)
Arsenates , Fullerenes , Nanoparticles , Water Pollutants, Chemical , Zebrafish , Fullerenes/toxicity , Animals , Arsenates/toxicity , Water Pollutants, Chemical/toxicity , Nanoparticles/toxicity , Nanotubes, Carbon/toxicity , Graphite/toxicityABSTRACT
Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 µm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 µg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.
ABSTRACT
Indoor PM2.5 pollution is one of the leading causes of death and disease worldwide. As monitoring indoor PM2.5 concentrations on a large scale is challenging, it is urgent to assess population-level exposure and related health risks to develop an easy-to-use and generalized model to predict indoor PM2.5 concentrations and spatiotemporal variations at the global level. Existing machine learning models of indoor PM2.5 are prone to deliver single-point predictions, and their input strategies are not widely applicable. Here, we developed a Bayesian neural network (BNN) model for predicting the distribution of daily average urban residential PM2.5 concentration based on multiple data sources available from nationwide comprehensive sensor-monitoring records in China. The BNN model showed good performance with a 10-fold cross-validation R2 of 0.70, mean-absolute-error of 9.45 µg/m3, root-mean-square error of 13.3 µg/m3, and 95 % prediction interval coverage of 85 %. To demonstrate the application process, this model was applied to predict indoor PM2.5 concentrations on a large spatiotemporal scale. Our modeled population-weighted annual indoor PM2.5 concentration for China in 2019 was 22.8 µg/m3, far exceeding the WHO standard. The validity of the model at the population level can be further bolstered, making it valuable for assessing and managing indoor air pollution-related health risks.
Subject(s)
Air Pollutants , Air Pollution, Indoor , Air Pollution , Deep Learning , Air Pollutants/analysis , Particulate Matter/analysis , Environmental Monitoring , Bayes Theorem , Air Pollution, Indoor/analysis , Air Pollution/analysisABSTRACT
Pien Tze Huang (PTH) was documented as an imperial prescription composed of Notoginseng Radix, Calculus Bovis, Snake Gallbladder, and Musk. It is famous in China and Asian countries due to its excellent effects in heat clearing, detoxifying, swelling reduction, and pain relieving. Modern pharmacological studies demonstrate that PTH shows excellent effects against various inflammatory diseases, liver diseases, and cancers. This review summaries the pharmacological effects, clinical applications, and mainchemical components of PTH. More importantly, its potential quality markers (Q-markers) were then analyzed based on the "five principles" of Q-markers under the guidance of Traditional Chinese Medicine theory, including transfer and traceability, specificity, efficacy, compatibility, and measurability. As a result, ginsenosides Rb1, ginsenoside Rg1, ginsenoside Rd, ginsenoside Re, notoginsenoside R1, dencichine, bilirubin, biliverdin, taurocholic acid, and muscone are considered as the Q-markers of PTH. These findings will provide guidance and assistance for the construction of a quality control system for PTH.
Subject(s)
Drugs, Chinese Herbal , Ginsenosides , Neoplasms , Humans , Ginsenosides/pharmacology , Drugs, Chinese Herbal/pharmacology , Medicine, Chinese Traditional , Quality Control , ChinaSubject(s)
Environmental Pollutants , Fluorocarbons , Humans , Birth Weight , Environmental Exposure , Fluorocarbons/analysisABSTRACT
BACKGROUND: Human breast milk is a primary route of exposure to perfluoroalkyl substances (PFAS) in infants. To understand the associated risks, the occurrence of PFAS in human milk and the toxicokinetics of PFAS in infants need to be addressed. OBJECTIVES: We determined levels of emerging and legacy PFAS in human milk and urine samples from Chinese breastfed infants, estimated renal clearance, and predicted infant serum PFAS levels. METHODS: In total, human milk samples were collected from 1,151 lactating mothers in 21 cities in China. In addition, 80 paired infant cord blood and urine samples were obtained from two cities. Nine emerging PFAS and 13 legacy PFAS were analyzed in the samples using ultra high-performance liquid chromatography tandem mass spectrometry. Renal clearance rates (CLrenals) of PFAS were estimated in the paired samples. PFAS serum concentrations in infants (<1 year of age) were predicted using a first-order pharmacokinetic model. RESULTS: All nine emerging PFAS were detected in human milk, with the detection rates of 6:2 Cl-PFESA, PFMOAA, and PFO5DoDA all exceeding 70%. The level of 6:2 Cl-PFESA in human milk (median concentration=13.6 ng/L) ranked third after PFOA (336 ng/L) and PFOS (49.7 ng/L). The estimated daily intake (EDI) values of PFOA and PFOS exceeded the reference dose (RfD) of 20 ng/kg BW per day recommended by the U.S. Environmental Protection Agency in 78% and 17% of breastfed infant samples, respectively. 6:2 Cl-PFESA had the lowest infant CLrenal (0.009mL/kg BW per day), corresponding to the longest estimated half-life of 49 y. The average half-lives of PFMOAA, PFO2HxA, and PFO3OA were 0.221, 0.075, and 0.304 y, respectively. The CLrenals of PFOA, PFNA, and PFDA were slower in infants than in adults. CONCLUSIONS: Our results demonstrate the widespread occurrence of emerging PFAS in human milk in China. The relatively high EDIs and half-lives of emerging PFAS suggest potential health risks of postnatal exposure in newborns. https://doi.org/10.1289/EHP11403.
Subject(s)
Breast Feeding , Fluorocarbons , Infant, Newborn , United States , Adult , Female , Humans , Infant , Body Burden , East Asian People , LactationABSTRACT
Previous estimations on the premature deaths attributable to indoor ambient particulate matter (PM) with aerodynamic diameter < 2.5 µm (PM2.5) of outdoor origin only considered the indoor PM2.5 concentration, which always neglected the impact from the distribution of particle size and the PM deposition in human airways. To tackle this issue, we first calculated the premature deaths due to PM2.5 was approximately 1,163,864 persons in mainland China in 2018 by using the global disease burden approach. Then, we specified the infiltration factor of PM with aerodynamic diameter < 1 µm (PM1) and PM2.5 to estimate the indoor PM pollution. Results showed that average concentrations of indoor PM1 and PM2.5 of outdoor origin were 14.1 ± 3.9 µg/m3 and 17.4 ± 5.4 µg/m3, respectively. The indoor PM1/PM2.5 ratio of outdoor origin was estimated to be 0.83 ± 0.18, which was 36 % higher than the ambient PM1/PM2.5 ratio (0.61 ± 0.13). Furthermore, we calculated the premature deaths from the indoor exposure of outdoor origin was approximately 734,696, accounting for approximately 63.1 % of total deaths. Our results are 12 % higher than previous estimations neglecting the impact from the distribution disparities of PM between indoor and outdoor. Regarding the cause-specific diseases, indoor PM2.5 exposure of outdoor origin accounted for 293,379 deaths to ischemic heart disease, followed by 158,238 deaths to chronic obstructive pulmonary disease, 134,390 deaths to stroke, 84,346 cases to lung cancer, 52,628 deaths to lower respiratory tract infection, and 11,715 deaths to type 2 diabetes. In addition, we for the first time estimated the indoor PM1 of outdoor origin has led to approximately 537,717 premature deaths in mainland China. Our results have well demonstrated the health impact may be approximately 10 % higher when considering the effects from infiltration and respiratory tract uptake and physical activity levels, comparing to the treatment that only used outdoor PM concentration.
Subject(s)
Air Pollutants , Air Pollution, Indoor , Diabetes Mellitus, Type 2 , Humans , Particulate Matter/adverse effects , Particulate Matter/analysis , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution, Indoor/adverse effects , Air Pollution, Indoor/analysis , Environmental Monitoring , Particle Size , China/epidemiology , Environmental ExposureABSTRACT
The ability to accurately assess the health risks of contaminants is limited by the shortcomings of toxicological standards. Using organophosphate esters (OPEs) as an example, this study attempted to integrate physiologically based pharmacokinetic (PBPK)-based forward dosimetry and in vitro bioassays to assess the likelihood of contaminants inducing biological effects in humans. The total exposure level of OPEs for Chinese residents was 19.5 ± 8.71 ng/kg/day with inhalation being the main exposure pathway. Then, human PBPK models were developed for individual OPEs to predict their steady-state concentrations in human tissues, and the predicted median levels in blood were close to the measurements. The reference doses (RfDs) of OPEs based on in vitro bioassays were comparable to in vivo animal-derived RfDs, demonstrating the reliability of in vitro bioassays. Therefore, the likelihood of OPEs inducing bioactivities in humans (RQin-vitro) was calculated using in vitro toxicity data and OPE levels in human tissues. The RQin-vitros of tris(2-chloroisopropyl) phosphate, tris(1,3-dichloropropyl) phosphate, and triphenyl phosphate (7.68 × 10-5-3.18 × 10-3) were comparable to the risks assessed using traditional RfDs (5.22 × 10-5-1.94 × 10-3), indicating the credibility of the method proposed in this study. This study establishes a new framework to improve the health risk assessment of contaminants without sufficient toxicity data and minimize the need for animal experimentation.
Subject(s)
Environmental Monitoring , Flame Retardants , Humans , Environmental Monitoring/methods , Reproducibility of Results , Esters , Flame Retardants/analysis , Organophosphates/toxicity , Phosphates , Risk Assessment , Biological Assay , ChinaABSTRACT
Due to special properties, nano-TiO2 will interact with heavy metals and other pollutants in water, thus affecting the environmental behavior and ecotoxicity of these pollutants. However, the exact manner in which nano-TiO2 affects the bioaccumulation mechanisms of heavy metals is still unclear now. In the present study, quantitative structure bioaccumulation relationship (QSBAR) models were established to explore the relationships between physicochemical parameters of heavy metals and their accumulation in Daphnia magna in the absence and presence of nano-TiO2 at low metal exposure concentrations. The results showed that different physicochemical parameters affected the bioaccumulation of metals in Daphnia magna. The metal accumulation could be described by means of a Comprehensive Parameter composed of seven parameters, i.e., atomic number (AN), relative atomic weight (AW), atomic radius (AR), atomic ionization potential (AN/ΔIP), covalent index (X2r), second ionization energy (I2) and electrochemical potential (E0), in the absence of nano-TiO2, whereas the metal accumulation increased with the increase in Van Der Waals radius (rw) of metals in the presence of nano-TiO2. It was demonstrated that the bioaccumulation mechanism of the metals to Daphnia magna changed in the presence of nano-TiO2. Moreover, the bioaccumulation of more than 85% of the metals increased in the presence of nano-TiO2, but it increased differently for different metals. The present study provides an alternative approach to understand the mechanism of heavy metal bioaccumulation at low metal exposure concentrations and the effect of nano-TiO2 on metal bioaccumulation.
Subject(s)
Metals, Heavy , Nanoparticles , Water Pollutants, Chemical , Animals , Daphnia , Bioaccumulation , Water Pollutants, Chemical/chemistry , Nanoparticles/toxicity , Titanium/chemistry , Metals, Heavy/toxicityABSTRACT
The projection of excess mortality due to diurnal temperature range (DTR) in future has not been evaluated yet in China. Based on daily cause-specific mortality data from 266 cities in China, this study aimed to examine the association between DTR and mortality, which help project the future mortality burden attributable to DTR by considering the modification effects of altitude and population migration. We first found that every 10 °C increase in the DTR would result in a 3.3 % (95 % confidence interval: 2.6 %-4.1 %) excess risk of non-accidental mortality. The unit risk of DTR-associated cause-specific mortality at moderate or high altitudes was significantly lower than at lower altitudes, especially for cardiovascular disease. Subsequently, DTR-associated excess mortality in 2017 in China was 233,154 deaths (with a population-weighted attributable fraction of 2.9 %). Furthermore, we projected DTR-attributable additional mortality in the future, with the associated mortalities to be 221,860 deaths in 2050-2059 (2050s) and 132,305 deaths in 2090-2099 (2090s), under the SSP1-2.6 scenario. Meanwhile, the regional inequalities were exacerbated by 18 % in 2050s and 13 % in 2090s when considering the modification effects of city altitude. Future population migration would increase excess mortality in most areas in central and southern China, and reduce the disease burden in most areas in eastern, western, and northern China. Our findings underpinned that regional strategies should be adopted to mitigate excess mortality attributable to global climate change.
Subject(s)
Cardiovascular Diseases , Humans , Temperature , China/epidemiology , Cities , Climate Change , Hot Temperature , MortalityABSTRACT
OBJECTIVES: The aim of this study was to explore whether indoor or outdoor relative humidity (RH) modulates the influenza epidemic transmission in temperate and subtropical climates. METHODS: In this study, the daily temperature and RH in 1558 households from March 2017 to January 2019 in five cities across both temperate and subtropical regions in China were collected. City-level outdoor temperature and RH from 2013 to 2019 were collected from the weather stations. We first estimated the effective reproduction number (Rt) of influenza and then used time-series analyses to explore the relationship between indoor/outdoor RH/absolute humidity and the Rt of influenza. Furthermore, we expanded the measured 1-year indoor temperature and the RH data into 5 years and used the same method to examine the relationship between indoor/outdoor RH and the Rt of influenza. RESULTS: Indoor RH displayed a seasonal pattern, with highs during the summer months and lows during the winter months, whereas outdoor RH fluctuated with no consistent pattern in subtropical regions. The Rt of influenza followed a U-shaped relationship with indoor RH in both temperate and subtropical regions, whereas a U-shaped relationship was not observed between outdoor RH and Rt. In addition, indoor RH may be a better indicator for Rt of influenza than indoor absolute humidity. CONCLUSION: The findings indicated that indoor RH may be the driver of influenza seasonality in both temperate and subtropical locations in China.
Subject(s)
Influenza, Human , Humans , Influenza, Human/epidemiology , Humidity , Weather , Seasons , Temperature , China/epidemiologyABSTRACT
This review focuses on the occurrence and interactions of engineered nanoparticles (ENPs) and brominated flame retardants (BFRs) such as polybrominated diphenyl ethers (PBDEs) in water systems and the generation of highly complex compounds in the environment. The release of ENPs and BFRs (e.g. PBDEs) to aquatic environments during their usage and disposal are summarised together with their key interaction mechanisms. The major interaction mechanisms including electrostatic, van der Waals, hydrophobic, molecular bridging and steric, hydrogen and π-bonding, cation bridging and ligand exchange were identified. The presence of ENPs could influence the fate and behaviour of PBDEs through the interactions as well as induced reactions under certain conditions which increases the formation of complex compounds. The interaction leads to alteration of behaviour for PBDEs and their toxic effects to ecological receptors. The intermingled compound (ENPs-BFRs) would show different behaviour from the parental ENPs or BFRs, which are currently lack of investigation. This review provided insights on the interactions of ENPs and BFRs in artificial, environmental water systems and wastewater treatment plants (WWTPs), which are important for a comprehensive risk assessment.
Subject(s)
Flame Retardants , Hydrocarbons, Brominated , Nanoparticles , Environmental Monitoring , Flame Retardants/analysis , Halogenated Diphenyl Ethers/analysis , Hydrocarbons, Brominated/analysis , Hydrogen , Ligands , WaterABSTRACT
Perfluorohexanesulfonic acid (PFHxS) is one of the persistent organic pollutants that has been recommended to be listed in Annex A of the Stockholm Convention. It has gained increasing attention in recent years due to its toxic effects. The guideline values of PFHxS are commonly associated with PFOS in various countries and regulatory agencies. In this study, multispecies bioassays were conducted to determine the ecological toxic effects of PFHxS, including plants, soil invertebrates, and soil microorganisms, which indicated the EC10/NOEC values ranged from 2.9 to 250 mg/kg. Where possible, logistic models were used to calculate the EC30 values for various endpoints. The species sensitivity distributions were employed to estimate the ecological investigation levels for PFHxS contamination in soils using toxicity results from literature and this study. The calculation using EC10/NOEC values from both literature and this study indicated a most conservative HC5 as 1.0 mg/kg (hazardous concentration for 5 % of the species being impacted). However, utilisation of EC30 values derived from this study resulted in a much higher HC5 for PFHxS in contaminated soils (13.0 mg/kg) which is at the higher end of the existing guideline values for PFOS for protecting ecological systems. The results obtained in this study can be useful in risk assessment processes to minimize any uncertainty using combined values with PFOS.
Subject(s)
Soil Pollutants , Soil , Animals , Fluorocarbons , Invertebrates , Risk Assessment , Soil Pollutants/analysis , Soil Pollutants/toxicity , Sulfonic AcidsABSTRACT
What is already known about this topic?: Environmental factors such as temperature and humidity play important roles in the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via droplets/aerosols. What is added by this report?: Higher relative humidity (61%-80%), longer spreading time (120 min), and greater dispersal distance (1 m) significantly reduced SARS-CoV-2 pseudovirus loads. There was an interaction effect between relative humidity and spreading time. What are the implications for public health practice?: The findings contribute to our understanding of the impact of environmental factors on the transmission of SARS-CoV-2 via airborne droplets/aerosols.
ABSTRACT
The nationwide occurrence of endosulfan residues in cotton fields has not yet been investigated. Therefore, in this study, 202 surface soil samples from 27 cities were collected from cotton fields in 8 major cotton-planting provinces of China, covering more than 97% of the national cotton sown area. The results showed that endosulfan residues were detected in cotton fields throughout the country. The main type of residue found was endosulfan sulfate (ES-sulfate), followed by ß-endosulfan and α-endosulfan, with average concentrations of 0.475, 0.129, and 0.048 µg/kg, respectively. Significant spatial variations in the endosulfan residues was noted, and the highest concentration of endosulfan residues was observed in the northwest inland cotton-growing area, followed by that in the Yellow River basin and Yangtze River basin cotton-growing areas. The endosulfan residues showed significant positive correlations with soil organic matter and soil clay contents. The α/ß endosulfan ratio was determined to be in the range of 0.02-1.20, indicating that endosulfan residues originated from the endosulfan application performed in historical cotton cultivation efforts. Together with the literature data, the concentrations of α-endosulfan and ß-endosulfan residues peaked in 2015 and 2017, respectively, and showed an overall decreasing trend from 2002 to 2021. The results of the ecological risk assessment suggested that Folsomia candida was most sensitive to endosulfan residues, with 20.8% of the sites presenting a high risk. However, in general, the soil ecological risk of cotton fields across the country was low. Our study demonstrated that China has achieved promising results in controlling the use and pollution of endosulfan, especially after 2014.