DNA walker-amplified signal-on electrochemical aptasensors for prostate-specific antigen coupling with two hairpin DNA probe-based hybridization reaction.

Electrochemical aptasensing systems have been developed for screening low-abundance disease-related proteins, but most of them involve multiple washings and multi-step separation during measurements, and thus are disadvantageous for routine use. In this work, an innovative and simple electrochemical aptasensing platform was designed for the voltammetric detection of prostate-specific antigen (PSA) in biological fluids without any washing and separation steps. This system mainly included a PSA-specific aptamer, a DNA walker and two hairpin DNA probes (i.e., thiolated hairpin DNA1 and ferrocene-labeled hairpin DNA2). Introduction of target PSA caused the release of the DNA walker from a partially complementary aptamer/DNA walker hybridization strand. The dissociated DNA walker opened the immobilized hairpin DNA1 on the electrode, accompanying subsequent displacement reaction with hairpin DNA2, thus resulting in the DNA walker step-by-step reaction with numerous hairpin DNA1 probes on the sensing interface. In this case, numerous ferrocene molecules were close to the electrode to amplify the voltammetric signal within the applied potentials. All reactions and electrochemical measurements including the target/aptamer reaction and hybridization chain reaction were implemented in the same detection cell. Under optimal conditions, the fabricated electrochemical aptasensor gave good voltammetric responses relative to the PSA concentrations within the range of 0.001-10 ng mL-1 at an ultralow detection limit of 0.67 pg mL-1. A good reproducibility with batch-to-batch errors was acquired for target PSA down to 11.5%. Non-target analytes did not interfere with the voltammetric signals of the electrochemical aptasensors. Meanwhile, 15 human serum specimens were measured with electrochemical aptasensors, and displayed well-matched results in comparison with the referenced human PSA enzyme-linked immunosorbant assay (ELISA) method. Significantly, this method provides a new horizon for the quantitative monitoring of low-concentration biomarkers or nucleic acids.

Derivation of human health risk-based thresholds for lead in soils promote the production of safer wheat and rice.

A reliable and accurate soil threshold helps prevent excessive dietary Pb intake risks to consumers of locally grown wheat and rice crops. Based on a three-year investigation of 206 wheat fields and 358 rice fields throughout China, this study aimed to improve the soil protection guidelines by investigating Pb accumulation in soil-wheat and soil-rice systems and by assessing Pb exposure risks through the soil-grain-human pathway. A site-specific bioconcentration factor (BCF, ratio of Pb concentration in plant to that in soil) was calculated and used to assess grain Pb intake risks instead of a generic BCF value to reduce data uncertainty. In addition to soil pH, cation-exchange capacity exerted a major influence on the Pb BCF variations in wheat, whereas the organic carbon dynamics affected the BCF variations in rice. Once normalized BCF against those soil variables, the distributions of BCF were log-normal in nature. Optimizing the pH and cation-exchange capacity of wheat soils would help protect 49.8% of local adults from excessive Pb dietary intake. The scenario soil thresholds linked to soil variables and grain Pb intake risks were then derived and validated by independent data from field surveys and published articles. Poor production practices in the wheat fields under study included using soils with low fertility.

Estimating accumulation rates and health risks of PAHs in residential soils of metropolitan cities.

Predicting temporal changes in PAH concentrations in urban soils and their corresponding health risk is essential for developing appropriate management measures to prevent those risks. Concentrations of PAHs in soils of residential areas with different building ages in three metropolitan cities were determined to estimate the accumulation rates of PAHs in soil. The mean concentrations of total PAHs (∑PAHs) were 1297 ng/g in Shanghai, 865 ng/g in Beijing, and 228 ng/g in Shenzhen. The primary sources of the PAHs were traffic and coal combustion for industrial activity and space heating. The high PAH concentrations in Shanghai were attributed to the relatively high average building age of the sampled residential areas and the low annual temperature in the city. The overall annual accumulation rates of PAHs in the soils were estimated from linear regressions between the PAH concentrations and building age of the residential areas. The annual accumulation rate of PAHs in the soils was 64.7 ng/g in Beijing, 24.2 ng/g in Shanghai, and 3.3 ng/g in Shenzhen. The higher rate in Beijing was due to the higher intensity of PAH emissions and the lower temperature. The regression estimations suggest that health risks posed by PAHs in residential soils of the metropolitan cities increase considerably with time.

Estimation of the accumulation rates and health risks of heavy metals in residential soils of three metropolitan cities in China.

Heavy metal concentrations in urban soils are likely to increase over time because of continuous urbanization and heavy metal emissions. To estimate the accumulation rates of heavy metals in urban soils, we collected soil samples from residential areas with different building ages in the metropolitan cities of Shanghai, Shenzhen, and Beijing, China. Heavy metal concentrations in the soils varied among the cities and were primarily affected by soil parent material and the intensity of anthropogenic sources. Regression analyses revealed that the accumulation rates of Cd and Cu in the soils ranged from 0.0034 to 0.0039 mg/(kg•year) and 0.343 to 0.391 mg/(kg•year), respectively, and were similar across the three cities, while accumulation rates of Zn and Pb in Shanghai were higher than those in Shenzhen and Beijing. The higher accumulation rates of Zn and Pb in Shanghai can be explained by differences in city history and industrial structures among the cities. Residential soils with high health risks posed by the heavy metals were mostly collected from old towns of Shanghai because of high Pb content in the areas. Although recent urbanization resulted in elevated concentrations of Cd, Cu, Zn, and Pb in the residential soils, the effect on the total health risks of residents exposed to the soils was negligible.

Evaluation of joint toxicity of heavy metals and herbicide mixtures in soils to earthworms (Eisenia fetida).

It is widely acknowledged that a simplified and robust approach to evaluating thecombined effects of chemical mixtures is critical for ecological risk assessment (ERA) of contaminated soil. The earthworm (Eisenia fetida) was used as a model to study the combined effects of polymetallic contamination and the herbicide siduron in field soil using a microcosm experiment. The responses of multiple biomarkers, including the activities of catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR) and acetylcholine esterase (AChE), the concentrations of glycogen, soluble protein (SP), malonaldehyde (MDA), and metallothionein (MT), and the neutral red uptake test (NRU), were investigated. Multivariate analysis, Principal Component Analysis (PCA) and Spearman's Rank Correlations analysis (BVSTEP) revealed that the activities of AChE and CAT and the NRU content were the prognostic biomarkers capturing the minimum data set of all the variables. Internal Cd (tissue Cd) in earthworms was closely related to the health status of worms under combined contamination of heavy metals and siduron. The integrated effect (Emix) calculated based on the activities of AChE and CAT and NRU content using the stress index method had significantly linear regression with internal Cd (p<0.01). Emix(10), Emix(20), and Emix(50) were then calculated, at 1.27, 1.63 and 2.71 mg/kg dry weight, respectively. It could be concluded that a bioassay-based approach incorporating multivariate analysis and internal dose was pragmatic and applicable to evaluating combined effects of chemical mixtures in soils under the guidance of the top-down evaluation concept of combined toxicity.

Ecological risk assessment of polymetallic sites using weight of evidence approach.

Ecological risk assessment (ERA) of polymetallic contamination in soils has caused extensive solicitude. However, objective and feasible methods suitable for soil ERA are limited. Therefore, in this study, a multidisciplinary and quantitative weight of evidence approach (WOE) specific to soil ecosystems was developed based on the previous WOE for aquatic ecosystems. The framework consisted of four lines of evidence (LOEs): DTPA-extractable heavy metal in soils, bioaccumulation in earthworms, integration of biomarker responses and expected community effect (multi-substance Potentially Affected Fraction, msPAF). These four LOEs were initially evaluated by each hazard quotient (HQ) of them based on the ratio to the reference (RTR) of each parameter. Then, Environmental risk index (EnvRI) integrated by HQs with different weights was calculated. At last, three sites, one for reference (N1) and two for contaminated soils (N2 and N3) were chosen to apply the modified WOE approach. Results showed that heavily contaminated site, N3 had higher HQ classification for each LOE and its EnvRI was classified as Major levels, while the EnvRI of N2 was assigned into Moderate. What's more, HQ of biomarker response (HQbiomarker) integrated by RTRs of biomarkers increased gradiently with the increase of heavy metal levels in soils though irregular changes were observed for most of those biomarkers. Overall, our results indicated that the quantitative WOE framework specific to soil ERA had the advantage of obtaining a comprehensive and objective risk assessment.

Manganese, Zinc, and pH Affect Cadmium Accumulation in Rice Grain under Field Conditions in Southern China.

Very little has been reported on the effects of pH, Zn, and Mn on Cd uptake in rice ( L.) and their levels under field conditions. Rice accumulates a high concentration of Cd in acid soils, even at low soil Cd levels. Lime (CaO) was spread at 1200 kg ha on the topsoil of a rice field during the tillering stage. Effects of liming on rice Cd, soil pH, and amorphous Mn (MnO-AM) were then investigated. Slight increases in pH from 5.17 to 5.45 and MnO-AM from 66.3 to 82.1 mg kg were observed after liming. The proportion of rice samples with a Cd concentration greater than the Chinese rice Cd standard (0.2 mg kg dry wt. in grain) decreased by ∼15%. The pH, which varied from 4.8 to 5.8, did not significantly affect rice Cd, whereas soil Cd and Zn had a significantly positive effect, together accounting for ∼14% of the variance. Soil Mn had significantly negative effects on rice Cd, accounting for >18% of the variance. For a Cd concentration <0.2 mg kg dry wt. in rice grain, the critical pH value in paddy soil was ∼5.7, and that for Mn at pH 4.8 to 5.8 was ∼300 mg kg. Our findings showed that Cd concentration in rice grain in an acid paddy soil increased with an increase of Zn and a decrease of Mn when these metals were at sufficient levels.

Effects of urbanization on heavy metal accumulation in surface soils, Beijing.

Urbanization processes affect the accumulation of heavy metals in urban soils. Effects of urbanization on heavy metal accumulation in soils were studied using Beijing as an example. It has been suggested that the ecological function of vegetation covers shifting from natural to agricultural settings and then to urban greenbelts could increase the zinc (Zn) concentrations of soils successively. The Zn concentration of urban soils was significantly correlated to the percentage of the impervious land surface at the 500m×500m spatial scale. For urban parks, the age or years since the development accounted for 80% of the variances of cadmium (Cd) and Zn in soils. The population density, however, did not affect the heavy metal distributions in urban soils. To conclude, the urban age turned out to be a notable factor in quantifying heavy metal accumulation in urban soils.

Effects of Reclaimed Water on the Characteristics of Dimethyl Phthalate Adsorption on Sediments.

Adsorptions of Dimethyl Phthalate (DMP) on three sediments in both reclaimed and ultrapure water were studied using the batch technique and the effects of reclaimed water on it were clarified. The data were interpreted by using Freundlich and Dubinin-Radushkviech models. The values of 1/n were among 0.207 to 0.766, showing the presence of multiple adsorption sites on sediments. Compared with the ultrapure water as the background solution, the adsorption capacities of sediments for DMP were reduced in case of reclaimed water due to the competition of substances in reclaimed water. The mean adsorption energy, E, is smaller in the reclaimed water than that in ultrapure water.

Mass balance-based regression modeling of Cd and Zn accumulation in urban soils of Beijing.

Accumulation of heavy metals in urban soil can pose adverse impacts on public health and terrestrial ecosystems. We developed a mass balance-based regression model to simulate the heavy metal accumulation in urban soils as a function of time and to explore connections between metal concentration and urbanization processes. Concentrations of Cd and Zn in 68 residential soil samples in the urban area of Beijing were used. The background concentrations, the loss rates and the input fluxes of Cd and Zn in urban soils of Beijing during the last three decades were estimated using a regression of the time series of accumulations of the metals. Based on the regression estimates, we simulated the general trends of Cd and Zn accumulation in the soils from 1978 to 2078. The concentrations of Cd and Zn in urban soil generally increased with the population growth, vehicle use and coal consumption. The mean concentrations of Cd and Zn in urban soil of Beijing would increase by 3 fold over the next 70years for the current development scenario. The mass balance-based regression approach, which is able to reconstruct the history data of urban soil pollution, provides fundamental information for urban planning and environmental management.

Distribution and risks of polycyclic aromatic hydrocarbons in suburban and rural soils of Beijing with various land uses.

We investigated the sources, distribution, and health risks of polycyclic aromatic hydrocarbons (PAHs) in soils of peri-urban Beijing. The mean concentrations of total 16 PAHs in suburban and rural soils of Beijing were 321.8 ± 408.2 and 219.2 ± 233.5 ng/g, respectively. The PAH concentrations decreased along the urban-suburban-rural gradient and varied with land use categories. The industrial areas had the highest soil PAH concentrations followed by the living areas, roadsides, green areas, and agricultural areas. The major sources of PAHs in these soils were coal and biomass combustion. Traffic emission was not the dominant source of PAHs in peri-urban Beijing. At a few sites, high soil PAH contents were caused by point sources such as iron and steel plants and a wood preservative factory. The incremental lifetime cancer risks (ILCRs) of adults and children exposed to PAHs in the soils were acceptable. However, cautions should be paid to the abandoned industrial sites, which might be converted to residential area during the urbanization process.

Effects of land use intensity on the natural attenuation capacity of urban soils in Beijing, China.

Urban soils are major sinks that provide the services of attenuating and detoxifying environmental pollutants. This significant ecosystem service of urban soil can be evaluated by the natural attenuation capacity (NAC). In this research, we develop a method to calculate the natural pollutant attenuation capacity of urban soils on the basis of 5 chemical and physical measurements. By selecting municipal parks soils for reference, we assessed the spatial and temporal changes of NAC in Beijing city soils under influences of rapid urbanization. Results indicated that NAC was increasingly impacted by land use in the order: parks

Bayesian risk prediction model: An accessible strategy to predict cadmium contamination risk in wheat grain grown in alkaline soils.

Excessive cadmium (Cd) concentration in wheat grain is becoming a widespread concern in China. Considering the complexity of Cd transfer in the soil-wheat system, how the Cd risk in wheat grain be accurately predicted from the limited details available is of great significance for the risk management of Cd. Bayes' theory could leverage existing data by combining prior information and observational data, providing a promising strategy with which to calculate a more robust posterior probability of a grain sample exceeding the food safety standard (FSS) for Cd (0.1 mg kg-1). In the current study, a risk prediction model, based on Bayes' theory, was established to achieve a more accurate prediction of the wheat grain Cd risk from a limited number of soil parameters. The risk prediction model could predict the risk probability of wheat grain with a Cd concentration exceeding the FSS under a given soil concentration of either total Cd or diethylenetriaminepentaacetic acid (DTPA)-extractable Cd. Soil total Cd concentration proved to be a better variable for the model with greater predictive accuracy. The model predicted that fewer than 5% of the wheat grain would have a Cd concentration exceeding the FSS when grown in soil with a total Cd concentration of less than 0.299 mg kg-1. The risk probability rose significantly to 50% when the soil total Cd reached 0.778 mg kg-1. The accuracy of the model was greater than the widely applied multiple linear regression model, whereas previously published data from similar soil conditions also confirmed that the Bayesian model could predict wheat Cd risk with minimal error. The proposed model provides an accurate, accessible and cost-effective methodology for predicting Cd risk in wheat grown in alkaline soils before harvest. The wider application to other soil conditions, crops or contaminants using the Bayesian model is also promising for risk management authorities.

Space-specific flux estimation of atmospheric chemicals from point sources to soil.

Predicting chemical flux to soil from industrial point sources accurately at a regional scale has been a significant challenge due to high uncertainty in spatial heterogeneity and quantification. To address this challenge, we developed an innovative approach by combining California Air Resources Board Puff (CALPUFF) and mass balance models, leveraging their complementary strengths in quantitative accuracy and spatial precision. Specifically, CALPUFF was used to predict the polycyclic aromatic hydrocarbons (PAHs) flux to soil due to industrial sources. Additionally, the spatial distribution coefficient of PAHs flux (e.g., si for spatial unit i) was calculated by neural network and combined with the mass balance model to obtain the results of total PAHs fluxes, which were then combined with the results predicted by CALPUFF to effectively estimate the contribution of industrial sources to soil PAHs flux. Taking a petrochemical industry region located in Zhejiang province, China as a case study, results showed the input Phenanthrene (Phe) and Benzo(a)pyrene (BaP) fluxes predicted by CALPUFF were generally lower than those by the mass balance model, with slightly different distribution patterns. CALPUFF results, based on 36 industrial sources, partially represent those of the mass balance model, which includes all sources and pathways. It was suggested that industrial sources contributed 49%-89% and 65%-100% of soil Phe and BaP, respectively across the study area. The average Phe flux from point sources by deposition averaged 2.68 mg m-2∙a-1 in 2021, accounting for approximately 60% of the total Phe flux to soil. The average BaP flux from point sources by deposition averaged 0.0755 mg m-2∙a-1, accounting for only 0.1%-3.65% of the total BaP flux to soil. Thereby, our approach fills up a gap between the relevance to point sources and the accuracy of deposition quantification in estimating chemical flux from specific point sources to soil at a regional scale.

Comparative study on anthropogenic impacts on soil PAHs: Accumulation and source apportionment in tourist and industrial cities in Hebei Province, China.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous organic contaminants in urban soils. The accumulation and source identifications of PAHs within a city have been frequently studied. However, impacts of urbanization development modes on PAHs accumulation patterns by taking a city as a whole have been seldom reported. Four cities with two development modes in Hebei province, Chengde and Zhangjiakou (tourist cities) and Handan and Tangshan (industrial cities), were selected. The concentrations of 16 priority PAHs in soils in the study areas were investigated. The results showed that the average concentrations of Σ16PAHs in Handan (2517 µg/kg) and Tangshan (2256 µg/kg) were more than twice of those in Chengde (696 µg/kg) and Zhangjiakou (926 µg/kg) approximately. Lines of evidence, provided by a combination of diagnostic ratios, pairwise correlation, and PMF methods, revealed that the dominant sources of PAHs in either city were industrial emission, vehicle emission, and petrogenic/biogenic process but with different proportions. Linear fittings based on Bayesian kernel machine regression analysis (BKMR) were constructed to illustrate the impact of industrialization on PAHs accumulation. The probability of excessing the 10 % (376 µg/kg) and 50 % (1138 µg/kg) of current ∑16PAHs would be higher than 90 % given the gross industrial production per unit area >5.00 × 106 and 20.5 × 106 CNY/km2, respectively. The proposed threshold values of industrialization are of significance for determining industrial structure and proportion in urban management.

Soil environmental carrying capacity and its spatial high-precision accounting framework.

Human activity intensity should be controlled within the carrying capacity of soil units, which is crucial for environmental sustainability. However, the existing assessment methods for soil environmental carrying capacity (SECC) rarely consider the relationship between human activity intensity and pollutant emissions, making it difficult to provide effective early warning of human activity intensity. Moreover, there is a lack of spatial high-precision accounting methods for SECC. This study first established a spatial soil environmental capacity (SEC) model based on the pollutant thresholds corresponding to the specific protection target. Next, a spatial net-input flux model was proposed based on soil pollutants' input/output fluxes. Then, the quantitative relationship between human activity intensity and pollutant emissions was established and further incorporated into the SECC model. Finally, the spatial high-precision accounting framework of SECC was proposed. The methodology was used to assess the SECC for the copper production capacity in a typical copper smelting area in China. The results showed that (i) the average SECs for Cu, Cd, Pb, Zn, As and Cr are 427.89, 16.84, 306.41, 376.8, 71.63, and 392.7 kg hm-2, respectively; (ii) heavy metal (HM) concentrations and land-use types jointly influence the spatial distribution pattern of SEC; (iii) atmospheric deposition is the dominant HM input pathway and the high net-input fluxes are mainly located in the southeast of the study area; (iv) with the current human activity intensity for 50 years, the average SECs for Cu, Cd, Pb, Zn, As and Cr are 202.31, 1.71, 20.9, 66.15, 36.73, and 3 kg hm-2, respectively; and (v) to maintain the protection target at the acceptable risk level within 50 years, the SECC for the increased copper production capacity is 1.53 × 106 t. This study provided an effective tool for early warning of human activity intensity.

Ecological risks of polycyclic musk in soils irrigated with reclaimed municipal wastewater.

HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8-hexamethylcyclopenta-c-2-benzopyrane) and AHTN (7-acetyl-1,1,3,4,4,6-hexamethyl-1,2,3,4-tetrahydronaphthalene) are found in reclaimed municipal wastewater. They may accumulate in soils receiving long-term application of reclaimed water thus adversely impact the soil biota. We evaluated the extent of their accumulation in receiving soils using HYDRUS-1D based on reclaimed municipal wastewater irrigation data at a public park in Beijing. The potential for ecological harms were assessed according to tested and reported outcomes of acute toxicity tests using wheat (Triticum aetivum L), earthworm (Eisenia fetida) and springtail (Bourletiella hortensis) as target organisms. Results of comparison among EC50 values from wheat, earthworm and springtail showed the EC50 value for root elongation inhibition of wheat germination was the least. Based on the least EC50, predicted no effect concentration in soils were 290 and 320ng /g for HHCB and ATHN, respectively. Comparable results from simulation to experimental and field investigating date validated the using of HYDRUS-1D in the work. Results of risk prediction showed it would take 243 and 666 years for HHCB and AHTN accumulated in soils at current irrigation practice to reach the levels for the resulting risk characterization ratios (RCRs) to cause potential ecosystem harms.

Heavy metal pollution triggers a shift from bacteria-based to fungi-based soil micro-food web: Evidence from an abandoned mining-smelting area.

Heavy metals pose significant threats to soil biota, ultimately disrupting soil micro-food web. However, no studies have yet elucidated the impact of heavy metals on soil micro-food web. In this study, we explored the response of bacteria, fungi, nematodes, and soil micro-food web along a gradient of heavy metals in an abandoned smelting-mining area. We found that bacteria responded strongly to heavy metals, whereas fungi showed greater resistance and tolerance. Nematodes responses were less apparent. With the increasing levels of heavy metal pollution, the importance of heavy metal-tolerant organisms in micro-food webs increased significantly. For instance, the keystone bacteria in soil micro-food web shifted from copiotrophic to oligotrophic types, while the keystone nematodes shifted from to bacterial-feeding (e.g., Eucephalobus) to fungal-feeding species (e.g., Ditylenchus). Additionally, elevated heavy metal concentrations increased the proportion of fungi (e.g., Mortierellomycota), intensifying their interactions with bacteria and nematodes and causing a shift from bacteria-based to fungi-based soil micro-food web. Furthermore, heavy metal contamination induced a more complex and stable soil micro-food web. Overall, we highlight the changes in soil micro-food web as a mechanism for coping with heavy metal stress. Our study provides valuable insights into how heavy metal pollution can cause shifts in soil micro-food webs and has critical implications for enhancing our understanding of the ecological consequences of environmental pollution at the ecosystem level.

Site-specific ecological effect assessment at community level for polymetallic contaminated soil.

Current ecological risk assessment (ERA) is based more on book-keeping than on science especially for terrestrial ecosystems due to the lack of relevance to real field. Accordingly, site-specific ecological effect assessment is critical for ERA, especially at high tiers. This study developed procedures to assess ecological effect at community level based on field data. As a case study, we assessed ecological effect of polymetallic contamination in soil in the surrounding of an abandoned mining and smelting site in Hunan, China. Firstly, Zn was identified as the dominant contaminant in soil and slope gradient (SG) and pH as environmental impact factors using distance-based redundancy analysis(db-RDA). Secondly, sensitive endpoints were screened using correlation analysis between Zn and parameters of plant community composition and functional traits. Thirdly, exposure-effect curves between Zn and screened endpoints were developed by taking SG and pH as covariates using Bayesian kernel machine regression analysis (BKMR), based on which half-effect concentrations (EC50s) and 10 %-effect concentrations (EC10s) of soil Zn for each endpoint were calculated. Finally, site-specific hazardous concentrations (HC50s) of Zn were estimated. It was revealed site-specific EC50s and EC10s for soil Zn ranged 80.5-201 mg kg-1 and 342-893 mgkg-1, respectively, and HC50s based on EC10s and EC50s ranged 104-110 mg kg-1 and 595-612 mg kg-1, respectively, which are more specific and inclusive than those obtained based on crop and vegetable seed germination and seedling growth toxicity experiments.

A machine learning based approach for estimating site-specific partition coefficient Kd of organic compounds: Application to nonionic pesticides.

The partitioning coefficient Kd for a specific compound and location is not only a key input parameter of fate and transport models, but also critical in estimating the safety environmental concentration threshold. In order to reduce the uncertainty caused by non-linear interactions among environmental factors, machine learning based models for predicting Kd were developed in this work based on literature datasets of nonionic pesticides including molecular descriptors, soil properties, and experimental settings. The equilibrium concentration (Ce) values were specifically included for the reason that a varied range of Kd corresponding to a given Ce occurred in a real environment. By transforming 466 isotherms reported in the literature, 2618 paired equilibrium concentrations of liquid-solid (Ce-Qe) data points were obtained. Results of SHapley Additive exPlanations revealed that soil organic carbon, Ce, and cavity formation were the most important. The distance-based applicability domain analysis was conducted for the 27 most frequently used pesticides with 15952 pieces of soil information from the HWSD-China dataset by setting three Ce scenarios (i.e., 10, 100, and 1000 µg L-1). It was revealed the groups of compounds showing log Kd < 0.06 and log Kd > 1.19 were composed mostly of those with log Kow of -0.800 and 5.50, respectively. When log Kd varied between 0.100 and 1.00, it was impacted by interactions among soil types, molecular descriptors, and Ce comprehensively, which accounted for 55% of the total 2618 calculations. It could be concluded that site-specific models developed in this work are necessary and practicable for the environmental risk assessment and management of nonionic organic compounds.