Soil and groundwater pollution in industrial parks arises from multiple pollution sources and overlapping spatiotemporal risk processes, posing a persistent threat to human health. Integrating remote sensing imagery with multi-source data is a promising approach for quantifying and mapping pollution risk distributions. However, the potential of high-resolution historical remote sensing imagery to capture long-term dynamic indicators at critical facility scale remains underutilized. This study develops a dynamic pollution risk assessment framework within a source-pathway-receptor paradigm, incorporating both static and dynamic indicators. A key innovation is the integration of long-term sub-meter remote sensing imagery, which enables the synchronous delineation of potential pollution areas and extraction of remote-sensing-based dynamic (RSD) indicators, such as surface rust, construction activities, and vegetation cover dynamics. The proposed method was applied to evaluate both current (2024) and historical cumulative (2005-2024) risks in a typical petrochemical industrial park in the Beijing-Tianjin-Hebei region. Correlation analysis and Light Gradient Boosting Machine (Light GBM) regression were employed to investigate the temporal variations in key drivers. Results indicated that cumulative effects increased overall pollution risk by 23.4%. Although the composition of pollution risks exhibited spatiotemporal heterogeneity, current risk was predominantly governed by chemical inventory and equipment age, while the contribution of dynamic indicators increased markedly with historical risk accumulation. This dynamic driving mechanism highlights the necessity of simultaneously controlling current risks and mitigating cumulative risks. The proposed methodology enables comprehensive and temporally explicit evaluation of pollution risks, supporting the transition of industrial parks from end-of-pipe remediation toward proactive, source-oriented risk prevention.

Metal slag has become an increasing environmental concern because of its hazardous constituents, prompting global initiatives to remove historical stockpiles as part of soil remediation programs. However, evaluating the effectiveness of these clearance efforts remains challenging, as residual slag-derived contamination is difficult to distinguish from geogenic backgrounds or anthropogenic inputs. This study aims to quantitatively assess the efficacy of aluminum-steel slag stockpile clearance by integrating lead (Pb) isotopic signatures with partial extraction techniques to evaluate changes in soil contamination before and after remediation. Based on the significant correlation between 1/Pb and the 206Pb/207Pb ratio, a binary mixing model was employed for source apportionment, thereby confirming a shared metal slag source. Model calculations indicate a significant reduction in the relative contribution of metal slag, which decreased from 95.2% pre-clearance to 41.4% post-clearance, reflecting a reduction of approximately 55.9%. Meanwhile, the absolute Pb concentration fell dramatically from 557.3 mg/kg to 20.6 mg/kg, representing a decrease of about 96.3%. This notable divergence underscores that while absolute mass reduction validates the effectiveness of remediation efforts, the persistent relative contributions highlight reconfigured source dynamics crucial for long-term stewardship. Our study establishes Pb isotopic analysis as a robust methodology that surpasses conventional bulk concentration measurements in assessing the success of environmental cleanup.

Mercury contamination at ammunition production sites represents a significant environmental issue due to its widespread dispersion, complex biogeochemical behavior, and long-term ecological risks. This study aims to develop an integrated approach combining geospatial analysis, mechanistic investigation, pollution assessment, and remediation design to systematically understand and mitigate mercury pollution—from source identification to sustainable control. The study employed geospatial analysis to delineate contamination distribution and identify key drivers affecting mercury migration, including source location, soil organic matter, pH, and particle size. A probabilistic health risk assessment was conducted to evaluate non-carcinogenic hazards across demographic groups. Remediation trials included ferric chloride treatment coupled with thermal processing (up to 350 °C for 10 weeks), as well as the application of a composite chemical agent to immobilize and capture leachable mercury. Results revealed severe mercury contamination, with a mean pollution index (Pi) of 22.17, indicating significant accumulation in hotspots. Key factors such as soil properties strongly influenced mercury mobility. Health risk assessment indicated unacceptable non-carcinogenic risks at the 95th percentile for all populations (hazard quotient: 1.41E + 01–1.78E + 01). Remediation experiments demonstrated that ferric chloride combined with thermal treatment reduced soil mercury content by 99.9

Benzo[a]pyrene (BaP) has attracted increasing attention due to its high toxicity. However, determining its ecological threshold through species sensitivity distribution is challenging, primarily due to a lack of ecotoxicity data for BaP-contaminated soils. This study examined the ecotoxicity of BaP on earthworms and its effect on soil dehydrogenase activity and nitrogen transformation processes, aiming to derive its ecological threshold using these representative receptors. Our results show a notable avoidance behavior and reduced weight gain in earthworms, along with a non-linear response in their antioxidant enzyme system. Exposure to BaP significantly altered microbial species composition and reduced diversity, leading to increased dehydrogenase activity and inhibited nitrogen transformation processes. This suggests that BaP induces oxidative stress in earthworms and impairs soil functions. Statistical modeling determined the ecological threshold for BaP in soil to be between 1.17 and 13.30 mg/kg. To ensure sensitivity protection and ecological safety, a reference value of 1.17 mg/kg is recommended for screening purposes. A comprehensive cost-benefit analysis of a contaminated site revealed that adopting this threshold could reduce remediation costs by 54.2 % compared to the current standard, yielding significant economic and ecological benefits.

Automotive technicians are exposed to lead during maintenance operations, and the associated risks remain unexplored. This study utilized the ghost wipe as a sampling medium to collect particulates on the wall surfaces from 12 automobile repair workshops. The measured lead deposition ranged from 15.2 +/- 0.06 to 416.9 +/- 83.13 mu g/m2. A linear correlation was observed between lead deposition and the number of repaired automotives. A lead deposition-air model was developed to estimate lead concentrations within automotive workshops. Three additional workshops were investigated, and the measured lead depositions of them are similar to the model ' s prediction. Furthermore, the lead emission factor (Cc: 0.0625 mu g/m3/car) was evaluated, and a risk model was developed based on Cc, employment duration, and annual number of repaired automotives. It was verified that wearing protective masks during maintenance operations and maintaining an acceptable air exchange rate can effectively reduce lead exposure. In summary, our study introduces the lead deposition-air model as a novel method for assessing occupational exposure in the context of particulate matter contamination.

Site-specific arsenic (As) bioaccessibility data can improve the accuracy of health risk assessments, but direct measurements are costly and time-consuming. Even when available, measured values such as the mean still yield remediation targets below natural background levels, limiting their practical use. Existing predictive models, including linear regressions and some machine learning (ML) approaches, often rely on artificially spiked or limited field-aged samples with high As concentrations, reducing their generalizability. A global dataset of 1458 records of As bioaccessibility in field-aged soils from studies since the 1990s were complied, covering a wide range of As concentrations (As-T) and soil properties. Gastric bioaccessibility showed a log-normal distribution with a mean of 23.4 %. Among eight ML models, the Random Forest (RF) model performed best (R² = 0.86, RMSE = 0.58). As-T explained 73.2 % of the variance, with significant relationships observed with Fe, Mn, organic carbon, and pH. Applied to a contaminated sintering site in southwest China, the RF-informed probabilistic risk assessment yielded a remediation target three times higher than current standards and reduced soil remediation volume and carbon emissions by 79.1 %. This study highlights the potential of ML to enhance risk assessment accuracy and support more sustainable site remediation strategies.

Dietary uptake is the main pathway of exposure to polycyclic aromatic hydrocarbons (PAHs). However, there is no data regarding the pollution and health risks posed by PAHs in Lilium davidii var. unicolor. We measured the concentrations of 16 PAHs in lily bulbs from Lanzhou; analyzed the bioaccumulation, sources, and pollution pathways of PAHs; assessed the influence of baking on PAH pollution in the bulb; and assessed the cancer risks associated with PAH exposure via lily consumption. The total PAH concentrations in raw bulbs were 30.39-206.55 μg kg-1. The bioconcentration factors of total PAHs ranged widely from 0.92 to 5.71, with a median value of 2.25. Pearson correlation analysis revealed that the octanol-water partition coefficients and water solubility values played important roles in the bioaccumulation of naphthalene, fluorene, phenanthrene, pyrene, and fluoranthene in the raw bulb by influencing PAH availability in soil. Correlation analysis and principal component analysis with multivariate linear regression indicated that biomass and wood burning, coal combustion, diesel combustion, and petroleum leakage were the major sources of PAHs in the raw bulbs. The paired t-test showed that the PAH concentrations in the baked bulbs were higher than those in the raw bulbs. PAH compositions in lily bulb changed during the baking process. Baked bulbs exhibited a higher cancer risk than raw bulbs. Local adults had low carcinogenic risks from consuming lily bulbs. This study fills the knowledge gap about PAH pollution and the related health risks of PAHs in the Lanzhou lily.

The mechanisms of triclosan (TCS) adsorption onto polyamide (PA), polystyrene (PS), polyvinylchloride (PVC) and low-density polyethylene (LDPE) microplastics (MPs) were investigated, along with the effects of solution pH, ionic strength, and dissolved organic matter (DOM). The Linear model better described TCS adsorption isotherms suggesting that hydrophobic partitioning was the primary mechanism for TCS adsorption, while the Freundlich and Langmuir model fittings showed that TCS adsorption onto MPs was favorable. Following normalization by the specific surface area (SSA) of MPs, adsorption distribution coefficient (Kd) values of 105.70, 0.56, 0.20, and 0.08 L/m2 were determined for PA, PS, PVC, and LDPE MPs, respectively. Hydrophobic interaction was the main adsorption mechanism, although other mechanisms, governed by the specific structure and functional groups of the MPs, also contributed. These included the formation of hydrogen bonds between the -OH on TCS (H-bond-donating) and the amide groups on PA (H-bond-accepting), and the π-π interactions between the benzene rings of PS and TCS, and hydrogen bonds between -OH on TCS and -COO-/-COOH on PVC MPs. TCS adsorption by MPs was found to be pH-dependent, indicating that TCS0 was the main species involved in adsorption. The effects of ionic strength on TCS adsorption were not significant and therefore could be ignored. Humic acid (HA) impeded the adsorption of TCS by PA, PS, and LDPE MPs, potentially due to the hydrophobic interactions of HA with the three MPs, the hydrogen bonds with PA MPs, and the π-π interactions with PS MPs, all of which competed with TCS for adsorption sites. Fulvic acid (FA) inhibited TCS adsorption onto PS MPs, as FA could be sorbed by PS MPs through π-π interactions, competing with TCS for adsorption sites. These findings improve the accuracy of risk evaluations for organic pollutants such as TCS when co-occurring with MPs, furthering our understanding of the impacts of complex pollutant mixtures on both human and environmental health.

The historical large mercury slag piles still contain high concentrations of mercury and their impact on the surrounding environment has rarely been reported. In this study, three different agricultural areas [the area with untreated piles (PUT), the area with treated piles (PT), and the background area with no piles (NP)] were selected to investigate mercury slag piles pollution in the Tongren mercury mining area. The mercury concentrations of agricultural soils ranged from 0.42 to 155.00 mg/kg, determined by atomic fluorescence spectrometry of 146 soil samples; and mercury concentrations in local crops (rice, maize, pepper, eggplant, tomato and bean) all exceeded the Chinese food safety limits. Soil and crop pollution trends in the three areas were consistent as PUT > PT > NP, indicating that mercury slag piles have exacerbated pollution. Mercury in the slag piles was adsorbed by multiple pathways of transport into soils with high organic matter, which made the ecological risk of agricultural soils appear extremely high. The total hazard quotients for residents from ingesting mercury in these crops were unacceptable in all areas, and children were more likely to be harmed than adults. Compared to the PT area, treatment of slag piles in the PUT area may decrease mercury concentrations in paddy fields and dry fields by 46.02% and 70.36%; further decreasing health risks for adults and children by 47.06% and 79.90%. This study provided a scientific basis for the necessity of treating large slag piles in mercury mining areas.

Cadmium (Cd) pollution has gained significant attention in mangrove sediments due to its high toxicity and mobility. However, the sources of Cd and the factors influencing its accumulation in these sediments have remained elusive. In this study, we utilized lead (Pb) isotopic signatures for the first time to assess Cd contamination in mangrove sediments from the northern region of the Beibu Gulf. A strong correlation was observed between Cd and Pb concentrations in the mangrove sediments, suggesting a shared source that can be estimated using Pb isotopic signatures. By employing a Bayesian mixing model, we determined that 70.1 ± 8.2% of Cd originated from natural sources, while 12.9 ± 4.9%, 9.8 ± 3.7%, and 7.1 ± 3.4% were attributed to agricultural activities, non-ferrous metal smelting, and coal combustion, respectively. Our study clearly suggests that natural Cd could also dominate the high Cd content. Agricultural activities were the most important anthropogenic Cd sources, and the increased anthropogenic Cd accumulation in mangrove sediment was related to organic matter. This study introduces a novel approach for assessing Cd contamination in mangrove sediment, providing useful insights into Cd pollution in coastal wetlands.

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The precise range of contamination determines the cost of treating heavy metals contamination of soils at industrial sites and was a key aspect of soil heavy metals contamination management. The pollution level and spatial correlation of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in one hundred and thirty topsoil samples from a typical contaminated site was analysed. Geochemical analysis showed that Hg pollution was the most serious in the site, followed by Cd, Pb, Zn, Cu and Cr. The contents of As and Ni in the soil did not exceed the background values. The interpolation accuracy, interpolation results and spatial distribution of inverse distance weight method (IDW), local polynomial method (LPI), radial basis function method (RBF) and ordinary kriging method (OK) were compared, respectively. The results show that the range, mean and coefficient of variation of the four interpolation methods were generally lower than that of the sampled data, which was mainly caused by smoothing effect. The smoothing effect of LPI and OK were the most serious, while the smoothing effect of IDW and RBF were not obvious. The optimal interpolation method of Cd, Cr, Hg, Pb and Zn in polluted sites was RBF and the optimal interpolation method for As, Cu and Ni was IDW. The evaluation of polluted area by IDW and RBF interpolation method was ranked as IDW > RBF, which was much larger than that calculated by sampling point. Both interpolation methods could increased the area of polluted area. The probability kriging (PK) method was similar to that based on sampling points, which can greatly improve the calculation accuracy of heavy metals polluted area in industrial contaminated sites. Geochemical data and spatial interpolation results show that phytoremediation techniques was the most suitable for remediation of heavy metal contaminated soils at this site.

The mechanisms of Triclosan (TCS) adsorption onto polyamide (PA), polystyrene (PS), polyvinylchloride (PVC) and low-density polyethylene (LDPE) MPs were investigated, along with the effects of solution pH, ionic strength and co-existing dissolved organic matter (DOM). Following normalization according to the specific surface area (SSA) of MPs, adsorption distribution coefficient (Kd) values of 105.70, 0.56, 0.20 and 0.08 L/m2 were determined for PA, PS, PVC and LDPE, respectively. Hydrophobic interactions were the main mechanism of TCS adsorption by MPs, although other adsorption mechanisms also occurred depending on the structure and functional groups of MPs. Other mechanisms contributing to TCS adsorption included the formation of hydrogen bonds between -OH on TCS (H-bond-donating) and the amide groups of PA (H-bond-accepting), π-π interactions with benzene rings of PS and H-bonds between -OH on TCS and -COO-/-COOH groups on PVC. TCS adsorption by MPs was also found to depend on the solution pH, indicating that TCS0 was the main species involved in the adsorption process. The effects of ionic strength on TCS adsorption were not significant and therefore, could be ignored. DOM had an inhibitory effect on the adsorption of TCS by certain MPs. HA impeded the adsorption of TCS by PA, PS and LDPE MPs, potentially due to the hydrophobic interaction of HA with the three MPs, and the formation of H-bonds with PA MPs, the π-π interaction with PS MPs, competing with TCS for adsorption sites. FA inhibited TCS sorption on PS MPs only, since FA can be sorbed by PS through π-π interactions between the benzene ring of FA and PS, thus competing with TCS for adsorption sites.These findings help improve the accuracy of risk evaluations for pollutants such as TCS when co-occurring with MPs, furthering our understanding of the impacts of complex pollutant mixtures on both human and environmental health.

Lead (Pb) pollution in sediments remains a major concern for ecosystem quality due to the robust interaction at the sediment/water interface, particularly in shallow lakes. However, understanding the mechanism behind seasonal fluctuations in Pb mobility in these sediments is lacking. Here, the seasonal variability of Pb concentration and isotopic ratio were investigated in the uppermost sediments of a shallow eutrophic drinking lake located in southeast China. Results reveal a sharp increase in labile Pb concentration during autumn-winter period, reaching ~ 3-fold higher levels than during the spring-summer seasons. Despite these fluctuations, there was a notable overlap in the Pb isotopic signatures within the labile fraction across four seasons, suggesting that anthropogenic sources are not responsible for the elevated labile Pb concentration in autumn-winter seasons. Instead, the abnormally elevated labile Pb concentration during autumn-winter was probably related to reduction dissolution of Fe/Mn oxides, while declined labile Pb concentration during spring-summer may be attributed to adsorption/precipitation of Fe/Mn oxides. These large seasonal changes imply the importance of considering seasonal effects when conducting sediment sampling. We further propose a solution that using Pb isotopic signatures within the labile fraction instead of the bulk sediment can better reflect the information of anthropogenic Pb sources.

The remediation goal (RG) for arsenic (As) calculated by the traditional method is approximately 0.45 mg·kg-1, significantly lower than the background values. This poses significant challenges for the management of As-contaminated sites. The present study focused on a typical glassworks site with an As contamination level of up to 298 mg·kg-1, predominantly existing as As (III), with a carcinogenic risk level as high as 8.6 × 10-5. We developed a novel method known as multi-media-equivalent dose (MMED), incorporating local exposure parameters, and investigated the impacts of site-specific bioaccessibility (from 6.9 % to 51.5 %) on the results. The RG of arsenic calculated via MMED was 34.4 mg·kg-1 and 54 mg·kg-1 when bioaccessibility was considered. Integrating with five exposure parameters across 31 provinces, the provincial remediation goals (PRGs) ranged from 15.1 to 31.7 mg·kg-1. The RG calculated using the new method were more aligned with the practical conditions of managing As-contaminated sites, with potential for broader implementation across various provinces.

Soil molybdenum (Mo) levels can reach ecologically hazardous levels. China has not yet established the relevant thresholds, posing challenges for environmental management. Therefore, we present our data relevant to Mo toxicity for several important species. By normalizing soil properties, we obtained a correlation model of Mo toxicity to Hordeum vulgare, as well as 31 models for the toxicity of other elements including Cu and Ni to invertebrates and microbial processes. Using interspecies correlation estimation (ICE) extrapolation, the sensitivity coefficient (0.12-0.71) for five plants were found. For invertebrates and microbial processes lacking Mo data, we used regression analysis to establish Mo toxicity models based on the soil quantitative ion character-activity relationships (s-QICAR; R2 =0.70-0.95) and known toxicities of other metal elements to invertebrate and microbial processes. Furthermore, combining species sensitivity distribution calculations, the HC5 values for protecting 95% of soil species from Mo in three typical soil scenarios in China were calculated. After correction, the predicted no -effect concentrations were 6.8, 4.8, and 3.4 mg/kg, respectively. This study innovatively combined ICE and s - QICAR to derive soil Mo thresholds. Our results can provide a basis for decision -making in the assessment and management of soil Mo pollution.

The iron and steel industry has always been a key and difficult point of environmental pollution control. In the present study, 493, 175, 153, 72, and 42 soil samples were collected from the soil depths of 0-0.5, 0.5-2, 2-3, 3-4, and 4-5 m (herein called the layers) of the Shougang Steel site, respectively. Compared with the evaluation criteria, the Shougang Steel surface soil was severely polluted by polycyclic aromatic hydrocarbons (PAHs). Inverse distance-weighted interpolation and the Kruskal-Wallis H test revealed that the soil PAH pollution in the iron-making area, especially the coking area, was severer than those in other areas. The PAH concentrations first decreased, and then, increased with the increase of depth. With the increase in depth, the contributions of 2- and 3-ring PAHs increased, while those of 4-, 5-, and 6-ring PAHs decreased. The bivariate local indicators of spatial association (LISA) analysis was used to identify the areas prone to soil PAH pollution due to atmospheric deposition of industrial waste gas and traffic emissions. The method could be used to analyze the impact of anthropogenic activities on soil's PAH pollution for other contaminated sites. Three main pollution sources of soil PAHs, the backfill source, the combustion of coal, and the traffic emissions, were identified based upon three diagnostic ratios, positive matrix factorization and the bivariate LISA analysis, and accounted for 53.8%, 23.5%, and 22.7%, respectively. The combination of bivariate LISA analysis and other source analysis methods could improve the accuracy of source analysis. Benzo[a]pyrene contributed the most to the total health risk among sixteen PAHs. The health risks related to the three pollution sources decreased in the order of backfill sources > coal combustion > traffic emissions. The incremental life-time carcinogenic risks were all below 10-4, indicating negligible or acceptable risks.

Apportioning the sources of heavy metals (HMs) in soil is of great importance for pollution control. A total of 64 soil samples from 13 sample points at depths of 0–21 m were collected along a proposed subway line in the southeast industrial district of Beijing. The concentrations, distribution characteristics, and sources of eight HMs were investigated. The results showed that the concentrations of Hg, Cd, Cu, Pb, As, and Zn in the topsoil (0–2 m) exceeded the Beijing soil background values. Three sources were identified and their respective contribution rates calculated for each of the HMs using multiple approaches, including correlation analysis (CA), top enrichment factor (TEF), principal component analysis (PCA), and positive matrix factor (PMF) methods. As (63.11%), Cr (61.67%), and Ni (70.80%) mainly originated from natural sources; Hg (97.0%) was dominated by fossil fuel combustion and atmospheric deposition sources; and Zn (72.80%), Pb (69.75%), Cu (65.36%) and Cd (53.08%) were related to traffic sources. Multiple approaches were demonstrated to be effective for HM source apportionment in soil, whilst the results using PMF were clearer and more complete. This work could provide evidence for the selection of reasonable methods to deal with soils excavated during subway construction, avoiding the over-remediation of the soils with heavy metals coming from natural sources.

Red mud (RM), a byproduct of aluminum production, is used as amendments to increase the pH and reduce the available Cd in soil, but the effects of RM treatments on rice and rhizosphere chemistry changes at different radial-oxygen-loss (ROL) rates and developmental stages remain unclear. To address this concern, a rhizobox trial was conducted to investigate the effect of 0%, 0.5%, and 1.0% RM, on Cd accumulation by rice cultivars differing in ROL rate (‘Zheyou12’ (ZY12), ‘Qianyou1’ (QY1), and ‘Chunjiangnuo2’ (CJN2)) at two growth stages (tillering and bolting). The results showed that mobility factors of Cd in the soil were decreased significantly at both stages. The Cd mobility factor (MF) of CJN2 was decreased by 33.01% under 1% RM treatment at bolting stage. The pH value was increased by 0.39–0.53 units at two stages. RM contains large amounts of metals, which can increase soil iron (Fe) and manganese (Mn) concentrations, reduce redox potential, and transform the available Cd into Fe/Mn oxide-bound Cd. In addition, the Fe plaque further increased to inhibit the transformation of Cd. These changes reduced the available Cd in the soil and further decreased Cd absorption by rice. With the increase in RM concentration, the shoot and root biomass increased, and Cd accumulation in the plant significantly decreased. Compared with that under 0% RM treatment, the shoot Cd concentrations of ZY12, QY1, and CJN2 under 1% RM treatment at the bolting stage decreased by 27.59%, 36.00%, and 46.03%, respectively. The relative Cd accumulation ability of the three rice cultivars was CJN2 < QY1 < ZY12. The ROL promotes Fe plaque formation on the root surface. The Fe plaque is an obstacle or buffer between Cd and rice, which can immobilize Cd in Fe plaque and further reduce Cd absorption by rice. The addition of RM, in combination with a high-ROL rice cultivar, is a potential strategy for the safe production of rice on Cd-contaminated soils.