Does the Geographic Difference of Soil Properties Matter for Setting Up the Soil Screening Levels in Large Countries Like China?

Impact of mixed benzene site exposure on bioaccessibility in simulated lung fluids and health risk assessment

Benzene series (BTEX) are predominant volatile organic compounds (VOCs) in petroleum production and downstream industrial sites, primarily enter human lungs via inhalation, posing significant health risks. To address the critical limitation of existing risk assessments that focus solely on individual components, this study investigated benzene and ethylbenzene based on contamination characteristics of petroleum refineries in Northwest China. An innovative in vitro membrane oxygenator system was developed to simulate single and mixed exposure scenarios at three soil concentrations: low (5 mg/kg), medium (10 mg/kg), and high (20 mg/kg), respectively. Health risk indices including inhalation risk (Inh), hazard quotient (HQ), and lifetime cancer risk (LCR) were calculated using bioaccessibility-adjusted parameters to precisely compare risk variations across exposure modes. Results demonstrated significant synergistic effects in gas-liquid mass transfer kinetics under mixed exposure (P < 0.05), the simulated lung fluid bioaccessibility of benzene and ethylbenzene was also significantly higher (P < 0.05), likely due to their intermolecular cosolvency. Risk assessment results indicated that Inh, HQ, and LCR indices in mixed exposure were significantly higher (P < 0.05) than in single exposure, with a concentration-dependent contribution to health risks. At low concentrations, benzene's health risk indices increased by 185 %-284 %, while ethylbenzene's increased by approximately 63 %-68 %, indicating a synergistic effect in mixed exposure scenarios. This study offers a new methodological basis for health risk assessment of BTEX mixed exposure at petrochemical sites.

Novel insight into deriving remediation goals of arsenic contaminated sites with multi-media-equivalent dose and local exposure parameters

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.

Risk hotspots and influencing factors identification of heavy metal(loid)s in agricultural soils using spatial bivariate analysis and random forest

Heavy metal(loid)s (HMs) in agricultural soils not only affect soil function and crop security, but also pose health risks to residents. However, previous concerns have typically focused on only one aspect, neglecting the other. This lack of a comprehensive approach challenges the identification of hotspots and the prioritization of factors for effective management. To address this gap, a novel method incorporating spatial bivariate analysis with random forest was proposed to identify high-risk hotspots and the key influencing factors. A large-scale dataset containing 2995 soil samples and soil HMs (As, Cd, Cr, Cu, Mn, Ni, Pb, Sb, and Zn) was obtained from across Henan province, central China. Spatial bivariate analysis of both health risk and ecological risks revealed risk hotspots. Positive matrix factorization model was initially used to investigate potential sources. Twenty-two environmental variables were selected and input into random forest to further identify the key influencing factors impacting soil accumulation. Results of local Moran's I index indicated high-high HM clusters at the western and northern margins of the province. Hotspots of high ecological and health risk were primarily observed in Xuchang and Nanyang due to the widespread township enterprises with outdated pollution control measures. As concentration and exposure frequency dominated the non-carcinogenic and carcinogenic risks. Anthropogenic activities, particularly vehicular traffic (contributing ∼37.8 % of the total heavy metals accumulation), were the dominant sources of HMs in agricultural soils. Random forest modeling indicated that soil type and PM2.5 concentrations were the most influencing natural and anthropogenic variables, respectively. Based on the above findings, control measures on traffic source should be formulated and implemented provincially; in Xuchang and Nanyang, scattered township enterprises with outdated pollution control measures should be integrated and upgraded to avoid further pollution from these sources.

Evaluating the protective capacity of soil heavy metals regulation limits on human health: A critical analysis concerning risk assessment - Importance of localization

Heavy metal pollution of agricultural soil is a major global concern, prompting the establishment of maximum allowable limits (MALs) to ensure food safety and protect human health. This study collected and compared MALs for six heavy metals (As, Cd, Hg, Pb, Zn, and Cu) in agricultural soils from representative countries and organizations (EU and WHO/FAO). The research evaluated the critical health risks and efficacy of these MALs under the hypothetical scenario of metals concentrations reaching the maximum allowable level. Safe thresholds for heavy metals were then derived based on maximum acceptable health risk levels. The comparative analysis revealed significant variations in the specific limit values and terms of MALs across countries and organizations, even for the same metal. This suggests that there is no consensus among countries and organizations regarding the level of metal-related health risks. Furthermore, the risk analysis of metal concentrations reaching the maximum level accentuated heightened risks associated with As, suggesting that the current risk of soil As exposure was underestimated, particularly for children. However, soil Cu, Cd, and Zn limits generally resulted in low health risks, implying that the current limits may overestimate their hazard. Overall, the results highlight that the current MALs for soil heavy metals may not fully safeguard human health. There is a critical need to optimize current soil MALs based on localized risks and the actual impact of these metals on human health. It is suggested to appropriately lower the limits of metals (such as As) whose impact on health risks is underestimated, and cautiously increase the limits of metals (such as Cu, Cd, and Zn) that currently pose minor health risks. This approach aims to reduce both over and insufficient protection problems of soil heavy metal MALs, emphasizing the importance of considering the locality in setting these limits.

Can we redevelop ammonia nitrogen contaminated sites without remediation? The key role of subsurface pH in human health risk assessment

Nitrogen fertilizer supports global food production, but its manufacturing results in substantial ammonia nitrogen (AN) contaminated sites which remain largely unexplored. In this study, ten representative AN contaminated sites were investigated, covering a wide range of subsurface pH, temperature, and AN concentration. A total of 7232 soil samples and 392 groundwater samples were collected to determine the concentration levels, migration patterns, and accurate health risks of AN. The results indicated that AN concentrations in soil and groundwater reached 12700 mg/kg and 12600 mg/L, respectively. AN concentrations were higher in production areas than in non-production areas, and tended to migrate downward from surface to deeper soil. Conventional risk assessment based on AN concentration identified seven out of the ten sites presenting unacceptable risks, with remediation costs and CO2 emissions amounting to $1.67 million and 17553.7 tons, respectively. A novel risk assessment model was developed, which calculated risks based on multiplying AN concentration by a coefficient fNH3 (the ratio of NH3 to AN concentration). The mean fNH3 values, primarily affected by subsurface pH, varied between 0.02 and 0.25 across the ten sites. This new model suggested all investigated sites posed acceptable health risks related to AN exposure, leading to their redevelopment without AN-specific remediation. This research offers a thorough insight into AN contaminated site, holds great realistic significance in alleviating global economic and climate pressures, and highlights the need for future research on refined health risk assessments for more contaminants.

Derivation of human health and odor risk control values for soil ammonia nitrogen by incorporating solid-liquid partitioning, ammonium/ammonia equilibrium: A case study of a retired nitrogen fertilizer site in China

Nitrogen fertilizer supports agricultural intensification, but its manufacturing results in substantial contaminated sites. Ammonia nitrogen is the main specific pollutant in retired nitrogen fertilizer sites with potential human health and odor risks. However, few studies focus on ammonia nitrogen risk assessment at contaminated sites, particularly considering its solid-liquid partitioning process (Kd) and ammonium/ammonia equilibrium process (R) in the soil. This study took a closed nitrogen fertilizer factory site as an example and innovatively introduced Kd and R to scientifically assess the human health and odor risk of ammonia nitrogen. The risk control values (RCVs) of ammonia nitrogen based on human health and odor risk were also derived. The maximum concentration of ammonia nitrogen was 3380 mg/kg in the unsaturated soil, which was acceptable for human health because the health RCVs were 5589 ∼ 137,471 mg/kg in various scenarios. However, odor risk was unacceptable for RCVs were 296 ∼ 1111 mg/kg under excavation scenarios and 1118 ∼ 35,979 mg/kg under non-excavation scenarios. Of particular concern, introducing Kd and R in calculation increased the human health and odor RCVs by up to 27.92 times. Despite the advancements in ammonia risk assessment due to the introduction of Kd and R, odor risk during excavation remains a vital issue. These findings inform a more scientific assessment of soil ammonia risk at contaminated sites and provide valuable insights for the management and redevelopment of abandoned nitrogen fertilizer plant sites.

Optimizing the development of contaminated land in China: Exploring machine-learning to identify risk markers

Often available for use, previously developed land, which includes residential and commercial/industrial areas, presents a significant challenge due to the risk to human health. China's 2018 release of health risk assessment standards for land reuse aimed to bridge this gap in soil quality standards. Despite this, the absence of representative indicators strains risk managers economically and operationally. We improved China's land redevelopment approach by leveraging a dataset of 297,275 soil samples from 352 contaminated sites, employing machine learning. Our method incorporating soil quality standards from seven countries to discern patterns for establishing a cost-effective evaluative framework. Our research findings demonstrated that detection costs could be curtailed by 60% while maintaining consistency with international soil standards (prediction accuracy = 90-98%). Our findings deepen insights into soil pollution, proposing a more efficient risk assessment system for land redevelopment, addressing the current dearth of expertise in evaluating land development in China.

Determining the soil odor control area: A case study of an abandoned organophosphorus pesticide factory in China

Currently, soil odor-active substance screening and evaluation methods for contaminated sites are underdeveloped, with unclear treatment objectives and areas. Consequently, some sites suffer from odor issues during and even after remediation. This study focused on an organophosphorus pesticide factory site in Guangdong Province, China. It established a method of determining the odorant control area using a comprehensive approach combining instrumental and olfactory soil sample analyses. The main odor-active substances identified were ethylbenzene, phenol, m, p-xylene, styrene, toluene, and o-xylene, with odorant control values (the limit of odor-active substance contents) of 35.2, 28.1, 8.0, 11.3, 40.2 and 89.3 mg/kg respectively. Instrumental analysis of soil samples revealed 11 sampling points where the main odor-causing substances exceeded standard levels. Among the substances, ethylbenzene (1.48E+04 mg/kg) had the highest content, exceeding the limit up to 421-fold. Olfactory analysis indicated 14 sampling points with odor intensity surpassing the standard (OI > 2). Based on the instrumental analysis results and the odorant control value, the initial estimated odor control area (area with the risk of odor nuisance) was 5.64E+03 m2. Incorporating the olfactory analysis findings, the control area was adjusted by 1.25E+03 m2, leading to a final calculated soil odor control area of 6.89E+03 m2 for the study site. The comprehensive approach to analyzing soil samples for odor control can help evaluate the extent of soil odor pollution in contaminated sites and provide a scientific basis for effectively removing and managing odor-causing substances in soil.

Reciprocal Interactions of Abiotic and Biotic Dechlorination of Chloroethenes in Soil

Chloroethenes (CEs) as common organic pollutants in soil could be attenuated via abiotic and biotic dechlorination. Nonetheless, information on the key catalyzing matter and their reciprocal interactions remains scarce. In this study, FeS was identified as a major catalyzing matter in soil for the abiotic dechlorination of CEs, and acetylene could be employed as an indicator of the FeS-mediated abiotic CE-dechlorination. Organohalide-respiring bacteria (OHRB)-mediated dechlorination enhanced abiotic CEs-to-acetylene potential by providing dichloroethenes (DCEs) and trichloroethene (TCE) since chlorination extent determined CEs-to-acetylene potential with an order of trans-DCE > cis-DCE > TCE > tetrachloroethene/PCE. In contrast, FeS was shown to inhibit OHRB-mediated dechlorination, inhibition of which could be alleviated by the addition of soil humic substances. Moreover, sulfate-reducing bacteria and fermenting microorganisms affected FeS-mediated abiotic dechlorination by re-generation of FeS and providing short chain fatty acids, respectively. A new scenario was proposed to elucidate major abiotic and biotic processes and their reciprocal interactions in determining the fate of CEs in soil. Our results may guide the sustainable management of CE-contaminated sites by providing insights into interactions of the abiotic and biotic dechlorination in soil.

Assessment of soil heavy metal pollution in provinces of China based on different soil types: From normalization to soil quality criteria and ecological risk assessment

Ecological risks can vary dramatically depending on abiotic factors, such as soil properties and the background values of elements. This study developed a framework for an integrated risk assessment system to derive soil quality criteria (SQC) for heavy metals (HMs) applicable to different soil types and to assess ecological risks at a multi-regional scale. Through the construction of normalization and species sensitivity distribution models, 248 SQC values for Cd, Pb, Zn, As, Cu, Cr, Sb, and Ni in 31 Chinese provinces were derived. These SQC considered the soil types and background values of the elements and effectively reduced the uncertainty caused by spatial heterogeneity. Using the derived SQC values, the qualitative and quantitative ecological risks of HMs in the terrestrial environment of China were comprehensively assessed using a three-level ecological risk assessment (ERA) approach. Compared to traditional ERA methods, the new methodology reached a more quantitative conclusion. The mean overall probabilities of ecological risk in China were 2.42 % (Cd), 2.82 % (Pb), 12.17 % (Zn), 14.89 % (As), 10.42 % (Cu), 32.20 %(Cr), and 8.88 % (Ni). The new framework could be useful for the ERA of various soil types.

Comparison and application of SOFM, fuzzy c-means and k-means clustering algorithms for natural soil environment regionalization in China

Soil attributes and their environmental drivers exhibit different patterns in different geographical directions, along with distinct regional characteristics, which may have important effects on substance migration and transformation such as organic matter and soil elements or the environmental impacts of pollutants. Therefore, regional soil characteristics should be considered in the process of regionalization for environmental management. However, no comprehensive evaluation or systematic classification of the natural soil environment has been established for China. Here, we established an index system for natural soil environmental regionalization (NSER) by combining literature data obtained based on bibliometrics with the analytic hierarchy process (AHP). Based on the index system, we collected spatial distribution data for 14 indexes at the national scale. In addition, three clustering algorithms-self-organizing feature mapping (SOFM), fuzzy c-means (FCM) and k-means (KM)-were used to classify and define the natural soil environment. We imported four cluster validity indexes (CVI) to evaluate different models: Davies-Bouldin index (DB), Silhouette index (Sil) and Calinski-Harabasz index (CH) for FCM and KM, clustering quality index (CQI) for SOFM. Analysis and comparison of the results showed that when the number of clusters was 13, the FCM clustering algorithm achieved the optimal clustering results (DB = 1.16, Sil = 0.78, CH = 6.77 × 10⁶), allowing the natural soil environment of China to be divided into 12 regions with distinct characteristics. Our study provides a set of comprehensive scientific research methods for regionalization research based on spatial data, it has important reference value for improving soil environmental management based on local conditions in China.