Accurate Prediction of Soil Heavy Metal Pollution Using an Improved Machine Learning Method: A Case Study in the Pearl River Delta, China.

In traditional soil heavy metal (HM) pollution assessment, spatial interpolation analysis is often carried out on the limited sampling points in the study area to get the overall status of heavy metal pollution. Unfortunately, in many machine learning spatial information enhancement algorithms, the additional spatial information introduced fails to reflect the hierarchical heterogeneity of the study area. Therefore, we designed hierarchical regionalization labels based on three interpolation techniques (inverse distance weight, ordinary kriging, and trend surface interpolation) as new spatial covariates for a machine learning (ML) model. It was demonstrated that regional spatial information improved the prediction performance of the model (R2 > 0.7). On the basis of the prediction results, the status of HM pollution in the Pearl River Delta (PRD) region was evaluated: cadmium (Cd) and copper (Cu) were the most serious pollutants in the PRD (the point overstandard rates are 18.77% and 12.95%, respectively). The analysis of index importance and bivariate local indicators of spatial association (LISA) shows that the key factors affecting the spatial distribution of heavy metals are geographical and climatic conditions [namely, altitude, humidity index, and normalized vegetation difference index (NDVI)] and some industrial activities (such as metal processing, printing and dyeing, and electronics industry). This study develops a novel approach to improve existing spatial interpolation techniques, which will enable more precise and scientific soil environmental management.

Digital mapping of soil organic carbon density in China using an ensemble model.

The soil organic carbon stock (SOCS) is considered as one of the largest carbon reservoirs in terrestrial ecosystems, and small changes in soil can cause significant changes in atmospheric CO2 concentration. Understanding organic carbon accumulation in soils is crucial if China is to meet its dual carbon target. In this study, the soil organic carbon density (SOCD) in China was digitally mapped using an ensemble machine learning (ML) model. First, based on SOCD data obtained at depths of 0-20 cm from 4356 sampling points (15 environmental covariates), we compared the performance of four ML models, namely random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and artificial neural network (ANN) models, in terms of coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values. Then, we ensembled four models using Voting Regressor and the principle of stacking. The results showed that ensemble model (EM) accuracy was high (RMSE = 1.29, R2 = 0.85, MAE = 0.81), so that it could be a good choice for future research. Finally, the EM was used to predict the spatial distribution of SOCD in China, which ranged from 0.63 to 13.79 kg C/m2 (average = 4.09 (±1.90) kg C/m2). The SOC storage amount in surface soil (0-20 cm) was 39.40 Pg C. This study developed a novel, ensemble ML model for SOC prediction, and improved our understanding of the spatial distribution of SOC in China.

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.

Human health risk-based Generic Assessment Criteria for agricultural soil in Jiangsu and Zhejiang provinces, China.

Agricultural soil pollution in China poses a major threat to human health and food safety. There are no agricultural soil environmental standards based on human health in China, which prevents effective screening and assessment of risks. Jiangsu (JS) and Zhejiang (ZJ) provinces, located in the Yangtze River Delta (YRD) core region, have obvious differences in agricultural land conditions, which will result in differences in Generic Assessment Criteria (GAC). In this study, we derived and compared human health risk-based GAC using the Contaminated Land Exposure Assessment (CLEA) model for agricultural land scenarios in these two provinces. We found differences in the GAC between JS and ZJ due to differences in parameters. These differences are greatest for benzene, and cadmium (Cd). For Cd, the contribution of oral intake exceeds 90 %, and the vegetable consumption rate and mean daily intake (MDI) may be key parameters affecting GAC. For the volatile organic compound benzene, the inhalation of indoor vapor accounts for about 30 %, and the key parameters affecting the GAC for benzene may be the attenuation factor and soil organic matte (SOM). The derived GAC are generally lager (i.e., less stringent) than the GB15618-2018 and UK Suitable 4 Use Levels (S4ULs); however, the derived GAC for JS and ZJ were lower than the soil screening values (SSV) for residential land in China. This may be related to methods, land use types, and critical receptors. This work will contribute to the development of regional soil environmental standards in China.

Human health risk-based soil environmental criteria (SEC) for park soil in Beijing, China.

Urban parks are important places that allow urban residents to experience nature but are also associated with the risk of exposure to contaminated soil. Therefore, it is necessary to establish appropriate soil environment criteria (SEC) to manage park soil quality. Studies on the demographic characteristics and behavioral patterns of urban park visitors are helpful for the selection of sensitive receptors and the determination of parameters in the establishment of SEC. This study explored the park visitors' demographic characteristics and behavioral patterns, and applied the results to derive SEC. Eighty-six parks in Beijing were selected, and mobile phone data were obtained to analysis the demographic characteristics and residence time of the visitors. Kruskal-Wallis test, kernel density estimation and random forest model were used for data analysis. The CLEA model was used to derive SEC. The results showed that the demographic characteristics and behavioral patterns of visitors in different types of parks were quite different. Parks were mostly used by males and visitors aged 31-45. Most visitors stayed in the park for 1-2 h, and the distance from a given visitor's home to the park was the most important factor affecting stay time. Then, several parameters such as the parameters related to the receptors and occupation period were optimized, and the SEC of sensitive parks and non-sensitive parks were derived. Exposure frequency may be the main reason for the difference of SEC between the two types of parks. The SECs of sensitive parks were higher than the soil screening values (SSVs) for class 1 land in GB36600-2018, indicating that the current SSVs for some parks may be too conservative. This study provides a reference for the formulation and revision of soil environmental standards for park land, and suggests strengthening research on human behavioral patterns.

Characters and environmental driving factors of bacterial community in soil of Beijing urban parks.

In an era of unprecedented human influence, different human activities have different degrees of impact on specific bacteria, resulting in the regional biological homogenization of soil bacteria. However, the contribution of the impact that a large number of anthropogenic activities on bacteria remains unknown. Here, by high-throughput amplicon sequencing, we characterized the composition, diversity and influencing factors of soil microbes in Beijing urban parks at geographic space and park management aspect. It is the first time to quantify and compare the importance of the impact of up to 15 human activities on soil bacterial communities. The results show that the dominant bacterial phyla in Beijing urban parks were Actinobacteria, Proteobacteria, Acidobacteria and Chloroflexi. The environmental management of different park types, as well as the land use history and development conditions of different regions, had significant differences in soil bacterial community structure. Soil bacteria in urban parks were disturbed by direct human interference far more than natural causes. The most important factors were related to the number of tourists and residents, industrial production and land use patterns. These factors may also be related to the abundance of unknown bacteria in urban parks. This also directly shows that human activities have a non-negligible impact on soil bacteria. The ways in which different human activities brought by global urbanization and their impacting mechanisms are used should be the starting point of future research.

Status of arsenic accumulation in agricultural soils across China (1985-2016).

Based on 1677 published studies, 1648 sites across China collected from 1985 to 2016 were used to research the concentrations of arsenic in agricultural soils. In order to understand the status of arsenic pollution in agricultural soils in China over the past three decades, and to learn about the arsenic stocks in agricultural soils in various regions, and compared the relationship with annual arsenic emissions in China, and finally evaluated the potential ecological risks and human health risks. The median arsenic concentration in the surface agricultural soils of China was 10.40 mg Kg-1, and it ranged from 0.4 mg Kg-1 to 175.8 mg Kg-1. The inventory of arsenic in Chinese agricultural surface soils was estimated to be 3.71 × 106 t. In this study, the arsenic concentrations were found to be higher in Central, South, and Southwest China than those in other regions. The trend of arsenic pollution in agricultural soils has gradually increased over the past three decades. However, the growth rate of arsenic concentrations pollution in farmlands agricultural in China slowed during 2012-2016. The ecological risk index and geoaccumulation index revealed that arsenic in Chinese agricultural soil poses a low risk to the ecosystem. For human health assessment, the dietary pathway was the main pathway of exposure to arsenic in farmland soil of China. However, children's soil intake also contributed 34.48% to the exposure to arsenic, owing to their behavior. This study can provide a reference for the management of arsenic agricultural pollution in farmland soils in China.

MicroRNA-155 promotes gastric cancer growth and invasion by negatively regulating transforming growth factor-ß receptor 2.

Gastric cancer (GC) is one of the most common malignancies worldwide and has high morbidity and mortality rates. It is essential to elucidate the molecular events of GC proliferation and invasion, which will provide new therapeutic targets for GC. The inactivation of transforming growth factor-ß receptor 2 (TGFßR2) correlates with cancer cell growth and metastasis, but the mechanisms underlying the downregulation of TGFßR2 expression remain unknown. MicroRNAs (miRNAs) act as post-transcriptional regulators and play a key role in the development of cancers. Bioinformatics analysis and luciferase reporter assays have shown that miR-155 directly binds to the 3'-UTR of TGFßR2 mRNA. In this study, we found that the TGFßR2 protein levels, but not mRNA levels, were downregulated in GC tissues, and the levels of miR-155 were significantly increased in GC tissues. We deduced that miR-155 was inversely correlated with TGFßR2 in GC cells. In vitro studies showed that overexpression of miR-155 in SGC7901 inhibited the expression of TGFßR2 and then promoted GC cell proliferation and migration, whereas miR-155 inhibitor showed opposite effects. In addition, the tumor-suppressing function of TGFßR2 was verified by using siRNA and TGFßR2 overexpressing plasmids. The results showed that miR-155 promotes cell growth and migration by negatively regulating TGFßR2. Thus, miR-155-regulated TGFßR2 as a potential therapeutic target in GC.

New insights into assembly processes and driving factors of urban soil microbial community under environmental stress in Beijing.

Rapid urbanization leads to drastic environmental changes, directly or indirectly affecting the structure and function of soil microbial communities. However, the ecological response of soil microbes to environmental stresses has not yet been fully explored. In this study, we used high-throughput sequencing to analyze the assembly mechanism and driving factors of soil microbial community under environmental stresses. The results indicated that environmental stresses significantly affected soil properties and the levels of beryllium, cobalt, antimony, and vanadium contamination in soil generally increased from the suburban areas toward the city core. The composition and distribution of soil microbial communities demonstrated clear differences under different levels of environmental stress, but there was no significant difference in microbial diversity. Random forest and partial least squares structural equation modeling results suggested that multiple factors influenced microbial diversity, but antimony was the key driver. The influence of environmental stress led to deterministic processes dominating microbial community assembly processes, which promoted the regional homogenization of soil microbes. Therefore, this study provides new insights into urban soil microbial management under environmental stresses.

Machine learning-based prediction of cadmium bioaccumulation capacity and associated analysis of driving factors in tobacco grown in Zunyi City, China.

Tobacco grown in areas with high-geochemical backgrounds exhibits considerably different cadmium (Cd) bioaccumulation abilities due to regional disparities and environmental changes. However, the impact of key factors on the Cd bioaccumulation ability of tobacco grown in the karst regions with high selenium (Se) geochemical backgrounds is unclear. Herein, 365 paired rhizospheric soil-grown tobacco samples and 321 topsoil samples were collected from typical karst tobacco-growing soil in southwestern China and analyzed for Cd and Se. XGBoost was used to predict and evaluate the Cd bioaccumulation ability of tobacco and potential influencing factors. Results showed that regional geochemical characteristics, such as soil Cd and Se contents, soil type, and lithology, have the highest influence on the Cd bioaccumulation ability of tobacco, accounting for 46.5% of the overall variation. Moreover, soil Se contents in high-geochemical background areas considerably affect Cd bioaccumulation in tobacco, with a threshold for the mutual suppression effects of Cd and Se at a soil Se content of 0.8 mg/kg. According to the results of bivariate local indicators of spatial association analysis, tobacco cultivated in the central, northeast, and southeast regions of Zunyi City carries a lower risk of soil Cd contamination. This study provides new insights for managing tobacco cultivation in karst regions.

Source, environmental behavior and potential health risk of rare earth elements in Beijing urban park soils.

Rare earth elements (REEs) have been increasingly diffused to the environment due to their extensive use and application in industries, agriculture, and high-tech devices, which have been regarded as emerge pollutants. However, the study concerning REEs in urban soils is still limited. Therefore, the objectives of this study were to investigate the potential source and risk of REEs in urban environment. We analyzed the concentration and distribution of REEs in urban park soils, and performed a combination of micro geochemical method and random forest method to characterize the pollution sources of REEs. The results showed that the ΣREE concentrations in Beijing urban park soils ranged from 117.19 to 198.09 mg/kg. Spatial distribution indicated that the high concentrations of REEs were mainly concentrated in the west of Beijing near an industrial area. The geochemical parameters, micro spherules and random forest results confirmed the anthropogenic pollution sources from industry and traffic. Risk assessment showed that the average daily doses of total REEs for children and adults were far below the reference threshold with values of 0.08 and 0.02 µg/kg/day, respectively. Our study has exhibited that though the reconstruction of parks from abandoned industrial sites showed an accumulation of REEs, the health risk of REEs for human beings are negligible.

[Prediction of PAHs Content in Soil Around Gas Stations in Beijing Based on BP Neural Network].

With the rapid development of urbanization in China, the number of gas stations in cities is increasing. The composition of oil products in gas stations is complex and diverse, and a series of pollutants will be generated in the process of oil diffusion. Polycyclic aromatic hydrocarbons (PAHs) produced by gas stations can pollute the nearby soil and affect human health. In this study, soil samples (0-20 cm) near 117 gas stations in Beijing were collected, and the contents of seven PAHs were analyzed. Based on the BP neural network model, the contents of PAHs in soil of Beijing gas stations in 2025 and 2030 were predicted. The results showed that the total concentrations of the seven PAHs were 0.01-3.53 mg·kg-1. The concentrations of PAHs were lower than the soil environmental quality risk control standard for soil contamination of development land (Trial) GB 36600-2018. At the same time, the toxic equivalent concentrations (TEQ) of the above seven PAHs were lower than the standard value (1 mg·kg-1) of the World Health Organization (WHO), which they indicate a lower risk to human health. The prediction results showed that the rapid development of urbanization had a positive correlation with the increase in soil PAHs content. By 2030, the content of PAHs in Beijing gas station soil will continue to grow. The predicted concentrations of PAHs in the soil of Beijing gas stations in 2025 and 2030 were 0.085-4.077 mg·kg-1and 0.132-4.412 mg·kg-1, respectively. The contents of seven PAHs were lower than the soil pollution risk screening value of GB 36600-2018; however, the concentration of PAHs increased over time.The contents of PAHs in Chaoyang, Fengtai, and Haidian were relatively higher, which requires further attention.

Spatial clustering and source-specific risk of combined pollutants in soils from an industrial area in Shanxi Province, China.

Heavy metal (loid)s (HMs) and polycyclic aromatic hydrocarbons (PAHs) in soils from a typical industrial county of Shanxi were synchronously measured to determine the spatial clustering of combined HMs and PAHs pollution, and the resulting source-specific health risks. The spatial interaction of HMs and PAHs was determined by the Moran's I index, and a bivariate local indicators of spatial association (LISA) analysis showed that the high HMs-high PAHs clusters were mainly distributed in Fencheng and Xijia towns, as well as the main urban areas of Xiangfen County. The spatial clusters of high naphthalene (Nap)-high HMs were more obvious than those of high benzo(a)pyrene (Bap)-high HMs. Based on positive matrix factorization (PMF), four sources were identified for both HMs and PAHs, with coal consumption and industrial emission identified as common sources of both pollutants. The source-oriented health risk was determined using an improved health risk assessment model. The cancer risk from the combined pollution industrial emissions was relatively serious for both adults and children, with the risk value exceeding 10-6. Therefore, special attention should be paid to emission control. Based on spatial clustering and source-specific health risk assessment, the largest risk areas and pollutant sources were in the main urban areas of Fencheng and Xijia towns. The spatial interaction patterns and source-specific HMs and PAHs pollution concentrations provide a basis for effective pollution management and control. Finally, a systematic framework for reference was proposed for risk area identification and analysis of the source-oriented health risks of combined HMs and PAHs pollution.

Antimony, beryllium, cobalt, and vanadium in urban park soils in Beijing: Machine learning-based source identification and health risk-based soil environmental criteria.

The pollution situation of antimony (Sb), beryllium (Be), cobalt (Co), and vanadium (V) is poorly understood, although they are widely used in daily life and production processes. Moreover, threshold levels ("soil environmental criteria", SEC) for these pollutants are lacking in China, which impedes effective soil quality management. This study explored pollution characteristics for park soils in urban area of Beijing, China at first. Then multivariate statistical analysis and machine learning model were used to identify the main sources of pollutants. Additionally, probabilistic health risk and SEC were studied to assess the risks of pollutants and manage soil pollutants. The results revealed that the overall pollution levels of Be, Co, Sb, and V were low, but Be and Sb were enriched to varying degrees. Source apportionment showed that Sb (85.5%) was mainly derived from fuel combustion and industrial legacy, Co (66.7%) and V (82.5%) from natural processes, and Be from the natural background (39.3%) and anthropogenic sources (53.8%). Risk assessment indicated that the pollutants' carcinogenic and noncarcinogenic risks were negligible. Exposure frequency and soil ingestion rate were the most important parameters affecting health risks. The SEC of Be, Co, Sb, and V were 31, 39.7, 41.3, and 348 mg/kg, respectively, all of which are higher than the corresponding soil quality standards in China, indicating that current soil quality standards may be too conservative for urban park land. This study provides a reference for the management of soil pollutants in Beijing's urban parks, and the formulation of soil environmental quality standards.

A novel method to analyze the spatial distribution and potential sources of pollutant combinations in the soil of Beijing urban parks.

Organic and inorganic pollutants are often co-sedimentary in soils and have the same sources in the urban environment. The identification of the sources and distribution of combined pollutants is a basic step in risk management. In this study, the levels of polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) were measured in urban park soils in Beijing. Bivariate local Moran's I and positive matrix factorization (PMF) source apportionment were used to identify the spatial clustering patterns and potential sources of PAHs and HMs, as well as to ultimately define a pollution risk control area. The results revealed an obvious clustered distribution of PAHs and HMs in the park soils. High-high areas were defined as sites containing a complex mixture of pollutants, which were mainly located in the center and north of Beijing. High-low and low-high areas were located outside the city center but had the potential for combined pollution, and therefore require continuous attention. Bivariate local indicators of spatial association (LISA) enabled a more accurate analyses of the mechanism controlling the spatial distribution of PAH and HM combinations in urban parks. The source apportionment indicated that industrial and traffic emissions were the most important sources of the pollutant combinations in urban parks, with traffic emissions accounting for most of the pollution.

Microplastics pollution in the soil mulched by dust-proof nets: A case study in Beijing, China.

As a driving factor of global changes, microplastics have gradually attracted widespread attention. Although MPs are extensively studied in aquatic systems, their presence and fate in terrestrial systems and soil are not fully understood. In China, construction-land must be mulched by dust-proof nets to prevent and control fine particulate pollution, which may cause MPs pollution and increase ecological risks. In order to understand the pollution characteristics and sources of MP in the soil covered by dust nets, we conducted a case study in Beijing. Our results revealed that the abundance of MPs in soil mulched by dust-proof nets ranged from 272 to 13,752 items/kg. Large-sized particles (>1000 µm) made up a significant proportion (49.83%) of MPs in the study area. The dominant MP polymer types were polyethylene (50.12%) and polypropylene (41.25%). The accumulation of MPs in construction-site soil mulched by dust-proof nets (average, 4910.2 items/kg) was significantly higher (P < 0.05) than that in unmulched soil (average, 840.8 items/kg), which indicates a dust-proof nets as an essential source of microplastics in the soil of construction land. We applied a remote-sensing data analysis technique based on remote imagery acquired from a high-resolution remote-sensing satellite combined with deep-learning convolutional neural networks to automatically detect and segment dust-proof nets. Based on high-resolution remote sensing images and using a U-net convolutional neural network, we extract the coverage area of Beijing's dust-proof nets (18.6 km2). Combined the abundance of MPs and the dust-proof nets' coverage area, we roughly estimate that 7.616 × 109 to 3.581 × 1011 MPs accumulated in the soil mulched by the dust-proof nets in Beijing. Such a large amount of MPs may cause a series of environmental problems. This study will highlight the understanding of soil MPs pollution and its potential environmental impacts for scientists and policymakers. It provides suggestions for decision-makers to formulate effective legislation and policies, so as to protect human health and protect the soil and the wider environment.

Comparison of the concentrations, sources, and distributions of heavy metal(loid)s in agricultural soils of two provinces in the Yangtze River Delta, China.

Jiangsu and Zhejiang provinces, located in the Yangtze River Delta (YRD) core region, are the most economically developed regions in China, as well as the areas with serious soil pollution. The concentrations, sources, and distributions of heavy metal(loid)s in agricultural soils of the two provinces were studied; positive matrix factorization model (PMF) analysis and kriging interpolation were combined to compare the pollution characteristics of heavy metal(loid)s. The results showed that the degree of accumulation might be more serious in Zhejiang province than in Jiangsu province, especially in terms of Cd, Hg, and Pb. PMF results showed anthropogenic activities were the dominant factors affecting the concentrations of soil heavy metal(loid)s. The contributions of the three sources in Jiangsu province were 40.28% natural and traffic sources, 37.49% agricultural sources, and 22.22% industrial and coal combustion sources. The contributions of the three sources in Zhejiang province were 43.45% agricultural and industrial sources, 32.15% natural sources, and 24.40% industrial sources. The kriging interpolation results of the two provinces showed that the concentrations of As, Cr, and Ni were significantly higher in Jiangsu province than in Zhejiang province; the concentrations of Cu were similar in the two provinces, while other heavy metals had higher concentrations in Zhejiang province. These accumulations of heavy metal(loid)s in agricultural soil in both provinces cannot be ignored. This work will contribute to the development of effective policies aimed at protecting the soil environment from long-term accumulation of heavy metal(loid)s.

Soil-air exchange of mercury from agricultural fields in Zhejiang, East China: Seasonal variations, influence factors, and models of fluxes.

Mercury exchange between soil and air is an important processe governing the biogeochemical cycling of Hg. This study investigated the in situ soil-air Hg fluxes in agricultural soils of Quzhou, Zhejiang Province, China, using a dynamic flux chamber coupled with a Hg vapor analyzer. Soil-air Hg exchange fluxes were overall emission for all seasons, indicating that agricultural soil was a Hg source for the atmosphere. Seasonal variations in soil-air Hg flux were observed, with low values in winter, elevated values in spring, peak values in summer, and a decline in autumn. Mercury emissions from soils showed a clear diurnal pattern where Hg released into the atmosphere reached a maximum at 11 a.m. and declined to a minimum at 2:00 and 20:00 in spring and summer, respectively. Meanwhile, soil-air Hg flux peaked at 1 p.m. and declined to a minimum at 6:00 and 23:00 in autumn and winter, respectively. The impact of each factor on the Hg exchange between soil and air varied in different seasons. Soil temperature was the major variable controlling the Hg flux in winter and spring; soil temperature and total gaseous Hg evidently affected the Hg flux in summer, and ozone (O3) played a dominant role in influencing the Hg flux in autumn. Models for estimating the Hg evasive flux from soils were developed, and the atmospheric O3 concentration was used for the first time as a parameter in these models. The measured and modeled Hg fluxes showed significant linear correlations (R2 = 0.61; P < 0.001).

Potential sources, influencing factors, and health risks of polycyclic aromatic hydrocarbons (PAHs) in the surface soil of urban parks in Beijing, China.

Urban parks are an important part of the urban ecological environment. The environmental quality of parks is related to human health. To evaluate sources of polycyclic aromatic hydrocarbons (PAHs) in soils of urban parks and their possible health risks, soil samples from 122 parks in Beijing, China, were collected and analyzed. The total content of 16 PAHs between 0.066 and 6.867 mg/kg. Four-ring PAHs were predominant, followed by 5-ring PAHs, while the fraction of 2-ring PAHs was the lowest. The dominant PAHs sources were found to be coal combustion and oil fuels such as gasoline and diesel. A conditional inference tree (CIT) was used to identify the key influencing factors for PAHs. Traffic emissions was the most important factor, followed by coal consumption, as well as the history and location of the park. Incremental lifetime cancer risk (ILCR) for urban park soil in Beijing were low under normal conditions. The soil PAHs exposure pathway risk for both children and adults decreased in the following order: ingestion > dermal contact > inhalation. The risk from soil in parks to children's health is slightly higher than that of adults, although the health risk due to exposure to PAHs was not extraordinary. Ecosystem risk was negligible.

Heavy metal(loid)s in the topsoil of urban parks in Beijing, China: Concentrations, potential sources, and risk assessment.

Urban parks play an important role in the urban ecosystem and are also used by residents for recreation. The environmental quality of urban park soils might influence human health following long-term exposure. To assess potential sources and pollution risks of heavy metal(loid)s in the topsoil of urban parks, we subjected metal concentrations in soil samples from 121 parks in the Beijing urban area to geostatistical analyses, conditional inference tree (CIT) analyses, ecological risk and human health risk assessment. CIT effectively explained the influence of human activity on the spatial variation and accumulation of soil metal(loid)s and identified the contributions of natural and anthropogenic inputs. The main factors influencing the accumulation of heavy metal(loid)s, including urbanization duration, park age, per capita GDP, industrial output, and coal consumption, were evaluated by CIT. Except for Cr and Ni, the average concentrations of the metal(loid)s tested (Cu, Pb, Zn, Hg, As, and Cd) were higher than the background values. In the urban parks, Ni and Cr derived mostly from soil parent materials. Concentrations of Cu, Zn, Pb, Cd, As, and Hg were strongly associated with human influences, including industrial, agricultural, and traffic activity. After assessing health and ecological risks, we conclude that heavy metal(loid)s in the soil of Beijing urban parks pose no obvious health risk to humans, and the ecological risk is also low.