Spatial distribution of heavy metal concentrations in peri-urban soils in eastern China

Receptor modeling, ecological risks, and human health impacts of mercury in some Ghanaian topsoils due to mining and commercial activities

Globally, elevated environmental mercury levels have been linked to artisanal and small-scale gold mining; however, investigations into mining communities often overlook other potential sources and their contributions to soil mercury accumulation. This study explored the positive matrix factorization (PMF) receptor model to identify other possible sources of mercury contamination in two major mining communities (Kenyasi and Obuasi) and a commercial city (Sunyani) in Ghana. The mercury concentrations across the three study areas showed no significant differences (p = 0.257 at the 95% confidence level). The PMF model identified mining as the major contributor to mercury accumulation in Obuasi and Kenyasi, with other activities, such as farming, also contributing substantially. The generation and burning of hazardous waste in the Sunyani municipality due to increased commercial activities have contributed significantly to mercury contamination. Although the hazard quotient indicated no adverse health effects in the study areas (hazard quotient < 1), the pollution and ecological risk indices showed that Obuasi was significantly enriched with mercury, with considerable levels found in Kenyasi and Sunyani. The results from this study will serve as a good database for environmental studies on mercury particularly in Kenyasi and Sunyani, where there has not been any extensive research on mercury contamination.

Pollution characteristics and source apportionment of heavy metal(loid)s in soil and groundwater of a retired industrial park

Heavy metal(loid)s (HMs) pollution has become a common and complex problem in industrial parks due to rapid industrialization and urbanization. Here, soil and groundwater were sampled from a retired industrial park to investigate the pollution characteristics of HMs. Results show that Ni, Pb, Cr, Zn, Cd, and Cu were the typical HMs in the soil. Source analysis with the positive matrix factorization model indicates that HMs in the topsoil stemmed from industrial activities, traffic emission, and natural source, and the groundwater HMs originated from industrial activities, groundwater-soil interaction, groundwater-rock interaction, and atmosphere deposition. The sequential extraction of soil HMs reveals that As and Hg were mainly distributed in the residue fraction, while Ni, Pb, Cr, Zn, Cd, and Cu mainly existed in the mobile fraction. Most HMs either in the total concentration or in the bioavailable fraction preferred to retain in soil as indicated by their high soil-water partitioning coefficients (Kd), and the Kd values were correlated with soil pH, groundwater redox potential, and dissolved oxygen. The relative stable soil-groundwater circumstance and the low active fraction contents limited the vertical migration of soil HMs and their release to groundwater. These findings increase our knowledge about HMs pollution characteristics of traditional industrial parks and provide a protocol for HMs pollution scrutinizing in large zones.

Spatial-temporal variation and source analysis of heavy metals in different land use types in Beilun District (2015 and 2022)

The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The results shown that the heavy metal contents in 2015 and 2022 were higher than the background soil values of Ningbo city, and there was an accumulation of heavy metals over these 7 years. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal distribution of heavy metal content showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. But the single-factor pollution index, pollution load index (PLI), and geoaccumulation index (Igeo) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. These results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment.

Determining the net input fluxes of pollutants based on the spatial source apportionment receptor model for early warning of regional soil pollution

Understanding the soil pollutants' net input fluxes is essential for accurate early warning of regional soil pollution. However, the traditional input-output investigation method for soil pollutants' net input fluxes is often costly, especially at the regional scale. This study first assessed the land-use effects on soil heavy metals around a typical copper smelting area in China. Next, an improved spatial source apportionment receptor model, namely robust absolute principal component scores/robust geographically weighted regression with category land-use information (RAPCS/RGWR-CLU), was proposed to apportion the net source contributions, and its performance was compared with those of RAPCS/RGWR and the traditional absolute principal component scores/multiple linear regression (APCS/MLR). Finally, the net input fluxes of soil heavy metals were determined based on RAPCS/RGWR-CLU, and its performance was compared with that of the traditional input-output investigation method. Results showed that (i) land-use effects are significant for soil As, Cu, Pb, and Zn; (ii) RAPCS/RGWR-CLU achieves higher source apportionment accuracy than RAPCS/RGWR and APCS/MLR; and (iii) the net input fluxes determined by RAPCS/RGWR-CLU have similar accuracy to those determined by the traditional input-output investigation method but with significantly lower costs. Therefore, this study provided a cost-effective solution to determine the net input fluxes of soil pollutants.

Ecological risk and spatial distribution, sources of heavy metals in typical purple soils, southwest China

The identification and quantification of the ecological risks, sources and distribution of heavy metals in purple soils are essential for regional pollution control and management. In this study, geo-accumulation index (Igeo), enrichment factor (EF), pollution index (PI), potential ecological risk index (RI), principal component analysis (PCA) model and geographical detector (GD) were combined to evaluate the status, ecological risk, and sources of heavy metals (HMs) in soils from a typical purple soil areas of Sichuan province. The results showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in purple soil were 7.77, 0.19, 69.5, 27.9, 0.077, 30.9, 26.5 mg/kg and 76.8 mg/kg, and the Igeo, EF and RI of topsoil Hg and Cd in designated area was the highest, and the average contents of Hg and Cd in topsoil were obviously greater than respective soil background value in Sichuan province and purple soil. The hot spots for the spatial distribution of 8 HMs were mainly focused in the southwest and northeast of the designated area, and there were also significant differences for 8 HMs distribution characteristics in the profile soil. Cu comes from both anthropogenic and natural sources, Zn, Ni and Cr mainly come from natural sources, but As, Pb, Hg and Cd mainly derived from human activities. GD results showed that soil texture (X18), altitude (X4), total nitrogen (TN), clay content (X3), sand content (X2) and silt content (X1) had the greatest explanatory power to 8 HMs spatial differentiation.This study provides a reference for understanding the status and influencing factors of HM pollution in typical purple soil, and lays a theoretical foundation for the environmental treatment of purple soil in China.

Effect of environmental factors on accumulation of trace metals in a typical shale gas exploitation area: A comprehensive investigation by machine learning and geodetector models

Whether a certain relationship is exist between shale gas exploitation and accumulation of trace metals in soil is a controversial issue in recent years. To date, few study clearly reveal the intrinsic contributions of natural and anthropogenic factors to accumulation of trace metals in soil. In this study, machine learning and geodetector models were integrated to investigate to contribution of environmental factors to variations of trace metals concentration. Before modeling, there are 10.33%-25.87% of soil considered as metal pollution, and the value of Pn further suggest that the Ba contribute the most to the comprehensive pollution index of trace metals in soil. The initial prediction of trace metals concentration by machine learning models is less effectively indicating the need for alternative approaches. To address this problem, post-constraints approach was used, and the post-constraint MSLR model demonstrates superior performance (R2 = 0.81) Additionally, through the utilization of geodetector model, the explanatory power (q) of CEC and SOM were identified as dominant natural factors with value of 0.055 and 0.089. respectively. Moreover, distance from working sites and working status were identified as the dominant anthropogenic factors associating to the spatial heterogeneity of trace metals in soil. The interaction between natural and anthropogenic factors showed a siginifacnt nonlinear enhancement effect on accumulation of Cr, Ba and Sr, and the highest value of q was 0.38 for SOM and distance. This study indicated that the potential metal contamination was related to shale gas exploitation and provide reference for controlling soil pollution in shale gas exploitation area and making management strategy.

Uncertainty Evaluation of Soil Heavy Metal(loid) Pollution and Health Risk in Hunan Province: A Geographic Detector with Monte Carlo Simulation

Research on soil heavy metal(loid) pollution and health risk assessment is extensive, but a notable gap exists in systematically examining uncertainty in this process. We employ the Nemerow index, the health risk assessment model, and the geographic detector model (GDM) to analyze soil heavy metal(loid) pollution, assess health risks, and identify driving factors in Hunan Province, China. Furthermore, the Monte Carlo simulation (MCS) method is utilized to quantitatively evaluate the uncertainties associated with the sampling point positions, model parameters, and classification boundaries of the driving factors in these processes. The experimental findings reveal the following key insights: (1) Regions with high levels of heavy metal(loid) pollution, accompanied by low uncertainty, are identified in Chenzhou and Hengyang Cities in Hunan Province. (2) Arsenic (As) and chromium (Cr) are identified as the primary contributors to health risks. (3) The GDM results highlight strong nonlinear enhanced interactions among lithology and other factors. (4) The input GDM factors, such as temperature, river distance, and gross domestic product (GDP), show high uncertainty on the influencing degree of soil heavy metal(loid) pollution. This study thoroughly assesses high heavy metal(loid) pollution in Hunan Province, China, emphasizing uncertainty and offering a scientific foundation for land management and pollution remediation.

Levels of heavy metal in soil and vegetable and associated health risk in peri-urban areas across China

Peri-urban vegetable field plays an essential role in providing vegetables for local residents. Because of its particularity, it is affected by both industrial and agricultural activities which have led to the accumulations of heavy metal in soil. So far, information on heavy metal pollution status, spatial features, and human health risks in peri-urban vegetable areas across China is still scarce. To fill this gap, we systematically compiled soil and vegetable data collected from 123 articles published between 2010 and 2022 at a national level. The pollution status of heavy metals (i.e., cadmium (Cd), mercury (Hg), arsenic (As), lead (Pb), chromium (Cr), copper (Cu), nickel (Ni), and zinc (Zn)) in peri-urban vegetable soils and vegetables were investigated. To evaluate the levels of heavy metal pollution in soil and human health risks, the geoaccumulation index (Igeo) and target hazard quotient (HQ) were calculated. The results showed that mean concentrations of Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn in peri-urban vegetable soils were 0.50, 0.53, 12.03, 41.97, 55.56, 37.69, 28.55, and 75.38 mg kg^-1, respectively. The main pollutants in peri-urban vegetable soil were Cd and Hg, and 85.25% and 92.86% of the soil samples had I_geo > 1, respectively. The mean I_geo values of this regions followed the order of northwest > central > south > north > east > southwest > northeast for Cd and northeast > northwest > north > southwest > east > central > south for Hg. The mean Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn concentrations in vegetables were 0.30, 0.26, 0.37, 0.54, 1.17, 6.17, 1.96, and 18.56 mg kg^-1, respectively. Approximately 87.01% (Cd), 71.43% (Hg), 20% (As), 65.15% (Pb), 27.08% (Cr) of the vegetable samples exceeded the safety requirement values. The vegetables grown in central, northwest, and northern China accumulated much more heavy metals than those grown in other regions. As the HQ values for adults, 53.25% (Cd), 71.43% (Hg), 84.00% (As), and 58.33% (Cr) of the sampled vegetables were higher than 1. For children, the HQ values were higher than 1 for 66.23% (Cd), 73.81% (Hg), 86.00% (As), and 87.50% (Cr) of the sampled vegetables. The findings of this study demonstrate that the situation of heavy metal pollution in peri-urban vegetable areas across China are not optimistic and residents who consume the vegetables are at high risk of health issues. To ensure soil quality and human health, strategies should be taken to guide vegetable production and remedy soil pollution in peri-urban areas with the rapidly urbanizing China.

Leaching characteristics and potential risk of heavy metals from drip irrigation pipes and mulch substrate in agricultural ecosystems

Drip irrigation is a valuable method for optimising water and fertiliser usage, motivating its increasing use. However, the ecological effects of drip irrigation fertilisation have not been sufficiently evaluated, limiting its effective and widespread use. Within this context, we aimed to determine the effects and potential ecological risks of using polyethylene irrigation pipes and mulch substrate under various drip irrigation conditions as well as burning of waste pipes and mulch substrate. Laboratory simulations of field conditions were used to determine the distribution, leaching, and migration pattern of heavy metals (Cd, Cr, Cu, Pb, and Zn) from plastic drip irrigation pipes and agricultural mulch substrate into various solutions. Maize samples obtained from drip-irrigated fields were analysed to determine the presence of heavy metal residues and assess the risk of heavy metal contamination. Heavy metal leaching from pipes and mulch substrate was high under acidic conditions, while the migration of heavy metals from plastic products was low in alkaline water-soluble fertiliser solutions. After combustion, heavy metal leaching from pipes and mulch residues increased considerably, with the migration capacity of Cd, Cr, and Cu increasing by >10-fold. Heavy metals in plastic pipes migrated primarily to the residue (bottom ash), whereas those from mulch substrate migrated to the fly ash component. Under experimental conditions, the migration of heavy metals from plastic pipes and mulch substrate had a negligible effect on the heavy metal content in aqueous environments. Although heavy metal leaching increased, the effect on water quality under actual irrigation conditions was relatively minor (in the order of 10^-9). Thus, the use of plastic irrigation pipes and mulch substrate did not result in significant heavy metal contamination and potential risk to the agriculture ecosystem. Our study findings provide evidence for the effective application and widespread promotion of drip irrigation and fertiliser technology.

Spatiotemporal patterns of soil heavy metal pollution risk and driving forces of increment in a typical industrialized region in central China

Excessive enrichment of soil heavy metals seriously damages human health and soil environment. Exploring the spatiotemporal patterns and detecting the influencing factors are conducive to developing targeted risk management and control. Based on the soil samples of Co, Cr, Cu, Mn, Ni, Pb, Zn, and Cd collected in one typical industrialized region in China from 2016 to 2019, this study analyzed the spatiotemporal pattern of geo-accumulation risk and potential ecological risk based on the spatiotemporal ordinary kriging (STOK) prediction, and probed the driving forces of heavy metal increments with the random forest (RF) regression model. The risk assessment revealed that soils were seriously contaminated by Pb, Cd, and Cu, moderately contaminated by Zn and Mn, and uncontaminated by Co, Cr, and Ni; more than 30% of areas had moderate to high potential ecological risks. From 2016 to 2019, soil heavy metal contents increased in more than 50% of regions and the growth rates of accumulations were ranked as Co (65%) > Ni (56%) > Mn (43%) > Pb (40%) > Cr (36%) > Zn (31%) > Cu (23%) > Cd (3%). High contents and increases of heavy metals in soils near industrial lands are higher. Smelter (24%), mine (20%), and factory (12%) were the major contributing factors for these heavy metal increments, followed by transportation (6%) and population (5%). The results indicated that the management of industrial discharge and contaminated soils should be strengthened to prevent the worsening soil heavy metal pollution in the study area.

Identifying Spatiotemporal Heterogeneity of PM2.5 Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River

Fine particulate matter (PM2.5) is a harmful air pollutant that seriously affects public health and sustainable urban development. Previous studies analyzed the spatial pattern and driving factors of PM2.5 concentrations in different regions. However, the spatiotemporal heterogeneity of various influencing factors on PM2.5 was ignored. This study applies the geographically and temporally weighted regression (GTWR) model and geographic information system (GIS) analysis methods to investigate the spatiotemporal heterogeneity of PM2.5 concentrations and the influencing factors in the middle and lower reaches of the Yellow River from 2000 to 2017. The findings indicate that: (1) the annual average of PM2.5 concentrations in the middle and lower reaches of the Yellow River show an overall trend of first rising and then decreasing from 2000 to 2017. In addition, there are significant differences in inter-province PM2.5 pollution in the study area, the PM2.5 concentrations of Tianjin City, Shandong Province, and Henan Province were far higher than the overall mean value of the study area. (2) PM2.5 concentrations in western cities showed a declining trend, while it had a gradually rising trend in the middle and eastern cities of the study area. Meanwhile, the PM2.5 pollution showed the characteristics of path dependence and region locking. (3) the PM2.5 concentrations had significant spatial agglomeration characteristics from 2000 to 2017. The “High-High (H-H)” clusters were mainly concentrated in the southern Hebei Province and the northern Henan Province, and the “Low-Low (L-L)” clusters were concentrated in northwest marginal cities in the study area. (4) The influencing factors of PM2.5 have significant spatiotemporal non-stationary characteristics, and there are obvious differences in the direction and intensity of socio-economic and natural factors. Overall, the variable of temperature is one of the most important natural conditions to play a positive impact on PM2.5, while elevation makes a strong negative impact on PM2.5. Car ownership and population density are the main socio-economic influencing factors which make a positive effect on PM2.5, while the variable of foreign direct investment (FDI) plays a strong negative effect on PM2.5. The results of this study are useful for understanding the spatiotemporal distribution characteristics of PM2.5 concentrations and formulating policies to alleviate haze pollution by policymakers in the Yellow River Basin.

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.

Abundance and fractional solubility of phosphorus and trace metals in combustion ash and desert dust: Implications for bioavailability and reactivity

Aerosol phosphorus (P) and trace metals derived from natural processes and anthropogenic emissions have considerable impacts on ocean ecosystems, human health, and atmospheric processes. However, the abundance and fractional solubility of P and trace metals in combustion ash and desert dust, which are two of the largest emission sources of aerosols, are still not well understood. In this study, the abundance and fractional solubility of P and trace metals in seven coal fly ash samples, two municipal waste fly ash samples, and three desert dust samples were experimentally examined. It was found that the abundance of aluminum (Al) in combustion ash was comparable or even higher than that in desert dust, and, therefore, care should be taken when using Al as a tracer of desert dust. The abundance and fractional solubility of P were higher in combustion ash, with a soluble P content ~4-6 times higher than that of the desert dust, indicating that combustion ash could be an important source of bioavailable P in the atmosphere. Except for Mn, the abundance and fractional solubility of other heavy metals were higher in the combustion ash compared to the desert dust, indicating the potential importance of combustion ash in ocean ecosystems, human health, and atmospheric processes. In contrast, both the abundance and solubility of Mn were highest in the desert dust, indicating a potentially important source of soluble Mn in the atmosphere. The fractional solubilities of P and trace metals are significantly affected by acidity and ions in the extraction solutions, and it is suggested that a buffer solution can better represent the acidity of the aqueous system in the true atmospheric environment. The results of this study improve our understanding of the sources of bioavailable and reactive P and trace metals in ambient aerosols.

Distribution Characteristics and Risk Assessment of Heavy Metals in Soil and Street Dust with Different Land Uses, a Case in Changsha, China

Rapid urbanization and industrialization have led to the accumulation of heavy metals in urban areas. The distribution and health risk of heavy metals in soil and street dust were studied by collecting the samples in pairs from different land uses in Changsha, China. The results showed that the average contents of the heavy metals Pb, Cd, Cu, Zn, Cr and Ni in the soil were 45.3, 0.69, 46.3, 220.4, 128.7 and 32.9 mg·kg-1, and the corresponding heavy metal contents in the street dust were 130.1, 3.9, 130.8, 667.2, 223.2, 50.5 mg·kg-1, respectively. The soils in the parks and roadsides have higher heavy metal contents than those in the residential and agricultural areas. The street dust collected from parks, roadsides and residential areas contained higher heavy metal contents than agricultural areas. Significant correlations were found between heavy metals, suggesting similar sources. However, most of the heavy metals in the soil were uncorrelated with those in the street dust. The contents of heavy metals in soil are the results of long-term pollution. Street dust is easily affected by natural or human disturbances, reflecting pollution emissions in a short period. The health risks posed by heavy metals in the soil are acceptable, but the street dust may threaten children's health, especially in residential areas. Pb, Cr and Cd are the main risk contributors. Reducing the emissions from industrial plants and traffic may reduce the risk of exposure to heavy metals in the street dust.

Interactive effects of natural and anthropogenic factors on heterogenetic accumulations of heavy metals in surface soils through geodetector analysis

The rapid socioeconomic development has led to severe pollution of urban soils by heavy metals. It is vital to identify and quantify the factors that affect trace-element pollution for better preventing and managing soil pollution. In this study, we collected 179 surface soil samples from Zhangzhou City in a coastal area of south China to determine the concentration of seven heavy metals (As, Cr, Cu, Hg, Ni, Pb, and Zn) and used the Nemerow Pollution Index (P_n) to estimate the level of heavy metal pollution in soils. Eighteen environmental factors, including six natural factors (e.g. soil properties, surface topography) and twelve anthropogenic factors (e.g. industry, road network, land use types and landscape pattern), were evaluated with the geodetector statistical method. The results indicate that the heavy metal contamination of soils in Zhangzhou City was highly heterogeneous. We found that the primary influencing factors for heavy metal concentrations were soil organic matter content, agriculture activities, and landscape pattern. Furthermore, the nonlinear relationship between the primary factors and their interaction factors enhanced soil contamination by the heavy metals. Among the anthropogenic factors, landscape pattern enhanced P_n the most when interacting with natural factor. In addition, the buffer zone should be considered when evaluating the effects of factors such as land use and landscape pattern, because the interactions between landscape pattern and slope aspect produce a maximum effect, accounting for 31.0% of the P_n value on the scale of 800 m. Based on this analysis, we identified the key factors of heavy metal pollution in the soils of Zhangzhou City and proposed strategic procedures for effective soil pollution prevention and treatment in the future.

Geochemical fractionation and spectroscopic fingerprinting for evaluation of the environmental transformation of potentially toxic metal(oid)s in surface-subsurface soils

The contamination of soil by toxic metal(oid)s has emerged as a major concern worldwide, particularly in developing countries. A metals behavior in the soil environment is influenced by organic matter, mineral phases, and oxidation states in which a particular metal exists. However, the spectroscopic evidence of metal(oid)s interactions in soil with organic matter and mineral phases can induce an extensive understanding. The surface and sub-surface soils (0-50 cm) from four sites of upper Indus basin, Pakistan, were collected and analyzed by using FTIR (Fourier-transform infrared spectroscopy), XRD (X-ray diffraction) and XPS (X-ray photoelectron spectroscopy) in addition to ICP-MS (inductively coupled plasma mass spectrometry) and geochemical fractionation. Geochemical fractionation of metal(oid)s indicated that As, Cu, Ni, Pb, and Zn were mostly found in the potentially bioavailable fractions. However, an increase in the residual fraction was observed from top to bottom. The absorption bands of FTIR spectra were divided into three spectral regions 700-400, 1700-800, and 3700-2800 cm^-1. The soil was found rich in organic matter and capable of retaining metals as abundant peaks were observed in the mid-infrared region. The mineralogical analysis of soil samples testified silicon oxides and zeolite as major mineral phases. The XPS spectra showed broad peaks of As(III), As₂O₃, As₄S₄, PbO₂, and PbCo₃. The study concludes that the source identification of metal(oid)s in the upper Indus is crucial to find out the particular source of contamination in the soil.

Effects of native forest and human-modified land covers on the accumulation of toxic metals and metalloids in the tropical bee Tetragonisca angustula

The intensive shift on land cover by anthropogenic activities have led to changes in natural habitats and environmental contamination, which can ultimately impact and threat biodiversity and ecosystem services, such as pollination. The aim of this study was to evaluate the effect of native forest and human-modified land covers on the concentrations of chemical elements accumulated in the neotropical pollinator bee T. angustula. Eight landscapes, within an Ecological Corridor in the State of São Paulo, Brazil, with gradients of forest cover, spatial heterogeneity and varying land covers were used as sampling unities. Bees collected in traps or through actives searches had the concentration of 21 chemical elements determined by ICP-MS. Results show a beneficial effect of forested areas on the concentrations of some well-known toxic elements accumulated in bees, such as Hg, Cd, and Cr. Multivariate Redundancy Analysis (RDA) suggests road as the most important driver for the levels of Cr, Hg, Sb, Al, U, As, Pb and Pt and bare soil, pasture and urban areas as the landscape covers responsible for the concentrations of Zn, Cd, Mn, Mg, Ba and Sr in bees. The results reinforce the potential use of T. angustula bees as bioindicators of environmental quality and also show that these organisms are being directly affected by human land use, offering potential risks for the Neotropical ecosystem. Our study sheds light on how land covers (native forest and human-modified) can influence the levels of contaminants in insects within human-dominated landscapes. The generation of predictions of the levels of toxic metals and metalloids based on land use can both contribute to friendly farming planning as well as to support public policy development on the surrounding of protected areas and biodiversity conservation hotspots.

The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China

High concentrations of potentially toxic elements (PTE) create global environmental stress due to the crucial threat of their impacts on the environment and human health. Therefore, determining the concentration levels of PTE and improving their prediction accuracy by sampling optimization strategy is necessary for making sustainable environmental decisions. The concentrations of five PTEs (Pb, Cd, Cr, Cu, and Zn) were compared with reference values for Shanghai and China. The prediction of PTE in soil was undertaken using a geostatistical and spatial simulated annealing algorithm. Compared to Shanghai’s background values, the five PTE mean concentrations are much higher, except for Cd and Cr. However, all measured values exceeded the reference values for China. Pb, Cu, and Zn levels were 1.45, 1.20, and 1.56 times the background value of Shanghai, respectively, and 1.57, 1.66, 1.91 times the background values in China, respectively. The optimization approach resulted in an increased prediction accuracy (22.4% higher) for non-sampled locations compared to the initial sampling design. The higher concentration of PTE compared to background values indicates a soil pollution issue in the study area. The optimization approach allows a soil pollution map to be generated without deleting or adding additional monitoring points. This approach is also crucial for filling the sampling strategy gap.

Identifying the spatiotemporal dynamic of PM2.5 concentrations at multiple scales using geographically and temporally weighted regression model across China during 2015-2018

Fine particulate matter (PM_2.5) is closely related to the air quality and public health. Numerous models have been introduced to simulate the PM_2.5 concentrations at large scale based on remote sensing and auxiliary data. However, the data precision provided by these models are inadequate for epidemiology and pollutant exposure studies at medium or small scale. The present study aims to calibrate PM_2.5 concentrations at 1 km resolution scale across China during 2015-2018 based on monitoring station data and auxiliary data using a novel geographically and temporally weighted regression model (GTWR). The cross-validation (CV) method and the geographically weighted regression (GWR) model are conducted for validation and cross-comparison. Additionally, the spatial autocorrelation and slope analysis methods are implemented to detect the spatiotemporal dynamic of PM_2.5 concentrations. A sample-based CV of the GTWR model demonstrates an acceptable precision with a coefficient of determination equal to 0.67, a root-mean-square error of 10.32 μg/m³, and a mean prediction error of-6.56 μg/m³. This result proves that the GTWR model can simulate PM_2.5 concentrations at a higher spatial resolution and accuracy across China than some previous models. Besides, the heterogeneity and spatiotemporal dynamic of PM_2.5 concentrations are obvious, that is, the High-High (H-H) agglomeration areas with strong haze pollution were mainly concentrated in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Chengdu-Chongqing (CY), and Guanzhong Plain (GZP). In addition, the PM_2.5 concentrations are undergoing a decreasing trend in most of the study area, and the decrease in the BTH is dramatic. The results of the present study are helpful for calibrating and detecting the spatiotemporal dynamic of PM_2.5 concentrations and useful for the government to make decisions about decreasing haze pollution in urban agglomeration scale.

Influence of site-classification approach on geochemical background values

This study of peri-urban minerogenic topsoil on glacigenic or post-glacial deposits shows the influence of the site-classification approach on the differentiated median background (DMB) values of major elements and the potentially harmful elements (PHEs) Ba, Cr, Cu, Mn, Ni, Pb and Zn. Composite samples from forests and meadows were taken in 25 sites, each of which had five sub-sites. A fraction of <2 mm was used to determine the organic matter by loss on ignition (LOI), grain size by laser diffraction and the elemental contents by X-ray fluorescence. The following five site-classification approaches are compared: geochemical (G), using relative median contents of Al, K, Ti; textural (T), according to mean percentages of clay-sized fraction (CLF) and silt fraction (SIF); lithological (L), based on soil parent material texture from the soil database; soil type (S), presented in the soil database; and parent material (P), generalising the underlying Quaternary deposits. Sites were classified into four level groups in which the DMB values were estimated after eliminating anomalies. The average ranks of three scores according to SIF, CLF, LOI, Al, K, Ti, Fe, Mg, Ca and S in the respective groups revealed the highest value for the G approach. It better eliminates the CLF and SIF influences on the median assessment indices of PHEs in sites.

Polycyclic aromatic hydrocarbons in leaves of Cinnamomum camphora along the urban-rural gradient of a megacity: Distribution varies in concentration and potential toxicity

Rapid urbanization and industrialization have precipitated the significant urban-rural gradient involving various aspects of human-related activities especially in megacities. Anthropogenic activities are the main source of polycyclic aromatic hydrocarbon (PAH) contamination, and the rising awareness concerning PAH potential toxicity to human health promotes a further understanding of its spatial distribution pattern in cities. Whether the distribution of PAH concentration and potential toxicity respond to the urban-rural gradient still requires investigation. This study applied a grid sampling method to investigate PAH concentration using Cinnamomum camphora leaves as bioindicators which were obtained from 84 sampling sites in a megacity, Shanghai. The potential toxicity of PAHs in leaves was calculated by toxicity factor equivalent method. Results revealed the patterns of PAH distribution in the city varied in concentration and potential toxicity: the total concentration of PAHs in leaves decreased along the urban-rural gradient, while the potential toxicity peaked at junction areas. The trend of PAH concentration along the distance from urban center corresponded to that of population density. The spatial distribution of potential toxicity did not correspond with the gradient but was influenced by high benzo(a)pyrene concentration originated from the industry districts nearby. Higher potential toxicity of PAHs was observed at the urban-suburban-rural junction areas of megacities, advocating health-risk attention and appropriate plan for land use of these transition areas in cities.

Phytoremediation of cadmium-polluted soil assisted by D-gluconate-enhanced Enterobacter cloacae colonization in the Solanum nigrum L. rhizosphere

Microbe-assisted phytoremediation for Cd-polluted soil is being regarded increasingly. However, the availability of microbes that can collaborate with Cd-hyperaccumulators effectively has become one of bottlenecks restricting the remediation efficiency. A siderophore-producing bacterium (Y16; Enterobacter cloacae) isolated from the rhizospheric soil of Cd-hyperaccumulator Solanum nigrum L. was identified by 16S rRNA gene sequencing and biochemical analysis, and then used for analyzing microbial chemotaxis, carbon source utilization, and insoluble P/Cd mobilization capacities. Besides, a soil-pot trial was performed to underlie the phytoremediation mechanism of Cd-polluted soil assisted by D-gluconate-enhanced Enterobacter cloacae colonization (DEYC) in the Solanum nigrum L. rhizosphere. Results displayed that D-gluconate was an effective chemoattractant and carbon source strengthening Y16 colonization, and Y16 exhibited strong abilities to mobilize insoluble P/Cd in shake flask by extracellular acidification (p < 0.05). In the soil-pot trial, DEYC observably enhanced soil Cd phytoextraction by Solanum nigrum L., and increased microbial diversity according to alpha- and beta-diversity analysis (p < 0.05). Taxonomic distribution and co-occurrence network analysis suggested that DEYC increased relative abundances of dominant microbial taxa associated with soil acidification (Acidobacteria-6), indoleacetic acid secretion (Ensifer adhaerens), soil fertility improvement (Flavisolibacter, Bdellovibrio bacteriovorus, and Candidatus nitrososphaera), and insoluble Cd mobilization (Massilia timonae) at different classification levels. Importantly, COGs analysis further shown that DEYC aroused the up-regulation of key genes related to chemotactic motility, carbon fixation, TCA cycle, and propanoate metabolism. These results indicated that DEYC drove the rhizospheric enrichment of pivotal microbial taxa directly or indirectly involved in soil Cd mobilization, meanwhile distinctly promoted plant growth for accumulating more mobilizable Cd. Therefore, Y16 could be used as bio-inoculants for assisting phytoremediation of Cd-polluted soil.

Ecological risk evaluation and source apportionment of heavy metals in park playgrounds: a case study in Xi'an, Shaanxi Province, a northwest city of China

Park playgrounds recently are suffering serious heavy metals contamination in China. It is urgent to assess the ecological risk and identify the sources for heavy metals. A total of 111 topsoil samples were collected from four park playgrounds in Xi'an, and the X-ray fluorescence (XRF) instrument was used to measure the concentrations of heavy metals including chromium(Cr), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), manganese (Mn), and cobalt (Co), respectively. Ecological risk ([Formula: see text]) and potential ecological risk index (RI) were introduced to determine the pollution level and ecological risk, and the absolute principal component score-multiple linear regression (APCS-MLR) model was implemented to identify the sources for heavy metals. The main results were as follows. (1) Except As, the mean concentrations of measured heavy metals of four park playgrounds surpassed the soil background values of Shaanxi Province. (2) In each park playground, the [Formula: see text] was below a "low" risk level ([Formula: see text]=10) for Cr, Ni, Zn, As, and Mn; Cu was between a "moderate" and "considerable" risk level; Pb was between a "low" and "moderate" risk level; and [Formula: see text] was between a "considerable" and "high" risk level for Co. Besides, the RI index was on a "high" risk level (120 < RI < 240) with an obvious spatial distinction. (3) The anthropogenic factors were the main sources for heavy metals, and mixed sources and natural sources were considered as the minor sources for metals. (4) The sources contributions for Co had obvious spatial heterogeneity in each park situated in four different urban planning districts.

Heavy-Metal Pollution Characteristics and Influencing Factors in Agricultural Soils: Evidence from Shuozhou City, Shanxi Province, China

Although soil quality can be highly altered by mining activities, there are few reports on soil pollution in mining cities. We systematically characterized the heavy metals (HMs) pollution, risks, sources, and influencing factors in the surrounding soils of Shuozhou. Specifically, 146 samples were collected, and the potential ecological risk index (RI) and the single-factor index were jointly used to understand the environmental risk of HMs. Meanwhile, correlation analysis was applied to find the influencing factors of HMs. The results of the soil pollution risk assessment in the entire area of Shuozhou were compared with those in the open-pit mine area. (1) The mean concentrations of Cr, As, Cd, Pb, and Hg in our study were found to be higher than the background value. The RI results indicated that most soil samples (82.88%) in Shuozhou had a low potential ecological risk. Compared with the Pingshuo open-pit mine (average RI value: 200.07), the potential ecological RI was lower. (2) The HM correlation indicated that Cr and As were associated with the parent rock, whereas Cd, together with Hg and Pb, were associated with anthropic activities. (3) There was no significant correlation between HM concentrations and farmland slope. Located in the Datong Basin, the terrain of Shuozhou is relatively flat and open and has little impact on the distribution of HMs. (4) Only Hg and Pb have a negative correlation with pH. This suggests that soil with a lower pH value may be beneficial to the accumulation of Hg and Pb in soil. (5) Among the eight industry types examined, the pollution capacity level of the leather, fur, feather, and footwear industries is the strongest, indicating that HMs around LI industry sites represent the maximum level among the eight types.

Effects of urbanization on Cd accumulation in agricultural soils: From the perspective of accessibility gradient

Road accessibility clearly reflects the spatial heterogeneity of urbanization. This study therefore adopted accessibility gradient to analyze the effects of urbanization on Cadmium (Cd) accumulation in agricultural soils. In total, 212 soil samples were collected along the accessibility gradient from agricultural soils in the Guangzhou-Foshan metropolitan region. Cd concentration showed a clearly decreasing pattern in agricultural soils with a decrease in accessibility level. The decreasing patterns varied in different accessibility ranges. The urban-rural ecotone (accessibility range 10-15) was the region with the most drastic changes in Cd accumulation. The influencing factors of Cd accumulation in agricultural soils mainly include industrial pollutants, agriculture chemicals, mining activities, domestic wastes, and soil properties. The importance of these factors varies across different accessibility ranges. Our findings imply that the characteristic variation of Cd accumulation with the road accessibility gradient must be considered in the formulation of targeted policies for controlling Cd contamination in agricultural soils.

Soil heavy metal contamination and health risk assessment associated with development zones in Shandong, China

Heavy metal pollution in soils of development zones has attracted wide attention. In this study, soil heavy metal pollution levels and health risks in 15 selected development zones in Shandong Province were investigated for the first time. Geo-accumulation and potential ecological risk indexes were used to assess pollution levels, and health risk was assessed using the US Environmental Protection Agency model. The soil was contaminated by various heavy metals, among which Hg was dominant. A total of 19% of the monitoring sites showed moderate ecological risk level, and low risk level was observed in general. Pollution control of Hg and Cd in each development zone must be strengthened. Health risk analysis showed that noncarcinogenic and carcinogenic risk levels for adults and children were acceptable or nearly acceptable. Positive matrix factorization model was used to identify three possible sources of heavy metal pollution, namely, industrial sources, atmospheric deposition, and transportation. Some specific measures should be taken to prioritize the control of Hg, As, and Cr for protecting the soil environment and human health, especially vulnerable groups, such as children.