Soil contamination in urban environment by trace metals is of public concerns. For better risk assessment, it is important to determine their background concentrations in urban soils. For this study, we determined the background concentrations of 9 trace metals including As, Ba, Cd, Co, Cu, Ni, Pb, Se, and Zn in 214 urban soils in Florida from two large cities (Orlando and Tampa) and 4 small cities (Clay County, Ocala, Pensacola and West Palm Beach). The objectives were to determine: 1) total concentrations of trace metals in urban soils in cities of different size; 2) compare background concentrations to Florida Soil Cleanup Target Levels (FSCTLs); and 3) determine their distribution and variability in urban soils via multivariate statistical analysis. Elemental concentrations in urban soils were variable, with Pb being the highest in 5 cities (165–552 mg kg⁻¹) and Zn being the highest concentration in Tampa (1,000 mg kg⁻¹). Besides, the As and Pb concentrations in some soils exceeded the FSCTL for residential sites at 2.1 mg kg⁻¹ As and 400 mg kg⁻¹ Pb. Among the cities, Clay County and Orlando had the lowest concentrations for most elements, with Cd, Co, and As being the lowest while Ba, Pb and Zn being the highest. Among all values, geometric means were the lowest while 95th percentile was the highest for all metals. Most 95th percentile values were 2–3 folds higher than the GM data, with Pb presenting the greatest difference, being 4 times greater than GM value (58.9 vs. 13.6 mg kg⁻¹). Still they were lower than FSCTL, with As exceeding FSCTL for residential sites at 2.1 mg kg⁻¹. In addition, the linear discriminate analysis showed distinct separation among the cities: Ocala (Ba & Ni) and Pensacola (As & Pb) were distinctly different from each other and from other cities with higher metal concentrations. The large variations among elemental concentrations showed the importance to establish proper background concentrations of trace metals in urban soils.

China and the UK use different risk-based approaches to derive soil screening or guideline values (SSVs; SGVs) for contaminants. Here we compare the approaches and the derived values for 6 illustrative contaminants. China’s SSVs are derived using an approach developed in the US as follows: for carcinogens, acceptable level of risk (ACR) is set at 10−6 and the SSVs calculated as 10−6 divided by the soil exposure and toxicity data; for non-carcinogens, the hazard quotient is 1 and the SSV is calculated as 1 divided by the soil exposure and toxicity data. The UK’s SGVs are calculated by the CLEA model, for which the Average Daily Exposure (ADE) from soil sources by a specific exposure route equals the health criteria values (HCVs) for that route, whether for carcinogens or a non-carcinogens. The UK’s CLEA model is also used here to derive SSVs with Chinese input parameters. China’s SSVs, the UK’s SGVs and values for Chinese conditions derived using the UK approach were as follows (mg/kg): As, <1, 35, 20; Cd, 20, 18, 11; Cr (VI), <1, 14, 29; benzene, 1, 1, 2; toluene, 1200, 3005, 3800; ethyl-benzene, 7, 930, 1200. By comparing the differences in toxicity assessment and risk characterization, exposure assessment and parameter types in the methodologies to obtain SSVs in China and the UK, and by combining the CLEA model with Chinese parameterisation, these comparisons highlight that the difference in toxicity assessment and risk characterization methods of carcinogens results in the biggest difference in SSVs between the 2 countries. However, for non-carcinogenic substances, the difference of SSVs calculation method and SSVs is small. The difference in SSVs for carcinogenic substances is also related to the route of exposure. For volatile organic compounds, the presence of indoor respiratory exposure pathways greatly reduces the differences caused by toxicity assessment and risk characterization methods. For non-volatile substances such as heavy metals, the effects of toxicity assessment and risk characterization methods are significant. The SSV of As obtained by the CLEA model with Chinese parameters is closer to the background value of soil in China. In the management of non-volatile contaminated sites such as heavy metals in China, the CLEA model can be used for risk assessment and calculation of site specific SSVs. In the future, China can use the UK method to strengthen its toxicity assessment and risk characterization methods for carcinogenic substances, to reduce the uncertainty in the risk assessment of contaminated sites and improve the scientific management of contaminated sites.

Microplastics with extremely high abundances are universally detected in marine and terrestrial systems. Microplastic pollution in the aquatic environment, especially in ocean, has become a hot topic and raised global attention. However, microplastics in soils has been largely overlooked. In this paper, the analytical methods, occurrence, transport, and potential ecological risks of microplastics in soil environments have been reviewed. Although several analytical methods have been established, a universal, efficient, faster, and low-cost analytical method is still not available. The absence of a suitable analytical method is one of the biggest obstacles to study microplastics in soils. Current data on abundance and distribution of microplastics in soils are still limited, and results obtained from different studies differ significantly. Once entering into surface soil, microplastics can migrate to deep soil through different processes, e.g. leaching, bioturbation, and farming activities. Presence of microplastics with high abundance in soils can alter fundamental properties of soils. But current conclusions on microplastics on soil organisms are still conflicting. Overall, research on microplastics pollution in soils is still in its infancy and there are gaps in the knowledge of microplastics pollution in soil environments. Many questions such as pollution level, ecological risks, transport behaviors and the control mechanisms are still unclear, which needs further systematical study.

Soil contamination posed by potentially toxic elements is becoming more serious under continuously development of industrialization and the abuse of fertilizers and pesticides. The investigation of soil potentially toxic elements is therefore urgently needed to ensure human and other organisms’ health. In this study, we investigated the feasibility of the separate and combined use of portable X-ray fluorescence (pXRF) and visible near-infrared reflectance (vis-NIR) sensors for measuring eight potentially toxic elements in soil. Low-level fusion was achieved by the direct combination of the pXRF and vis-NIR spectra; middle-level fusion was achieved by the combination of selected bands of the pXRF and vis-NIR spectra using the Boruta feature selection algorithm; and high-level fusion was conducted by outer-product analysis (OPA) and Granger–Ramanathan averaging (GRA). The estimation accuracy for the eight considered elements were in the following order: Zn > Cu > Ni > Cr > As > Cd > Pb > Hg. The measurement for Cu and Zn could be achieved by pXRF spectra alone with Lin’s concordance correlation coefficient (LCCC) values of 0.96 and 0.98, and ratio of performance to interquartile distance (RPIQ) values of 2.36 and 2.69, respectively. The measurement of Ni had the highest model performance for high-level fusion GRA with LCCC of 0.89 and RPIQ of 3.42. The measurements of Cr using middle- and high-level fusion were similar, with LCCC of 0.86 and RPIQ of 2.97. The best estimation accuracy for As, Cd, and Pb were obtained by high-level fusion using OPA, with LCCC >0.72 and RPIQ >1.2. However, Hg measurement by these techniques failed, having an unacceptable performance of LCCC <0.20 and RPIQ <0.75. These results confirm the effectiveness of using portable spectrometers to determine the contents of several potentially toxic elements in soils.

Environmental distribution and concentration of tetrabromobisphenol A bis- (2-hydroxyethyl) ether (TBBPA-DHEE) and tetrabromobisphenol A mono- (hydroxyethyl) ether (TBBPA-MHEE), are obscure due to the lack of available analytical methods. Here two novel immunoassays were established to systematically investigate their distributions in Taizhou, Eastern China. Five monoclonal antibodies against pollutants were generated with two designed haptens through animal immunization. After matched with different coating antigens/antibodies, ELISAs were established (LOD for TBBPA-DHEE, 0.12 ng/mL, based on OVA-M3/mAb-D4G6; LOD for TBBPA-MHEE, 0.79 ng/mL, based on OVA-M3/mAb-D2G6) and applied for investigation of their occurrences at a typical e-waste recycling area after 2-year samples collection, where the total 33 water, 32 soil and 16 biological samples were collected with the highest concentrations of 3.46 ng/mL, 2.76 ng/g (dry weight, dw) and 5.01 ng/g (dw), respectively. Meanwhile, our study also indicated that at the centralizing e-waste recycling sites the serious pollution for both chemicals still existed despite of various efforts. Besides, obvious improvements were observed at an abandoned e-waste recycling region treated and remedied for many years by the local Chinese government. These findings highlight the importance of policy decisions in treatment of pollutants to reduce organic pollutant-related health risks.

Intensive anthropogenic activity has triggered serious heavy metal contamination of soil. Land use and land cover (LULC) changes bear significant impacts, either directly or indirectly, on the distribution of heavy metal in soils. A total of 180 samples were acquired from various land covers at different depths, namely surface soils (020 cm) and subsurface soils (20–40 cm). Spatial interpolation, geographically weighted regression (GWR) and self-organizing map (SOM) were used to discern how variations in the spatial distributions of soil heavy metals were caused by human activities for different land uses, and how these pollutants contributed to environmental risks. The medium concentrations of Cd, Cr, Cu, Pb and Zn in surface soil all exceeded the corresponding local background values in flat cropland and developed area soil. The overall ecological risk level of the study varied from low to medium. The GWR model indicated that the land use intensity had a certain influence on the accumulation of heavy metals in the surface soil. K-means clustering of the SOM revealed that the type of LULC also contributed to the redistribution of heavy metals in the surface soil.

Environmental complexity leads to differences in the spatial distribution of heavy metal pollution in soil and rice. Such spatial differences will seriously affect the safety of planted rice and can impact regional management and control. How to scientifically reveal these spatial differences is an urgent problem. In this study, the spatial mismatch relationship between Cd pollution in soil and rice grains (brown rice) was first explored by the interpolation method. To further reveal the causes of these, the specific recognition rules of the spatial relationship of Cd pollution were extracted based on a decision tree model, and the results were mapped. The results revealed a spatial mismatch in Cd pollution between the soil and rice grains in the study area, and the main results are as follows: (i) slight soil pollution and safe rice accounted for 68.88% of the area; (ii) slight soil pollution and serious rice pollution accounted for 13.39% of the area and (iii) safe soil and serious rice pollution accounted for 11.63% of the area. In addition, 11 recognition rules of Cd spatial pollution relationship between soil and rice were proposed, and the main environmental factors were determined: SOM (soil organic matter), Dis-residence (distance from residential area), soil pH and LAI (leaf area index). The average accuracy of rule recognition was 75.90%. The study reveals the spatial mismatch of heavy metal pollution in soil and crops, providing decision-making references for the spatial accurate identification and targeted prevention of heavy metal pollution spaces.

The long-term contamination of soil by microplastics may pose risks that are often still not well understood, and the ecological effects of microplastics are mainly dependent on their environmental behavior in environments. This study used saturated quartz sand as a solid porous medium to study the migration and influencing factors of 40–48 μm polyethylene (PE) particles in saturated porous media. The breakthrough curves at different injection concentrations (0.3, 0.4, 0.5 mg/L), flow rates (1.0, 1.5, 2.0, 2.5 ml/L), porous medium particle sizes (1–2, 2–4 mm), ionic strengths (0, 0.01, 0.05 mol/L) and concentrations of fulvic acid (FA) (0, 5, 10 mg/L) were compared and analyzed. The Derjaguin-Landau-Verwey-Overbeek (DLVO) theory was used to more accurately explain relevant transport behaviors. The results showed that the input concentration, flow rate, and particle size can affect the migration of PE particles individually or in combination. As ionic strength increased, the repulsion between microplastics and quartz sand gradually disappeared according to DLVO theory, and their attraction gradually strengthened. As a result, fewer microplastics could penetrate the sand column and reach the water body. With the continuous addition of FA, the repulsive energy between microplastics and quartz sand rose from DLVO theory, and the migration ability of microplastics initially increased before becoming stable because of the effect of straining. In all cases, the migration ability of PE was low (C/C₀ < 0.35), and most PE particles remained in the porous media during the whole experimental periods. This study provides new insights of understanding the migration of microplastics in environment.

Mercury (Hg) is a toxic and persistent pollutant and has long-term impacts on ecological systems and human health. Coal-fired power plants (CFPPs) are the main source of anthropogenic Hg emission, and the emitted atmospheric Hg is deposited to the surrounding environments which causes soil pollution. To assess the effects of atmospheric Hg from CFPPs in China on the temperate steppe, Hg contents in the topsoil and subsoil were analyzed for samples collected from 80 sites in central Inner Mongolia during 2012–2015. The average content of Hg in topsoil and subsoil were 14.9 ± 10.4 μg kg⁻¹ and 8.9 ± 5.8 μg kg⁻¹, respectively. The principal components analysis (PCA) indicated that the soil organic matter content and atmospheric deposition were the main factors determining soil Hg content in Inner Mongolia. We used the power plant impact factor (PPIF) to evaluate the impacts of the surrounding CFPPs. The PPIF results showed the most positive correlation with Hg content in topsoil at more than 400 km distances, indicating that the contribution of the long-range transport of Hg emitted from CFPPs is regional in scale. Considering the potential of Hg accumulation in soil, long-term and regional measurements of soil Hg and stricter emission-limit standards for power plants should be implemented to control soil Hg pollution in China.

Cadmium (Cd) contamination in soils has become a serious and widespread environmental problem, especially in areas with high natural background Cd values, but the mechanism of Cd enrichment in these areas is still unclear. This study uses the Guangxi Zhuang Autonomous Region (Guangxi), a typical area with a high background Cd level and Cd pollution related to mining activities, as an example to explore the source and predict areas with high Cd risk in soils based on the geographical detector method. The areas with high Cd in Guangxi soils were classified into non-mining areas and mining areas according to their potential Cd sources. The results show that the rich Cd content in the soils from the non-mining area of Guangxi was mainly derived from the soil type (q = 0.34), geological age (q = 0.27), rock type (q = 0.26) and geomorphic type (q = 0.20). Specifically, the Cd content was derived from the weathering and deposition processes of carbonatite from the Carboniferous system in the karst area. The high Cd content in the soils of the mining area of Guangxi was mainly derived from the area mined for mineral resources (q = 0.08) and rock type (q = 0.05). Specifically, the Cd content was derived from the mining of lead-zinc ores. The areas in Guangxi with a high risk of Cd soil pollution are mostly concentrated in karst areas, such as Hechi, Laibin, Chongzuo, southern Liuzhou and Baise, northern Nanning city and northeastern Guilin city, and some mining areas. These results indicated that the high Cd concentration in the soils of large areas of Guangxi is probably due to natural sources, while the high Cd concentration around mining areas is due to anthropogenic sources. The results will be useful for soil restoration and locating and controlling contaminated agricultural land.