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Environmental problems caused by heavy metal pollution in soil have attracted widespread attention worldwide. Identifying and quantifying the heavy metal pollution sources and risks is crucial for subsequent soil management. In this study, an integrated source-risk method for source apportionment and risk assessment based on the PMF model, the geodetector model and the health risk assessment model (HRA) was proposed and applied. Analysis of Hg, As, Pb, Cd, Cu, Ni, Cr, and Zn in 208 topsoils showed that the average contents of eight heavy metals were 1.87-5.86 times greater than corresponding background values, among which Cd and As were relatively high, which were higher than the specified soil risk screening values, high-value areas of heavy metals are mainly concentrated in the central part of the study area. The source apportionment showed that the accumulation of heavy metals was affected by five sources: atmospheric deposition (16.3 %), natural sources (33.1 %), industrial activities dominated by metal mining (15.1 %), industrial activities dominated by metal smelting (12.6 %) and traffic sources (22.9 %). The results of the health risk assessment showed that the carcinogenic risks (adult: 4.74E-05, children: 7.41E-05) of heavy metals in soil to the study population were both acceptable, the non-carcinogenic risk of adult (THI = 0.277) was within the limit, while the non-carcinogenic risk of children (THI = 1.70) was higher than the limit value. Ingestion (89.5 %-95.9 %) contributed the greatest health risk among all exposure routes. Source 3 (arsenic-related industrial activities dominated by metal mining) contributed the most to the HI and CRI of adults and children (all above 50 %), therefore, in the formulation stage of soil management strategy in this area, priority should be given to the control and management of this pollution source. These results can provide more detailed support for environmental protection departments to propose targeted soil pollution control measures.

Soil pollution has caused increasingly widespread attention in China. The environmental risk threshold of pollutants is a yardstick to measure soil environmental quality. For decades, plenty of research on soil environmental quality standards (SEQSs) has been carried out, providing scientific basis for the investigation and supervision of soil environmental quality. This paper summaries the development of SEQSs in China, the corresponding influencing factors and methodology of SEQSs derivation. In the current version of SEQSs (GB15618-2018), the thresholds of soil pollutants are derived by the methods of environmental risk assessment, which are more methodologically scientific than geochemical method and ecological effect method used in the previous version (GB15618-1995). Abundant toxicology data on related species is required for risk assessment of soil pollution using extrapolation; however, basic toxicological data is insufficient and few valid data is available at present. Besides, the inadequate consideration on influencing factors for the derivation of soil pollutant threshold would affect the scientificity and rationality of SEQSs, such as biotic factors (species type, test endpoint etc.) and abiotic factors (aging effect, leaching effect, synergistic or antagonistic effects of elements etc.). These problems should be paid close attention in future research on soil environmental quality standards. The contents summarized in this review may provide reference for decision-making on supervision of soil environmental quality and point out important directions for future studies.

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.

Previous studies have found that Cadmium (Cd) may be condensed during the processes of the weathering and soil formation over carbonate bedrock, which is a typical phenomenon in the southwest region of China. However, the extent of the high value background and the geographical factors influencing its spatial distribution are still unknown. This study collected data from the Multi-Purpose Regional Geochemical Survey (MPRGS) and the Regional Geochemistry-National Reconnaissance Program (RGNR) to investigate the extent and its controlling factors based on spatial analysis. It was found that the RGNR is an ideal data source for regional Cd background studies. Spatially, the high Cd area (Cd 1.5 m/kg with reference of the GB15618-2018 soil environmental quality in China, 68.9 × 10

Heavy metals in soil are a great threat to ecosystems and human health. The rapid development of industrialization has created a serious risk of heavy metal pollution in soil. The study took the industrial-intensive Dahetan subbasin as the typical area. The factors and interactions that affected the distribution of soil heavy metals (Cd, Hg, As, Pb and Cr) in the typical area were explored based on the Geodetector model. The analysis results were extended to predict high-risk areas of heavy metal pollution in the soil in the Xiangjiang River basin. The results showed that Cd, As and Pb were significantly affected by local industrial and mining activities, and Hg and Cr were primarily affected by natural factors, such as pH and soil type. Compared to a single factor, the interaction between factors had a greater impact on the concentration of heavy metals. The high-risk areas of soil heavy metal pollution in the Xiangjiang River basin were primarily concentrated in the upper reaches and middle reaches.Significant overlapping of high-risk areas of multiple heavy metals occurred in the west, middle and south of the basin. The spatial visualization of the high-risk areas was realized, and the influence of several factors was integrated via layer superposition. This study proposes a new idea to predict the high-risk areas of soil pollution in large-scale areas to provide a reference for the regional prevention and control of soil pollution.

Mining activities are among the main sources of heavy metal contamination in the environment. To analyze heavy metal pollution of soils from coal mines in China, we assessed pollution and potential ecological risk, compared heavy metal concentrations between soils from coal mines and soils from metal mines and identified the relationship between heavy metals on the nationwide scale. The data of heavy metal concentrations for 50 coal mines and 35 metal mines were collected from the published literature. Coal mines referred in this paper are distributed in 18 provinces and 4 climatic zones in China. Methods including Index of geoaccumulation (Igeo), Nemerow pollution index (P), potential ecological risk index and other statistics (Pearson correlation method and ANOVA variance analysis) were utilized. Compared with soils influenced by metal mining, heavy metal concentrations in soils from coal mines were much lower. For heavy metals, higher Igeo for Cd, Pb and Ni was observed. Soils were contaminated or slightly contaminated when calculated based on Chinese soil guidelines (grade I and grade II) but slightly contaminated or severely contaminated when calculated based on province backgrounds. Most heavy metals (i.e., As, Cr, Cu, Ni and Zn) showed a low potential ecological risk, whereas Cd, Pb and Hg showed slightly higher ecological risk potential. Statistically significant and positive correlations were found in pairs of As/Cr, As/Ni, As/Pb, As/Hg, Ni/Cr and Ni/Cu (P

It is important to understand the status and extent of soil contamination with heavy metals to make sustainable management strategies for agricultural soils. Input and output inventory of heavy metals in agricultural soil of Zhejiang Province was systematically studied. The results showed that atmospheric deposition was responsible for 47.88% and 76.87% of the total Cr and Pb inputs, respectively. Livestock manures accounted for approximately 54–85% of the total As, Cu, and Zn inputs. Livestock manure and irrigation were the main sources of Hg, contributed 50.25% and 38.63% of the total inputs, respectively. Ni was derived mainly from atmospheric deposition (57.86%), followed by irrigation (22.69%). As for Cd, the relative contributions of atmospheric deposition, irrigation, and livestock manure were similar. Crop harvesting and leaching were found to be the dominant output pathways of the soil elements Cd, Cu, Hg, and Zn, being responsible for 74.43–83.62% of the total outputs. Surface runoff was the dominant output pathway for As, Cr, Ni, and Pb, accounting for approximately 73.36%, 46.32%, 54.16%, and 48.11% of the total outputs, respectively. According to prediction and early warning, Cd is the priority control pollutant in agricultural soil. This work will assist in developing strategies for reducing heavy metal inputs to agricultural soil and effectively targeting policies to protect soil environment from long-term heavy metal accumulation.

Flooding in paddy soils alters the soil redox of manganese (Mn) and produces elevated concentrations of soluble Mn that can reduce cadmium (Cd) uptake by rice. To better understand the fates of Mn and Cd, along with changes in soil redox conditions, we conducted microcosm incubations in paddy soil covering the reduction to oxidation to re-reduction phases. The extractable Cd concentration decreased rapidly during the reduction phases but increased upon oxidation, and Cd availability largely depended on soil pH, Eh, pe + pH, and the extractable Mn concentration. Exogenous Mn can promote Cd binding with Fe–Mn(oxyhydro)oxides. A trade-off effect between the soil-extractable Cd and Mn concentrations across changes in pH, Eh, pe + pH was identified, and attaining an optimal pe + pH value of 6.8 was targeted. Furthermore, to provide insights into how the redox status of Mn changes to alter Cd mobilization in a paddy soil-rice system, Cd isotope ratios across the paddy soil-rice tissue continuum were investigated using planted rhizobox experiments under different irrigation regimes. The heavy Cd isotopes from the soil to liquid-phase (Δ114/110Cdextract-soil = 0.40–0.82‰) and from the soil to rice grain (Δ114/110Cdgrain-soil = 0.84–0.89‰) were preferentially enriched. Light isotopes were likely to be enriched in Cd bound to Fe/Mn-oxides, a process that was promoted by increased Mn availability. These results suggest that Cd isotopes are systematically fractionated within the paddy soil–rice system, which is caused by the unsteady soil redox, and the stabilization of Cd in the bound soil pool such as Fe–Mn(oxyhydro)oxides-Cd under reducing conditions could be developed as a Cd retention mechanism in paddy soils.

Sodium sulfate stress is known to improve cadmium (Cd) mobilization in soil and microbial sulfur oxidation, Cd resistance, and the accumulation of stress tolerance-associated metabolites has been correlated with increased soil Cd availability and toxicity. In this study, aerobic soil microcosms with Cd-contamination were stimulated with sodium sulfate to investigate its effects on soil microbial community structure, functional genes, and associated metabolite profiles. Metagenomic analysis revealed that sulfur oxidizing and Cd-resistant bacteria carried gene clusters encoding sox, dsr, and sqr genes, and znt, czc, and cad genes, respectively. Exposure to sodium sulfate resulted in the reprogram of soil metabolites. In particular, intensification of sulfur metabolism triggered an up-regulation in the tricarboxylic acid (TCA) cycle, which promoted the secretion of carboxylic acids and their precursors by soil bacteria. The accumulation of organic acids induced in response to high sodium sulfate dosages potentially drove an observed increase in Cd mobility. Pseudomonas and Erythrobacter spp. exhibited a high capacity for adaptation to heavy metal- or sulfur-induced stress, evident by an increased abundance of genes and metabolites for sulfur cycling and Cd resistance. These results provide valuable insights towards understanding the microbial mechanisms of sulfur transformation and Cd dissolution under saline stress.

The types of land used for farmland can greatly influence the source and accumulation risk of heavy metals in soil. However, the apportioning quantitatively the source of soil heavy metals has been studied insufficiently, especially in terms of different types of farmland. In this study, a total of 252 soil samples were taken from dry land, paddy fields and greenhouse fields in the Jinyuan district of Taiyuan city, China, to assess the accumulation risk of heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb and Zn). The results were then integrated, and source apportionment was evaluated by geospatial analysis, multivariate statistical analysis and positive matrix factorization (PMF). Cr, Cd and Hg were the dominant pollutants in the studied area. Accumulation risk by Cd and Cu was more severe in greenhouse fields than in dry land or paddy fields, whereas As, Hg and Pb had relatively higher accumulation in paddy fields than in dry land or greenhouse fields. Hg was derived mainly from coal combustion by atmospheric precipitation for the three types of farmland. Long-term irrigation using sewage is the main reason for the accumulation of Cu and Ni in dry land soil, Cu and Zn in paddy field soil and Zn in greenhouse soil. Cd in dry land, Cd and Pb in paddy fields and Cd, Cu, Ni and Pb in greenhouse fields were primarily added to soil through fertilization. Sewage irrigation and fertilization were the dominant sources of heavy metals for paddy field (31.3%) and greenhouse field (33.1%), respectively.

Soil organic matter (SOM) and pH are critical soil properties strongly linked to carbon storage, nutrient cycling and crop productivity. Land use is known to have a dominant impact on these key soil properties, but we often lack the ability to examine temporal trajectories across extensive spatial scales. Large-scale monitoring programmes provide the data to evaluate these longer-term changes, and under different climatic conditions. This study used data from Chinese soil surveys to examine changes in soil pH and SOM across different land uses (dry farmland, paddy fields, grassland, woodland, unused land), with surface soil (0-20 cm) collected in the periods 1985-90 (Survey 1; 890 samples) and 2006-10 (Survey 2; 5005 samples) from two contrasting areas. In the southern part of China the mean pH of paddy soils fell sharply over the two decades between surveys - from pH 5.81 to 5.19 (p < 0.001), while dry farmlands in the northern sampling area fell slightly (from pH 8.15 to 7.82; p < 0.001). The mean SOM content of dry farmland soil rose in both areas and the mean SOM of paddy fields in the southern area also rose (all p < 0.001). Woodland soil pH in the south showed an increase from 4.71 to 5.29 (p < 0.001) but no significant difference was measured in the woodlands of the northern area, although the trend increased. The SOM content of woodland top soils rose in the northern (p = 0.003) and southern (p < 0.001) study areas. The implications and potential causes of these changes over the two decade timespan between surveys are discussed and suggestions made as to how large scale soil sampling campaigns can be designed to monitor for changes and potential controlling factors.

The intercropping of hyperaccumulators and fruit trees has great application prospects owing to its environmental and economic benefits. However, the variation tendency and spatial distribution characteristics of pollutants in soil are unclear. A 19-month pot positioning experiment was conducted to clarify the spatio-temporal characteristics of arsenic (As) during Pteris vittata L.-Citrus reticulata Blanco intercropping process. The results showed that: (1) In the early stage, the solubilization of soil As by P. vittata was dominant. At 3 months, the water-soluble As in P. vittata rhizosphere soil increased by 19.4-55.4% compared with the initial state. In the later stage, the As extraction from soil by P. vittata was dominant. At 19 months, the water-soluble As in P. vittata rhizosphere soil decreased by 24.6-71.2% compared with the initial state. The water-soluble As in C. reticulata rhizosphere soil in intercropping, under the role of P. vittata, reached 1.75-2.35 times that of monoculture at 7 months, and was not significantly different from that of monoculture at 19 months. (2) The spatial distribution characteristics of soil As, affected by As-hyperaccumulation of P. vittata, showed that the As variability of intercropping and P. vittata monoculture was greater than that of C. reticulata monoculture. The area of P. vittata remediating soil was approximately 15 cm horizontally around its planting point and at least 25 cm vertically. (3) P. vittata-C. reticulata intercropping did not affect the phytoremediation efficiency and effectively reduced the risk of As pollution for C. reticulata. The As concentration in C. reticulata leaves of open intercropping decreased by 39.0-64.2% (early-maturity) and 25.6-59.1% (late-maturity) compared with that of monoculture, similar to that in clean soil. This study analyzed the As migration characteristics during P. vittata-C. reticulata intercropping through time and space and provides important theoretical support for the remediation and safe use of As-contaminated farmland.

Identifying the inflection points and main influencing factors for arsenic (As) accumulation in Pteris vittata L. under field conditions is important to improve the phytoremediation efficiency. In this study, data on the entire growth cycle (270 days) of P. vittata over a year were recorded through a field trial. The results showed that the As accumulation characteristics of P. vittata were obviously different from those observed in greenhouse experiments. The aboveground biomass of P. vittata began to stabilize on day 180; the As concentration increased to a peak on day 90 and subsequently declined until day 180. The As accumulation was 318.11 g/hm2 after 120 days, reaching 96.7% of the highest value predicted by the logistic model. The results indicated that soil humidity is the key influencing factor for As accumulation by P. vittata. Increasing the soil humidity can substantially improve the As extraction efficiency. Based on the results of As accumulation in P. vittata, it could be suggested that the effect of As efflux on P. vittata was not significant. According to theoretical calculations, the total As loss caused by rainfall leaching accounted for less than 2.2% of the total As accumulation. The parameters obtained herein are significant for guiding the remediation of As-contaminated soils under similar climatic conditions.

Probability models are preferred over regression models recently in contamination evaluation but lacking proper performance comparison between two model types. Linear regression, logistic regression, XGBoost-based regression, and probability models were built considering soil arsenic and certain soil physicochemical properties of 287 samples to predict arsenic in rice grains. The outputs of all models were binarily classified uniformly for comparison. The complex algorithm-based models––XGBoost-based regression (R2 =0.046 ± 0.036) and probability models (cross-entropy = 0.697 ± 0.020)—did not surpass the simple linear regression (R2 =0.046 ± 0.031) and logistic regression models (cross-entropy = 0.694 ± 0.021). Accuracy, sensitivity, specificity, precision, and F1 score showed that the probability models exhibit no advantage on regression models, although the indicators above did not serve as proper scoring rules for the probability model. When discretizing the contaminant concentration in grains for probabilistic modeling, the limit concentration was considered as the splitting point but not the structure of the datasets, which would reduce the inherent advantage of the probability model. When predicting the contamination of crops, the probability model cannot eliminate the regression model, and simple but robust algorithm-based models are preferred when the quality and quantity of the dataset are undesirable.

As a redox-sensitive element, manganese (Mn) plays a critical role in Cd mobilization, especially in paddy soil. In an anoxic environment, the precipitation of Mn(II)-hydroxides specifically favors Cd retention, while draining the paddy fields results in substantial remobilization of Cd. However, how the change in Mn redox states during the periodical transit of anoxic to oxic systems affects Cd mobility remains unclear. In this study, we demonstrate that the radical effect generated during the oxidation of Mn(II)-hydroxides exerts a significant effect on the oxidative dissolution of Cd during the aeration of paddy soils. The extractable Cd concentration decreased rapidly during the reduction phases but increased upon oxidation, while Cd availability produced the opposite effect with soil pe + pH and the extractable Mn concentration. Inhibiting the oxidation of Mn(II)-containing phases by microbes suppressed the production of hydroxyl free radicals (•OH) and Cd mobilization in the drainage phase. Analysis of X-ray absorption spectroscopy and sequential extraction demonstrated that the transformation from the Mn phase of Mn(II) to Mn(III/IV) determines Cd solubility. Altogether, the oxidization of Mn(II)-hydroxides was associated with the generation of significant amounts of •OH. The dissolution of Mn(II)- incorporating phases lead to a net release of Cd into soils during soil aeration.

With rapid economic development and continuous population growth, several important cities in China suffer serious air pollution, especially in the Beijing-Tianjin-Hebei economic developing area. Based on the daily air pollution index (API) and surface meteorological elements in Beijing, Tianjin, and Shijiazhuang (the capital of Hebei province) from 2001 to 2010, the relationships between API and meteorological elements were analyzed. The statistical analysis focused on the relationships at seasonal and monthly average scales, on different air pollution grades and air pollution processes. The results revealed that the air pollution conditions in the 3 areas gradually improved from 2001 to 2010, especially during summer; the worst conditions in air quality were recorded in Beijing in spring due to the influences of dust, and in Tianjin and Shijiazhuang in winter due to household heating. Meteorological elements exhibited different influences on air pollution, showing similar relationships between API in monthly averages and 4 meteorological elements (i.e., the average, maximum, and minimum temperatures; maximum air pressure; vapor pressure; and maximum wind speed), whereas the relationships on a seasonal average scale demonstrated significant differences. Compared with seasonal and monthly average scales of API, the relation coefficients based on different air pollution grades were significantly lower, whereas the relationship between API and meteorological elements based on air pollution processes reduced the smoothing effect due to the average processing of seasonal and monthly API and improved the accuracy of the results. Finally, statistical analysis of the distribution of pollution days in different wind directions indicated the directions of extreme and maximum wind speeds that mainly influence air pollution, representing valuable information that could support the definition of air pollution control strategies through the identification of the regions (and the located emission sources) where the implementation of emission reduction actions should be focused. Integr Environ Assess Manag 2018;14:710-721. © 2018 SETAC.

The concentrations of 16 priority polycyclic aromatic hydrocarbons (PAHs) were measured in 128 surface soil samples from Xiangfen County, northern China. The total mass concentration of these PAHs ranged from 52 to 10,524ng/g, with a mean of 723ng/g. Four-ring PAHs contributed almost 50% of the total PAH burden. A self-organizing map and positive matrix factorization were applied to investigate the spatial distribution and source apportionment of PAHs. Three emission sources of PAHs were identified, namely, coking ovens (21.9%), coal/biomass combustion (60.1%), and anthracene oil (18.0%). High concentrations of low-molecular-weight PAHs were particularly apparent in the coking plant zone in the region around Gucheng Town. High-molecular-weight PAHs mainly originated from coal/biomass combustion around Gucheng Town, Xincheng Town, and Taosi Town. PAHs in the soil of Xiangfen County are unlikely to pose a significant cancer risk for the population.

Heavy metals (HMs) in soil are some of the most serious pollutants due to their toxicity and nonbiodegradability. Especially across large-scale areas affected by industry, the complexity of pollution sources has attracted extensive attention. In this study, an approach based on zoning to analyze the sources of heavy metals in soil was proposed. Qualitative identification of pollution sources and quantification of their contributions to heavy metals in soil are key approaches in the prevention and control of heavy metal pollution. The concentrations of five HMs (Cd, Hg, As, Pb and Cr) in the surface soil of the Chenzhou industrial impact area were the research objects. Multiple methods were used for source identification, including positive matrix factorization (PMF) analysis combined with multiple other analyses, including random forest modeling, the geo-accumulation index method and hot spot analysis. The results showed that the average concentrations of the five heavy metals were 9.46, 2.36, 2.22, 3.27 and 1.05 times the background values in Hunan soil, respectively. Cd was associated with moderately to strongly polluted conditions, Hg, As and Pb were associated with unpolluted to moderately polluted conditions and Cr was associated with practically unpolluted conditions. The mining industry was the most significant anthropogenic factor affecting the content of Cd, Pb and As in the whole area, with contribution rates of 87.7%, 88.5% and 62.5%, respectively, and the main influence area was within 5 km from the mining site. In addition, we conducted hot spot analysis on key polluting enterprises and identified hot spots, cold spots, and areas insignificantly affected by enterprises, used this information as the basis for zoning treatment and discussed the sources of heavy metals in the three subregions. The results showed that Cd originated mainly from agricultural activities, with a contribution rate of 63.6%, in zone 3. As originated mainly from sewage irrigation, with a contribution rate of 65.0%, in zone 2, and the main influence area was within 800 m from the river. This element originated mainly from soil parent materials, with a contribution rate of 69.7%, in zone 3. Pb mainly originated from traffic emissions, with a contribution rate of 72.8%, in zone 3, and the main influence area was within 500 m from the traffic trunk line. Hg was mainly derived from soil parent materials with a contribution rate of 92.1% in zone 1, from agricultural activities with a contribution rate of 77.5% in zone 2, and from a mixture of natural and agricultural sources with a contribution rate of 74.2% in zone 3. Cr was mainly derived from the soil parent materials in the whole area, with a contribution rate of 90.7%. The study showed that in large-scale industrial influence areas, the results of heavy metal source analysis can become more accurate and detailed by incorporating regional treatment, and more reasonable suggestions can be provided for regional enterprise management and soil pollution control decision making.

Soil acidification, caused by intensified fertilizer application and acid deposition, has threatened the sustainability of agricultural ecosystems and soil quality in parts of China since the 1980s. However, little is known about the spatio-temporal change of soil pH in cropland at a large basin scale. Poyang Lake Basin of China was selected as the study area to identify the spatio-temporal change of cropland pH and detect potential soil acidification factors. A total of 507 and 503 topsoil samples were collected in 2012 and 2018, respectively, and methods including one-way analysis of variance (ANOVA), Pearson’s correlation analyses, and Inverse Distance Weighted (IDW) were applied. Results showed that soil pH ranged from 3.96 to 7.95 in 2012 and from 3.34 to 8.19 in 2018, with most samples being acidic (pH &lt, 7) in both sets of data. The two soil datasets showed a significant decline (p &lt, 0.05) of 0.1 pH units over the past six years and several soil samples that exhibited obvious uptrends in the groups of pH &lt, 4.5 and 4.5–5.0 from 2012 to 2018. Overall, the distribution patterns of pH at the two sampling dates were similar, whereas local details of the pH spatial distribution patterns differed. While we found a significant correlation (p &lt, 0.05) between soil pH and aspect, elevation and slope showed no significant correlation with pH. ANOVA showed that pH values in the water density (river or lake network density) range of 6.27–19.94 were significantly higher (p &lt, 0.05) than the other water densities. Large amounts of precipitation with low pH values were found to significantly influence soil pH, whereas N-fertilizer inputs exerted limited effects on soil pH over the entire study area. These findings provided new insights on soil acidification assessment and potential factor detection at the basin scale.

Mining is a common industrial activity and significant source of soil heavy metal (HM) pollution. However, nearly all studies on the effects of mining activities on soil environmental quality have entailed field monitoring of small regions or bibliometric analyses. This study therefore investigated the pollution of surface soils surrounding 135 large opencast coal mining pits in China. A total of 1772 surface soil samples were collected, and the concentrations of eight major HMs were determined. The HM concentrations in this study were relatively lower than the published HM concentrations of coal mine soils from 50 typical Chinese coal mines. However, pollution assessments indicated that Cd, Cu, and As concentrations were concerning. Significant correlations existed between all of the HMs and mining pit area (p 0.01), as well as between the Pb and Zn concentrations and direction (p 0.05). Climate conditions had large influences on the HM concentrations. The concentrations of all studied HMs, except for Ni, were highest in Anthrosols and lowest in hydromorphic soils. The concentrations of all HMs, except for Hg, in land use types showed a descending trend of cultivated land garden plot grassland. Significantly negative correlations (p 0.01) between all HM concentrations and elevation were observed. Cr, Zn, and Ni were significantly and positively correlated with the slope, and no HMs, except Cr, showed significant correlations with the parcel area. This paper provides insights for the policymakers regarding soil pollution control and management strategies near coal mine pits.

With rapid economic development and continuous population growth, several important cities in China suffer serious air pollution, especially in the Beijing-Tianjin-Hebei economic developing area. Based on the daily air pollution index (API) and surface meteorological elements in Beijing, Tianjin, and Shijiazhuang (the capital of Hebei province) from 2001 to 2010, the relationships between API and meteorological elements were analyzed. The statistical analysis focused on the relationships at seasonal and monthly average scales, on different air pollution grades and air pollution processes. The results revealed that the air pollution conditions in the 3 areas gradually improved from 2001 to 2010, especially during summer; the worst conditions in air quality were recorded in Beijing in spring due to the influences of dust, and in Tianjin and Shijiazhuang in winter due to household heating. Meteorological elements exhibited different influences on air pollution, showing similar relationships between API in monthly averages and 4 meteorological elements (i.e., the average, maximum, and minimum temperatures; maximum air pressure; vapor pressure; and maximum wind speed), whereas the relationships on a seasonal average scale demonstrated significant differences. Compared with seasonal and monthly average scales of API, the relation coefficients based on different air pollution grades were significantly lower, whereas the relationship between API and meteorological elements based on air pollution processes reduced the smoothing effect due to the average processing of seasonal and monthly API and improved the accuracy of the results. Finally, statistical analysis of the distribution of pollution days in different wind directions indicated the directions of extreme and maximum wind speeds that mainly influence air pollution, representing valuable information that could support the definition of air pollution control strategies through the identification of the regions (and the located emission sources) where the implementation of emission reduction actions should be focused. Integr Environ Assess Manag 2018;14:710-721. © 2018 SETAC.

The fully coupled online air quality model WRF/chem was used to investigate the aerosol-radiation interaction and aerosol-cloud interaction on the regional meteorological factors over China in 2006.The aerosol-radiation interaction and aerosol-cloud interaction of aerosols influence the various regional meteorological factors in the worst aerosol-polluted regions of China. Domain-wide monthly-mean over all day and night hours incoming solar radiation decreased by –11.03 W/m2, –9.84 W/m2, –5.84 W/m2 and –12.37 W/m2; temperature at 2 meters (T2) decreased by –0.22°C, –0.12°C, –0.06°C and –0.24°C; Planetary boundary layer (PBL) height decreased by –16.44 m, –15.90 m, –5.48 m and –31.59 m in January, April, July and October, respectively. The values of the monthly-mean incoming solar radiation, T2 and PBL height had greater decreases in east China. Due to aerosol feedbacks, a slight increase of the monthly-mean precipitation occurred in southern and south-eastern China. The aerosol-radiation interaction and aerosol-cloud interaction of aerosols were compared for the United States (U.S.) continent, Europe, India and this study. Due to the higher aerosol load in China, the monthly-mean incoming solar radiation, T2 and PBL height exhibited greater decreases in China than in the U.S. continent and in Europe. Aerosol extinction was the dominant effect on the incoming solar radiation for either cloudless or cloudy weather conditions in China, but aerosol extinction was only apparent during cloudless weather in Europe. In India, the incoming solar radiation decreased by –20 W/m2 or more in the most aerosol polluted area, which is close to the value of decrease determined in China.

In this study, a hybrid approach of combining numerical prediction with statistical analysis was proposed to forecast high-PM_10 (aerosol particle with aerodynamic diameter less than 10μm) concentration events in Beijing, China. This approach was used to forecast the daily PM_10 in Beijing from January 1 to December 30, 2013. The WRF-CMAQ modeling system was also applied to simulate Beijing’s PM_10 in the same period. The performance of the two methods was then assessed according to the mean bias (MB), normalized mean bias (NMB), normalized mean gross error (NME), mean normalized bias (MNB), mean normalized gross error (MNE), and root mean square error (RMSE). The results demonstrate that both methods perform well during low-PM10 concentration periods (PM_10 concentration ＜ 250μg/m^3), the MB, NMB, NME, MNB, MNE and RMSE for hybrid approach during low-PM10 concentration periods were 26.15, 24.88%, 41.94%, 43.23%, 56.35% and 61.67, respectively. The MB, NMB, NME, MNB, MNE and RMSE for CMAQ during low-PM_10 concentration periods were -6.04, 57.47%, 41.49%, 21.52%, 55.64% and 60.11, respectively. While the MB, NMB, NME, MNB, MNE and RMSE for CMAQ during high-PM10 concentration periods (PM10 concentration ≥250μg/m^3) were -162.87, -50.37%, 50.37%, -49.86%, 49.86% and 175.93, respectively. The MB, NMB, NME, MNB, MNE and RMSE for hybrid approach during high-PM10 concentration periods were -30.3, -9.37%, 23.21%, -8.21%, 24.25% and 97.37, respectively. The hybrid approach shows significant improvement in accuracy during high-PM_10 concentration periods.

The human population is both an emitter and receptor of metals. This study aims to clarify how the relationship of metals and metalloids to human populations influences their source characterization and health risk, based on metal concentrations in 298 soil samples in the Pearl River Delta (PRD) and the corresponding zip-code level population. Nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), and lead (Pb), but not chromium (Cr) and arsenic (As), were significantly correlated with population (p0.01), suggesting potential anthropogenic sources. A principal component analysis (PCA) revealed three factors (i.e., F1, F2, and F3) contributing to metal levels in the PRD: (1) metal transport from rivers (F1), which explained the high levels of Cr, Ni, Cu, Zn, As, and Cd in downstream areas; (2) industrial sources (F2), mainly contributing to Ni, Cu, Zn, Cd, Hg, and Pb; and (3) natural and agricultural sources (F3), mainly contributing to As and Pb. F2 was significantly correlated with population, while F3 was not, indicating that an analysis of the correlation with population could be used to identify industrial sources of metals. Compared with directly calculated risks, the population-weighted non-carcinogenic and carcinogenic risks were increased by 4.2-4.9% and 7.7-9.2%, respectively. A unit increase in the concentration of industrial metals led to higher extra risks than a corresponding increase in natural metals due to the proximity to human populations.

Estimation of wind erosion rates of Mongolian Plateau by using 137Cs tracing technique Wind erosion is one of the major environmental problems in semi-arid and arid regions. Here we established a transect from northwest (Tariat, Mongolia) to southeast (Xilingol, Inner Mongolia of China) across the Mongolian Plateau, and selected eight sampling sites along the transect. We then estimated the soil wind erosion rates by using the 137Cs tracing technique and examined their spatial dynamics. In the Mongolia section (from Tariat to Sainshand), the wind erosion rate increased gradually with vegetation type and climatic regimes; the wind erosion process was controlled by physical factors such as annual precipitation and vegetation coverage, etc. While in the China section (Inner Mongolia), the wind erosion rates of Xilinhot, Zhengxiangbai Banner and Taipusi Banner were thrice as much as those of Bayannur of Mongolia, although these four sites were all dominated by typical steppe. Besides the physical factors, higher population density and livestock carrying level should be responsible for the higher wind erosion rates in these regions of Inner Mongolia.

The most serious environmental problems of the Mongolian Plateau are land degradation and sand storms caused by wind erosion, but the evaluation of wind erosion at regional scales has been a difficult process in wind erosion research. In this study, fuzzy c-means clustering (FCM) was used to assess the spatial pattern of wind erosion hazard on the Mongolian Plateau. By fuzzy clustering four main wind erosion factors (vegetation cover, average degree of land surface relief, degree of soil dryness and intensity of wind energy), wind erosion hazard was classified into six grades. Results show that FCM can effectively integrate related information between wind erosion and environmental factors, which provides the basis for predictive mapping of wind erosion hazard. Spatial patterns of wind erosion hazard indicate a gradual trend of increasing hazard in the Mongolian Plateau from east to west. Similar patterns were also found in NDVI and soil dryness, indicating that soil moisture and vegetation are the most important factors in the formation of wind erosion hazard. In addition, the distribution of different levels of wind erosion hazard is basically consistent with the regional distribution of landscape vegetation types in the Mongolian Plateau.

Wind erosion is one of the major factors of land degradation in the typical steppe region, northern Mongolian Plateau. Using 137Cs tracing technique, we estimated the wind erosion rates of different pastures and abandoned farmland at Bayannur and Karakorum in Mongolia. The pastures and cutting grassland at Bayannur were slightly eroded by wind, with the rates of 64.58–169.07 t·km−2·a−1. The abandoned farmland in Karakorum, however, was strongly eroded by wind, with annual surface soil loss of 4.05 mm·a−1, and wind erosion rates up to 6723.06 t·km−2·a−1. The total loss of surface soil due to wind erosion has been 17.4 cm since the cultivation of the steppe land in the 1960s. The wind erosion rate at the abandoned farmland was much higher than that at the typical steppe sites, showing that the cultivation led to serious wind erosion in the typical steppe region, northern Mongolian Plateau. By contrast, traditional livestock grazing resulted in less disturbance to the surface soil, and did not induce to devastating wind erosion, which plays an important role in maintaining the stability of the steppe ecosystem in the northern Mongolian Plateau.

Wind erosion is one of the major environmental problems in semi-arid and arid regions. Here we established the Tariat-Xilin Gol transect from northwest to southeast across the Mongolian Plateau, and selected seven sampling sites along the transect. We then estimated the soil wind erosion rates by using the 137Cs tracing technique and examined their spatial dynamics. Our results showed that the 137Cs inventories of sampling sites ranged from 265.63±44.91 to 1279.54±166.53 Bq·m−2, and the wind erosion rates varied from 64.58 to 419.63 t·km−2·a−1 accordingly. In the Mongolia section of the transect (from Tariat to Sainshand), the wind erosion rate increased gradually with vegetation type and climatic regimes; the wind erosion process was controlled by physical factors such as annual precipitation and vegetation coverage, etc., and the impact of human activities was negligible. While in the China section of the transect (Inner Mongolia), the wind erosion rates of Xilin Hot and Zhengxiangbai Banner were thrice as much as those of Bayannur of Mongolia, although these three sites were all dominated by typical steppe. Besides the physical factors, higher population density and livestock carrying level should be responsible for the higher wind erosion rates in these two regions of Inner Mongolia.

This paper establishes a natural-factor database on the basis of researching the literature and considering the availability of data, using remote-sensing data and meteorological observation data, and employs the Fuzzy Clustering and expert knowledge to establish an assessment model of wind erosion hazard to assess the wind erosion hazard of Erenhot-Zhangjiakou. The result shows: the trend of the wind erosion hazard in Erenhot-Zhangjiakou is an increasing hazard from southeast to northwest, which is consistent with environmental and climate conditions; the area of severe hazard and intense hazard is 1.80×104 km2 and 7.58×104 km2 respectively. It takes up the fifty-six percentage of total area, and indicates that the wind erosion has been the serious environmental problem.

Wind erosion is one of the major environmental problems in semi-arid and arid regions. Here we established a transect from northwest (Tariat, Mongolia) to southeast (Xilingol, Inner Mongolia of China) across the Mongolian Plateau, and estimated the soil wind erosion gradient patterns by using the 137Cs tracing technique. In the Mongolia section, the wind erosion rate increased gradually with vegetation type and climatic regimes, controlled by physical factors such as annual precipitation and vegetation coverage, etc. While in the Inner Mongolia section, the wind erosion rates were thrice as much as those of Bayannur of Mongolia. Besides the physical factors, higher population density and livestock carrying level should be responsible for the higher wind erosion rates in Inner Mongolia.

Soil wind erosion is the primary process and the main driving force for land desertification and sand-dust storms in arid and semi-arid areas of Northern China. Many researchers have paid more attention to this issue. This paper select Inner Mongolia autonomous region as the research area, quantify the various indicators affecting the soil wind erosion, using the GIS technology to extract the spatial data, and construct the RBFN (Radial Basis Function Network) model for assessment of wind erosion hazard. After training the sample data of the different levels of wind erosion hazard, we get the parameters of the model, and then assess the wind erosion hazard. The result shows that in the Southern parts of Inner Mongolia wind erosion hazard are very severe, counties in the middle regions of Inner Mongolia vary from moderate to severe, and in eastern are slight. The comparison of the result with other researches shows that the result is in conformity with actual conditions, proving the reasonability and applicability of the RBFN model.

In the research of large-scale opencast coal mine land reclamation and ecological restoration, the processed data has many types, and the amount of information is huge, while the data attribute and topology relationship are complicated, and the information with large temporal and spatial changes is involved with lots of structural and nonstructural problems. Taking PingShuo opencast mine area as a example, based on the characteristics of land reclamation and ecological restoration engineering and the demands of scientific data management The information involved with land destruction, landform reshape, soil reconstruction, vegetation reconstruction, social economy and land utilization etc was analyzed and studied. And the physical and logical independence of land reclamation and ecological restoration data were realized based on the opencast mine land reclamation database which include about 200 pieces of information; Using the software of Microsoft SQL Server 2000 and VB 6.0, the land reclamation and ecological restoration information system has been studied and developed systematically. The paper introduces the whole design, database design and technical main points of the system. The system improves the indispensable condition for the scientific decision, tests demonstration, popularization and application of land reclamation and founded bases for the more application of GIS, ES in the work of opencast mine area land reclamation and ecological restoration.

Based on the GLO-PEM simulated data, net primary productivity (NPP) and its spatiotemporal patterns in Loess Plateau were studied from 1981 to 2000. Our research indicated that the distribution of annual NPP in Loess Plateau was obviously different from east to west and from south to north. The average of annual total NPP is 0.15PgC, with an annual increasing rate of 0.01%. NPP decreased in most parts of Loess Plateau, with the largest decrease in the southeast of Shanxi Province and northeast of Loess Plateau, But it increased in the area along the boundary between Shaanxi Province, Inner Mongolia Province and Lanzhou Basin in the west of Loess Plateau, The early 1990s (1991-1995) is the time with fastest NPP increase. The variation of NPP is different seasonally. It decreased mostly in winter, with an annual rate of 0.57%, and increased with an annual rate of 0.51% from April to May.