Cadmium source identification in soils and high-risk regions predicted by geographical detector method

Zhao, Yinjun; Deng, Qiyu; Qing, Lin; Zeng, Changyu; Cong, Zhen

doi:10.1016/j.envpol.2020.114338

Cited by 74 publications

(29 citation statements)

References 38 publications

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“…Meanwhile, the results of enrichment factor, which eliminates the effect of the geological background and reflects the enrichment characteristic of metals along soil profile, further confirm that, except for Cd, the trace metals in the soils of most mountains were determined by the soil parent materials at the location. This is also in agreement with other studies, which found that the local geological background determined the distribution of trace metals in soils (Huang et al, 2019;Hou et al, 2020;Zhao et al, 2020).…”

Section: Potential Drivers Of Trace Metal Accumulation In the Mountain Soilssupporting

confidence: 93%

Trace metal contamination in soils from mountain regions across China: spatial distribution, sources, and potential drivers

et al. 2021

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Trace metal contamination in soils is a threat with an uncertain limit to maintain planet safety, and the issue of trace metal contamination in mountain soils is still of low concerned. In this study, we assessed the contamination of six trace metals (Cd, Cr, Cu, Ni, Pb, and Zn) in mountain soils across China and deciphered the potential drivers of their spatial distribution. The results showed that concentrations of Cd and Pb decreased significantly with soil depth, and their concentrations were markedly higher in northwest, south, and southwest China than elsewhere. Among the metals, Cd was the priority for control with moderate to heavy contamination, followed by Pb, whereas the other metals did not show evident contamination. The altitudinal pattern and isotopic tracing revealed that the significant enrichment and marked contamination of Cd and Pb in surface soils were primarily attributed to deposition through long-range transboundary atmospheric transport and condensation. Ore mining, nonferrous smelting, and coal and fuel combustion were identified as primary anthropogenic sources of the Cd and Pb. Soil organic matter content, pH, and soil forming processes directly determined the accumulation of trace metals in the soils, and orographic effects, including local climate, vegetation composition, and canopy filtering, regulated the spatial distribution of the metals. This study highlights the significance of soil Cd contamination in mountains, which are considered of low concern, and suggests that long-term monitoring of trace metal contamination is necessary to improve biogeochemical models that evaluate the responses of the mountain critical zone to future human-and climate-induced environmental changes.

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Section: Potential Drivers Of Trace Metal Accumulation In the Mountain Soilssupporting

confidence: 93%

Trace metal contamination in soils from mountain regions across China: spatial distribution, sources, and potential drivers

et al. 2021

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“…Combined with the results of the PMF model analysis, it can be seen that the long-term accumulation of Cd, Pb and As in the soil should be taken seriously because of the industrial waste discharged by the mining industry, with contribution rates of 87.7, 88.5 and 62.5%, respectively. This result is consistent with those from related studies [10,[46][47][48]. Similarly, fertilizer usage and agrotype were the most significant factors affecting Hg and Cr, with contribution rates of 66 and 90.7%, respectively.…”

Section: Qualitative Identification Of Pollution Sourcessupporting

confidence: 92%

“…This type of model does not rely on the analysis of the chemical composition of the pollution source, the migration and transformation pathways of the pollutants do not need to be specified, and the data are relatively easy to obtain and realize [7][8][9]. Commonly used receptor models include chemical mass balance (CMB), principal component analysis/multilinear regression (PCA-MLR), positive matrix factorization (PMF) and UNMIX models [10][11][12]. However, the judgement of the results of receptor models is highly subjective, mostly relying on previous experience and expert assessment, and the analytical results are difficult to verify [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Identification of Soil Heavy Metal Sources in a Large-Scale Area Affected by Industry

Shi

Yang

et al. 2021

Sustainability

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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.

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“…The geographical detector model (GDM) proposed by Wang [24] can estimate the linear, nonlinear, and interactive influence of explanatory variables on the target variable based on the coherence of their spatial distribution pattern. The GDM has been widely used in soil science [25][26][27][28], ecology [29][30][31][32], meteorology [33][34][35], public health [36][37][38][39][40] and other fields. In this study, the GDM was used to identify the primary factors influencing SOM in the black soil zone of northeast China.…”

Section: Introductionmentioning

confidence: 99%

A Quantitative Analysis of Factors Influencing Organic Matter Concentration in the Topsoil of Black Soil in Northeast China Based on Spatial Heterogeneous Patterns

Gao

et al. 2021

IJGI

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Black soil is fertile, abundant with organic matter (OM) and is exceptional for farming. The black soil zone in northeast China is the third-largest black soil zone globally and produces a quarter of China’s commodity grain. However, the soil organic matter (SOM) in this zone is declining, and the quality of cultivated land is falling off rapidly due to overexploitation and unsustainable management practices. To help develop an integrated protection strategy for black soil, this study aimed to identify the primary factors contributing to SOM degradation. The geographic detector, which can detect both linear and nonlinear relationships and the interactions based on spatial heterogeneous patterns, was used to quantitatively analyze the natural and anthropogenic factors affecting SOM concentration in northeast China. In descending order, the nine factors affecting SOM are temperature, gross domestic product (GDP), elevation, population, soil type, precipitation, soil erosion, land use, and geomorphology. The influence of all factors is significant, and the interaction of any two factors enhances their impact. The SOM concentration decreases with increased temperature, population, soil erosion, elevation and terrain undulation. SOM rises with increased precipitation, initially decreases with increasing GDP but then increases, and varies by soil type and land use. Conclusions about detailed impacts are presented in this paper. For example, wind erosion has a more significant effect than water erosion, and irrigated land has a lower SOM content than dry land. Based on the study results, protection measures, including conservation tillage, farmland shelterbelts, cross-slope ridges, terraces, and rainfed farming are recommended. The conversion of high-quality farmland to non-farm uses should be prohibited.

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Cadmium source identification in soils and high-risk regions predicted by geographical detector method

Cited by 74 publications

References 38 publications

Trace metal contamination in soils from mountain regions across China: spatial distribution, sources, and potential drivers

Trace metal contamination in soils from mountain regions across China: spatial distribution, sources, and potential drivers

Identification of Soil Heavy Metal Sources in a Large-Scale Area Affected by Industry

A Quantitative Analysis of Factors Influencing Organic Matter Concentration in the Topsoil of Black Soil in Northeast China Based on Spatial Heterogeneous Patterns

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