Multivariate receptor models and robust geostatistics to estimate source apportionment of heavy metals in soils

Lv, Jianshu

doi:10.1016/j.envpol.2018.09.147

Cited by 251 publications

(74 citation statements)

References 63 publications

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“…In particular, Cd, Cu and Hg were 1.81, 1.80 and 1.63 times higher than the background values, respectively, suggesting that the topsoil, which is affected by human activities, was enriched by these potentially toxic elements. Compared with the surrounding cities with developed industry and mining, such as Rizhao [ 27 ], Guangrao [ 28 ] and Ju County [ 29 ], it was found that the average value of potentially toxic elements in soils had the above similar characteristics as in Longkou, and Cd and Hg were also considered to be the most risky. To further evaluate the enrichment degree of potentially toxic elements, the index of geo-accumulation (I geo ) was calculated using Muller’s equation [ 40 ], which indicated that the soil ranged from not contaminated to moderately contaminated with respect to Cd, Cu, and Hg, which were ranked as Cd>Hg>Cu, and the soil was not contaminated with the other elements.…”

Section: Resultsmentioning

confidence: 99%

“…A total of 138 soil samples were collected in the summer of 2017 based on the grid layout sample point method [ 27 – 29 ]. Sample sites were selected according to a sampling density of less than 2 km based on Landsat images, and each sample consisted of a mixture of five subsamples collected from five spots across an area of approximately 30 m 2 .…”

Section: Methodsmentioning

confidence: 99%

“…Kriged maps can characterize the hotspots and outlines. Previous studies have successfully used the spatial variation and spatial distribution of potentially toxic elements in soils to identify risk areas, which have been superimposed with land use maps to predict potentially toxic element pollution sources [ 27 – 29 ]. However, prior studies have rarely explored the spatial variation information of factor variables and the superposition information of kriged maps that form factor variables and potentially toxic elements, which contain important information for source apportionment.…”

Section: Introductionmentioning

confidence: 99%

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Source apportionment of potentially toxic elements in soils using APCS/MLR, PMF and geostatistics in a typical industrial and mining city in Eastern China

Cao

Zhang³

et al. 2020

PLoS ONE

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Source apportionment of potentially toxic elements in soils is a critical step for devising soil sustainable management strategies. However, misjudgment or imprecision can occur when traditional statistical methods are applied to identify and apportion the sources. The main objective of the study was to develop a robust approach composed of the absolute principal component score/multiple linear regression (APCS/MLR) receptor model, positive matrix factorization (PMF) receptor model and geostatistics to identify and apportion sources of soil potentially toxic elements in typical industrial and mining city, eastern China. APCS/ MLR and PMF were applied to provide robust factors with contribution rates. The geostatistics coupled with the variography and kriging methods was used to present factors derived from these two receptor models. The results indicated that mean concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn exceeded the local background levels. Based on multivariate receptor models and geostatistics, we determined four sources of eight potentially toxic elements including natural source (parent material), agricultural practices, pollutant emissions (industrial, mining and traffic) and the atmospheric deposition of coal combustion, which accounted for 68%, 12%, 12% and 9% of the observed potentially toxic element concentrations, respectively. This study provides a reliable and robust approach for potentially toxic elements source apportionment in this particular industrial and mining city with a clear potential for future application in other regions.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Source apportionment of potentially toxic elements in soils using APCS/MLR, PMF and geostatistics in a typical industrial and mining city in Eastern China

Cao

Zhang³

et al. 2020

PLoS ONE

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“…Through this research, we discovered the relationship among the intensity of human activities and the accumulation of PTEs in the sediment core from North Aral Sea, but the specific source of PTEs was not determined. For this, the results of this research may need to be integrated with isotope tracing studies [64][65][66][67], as well as source apportionment models [68][69][70][71] combined with the emission inventory for PTEs in the Aral Sea basin. The correlation coefficients (Table 3) indicate that the significant enrichment in PTEs is related to the significant enhancement in human activities after the 1970s.…”

Section: Discussionmentioning

confidence: 99%

Historical Change and Ecological Risk of Potentially Toxic Elements in the Lake Sediments from North Aral Sea, Central Asia

Liu

Abuduwaili

2020

Applied Sciences

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The Aral Sea has received worldwide attention for the deterioration of its biological and chemical status. The accumulation of potentially toxic elements (PTEs) in the lake sediments reflects changes in the surrounding watershed and represents a potential hazard for the lake ecosystem. In conjunction with existing environmental records from the Aral Sea basin, sedimentary records of PTEs in North Aral Sea covering a short time scale, anno Domini (AD) 1950–2018, were used to reveal historical changes in PTE concentrations and potential risks to lake functioning. The results suggested that the levels of PTEs in lake sediments from North Aral Sea changed abruptly around 1970 AD, which is concurrent with the intensification of human activities within the basin. After 1970 AD, with the exception of As, which remained at unpolluted-to-moderately polluted levels, the geo-accumulation indices of the remaining PTEs studied (V, Cr, Zn, Co, Pb, Ni, Cu and Cd) inferred a moderately polluted status. Before 1970 AD, the total ecological risk was low, but since 1970, the total ecological risk index has exceeded 150, indicating moderate risk. Historical changes in PTE levels of lake sediments from North Aral Sea and their potential ecological risks are reported for the first time. The conclusions provide an important reference for the protection of lake ecosystems and will provide data for regional/global comparisons of environmental change during the Anthropocene.

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“…Such model has been frequently applied to the study of soil heavy metal in recent years. The model can recognize pollution sources by analyzing pollution content in the receptors and then calculating the contribution rate of each source [27][28][29][30][31][32]. Positive matrix factorization (PMF) models are calculated by the source profile and contribution rate, and the fitting is preferable at low content points.…”

Section: Introductionmentioning

confidence: 99%

Source apportionment of soil contamination based on multivariate receptor and robust geostatistics in a typical rural–urban area, Wuhan city, middle China

Zhu

et al. 2020

Open Chemistry

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AbstractIn this study topsoil samples were collected from 57 sites of Dongxihu District which is a typical Chinese urban–rural combination area, to analyze the causes and effects of 6 heavy elements. (Ni, Pb, As, Cu, Cd, and Hg) Pollution of Enrichment factor, multivariate statistics, geostatistics were adopted to study the spatial pollution pattern and to identify the priority pollutants and regions of concern and sources of studied metals. Most importantly, the study area was creatively divided into central urban, semi-urbanized, and rural areas in accordance with the characteristics of urban development and land use. The results show that the pollution degree of potential ecological risk assessment is Hg>Ni>Cu>As>Cd>Pb, and semi-urban regions> city center> rural areas. Results based on the proposed integrated source identification method indicated that As was probably sourced from agricultural sources (33.99%), Pb was associated with atmospheric deposition (50.11%), Cu was related to industrial source 1 (45.97%), Cd was mainly derived from industrial source 2 (42.97%) and Hg come mainly from industrial source 3 (56.22%). The pollution in semi-urban areas in urbanization need more attention.

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Multivariate receptor models and robust geostatistics to estimate source apportionment of heavy metals in soils

Cited by 251 publications

References 63 publications

Source apportionment of potentially toxic elements in soils using APCS/MLR, PMF and geostatistics in a typical industrial and mining city in Eastern China

Source apportionment of potentially toxic elements in soils using APCS/MLR, PMF and geostatistics in a typical industrial and mining city in Eastern China

Historical Change and Ecological Risk of Potentially Toxic Elements in the Lake Sediments from North Aral Sea, Central Asia

Source apportionment of soil contamination based on multivariate receptor and robust geostatistics in a typical rural–urban area, Wuhan city, middle China

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