Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models

Guan, Qingyu; Zhao, Rui; Pan, Ninghui; Wang, Feifei; Yang, Yanyan; Luo, Haiping

doi:10.1016/j.jclepro.2019.117792

Cited by 144 publications

(63 citation statements)

References 73 publications

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“…A high positive correlation at the 0.01 level is displayed in the group of Cr-Cu (0.787), which indicates that the origin and pathway of emission for this group are likely similar. Another group, Cr-Ni-Cu-Zn-Cd-Pb, shows significant correlations with each other at p < 0.01, especially Cr-Cu The principal component analysis (PCA) method was applied with the SPSS software for identification of the eight HE pollution sources (Guan et al 2019). The Kaiser-Meyer-Olkin (KMO) and Bartlett tests on the logarithmic conversion data of HE concentration showed that the KMO measurement value was 0.806, and the significance level of the Bartlett test was 0.00, which suggests that the data were suitable for further principal component analysis and factor analysis.…”

Section: Identification Of Pollution Sourcesmentioning

confidence: 99%

Spatial distribution of pollution characteristics and human health risk assessment of exposure to heavy elements in road dust from different functional areas of Zhengzhou, China

Wang

Shen

Kang

et al. 2020

Environ Sci Pollut Res

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Road dust from different sources directly contacts the human body and has potential effects on public health. In this study, a total number of 87 road dust samples were collected at 29 sampling sites from five different functional areas (commercial area (CA), residential area (RA), educational area (EA), industrial area (IA), and park area (PA)) in Zhengzhou to study the contamination status, distribution, source identification, ecological risk assessment, and spatial distribution of human health risks due to eight heavy elements. The geo-accumulation index (I geo) and pollution index (PI) revealed that there was very high contamination with Cd and Hg caused by atmospheric deposition, which should be paid special attention. Additionally, the source identification indicated that Cr, Ni, Cu, Zn, Cd, and Pb originate from anthropogenic activities related to traffic, and Hg can originate from medical equipment and agricultural chemicals, while the extremely low level of pollution with As could be explained by geographic sources. Moreover, the calculated ecological risk index values were increased in the order of CA > RA > EA > IA > PA in different functional areas. According to the human health risks of the whole city, children exposed to Pb have the highest health risk, especially for CA and IA, as calculated by the noncarcinogenic hazard index (HI). For adults and children, health risks caused by Cu, Zn, and Pb were higher in the CA, RA, and PA of the downtown area, whereas Cr and Ni had the highest noncarcinogenic exposure risk in northwestern Zhengzhou due to point source pollution. Calculations of the carcinogenic risk (CR) values for Cr, Ni, As, and Cd indicate that the value of Cr is highest (1.17 × 10 −7), especially inside the industrial area (8.55 × 10 −7), which is close to the lower limit of the threshold values (10 −6 to 10 −4). These results can provide a theoretical basis and data support for air treatment, pollution control, and the implementation of public prevention in different functional areas of Zhengzhou.

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Section: Identification Of Pollution Sourcesmentioning

confidence: 99%

Spatial distribution of pollution characteristics and human health risk assessment of exposure to heavy elements in road dust from different functional areas of Zhengzhou, China

Wang

Shen

Kang

et al. 2020

Environ Sci Pollut Res

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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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“…(11)) [19]. (10) (11) ...where ADD i denotes average daily exposure dose by ingestion (ADD ing ), average daily exposure dose by inhalation (ADD inh ), and average daily exposure dose by dermal absorption (ADD drem ), respectively (mg•kg -1 •d -1 ); where RfD i is the homologous reference dose and originates from Table 4 [67] (Table 4). ...where ADD i is the same to Eq.…”

Section: Health Risk Assessment For Risk Elementsmentioning

confidence: 99%

“…The rapid development of urbanization, industrialization and rural intensification have led to the massive emission of toxic risk elements and pollutants [6,7]. What's more, soil resources are facing unreasonable exploitation and utilization, such as overuse of chemical fertilizers and pesticides, unreasonable treatment of industrial gas and waste water, which result in severe environmental pollution [8][9][10]. Soil risk elements are difficult to degrade and can migrate to plants and human bodies through food chains and water supply systems, which cause direct or indirect harm to food safety and human health [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Contamination, Distribution and Health Risk Assessment of Risk Elements in Topsoil for Amusement Parks in Xi’an, China

Guo¹,

Su²,

Lin³

et al. 2020

Pol. J. Environ. Stud.

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The index of geo-accumulation (I geo) and the pollution load index (PLI) were used to assess the pollution level and the U.S. Environmental Protection Agency (EPA) health risk model was implemented to determine the health risk for children. Besides, a geographic information system (GIS) was utilized to map the distribution characteristics of risk elements contents. The results showed that: (1) the mean content of Mn was the highest in each park. Besides, the mean content of all risk elements except As exceeded the background value of Shaanxi in each park. (2) The I geo of Co was obviously higher than other elements in each park and the highest (4.07) content occurred in the Xing Qing Park (XQP). The pollution condition of the Urban Sports Park (USP) was the most serious among the four parks. (3) The children were more susceptible to risk elements pollution through oral intake. (4) The hazard indices (HI) of non-carcinogenic risk (NCR) were within the safe range (HI = 1) and the carcinogenic risks (CR) of Cr, Ni, As and Co for children were within the receivable range in each park.

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Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models

Cited by 144 publications

References 73 publications

Spatial distribution of pollution characteristics and human health risk assessment of exposure to heavy elements in road dust from different functional areas of Zhengzhou, China

Spatial distribution of pollution characteristics and human health risk assessment of exposure to heavy elements in road dust from different functional areas of Zhengzhou, China

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

Contamination, Distribution and Health Risk Assessment of Risk Elements in Topsoil for Amusement Parks in Xi’an, China

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