Ecological risk assessment and source identification of heavy metal pollution in vegetable bases of Urumqi, China, using the positive matrix factorization (PMF) method

Abstract

Heavy metal pollution is a widespread problem and strongly affects human health through the food chain. In this study, the overall pollution situation and source apportionment of heavy metals in soil (Hg, Cd, As, Pb, Ni, Zn, Cu and Cr) were evaluated using various methods including geo-accumulation index (I geo), potential ecological risk index (RI) and positive matrix factorization combined with Geographical Information System (GIS) to quantify and identify the possible sources to these heavy metals in soils. The results of I geo showed that this farmland top soil moderate contaminated by Hg, other selected elements with noncontamination level. And the average RI in the top soil was 259.89, indicating a moderate ecological risk, of which Hg and Cd attributed 88.87% of the RI. The results of the PMF model showed that the relative contributions of heavy metals due to atmospheric depositions (18.70%), sewage irrigations (21.17%), soil parent materials (19.11%), industrial and residential coal combustions (17.43%) and agricultural and lithogenic sources (23.59%), respectively. Of these elements, Pb and Cd were came from atmospheric deposition. Cr was attributed to sewage irrigations. As was mainly derived from the soil parent materials. Hg originated from industrial and residential coal combustions, and most of the Cu, Zn and Ni, except for Pb, were predominantly derived from agricultural and lithogenic sources. These results are important in considering management plans to control the aggravation of heavy metal pollution and ultimately to protect soil resources in this region. In addition, this study enhances the understanding of heavy metal contamination occurrence in agroecosystem that helps predicting and limiting the potential of heavy metal exposure to people and ecosystem.

Potential Ecological Risk Assessment of Ni, Cu, Zn, Cd, and Pb in Roadside Soils

“…In various studies, this factor is used to determine the degree of environmental risk. So, Kuerban et al (2020) used this index to determine environmental risk. The results showed that the Xinjiang oasis area had a low environmental risk due to the low values of PERI.…”

Ecological and Health Risk Assessment of Trace Metal Pollution in Vegetable Field Soils from the Eastern Nile Delta, Egypt

“…However, the mean concentrations of Cd, Co, Pb and Zn were exceeded their background values, which can demonstrate that the soils of the studied area are polluted with these metals by the anthropogenic activities 23 . In the same line, higher contents of Cd, Pb, Cu, Zn were observed in vegetable elds in China 30 . The main contribution of trace metals to agricultural soils is the use of chemical fertilizers, pesticides and organic fertilizers 5,17,30 .…”

“…In the same line, higher contents of Cd, Pb, Cu, Zn were observed in vegetable elds in China 30 . The main contribution of trace metals to agricultural soils is the use of chemical fertilizers, pesticides and organic fertilizers 5,17,30 . Thus, Cd, Co, Pb and Zn require more attention in the future, and continuous monitoring of the application of agrochemicals in the production of vegetables is recommended to decrease the probable ecological risks caused by these trace metals in soils of the Eastern Nile Delta.…”

Pollution-Induced Food Safety Problem in China: Trends and Policies

“…Data for 2000–2018 are from Zeng et al ( 14 ). Data for 2019–2020 are compiled from Ali et al ( 35 ), Chai et al ( 36 ), Chen et al ( 37 ), Guan et al ( 38 ), Guo et al ( 39 ), Han et al ( 40 ), Hou et al ( 41 ), Hu et al ( 42 ), Huang et al ( 43 ), Jiang and Guo ( 44 ), Jin et al ( 45 ), Jin et al ( 46 ), Lu et al ( 47 ), Lv and Sun ( 48 ), Song et al ( 49 ), Wang et al ( 50 ), Wu et al ( 51 ), Xiao et al ( 52 ), Yang et al ( 53 ), Zhao et al ( 54 ), Zhou et al ( 55 ), Bao et al ( 56 ), Cao et al ( 57 ), Chai et al ( 58 ), Cheng ( 59 ), Duan et al ( 60 ), Guo et al ( 61 ), He et al ( 62 ), Hu et al ( 63 ), Ji et al ( 64 ), Kuerban et al ( 65 ), Li et al ( 66 ), Ma et al ( 67 ), Miao et al ( 68 ), Peng et al ( 69 ), Shi et al ( 70 ), Su and Yang ( 71 ), Sun et al ( 72 ), Tan et al ( 73 ), Tang et al ( 74 ), Wei et al ( 75 ), Xiao et al ( 76 ), Zhang et al ( 77 ), Zhang et al ( 78 ), Zhao et al ( 79 ), Zhuang et al ( 80 ).…”