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| Assessment and source analysis of heavy metals pollution in farmland soil at the field scal |
| Received:August 30, 2021 Revised:December 03, 2021 |
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| KeyWord:heavy metal;pollution evaluation;spatial distribution;speciation;absolute principal component score receptor model |
| Author Name | Affiliation | E-mail | | MU Demiao | College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
Key Laboratory of Original AgroEnvironmental Pollution Prevention and Control, Ministry of Agriculture and Rural Affairs/Tianjin Key Laboratory of Agro-Environment and Agro-Product Safety, Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China | | | CHEN Yanqiu | Plant Protection and Plant Inspection Station, Anning City, Yunnan Province, Anning 650300, China | | | HU Tao | Plant Protection and Plant Inspection Station, Anning City, Yunnan Province, Anning 650300, China | | | LIN Dasong | Key Laboratory of Original AgroEnvironmental Pollution Prevention and Control, Ministry of Agriculture and Rural Affairs/Tianjin Key Laboratory of Agro-Environment and Agro-Product Safety, Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China | | | YANG Zhenglan | Plant Protection and Plant Inspection Station, Anning City, Yunnan Province, Anning 650300, China | | | SUN Yuebing | Key Laboratory of Original AgroEnvironmental Pollution Prevention and Control, Ministry of Agriculture and Rural Affairs/Tianjin Key Laboratory of Agro-Environment and Agro-Product Safety, Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China | sunyuebing@aepi.org.cn |
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| Abstract: |
| A total of 120 surface soil samples were collected in various farmlands at the field scale. Next, absolute principal component score-multiple linear regression(APCS-MLR)and geostatistical analysis were adopted to analyze the spatial distribution and sources of eight contaminating heavy metals(As, Cd, Cu, Cr, Mn, Ni, Pb, and Zn)in the studied area; furthermore, the geo-accumulation index and potential ecological risk index of each heavy metal were calculated to carry out ecological risk assessment. The results showed that the contents of these eight heavy metals in surface soils differed significantly; in particular, the over-limit ratios of the location points of As, Cd, and Cr were 61.83%, 90.83%, and 92.52%, respectively, whereas the heavy metals Zn, Cu, Cr, and Ni mainly existed in the soil in the form of residues, which accounted for more than 80% of the total Zn, Cu, Cr, and Ni contents. The spatial distributions of Cd, Cr, and Cu contents exhibited the following pattern:high concentrations in the southeastern part, intermediate concentrations in the central part, and low concentrations in the northwestern part. Conversely, the spatial distributions of Pb and Zn contents followed the opposite pattern. APCS-MLR modeling revealed that, on the one hand, the heavy metals As, Cr, Cu, and Ni in the study area mainly derived from natural sources, which accounted for 39.34%, 47.32%, 44.53%, and 50.23% of the heavy metal contents derived from all sources, respectively; on the other hand, Pb and Zn mainly derived from industrial activities(accounting for 31.93% and 30.53% of total contents, respectively)and traffic(accounting for 23.36% and 22.17% of total contents, respectively); finally, Cd from agricultural activities accounted for 53.63% of the total Cd content. Soil pH was negatively correlated to the available contents of As, Cd, Cu, and Ni(P<0.01). Analysis of geoaccumulation indices showed that Cr pollution in the soil presented middle and severe levels, followed by Cd pollution; moreover, analysis of ecological hazard indices pointed at Cr and Cd as the main ecologically hazardous elements, with single potential ecological hazard index values ranging from 5.20 to 41.12, and from 11.56 to 113.35, respectively. Altogether, our results reveal relatively serious levels of Cr and Cd pollution in the study area, which entail potential risks; therefore, safe use practices, remediation approaches, and other measures should be adopted to lower the risk level. |
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