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Earth science

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Soil science

Heavy metals

Chemistry

Apportionment

Journal of Cleaner Production

Receptor models are, rarely utilized in soil but are often used to identify pollutant sources and quantify their contribution. This paper focuses on the soil in oasis farmland. A geochemical baseline is used to assess the pollution of the soil, and then three models are tentatively utilized to apportion heavy metals and compare the sources, the contributions and the operation effects. Pollution assessment indicated that the farmland soil of Wuwei was lightly contaminated by heavy metals. Source apportionments suggested that atmospheric deposition contributed the most pollution (53.95%–65.35%). The three models supplemented each other, and the grouped principal component analysis/absolute principal component scores (GPCA/APCS) was outstanding. GPCA/APCS and UNMIX suggested that agricultural activities were the prime anthropogenic source (51.06%–61.56%), followed by the combustion of fossil fuels (coal and oil) (27.92%–28.66%) and building materials-related activities source (10.52%–20.29%). Fertilizers and pesticides (67.88%–74.81%) contributed more than traffic emissions (25.19%–32.12%) in agricultural activities. Similar results were acquired via positive matrix factorization (PMF), while industrial activity was the highest individual contributor (29.91%). Therefore, combining these three models was the most effective approach, and more attention should be paid to mitigating the pollution caused by the use of fertilizers and pesticides as well as the industrial activities in Wuwei. The results of this study could provide reference in reduction of heavy metal pollution in farmland soil.

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