Source Analysis of Heavy Metal Pollution Using UNMIX and PMF Models in Soils along the Shuimo River in Urumqi, China.

Int J Environ Res Public Health

Department of Environment, College of Ecology and Environment, Xinjiang University, Urumqi 830017, China.

Published: November 2022


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Article Abstract

Eight kinds of heavy metals in soil within 0-2 km from the banks of Shuimo River in Urumqi were analyzed by using an X-ray fluorescence spectrometer and national standard detection methods. Unmix and PMF models are comprehensively used to analyze potential pollutant sources and contribution rates. Soil samples are sampled in three layers of 0-20, 20-40, and 40-60 cm, and each group of sample points in each layer is 5 m, 1 km, and 2 km away from the riverbank, respectively. Only the average concentration of Mn in each layer of soil is lower than the background value, according to the analytical results, while the average concentration of other heavy metals surpasses the background value. The highest proportion of exceeding the background value is Ni in the 40-60 cm soil layer, up to 1.92 times. Unmix and PMF models are used to analyze pollutants' source quantity and contribution rate, respectively. The results show that the two models can identify two pollution sources at the three soil layers, and their contribution rates are similar, and each index of the analysis results of the two models is within the required range of model reliability. By comparing with the Pearson correlation coefficient and distribution map of heavy metal concentration in surface soil, it is concluded that Zn, Pb, Cr, and Cu are mainly from industrial sewage and air pollution from coal combustion, while As, Mn, Ni, and V are mainly from agricultural pollution and light industrial pollution. In future research, it is necessary to investigate the change of heavy metal concentration in detail from the time dimension to further quantitatively calculate the potential pollutant source and contribution rate.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690826PMC
http://dx.doi.org/10.3390/ijerph192214794DOI Listing

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