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[Display omitted] • Various indices and PMF were used to explore contaminations, health risk and sources of metals heavy metal. • 86.91% of sampling points in the soil belong to moderate, high and extreme ecological risks. • Carcinogenic and non-carcinogenic risks of heavy metals to the human body are insignificant. • The four main sources mainly include natural sources, transportation sources, agricultural sources and industrial sources. For the purpose of pollution assessment, human health risk assessment and quantitative source apportionment of heavy metals in cultivated soils, a total of 382 cultivated soil samples were collected from cultivated of Lanzhou in September 2019. Various indices, including pollution index (PI), Nemerow integrated pollution index (NIPI) and potential ecological risk index (RI) were used to analyze the pollution levels caused by heavy metals. Human health risk assessment, geographic information system (GIS) and positive matrix factorization (PMF) receptor modeling were employed to analyze the human health risk and source of heavy metals. The results showed that mean concentrations of Hg exceeded the national soil pollution risk screening value (GB 15618–2018). Spatially, except Cr in the study area, Pb, Cd, As, Cu, Zn and Ni have high value in Chengguan and Qilihe. Hg has high values in study areas outside Chengguan, Anning and Qilihe. The Nemerow integrated pollution index showed that the moderate and severe samples sites were 37.70% and 3.66%, respectively. The potential ecological risk indicates that most of the sampling sites are moderate risks. According to the health risk assessment results, the carcinogenic and non-carcinogenic risks of heavy metals to the human body are insignificant. Based on positive matrix factorization, there are four main sources of eight heavy metals. Pb, Cd, Zn and Ni were attributed to traffic sources; Hg were closely related to agricultural activities and medical treatment; Cr, Cu and Ni originated from natural source, As was derived from industrial activity. In this study enhance understanding of the pollution levers of heavy metals in Lanzhou cultivated soils, and also serves as reference for pollution source apportionment in other regions. [ABSTRACT FROM AUTHOR]

To estimate spatial distribution, source analysis and uncertainty of heavy metals (Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni) based on geographic information system (GIS), positive matrix factorization model (PMF) and bootstrap (BS) using 382 soil samples collected from cultivated soils in Lanzhou. The mean contents of Cd, Hg, Cu, Zn and Ni were high as 1.7,1.7, 2.1, 1.5 and 1.3 times local background values, mean contents of Pb, Cr and As were lower than local background values. However, the mean contents of eight heavy metals were lower environmental quality risk control standard for soil contamination of agricultural soil. Proportions of four sources were identified: Cr was predominantly contributed by natural sources (29.14%), Cu, Zn and Ni was primarily from industrial sources (25.26%), Hg and As were mainly of agricultural sources (27.49%), Pb and Cd mainly came from traffic source and smelting-related activities (18.09%). Uncertainties analysis contained three aspects: bootstrap runs, factor contributions in the PMF solution, and coefficient of variation (CV) values. By combining the four pollution source factors with bootstrap runs, the accuracy of the four pollution source factors were reliable based on PMF model. The median values in the BS runs was considered the most true factor contribution, and the 5th–95th quartile interval represents the variability of each factor, Factor 4 (traffic source) R2 was 0.70 and lower variability. The highest CV value usually means a significantly deviation degree. In this study, the CV values of Cr in Factor 1, Cu, Zn, and Ni in Factor 2, Hg, and As in Factor 3, Pb, and Cd in Factor 4 were lower, indicates a lower deviation degree. and with the lowest content among heavy metals usually was also with the greatest uncertainties. In this study improves understanding of the reduction of heavy metal pollution in cultivated soil, and also serves as reference for pollution source apportionment in other regions. [Display omitted] • Four sources were identified and natural sources and agricultural sources were the largest. • Combination with Bootstrap can help improve the accuracy of the four pollution source factors. • The determination coefficient (R2) of the four factors was between 0.52 and 0.70. • The lowest concentrations heavy metals usually became with higher uncertainties. [ABSTRACT FROM AUTHOR]