Source apportionment of heavy metals in agricultural soil based on PMF: A case study in Hexi Corridor, northwest China.

Hexi Corridor is the most important base of commodity grain and producing area for cash crops. However, the rapid development of agriculture and industry has inevitably led to heavy metal contamination in the soils. Multivariate statistical analysis, GIS-based geostatistical methods and Positive Matrix Factorization (PMF) receptor modeling techniques were used to understand the levels of heavy metals and their source apportionment for agricultural soil in Hexi Corridor. The results showed that the average concentrations of Cr, Cu, Ni, Pb and Zn were lower than the secondary standard of soil environmental quality; however, the concentrations of eight metals (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn) were higher than background values, and their corresponding enrichment factor values were significantly greater than 1. Different degrees of heavy metal pollution occurred in the agricultural soils; specifically, Ni had the most potential for impacting human health. The results from the multivariate statistical analysis and GIS-based geostatistical methods indicated both natural sources (Co and W) and anthropogenic sources (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn). To better identify pollution sources of heavy metals in the agricultural soils, the PMF model was applied. Further source apportionment revealed that enrichments of Pb and Zn were attributed to traffic sources; Cr and Ni were closely related to industrial activities, including mining, smelting, coal combustion, iron and steel production and metal processing; Zn and Cu originated from agricultural activities; and V, Ti and Mn were derived from oil- and coal-related activities.

Guan Q ，Wang F ，Xu C ，Pan N ，Lin J ，Zhao R ，Yang Y ，Luo H ... -  《-》

Quantitative source apportionment of heavy metals in cultivated soil and associated model uncertainty.

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.

Chai L ，Wang Y ，Wang X ，Ma L ，Cheng Z ，Su L ，Liu M ... -  《-》

Source identification and spatial distribution of arsenic and heavy metals in agricultural soil around Hunan industrial estate by positive matrix factorization model, principle components analysis and geo statistical analysis.

Characterizing the distribution and defining potential sources of arsenic and heavy metals are the basic preconditions for reducing the contamination of heavy metals and metalloids. 71 topsoil samples and 61 subsoil samples were collected by grid method to measure the concentration of cadmium (Cd), arsenic (As), lead (Pb), copper (Cu), zinc (Zn), nickel (Ni) and chromium (Cr). Principle components analysis (PCA), GIS-based geo-statistical methods and Positive Matrix Factorization (PMF) were applied. The results showed that the mean concentrations were 9.59 mg kg-1, 51.28 mg kg-1, 202.07 mg kg-1, 81.32 mg kg-1 and 771.22 mg kg-1 for Cd, As, Pb, Cu and Zn, respectively, higher than the guideline values of Chinese Environmental Quality Standard for Soils; while the concentrations of Ni and Cr were very close to recommended value (50 mg kg-1, 200 mg kg-1), and some site were higher than guideline values. The soil was polluted by As and heavy metals in different degree, which had harmful impact on human health. The results from principle components analysis methods extracted three components, namely industrial sources (Cd, Zn and Pb), agricultural sources (As and Cu) and nature sources (Cr and Ni). GIS-based geo-statistical combined with local conditions further apportioned the sources of these trace elements. To better identify pollution sources of As and heavy metals in soil, the PMF was applied. The results of PMF demonstrated that the enrichment of Zn, Cd and Pb were attributed to industrial activities and their contribution was 24.9%; As was closely related to agricultural activities and its contribution was 19.1%; Cr, a part of Cu and Ni were related to subsoil and their contribution was 30.1%; Cu and Pb came from industry and traffic emission and their contribution was 25.9%.

Zhang X ，Wei S ，Sun Q ，Wadood SA ，Guo B ... -  《-》

Spatial distribution and source identification of heavy metals in surface soils in a typical coal mine city, Lianyuan, China.

In this study, we investigated the pollution degree and spatial distribution of heavy metals and determined their sources in topsoil in a typical coal mine city, Lianyuan, Hunan Province, China. We collected 6078 soil surface samples in different land use types. And the concentrations of Zn, Cd, Cu, Hg, Pb, Sb, As, Mo, V, Mn, Fe and Cr were measured. The average contents of all heavy metals were lower than their corresponding Grade II values of Chinese Soil Quality Standard with the exception of Hg. However, average contents of twelve heavy metals, except for Mn, exceeded their background level in soils in Hunan Province. Based on one-way analysis of variance (ANOVA), the contents of Cu, Zn, Cd, Pb, Hg, Mo and V were related to the anthropogenic source and there were statistically significant differences in their concentrations among different land use patterns. The spatial variation of heavy metal was visualized by GIS. The PMF model was used to ascertain contamination sources of twelve heavy metals and apportion their source contributions in Lianyuan soils. The results showed that the source contributions of the natural source, atmospheric deposition, industrial activities and agricultural activities accounted for 33.6%, 26.05%, 23.44% and 16.91%, respectively.

Liang J ，Feng C ，Zeng G ，Gao X ，Zhong M ，Li X ，Li X ，He X ，Fang Y ... -  《-》

Risk Assessment and Source Identification of Toxic Metals in the Agricultural Soil around a Pb/Zn Mining and Smelting Area in Southwest China.

Mining and smelting activities are the primary sources of toxic metal pollution in China. The purpose of this study was to investigate the pollution risk and identify sources of metals in the arable soil of a Zn/Pb mining and smelting district located in Huize, in Southwest China. Topsoil (346) and profile (three) samples were collected and analyzed to determine the total concentrations of eight toxic elements (Cd, Hg, As, Pb, Cr, Cu, Zn and Ni). The results showed that the mean Cd, Hg, As, Pb, Cr, Cu, Zn and Ni concentrations were 9.07, 0.37, 25.0, 512, 88.7, 239, 1761 and 90.3 mg/kg, respectively, all of which exceeded both the Huize and Yunnan soil background levels. Overall the topsoil was quite acidic, with a mean pH of 5.51. The mean geoaccumulation index () revealed that the pollution level was in the order of Pb > Zn > Cd > Hg > As > Ni > Cu > Cr. The ecological risk index () indicated that there were serious contamination risks for Cd and Hg, high risk for Pb, moderate risk for As, and Cd and Hg were the dominant contributors to the high combined ecological risk index () with a mean parameter of 699 meaning a serious ecological risk. The Nemerow pollution index () showed that 99.1% of soil samples were highly polluted or worse. Horizontally, high concentrations of Cd, Hg, As, Pb and Zn appeared in the north and middle of the study area, while Cr, Cu and Ni showed an opposite trend. Vertically, as the depth increased, Cd, Hg, As, Pb and Zn contents declined, but Cr, Cu and Ni exhibited an increasing trend. The mobilities of the metals were in the order of Zn > Cd > Hg > As > Pb. Horizontal and vertical distribution, coupled with correlation analysis, PCA and CA suggested that Cd, Hg, As, Pb and Zn mainly came from the anthropogenic sources, whereas Cr and Ni had a lithogenic origin. The source of Cu was a combination of the presence of parent materials as well as human activities. This study provides a base for the local government to control the toxic metal pollution and restore the soil environment system and an effective method to identify the sources of the studied pollutants.

Wu J ，Long J ，Liu L ，Li J ，Liao H ，Zhang M ，Zhao C ，Wu Q ... -  《-》