Evaluation and Source of Heavy Metal Pollution in Surface Soils in Typical Alpine Agricultural Areas of Qinghai Province

Heavy metal pollution in soils is often the result of multiple genetic sources and action paths. Simple identification of the sources of heavy metals is not enough to provide sufficient information for the control of regional heavy metal pollution. So, it is necessary to quantitatively calculate the relative contribution rate of various emission sources to determine the main pollution sources. The heavy metal contents in the surface soils of the Qinghai—Tibet Plateau (QTP) have a tendency of aggregation, and quantitative analysis of the sources of heavy metals should be emphasized.

To understand the contents, spatial distribution, ecological risk and sources of heavy metals with the surface soils in a typical alpine agricultural area in Qinghai Province.

The surface soil (0-20cm) samples were collected from Zeku County in the eastern Qinghai—Tibet Plateau (QTP). AFS, ICP-MS/OES were used to determine the contents of 10 heavy metals (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn). The contents and spatial distribution of heavy metals in the soils, as well as the comparison with the other typical agricultural soils in plain areas were studied. The level of contamination and ecological risks was analyzed using the enrichment factor (EF), geo-accumulation index (I_geo) and the potential ecological risk index (PERI). The principal component analysis-absolute principal component score-multiple linear regression (PCA-APCS-MLR) receptor model was identified as the potential source of heavy metals for the study area.

(1) The average content of As exceeded the soil environment standard and the national background value. The average contents of Cd, Cr, Cu, Co, Ni, Zn, Pb and Hg were 0.14, 63.15, 23.84, 13.85, 30.65, 74.96, 23.2, and 0.02mg/kg, respectively, that were all far lower than the screening standard of soil environmental quality. Compared with the national surface soil background values and the surface soil background values of Qinghai Province, the contents of Cd and Hg were lower, while the contents of Co, Cr, Ni, Pb and Zn were slightly higher, and the content of Cu was close to the background value. The content of Mn ranged from 448mg/kg to 1286mg/kg, with the average 774mg/kg, which exceeds the national and Qinghai provincial background values. The spatial distribution characteristics of heavy metals were obvious. The contents of As, Cu, Cd and Cr were higher in the northern region. The highest contents of Co, Zn and Ni were around Maixiu Town in the northwest region for the study area. The content of Hg was low in the whole region, but slightly higher in the west than in the east. Pb showed the characteristics of sporadic high points. Mn was significantly higher in the eastern region than in the western region. In the whole study area, the contents of heavy metals in the northern and northeastern regions were higher than those in the western and southern regions. Compared with other regions of QTP, such as Qinghai Lake Basin, soils along highways, Yushu County, the surface soils of Zeku County had higher contents of As and Mn. The contents of Cd, Co, Cr, Cu, Hg, Ni, Pb and Zn in the study area in Qinghai Province were higher than those in the soils around Qinghai Lake Basin, but lower than those along the highways and in Yushu County where human activities were abundant. Compared with the farmland soils in Sanjiang Plain, Huaibei Plain and other typical plain areas, the contents of heavy metals in Zeku County, as a typical alpine farmland area, were mostly lower.　　(2) The ecological risk of heavy metals in soils of Zeku County was evaluated by EF, I_geo and PERI. The results showed the value of EF was in the order of As(2.33)>Mn(1.27)>Ni(1.17)>Co(1.16)>zinc(1.15)>Pb(1.11)>Cr(0.92)>Cd(0.82), which indicates that As has moderate enrichment and other elements have mild enrichment in the soils. The I_geo of 10 heavy metals was in the order of Cd(−1.02)<Hg(−1.00)<Cr(−0.86)<Cu(−0.64)<Ni(−0.53)<Pb(−0.52)<Co(−0.50)<Zn(−0.48)<Mn(−0.37)<As(0.13), in which As showed moderate pollution and the other elements showed slightly contaminated. The PERI of As was up to 130, and PERI of the other elements was all less than 100. The PERI of all heavy metals ranged from 40 to 200, which indicates that the soil is in slight to moderate hazard. Among 43 sampling sites, 42 sites were in mild risk, and only 1 site was in moderate risk. The moderate risk site corresponds to the site with the highest ecological risk coefficient of As.　　(3) Correlation analysis results of each element showed that As-Cu, Cd-Cu, Cd-Pb, Co-Cr, Co-Cu, Co-Mn, Co-Ni, Co-Zn, Cr-Ni, Mn-Pb, Mn-Zn and Pb-Zn had extremely significant positive correlation with p<0.01 and Cd-Hg, Cr-Cu, Cd-Zn, Cr-Mn, Cu-Ni, Cu-Zn, Hg-Mn and Mn-Ni were significantly positively correlated with p<0.05. The larger the correlation coefficient, the stronger the relationship between these heavy metals, indicating that the heavy metals have common or similar sources. Based on correlation analysis, the principal component analysis was carried out. The results of principal component analysis showed that there were four principal components with eigenvalues greater than 1, whose contribution rates were 33.91%, 22.85%, 16.05% and 12.18%, respectively. The cumulative contribution rates of the four principal components, which could explain most information for the studied heavy metals, were 84.98%. The first principal component (F1) had the highest load on heavy metals Co, Cr, Cu, Mn, Ni and Zn. The second (F2) had a larger load on Cd, Pb and Zn. The third (F3) had a larger load on As and Cu. The fourth (F4) was only highly loaded on the heavy metal Hg. According to the comprehensive analysis of the geochemical characteristics of elements, correlation analysis results and land use research results, F1 represented the influence of natural sources, F2 represented the influence of traffic sources, F3 represented the smelting industrial sources, and F4 represented the remote atmospheric transmission. After the pollution sources were identified by principal component analysis, multiple linear regression (MLR) was performed for the concentrations of each tracer element to calculate the relative contribution rate of each source. From the analysis results of the rate of contribution, F1 had the greatest influence on Cr, Co, Mn and Ni, with the contribution rate of 64.49%, 48.35%, 67.68% and 77.99%, respectively. F2 had the greatest influence on Cd, Pb and Zn, contributing 75.46%, 50.75% and 55.54%, respectively. F3 had the greatest influence on As and Cu, contributing 43.53% and 37.29%, respectively. The contribution rate of F4 to Hg reached 49.39%. The model showed that the contribution of other sources to As, Cr, Hg, Cu and Pb was also higher, which were 42.85%, 32.7%, 45.69%, 39.47% and 42.97%, respectively. According to correlation analysis, principal component analysis and regression model analysis, the soil heavy metals are a collection of many sources, and an element is usually affected by multiple factors.

For the surface soils in Zeku, As was more enriched than the other heavy metals, but the degree of enrichment was not high. So, it is necessary to pay attention to the content change of As. The sources of heavy metals in the study area are mainly influenced by the 4 sources of natural, traffic, mining smelting and atmospheric subsidence, and the uncertain sources should be further researched. It is also important to note that three of the four major sources were attributable to human activities. Therefore, the influence of human activities on heavy metals in Zeku County should be addressed, and the relevant measurements should be taken to avoid the enrichment of heavy metal pollution.