Evaluation and Source of Heavy Metal Pollution in Surface Soils in Typical Alpine Agricultural Areas of Qinghai Province
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摘要:
土壤中重金属污染往往是多种成因来源和作用途径叠加综合的结果，简单地判别重金属元素来源不足以为区域土壤重金属污染治理提供足够信息，需定量计算各类排放源对元素的相对贡献率，确定主要污染源。中国青藏高原表土重金属含量近年来有聚集趋势，但是对于重金属来源的定量解析缺乏，位于青藏高原东部区域以及农业土壤的研究也有待补充。为深入了解青藏高原东部典型高山农业区的土壤重金属分布特征、生态风险及污染来源，本文对青海省泽库县的表层土壤（0~20cm）样品进行了采集，对As、Cd、Co、Cr、Cu、Hg、Mn、Ni、Pb、Zn等10种重金属含量进行了分析。采用原子荧光光谱法（AFS）、电感耦合等离子体质谱/发射光谱法（ICP-MS/OES）等方法测定元素含量，结合基础统计分析方法及对比分析法，研究了重金属含量和空间分布特征；应用富集因子（EF）、地累积指数（Igeo）和潜在生态风险指数（PERI）确定了研究区土壤重金属污染程度和生态风险情况，并利用主成分分析-绝对主成分分数-多元线性回归模型（PCA-APCS-MLR）定量解析了重金属主要潜在来源。结果表明：①As元素的含量均值高于土壤国家环境质量标准，其他重金属含量均小于土壤环境质量标准值。②与中国土壤环境背景值与青海省表层土壤背景值相比，Cd、Hg含量均小于背景值，As、Mn均值含量远超背景值，Co、Cr、Ni、Pb、Zn含量略大于背景值，Cu基本接近于背景值。③富集因子（EF）、地累积指数（Igeo）和潜在生态风险指数（PERI）分析结果基本一致，As表现出的危害趋势最高，其他重金属均较低。④空间分布上，泽库北部重金属含量明显要高于其他区域，位于泽库县东北部的麦秀镇表现出多种重金属含量高的现象。⑤与青海湖流域、公路沿线土壤、玉树县等青藏高原其他区域相比，泽库县表层土壤中As、Mn含量较高。Cd、Co、Cr、Cu、Hg、Ni、Pb、Zn元素含量基本上要高于青海湖流域地区，但是与公路沿线、玉树县等人为活动较为丰富的区域相比则含量低。与三江平原、淮北平原等典型平原地区农田土壤相比，泽库县作为典型高山区域的农田区域，其重金属含量绝大部分要低于平原地区农田土壤。⑥根据相关性分析、主成分分析和PCA-APCS-MLR的结果，研究区重金属主要有4个来源，自然源对Cr、Co、Mn、Ni贡献率分别为64.49%、48.35%、67.68%、77.99%，交通源对Cd、Pb、Zn影响大，贡献率分别为75.46%、50.75%、55.54%，矿业冶炼对于As、Cu影响较大，贡献率分别为43.52%、37.29%，大气沉降的远源因素对Hg的影响最显著，贡献率达到43.39%。其他源对As、Cr、Hg、Cu 和 Pb的影响也较大，需进一步研究明确。综上，对于泽库县，As较其他重金属元素富集明显，但富集程度不高，需进一步预防土壤中As的深度污染。研究区内重金属有自然源、交通源、矿业冶炼及大气沉降的远源等主要4种来源，其他源的定性未能明确需进一步加强研究，而4个主要来源中有3个来源属于人类活动性质，因此人类活动对于泽库县这类典型高山农业土壤的重金属影响需受到关注，采取相关措施避免重金属污染富集现象加重。
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关键词:
- 高山农业区 /
- 表土 /
- 重金属 /
- 污染来源 /
- 电感耦合等离子体质谱/发射光谱法 /
- PCA-ACPS-MLR
Abstract:BACKGROUND 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.
OBJECTIVES 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.
METHODS 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 (Igeo) 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.
RESULTS (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, Igeo 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 Igeo 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.
CONCLUSIONS 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.
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Key words:
- alpine agricultural area /
- topsoil /
- heavy metals /
- pollution sources /
- ICP-MS/OES /
- PCA-APCS-MLR
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图 2 表层土壤重金属元素（a） As、（b） Cu、（c） Cd、（d） Cr 、（e） Co、（f） Zn、（g） Ni 、（h） Hg、（i） Pb、（j） Mn地球化学空间分布图
Figure 2.
表 1 富集因子（EF）和地累积指数(Igeo)与污染程度关系
Table 1. Relationship between enrichment factor (EF), geoaccumulation (Igeo) and contamination grades.
EF 富集程度等级 Igeo 污染程度判定 EF≤1 未富集 Igeo≤0 未污染 1<EF≤2 轻微富集 0<Igeo≤1 未污染至中度污染 2<EF≤5 中度富集 1<Igeo≤2 中度污染 5<EF≤20 显著富集 2<Igeo≤3 中度至高度污染 20<EF≤40 强烈富集 3<Igeo≤4 重度污染 40< EF 极强富集 4<Igeo≤5 重度至极度污染 Igeo>5 极度污染 
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表 2 潜在生态危害系数（
$ {E}_{r}^{i} $ ）及危害指数（PERI）与风险程度Table 2. Potential ecological risk efficient (
$ {E}_{\mathrm{r}}^{\mathrm{i}} $ ), potential ecological risk index (PERI) and risk level.$ {E}_{\mathrm{r}}^{\mathrm{i}} $ 危害程度 PERI 危害程度 $ {E}_{\mathrm{r}}^{\mathrm{i}} $ ≤40轻微 PERI<150 轻微 40≤ $ {E}_{\mathrm{r}}^{\mathrm{i}} $ <80中等 150≤PERI<300 中等 80≤ $ {E}_{\mathrm{r}}^{\mathrm{i}} $ <160强 300≤PERI<600 强 160≤ $ {E}_{\mathrm{r}}^{\mathrm{i}} $ <320很强 PERI≥600 很强 $ {E}_{\mathrm{r}}^{\mathrm{i}} $ >320极强
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表 3 研究区土壤重金属含量统计特征
Table 3. Statistical characteristics of soil heavy metal concentrations.
重金属含量统计值 As Cd Co Cr Cu Hg Mn Ni Pb Zn 样本数（件） 43 43 43 43 43 43 43 43 43 43 平均值(mg/kg) 28.95 0.14 13.85 63.15 23.84 0.017 774.14 30.65 23.20 74.96 标准差(mg/kg) 39.35 0.05 3.77 21.49 6.95 0.008 150.26 12.56 3.32 10.16 方差 1548.65 0.00 14.21 461.94 48.32 0.00 22579.12 157.80 11.00 103.13 峰度 26.73 6.94 7.75 19.77 12.99 6.016 2.55 20.88 0.47 2.11 偏度 4.90 2.09 2.02 3.56 2.76 1.975 0.73 3.87 0.29 0.26 最小值(mg/kg) 8.66 0.08 7.45 25.20 11.80 0.009 448.00 11.10 16.40 46.60 最大值(mg/kg) 254.00 0.36 30.20 178.00 57.70 0.049 1286.00 98.70 31.30 105.00 变异系数（CV） 1.36 0.35 0.27 0.34 0.29 0.450 0.19 0.41 0.14 0.14 土壤环境质量标准 (mg/kg) 25 0.6 - 250 100 3.4 - 190 170 300 中国土壤背景值(mg/kg) 9.1 0.15 11.7 63 23 0.050 552 26 25 67 青海省表层土壤背景值（mg/kg） 13.0 0.184 12.7 73 24 0.021 654 28 22 69
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表 4 研究区与其他地区表层土壤的重金属含量对比
Table 4. Comparison of heavy metals content in topsoil between the study area and other areas.
重金属
元素本研究区含量
(mg/kg)青藏高原其他地区重金属含量（mg/kg） 青海省
玉树县[26]青藏高原
东北部地区[27]青藏高原东北—
西南方向[15]环青海湖
地区[28]青海湖流域
表层土壤[29]青海省重要
交通沿线[30]一江两河流域
中部地区[31]As 28.95 20.95 - - 11.73 11.66 21.60 - Cd 0.14 0.24 0.68 0.17 0.62 - 0.19 0.21 Co 13.85 - 11.59 11.39 12.38 12.73 10.50 - Cr 63.15 72.84 83.10 70.84 41.35 54.17 74.60 82.95 Cu 23.84 24.18 40.74 23.92 19.33 19.72 22.00 34.67 Hg 0.017 0.046 0.280 - - - 0.050 - Mn 774.14 735.06 - 639.64 546.96 626.28 - 697.39 Ni 30.65 - 54.73 31.64 21.18 24.96 39.40 49.99 Pb 23.20 26.93 72.49 28.65 21.86 20.47 32.90 35.81 Zn 74.96 85.10 145.64 73.31 63.51 - 100.30 75.31 重金属
元素本研究区含量
(mg/kg)其他平原地区农田土壤含量（mg/kg） 三江平原[32] 江苏省[33] 浙江省[33] 淮北平原[34] 长三角地区[35] 江汉平原[36] As 28.95 16.87 10.24 7.25 12.1 8.14 - Cd 0.14 0.18 0.18 0.23 0.48 0.25 0.48 Co 13.85 - - - - - - Cr 63.15 69.83 71.49 47.84 72.24 68.84 - Cu 23.84 35.28 26.56 23.96 23.73 32.58 48.2 Hg 0.017 0.072 0.070 0.120 0.046 0.140 0.120 Mn 774.14 - - - - - - Ni 30.65 22.29 29.68 21.31 33.23 33.02 48.80 Pb 23.20 18.26 28.80 36.79 24.65 32.32 36.50 Zn 74.96 68.21 75.87 91.39 131.79 92.35 96.80
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表 5 土壤中重金属元素的潜在生态风险系数统计
Table 5. Comprehensive potential ecological risk coefficients of heavy metals in the soils.
潜在生态风险系数（ $ {E}_{\mathrm{r}}^{\mathrm{i}} $ ）统计值As Cd Co Cr Cu Hg Mn Ni Pb Zn 平均值 14.85 15.59 3.64 1.15 3.31 21.59 0.79 3.65 3.52 0.72 中位数 9.08 14.13 3.52 1.11 3.24 19.05 0.78 3.45 3.53 0.72 众数 8.46 16.30 3.54 1.16 3.64 15.24 0.70 3.58 3.58 0.68 标准差 20.18 5.52 0.99 0.39 0.97 9.71 0.15 1.50 0.50 0.10 最小值 4.44 8.59 1.96 0.46 1.64 11.43 0.46 1.32 2.48 0.45 最大值 130.26 39.13 7.93 3.25 8.01 62.22 1.31 11.75 4.74 1.01
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表 6 土壤重金属元素间相关性分析
Table 6. Correlation analysis of heavy metals in the soils.
元素 As Cd Co Cr Cu Hg Mn Ni Pb Zn As 1 Cd 0.24 1 Co 0.03 0.15 1 Cr −0.00 −0.10 0.90** 1 Cu 0.82** 0.21 0.44** 0.36* 1 Hg −0.09 0.38* 0.06 0.03 −0.18 1 Mn −0.05 0.44** 0.53** 0.32* 0.20 0.31* 1 Ni −0.02 0.01 0.93** 0.97** 0.34* 0.02 0.33* 1 Pb 0.21 0.52** 0.04 −0.17 0.22 0.17 0.42** −0.17 1 Zn −0.06 0.38* 0.48** 0.28 0.32* 0.12 0.62** 0.27 0.43** 1 注：“*”表示p<0.05, “**”表示p<0.01。
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表 7 土壤重金属主成分分析矩阵
Table 7. Principal component analysis matrix of heavy metals in the soils.
元素 主成分 F1 F2 F3 F4 As 0.14 0.28 0.88 0.28 Cd 0.26 0.67 −0.06 0.44 Co 0.95 −0.18 −0.03 −0.02 Cr 0.88 −0.45 0.00 0.01 Cu 0.53 0.24 0.78 0.00 Hg 0.15 0.29 −0.48 0.68 Mn 0.64 0.46 −0.33 −0.03 Ni 0.88 −0.44 −0.02 0.07 Pb 0.16 0.79 0.01 −0.02 Zn 0.60 0.52 −0.20 −0.39 初始特征值 4.07 2.74 1.93 1.46 方差贡献率（%） 33.91 22.85 16.05 12.18 累积贡献率（%） 33.91 56.76 72.80 84.98
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表 8 泽库县表层土壤重金属污染源贡献分析结果
Table 8. Analysis of contribution of heavy metal pollution sources in the soils.
重金属
元素贡献率（%） ET OT E/O
（%）R2 F1 F2 F3 F4 其他源 As 9.38 4.08 43.52 0.18 42.85 28.95 28.95 99.997 0.98 Cd 3.79 75.46 2.00 1.10 17.65 0.14 0.14 100.418 0.85 Co 48.35 36.91 0.57 0.16 14.01 13.85 13.85 99.986 0.97 Cr 64.49 2.36 0.36 0.09 32.70 63.14 63.15 99.983 0.99 Cu 17.51 5.51 37.29 0.22 39.47 23.84 23.84 99.996 0.97 Hg 1.53 1.34 2.06 49.39 45.69 0.02 0.02 100.00 0.90 Mn 67.68 13.70 0.36 0.20 18.07 774.13 774.15 99.998 0.86 Ni 77.99 0.94 0.43 0.05 20.59 30.63 30.65 99.931 0.99 Pb 5.51 50.75 0.62 0.15 42.97 23.17 23.21 99.828 0.81 Zn 18.07 55.54 0.14 0.03 26.22 74.95 74.96 99.993 0.91
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