Distribution Characteristics and Ecological Risk Assessment of Heavy Metals in Surface Dust from a University Campus in Kaifeng, China
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摘要:
目的 高校校园地表灰尘重金属污染关系到师生健康,探究其地表灰尘重金属环境风险,可为高校校园管理提供数据支持。 方法 采集开封市某高校校园内外地表灰尘52个样品,测定样品中重金属镉(Cd)、铬(Cr)、铜(Cu)、镍(Ni)、铅(Pb)和锌(Zn)的含量,使用地积累指数法和潜在生态风险指数法分析重金属的污染程度和生态风险。 结果 高校地表灰尘重金属Cd、Cr、Cu、Ni、Pb和Zn平均含量分别为1.05、88.36、47.04、29.76、68.72和328.87 mg kg−1,其中Cd和Zn含量分别为当地灰尘背景值的3.49倍和4.26倍。地积累指数分析表明,地表灰尘重金属污染指数平均值由高到低依次为Zn > Cd > Pb > Cu > Cr > Ni,其中Zn与Cd处于偏中度污染,Pb,Cu和Cr处于轻度污染,Ni处于无污染状态。潜在生态风险评价表明,高校地表灰尘中6种重金属综合潜在生态风险指数为144.53,属于“轻微”生态风险等级,其中Cd是该高校地表灰尘中最主要的生态风险影响因子。正定矩阵因子分析法(PMF)表明,Cr和Ni主要来源于成土母质,Cd、Cu、Pb和Zn主要来源于交通、工业污染、大气沉降等复合源。 结论 该高校道路地表灰尘重金属处于轻度到中度污染水平之间,重金属Cd是高校地表灰尘中最主要的污染因子,这些数据可为今后高校校园管理和环境规划提供一些参考。 Abstract:Objective Heavy metal pollution of surface dust in the university campus is an important issue for the safety of teachers and students. The environmental concentration and risk of heavy metals in the surface dust from the university campus were investigated in order to provide a reference for the health of teachers and students and campus management. Method Surface dust samples were collected from the university campus in Kaifeng city. The concentrations of Cd, Cr, Cu, Ni, Pb and Zn were measured by standard methods. The pollution degree of heavy metals pollution was calculated by the geo-accumulation index method and the ecological risk of heavy metals was assessed by the potential ecological risk index method. Result The results showed that the average concentrations of Cd, Cr, Cu, Ni, Pb, and Zn were 1.05, 88.36, 47.04, 29.76, 68.72 and 328.87 mg kg−1, respectively, of which the contents of Cd and Zn were 3.49 and 4.26 times of the background value of dust in Kaifeng, respectively. Geo-accumulated index analysis showed that the order of pollution index of heavy metals from the high to low was Zn, Cd, Pb, Cu, Cr, Ni, and Zn and Cd had been shown the moderate pollution, Pb, Cu and Cr were the light pollution, while Ni was no enrichment. The results of the potential ecological risk assessment indicated that the order of the average ecological risk of heavy metals in surface dust from the high to low was Cd, Pb, Cu, Ni, Zn, and Cr. The average comprehensive potential ecological risk index (RI) value was 144.53, which belongs to a slight level. Moreover, the main factor of potential ecological risks was attributed to cadmium in surface dust. The results of positive definite matrix factor analysis (PMF) showed that, Cr and Ni mainly came from natural parent materials, Cd, Cu, Pb and Zn mainly were derived from the source of vehicle emissions, industrial pollution and atmospheric deposition sources. Conclusion The accumulation degree of heavy metals in the surface dust of the university campus is in the range of mild to moderate pollution level, and the Cd element is the most important pollution factor. Our results can provide some insights into the heavy metal pollution control in the university campus management and environmental planning. -
Key words:
- University campus /
- Greenbelt soils /
- Surface dust /
- Heavy metal /
- Risk assessment
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表 1 地表灰尘和土壤采样信息
Table 1. Detailed information of collected samples in surface dusts and soils
来源
Source采样位置
Location采样校区
Campus采样编号
Number周边环境情况
Surrounding environment灰尘 校园道路 新区 D1 ~ D10 紧邻主干路,伴有餐厅,教学楼,图书馆等教学生活区 老区 D11 ~ D18 校周边道路 新区 V1 ~ V10 紧邻城市主干路,靠近学校大门口,师生主要通过路口,
其中老区在城市老城区老区 V11 ~ V16 土壤 校园绿地 新区 S1 ~ S10 远离主干道,靠近水体,宿舍,
伴有大量绿色植被(如灌木和乔木)老区 S11 ~ S18 表 2 国内不同城市地表灰尘含量比较
Table 2. Comparison of heavy metal concentrations in surface dusts from different cities of China
城市体系
Urban System重金属含量
Concentrations of heavy metals (mg kg−1)参考文献
ReferencesCd Cr Cu Ni Pb Zn 西安校园 − 145.1 93.5 35.8 158.6 665.9 [25] 新疆昌吉 0.21 − 59.33 26.35 46.83 − [26] 漳州公园 − 61.74 77.89 25.20 71.74 77.89 [27] 兰州城区 − 59.85 22.94 26.52 21.98 67.06 [28] 郑州道路 5.1 90.4 39.0 42.5 72.8 627 [29] 开封幼儿园 − 82.13 38.92 52.57 242.99 297.32 [30] 开封公园 1.05 53.11 36.40 23.87 36.71 164.03 [31] 开封高校 1.05 88.36 47.04 29.76 68.72 328.87 本研究 注:−, 无数据。 表 3 地表灰尘与土壤重金属地积累指数均值(Igeo)和划分等级
Table 3. The average (Igeo) of accumulation index and classification of heavy metals in surface dusts and soils
来源位置
SourceCd Cr Cu Ni Pb Zn Igeo
Value等级
GradeIgeo
Value等级
GradeIgeo
Value等级
GradeIgeo
Value等级
GradeIgeo
Value等级
GradeIgeo
Value等级
GradeDX 1.18 a 2 0.46 a 1 0.42 b 1 −0.27 a 0 1.05 a 2 1.74 a 2 DL 1.01 a 2 0.16 ab 1 0.14 bc 1 −0.50 a 0 0.60 a 1 1.47 ab 2 VX 0.68 a 1 0.26 a 1 0.54 b 1 −0.50 a 0 0.83 a 1 1.20 b 2 VL 1.38 a 2 0.41 a 1 1.22 a 2 −0.61 a 0 0.86 a 1 1.40 ab 2 SX 1.53 a 2 −0.24 bc 0 −0.41 c 0 −0.36 a 0 0.68 a 1 0.18 c 1 SL 1.09 a 2 −0.50 c 0 −0.25 bc 0 −0.36 a 0 0.89 a 1 0.29 c 1 注:各个数字右上角字母(a,b和c)表示不同区域采样点间重金属的地积累指数数值之间存在显著差异(P < 0.05)。 表 4 不同生态风险级别样点数占总样点的百分数及生态风险指数
Table 4. Percentages of sites at different risk levels in the total sample sites and potential ecological risk index of heavy metals in surface dusts
评价指标
Evaluating indicator风险指数
Risk index轻微风险(%)
Light中等风险(%)
Medium较强风险(%)
Strong很强风险(%)
Very strong极强风险(%)
Extremely strongE Cd 105.36 8.82 41.18 35.29 14.71 0 Cr 3.80 100 0 0 0 0 Cu 11.45 100 0 0 0 0 Ni 5.68 100 0 0 0 0 Pb 13.98 100 0 0 0 0 Zn 4.26 100 0 0 0 0 RI − 144.53 64.71 35.29 0 0 − 表 5 地表灰尘重金属污染源贡献率
Table 5. Source contribution ratios of heavy metals in surface dusts
重金属
Heavy metal因子1
Factor 1因子2
Factor 2因子3
Factor 3Cd 16.39% 50.46% 33.15% Cr 65.10% 21.10% 13.80% Cu 24.76% 26.33% 48.91% Ni 63.08% 29.36% 7.56% Pb 11.49% 21.48% 67.03% Zn 11.87% 22.19% 65.93% -
[1] Wang H, Zhao Y Y, Walker T R, et al. Distribution characteristics, chemical speciation and human health risk assessment of metals in surface dust in Shenyang City, China[J]. Applied geochemistry, 2021, (131): 105031. [2] 张丹龙, 方凤满, 姚有如, 等. 淮南市不同功能区叶面尘和地表灰尘中重金属分布特征、来源及健康风险评价[J]. 环境科学学报, 2016, 36(9): 3322 − 3332. [3] 申红彬, 徐宗学, 吴保生. 城市地表径流-灰尘-污染物输移研究进展[J]. 水科学进展, 2020, 31(3): 450 − 462. [4] Aguilear A, Bautista F, Gutierrze-ruiz M, et al. Heavy metal pollution of street dust in the largest city of Mexico, sources and health risk assessment[J]. Environmental Monitoring and Assessment, 2021, 193(4): 193. doi: 10.1007/s10661-021-08993-4 [5] 张文娟, 王利军, 王 丽, 等. 西安市地表灰尘中重金属污染水平与健康风险评价[J]. 土壤通报, 2017, 48(2): 481 − 487. [6] Alghamdi A G, Ei-saeid M H, Abdulhakim A J, et al. Heavy metal pollution and associated health risk assessment of urban dust in Riyadh, Saudi Arabia[J]. PloS one, 2022, 17(1): e0261957. doi: 10.1371/journal.pone.0261957 [7] 孙宗斌, 刘百桥, 周 俊, 等. 天津城市道路灰尘重金属污染及生态风险评价[J]. 环境科学与技术, 2015, 38(8): 244 − 250. [8] 吴绽蕾, 周 俊, 胡蓓蓓, 等. 天津公园灰尘与土壤重金属污染特征[J]. 生态学杂志, 2013, 32(4): 1030 − 1037. [9] 武家园, 方凤满, 姚有如, 等. 淮南小学校园不同活动场所灰尘重金属区域分异及生物可给性[J]. 环境科学学报, 2017, 37(4): 1287 − 1296. [10] 曾伟斌, 顾高铨, 万小铭, 等. 多功能区工业园土壤和地表灰尘重金属污染及生态风险差异分析[J]. 环境科学, 2021, 42(3): 1105 − 1113. [11] 黄 浩, 徐子琪, 严俊霞, 等. 太原市城乡居民区采暖季室内灰尘中重金属的污染特征及其生态风险评价[J]. 环境科学, 2021, 42(5): 2143 − 2152. [12] 颜 钰, 李盼盼, 陶 军, 等. 北京高校校园道路灰尘重金属污染特征及健康风险评价[J]. 环境污染与防治, 2016, 38(1): 58 − 63. [13] 蔡云梅, 黄涵书, 任露陆, 等. 珠三角某高校室内灰尘重金属含量水平、来源及其健康风险评价[J]. 环境科学, 2017, 38(9): 3620 − 3627. [14] 盛红坤, 徐 泽, 王佳楠, 等. 天津市某校园土壤中重金属污染研究及其评价[J]. 应用化工, 2021, 50(6): 1529 − 1532. doi: 10.3969/j.issn.1671-3206.2021.06.017 [15] 胡梦珺, 王 佳, 张亚云, 等. 基于随机森林评价的兰州市主城区校园地表灰尘重金属污染[J]. 环境科学, 2020, 41(4): 1838 − 1846. [16] Boutotte C L M, Sugauara L E, De marchi M R R, et al. Trace metals and PAHs in topsoils of the university campus in the megacity of Sao Paulo, Brazil[J]. Anais da academia brasileira de ciencias, 2019, 91(3): e20180334. doi: 10.1590/0001-3765201920180334 [17] 王小莉, 陈志凡, 魏张东, 等. 开封市城乡交错区农田土壤重金属污染及潜在生态风险评价[J]. 环境化学, 2018, 37(3): 513 − 522. doi: 10.7524/j.issn.0254-6108.2017072407 [18] 李一蒙, 马建华, 刘德新, 等. 开封城市土壤重金属污染及潜在生态风险评价[J]. 环境科学, 2015, 36(3): 1037 − 1044. [19] Muller G. Index of geoaccumulation in sediments of the Rhine River[J]. Geo Journal, 1969, 2(3): 108 − 118. [20] 河南省土壤普查办公室. 河南土壤[M]. 北京: 中国农业出版社, 2004: 559-592. [21] 马建华, 董运武, 陈彦芳. 开封市周边地区地表灰尘重金属背景值研究[J]. 环境科学学报, 2020, 40(5): 1798 − 1806. [22] Hakanson L. An ecological risk index for aquatic poltion-control: a sedimen-tological approach[J]. Water Research, 1980, 14(8): 975 − 1001. doi: 10.1016/0043-1354(80)90143-8 [23] Paatero P, Tapper U. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values[J]. Environmetrics, 1994, 5(2): 111 − 126. doi: 10.1002/env.3170050203 [24] 陈志凡, 化艳旭, 徐 薇, 等. 基于正定矩阵因子分析模型的城郊农田重金属污染源解析[J]. 环境科学学报, 2020, 40(1): 276 − 283. [25] 樊馨瑶, 卢新卫, 刘慧敏, 等. 西安市高校校园地表灰尘重金属污染来源解析[J]. 环境科学, 2020, 41(8): 3556 − 3562. [26] 杨秀云, 麦麦提吐尔逊艾则孜, 阿迪莱伊斯马伊力, 等. 新疆昌吉市地表灰尘重金属污染及潜在健康风险[J]. 环境科学与技术, 2021, 44(5): 211 − 219. [27] 范逸飞, 陈秀玲, 方滋婧, 等. 漳州市城市公园灰尘重金属来源及健康风险评价[J]. 地球环境学报, 2021, 12(1): 104 − 120. [28] 李春艳, 胡梦珺, 王 佳, 等. 兰州市主城区校园地表灰尘重金属时空污染特征及健康风险评价[J]. 湖北农业科学, 2021, 60(5): 39 − 47. [29] 沈墨海, 董文静, 王梦蕾, 等. 道路灰尘中重金属的污染特征及其与道路等级的关系—以北京和郑州为例[J]. 环境化学, 2018, 37(5): 942 − 951. [30] 王晓云, 马建华, 侯 千, 等. 开封市幼儿园地表灰尘重金属积累及健康风险[J]. 环境科学学报, 2011, 31(3): 583 − 593. [31] 段海静, 蔡晓强, 阮心玲, 等. 开封市公园地表灰尘重金属污染及健康风险[J]. 环境科学, 2015, 36(8): 2972 − 2980. [32] Wang L, Zhu G F, Pan H X, et al. Surface dust heavy metals in the major cities, China[J]. Environmental Earth Sciences, 2017, 76(22): 757. [33] Long Z J, Zhu H, Bing H J, et al. Contamination, sources and health risk of heavy metals in soil and dust from different functional areas in an industrial city of Panzhihua City, Southwest China[J]. Journal of Hazardous Materials, 2021, 420: 126638. doi: 10.1016/j.jhazmat.2021.126638 [34] Bisht L, Gupta V, Singh A, et al. Heavy metal concentration and its distribution analysis in urban road dust: A case study from most populated city of Indian state of Uttarakhand[J]. Spatial and Spatio-temporal Epidemiology, 2022, (40): 100470. [35] Peng C, Zhang K, Wang M E, et al. Estimation of the accumulation rates and health risks of heavy metals in residential soils of three metropolitan cities in China[J]. Journal of Environmental Sciences, 2022, (115): 149 − 161. [36] 吴 琳, 张新峰, 门正宇, 等. 机动车轮胎磨损颗粒物化学组分特征研究[J]. 中国环境科学, 2020, 40(4): 1486 − 1492. doi: 10.3969/j.issn.1000-6923.2020.04.013