基于Meta分析的近10年中国农田土壤重金属污染特征与风险解析

doi:10.16258/j.cnki.1674-5906.2024.09.012

生态环境学报 ›› 2024, Vol. 33 ›› Issue (9): 1451-1459.DOI: 10.16258/j.cnki.1674-5906.2024.09.012

• 研究论文【环境科学】 • 上一篇下一篇

基于Meta分析的近10年中国农田土壤重金属污染特征与风险解析

丛鑫¹(), 张怀迪¹^,², 张荣², 赵琛², 陈坤², 刘寒冰²^,^*()

1.辽宁工程技术大学环境科学与工程学院，辽宁阜新 123000
2.生态环境部土壤与农业农村生态环境监管技术中心，北京 100012

收稿日期:2024-05-08 出版日期:2024-09-18 发布日期:2024-10-18
通讯作者: ^*刘寒冰。E-mail: liuhb@craes.org.cn
作者简介:丛鑫（1976年生），女，教授，博士，研究方向为土壤环境化学和生态修复。E-mail: congxin1800@163.com
基金资助:
国家重点研发计划项目(2022YFC3704800)

Pollution Characteristics and Risk Analysis of Heavy Metal in Farmland Soils of China in Recent 10 Years Based on Meta Analysis

CONG Xin¹(), ZHANG Huaidi¹^,², ZHANG Rong², ZHAO Cen², CHEN Kun², LIU Hanbing²^,^*()

1. College of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, P. R. China
2. Technical Center for Soil, Agricultural and Rural Ecology and Environment, Ministry of Ecology and Environment of the People’s Republic China, Beijing 100012, P. R. China

Received:2024-05-08 Online:2024-09-18 Published:2024-10-18

摘要/Abstract

摘要：

基于2014－2023年期间在中国知网和Web of Science两个数据库发表的有关中国农田土壤重金属文献数据，采用Meta分析方法探讨了近10年来中国30个行政区中93个城市的农田土壤砷（As）、镉（Cd）、铬（Cr）、铜（Cu）、汞（Hg）、镍（Ni）、铅（Pb）和锌（Zn）的污染现状和空间分布特征，运用地累积指数法和潜在生态风险指数法对农田土壤8种重金属污染程度和潜在生态风险进行了评价，并采用主成分分析法来解析各种活动对重金属污染风险的贡献。研究结果表明，中国农田土壤重金属含量均值普遍超出区域土壤背景值，研究区域农田土壤中8种重金属超标占比为38.2%－84.1%。且研究区域土壤中Cd的算术平均值超过了《土壤环境质量农用地土壤污染管控标准》（GB 15618—2018）中Cd的风险筛选值。地累积指数评价结果显示农田土壤8种重金属的污染程度由高到低依次为：Hg>Cd>Pb>Zn>Cu>Ni>Cr>As。Cd和Hg的污染等级较高，轻度及以上污染区域分别占到研究区域的69.3%和65.9%。潜在生态风险指数（I_r）计算结果表明，研究区域农田土壤中Cd和Hg元素属于较强生态风险危害范围，I_r>300的区域中Cd占比为41.9%，Hg为45.2%。主成分分析结果表明，研究区域农田土壤重金属污染风险可能主要来自农业活动、工业生产、自然源以及各种活动的混合贡献，3个主成分累计方差贡献为72.3%。

关键词: Meta分析, 农田土壤, 重金属, 污染特征, 风险解析, 发表性偏倚

Abstract:

The current status and spatial distribution characteristics of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) pollution in farmland soils of 93 cities in 30 administrative regions of China over the past 10 years were investigated by meta-analysis, based on literature data on heavy metals in Chinese farmland soils published in two databases, CNKI and Web of Science, from 2014 to 2023. The soil accumulation index and potential ecological risk index methods were used to evaluate the degree of pollution and potential ecological risk of the eight heavy metals in farmland soil, and principal component analysis was applied to elucidate the contributions of various activities to the risk of heavy metal pollution. The results showed that the heavy metal content in farmland soil in China generally exceeded the regional soil background value, and the proportion of eight heavy metals exceeding the standard in farmland soil in the study area was 38.2%-84.1%. In addition, the arithmetic mean value of Cd in the soil of the study area exceeded the risk screening value for Cd in the “Soil Environmental Quality Control Standard for Agricultural Land Soil Pollution” (GB 15618—2018). The results of the soil accumulation index showed that the degree of pollution of the eight heavy metals in farmland soil was Hg>Cd>Pb>Zn>Cu>Ni>Cr>As, from high to low. The pollution levels of Cd and Hg were high, and areas with mild or high pollution accounted for 69.33% and 65.9% of the study area, respectively. The calculation results of the potential ecological risk index (I_r) indicated that Cd and Hg in farmland soils in the study area were in the range of strong ecological risk. The proportions of Cd and Hg in the areas with I_r>300 were 41.9% and 45.2%, respectively. Principal component analysis revealed that the risk of heavy metal pollution in agricultural soils within the study area was primarily attributed to a combination of agricultural activities, industrial production, natural sources, and various other activities. These three principal components collectively accounted for 72.3% of the variance.

Key words: meta analysis, farmland soils, heavy metals, pollution characteristics, risk analysis, publication bias

中图分类号:

丛鑫, 张怀迪, 张荣, 赵琛, 陈坤, 刘寒冰. 基于Meta分析的近10年中国农田土壤重金属污染特征与风险解析[J]. 生态环境学报, 2024, 33(9): 1451-1459.

CONG Xin, ZHANG Huaidi, ZHANG Rong, ZHAO Cen, CHEN Kun, LIU Hanbing. Pollution Characteristics and Risk Analysis of Heavy Metal in Farmland Soils of China in Recent 10 Years Based on Meta Analysis[J]. Ecology and Environment, 2024, 33(9): 1451-1459.

图/表 11

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地区	As	Cd	Cr	Cu	Hg	Ni	Pb	Zn	文献
北京	9.70	0.074	68.1	25.4	0.069	29.0	25.4	103	杨雳等, 2023
天津	9.60	0.090	84.2	21.0	0.084	33.3	21.0	79.3	杨雳等, 2023
河北	13.6	0.094	68.3	21.5	0.036	30.8	21.5	78.4	杨雳等, 2023
山西	9.80	0.128	61.8	15.8	0.027	32.0	15.8	75.5	杨雳等, 2023
辽宁	8.80	0.108	57.9	21.4	0.037	25.6	21.4	63.5	杨雳等, 2023
吉林	8.00	0.099	46.7	28.8	0.037	21.4	28.8	80.4	杨雳等, 2023
黑龙江	7.30	0.086	58.6	24.2	0.037	22.8	24.2	70.7	杨雳等, 2023
上海	9.19	0.138	70.2	25.0	0.095	29.9	25.0	81.3	杨雳等, 2023
江苏	11.0	0.126	77.8	26.2	0.289	26.7	26.2	62.6	杨雳等, 2023
浙江	9.20	0.070	52.9	23.7	0.086	24.6	23.7	70.6	杨雳等, 2023
安徽	9.99	0.097	66.5	26.6	0.033	29.8	26.6	62.0	杨雳等, 2023
福建	5.78	0.054	41.3	34.9	0.081	18.2	34.9	82.7	杨雳等, 2023
江西	14.9	0.108	45.9	32.3	0.084	18.9	32.3	69.4	杨雳等, 2023
山东	9.30	0.084	66.0	25.8	0.019	25.8	25.8	63.5	杨雳等, 2023
河南	11.4	0.074	63.8	19.6	0.034	26.7	19.6	60.1	杨雳等, 2023
湖北	12.3	0.172	86.0	26.7	0.080	37.3	26.7	83.6	杨雳等, 2023
湖南	15.7	0.126	71.4	29.7	0.116	31.9	29.7	94.4	杨雳等, 2023
广东	8.99	0.056	50.5	36.0	0.078	14.4	36.0	47.3	杨雳等, 2023
广西	20.5	0.267	82.1	24.0	0.152	26.6	24.0	75.6	杨雳等, 2023
四川	10.4	0.079	79.0	30.9	0.061	32.6	30.9	86.5	杨雳等, 2023
贵州	20.0	0.659	95.9	35.2	0.110	39.1	35.2	99.5	杨雳等, 2023
云南	18.4	0.218	65.2	40.6	0.058	42.5	40.6	89.7	杨雳等, 2023
西藏	16.2	0.074	68.0	19.4	0.021	32.1	27.6	70.7	杨雳等, 2023
陕西	11.1	0.094	62.5	21.4	0.030	28.8	21.4	69.4	杨雳等, 2023
甘肃	12.6	0.116	70.2	18.8	0.020	35.2	18.8	68.5	杨雳等, 2023
宁夏	11.9	0.112	60	20.9	0.021	36.5	20.9	58.8	杨雳等, 2023
新疆	11.2	0.120	49.3	19.4	0.017	26.6	19.4	68.8	杨雳等, 2023
重庆	5.82	0.133	76.1	23.8	0.053	30.6	25.5	75.8	杨雳等, 2023
内蒙古	6.12	0.050	39.8	13.9	0.030	18.6	16.8	56.6	高红霞等, 2007
海南	1.14	0.050	15.2	4.95	0.030	4.12	22.3	35.1	谭凌智等, 2010

地区	As	Cd	Cr	Cu	Hg	Ni	Pb	Zn	文献
北京	9.70	0.074	68.1	25.4	0.069	29.0	25.4	103	杨雳等, 2023
天津	9.60	0.090	84.2	21.0	0.084	33.3	21.0	79.3	杨雳等, 2023
河北	13.6	0.094	68.3	21.5	0.036	30.8	21.5	78.4	杨雳等, 2023
山西	9.80	0.128	61.8	15.8	0.027	32.0	15.8	75.5	杨雳等, 2023
辽宁	8.80	0.108	57.9	21.4	0.037	25.6	21.4	63.5	杨雳等, 2023
吉林	8.00	0.099	46.7	28.8	0.037	21.4	28.8	80.4	杨雳等, 2023
黑龙江	7.30	0.086	58.6	24.2	0.037	22.8	24.2	70.7	杨雳等, 2023
上海	9.19	0.138	70.2	25.0	0.095	29.9	25.0	81.3	杨雳等, 2023
江苏	11.0	0.126	77.8	26.2	0.289	26.7	26.2	62.6	杨雳等, 2023
浙江	9.20	0.070	52.9	23.7	0.086	24.6	23.7	70.6	杨雳等, 2023
安徽	9.99	0.097	66.5	26.6	0.033	29.8	26.6	62.0	杨雳等, 2023
福建	5.78	0.054	41.3	34.9	0.081	18.2	34.9	82.7	杨雳等, 2023
江西	14.9	0.108	45.9	32.3	0.084	18.9	32.3	69.4	杨雳等, 2023
山东	9.30	0.084	66.0	25.8	0.019	25.8	25.8	63.5	杨雳等, 2023
河南	11.4	0.074	63.8	19.6	0.034	26.7	19.6	60.1	杨雳等, 2023
湖北	12.3	0.172	86.0	26.7	0.080	37.3	26.7	83.6	杨雳等, 2023
湖南	15.7	0.126	71.4	29.7	0.116	31.9	29.7	94.4	杨雳等, 2023
广东	8.99	0.056	50.5	36.0	0.078	14.4	36.0	47.3	杨雳等, 2023
广西	20.5	0.267	82.1	24.0	0.152	26.6	24.0	75.6	杨雳等, 2023
四川	10.4	0.079	79.0	30.9	0.061	32.6	30.9	86.5	杨雳等, 2023
贵州	20.0	0.659	95.9	35.2	0.110	39.1	35.2	99.5	杨雳等, 2023
云南	18.4	0.218	65.2	40.6	0.058	42.5	40.6	89.7	杨雳等, 2023
西藏	16.2	0.074	68.0	19.4	0.021	32.1	27.6	70.7	杨雳等, 2023
陕西	11.1	0.094	62.5	21.4	0.030	28.8	21.4	69.4	杨雳等, 2023
甘肃	12.6	0.116	70.2	18.8	0.020	35.2	18.8	68.5	杨雳等, 2023
宁夏	11.9	0.112	60	20.9	0.021	36.5	20.9	58.8	杨雳等, 2023
新疆	11.2	0.120	49.3	19.4	0.017	26.6	19.4	68.8	杨雳等, 2023
重庆	5.82	0.133	76.1	23.8	0.053	30.6	25.5	75.8	杨雳等, 2023
内蒙古	6.12	0.050	39.8	13.9	0.030	18.6	16.8	56.6	高红霞等, 2007
海南	1.14	0.050	15.2	4.95	0.030	4.12	22.3	35.1	谭凌智等, 2010

项目	地积累指数污染程度等级
I_geo	3<I_geo	2<I_geo≤3	1<I_geo≤2	0<I_geo≤1	I_geo≤0
分级	4	3	2	1	0
污染程度	严重污染	重度污染	中度污染	轻度污染	无污染

项目	地积累指数污染程度等级
I_geo	3<I_geo	2<I_geo≤3	1<I_geo≤2	0<I_geo≤1	I_geo≤0
分级	4	3	2	1	0
污染程度	严重污染	重度污染	中度污染	轻度污染	无污染

项目	潜在生态风险等级
潜在风险	轻微风险	中等风险	较强风险	很强风险	极强风险
I_r,_i	I_r,_i ≤40	40<I_r,_i≤80	80<I_r,_i≤160	160<I_r,_i≤320	I_r_,i>320
I_r	I_r≤150	150<I_r≤300	300<I_r≤600	600<I_r≤1200	I_r>1200

基于Meta分析的近10年中国农田土壤重金属污染特征与风险解析

Pollution Characteristics and Risk Analysis of Heavy Metal in Farmland Soils of China in Recent 10 Years Based on Meta Analysis

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图/表 11

参考文献 42

相关文章 15

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Metrics

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元素	As	Cd	Cr	Cu	Hg	Ni	Pb	Zn
最大值	34.63	3.915	149.6	167.6	20.90	96.11	141.3	333.5
最小值	2.420	0.043	9.710	0.350	0.003	5.600	10.04	31.65
中位数	8.368	0.250	56.33	25.62	0.285	26.24	28.16	70.55
算数平均值	10.93	0.391	60.96	29.59	0.495	25.06	34.20	85.47
几何平均值	7.399	0.309	38.06	22.86	0.321	21.61	25.71	59.46
标准差	5.960	0.596	24.75	23.09	1.249	14.72	17.53	55.93
变异系数/%	54.53	152.4	40.60	78.05	252.3	58.74	51.25	65.44
超背景值占比/%	43.53	84.09	38.20	55.29	80.49	43.04	65.93	60.49

成分	初始特征值			提取平方和载入			旋转平方和载入
成分	总计	方差/ %	累计/ %	总计	方差/ %	累计/ %	总计	方差/ %	累计/ %
1	2.80	35.0	35.0	2.80	35.0	35.0	2.58	32.28	32.3
2	1.76	22.0	57.0	1.76	22.0	57.0	1.97	24.6	56.9
3	1.23	15.3	72.30	1.23	15.3	72.3	1.23	15.4	72.3
4	0.784	9.80	82.1
5	0.566	7.08	89.2
6	0.337	4.21	93.4
7	0.311	3.89	97.3
8	0.219	2.74	100

主成分	As	Cd	Cr	Cu	Hg	Ni	Pb	Zn
1	0.061	0.805	0.442	0.692	0.041	0.418	0.772	0.836
2	−0.178	−0.325	0.720	0.295	−0.360	0.791	−0.426	−0.283
3	−0.755	−0.130	0.141	−0.168	0.750	0.123	0.083	0.071

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