环境科学  2022, Vol. 43 Issue (2): 975-984   PDF    
引用本文
黄钟霆, 易盛炜, 陈贝贝, 彭锐, 石雪芳, 李峰. 典型锰矿区周边农田土壤-农作物重金属污染特征及生态风险评价[J]. 环境科学, 2022, 43(2): 975-984.
HUANG Zhong-ting, YI Sheng-wei, CHEN Bei-bei, PENG Rui, SHI Xue-fang, LI Feng. Pollution Properties and Ecological Risk Assessment of Heavy Metals in Farmland Soils and Crops Around a Typical Manganese Mining Area[J]. Environmental Science, 2022, 43(2): 975-984.
典型锰矿区周边农田土壤-农作物重金属污染特征及生态风险评价
黄钟霆1, 易盛炜2, 陈贝贝1, 彭锐3, 石雪芳4, 李峰2     
1. 湖南省生态环境监测中心, 国家环境保护重金属污染监测重点实验室, 长沙 410027;
2. 湘潭大学环境与资源学院, 湘潭 411199;
3. 湖南省长沙生态环境监测中心, 长沙 410001;
4. 湘西州生态环境局花垣分局, 湘西 416400
收稿日期: 2021-05-05; 修订日期: 2021-07-07
基金项目: 国家自然科学基金项目（21577118）；湖南省教育厅开放创新基金项目（19K090）；湖南省环保基金项目
作者简介: 黄钟霆(1980~), 男, 硕士, 高级工程师, 主要研究方向为环境分析监测, E-mail: 13643860@qq.com
通信作者: 李峰，E-mail: lifeng6220@xtu.edu.cn
摘要: 以湖南省某典型关停锰矿区为研究对象，采集了矿区周边（污染区）和远离矿区（对照区）的农作物及其对应的土壤样品，测定了Cr、Mn、Ni、Cu、Zn、As、Cd和Pb等8种重金属含量，利用ArcGIS空间插值和主成分分析法分析了土壤重金属的分布及主要来源，重点探讨了土壤及对应农作物间重金属迁移规律，采用单因子、综合污染指数法以及潜在生态风险指数法进行了生态风险评价.结果表明，污染区存在严重的Cd、Zn、As和Mn污染，其中旱田中的平均含量分别为6.22、612.28、37.72和1506.2 mg·kg-1，相较农用地风险筛选值，Cd、Zn和As超标率分别为88.41%、94.2%和84.06%，Mn的平均含量是湖南土壤背景值的3倍，水田污染相对较轻.由主成分分析可知农田土壤中Cd、Zn和Mn的来源与锰矿开采有关，As可能来源于农业活动.污染区为重污染等级，Cd、Mn和Zn是主要的污染因子，土壤中Cd存在极强的潜在生态风险，其余重金属具有轻微的潜在生态风险.研究区农作物主要存在Cr、Pb和Cd超标且超标率在1.1%~37.3%，其中，玉米中各超标重金属含量均值均高于大米，叶菜类蔬菜中各重金属含量均值均高于根茎类蔬菜.农田土壤污染程度会影响作物的富集能力，且不同作物对重金属的富集能力不同，蔬菜和玉米中8种重金属以及大米中Cd和As与对应土壤中重金属呈现正相关.
关键词: 农田土壤      重金属      污染程度      生态风险      评价     
Pollution Properties and Ecological Risk Assessment of Heavy Metals in Farmland Soils and Crops Around a Typical Manganese Mining Area
HUANG Zhong-ting1 , YI Sheng-wei2 , CHEN Bei-bei1 , PENG Rui3 , SHI Xue-fang4 , LI Feng2     
1. State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants, Hunan Environmental Monitoring Center, Changsha 410027, China;
2. College of Environment and Resources, Xiangtan University, Xiangtan 411199, China;
3. Changsha Environmental Monitoring Center, Changsha 410001, China;
4. Huayuan Branch of Xiangxi Ecologcial Environment Bureau, Xiangxi 416400, China
Abstract: In order to assess the ecological risks of heavy metals and explore the pattern of heavy metal migration between farmland and corresponding crops in a typical and closed manganese mining area in Hunan province, farmland soils and crops surrounding the mining area (pollution area) and away from the mining area (control area) were collected, and then the contents of Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb were analyzed. The sources and distribution of heavy metals in farmland soils were analyzed using Kriging spatial interpolation and principal component analysis, and the ecological risk was evaluated using the single factor index, comprehensive pollution index, and potential ecological risk index. The results showed that the surrounding farmland soils in the closed Manganese mining area presented serious pollution of Cd, Zn, As, and Mn, in which the average contents of the above heavy metals in the dry land soil in the polluted area were 6.22, 612.28, 37.72, and 1506.2 mg·kg-1, respectively. Compared with the soil risk screening value of agricultural land, the over-standard rates of Cd, Zn, and As were 88.41%, 94.20%, and 84.06%, respectively, and the average content of Mn in the farmland soil was three times that of the background value in the Hunan soil; however, the heavy metal pollution in the paddy field was relatively light. The principal component analysis showed that the sources of Cd, Mn, and Zn in the farmland soil were related to the manganese ore mining, whereas the source of As in the farmland soil might originate from agricultural activities. The pollution area was at a heavy pollution level, and the main pollution factors were Cd, Mn, and Zn. The Cd in the farmland soil could pose a strong potential ecological risk, but the rest of the heavy metals presented only a slight potential ecological risk. The content of Cr, Pb, and Cd in the crops in the study area exceeded the standard, and the exceeding standard rate was between 1.1% and 37.3%, where the average content of over-standard heavy metals in corn was higher than that in rice, and the average content of heavy metals in leafy vegetables was higher than that in root vegetables. The soil pollution degree of heavy metals could affect the accumulation ability of crops, and different crops had different accumulation abilities. For instance, leafy vegetables and root vegetables easily accumulated Cd and Zn; however, rice and corn separately enriched Cd and Cr, as well as Zn and Cu. The contents of heavy metals in dryland soils had a positive correlation with the content of heavy metals in corresponding crops. The contents of Cd and As in the paddy field and rice presented a positive correlation, but the remaining six heavy metal contents in rice (i.e., Cr, Mn, Ni, Cu, Zn, and Pb) did not correlate with the content of the paddy fields.
Key words: farmland soil      heavy metals      pollution degree      ecological risk      evaluation     

农田土壤是保障人类生存和发展的重要资源, 长期的矿山开采和金属冶炼活动会造成周边农田土壤重金属污染.由于各矿区的重金属污染特征、主要农作物类型和农作物富集能力的差异性, 不同矿区周边农田土壤和农作物面临的生态风险不尽相同, 客观正确地评价典型矿区周边农田土壤和农作物的污染状况对今后矿区农用地污染控制修复以及安全利用有着积极意义.

湘西花垣县锰矿资源丰富, 有中国锰矿“金三角”的美誉, 但由于历史上开发无序及废弃矿石随意堆放, 造成了矿区周边空气、河流和土壤不同程度地重金属污染[1~4].近年来, 政府已负责任地关闭了大量的非法采选冶炼企业, 但锰矿区开采遗留的重金属污染问题短时间内难以解决, 仍存在一定的潜在风险.早期已有研究分别对花垣县部分矿区土壤和蔬菜重金属污染进行了调查[5~9], 但缺乏对花垣典型锰矿区周边农田土壤-农作物重金属污染特征和生态风险的系统性分析, 尤其是不同类型和污染程度的土壤与对应农作物间重金属迁移规律尚不清楚.

为此, 本文以湖南省某关闭锰矿区周边农田土壤及其农产品为研究对象, 对不同类型土壤及粮食和蔬菜等农产品进行采样, 利用克里金空间插值及主成分分析法解析土壤重金属空间分布并揭示其来源, 并利用单因子污染指数法、内梅罗综合污染指数法和潜在生态风险评价法对其生态风险进行评价[10~12], 探讨了农田土壤和农作物中重金属污染特征及其之间的关联特性, 以期为矿区周边农田土壤的风险管控和保证农产品安全提供科学依据.

1 材料与方法 1.1 研究区概况

研究区位于湘西土家族苗族自治州花垣县东北部和中部, 对照区距污染区直线距离约20 km, 锰矿集中分布在污染区行政村1, 污染区以锰矿尾矿矿渣堆积点为中心布设30个点位, 对照区布设119个点位(图 1).研究区农作物种植以水稻、玉米、白菜和萝卜等为主.污染区和对照区的pH范围为旱田6.6~7.8, 水田6.5~7.2.

图 1 土壤样品采集区及采样点分布示意 Fig. 1 Distribution maps of soil sampling areas and points

1.2 样品采集及处理方法

污染区水田和旱田, 对照区水田和旱田土壤样品分别为20和69、52和67个, 为作物根附着土混合样.农作物样品采集点位与土壤样品采集点位吻合, 水田采集的脱壳稻米、玉米、白菜、空心菜、红菜苔、萝卜和莴笋样品分别为94、74、95、57、57、68和35份.土壤及农作物的采样布点详见图 1.采集的土壤样品自然风干, 研磨过100目筛后装袋备用.采集的蔬菜样品用去离子水清洗后烘干至恒重, 磨细装袋备用.

1.3 样品分析方法 1.3.1 土壤和农作物中重金属的测定

土壤样品参考《土壤和沉积物-金属元素总量的消解-微波消解法》(HJ 832- 2017)进行消解.农作物样品采用HNO3-H2O2加热消解.土壤消解液和农作物消解液经电感耦合等离子体质谱法(ICP-MS)测定.分析过程中使用国家标准样品和空白样品进行质控, 标准样品为国家标准物质土壤(GBW07430)、大米(GBW10045)、玉米(GBW10012)和菠菜(GBW10015).标准样品中总铬、总锰、总镍、总铜、总锌、总砷、总镉和总铅的加标回收率均在90%~105%之间.测试过程发现农作物中总砷含量远小于无机砷标准限值, 故仅测定总砷含量.

1.3.2 重金属污染评价方法

土壤中的重金属污染评价采用单因子污染指数法和综合污染指数法, 以湖南省的土壤背景值作为标准[13]进行评价.

单因子污染指数法:

式中, Pi为重金属单因子污染指数, Ci为重金属的实测值, Si为重金属i的评价标准值. Pi < 1, 表示未污染; Pi > 1, 表示污染, Pi越大污染越严重.

综合污染指数法:

式中, Pzong为重金属综合污染指数, Pave为单因子污染指数的平均值, Pmax为单因子污染指数中的最大值.分级标准见文献[14].

潜在生态危害指数法:

式中, Ci、Si、Ti和Ei分别为第i种土壤重金属的实测值、参比值、毒性系数和潜在生态危害系数; RI为土壤中多种重金属的综合生态危害指数.相关分级标准见文献[15, 16].

农作物中Pb、Cd、As和Cr采用《食品安全国家标准-食品中污染物限量》(GB 2762-2017), Zn和Cu分别采用《食品中锌限量卫生标准》(GB 13106-1991)和《食品中铜限量卫生标准》(GB 15199-1994)评价超标率, Mn和Ni因无参考标准故未作评价[17].

生物富集系数(BCF)计算公式如下:

式中, CR为作物中重金属的含量, Cs为对应土壤中同一重金属的含量.

1.4 统计分析方法

数据分析和作图利用ArcGIS 10.2.2、Origin 8.5和SPSS Statistics 25等软件.

2 结果与讨论 2.1 土壤中重金属来源、分布及污染评价

土壤中重金属含量如图 2所示, 按照GB 15618-2018中土壤风险筛选值计算超标率, 研究区土壤Zn、Cd、As、Cu和Pb均有超标, 其中污染区旱田超标率分别为94.2%、88.41%、8.06%、49.3%和8.7%, 对照区旱田超标率为29.9%、40.3%、37.31%、40.3%和4.5%, Cr和Ni未超标.研究区水田中Cu、Zn、Cd和Pb等重金属超标率略低于旱田, 而As在水田的超标率明显低于旱田, 可能由于轮作中水稻相较蔬菜和玉米等旱田作物对土壤中砷的富集吸收能力更强导致[18].污染区与对照区的旱田和水田中Zn、Cd、As、Pb和Mn均有显著性差异(P < 0.05), 说明存在外界活动的干扰, 为进一步解析研究区土壤的重金属来源, 对研究区8种重金属进行主成分分析, 数据检验的KMO值为0.747, Bartlett's检验的P值小于0.001, 可以进行主成分提取.如图 3所示, 提取了2个特征值大于1的成分, 累计解释了总方差的62.8%.第一主成分中具有较高载荷的重金属元素为Cu、Ni、Cr、As和Pb, 方差贡献率为44.2%, Cu、Ni、Cr、As和Pb的Pearson相关系数在0.401~0.8之间, 相关性较强, 具有同源性, 可能来源于农业活动如施肥及污水灌溉; 第二主成分中具有较高载荷的重金属元素为Cd、Zn、Pb和Mn, 方差贡献率为18.6%, Cd的载荷最大为0.702, Cd、Zn和Pb的相关系数在0.357~0.627之间, 可能来源于锰矿矿渣雨水淋溶、大气沉降和污水排放等重金属迁移途径.值得注意的是, Pb不仅来源于农业活动, 同时也受锰矿开采的影响.严重的Cd、Zn和As等重金属污染会对作物及动物的生长发育产生显著抑制作用, 人群通过膳食暴露等途径长期摄入会造成较高的健康风险[19, 20].

1.污染区早田, 2.污染区水田, 3.对照区早田, 4.对照区水田; 不同小写字母代表处理组间差异显著(P < 0.05) 图 2 污染区和对照区不同类型土壤重金属含量水平 Fig. 2 Heavy metal contents of different types of soil in contaminated area and control area

图 3 污染区土壤重金属元素主成分荷载 Fig. 3 Heavy metal loading of the principal components in contaminated soil

研究区土壤8种重金属含量在空间上分布如图 4所示, 污染区高浓度重金属区域主要分布于西南部的行政村1内, 该村锰矿企业分布较为集中.污染区河流上游两侧土壤中Cd、Mn、Zn、As和Pb等重金属浓度较高, 未来应加强河流中的重金属监测, 防范土壤中重金属通过雨水冲刷或下渗等方式向河流迁移.

图 4 污染区和对照区土壤中8种重金属含量空间分布 Fig. 4 Spatial distribution of eight heavy metal concentrations in the contaminated area and control area

如图 5所示, 按单因子污染指数法评价, 污染区土壤受8种重金属污染程度为: Cd > Mn > Zn > As > Pb, Cu、Cr和Ni无污染.从综合污染指数评价知, 污染区3个行政村均属于重污染, 对照区的行政村均属于轻污染, 其中Cd、Mn和Zn是导致污染指数偏高的主要原因.由表 1可知, 污染区及对照区土壤中Cd的潜在生态风险指数均达到了极强等级, 其余重金属生态风险为轻微等级.有学者调查北方或南方工矿业周边农田土壤同样发现Cd存在极强的潜在生态风险[21~23].由综合潜在生态风险指数知, 污染区和对照区的生态风险等级分别为极强和中等级.值得注意的是, Cd是造成潜在生态风险的主要因素, 其次为Pb和As.Mn虽然造成了较为严重的土壤重金属污染, 但潜在生态风险较低.

数字代表不同的行政村 图 5 土壤重金属单因子污染指数和综合污染指数 Fig. 5 Single-factor and composite pollution index of heavy metals in soil

表 1 污染区土壤潜在生态风险指数及综合潜在生态风险指数统计特征 Table 1 Descriptive statistics of potential risk coefficients and integrated potential ecological risk index of heavy metals in soils in the contaminated area and control area

2.2 作物中重金属含量

由表 2可知, 污染区大米和玉米中的Cr、Pb、Cd和Cu存在超标且超标率在3.3%~37.3%之间, Cd的超标率最低.大米中各超标重金属的含量均值低于玉米, 可能是因为水田在淹水条件下部分重金属生成了硫化物沉淀, 生物有效性有所降低[24].从变异系数来看, 粮食中Pb、Cr、Cu和Ni为高等变异(CV > 35%), Cd、Mn、As和Zn为弱变异(CV < 15%).可见土壤中污染越重的重金属, 对应粮食作物中含量越相近, 而重金属污染程度较轻的土壤中重金属生物有效性受空间分布、pH和有机质含量等土壤性质影响较大, 导致粮食作物中重金属各点位含量差异显著, 这也是对照区大米和玉米中Cr和Pb的均值含量高于污染区的可能原因, 因此土壤中重金属污染程度可能影响粮食作物对重金属的吸收富集[25, 26].进一步说明利用现行土壤环境质量标准及生态风险标准在评价特定粮食种植安全性时应考虑土壤中重金属的空间分布差异、生物有效性及赋存状态[27, 28].

表 2 污染区和对照区中大米和玉米重金属元素的含量水平/mg·kg-1 Table 2 Heavy metal contents in rice and maize produced in the pollution area and the control area/mg·kg-1

如表 3所示, 研究区蔬菜Pb、Cd、Cr和As存在超标, 超标率在1.1%~10.9%之间, 其中Cd和Pb的超标率较高, 叶菜类蔬菜各重金属含量均值高于根茎类蔬菜.污染区蔬菜中Cd和Zn的含量明显高于对照区.值得注意的是, 由于研究区土壤中Zn和Cu含量较高, 且蔬菜对于Zn和Cu的生物富集能力除低于Cd外远高于其余重金属, 直接导致研究区蔬菜中的ω(Zn)最高达15.6 mg·kg-1, ω(Cu)最高达5.71 mg·kg-1. ω(Cu)在空心菜中最高、ω(Zn)在红菜薹中最高, 过量摄入ω(Zn)和ω(Cu)过高的蔬菜对人体产生的健康风险未来也应值得关注[29].

表 3 污染区和对照区叶菜蔬菜及根茎蔬菜中重金属元素的含量水平/mg·kg-1 Table 3 Heavy metal contents in leaf and root vegetable produced in the pollution area and the control area/mg·kg-1

2.3 农作物对重金属的富集系数评价

不同农作物对重金属的富集能力一般存在着较大的差异[30, 31].如图 6所示, 污染区和对照区的叶菜类蔬菜和根茎类蔬菜均容易富集Cd、Cu和Zn, 其富集系数明显高于其他5种重金属, 这与张鹏帅等[32]调查福州市郊农田蔬菜中各重金属富集系数得出的结论一致.叶菜类蔬菜的重金属富集能力高于根茎类蔬菜, 这与孙硕等[33]调查河北省大棚蔬菜中重金属富集能力得出的结论一致, 可能是由于叶菜蔬菜发达的根系对重金属的吸收转运能力较强导致[34, 35].大米更容易富集Cd、Zn和Cr, 玉米更容易富集Zn、Cu和Cr, 与前人的研究结果较为一致[36].土壤污染程度会影响作物的富集能力, 其中土壤污染程度加深明显提高了农作物对Cd的富集能力, 降低了对Zn的富集能力.大米和玉米中Cr、Ni和Zn的富集系数明显高于蔬菜, 叶菜类蔬菜对Cd富集系数明显高于玉米和大米.在实际生产中, 应充分考虑农作物重金属累积特性以保证作物安全生产.

图 6 污染区和对照区大米、玉米和蔬菜对8种重金属的富集系数 Fig. 6 Biological concentration factors of rice, maize, and vegetables for eight heavy metals in the contaminated area and control area

2.4 土壤中重金属含量与农作物中重金属含量的相关性分析

为明确调查区土壤对农作物中重金属累积的影响, 根据土壤和农作物中重金属含量的测定结果, 对蔬菜和粮食中重金属含量与土壤中重金属含量进行Pearson相关性检验分析, 其结果列于表 4中.结果表明: 旱地土壤中8种重金属含量与叶菜类蔬菜、根茎类蔬菜及玉米中相应重金属含量呈正相关关系, 即土壤中重金属含量越高, 对应作物中含量也越高, 相关系数范围为0.662 8~0.800 8; 除了大米中Cd和As具有相关性外, 其余6种重金属与水田土壤重金属的含量不呈相关性, 与前人得出的结论基本一致[37, 38].说明土壤重金属在水稻生长过程中的迁移转化行为更加复杂[39].

表 4 污染区与对照区土壤与农作物中重金属含量之间的Pearson相关性分析1) Table 4 Relation analysis of Pearson regarding the heavy metal contents in soil and crops from the contaminated area and control area

3 结论

(1) 污染区周边农田土壤存在严重的Cd、Zn、As和Mn污染.由主成分分析可知Cd、Zn和Mn源于锰矿的生产活动, Cu、Ni、Cr和As源于农业活动如施肥及污水灌溉, Pb则源于上述两者活动的影响.

(2) 污染区河流上游两侧土壤中Cd、Mn、Zn、As和Pb等重金属浓度较高, 未来应加强河流中的重金属监测, 防范土壤中重金属通过雨水冲刷或下渗等方式向河流迁移.

(3) Cd、Mn和Zn是主要的污染因子, 污染区3个行政村土壤污染程度均为重污染, 对照区6个行政村土壤均为轻污染.研究区土壤中Cd均存在极强的潜在生态风险.未来除了加强对污染区Cd、Zn、As和Mn等重金属的修复, 还应开展对照区土壤及农作物协同监测, 进一步保障农产品质量安全.

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