滨海开发带土壤重金属分布特征及来源分析
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摘要
以江苏省大丰市为例,研究了土壤中8种重金属的空间分布特征及其与土地利用的关系,并通过主成分分析方法,对其可能的来源进行了探讨。结果表明:研究区8种土壤重金属Cu、Zn、Pb、Cd、Cr、As、Hg、Ni平均含量分别为17.40、74.38、18.14、0.105、55.58、8.33、0.074、25.73mg/kg,不同采样点之间变异不大。沿垂直海岸线方向,随距海岸线距离增加,Cu、Zn、Pb、Cr、Hg、Ni 6种重金属含量逐渐升高,As含量逐渐降低,Cd含量则先升高、后降低。Cu、Zn、Pb、Cr、Hg、Ni 6种重金属均在水田土壤中含量最高,Cd在旱地土壤中含量最高,As则在滩涂土壤中含量最高。相关分析表明,土壤As含量与其他重金属元素含量的相关性均不显著,土壤Cd含量与Zn、Pb、Hg、Cr含量的相关性显著,与Cu、As、Ni含量的相关性不显著,其他各元素间相关性均达极显著水平。基于主成分分析结果,认为研究区土壤Cu、Zn、Pb、Cr、Hg、Ni 6种重金属元素含量受土壤母质影响较大,Cd含量与农业生产中磷肥施用关系密切,As含量的累积受磷肥施用的影响,但以水稻种植为主的耕作土壤As含量总体上呈下降趋势。本研究可为滨海开发带土地利用规划提供指导。
A case study of Dafeng City of Jiangsu Province was carried out to explore soil heavy metal pollution in the coast development zone. A total of 162 topsoil samples were collected in 2014, the contents of Cu, Zn, Pb, Cd, Cr, As, Hg and Ni were measured, the spatial distribution characteristics and the correlation of heavy metals with the land use were studied, and the possible sources of these heavy metals were discussed by the principal component analysis. The results showed that the average contents of Cu, Zn, Pb, Cd, Cr, As, Hg and Ni were 17.40, 74.38, 18.14, 0.105, 55.58, 8.33, 0.074 and 25.73 mg/kg, respectively,and with the little coefficient variation between the different sampling points. Cu, Zn, Pb, Cr, Hg and Ni gradually increased in three areas of 0–15 m, 15–30 km and 30–45 km from the coast to inland along the vertical direction of the coastline, while As gradually decreased and Cd first increased and then decreased. The highest contents of Cu, Zn, Pb, Cr, Hg and Ni were all in paddy soil, the highest content of Cd in dryland soil, and the highest content of As in beach land soil. As was not significantly correlated with the other heavy metals, Cd was extremely significantly correlated(P<0.01) with Zn, Pb, Hg and Cr, while Cd was not significantly correlated with Cu, As and Ni. The principal component analysis showed that the accumulation of Cu, Zn, Pb, Cr,Hg and Ni in soil were more affected by soil parent material, the accumulation of Cd affected by phosphate fertilization, the accumulation of As also affected a little by phosphate fertilization, while rice planting may decrease the content of soil As. The findings can provide guidance for land use planning of coastal development zone.
A case study of Dafeng City of Jiangsu Province was carried out to explore soil heavy metal pollution in the coast development zone. A total of 162 topsoil samples were collected in 2014, the contents of Cu, Zn, Pb, Cd, Cr, As, Hg and Ni were measured, the spatial distribution characteristics and the correlation of heavy metals with the land use were studied, and the possible sources of these heavy metals were discussed by the principal component analysis. The results showed that the average contents of Cu, Zn, Pb, Cd, Cr, As, Hg and Ni were 17.40, 74.38, 18.14, 0.105, 55.58, 8.33, 0.074 and 25.73 mg/kg, respectively,and with the little coefficient variation between the different sampling points. Cu, Zn, Pb, Cr, Hg and Ni gradually increased in three areas of 0–15 m, 15–30 km and 30–45 km from the coast to inland along the vertical direction of the coastline, while As gradually decreased and Cd first increased and then decreased. The highest contents of Cu, Zn, Pb, Cr, Hg and Ni were all in paddy soil, the highest content of Cd in dryland soil, and the highest content of As in beach land soil. As was not significantly correlated with the other heavy metals, Cd was extremely significantly correlated(P<0.01) with Zn, Pb, Hg and Cr, while Cd was not significantly correlated with Cu, As and Ni. The principal component analysis showed that the accumulation of Cu, Zn, Pb, Cr,Hg and Ni in soil were more affected by soil parent material, the accumulation of Cd affected by phosphate fertilization, the accumulation of As also affected a little by phosphate fertilization, while rice planting may decrease the content of soil As. The findings can provide guidance for land use planning of coastal development zone.
引文
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[23]雷鸣,曾敏,廖柏寒,等.含磷物质对水稻吸收土壤砷的影响[J].环境科学,2014,35(8):3149-3154
[24]邱孟龙,李芳柏,王琦,等.工业发达城市区域耕地土壤重金属时空变异与来源变化[J].农业工程学报,2015,32(2):298-305
[25]徐明露,方凤满,林跃胜.湿地土壤重金属污染特征、来源及风险评价研究进展[J].土壤通报,2015,46(3):762-768
[26]Xie Z L,Zhao G S,Sun Z G.Comparison of arsenic and heavy metals contamination between existing wetlands and wetlands created by river diversion in the Yellow River estuary,China[J].Environmental Earth Sciences,2014,65(5):1459-1473
[27]王天巍,蔡崇法,李朝霞,等.道路边际土壤重金属分布格局的神经网络模拟--以现代黄河三角洲为例[J].生态学报,2009,29(6):3154-3162
[28]施加春.浙北环太湖平原不同尺度土壤重金属污染评价与管理信息系统构建[D].杭州:浙江大学,2006
[29]郑袁明,罗金发,陈同斌,等,周建利.北京市不同土地利用类型的土壤镉含量特征[J].地理研究,2005,24(4):542-548
[30]张慧,郑志志,杨欢,等.基于多元统计和地统计的肇源县表层土壤重金属来源辨析[J].土壤,2017,49(4):819-827
[31]宋金茜,朱权,姜小三,等.基于GIS的农业土壤重金属风险评价研究--以南京市八卦洲为例[J].土壤学报,2017,54(1):81-91
[2]陈怀满.土壤中化学物质的行为与环境质量[M].北京:科学出版社,2002
[3]Sahu S J,Nath B,Roy S,et al.A laboratory batch study on arsenic sorption and desorption on guava orchard soils of Baruipur,West Bengal,India[J]Journal of Geochemical Exploration,2011,108(2):157-162
[4]王娜娜,齐伟,王丹,等.基于样带的滨海盐碱地土壤养分和盐分的空间变异[J].应用生态学报,2012,23(6):1527-1532
[5]傅伯杰,周国逸,白永飞,等.中国主要陆地生态系统服务功能与生态安全[J].地球科学进展,2009,24(6):571-576
[6]张利,陈影,王树涛,等.滨海快速城市化地区土地生态安全评价与预警--以曹妃甸新区为例[J].应用生态学报,2015,26(8):2445-2454
[7]刘志杰,李培英,张晓龙,等.黄河三角洲滨海湿地表层沉积物重金属区域分布及生态风险评价[J].环境科学,2012,33(4):1182-1188
[8]姚荣江,杨劲松,谢文萍,等.苏北滨海滩涂区土壤重金属含量及其时空变异研究[J].中国环境科学,2016,36(6):1810-1820
[9]陈穗玲,李锦文,陈南,等.福建沿海地区农田土壤重金属Hg、Pb、Cd区域分布特征与污染评价[J].环境化学,2013,32(1):162-163
[10]方杰.浙江沿海沉积物和海洋生物中持久性有机污染物及重金属的分析与研究[D].杭州:浙江大学,2007
[11]鲍士旦.土壤农化分析(第3版)[M].北京:中国农业出版社,2000
[12]徐建华.现代地理学中的数学方法(第2版)[M].北京:高等教育出版社,2002
[13]伊元荣,海米提·依米提,王涛,等.主成分分析在城市河流水质评价中的应用[J].干旱区研究,2008,25(4):497-501
[14]刘潇,薛莹,纪毓鹏,等.基于主成分分析法的黄河口及其邻近水域水质评价[J].中国环境科学,2015,35(10):3187-3192
[15]赵彦锋,郭恒亮,孙志英,等.基于土壤学知识的主成分分析判断土壤重金属来源[J].地理科学,2008,28(1):45-50
[16]Boruvka L,Vacek O,Jehlicka J.Principal component analysis as a tool to indicate the origin of potentially toxic elements in soils[J].Geoderma,2005,128(3):289-300
[17]付传城,王文勇,潘剑君,等.城乡结合带土壤重金属时空变异特征与源解析--以南京市柘塘镇为例[J].土壤学报,2014,51(5):1066-1077
[18]Korre A.Statistical and spatial assessment of soil heavy metal contamination in areas of poorly recorded,complex sources of pollution[J].Stochastic Environmental Research and Risk Assessment,1999,13(4):260-287
[19]Facchinelli A,Sacchi E,Mallen L.Multivariate statistical and GIS-based approach to identify heavy metal sources in soils[J].Environmental pollution,2001,114(3):313-324
[20]许仙菊,马洪波,陈杰,等.基于养分丰缺诊断和主成分分析相结合的桑园土壤肥力评价[J].土壤,2013,45(3):470-476
[21]国家环境保护总局.土壤环境质量标准(GB 15618-1995).北京:中国环境科学出版社,1995
[22]柴世伟,温琰茂,韦献革,等.珠江三角洲主要城市郊区农业土壤的重金属含量特征[J].中山大学学报(自然科学版),2004,43(4):90-94
[23]雷鸣,曾敏,廖柏寒,等.含磷物质对水稻吸收土壤砷的影响[J].环境科学,2014,35(8):3149-3154
[24]邱孟龙,李芳柏,王琦,等.工业发达城市区域耕地土壤重金属时空变异与来源变化[J].农业工程学报,2015,32(2):298-305
[25]徐明露,方凤满,林跃胜.湿地土壤重金属污染特征、来源及风险评价研究进展[J].土壤通报,2015,46(3):762-768
[26]Xie Z L,Zhao G S,Sun Z G.Comparison of arsenic and heavy metals contamination between existing wetlands and wetlands created by river diversion in the Yellow River estuary,China[J].Environmental Earth Sciences,2014,65(5):1459-1473
[27]王天巍,蔡崇法,李朝霞,等.道路边际土壤重金属分布格局的神经网络模拟--以现代黄河三角洲为例[J].生态学报,2009,29(6):3154-3162
[28]施加春.浙北环太湖平原不同尺度土壤重金属污染评价与管理信息系统构建[D].杭州:浙江大学,2006
[29]郑袁明,罗金发,陈同斌,等,周建利.北京市不同土地利用类型的土壤镉含量特征[J].地理研究,2005,24(4):542-548
[30]张慧,郑志志,杨欢,等.基于多元统计和地统计的肇源县表层土壤重金属来源辨析[J].土壤,2017,49(4):819-827
[31]宋金茜,朱权,姜小三,等.基于GIS的农业土壤重金属风险评价研究--以南京市八卦洲为例[J].土壤学报,2017,54(1):81-91