基于随机森林模型的土壤重金属源解析——以晋中盆地为例
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摘要
为了解晋中盆地土壤重金属污染现状及来源,测定了302个土壤样品中Pb、Cr、Cd、As和Hg五种重金属的含量,采用多元统计方法、地统计学方法和随机森林模型,分析了盆地内土壤重金属的污染状况和污染来源。结果表明:五种重金属含量均值都高于山西省背景值含量,其中As和Cr含量均值接近山西省背景值含量,Pb略高于山西土壤背景值、Cd和Hg则存在明显超标,其中Hg和Cd分别有11. 5%和60. 0%的样点超过国家土壤质量二级标准。源解析结果显示:As和Cr主要来源于土壤母质等自然源,Pb、Cd和Hg主要来源于工、农业生产等人为源。随机森林结果显示:影响Cd含量的主要因素重要性排序依次为土壤有机质含量、人均工业产值和土壤全氮含量,说明Cd的积累受工业活动和农业活动中化肥施用的共同影响;影响Hg含量的主要因素重要性排序依次为人均工业产值和污染企业距离,说明Hg主要来源于工业污染活动;影响Pb含量的主要因素重要性排序依次为道路距离、人均工业产值和污染企业距离,说明Pb既受交通运输的影响又受工业活动的影响。
To understand the status and sources of heavy metal pollution in soil in Jinzhong basin,the contents of Pb,Cr,Cd,As,and Hg in 302 soil samples were determined.The pollution status and sources of heavy metals in soil in the basin were analyzed by using multivariate statistical method,geostatistical method,and the random forest model.Results show that the mean contents of five heavy metals are all higher than the corresponding background values for Shanxi.Specifically,As and Cr content averages are close to background values.The content of Pb is slightly higher than that of soil background values in Shanxi.Cd and Hg contents are significantly above the standard,Hg and Cd in 11.5% and 60.0% of sample points,respectively,exceed the levels of national second-level soil quality standard.The results of source analysis show that As and Cr are mainly from natural sources like soil parent materials,whereas Pb,Cd,and Hg are mainly from artificial sources including industrial and agricultural production.The random forest model results show that the importance of the main factors affecting the Cd content follow the order of soil organic matter content,industrial output per capita,and soil total nitrogen content.This indicates that the accumulation of Cd is affected by combined effects of industrial activities and chemical fertilizer application in agricultural activities.The most important factor affecting the Hg content is per capita industrial output value,followed by distance from polluting enterprises,indicating that Hg is mainly from industrial pollution activities.The main factors affecting Pb content are ranked in the order of road distance,per capita industrial output value,and distance from polluting enterprises,indicating that Pb is affected by both transportation and industrial activities.
To understand the status and sources of heavy metal pollution in soil in Jinzhong basin,the contents of Pb,Cr,Cd,As,and Hg in 302 soil samples were determined.The pollution status and sources of heavy metals in soil in the basin were analyzed by using multivariate statistical method,geostatistical method,and the random forest model.Results show that the mean contents of five heavy metals are all higher than the corresponding background values for Shanxi.Specifically,As and Cr content averages are close to background values.The content of Pb is slightly higher than that of soil background values in Shanxi.Cd and Hg contents are significantly above the standard,Hg and Cd in 11.5% and 60.0% of sample points,respectively,exceed the levels of national second-level soil quality standard.The results of source analysis show that As and Cr are mainly from natural sources like soil parent materials,whereas Pb,Cd,and Hg are mainly from artificial sources including industrial and agricultural production.The random forest model results show that the importance of the main factors affecting the Cd content follow the order of soil organic matter content,industrial output per capita,and soil total nitrogen content.This indicates that the accumulation of Cd is affected by combined effects of industrial activities and chemical fertilizer application in agricultural activities.The most important factor affecting the Hg content is per capita industrial output value,followed by distance from polluting enterprises,indicating that Hg is mainly from industrial pollution activities.The main factors affecting Pb content are ranked in the order of road distance,per capita industrial output value,and distance from polluting enterprises,indicating that Pb is affected by both transportation and industrial activities.
引文
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[2]Khosravi Y,Zamani A A,Parizanganeh A H,et al. Assessment of spatial distribution pattern of heavy metals surrounding a lead and zinc production plant in Zanjan Province,Iran[J]. Geoderma Regional,2018,12:10-17.
[3]Li S,Jia Z. Heavy metals in soils from a representative rapidly developing megacity(SW China):Levels,source identification and apportionment[J]. Catena,2018,163:414-423.
[4]Jian L,Jiao W B,Qiu H Y,et al. Origin and spatial distribution of heavy metals and carcinogenic risk assessment in mining areas at You'xi County southeast China[J]. Geoderma,2018,310:99-106.
[5]Pan L B,Ma J,Wang X L,et al. Heavy metals in soils from a typical county in Shanxi Province,China:Levels,sources and spatial distribution[J]. Chemosphere,2016,148:248-254.
[6]Zhang G,Bai J,Zhao Q,et al. Heavy metals in wetland soils along a wetland-forming chronosequence in the Yellow River Delta of China:Levels,sources and toxic risks[J]. Ecological Indicators,2016,69:331-339.
[7]Wang L,Coles N A,Wu C,et al. Spatial variability of heavy metals in the coastal soils under long-term reclamation[J]. Estuarine Coastal&Shelf Science,2014,151:310-317.
[8]曾希柏,徐建明,黄巧云,等.中国农田重金属问题的若干思考[J].土壤学报,2013,50(1):186-194.
[9]Breiman L. Random Forests[J]. Machine Learning,2001,45(1):5-32.
[10]王奕森,夏树涛.集成学习之随机森林算法综述[J].信息通信技术,2018(1):49-55.
[11]宋志廷,赵玉杰,周其文,等.基于地质统计及随机模拟技术的天津武清区土壤重金属源解析[J].环境科学,2016,37(7):2756-2762.
[12]杨其坡,武伟,刘洪斌.基于地形因子和随机森林的丘陵区农田土壤有效铁空间分布预测[J].中国生态农业学报,2018,26(3):422-431.
[13]Zhang H,Wu P,Yin A,et al. Prediction of soil organic carbon in an intensively managed reclamation zone of eastern China:A comparison of multiple linear regressions and the random forest model[J]. Science of the Total Environment,2017,592:704-713.
[14]Wang Q,Xie Z,Li F. Using ensemble models to identify and apportion heavy metal pollution sources in agricultural soils on a local scale[J].Environmental Pollution,2015,206:227-235.
[15]Genuer R,Poggi J M,Tuleau-Malot C. Variable selection using random forests[J]. Pattern Recognition Letters,2010,31(14):2225-2236.
[16]Liaw A,Wiener M. Classification and regression by Random Forest[J]. R News,2002,2(3):18-22.
[17]国家统计局农村社会经济调查司.中国县域统计年鉴(乡镇卷)[R].北京:中国统计出版社,2015.
[18]史崇文,赵玲芝,郭新波,等.山西土壤元素背景值及其特征[J].华北地质矿产杂志,1994(2):188-196.
[19]陈毛华,高鹏,刘明广,等.基于GS+的阜阳市城郊菜地重金属空间分布研究[J].干旱区资源与环境,2017,31(8):148-152.
[20]方淑波,贾晓波,安树青,等.盐城海岸带土壤重金属潜在生态风险控制优先格局[J].地理学报,2012,67(1):27-35.
[21]张鹏岩,秦明周,闫江虹,等.黄河下游滩区开封段土壤重金属空间分异规律[J].地理研究,2013,32(3):421-430.
[22]Lei L,Ma Y B,Zhang S Z,et al. An inventory of trace element inputs to agricultural soils in China[J]. Journal of Environmental Management,2009,90(8):2524-2530.
[23]刘勇,张红,尹京苑.汾河太原段土壤中Hg、Cr空间分布与污染评价[J].农业工程学报,2008,24(5):57-60.
[24]李霞,张慧鸣,徐震,等.农田Cd和Hg污染的来源解析与风险评价研究[J].农业环境科学学报,2016,35(7):1314-1320.
[25]马东升,张辉.公路重金属污染的形态特征及其解吸、吸持能力探讨[J].环境化学,1998,17(6):564-568.
[26]宋波,曾炜铨.土壤有机质对镉污染土壤修复的影响[J].土壤通报,2015,46(4):1018-1024.
[27]Yan D,Wang D,Yang L. Long-term effect of chemical fertilizer,straw,and manure on labile organic matter fractions in a paddy soil[J]. Biology&Fertility of Soils,2007,44(1):93-101.
[28]麦麦提吐尔逊·艾则孜,阿吉古丽·马木提,艾尼瓦尔·买买提.新疆焉耆盆地辣椒地土壤重金属污染及生态风险预警[J].生态学报,2018,38(3):1075-1086.
[29]董辰寅,张卫国,王冠,等.上海宝山区城市土壤铅污染来源的同位素判别[J].环境科学,2012,33(3):754-759.