Use of machine-learning and receptor models for prediction and source apportionment of heavy metals in coastal reclaimed soils

被引:67
作者
Zhang, Huan [1 ,2 ]
Yin, Aijing [3 ]
Yang, Xiaohui [4 ]
Fan, Manman [1 ]
Shao, Shuangshuang [1 ]
Wu, Jingtao [1 ]
Wu, Pengbao [5 ]
Zhang, Ming [6 ]
Gao, Chao [1 ]
机构
[1] Nanjing Univ, Sch Geog & Ocean Sci, Nanjing 210023, Peoples R China
[2] Inst Land Surveying & Planning Jiangsu, Key Lab Coastal Zone Exploitat & Protect, Minist Nat Resources, Nanjing 210096, Peoples R China
[3] Minist Ecol & Environm, Nanjing Inst Environm Sci, Nanjing 210042, Peoples R China
[4] Linyi Univ, Coll Resources & Environm, Shandong Prov Key Lab Water & Soil Conservat & En, Linyi 276000, Shandong, Peoples R China
[5] Huizhou Univ, Sch Geog & Tourism, Huizhou 516007, Guangdong, Peoples R China
[6] China Geol Survey, Nanjing Ctr, Nanjing 210000, Peoples R China
基金
中国国家自然科学基金;
关键词
Source apportionment; Spatial prediction; Heavy metal; Random forest; Positive matrix factorization; AGRICULTURAL SOILS; ORGANIC-MATTER; SOURCE IDENTIFICATION; POLLUTION SOURCES; EASTERN CHINA; STOCHASTIC-MODELS; COPPER-SULFATE; TRACE-ELEMENTS; SURFACE SOILS; RIVER ESTUARY;
D O I
10.1016/j.ecolind.2020.107233
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Quantitative estimations of sources and spatial distribution of soil heavy metals (HMs) is essential for strategizing policies for soil protection and remediation. As a special soil ecosystem, the intensified human activities on coastal reclaimed lands generally causes soil contamination with HMs. This study aimed to apportion sources of HMs and predict their spatial distributions on coastal reclaimed lands. A total of 241 surface (0-20 cm) soil and sediment samples were collected from a reclamation zone following intensive agricultural use of eastern China. The concentrations of soil and sediment As, Cr, Cu, Ni, Pb, Zn, Cd, and Hg were measured along with organic carbon, nitrogen, phosphorus, pH, Cl, clay, silt, sand, CaO, Fe2O3, Al2O3, and SiO2. The potential sources of HMs were identified and apportioned using random forest (RF) and positive matrix factorization (PMF) models. According to the models, natural and a portion of anthropogenic sources, agricultural activities, and human emission from solar power generation and vehicle exhaust contributed 42.9%, 28.9%, and 28.2% of the total HMs, respectively. Separately, 65.0% of As, 36.6% of Cr, 49.1% of Cu, 46.4% of Ni, 39.5% of Pb, and 44.0% of Zn were originated from natural and some anthropogenic sources. Agricultural activities contributed 54.9% of Cd and 46.4% of Hg to the reclaimed soils. Emissions from solar power generation and vehicle exhaust had significant influences on Cr and Pb, with contributions of 39.0% and 28.0%, respectively. Furthermore, the RF model yielded satisfying results in predicting HM distributions based on the measurement of soil variables. When only considering independent variables, the RF model revealed slightly lower but still satisfactory abilities in HMs prediction. In reclaimed soils, the temporal increase and close relationship between soil Cd and phosphorus signified the potential threats of Cd contamination in coastal reclaimed soils. Therefore, the applications of Cdrich phosphoric fertilizers should be considered with high concern.
引用
收藏
页数:11
相关论文
共 99 条
[11]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[12]   Impacts of aerosol compositions on visibility impairment in Xi'an, China [J].
Cao, Jun-ji ;
Wang, Qi-yuan ;
Chow, Judith C. ;
Watson, John G. ;
Tie, Xue-xi ;
Shen, Zhen-xing ;
Wang, Ping ;
An, Zhi-sheng .
ATMOSPHERIC ENVIRONMENT, 2012, 59 :559-566
[13]   Mechanisms and pathways of trace element mobility in soils [J].
Carrillo-Gonzalez, R. ;
Simunek, Jirka ;
Sauve, Sebastien ;
Adriano, Domy .
ADVANCES IN AGRONOMY, VOL 91, 2006, 91 :111-178
[14]  
Chen B. B., 1985, J NANJING AGR U, V8, P54
[15]   Metal concentrations and mobility in marine sediment and groundwater in coastal reclamation areas: A case study in Shenzhen, China [J].
Chen, Kouping ;
Jiao, Jiu J. .
ENVIRONMENTAL POLLUTION, 2008, 151 (03) :576-584
[16]   Investigation of sources of atmospheric aerosol at urban and suburban residential areas in Thailand by positive matrix factorization [J].
Chueinta, W ;
Hopke, PK ;
Paatero, P .
ATMOSPHERIC ENVIRONMENT, 2000, 34 (20) :3319-3329
[17]  
Environmental Protection Agency, 2014, EPA POS MATR FACT VE
[18]   Multivariate statistical and GIS-based approach to identify heavy metal sources in soils [J].
Facchinelli, A ;
Sacchi, E ;
Mallen, L .
ENVIRONMENTAL POLLUTION, 2001, 114 (03) :313-324
[19]   Source identification of heavy metals in pastureland by multivariate analysis in NW Spain [J].
Franco-Uria, Arnaya ;
Lopez-Mateo, Cristina ;
Roca, Enrique ;
Luisa Fernandez-Marcos, Maria .
JOURNAL OF HAZARDOUS MATERIALS, 2009, 165 (1-3) :1008-1015
[20]   Influence of temperature and salinity on heavy metal uptake by submersed plants [J].
Fritioff, Å ;
Kautsky, L ;
Greger, M .
ENVIRONMENTAL POLLUTION, 2005, 133 (02) :265-274