title: Spatial patterns and origins of heavy metals in Sheyang River catchment in Jiangsu, China based on geographically weighted regression.
abstract: Multivariate statistical analyses combined with geographically weighted regression (GWR) were used to identify spatial variations of heavy metals in sediments and to examine relationships between metal pollution and land use practices in watersheds, including urban land, agriculture land, forest and water bodies. Seven metals (Cu, Zn, Pb, Cr, Ni, Mn and Fe) of sediments were measured at 31 sampling sites in Sheyang River. Most metals were under a certain degree enrichment based on the enrichment factors. Cluster analysis grouped all sites into four statistically significant cluster, severely contaminated areas were concentrated in areas with intensive human activities. Correlation analysis and PCA indicated Cu, Zn and Pb were derived from anthropogenic activities, while the sources of Cr and Ni were complicated. However, Fe and Mn originated from natural sources. According to results of GWR, there are stronger association between metal pollution with urban land than agricultural land and forest. Moreover, the relationships between land use and metal concentration were affected by the urbanization level of watersheds. Agricultural land had a weak associated with heavy metal pollution and the relationships might be stronger in less-urbanized. This study provided useful information for the assessment and management of heavy metal hazards in studied area.
authors.affiliation: School of Geographical Science, Nanjing Normal University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China; Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, Jiangsu 210023, China; State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China.
authors.forename: Shan-Shan
authors.initials: SS
authors.lastname: Wu
authors.affiliation: School of Geographical Science, Nanjing Normal University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China; Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, Jiangsu 210023, China; State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Yang
authors.affiliation: School of Geographical Science, Nanjing Normal University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China; Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, Jiangsu 210023, China; State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Guo
authors.affiliation: School of Geographical Science, Nanjing Normal University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China; Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, Jiangsu 210023, China; State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China. Electronic address: ruiminghan@njnu.edu.cn.
authors.forename: Rui-Ming
authors.initials: RM
authors.lastname: Han
keywords: Enrichment factor; Geographically weighted regression; Heavy metal; Land use; Multivariate statistical analyses; Sheyang River