Application of a combined approach including contamination indexes, geographic information system and multivariate statistical models in levels, distribution and sources study of metals in soils in Northern China

• Published in: PloS one 2018-02, Vol.13 (2), p.e0190906-e0190906
• Main Authors: Huang, Kuixian, Luo, Xingzhang, Zheng, Zheng
• Format: Article
• Language: English
• Subjects: Agricultural management; Airborne particulates; Algorithms; Biology and Life Sciences; Cadmium; Contamination; Data processing; Ecology and Environmental Sciences; Emissions; Engineering and Technology; Environmental aspects; Environmental management; Environmental science; Geochemistry; Geographic information systems; Geostatistics; Heavy metals; Industrial areas; Irrigation; Laboratories; Lead; Manufacturing; Mathematical models; Medicine and Health Sciences; Mercury; Mercury (metal); Metals; Metals (Materials); Multivariate analysis; Physical Sciences; Pollutants; Pollution; Pollution control; Pollution sources; Prevention; Principal components analysis; Remote sensing; Sediment pollution; Sediments; Soil contamination; Soil environment; Soil management; Soil pollution; Soil surfaces; Spatial distribution; Statistical analysis; Statistical methods; Statistical models; Trace metals; Zinc
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0190906

The purpose of this study is to recognize the contamination characteristics of trace metals in soils and apportion their potential sources in Northern China to provide a scientific basis for basic of soil environment management and pollution control. The data set of metals for 12 elements in surface soil samples was collected. The enrichment factor and geoaccumulation index were used to identify the general geochemical characteristics of trace metals in soils. The UNMIX and positive matrix factorizations (PMF) models were comparatively applied to apportion their potential sources. Furthermore, geostatistical tools were used to study the spatial distribution of pollution characteristics and to identify the affected regions of sources that were derived from apportionment models. The soils were contaminated by Cd, Hg, Pb and Zn to varying degree. Industrial activities, agricultural activities and natural sources were identified as the potential sources determining the contents of trace metals in soils with contributions of 24.8%-24.9%, 33.3%-37.2% and 38.0%-41.8%, respectively. The slightly different results obtained from UNMIX and PMF might be caused by the estimations of uncertainty and different algorithms within the models.