期刊
JOURNAL OF HAZARDOUS MATERIALS
卷 360, 期 -, 页码 32-42出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhazmat.2018.07.075
关键词
Farmland; Reactive heavy metal (RHM); Pollution characteristics; Predictive models; Absolute principal component score with multiple linear regression (APCS-MLR)
资金
- National Water Grant Major Science and Technology Program for Water Pollution Control and Treatment [2017ZX07202002]
- Shenzhen Science and Innovation Commission [JSGG20160428181710653, JSGG20170412145935322]
- Development and Reform Commission of Shenzhen Municipality
Recently, soil contamination by heavy metals in farmland has become a severe problem. In this study, a novel assessment method of heavy metal pollution based on reactive heavy metals (RHMs) was introduced. RHMs showed strong correlation with soil profile and land use, distinctly different from the variation of total heavy metals. According to modified geoaccumulation and Hakanson index, farmlands in study area were certainly polluted by various heavy metals, but had low ecological risk. RHMs were greatly influenced by soil properties such as nitrogen, phosphorus, organic matter (OM), pH, moisture content, cation exchange capacity (CEC), electrical conductivity, inorganic anion, and soil texture. Freundlich-type empirical models were developed by combining pH, OM, CEC, total phosphorus, and clay for sufficiently robust and accurate prediction of RHM contents in farmland. The absolute principal component score with multiple linear regression (APCS-MLR) model was used to quantify sources of RHMs in farmland. Agricultural production (water-fertilizer management practice and fertilizer/pesticide use) was the major influence on RHMs with contributions greater than 50% for Fe, Cu, Zn, Pb, and As. Industrial activity, traffic emission, and soil erosion should be also given special attentions because of their great influence on soil RHM contents.
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