Semantic Scholar Open Access 2019 103 sitasi

Fuzzy synthetic evaluation and health risk assessment quantification of heavy metals in Zhangye agricultural soil from the perspective of sources.

Rui Zhao Qingyu Guan Haiping Luo Jinkuo Lin Liqin Yang +3 lainnya

Abstrak

Heavy metals in agricultural soil receive much attention because they are easily absorbed by crop into the ecosystem. Managing the discharge of heavy metals from the source is an effective way to prevent and control heavy metals pollution. Grouped principal component analysis (GPCA) and Positive Matrix Factorization (PMF) receptor models were utilized in this study to conduct source apportionment, and the former was optimal because of the accuracy of predicting. Based on the source contribution by GPCA/APCS, heavy metals were evaluated by fuzzy synthetic evaluation model and health risk assessment model. The results of source apportionment showed that heavy metals in Zhangye agricultural soil were mainly affected by steel industry, traffic, agrochemicals, manures, mining activities, leather industry and metal processing industry source. Fuzzy synthetic evaluation showed that the pollution levels of Chromium (Cr) derived by leather industry and metal processing industry and Nickel (Ni) derived by steel industry and traffic source were higher. Health risk assessment revealed that the non-carcinogenic and carcinogenic risks of Cr derived by leather industry and metal processing industry and Lead (Pb) derived by steel industry and traffic source were higher.

Penulis (8)

R

Rui Zhao

Q

Qingyu Guan

H

Haiping Luo

J

Jinkuo Lin

L

Liqin Yang

F

Feifei Wang

N

Ninghui Pan

Y

Yanyan Yang

Format Sitasi

Zhao, R., Guan, Q., Luo, H., Lin, J., Yang, L., Wang, F. et al. (2019). Fuzzy synthetic evaluation and health risk assessment quantification of heavy metals in Zhangye agricultural soil from the perspective of sources.. https://doi.org/10.1016/j.scitotenv.2019.134126

Akses Cepat

Informasi Jurnal
Tahun Terbit
2019
Bahasa
en
Total Sitasi
103×
Sumber Database
Semantic Scholar
DOI
10.1016/j.scitotenv.2019.134126
Akses
Open Access ✓