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Comparing CaCl2, EDTA and DGT methods to predict Cd and Ni accumulation in rice grains from contaminated soils.
Environ Pollut. 2020 May; 260:114042.EP

Abstract

Urbanization and industrialization have elevated metal concentrations in soils. However, systematic investigation on their availability in regional soils under industrial impacts is lacking. In this study, 230 paired soil-rice samples were collected from two areas in Southeast China, with low and high industrial impacts. Classic equilibrium-based CaCl2 and EDTA extraction methods, and dynamic-based diffusive gradients in thin-films (DGT) technique were used to study metal availability in soils, with the results being compared with metal concentrations in soils and rice grains. Generally, Cd, Ni, Cu, Zn, Cr and Pb concentrations in soils exceeded the Chinese Soil Quality Standard (GB15618-2018), whereas only Cd and Ni in some rice grains exceeded the Chinese Safety Guidelines. CaCl2 and EDTA extractions, DGT method and soil total metal concentrations provided good predication of grain Cd (R = 0.51-0.66, p < 0.01), whereas only CaCl2 and DGT tests provided good predication of grain Ni (R = 0.36-0.47, p < 0.01). Overall, CaCl2 extraction best predicted Cd and Ni accumulation in rice grains, explaining 66% of grain Cd and 47% of grain Ni. The extraction rate of available Cd was higher than that of Ni, indicating higher Cd availability than Ni, consistent with the parameters (response time, Tc, and desorption rate, k-1) from DIFS (DGT-induced flux in soils) model and bioconcentration factor values. This study showed that, at regional scale, CaCl2 extraction method is efficient in predicting Cd and Ni accumulation in rice grains from contaminated soils.

Authors+Show Affiliations

Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing, 210023, China.Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing, 210023, China.Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing, 210023, China; Institute of Surface-Earth System Science, Tianjin University, Tianjin, 300072, China. Electronic address: dxguan@tju.edu.cn.Institute of Surface-Earth System Science, Tianjin University, Tianjin, 300072, China.Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing, 210023, China.Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32000029

Citation

Ma, Qiang, et al. "Comparing CaCl2, EDTA and DGT Methods to Predict Cd and Ni Accumulation in Rice Grains From Contaminated Soils." Environmental Pollution (Barking, Essex : 1987), vol. 260, 2020, p. 114042.
Ma Q, Zhao W, Guan DX, et al. Comparing CaCl2, EDTA and DGT methods to predict Cd and Ni accumulation in rice grains from contaminated soils. Environ Pollut. 2020;260:114042.
Ma, Q., Zhao, W., Guan, D. X., Teng, H. H., Ji, J., & Ma, L. Q. (2020). Comparing CaCl2, EDTA and DGT methods to predict Cd and Ni accumulation in rice grains from contaminated soils. Environmental Pollution (Barking, Essex : 1987), 260, 114042. https://doi.org/10.1016/j.envpol.2020.114042
Ma Q, et al. Comparing CaCl2, EDTA and DGT Methods to Predict Cd and Ni Accumulation in Rice Grains From Contaminated Soils. Environ Pollut. 2020;260:114042. PubMed PMID: 32000029.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Comparing CaCl2, EDTA and DGT methods to predict Cd and Ni accumulation in rice grains from contaminated soils. AU - Ma,Qiang, AU - Zhao,Wanfu, AU - Guan,Dong-Xing, AU - Teng,H Henry, AU - Ji,Junfeng, AU - Ma,Lena Q, Y1 - 2020/01/22/ PY - 2019/12/16/received PY - 2020/01/19/revised PY - 2020/01/21/accepted PY - 2020/1/31/pubmed PY - 2020/6/20/medline PY - 2020/1/31/entrez KW - Chemical extractions KW - Diffusive gradients in thin-films (DGT) KW - Industrial pollution KW - Paddy soils KW - Toxic metals SP - 114042 EP - 114042 JF - Environmental pollution (Barking, Essex : 1987) JO - Environ Pollut VL - 260 N2 - Urbanization and industrialization have elevated metal concentrations in soils. However, systematic investigation on their availability in regional soils under industrial impacts is lacking. In this study, 230 paired soil-rice samples were collected from two areas in Southeast China, with low and high industrial impacts. Classic equilibrium-based CaCl2 and EDTA extraction methods, and dynamic-based diffusive gradients in thin-films (DGT) technique were used to study metal availability in soils, with the results being compared with metal concentrations in soils and rice grains. Generally, Cd, Ni, Cu, Zn, Cr and Pb concentrations in soils exceeded the Chinese Soil Quality Standard (GB15618-2018), whereas only Cd and Ni in some rice grains exceeded the Chinese Safety Guidelines. CaCl2 and EDTA extractions, DGT method and soil total metal concentrations provided good predication of grain Cd (R = 0.51-0.66, p < 0.01), whereas only CaCl2 and DGT tests provided good predication of grain Ni (R = 0.36-0.47, p < 0.01). Overall, CaCl2 extraction best predicted Cd and Ni accumulation in rice grains, explaining 66% of grain Cd and 47% of grain Ni. The extraction rate of available Cd was higher than that of Ni, indicating higher Cd availability than Ni, consistent with the parameters (response time, Tc, and desorption rate, k-1) from DIFS (DGT-induced flux in soils) model and bioconcentration factor values. This study showed that, at regional scale, CaCl2 extraction method is efficient in predicting Cd and Ni accumulation in rice grains from contaminated soils. SN - 1873-6424 UR - https://www.unboundmedicine.com/medline/citation/32000029/Comparing_CaCl2_EDTA_and_DGT_methods_to_predict_Cd_and_Ni_accumulation_in_rice_grains_from_contaminated_soils_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0269-7491(19)37553-0 DB - PRIME DP - Unbound Medicine ER -