Application of machine learning and multivariate approaches for source apportionment and risks of hazardous elements in the cropland soils near industrial areas in Bangladesh

Application of machine learning and multivariate approaches for source apportionment and risks of hazardous elements in the cropland soils near industrial areas in Bangladesh

Quick industrial and urban development accelerates the hazardous elements (HEs) content in agricultural soil which is a matter of concern for ecological and public health. This present study investigates the HEs content (As, Pb, Cd, Cr, Ni, and Cu) in agricultural fields near industrial areas of Ban...

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Bibliographic Details
Main Authors: Tapos Kumar Chakraborty, Most. Zaima Mobaswara, Md. Simoon Nice, Khandakar Rashedul Islam, Baytune Nahar Netema, Md. Sozibur Rahman, Ahsan Habib, Samina Zaman, Gopal Chandra Ghosh, Khadiza Tul-Coubra, Asadullah Munna, Md Shahnul Islam, Md Ripon Hossain, Sujoy Sen, Monishanker Halder, Abu Shamim Khan
Format: Article
Language:English
Published: Elsevier 2023-10-01
Series:Ecological Indicators
Subjects:
Hazardous elements
Agricultural soil
Public and ecological health
Pollution
Machine learning approaches
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X23009986

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http://www.sciencedirect.com/science/article/pii/S1470160X23009986

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