An innovative approach to visualizing heavy metal pollution risk in chernozem soils: Leveraging the fuzzy logic algorithm
Year: 2025
Type: article
Abstract: Effective management of heavy metal contamination in soils requires accurate identification of pollution sources and characteristics. This study developed a membership-function integrated model coupled with positive matrix factorization (PMF) to analyze contamination patterns through probabilistic source attribution. Results revealed that a mixed source of agricultural activities and atmospheric deposition were the dominant contributors to heavy metal contamination in the study area. These fertilizer applications and atmospheric deposition were the main anthropogenic sources of Cd, with contributions of 66.30% and 33.70%, respectively. By iteratively calculating membership values for each data point, the model resolved complex multi-source interactions, revealing that agricultural sources, particularly fertilizer use, drive polymetallic soil contamination. The source-specific comprehensive soil assessment highlighted that cadmium concentrations in long-term intensively cultivated croplands exceeded 0.16 mg kg−1, emphasizing the critical role of local, discrete contamination sources that might be overlooked in broader assessments. The integrated membership-function framework significantly mitigated uncertainties in source attribution arising from spatial heterogeneity and source intersection, providing a robust tool for targeted soil remediation.
Authors: Guohao Xie, Yang Yang, Yao Zhang, Tian Zhang, Weiping Chen
Language: English
Topic: Heavy metals in environment
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,400
Awards: G2382462870, G4363831155
OpenAlex ID: W7114794002