Predicting the environmental fate of biodegradable mulch films: A machine learning approach for sustainable agriculture.

Journal: Journal of hazardous materials
Published Date: Apr 13, 2025

Abstract

Biodegradable plastic mulch films (BDM) have been proposed as one of the dominant strategies for plastic pollution prevention in agriculture. As the BDM degradation is a complex process affected by multiple factors, the degradation cycle of BDM has significant regional differences ranging from months to years, resulting in its mismatch to the crop cycle. Existing works focus on only a few influencing factors as it is too laborious to elaborate on all the factors by experiments, limiting our comprehensive understanding of BDM degradation. Here, we integrated meta-analysis with a machine-learning approach to quantify the impacts of multiple factors and develop a prediction model on BDM degradation. 24 influencing factors, including material composition, weather, soil properties, microbial activity, and other factors, were reorganized systematically and quantified for the first time. The established machine learning model enables the prediction of the regional BDM degradation rate for over 2800 counties/districts in China, which has a vast geographical distribution and diverse climatic characteristics. In this work, our study provides deeper insights into current understanding of BDM degradation and paves the way for future investigations into the environmental degradation of biodegradable materials, offering critical insights for environmental management and policy-making in agriculture.

Authors

  • Shan Chen
    National Academy of Economic Security, Beijing Jiaotong University, Beijing 100044, China.
  • Guohailin Xu
    Institute of Agricultural Engineering, Jiangsu University, Zhenjiang 212001, China.
  • Jingwen Chen
    Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China. Electronic address: jwchen@dlut.edu.cn.
  • Hui Zhang
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Xizhi Jiang
    Institute of Agricultural Facilities and Engineering Technology Research Center of Biomass Composites and Addictive Manufacturing, Key Laboratory for Protected Agricultural Engineering in the Middle and Lower Reaches of Yangtze River, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Facilities and Equipment, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu 210014, China.
  • Ziwen Liu
    Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Zhiwei Lin
    State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
  • Congzhi Zhang
    Fengqiu Experimental Station of National Ecosystem Research Network of China, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 211135, China.
  • Lei Xu
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
  • Jiabao Zhang
    Fengqiu Experimental Station of National Ecosystem Research Network of China, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 211135, China. Electronic address: jbzhang@issas.ac.cn.

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