Apply machine learning to predict greenhouse gas emissions in aerobic composting and achieve emission reduction by nanomembrane covering mode

with actual measurements under nanomembrane-covered conditions to quantify emission reduction. This study offers technical methods for manure fertilization and emission reduction in cold environments and provides a valuable reference for the application of aerobic composting mode with nanomembrane in the cold high-altitude regions of Northeast China.

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Publication Details

Journal
Waste Management
Published
2026-04-06
DOI
https://doi.org/10.1016/j.wasman.2026.115512
Primary Topic
Composting and Vermicomposting Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Apply machine learning to predict greenhouse gas emissions in aerobic composting and achieve emission reduction by nanomembrane covering mode

Hong Wang, Xiping Sun, Samuel Jin, Yu Xu et al.
Waste Management
Composting and Vermicomposting Techniques
article

Apply machine learning to predict greenhouse gas emissions in aerobic composting and achieve emission reduction by nanomembrane covering mode

Hong Wang, Xiping Sun, Samuel Jin, Yu Xu, Xuan Wang, Wei Zhao
article en

Abstract

with actual measurements under nanomembrane-covered conditions to quantify emission reduction. This study offers technical methods for manure fertilization and emission reduction in cold environments and provides a valuable reference for the application of aerobic composting mode with nanomembrane in the cold high-altitude regions of Northeast China.

Waste ManagementVol. 217
Northeast Agricultural University (CN), Cornell University (US), New York State College of Agriculture & Life Sciences (US), University of Pennsylvania (US)
Openalex Percentile: Top 23%
Composting and Vermicomposting Techniques
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