An approach to predict methane emissions from pig housing by developing surrogated models of mass transfer coefficient and methane concentration at slurry surface

Methane (CH 4 ) emissions from pig production are about 13% of the agricultural sector's total greenhouse gas (GHG) emissions. Most CH 4 emissions from pig farms originate from manure storage inside the pig housing and outdoor storage. Researchers have endeavoured to identify the mechanisms of CH 4 generation within manure. The knowledge generated from these studies is essential for understanding the mechanisms but is yet to be applied in practice, because, for example, sampling and analysis of manure are required. The objective of this study is to develop an approach to predict CH 4 emissions using computational fluid dynamics (CFD) to obtain sub-models of the mass transfer coefficient and, based on available experimental data from sections with two pig pens, CH 4 concentration at slurry surface. The inputs for predicting CH 4 concentration at slurry surface include pig weight, manure age and amount, climatic parameters such as temperature and humidity, ventilation rates, which can be easier to be monitored on site. The results show that the mass transfer coefficient of CH 4 is positively correlated with both ventilation rate and slurry volume. The sensitivity analysis shows CH 4 concentrations at the slurry surface are primarily influenced by slurry volume and slurry age. The models to estimate CH 4 emission is explicit, physically interpretable, and performs reasonably well under sidewall jet ventilation (R 2 of 0.88, RMSE of 1093.19 mg/h), while predictive accuracy declines under diffuse ceiling ventilation (R 2 of 0.78, RMSE of 1548.96 mg/h).

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Publication Details

Journal
Biosystems Engineering
Published
2026-06-26
DOI
https://doi.org/10.1016/j.biosystemseng.2026.104527
Primary Topic
Odor and Emission Control Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

An approach to predict methane emissions from pig housing by developing surrogated models of mass transfer coefficient and methane concentration at slurry surface

Li Rong, Chao Zong, Chenglong Wang, Guoqiang Zhang
Biosystems Engineering
Odor and Emission Control Technologies
article

An approach to predict methane emissions from pig housing by developing surrogated models of mass transfer coefficient and methane concentration at slurry surface

Li Rong, Chao Zong, Chenglong Wang, Guoqiang Zhang
article en

Abstract

Methane (CH 4 ) emissions from pig production are about 13% of the agricultural sector's total greenhouse gas (GHG) emissions. Most CH 4 emissions from pig farms originate from manure storage inside the pig housing and outdoor storage. Researchers have endeavoured to identify the mechanisms of CH 4 generation within manure. The knowledge generated from these studies is essential for understanding the mechanisms but is yet to be applied in practice, because, for example, sampling and analysis of manure are required. The objective of this study is to develop an approach to predict CH 4 emissions using computational fluid dynamics (CFD) to obtain sub-models of the mass transfer coefficient and, based on available experimental data from sections with two pig pens, CH 4 concentration at slurry surface. The inputs for predicting CH 4 concentration at slurry surface include pig weight, manure age and amount, climatic parameters such as temperature and humidity, ventilation rates, which can be easier to be monitored on site. The results show that the mass transfer coefficient of CH 4 is positively correlated with both ventilation rate and slurry volume. The sensitivity analysis shows CH 4 concentrations at the slurry surface are primarily influenced by slurry volume and slurry age. The models to estimate CH 4 emission is explicit, physically interpretable, and performs reasonably well under sidewall jet ventilation (R 2 of 0.88, RMSE of 1093.19 mg/h), while predictive accuracy declines under diffuse ceiling ventilation (R 2 of 0.78, RMSE of 1548.96 mg/h).

Biosystems EngineeringVol. 269
University of Idaho (US), Aarhus University (DK)
Innovationsfonden
Sustainable cities and communities
Openalex Percentile: Top 16%
Odor and Emission Control Technologies
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An approach to predict methane emissions from pig housing by developing surrogated models of mass transfer coefficient and methane concentration at slurry surface — Li Rong, Chao Zong, et al. · Biosystems Engineering (2026) | TGRS Research Map | TGRS