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Identified factors and predicted unidentified-factors affecting ammonia emissions from a swine building
Large variabilities in ammonia (NH3) released from animal manure and emitted from different livestock buildings were frequently reported, but the factors influencing the emissions were not sufficiently investigated. In this paper, continuously monitored data of NH3 emissions and other relevant envir...
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Published in: | Journal of hazardous materials 2023-07, Vol.453, p.131365-131365, Article 131365 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Large variabilities in ammonia (NH3) released from animal manure and emitted from different livestock buildings were frequently reported, but the factors influencing the emissions were not sufficiently investigated. In this paper, continuously monitored data of NH3 emissions and other relevant environmental variables under controlled conditions in a 12-room experimental swine building for a 155-d complete wean-to-finish cycle were studied. Measurement data mining was conducted at both spatial and temporal dimensions using panel data analysis with heterogeneous time trends. The pig diet, total pig weight, and the pit air temperature were identified as the major influencing factors for the variabilities by using multivariate linear regression. Two unidentified factors that imposed substantial influences on the NH3 emission variabilities were predicted. They were most possibly related to variations in microenvironment and microbial activity inside the manure in the pit. The results suggest necessary future research to identify physical properties of the new NH3 emissions factors in microbiological and biochemical processes.
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•Data of 155 days ammonia (NH3) emissions from a research swine building were mined.•Pig diet, total pig weight, and pit air temperature were identified as the major influencing factors.•Two unidentified factors influencing NH3 emissions were predicted using panel data analysis. |
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ISSN: | 0304-3894 1873-3336 |
DOI: | 10.1016/j.jhazmat.2023.131365 |