Meta-Analysis of Greenhouse Gas Emissions from Anaerobic Digestion Processes in Dairy Farms
This meta-analysis quantifies the changes in greenhouse gas (GHG) emissions from dairy farms, caused by anaerobically digesting (AD) cattle manure. As this is a novel quantifiable synthesis of the literature, a database of GHG emissions from dairy farms is created. Each case in the database consists...
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Published in | Environmental science & technology Vol. 49; no. 8; pp. 5211 - 5219 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
21.04.2015
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Subjects | |
Online Access | Get full text |
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Summary: | This meta-analysis quantifies the changes in greenhouse gas (GHG) emissions from dairy farms, caused by anaerobically digesting (AD) cattle manure. As this is a novel quantifiable synthesis of the literature, a database of GHG emissions from dairy farms is created. Each case in the database consists of a baseline (reference with no AD system) and an AD scenario. To enable interstudy comparison, emissions are normalized by calculating relative changes (RCs). The distributions of RCs are reported by specific GHGs and operation units. Nonparametric tests are applied to the RCs in order to identify a statistical difference of AD with respect to baseline scenarios (Wilcoxon rank test), correlations (Spearman test), and best estimation for changes in emissions (Kernel density distribution estimator). From 749 studies identified, 30 papers yield 89 independent cases. The median reductions in emissions from the baseline scenarios, according to operation units, are −43.2% (n.s.) for storage, −6.3% for field application of slurries, −11.0% for offset of energy from fossil fuel, and +0.4% (n.s.) for offset of inorganic fertilizers. The leaks from digesters are found to significantly increase the emissions from baseline scenarios (median = +1.4%). |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0013-936X 1520-5851 |
DOI: | 10.1021/acs.est.5b00018 |