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Understanding methane emission from stored animal manure: A review to guide model development
Author(s) -
Dalby Frederik R.,
Hafner Sasha D.,
Petersen Søren O.,
VanderZaag Andrew C.,
Habtewold Jemaneh,
Dunfield Kari,
Chantigny Martin H.,
Sommer Sven G.
Publication year - 2021
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.1002/jeq2.20252
Subject(s) - manure , manure management , methane , production (economics) , environmental science , anaerobic digestion , adaptation (eye) , biochemical engineering , ecology , engineering , biology , economics , macroeconomics , neuroscience
National inventories of methane (CH 4 ) emission from manure management are based on guidelines from the Intergovernmental Panel on Climate Change using country‐specific emission factors. These calculations must be simple and, consequently, the effects of management practices and environmental conditions are only crudely represented in the calculations. The intention of this review is to develop a detailed understanding necessary for developing accurate models for calculating CH 4 emission from liquid manure, with particular focus on the microbiological conversion of organic matter to CH 4 . Themes discussed are (a) the liquid manure environment; (b) methane production processes from a modeling perspective; (c) development and adaptation of methanogenic communities; (d) mass and electron conservation; (e) steps limiting CH 4 production; (f) inhibition of methanogens; (g) temperature effects on CH 4 production; and (h) limits of existing estimation approaches. We conclude that a model must include calculation of microbial response to variations in manure temperature, substrate availability and age, and management system, because these variables substantially affect CH 4 production. Methane production can be reduced by manipulating key variables through management procedures, and the effects may be taken into account by including a microbial component in the model. When developing new calculation procedures, it is important to include reasonably accurate algorithms of microbial adaptation. This review presents concepts for these calculations and ideas for how these may be carried out. A need for better quantification of hydrolysis kinetics is identified, and the importance of short‐ and long‐term microbial adaptation is highlighted.