1. Effects of environmental and housing system factors on ammonia and greenhouse gas emissions from cattle barns: A meta-analysis of a global data collation.
- Author
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Çinar, Gültac, Dragoni, Federico, Ammon, Christian, Belik, Vitaly, van der Weerden, Tony J., Noble, Alasdair, Hassouna, Mélynda, and Amon, Barbara
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GREENHOUSE gases , *AMMONIA gas , *BARNS , *HOUSING , *EMISSION inventories , *DRYING agents , *AMMONIA - Abstract
• Significant effects of key drivers on gaseous emissions from cattle housing were identified. • NH 3 emissions differ between housing types but not between floor types. • CH 4 emissions differ by barn temperature and relative humidity only. • N 2 O and NH 3 emissions are lower in temperate wet zones than in temperate dry zone. • Global data analysis shows the need to differentiate emission factors by agro-ecosystems. This study provides a meta-analysis on the relationships between cattle barn CH 4 , NH 3 and N 2 O emission rates and their key drivers (i.e., housing type, floor type, environmental conditions). Understanding these relationships is essential to reduce uncertainties in emission inventories and suggest targeted mitigation measures. The total number of daily emission rates included in the analysis was 139 for CH 4 , 293 for NH 3 and 100 for N 2 O emissions. Emission rates in the database showed a large variation with 45–803.5 g/LU d−1 for CH 4 , 0.036–146.7 gN LU−1 d−1 for NH 3 , and 0.002–18 gN LU−1 d−1 for N 2 O emissions. Despite the high emission variability, significant effects were identified·NH 3 showed positive correlation with air temperature; NH 3 emissions differed between housing types but not between floor types·NH 3 emissions from tied stalls were lower than the ones from cubicle housing regardless of the floor type. Additionally, NH 3 emissions from loose housings were lower than the ones from cubicle housing·NH 3 and N 2 O emission rates from temperate wet zones were lower than the ones from temperate dry zones. CH 4 emission rates were affected by environmental factors only and not by housing and floor type, showing negative correlation with air temperature and humidity. The factors investigated can be suggested as ancillary variables and descriptors when cattle barn emissions are measured, in order to make best use of emission data. Country-specific data of these key drivers can be included into national inventories to adapt them to different agroecosystems and support targeted policies. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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