Greenhouse gas emissions on Chinese dairy farms and potential for reduction
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Dong H, Wei S. 2021. Greenhouse gas emissions on Chinese dairy farms and potential for reduction. CCAFS Working Paper no. 384. Wageningen, the Netherlands: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).
Permanent link to cite or share this item: https://hdl.handle.net/10568/116718
A life cycle assessment method was used to calculate the greenhouse gas (GHG) emissions of a sample of 181 dairy farms. A database with survey data of these dairy farms was used to calculate and analyze the resulting GHG emission data. The results show that the annual average carbon footprint of milk from the sample farms is 1.95 kg CO2-eq kg-1 fat and protein corrected milk (FPCM). There are great differences in GHG emission, ranging from 0.82 to 5.09 kg CO2-eq kg-1 FPCM. Regions in south China have the highest carbon footprint, while those in North China have the lowest level. The largest emission source is feed production and processing (31.8%), followed by enteric fermentation (30.0%), manure management (20.8%), energy consumption (9.7%), transport (7.7%) and manure application (7.2%). This large range is caused by different farm conditions and farm management practices, such as herd size, milk yield, and manure management among others. Improving the local dairy production efficiency, manure management, and the integration of crop and dairy production systems are major factors to combine the growing Chinese demand for milk consumption with the global need to reduce GHG emissions. This should be guided through governmental policies, including closing the productivity and efficiency gaps in domestic dairy and feed production, innovations in manure management and the use of green energy. Policy guidelines for the reduction of GHG emissions should take into account differences between regions and farms.
Other CGIAR Affiliations
SubjectsLOW EMISSIONS DEVELOPMENT;
Organizations Affiliated to the AuthorsChinese Academy of Agricultural Sciences
- CCAFS Working Papers