Abstract
Rice is a staple food for more than half of humanity, and 90 % of rice is grown and consumed in Asia. However, paddy rice cultivation creates an ideal environment for the production and release of methane (CH4). How to estimate regional CH4 emissions accurately and how to mitigate them efficiently have been of key concern. Here, with a machine learning method, we investigate the spatiotemporal changes, the major controlling factors and mitigation potentials of paddy rice CH4 emissions across Monsoon Asia at a resolution of 0.1° (∼10 km). Spatially CH4 emissions are highly heterogeneous, with the Indo-Gangetic Plain, Deltas of the Mekong, and Yangtze River Basin as the hotspots. Nationwide, China, India, Bangladesh and Vietnam are the major emitters. Straw applied on season is a critical controlling factor for CH4 emission in rice fields. The single-season rice contributes to over 80 % of the total emissions. CH4 emissions from Monsoon Asia have notably declined since 2007. Three mitigation strategies, including water management techniques, off-season straw return, and straw to biochar, may reduce CH4 emissions by 27.66 %, 23.78 %, and 21.79 %, respectively, with the most effective strategy being rice cultivation type-specific and environment-specific. Our findings gain new insights into CH4 emissions and mitigations across Monsoon Asia, providing evidence to adopt precise mitigation strategies based on rice cultivation types and local environment.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.