Quantifying Greenhouse Gas Emissions from Livestock in Pastoral Areas based on Unmanned Aerial Vehicles

Accurate measurement of greenhouse gas (GHG) emissions from livestock is essential for developing effective emission reduction strategies. This study introduces the use of Unmanned Aerial Vehicles (UAVs) and deep learning technology to estimate methane (CH₄) and nitrous oxide (N₂O) emissions from enteric fermentation and manure management in pastoral areas. More accurate animal GHG emission factors are derived by considering animal weight, feed quality, breeding methods, and grassland types, which improves the precision of measuring GHG emissions from livestock. Potential emission reductions from different strategies, along with their associated costs and benefits, are projected to identify the optimal emission reduction strategy. We also discuss appropriate carbon pricing mechanisms for mitigating livestock-related GHG emissions. These findings offer valuable guidance for shaping effective emission reduction strategies in pastoral livestock production.