Quantifying Greenhouse Gas Emissions from Livestock in Pastoral Areas Using Unmanned Aerial Vehicles and Assessing Emission Reduction Strategies

Accurate measurement of greenhouse gas (GHG) emissions from livestock is essential for developing effective emission reduction strategies. Herein, we used unmanned aerial vehicles (UAVs) and deep learning technology to estimate methane and nitrous oxide emissions from enteric fermentation and manure management in pastoral regions. Refined GHG emission factors were derived by considering animal weight, feed quality, breeding methods, and grassland types, thereby improving the precision of livestock GHG emission measurements. Based on the refined emission factors, average household-level livestock emissions were estimated at 110.6 tons CO₂e. Potential emission reductions from different strategies, including reducing livestock numbers, improving feed quality, and changing breeding methods, together with their associated costs and benefits, were evaluated to identify the optimal mitigation strategy. Among the tested options, improving feed quality showed the best balance between emission reduction potential and cost-effectiveness. In particular, converting low-quality forage to medium-quality forage could reduce emissions by 45.8 tons CO₂e per household, with an estimated regional mitigation potential of 17.57 million tons CO₂e in our study area. We also discussed appropriate carbon pricing mechanisms for mitigating livestock-related GHG emissions. This study offers valuable guidance for developing effective emission reduction strategies for pastoral livestock.