Can the Spatial Planning of Livestock Production Tackle Future Nitrogen Pollution in China?
Year: 2026
Type: article
Abstract: Nitrogen (N) pollution from livestock production significantly threatens China’s air and water quality, necessitating innovative solutions to balance food security and environmental sustainability. Studies have mostly overlooked the spatial heterogeneity of N-related environmental impacts and the trade-offs between reducing ammonia (NH3) emissions and N concentrations in water. This study develops a spatially explicit multiscale model system encompassing 13,000 polygons across China to assess soil N balance, NH3 emission intensity, and N concentrations in surface water, aiming to explore integrated spatial-planning (SP) strategies that maximize synergy and minimize trade-offs. Our findings reveal that single-purpose SP scenarios (e.g., reducing NH3 emissions or instream N concentrations) can effectively address one N-related issue but produce substantial trade-offs, leaving >50% of China’s population exposed to at least another N-related problem. However, an integrated SP approach could reduce harmful N exposures for 90% of China’s population while ensuring food security. This approach involves reallocating 14% of livestock production, reducing livestock numbers by one-third relative to the 2050 baseline, and implementing advanced technologies to mitigate N pollution hotspots. Thus, our findings emphasize the importance of spatially explicit N boundaries and multicriteria planning to tackle N pollution in air and water simultaneously, supporting cross-media N management policy-making and region-specific strategies.
Institutions: Chinese Academy of Sciences, Institute of Urban Environment, Institute of Genetics and Developmental Biology, Wageningen University & Research, Utrecht University, Shandong Agricultural University, Nanjing University, Huazhong Agricultural University, Hebei University of Science and Technology
Language: English
Subfield: Environmental Chemistry
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,500
Awards: G3936694175, G5110469169, G7263464042
OpenAlex ID: W7225337408
