Fertilizer management plays a crucial role in reducing global ammonia emissions from crop production, which threatens air quality, human health, and ecosystems. However, accurately estimating these emissions is challenging due to limited data, hindering the ability to identify effective mitigation strategies. To address this issue, researchers have developed a machine learning model that provides crop-specific and detailed spatial information on ammonia emissions globally.
The study, conducted at a 5-arcmin resolution, used field observations to estimate that global ammonia emissions from rice, wheat, and maize fields in 2018 were 4.3 +- 1.0 Tg N yr-1, a lower figure than previously thought. This discrepancy was largely due to past estimates not fully considering fertilizer management practices. By optimizing fertilizer management based on the machine learning model, researchers found that global ammonia emissions could potentially be reduced by 38% (1.6 +- 0.4 Tg N yr-1) without reducing total nitrogen inputs.
The results also indicate that significant reductions in ammonia emissions are possible for specific crops, with potential reductions of 47% for rice, 27% for maize, and 26% for wheat cultivation. These findings highlight the importance of targeted fertilizer management practices in reducing ammonia emissions and improving overall air quality.
Looking ahead, the study also considered how future climate change scenarios may impact ammonia emissions. Under the SSP1 2.6 scenario, researchers estimate a 4.0 +- 2.7% increase in ammonia emissions by 2030-2060, with a steeper increase of 5.5 +- 5.7% under the SSP5 8.5 scenario. However, the researchers suggest that targeted fertilizer management measures could help mitigate these projected increases, underscoring the importance of proactive environmental management practices in addressing the challenges of global agricultural emissions.
In conclusion, this study highlights the critical role of fertilizer management in reducing ammonia emissions from crop production. By utilizing advanced modeling techniques and field observations, researchers were able to provide detailed insights into global patterns of ammonia emissions and potential mitigation strategies. These findings underscore the importance of sustainable and targeted fertilizer practices in addressing environmental challenges and promoting air quality and ecosystem health.
