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Reducing ammonia emissions through targeted fertilizer management

Posted on February 3, 2024 By admin


Based on machine learning, researchers have come up with detailed estimates of ammonia emissions from rice, wheat and maize crops. The dataset enabled a cropland-specific assessment of the potential for emission reductions, which indicates that effective management of fertilizer in the growing of these crops could lower atmospheric ammonia emissions from farming by up to 38%. The paper was published in the journal Nature.

Atmospheric ammonia is a key environmental pollutant that affects ecosystems across the planet, as well as human health. Around 51-60% of anthropogenic ammonia emissions can be traced back to crop cultivation, and about half of these emissions are associated with three main staple crops: rice, wheat and maize. However, quantifying any potential reductions in ammonia emissions related to specific croplands at high resolution is challenging and depends on details such as nitrogen inputs and local emission factors.

Yi Zheng from the Southern University of Science and Technology, Shenzhen, China and others used machine learning to model ammonia output from rice, wheat and maize agriculture worldwide on the basis of variables that include climate, soil characteristics, crop types, irrigation, tillage and fertilization practices. To inform the model, the researchers developed a dataset of ammonia emissions from over 2,700 observations obtained via systematic review of the published literature. Using this model, the researchers estimate that global ammonia emission reached 4.3 teragrams (4.3 billion kilograms) in 2018. The authors calculated that spatially optimizing fertilizer management — as guided by the model — could result in a 38% reduction in ammonia emissions from the three crops. The optimised strategy involves placing enhanced-efficiency fertilizers deeper into the soil using conventional tillage practices during the growing season.

The researchers found that under the fertilizer management scenario rice crops could contribute 47% of the total reduction potential, and maize and wheat could contribute 27% and 26%, respectively. Without any management strategies, the authors calculated that ammonia emissions could rise by between 4.6% to 15.8% by 2100, depending on the level of future greenhouse gas emissions.



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Science Tags:Ammonia emissions, Cropland-specific assessment, Machine learning

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