Fertilizer management for global ammonia emission reduction.

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 0410462 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-4687 (Electronic) Linking ISSN: 00280836 NLM ISO Abbreviation: Nature Subsets: MEDLINE

Publication: Basingstoke : Nature Publishing Group
Original Publication: London, Macmillan Journals ltd.

Ammonia*/analysis ; Ammonia*/metabolism ; Crop Production*/methods ; Crop Production*/statistics & numerical data ; Crop Production*/trends ; Fertilizers*/adverse effects ; Fertilizers*/analysis ; Fertilizers*/statistics & numerical data; Datasets as Topic ; Ecosystem ; Machine Learning ; Nitrogen/analysis ; Nitrogen/metabolism ; Oryza/metabolism ; Soil/chemistry ; Triticum/metabolism ; Zea mays/metabolism ; Climate Change/statistics & numerical data

Crop production is a large source of atmospheric ammonia (NH 3 ), which poses risks to air quality, human health and ecosystems ^1-5 . However, estimating global NH 3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy ^4,5 . Here we develop a machine learning model for generating crop-specific and spatially explicit NH 3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH 3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr ^-1 , lower than previous estimates that did not fully consider fertilizer management practices ^6-9 . Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH 3 emissions by about 38% (1.6 ± 0.4 Tg N yr ^-1 ) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH 3 emissions reductions of 47% (44-56%) for rice, 27% (24-28%) for maize and 26% (20-28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH 3 emissions could increase by 4.0 ± 2.7% under SSP1-2.6 and 5.5 ± 5.7% under SSP5-8.5 by 2030-2060. However, targeted fertilizer management has the potential to mitigate these increases.
(© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

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7664-41-7 (Ammonia)
0 (Fertilizers)
N762921K75 (Nitrogen)
0 (Soil)

Date Created: 20240131 Date Completed: 20240223 Latest Revision: 20240226

20240227

10.1038/s41586-024-07020-z

38297125