Modeling the Sources and Transport Processes During Extreme Ammonia Episodes in the U.S. Corn Belt

Cheng Hu, Timothy J. Griffis, John M. Baker, Jeffrey D. Wood, Dylan B. Millet, Zhongjie Yu, Xuhui Lee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Atmospheric ammonia (NH3) is the primary form of reactive nitrogen (Nr) and a precursor of ammonium (NH4 +) aerosols. Ammonia has been linked to adverse impacts on human health, the loss of ecosystem biodiversity, and plays a key role in aerosol radiative forcing. The midwestern United States is the major NH3 source in North America because of dense livestock operations and the high use of synthetic nitrogen fertilizers. Here, we combine tall-tower (100 m) observations in Minnesota and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) modeling to investigate high and low NH3 emission episodes within the U.S. Corn Belt to improve our understanding of the distribution of emission sources and transport processes. We examined observations and performed model simulations for cases in February through November of 2017 and 2018. The results showed the following: (1) Peak emissions in November 2017 were enhanced by above-normal air temperatures, implying a Q10 (i.e., the change in NH3 emissions for a temperature increase of 10°C) of 2.5 for emissions. (2) The intensive livestock emissions rom northern Iowa, approximately 400 km away from the tall tower, accounted for 17.6% of the abundance in tall-tower NH3 mixing ratios. (3) Ammonia mixing ratios in the innermost domain 3 frequently (i.e., 336 hr, 48% of November 2017) exceeded 5.3 ppb, an important air quality health standard. (4) In November 2017, simulated NH3 net ecosystem exchange (the difference between NH3 emissions and dry deposition) accounted for 60–65% of gross NH3 emissions for agricultural areas and was 2.8–3.1 times the emissions of forested areas. (5) We estimated a mean annual NH3 net ecosystem exchange of 1.60 ± 0.06 nmol · m−2 · s−1 for agricultural lands and −0.07 ± 0.02 nmol · m−2 · s−1 for forested lands. These results imply that future warmer fall temperatures will enhance agricultural NH3 emissions, increase the frequency of dangerous NH3 episodes, and enhance dry NH3 deposition in adjacent forested lands.

Original languageEnglish (US)
Article numbere2019JD031207
JournalJournal of Geophysical Research Atmospheres
Volume125
Issue number2
DOIs
StatePublished - Jan 27 2020

Bibliographical note

Funding Information:
This research was partially supported by the National Science Foundation (grant 1640337), the U.S. Department of Agriculture National Institute of Food and Agriculture (USDA NIFA grant 2018‐67019‐27808), USDA Agricultural Research Service, and the Minnesota Supercomputing Institute for Advanced Computational Research. Jeffrey D. Wood acknowledges support from the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research Program, through Oak Ridge National Laboratory's Terrestrial Ecosystem Science Focus Area; ORNL is managed by UT‐Battelle, LLC, for the U.S. DOE under contract DE‐AC05‐00OR22725. We acknowledge use of the National Atmospheric Deposition Program databases. Finally, the observational data presented in this manuscript are available at www.biometeorology.umn.edu/research/data‐archives and ESS‐DIVE (Deep Insights for Earth Science Data, https://data.ess‐dive.lbl.gov/view/doi:10.15485/1550921 ). The NH data can also be obtained from our group website https://www.biometeorology.umn.edu/research/data‐archives . The WRF‐Chem model code is available on https://www2.mmm.ucar.edu/wrf/users/download/ . Finally, the WRF‐CHEM setup parameters (namelist) are provided in the supporting information . 3

Funding Information:
This research was partially supported by the National Science Foundation (grant 1640337), the U.S. Department of Agriculture National Institute of Food and Agriculture (USDA NIFA grant 2018-67019-27808), USDA Agricultural Research Service, and the Minnesota Supercomputing Institute for Advanced Computational Research. Jeffrey D. Wood acknowledges support from the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research Program, through Oak Ridge National Laboratory's Terrestrial Ecosystem Science Focus Area; ORNL is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725. We acknowledge use of the National Atmospheric Deposition Program databases. Finally, the observational data presented in this manuscript are available at www.biometeorology.umn.edu/research/data-archives and ESS-DIVE (Deep Insights for Earth Science Data, https://data.ess-dive.lbl.gov/view/doi:10.15485/1550921). The NH3 data can also be obtained from our group website https://www.biometeorology.umn.edu/research/data-archives. The WRF-Chem model code is available on https://www2.mmm.ucar.edu/wrf/users/download/. Finally, the WRF-CHEM setup parameters (namelist) are provided in the supporting information.

Publisher Copyright:
©2019. American Geophysical Union. All Rights Reserved.

Keywords

  • NH
  • WRF-Chem model
  • agriculture
  • dry deposition
  • forests
  • tall tower observations

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