Utilizing satellite ammonia observations to better understand ammonia variability

Ammonia (NH₃) is a key precursor to fine particulate matter (PM_2.5) and has remarkable impacts on air quality, climate, and ecosystem diversity. Satellite NH₃ observations from the Infrared Atmospheric Sounding Interferometer (IASI) provide long-term measurements of ammonia globally since 2007 and have been validated by both ground based and airborne measurements. In this study, IASI Level 2 NH₃ columns were oversampled at high-resolution (0.02°×0.02°) from 2008 to 2017 to yield monthly NH₃ maps covering the two top agricultural exporting regions in the world, the contiguous U.S. (CONUS) and Europe. K-means clustering was applied to identify NH₃ seasonality observations. The U.S. and Europe showed large temporal variabilities that differed by region and agricultural activities. For example, in the U.S., areas dominated by livestock waste emissions had peak NH₃ column abundances in the summer, while cropland-dominated regions tended to have spring peak and sometimes a fall shoulder. We also compared IASI NH₃ column amounts to NH₃ surface concentrations provided by the Ammonia Monitoring Network (AMoN) in the CONUS. Since IASI provides column NH₃ at ~ 9:30 LST while AMoN provides biweekly averaged surface NH₃, different factors were examined to find out the most important factors for the comparison between the two datasets (spatial window, temporal coverage, data averaging). We found that IASI data temporal coverage of the 2-week AMoN sampling period was the key factor in improving correlations. The r value increased from 0.38 to 0.73 when at least 80% of the two-week AMoN period had concurrent satellite measurements within a 25 km radius of the site. Neglecting interannual variability, the r value of multiyear monthly averaged AMoN and IASI NH₃ is 0.68, indicating the importance of temporal averaging. The good agreement between AMoN and IASI NH₃ concentrations demonstrates the feasibility of utilizing satellite NH₃ retrievals to better understand NH₃ variability in these agricultural intensive regions. With the global coverage and long data record, satellite measurements are likely to be a cost-effective approach as a supplemental source of information for understanding NH₃ variability, as well as guiding the locations of future sites within ground monitoring network. Finally, IASI NH₃ spatiotemporal variabilities will be compared to AM3 model output with bottom-up emission inventory (Magnitude And Seasonality of Agricultural Emissions model for NH3, MASAGE_NH3).