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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2020-319
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-319
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  31 Aug 2020

31 Aug 2020

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This preprint is currently under review for the journal AMT.

Multiscale observations of NH3 around Toronto, Canada

Shoma Yamanouchi1, Camille Viatte2, Kimberly Strong1, Erik Lutsch1, Dylan B. A. Jones1, Cathy Clerbaux2, Martin Van Damme3, Lieven Clarisse3, and Pierre-Francois Coheur3 Shoma Yamanouchi et al.
  • 1Department of Physics, University of Toronto, Toronto, Ontario, Canada
  • 2LATMOS/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France
  • 3Université Libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the observational footprint of the FTIR measurements.

All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.46 %/year from 2002 to 2018 in the FTIR columns, 8.88 ± 2.83 %/year from 2013 to 2017 in the surface in-situ data, and 8.38 ± 0.77 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤ 25 km and ≤ 20 minutes, with r = 0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in-situ measurements were standardized and correlated. Comparison of 24-day averages and monthly averages resulted in correlation coefficients of r = 0.72 and r = 0.75, respectively, although correlation without resampling to reduce high-frequency variability led to a poorer correlation, with r = 0.39.

The GEOS-Chem model, run at 2° × 2.5° resolution, was compared against FTIR and IASI to assess model performance and investigate correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35° N to 53° N, and 93.75° W to 63.75° W) resulted in r = 0.57, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2 = 0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2 = 0.13, indicating that a finer spatial resolution is needed for modeling NH3.

Shoma Yamanouchi et al.

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Shoma Yamanouchi et al.

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Short summary
Ammonia (NH3) is a major source of pollution in the air. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 over Toronto, Canada, derived from multiscale datasets are examined. These NH3 datasets were compared against each other, and against a model to better understand NH3 variability, and to assess model performance.
Ammonia (NH3) is a major source of pollution in the air. As such, there have been increasing...
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