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Title: A high-resolution and observationally constrained OMI NO 2 satellite retrieval

Abstract

Here, this work presents a new high-resolution NO 2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO 2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO 2 vertical profile shape factors from a 1.25° × 1° (~110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO 2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO 2 vertical columns during summertime in the eastern US. In this new product, OMI NO 2 tropospheric columns increase by up to 160% in city centers and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO 2 and Airborne Compact Atmospheric Mapper (ACAM) NO 2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO 2 monitors in urban areas hasmore » improved dramatically: r 2 = 0.60 in the new product vs. r 2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NO x emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO 2 satellite retrievals.« less

Authors:
 [1];  [2];  [3]; ORCiD logo [4];  [1];  [1]
  1. Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, Chicago, IL (United States)
  2. Univ. Space Research Assoc., Columbia, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  3. NOAA Air Resources Lab., College Park, MD (United States); Univ. of Maryland, College Park, MD (United States)
  4. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Johns Hopkins Univ. Applied Physics Lab., Laurel, MD (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USEPA
OSTI Identifier:
1411029
Grant/Contract Number:
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 17; Journal Issue: 18; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Goldberg, Daniel L., Lamsal, Lok N., Loughner, Christopher P., Swartz, William H., Lu, Zifeng, and Streets, David G. A high-resolution and observationally constrained OMI NO2 satellite retrieval. United States: N. p., 2017. Web. doi:10.5194/acp-17-11403-2017.
Goldberg, Daniel L., Lamsal, Lok N., Loughner, Christopher P., Swartz, William H., Lu, Zifeng, & Streets, David G. A high-resolution and observationally constrained OMI NO2 satellite retrieval. United States. doi:10.5194/acp-17-11403-2017.
Goldberg, Daniel L., Lamsal, Lok N., Loughner, Christopher P., Swartz, William H., Lu, Zifeng, and Streets, David G. 2017. "A high-resolution and observationally constrained OMI NO2 satellite retrieval". United States. doi:10.5194/acp-17-11403-2017. https://www.osti.gov/servlets/purl/1411029.
@article{osti_1411029,
title = {A high-resolution and observationally constrained OMI NO2 satellite retrieval},
author = {Goldberg, Daniel L. and Lamsal, Lok N. and Loughner, Christopher P. and Swartz, William H. and Lu, Zifeng and Streets, David G.},
abstractNote = {Here, this work presents a new high-resolution NO2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (~110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO2 vertical columns during summertime in the eastern US. In this new product, OMI NO2 tropospheric columns increase by up to 160% in city centers and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO2 and Airborne Compact Atmospheric Mapper (ACAM) NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in the new product vs. r2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals.},
doi = {10.5194/acp-17-11403-2017},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 18,
volume = 17,
place = {United States},
year = 2017,
month = 9
}

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