References

ACP

Atmospheric Chemistry and Physics

ACP

1680-7324

Copernicus GmbH

Göttingen, Germany

10.5194/acp-11-11761-2011

Novel application of satellite and in-situ measurements to map surface-level NO2 in the Great Lakes region

Lee

C. J.

¹ Brook

J. R.

² Evans

G. J.

¹ Martin

R. V.

³ ⁴ Mihele

Southern Ontario Centre for Atmospheric Aerosol Research, Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada

Air Quality Research Division, Science and Technology Branch, Environment Canada, Downsview, ON, Canada

Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada

Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA

24 11 2011

11 22 11761 11775

This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

This article is available from http://www.atmos-chem-phys.net/11/11761/2011/acp-11-11761-2011.html

The full text article is available as a PDF file from http://www.atmos-chem-phys.net/11/11761/2011/acp-11-11761-2011.pdf

Ozone Monitoring Instrument (OMI) tropospheric NO2 vertical column density data were used in conjunction with in-situ NO2 concentrations collected by permanently installed monitoring stations to infer 24 h surface-level NO2 concentrations at 0.1° (~11 km) resolution. The region examined included rural and suburban areas, and the highly industrialised area of Windsor, Ontario, which is situated directly across the US-Canada border from Detroit, MI. Photolytic NO2 monitors were collocated with standard NO2 monitors to provide qualitative data regarding NOz interference during the campaign. The accuracy of the OMI-inferred concentrations was tested using two-week integrative NO2 measurements collected with passive monitors at 18 locations, approximating a 15 km grid across the region, for 7 consecutive two-week periods. When compared with these passive results, satellite-inferred concentrations showed an 18% positive bias. The correlation of the passive monitor and OMI-inferred concentrations (R=0.69, n=115) was stronger than that for the passive monitor concentrations and OMI column densities (R=0.52), indicating that using a sparse network of monitoring sites to estimate concentrations improves the direct utility of the OMI observations. OMI-inferred concentrations were then calculated for four years to show an overall declining trend in surface NO2 concentrations in the region. Additionally, by separating OMI-inferred surface concentrations by wind direction, clear patterns in emissions and affected down-wind regions, in particular around the US-Canada border, were revealed.

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