Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area

Matthew J. Bechle, Dylan B. Millet, Julian D. Marshall

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106 Scopus citations


Remote sensing may be a useful tool for exploring spatial variability of air pollution exposure within an urban area. To evaluate the extent to which satellite data from the Ozone Monitoring Instrument (OMI) can resolve urban-scale gradients in ground-level nitrogen dioxide (NO2) within a large urban area, we compared estimates of surface NO2 concentrations derived from OMI measurements and US EPA ambient monitoring stations. OMI, aboard NASA's Aura satellite, provides daily afternoon (∼13:30 local time) measurements of NO2 tropospheric column abundance. We used scaling factors (surface-to-column ratios) to relate satellite column measurements to ground-level concentrations. We compared 4138 sets of paired data for 25 monitoring stations in the South Coast Air Basin of California for all of 2005. OMI measurements include more data gaps than the ground monitors (60% versus 5% of available data, respectively), owing to cloud contamination and imposed limits on pixel size. The spatial correlation between OMI columns and corrected in situ measurements is strong (r=0.93 for annual average data), indicating that the within-urban spatial signature of surface NO2 is well resolved by the satellite sensor. Satellite-based surface estimates employing scaling factors from an urban model provide a reliable measure (annual mean bias: -13%; seasonal mean bias: <1% [spring] to -22% [fall]) of fine-scale surface NO2. We also find that OMI provides good spatial density in the study region (average area [km2] per measurement: 730 for the satellite sensor vs. 1100 for the monitors). Our findings indicate that satellite observations of NO2 from the OMI sensor provide a reliable measure of spatial variability in ground-level NO2 exposure for a large urban area.

Original languageEnglish (US)
Pages (from-to)345-353
Number of pages9
JournalAtmospheric Environment
StatePublished - Apr 2013

Bibliographical note

Funding Information:
This work was supported by NSF-Division of Chemical, Bioengineering, Environmental, and Transport Systems (CBET) (grant 0853467 ). We acknowledge the NASA GES DISC for the dissemination of OMI data, and the US EPA AQS Data Mart for the dissemination of EPA monitor data.


  • Exposure
  • Nitrogen dioxide
  • OMI
  • Remote sensing
  • Urban air quality


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