Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality

Engel-Cox, Jill; Holloman, Christopher; Coutant, Basil W.; Hoff, R. M.

doi:10.1016/j.atmosenv.2004.01.039

Cited by 560 publications

(347 citation statements)

References 16 publications

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“…The comparison of this first relationship between POLDER AOT and PM2.5 with those previously established by using MODIS is complicated by the influence of several factors, like using PM10 instead of PM2.5 (Chu et al, 2003;Li et al, 2005), different wavelengths and spatial resolutions for the satellite AOT (Engel-Cox et al, 2004;Wang and Christopher, 2003), different time periods, and alternative approaches forcing the offset of the PM/Satellite AOT relationship through 0. Additionally the difference of sensitivity of the two sensors to fine particles, and their different inversion algorithm for the AOT might have a significant impact on their relationship with PM2.5.…”

Section: Comparison Between Polder-2 Derived Aot and Pm25 Massmentioning

confidence: 99%

“…Primary aerosol quantity derived from space borne remote sensors operating in the solar spectrum is the aerosol optical thickness. The relationship between column aerosol optical thickness (AOT) derived from satellite imagery and fine particulate mass ground measurements (PM) has already been explored over the United States (Engel-Cox et al, 2004;Wang and Christopher, 2003;AlSaadi et al, 2005) and other populated and industrialized regions in Asia (Li et al, 2005) and Europe (Chu et al, 2003) using retrievals from the MODIS radiometer (MODerate Imaging Spectroradiometer, on board Earth Observing System (EOS) TERRA and AQUA satellites). Wang and Christopher (2003) have used a simple linear relationship between MODIS derived AOT and 24 hr mean PM2.5 to quantitatively estimate air quality categories as defined by the U.S. Environmental Protection Agency (EPA) with an accuracy of more than 90% in cloud-free conditions.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data

et al. 2006

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Abstract. We analyze the relationship between daily fine particle mass concentration (PM2.5) and columnar aerosol optical thickness derived from the Polarization and Directionality of Earth's Reflectances (POLDER) satellite sensor. The study is focused over France during the POLDER-2 lifetime between April and October 2003. We have first compared the POLDER derived aerosol optical thickness (AOT) with integrated volume size distribution derived from ground-based Sun Photometer observations. The good correlation (R=0.72) with sub-micron volume fraction indicates that POLDER derived AOT is sensitive to the fine aerosol mass concentration. Considering 1974 match-up data points over 28 fine particle monitoring sites, the POLDER-2 derived AOT is fairly well correlated with collocated PM2.5 measurements, with a correlation coefficient of 0.55. The correlation coefficient reaches a maximum of 0.80 for particular sites. We have analyzed the probability to find an appropriate air quality category (AQC) as defined by U.S. Environmental Protection Agency (EPA) from POLDER-2 AOT measurements. The probability can be up to 88.8% (±3.7%) for the "Good" AQC and 89.1% (±3.6%) for the "Moderate" AQC.

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Section: Comparison Between Polder-2 Derived Aot and Pm25 Massmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data

et al. 2006

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“…One unexpected application of the MODIS Dark Target aerosol product is its use as a proxy for particulate pollution by the air quality community (Chu et al, 2003;Wang and Christopher, 2003;Engel-Cox et al, 2004). The interest in using MODIS aerosol products to characterize air pollution has progressed both in the research arena (van Donkelaar et al, 2006(van Donkelaar et al, , 2010 and on the operational side (Al-Saadi et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

MODIS 3 km aerosol product: algorithm and global perspective

et al. 2013

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After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODerate resolution Imaging Spectroradiometer (MODIS) aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over the ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm such as over bright or urban surfaces, the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than that of the 10 km product: ± 0.05 ± 0.20 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: ± 0.03 ± 0.05 AOD, but slightly less accurate in the coastal zone. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community

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“…Yet studies [12] suggested that MODIS data could be used to estimate surface PM concentrations. Could a better MODIS retrieval over Maryland yield better estimates of surface PM concentrations?…”

Section: Modis Collection 5 and Validationmentioning

confidence: 99%

Growing up MODIS: Towards a mature aerosol climate data record

Levy¹

2013

AIP Conference Proceedings

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Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality

Cited by 560 publications

References 16 publications

Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data

Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data

MODIS 3 km aerosol product: algorithm and global perspective

Growing up MODIS: Towards a mature aerosol climate data record

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