Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States

Abstract

Satellite-retrieved aerosol optical depth (AOD) has become an important predictor of ground-level particulate matter (PM) and greatly empowered air pollution research worldwide. We evaluated the AOD parameters included in the Collection 6 aerosol product of the Moderate Resolution Imaging Spectroradiometer (MODIS) for two key factors affecting their applications in air quality research-coverage and accuracy-over the continental US. For the high confidence retrievals (QAC 3), the 10 km DB-DT combined AOD has the best coverage nationwide (29.7% of the days in a year in any given 12 km grid cell). While the Eastern US generally had more successful AOD retrievals, the highest spatial coverage of AOD parameters were found in California (>55%) and other vegetated parts of the Western US. If lower QAC retrievals were included, the coverage of the 10 km DB AOD was dramatically increased to 49.6%. In the Eastern US, the QAC 3 retrievals of all four AOD parameters are highly correlated with AERONET observations (correlation coefficients between 0.80 and 0.92). In the Western US, positive retrieval errors existed in all MODIS AOD parameters, resulting in lower correlations with AERONET. AOD retrieval errors showed significant dependence on flight geometry, land cover type, and weather conditions. To ensure appropriate use of these AOD values, air quality researchers should carefully balance the needs for coverage and accuracy, and develop additional data screening criteria based on their study design.

Effect of Heat Wave Conditions on Aerosol Optical Properties Derived from Satellite and Ground-Based Remote Sensing over Poland

“…In fact, an agreement of the obtained SEVIRI AOD at 635 nm maps with the MODIS AOD at 550 nm maps is reasonable (MODIS available only for 12, 13 and 15 September via www.polandaod.pl; not shown for brevity); however, it is rather general, as the MODIS AOD maps are daily composites and are not directly comparable with the high temporal resolution of the derived SEVIRI AOD maps. Secondly, the uncertainty of the Lidar-derived AOD and the SEVIRI-derived AOD decreases with the increasing aerosol load, unlike the MODIS AOD retrieval, where the uncertainty of AOD derivation is directly proportional to the aerosol load sensed [31,32]. The high aerosol loads observed during the studied heat wave event resulted in a good-agreement of the Lidar and SEVIRI AOD (Figure 11).…”

“…The obtained good-agreement of the AOD Lidar and SEVIRI data (high correlation r 2 of 0.86 for 355 nm and 0.85 for 532 nm) can be explained by the specifics of both retrieval algorithms. Firstly, for the Lidar AOD algorithm, the near-range detection unit allows for the extension of the Lidar aerosol extinction coefficient profiles down to approximately 400 m with respect to the far-range unit, that typically provides such profiles only down to about 1000 m. Secondly, the uncertainty of the Lidar-derived AOD and the SEVIRI-derived AOD decreases with the increasing aerosol load, unlike the MODIS AOD retrieval, where the uncertainty of AOD derivation is directly proportional to the aerosol load sensed [31,32]. The high aerosol loads observed during the studied heat wave event resulted in a good-agreement of the Lidar and SEVIRI AOD (Figure 11).…”

“…The satellite retrieval of aerosol properties over land is a difficult task, mainly due to estimation of the surface reflectance (in terms of its high temporal variability and spatial inhomogeneity) and the anisotropic bi-directional reflectance of land surfaces (inducing higher uncertainties of retrieved parameters) [28][29][30]. However, the satellite-derived AODs are recognized as an important predictor of ground-level particulate matter (PM), which empowers the air pollution research [31,32].…”

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

“…However, significant challenges associated with the use of these observations remain. A large proportion of satellite observations are missing (estimated at ~70% in the 10 km AOD products), chiefly as a result of cloud-cover, snow-cover, and surface brightness [ 2 , 3 ]. Previous work to address this gap-filling problem has largely assumed that the observed aerosols are comparable to aerosols that could not be observed [ 4 , 5 ].…”

Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing

“…These results may not be biased for an area such as Western Europe or North America, where air qualities are good. For example, the number of successful retrievals of 3 km DT was far more than those of 10 km DT and 10 km DB over Atlanta, USA [65]. In China, however-especially Northern China, which has frequent haze-fog events when PM 2.5 concentrations are very high-most satellite-based aerosol retrieval schemes have difficulties in separating the surface and atmospheric contribution.…”