Impact of data quality and surface-to-column representativeness on the PM<sub>2.5</sub> / satellite AOD relationship for the contiguous United States

Abstract

Abstract. Satellite-derived aerosol optical depth (AOD) observations have been used to estimate particulate matter smaller than 2.5 µm (PM 2.5 ). However, such a relationship could be affected by the representativeness of satellitederived AOD to surface aerosol particle mass concentration and satellite AOD data quality. Using purely measurementbased methods, we have explored the impacts of data quality and representativeness on the AOD-inferred PM 2.5 / AOD relationship for the contiguous United States (CONUS). This is done through temporally and spatially collocated data sets of PM 2.5 and AOD retrievals from Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). These analyses show that improving data quality of satellite AOD, such as done with data assimilation-grade retrievals, increases their correlation with PM 2.5 . However, overall correlation is relatively low across the CONUS. Also, integrated extinction observed within 500 m above ground level (a.g.l.), as measured by CALIOP, is not well representative of the total column AOD. Surface aerosol in the eastern CONUS is better correlated with total column AOD than in the western CONUS. The best correlation values are found for estimated dry mass CALIOP extinction at 200-300 m a.g.l. and PM 2.5 , but additional work is needed to address the ability of using actively sensed AOD as a proxy for PM 2.5 concentrations.

Ground‐based High Spectral Resolution Lidar observation of aerosol vertical distribution in the summertime Southeast United States

“…PM 2.5 events largely coincided with AOTs events listed above (with the most notable event reaching 28 μg m À3 coinciding with 7-10 September 2013) although PM 2.5 showed much less dynamic range. Consequently, correlations between daily average AOT from AERONET Level 2 data and PM 2.5 were middling (r 2 = 0.48), consistent with the findings of the literature review of Toth et al [2014].…”

A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth

“…In addition to the models mentioned above, other researchers used linear correlations [16,30,31,37,42,58,71,113,115,117], GAM [23,24,53,65,77], LUR [66,69,70,78,91,122], Kriging [88,90,108] or the nonlinear regression model. Those PM 2.5 estimating models all regard AOD as the primary independent variable.…”

Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

“…Ford and Heald, 2012), these are indirect measurements with their own limitations and errors. The uncertainty in satellite AOD can be due to a variety of issues such as the presence of clouds, the choice of optical model used in the retrieval algorithm, and surface properties (Toth et al, 2014; Zhang and Reid, 2006). For validation of satellite products, studies have often relied on comparisons against AOD measured with sun photometers at AERONET ground sites (e.g.…”

“…This suggests that the average AOD values can also be influenced by the chosen filtering and data quality standards. Analysis of the impact of satellite data quality on the AOD to PM 2.5 relationship is discussed in Toth et al (2014). They find that using higher quality observations does tend to improve correlations between observed AOD and surface PM 2.5 across the U.S. though in general correlations are low (<0.55).…”