A bulk-mass-modeling-based method for retrieving particulate matter pollution...

Toth, T., J. Zhang, J. S. Reid, and M. A. Vaughan (2019), A bulk-mass-modeling-based method for retrieving particulate matter pollution using CALIOP observations, Atmos. Meas. Tech., 12, 1739-1754, doi:10.5194/amt-12-1739-2019.

In this proof-of-concept paper, we apply a bulk-mass-modeling method using observations from the NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument for retrieving particulate matter (PM) concentration over the contiguous United States (CONUS) over a 2-year period (2008–2009). Different from previous approaches that rely on empirical relationships between aerosol optical depth (AOD) and PM2.5 (PM with particle diameters less than 2.5 µm), for the first time, we derive PM2.5 concentrations, during both daytime and nighttime, from near-surface CALIOP aerosol extinction retrievals using bulk mass extinction coefficients and model-based hygroscopicity. Preliminary results from this 2-year study conducted over the CONUS show a good agreement (r 2 ∼ 0.48; mean bias of −3.3 µg m−3 ) between the averaged nighttime CALIOPderived PM2.5 and ground-based PM2.5 (with a lower r 2 of ∼ 0.21 for daytime; mean bias of −0.4 µg m−3 ), suggesting that PM concentrations can be obtained from active-based spaceborne observations with reasonable accuracy. Results from sensitivity studies suggest that accurate aerosol typing is needed for applying CALIOP measurements for PM2.5 studies. Lastly, the e-folding correlation length for surface PM2.5 is found to be around 600 km for the entire CONUS (∼ 300 km for western CONUS and ∼ 700 km for eastern CONUS), indicating that CALIOP observations, although sparse in spatial coverage, may still be applicable for PM2.5 studies.

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Atmospheric Composition Modeling and Analysis Program (ACMAP)