Abstract This study develops a new approach to improve simulations of the particulate matter of aerodynamic diameter smaller than 2.5 μm (PM2.5) in the Community Multiscale Air Quality (CMAQ) model via assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals using the Gridpoint Statistical Interpolation (GSI) system. In contrast to previous studies that only consider errors due to transport, our computation of the background error covariance matrix incorporates uncertainties in anthropogenic emissions. To understand the impact of this approach, three experiments (one background and two assimilations) are performed over the contiguous United States (CONUS) from 15 July to 14 August 2014. The background CMAQ experiment significantly underestimates both the MODIS AOD and surface PM2.5 levels. MODIS AOD assimilation pushes both the CMAQ AOD and surface PM2.5 distributions toward the observed distributions, but CMAQ still underestimates the observations. Averaged over CONUS, the two assimilation experiments with and without including the anthropogenic emission uncertainties improve the correlation coefficient between the model and independent observations of PM2.5 by  67% and  48%, respectively, and reduces the mean bias by  38% and  10%, respectively. The assimilation improves the model performance everywhere over CONUS, except the New York and Wisconsin, where CMAQ overestimates the observed PM2.5 during nighttime after assimilation likely because of overcorrection of aerosol mass concentrations by the AOD assimilation. Future work should incorporate uncertainties in other processes (biomass burning and biogenic emissions, deposition, chemistry, transport, and boundary conditions) to further enhance the value of assimilating spaceborne AOD retrievals.

The NASA Langley airborne second-generation High Spectral Resolution Lidar (HSRL-2) uses a density-tuned field-widened Michelson interferometer to implement the HSRL technique at 355&\#x00A0;nm. The Michelson interferometer optically separates the received backscattered light between two channels, one of which is dominated by molecular backscattering, while the other contains most of the light backscattered by particles. This interferometer achieves high and stable contrast ratio, defined as the ratio of particulate backscatter signal received by the two channels. We show that a high and stable contrast ratio is critical for precise and accurate backscatter and extinction retrievals. Here, we present retrieval equations that take into account the incomplete separation of particulate and molecular backscatter in the measurement channels. We also show how the accuracy of the contrast ratio assessment propagates to error in the optical properties. For both backscattering and extinction, larger errors are produced by underestimates of the contrast ratio (compared to overestimates), more extreme aerosol loading, and&\#x2014;most critically&\#x2014;smaller true contrast ratios. We show example results from HSRL-2 aboard the NASA ER-2 aircraft from the 2016 ORACLES field campaign in the southeast Atlantic, off the coast of Africa, during the biomass burning season. We include a case study where smoke aerosol in two adjacent altitude layers showed opposite differences in extinction- and backscatter-related &\#x00C5;ngstr&\#x00F6;m exponents and a reversal of the lidar ratio spectral dependence, signatures which are shown to be consistent with a relatively modest difference in smoke particle size.

Intense haze events in China provide ideal opportunities to study meteorological and chemical feedbacks due to extremely high aerosol loadings. In this chapter, an online coupled meteorology-chemistry model, WRF-Chem, is applied to simulate impacts of aerosol feedbacks on meteorology and air quality during the January 2010 haze event over the North China Plain (NCP). The results show that the model reasonably reproduces well most meteorological, chemical and optical variables. Aerosols during this haze event can reduce surface downward shortwave radiation by 25.7% and planetary boundary layer height by 14.9%. Due to aerosol feedbacks, PM2.5 concentrations in urban Beijing increase by 11.2% at 14:00. The severe haze also enhances cloud droplet number concentrations, which can further affect cloud chemistry. These results indicate that aerosol feedbacks in the NCP, especially in urban regions, are important and should be considered when develop air pollution control and climate mitigation strategies.