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.
Limitations in current capabilities to constrain aerosols adversely impact atmospheric simulations. Typically, aerosol burdens within models are constrained employing satellite aerosol optical properties, which are not available under cloudy conditions. Here we set the first steps to overcome the long-standing limitation that aerosols cannot be constrained using satellite remote sensing under cloudy conditions. We introduce a unique data assimilation method that uses cloud droplet number (Nd) retrievals to improve predicted below-cloud aerosol mass and number concentrations. The assimilation, which uses an adjoint aerosol activation parameterization, improves agreement with independent Nd observations and with in situ aerosol measurements below shallow cumulus clouds. The impacts of a single assimilation on aerosol and cloud forecasts extend beyond 24 h. Unlike previous methods, this technique can directly improve predictions of near-surface fine mode aerosols responsible for human health impacts and low-cloud radiative forcing. Better constrained aerosol distributions will help improve health effects studies, atmospheric emissions estimates, and air-quality, weather, and climate predictions.