Air quality forecasts and attainment projections rely upon semi-empirical parameterizations within numerical models for the description of dispersion, formation and fate of pollutants influenced by the spatial and temporal distribution of emissions in cities, the topography, and weather. The gases (O3, NO2, etc.) and particulate matter (PM) measured at the ground level is a common way to quantify the amount of aerosol particles and gas concentrations in the atmosphere and is used as a standard to evaluate air quality. PM and trace gases forecasting needs a thorough understanding of the processes affecting aerosol and gas concentrations as well as vertically-resolved measurements in the atmospheric column.
The lidar portfolio (elastic, Raman, DIAL, Doppler wind) at Hampton University provide high resolution information on the altitude dependence of troposphere aerosols and trace gases, providing precise measurements in regions of the lower atmosphere above a city, which would inaccessible to either aircraft or tethered balloons. Retrieved backscatter signals are used to derive variations of the atmospheric structure and transport, gaining knowledge of aerosol and trace gases radiative properties needed to evaluate their effects on climate and air quality. These measurements provide insight into the planetary boundary layer (PBL) temporal structure, height and variability. Regarding air quality, the PBL height determines the volume available for pollutant dispersion and the resulting concentrations and is therefore one of the fundamental parameters in many dispersion models. HU lidar observations when used in conjunction with satellite data can be assimilated into forecasting models to reproduce current distributions of aerosols and oxidants in urban areas and to improve their accuracy in forecasting air quality and understanding regional pollution dynamics. Also, provides ground truth for satellite retrieval over areas with high surface albedo, allowing instrument accuracy assessments of regional water vapor and aerosol variability.