Air Quality
Elastic lidar timeseries showing particle pollution in the lower troposphere.
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 particulate matter (PM) mass measured at the ground level is a common way to quantify the amount of aerosol particles in the atmosphere and is used as a standard to evaluate air quality. PM forecasting needs a thorough understanding of the processes affecting aerosol concentrations as well as vertically-resolved measurements in the atmospheric column.
Lidar measurements at Hampton University have supported local, state and federal agencies to determine the relative impact of long-range transport versus local emissions. These efforts allows gain insight into interstate transport and direct policy decisions towards fair and equitable emission control strategies. Lidar activities are key support component of the National Oceanic and Atmospheric Administration (NOAA) Center for Earth Systems Sciences and Remote Sensing Technology to monitor and study regional and urban air quality in the eastern United States. This work contributes to NOAA’s “Weather Ready Nation” goal and addresses the following objectives within this goal: 1) “Healthy people and communities through improved air and water quality”, and 2) “Reduced loss of life, property, and disruption from high-impact events”.
Lidar provides high resolution information on the altitude dependence of troposphere aerosols and water vapor, providing precise measurements in regions of the lower atmosphere above a city, which would inaccessible to either aircraft or tethered balloons. Retrieved aerosol and trace gas profiles are used to derive variations of the atmospheric structure and transport, gaining knowledge in 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 is leading the Unified Ceilometer Network (UCN), a collaboration between the Hampton University, the University of Maryland-Baltimore County (UMBC), the U.S. Environmental Protection Agency (EPA), National Aeronautics and Space Administration (NASA) and National Atmospheric and Oceanic Administration (NOAA) on a ground-based ceilometer network to support activities that will provide a comprehensive three-dimensional assessment of the chemical and dynamical processes in the lower atmosphere that can aid future policy decisions and strategies to key questions on the influence of gases and aerosols in air quality, atmospheric composition and climate.
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 , trace gases and aerosol variability.
Air Quality Observing System – Measurements and analysis from in-situ/ground, remote sensing (lidar, radar, radiosondes, AERI) and column (ground/satellite measurements) of meteorological variables and air chemical composition are carried out to determine the relative impact of long-range transport versus local emissions during pollution events. This synergetic approach provides a comprehensive 3D monitoring of particle pollution (e.g., aerosols, smoke, dust, etc.), gases and meteorological variables in the Mid-Atlantic United States and that can be expanded throughout the United States. This aids future policy decisions and strategies as the remote sensing observations contribute to provide answers on the influence of gases and aerosols in air quality, atmospheric composition, and climate. Dr. Delgado is a member of the World Meteorological Organization (WMO) Vegetation Fire and Smoke Pollution Warning Advisory and Assessment System (VFSP-WAS) Wildfire Risk Forecast working group.
Environmental Justice: Disparities in Air Quality – Results from receptor models of source apportionment of pollution are correlated to Census population and socio-economic data. This project includes plans to leverage existing relationships with community organizations to enable effective risk communication strategies and to develop scientific literacy. To this end, Dr. Delgado will be collaborating with Dr. Daniel Orozco (National Parks Conservation Association) and Grace Holmes (VA Dept. of Environmental Quality), to facilitate workshops for local state and federal stakeholders in air quality, energy, and natural resources to build community engagement and integrate stakeholders in state and federal environmental, energy and natural resources agencies. Students will be able to contribute to the Tidewater Air Monitoring Evaluation (TAME) project studying the potential health risks associated with dust coming from nearby coal storage and transportation facilities in communities located in Lambert’s Point and the East End, in Norfolk and Newport News, respectively.