In 2006, we began a three-year project funded by the NASA Integrated Decisions Support program to develop a three-dimensional air quality system (3D-AQS). The focus of 3D-AQS is on the integration of aerosol-related NASA Earth Science Data into key air quality decision support systems used for air quality management, forecasting, and public health tracking. These will include the U.S. Environmental Protection Agency (EPA)'s Air Quality System/AirQuest and AIRNow, Infusing satellite Data into Environmental Applications (IDEA) product, U.S. Air Quality weblog (Smog Blog) and the Regional East Atmospheric Lidar Mesonet (REALM). The project will result in greater accessibility of satellite and lidar datasets that, when used in conjunction with the ground-based particulate matter monitors, will enable monitoring across horizontal and vertical dimensions. Monitoring in multiple dimensions will enhance the air quality community's ability to monitor and forecast the geospatial extent and transboundary transport of air pollutants, particularly fine particulate matter. This paper describes the concept of this multisensor system and gives current examples of the types of products that will result from it.
The University of Maryland Baltimore County (UMBC) airborne Visible-Near Infrared (VNIR) hyperspectral sensor is a grating spectrometer that collects data in the 380 to 985 nm spectral range with spectral resolution as high as 1.15 nm. This imager is a push-broom type sensor utilizing a two dimensional charge coupled device (CCD, 480×640) camera to collect the spectral information along a single line on the ground perpendicular to the aircraft flight line. The UMBC sensor can provide measurements for a variety of studies, including land development and land use, cultivated and natural vegetation and forestry, and water turbidity and coastal environments. Due to the sensor's wealth of spectral bands, high signal-to-noise, and narrow band widths, a number of atmospheric constituents can be also detected that can be incorporated into atmospheric correction models to benefit the retrievals of surface properties. We present a detailed description of the sensor as well as preliminary results of its calibration in this paper. Related on-going research and some potential applications of this sensor are summarized.
Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and Aqua satellites, were take over the Central Valley. The MODIS Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km.
The Central Valley topography was overlaid with MODIS AOD (5x5 km2 resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and MODIS AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the MODIS AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.
High resolution (5x5 km2 horizontal resolution) retrievals of aerosol optical depth (AOD) from the MODerate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA's Aqua and Terra satellite platforms have been examined. These data products have been compared to coincident, hourly measurements of ground-based PM-2.5 routinely obtained by the San Joaquin Valley Air Pollution Control District (SJV APCD) and California Air Resources Board (CARB) and to airborne light detection and ranging (lidar) aerosol scattering measurements obtained by NASA in July 2003 in San Joaquin Valley (SJV). Comparison of MODIS AOD to ground based PM-2.5 measurement shows significant improvement for the higher resolution MODIS AOD. Lidar aerosol scattering measurements correspond well to MODIS AOD during a variety of atmospheric conditions, and throughout the SJV. Future lidar measurements are proposed to establish a high resolution vertical link between satellite and ground-based measurements during the winter. With the data from these two episodes, we plan to characterize the horizontal, vertical, and temporal distribution of PM-2.5 in SJV and evaluate the need for future intensive ground-based measurement and modeling studies in SJV.
We present an intercomparison of retrieved dust parameters obtained from
analyzing AIRS and MODIS satellite data. Recent papers have highlighted
using AIRS data to retrieve dust top (layer) height, loading and particle size.
Different methods have been used, such as assuming a fixed particle size
and dust top height before fitting radiance
data from selected AIRS channels, or using lookup tables to retrieve dust
loading, height and particle size. In this paper we use the combination
of dust retrievals from MODIS visible and AIRS thermal infrared channels
to provide information on dust top height by forcing the error term (or
intercept of the linear regression of dust optical depths retrieved from
MODIS and AIRS) to zero. When available, GLAS measurements will be used to
validate dust top height. Collocated ship based M-AERI observations, obtained in March 2004 during the AEROSE campaign will also be analyzed to verify this
approach.
MODIS aerosol optical depth (AOD) product provides a quantitative measure of columnar aerosol abundance over both land and ocean. The satellite-derived AOD has shown to correlate with surfaced-measured PM2.5 (particulate matter particulate matter with aerodynamic diameter < 2.5 μm) concentration. The timely MODIS AOD product from direct broadcasting facilitates near real-time (1-2 hours after satellite overpass) monitoring of PM distribution and movement over the continental US the Infusing Satellite into Environmental Application (IDEA) (http://idea.ssec.wisc.edu). Many questions, however, are raised in regard to correlation between AOD and PM2.5. In this paper, we characterize the correlation between MODIS AOD and surface-measured PM2.5 in different conditions and introduce mean absolute error as a second measure to help assess satellite derived AOD for air quality application.
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