Air Quality Management Through Earth Observations & Models

Lawrence Friedl, Doreen Neil, R. Bradley Pierce, and the NASA Air Quality Program Team

Satellite observations and Earth science model products are now serving air quality managers withnformation to support forecasting and planning and enhance air quality policy and decision making. Research and operational atmospheric measurements complement ground measurements to help understand pollution episodes and improve forecasts. This article provides an overview of NASA's Air Quality program, including recent and future applications of NASA spacecraft observations and model products.

NASA & Atmospheric Composition

Table 1: Tropospheric Chemistry & Aerosol Missions. Click on image to see enlarged.

Atmospheric composition is one of the primary focus areas for NASA Earth science research. Atmospheric composition research provides direct observations of trace constituen and aerosols with vertical and temporal resolution for use in global, regional, and climate models. NASA launched Aura in July 2004 to provide tropospheric and stratospheric observations of ozone and trace constituents. NASA plans to launch CloudSat and CALIPSO, a space-based LiDAR, in 2005 to provide measurements of cloud dynamics and vertical structures of aerosols. NASA is also examining observational platforms that can provide new spatial and temporal insights, such as atmospheric measurementsrom geostationary or Lagrange-point orbits. Table 1 provides a synopsis of current spacecraft and sensors that provide tropospheric chemistry and aerosol measurements. The sensors were primarily designed for observations to support global to regional studies, and the spatial and temporal resolution of these sensors vary from sub-kilometer to tens of kilometers. Information on the resolution of these sensors is available through Earth-S System Division and Earth-Sun components websites.

A key priority within NASA is to make the spacecraft observation products available to the community. Some data is available in near real-time through direct broadcast from the satellites. NASA has developed archiving centers and information product federations to encourage and facilitate use of thebservations. In addition, the DataFed gateway facilitates the access, cataloging, and flow of atmospheric data, especially aerosol and emissions measurements initially, to users through "data wrappers" for access by Web services.

NASA Applied Sciences & Air Quality

NASA extends Earth science research results to government, business, and non-profit organizations to support their operational, decision-making responsibilities in order to maximize the sooeconomic benefits from NASA's research and technology. The Air Quality Management Program Element is one of twelve applications of national priority for the NASA Applied Sciences Program [science.hq.nasa.gov/earth-sun/applications].

Figure 1: . Air Quality Program Integrated Systems Solutions Architecture. Click on image to see enlarged.

The NASA Air Quality Management program supports organizations' uses of Earth science results to serve national priority air quality policy and management responsibilities. The Air Quality program focuses on air quality planning and assessment, compliance, and forecasting — especially on issues related to ozone, particulate matter M), transport, emissions, and public and environmental health. The primary federal partners are the US Environmental Protection Agency (EPA), the National Oceanic and Atmospheric Administration (NOAA), and the US Department of Agriculture (USDA). Figure 1 depicts the framework architecture that illustrates the Air Quality Program's approach; a complete description is available through the Applied Sciences Program's website.

Rent and current projects include use of space-based aerosol observations to support EPA's AIRNow Air Quality Index (AQI); use of EP-TOMS, solar occultation, and GOES ozone data via global and regional chemical data assimilation to support the Community Multi-scale Air Quality (CMAQ) model; use of MODIS aerosol data to support the draft EPA Interstate PM Transport Rule-making; and support to emissions inventories, regional haze, and fire emissions decision support tools, such as BlueSkyRAINS.

Projects related to the use of Earth science spacecraft and models for air quality forecasting and planning are described below.

Air Quality Forecasting

NASA launched the Terra and Aqua satellites to gather information to answer fundamental scientific questions about the Earth system, including how aerosols affect the climate and generate other pollutants. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard NASA's Terra and Aquaatellites gather information about the location and thickness of dust and haze. When several MODIS products are used in combination, users can distinguish between clouds and dust/haze and can track the severity and movement of pollution events across regions and continents.

Figu 2: . MODIS visible image of haze and clouds (10 Sept. 2002). Image from NASA-Goddard Space Flight Center and NASA-Langley Research Center.

Two standard MODIS products include the Aerosol Optical Depth (AOD), which is a measure of the total extinction by aerosols from the satellite to the ground, and the Cloud Optical Thickness (COT). MODIS AOD values retrieved over land use 500 meter bands at 0.47 and 0.66 micrometer and interpolated to 0.55 micrometer in order to be mapped with those retrieved overcean. Figures 2 and 3 provide a visible image and a processed image for AOD and COT; the comparisons highlight Hurricane Gustav off the East Coast and high aerosol/haze conditions in the Midwest. In addition to aerosol thickness, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents, and daily Level 2 data are produced at the spatial resolution of a 1010 1-kilometer (nadir)-pixel array.

Figure 3: . MODIS processed image of aerosol optical depth and cloud optical thickness (10 Sept. 2002). Image from NASA-Goddard Space Flight Center and NASA-Langley Research Center. Click on image to see enlarged.

The AIRNow program is a joint partnership between EPA and state and local air quality agencies to provide real-time air quality information in a visual format, such as thAir Quality Index (AQI), to numerous cities across the country. The AQI is derived using an extensive network of ground monitors, and the system alerts the public once pollution levels exceed a certain level so that sensitive groups may restrict their outdoor activities. A team of researchers from NASA, EPA, NOAA, and academia has prototyped the use of near real-time MODIS satellite data in AQI to help forecasters improve the next-day, regional forecasts of particle pollution, and forecasters now include satellite-based techques in operational use. The visual nature of the satellite images provides significant opportunities to describe pollution events to the media and the public and explain the broader conditions and contributing factors leading to the pollution event.

The project team initially developed a "fused" product that combined EPA ground measurements with the MODIS satellite data and expanded this product to multiple-day, time-looped animations of aerosol levels and trends. These tools provided the ability to identifand track the frequency and extent of particle pollution transport episodes. During a prototype test, the project team created three-day loops, each showing MODIS aerosol and cloud data over the entire continental United States, overlaid by either wind vectors or air parcel trajectories and hourly measured ground particle concentration data from TEOM monitors. The visualizations were created using Virtual Global Explorer and Observatory (VGEO) by VRCO Inc., and the products were updated and delivered daily to test forecastervia the project website.

Figure 4: Individual picture file extracted from the data fusion and alysis of a large scale PM event in September 2002. Relationship between aerosols, clouds, winds, fire locations and ground aerosol measurements to provide a pseudo-synoptic view of aerosol events across North America. Image from NASA-Goddard Space Flight Center and NASA-Langley Research Center. Click on image to see enlarged.

Figure 4 shows an individual picture file extracted from the data fusion and analysis of a large scale PM event in September 2002. The fure shows MODIS aerosol optical depth (color contours); MODIS cloud optical thickness (gray contours); hourly PM2.5 (particulate matter that is 2.5 micrometers or smaller in size) concentrations from TEOM monitors (vertical color bars-AQI level); NCEP re-analysis winds fields (red arrows); and WF-ABBA fire counts (pink and violet triangles). NOAA Hysplit air parcel trajectories (not shown) were also modeled.

The project team relied on the MODIS "direct broadcast capability." While spacecraft usually collect d store data on-board and transmit the data to ground stations in large batches, MODIS stores data on board and also broadcasts the raw data it collects immediately. Ground stations equipped to receive the MODIS data can receive the data in real-time. Both the Terra and Aqua spacecraft have the MODIS sensor on board; they are polar orbiting satellites and have equatorials crossings at 10:30 am and 1:30 pm, respectively, providing morning and afternoon measurements.

The data fusion product visualizes e relationship between MODIS AOD and PM2.5 ground monitor data. The three-day visualization loops show how MODIS AOD can depict temporal and spatial relationships to provide a synoptic view of aerosol events across North America and support forecasting efforts. Analyses have indicated strong correlations between the hourly PM2.5 surface monitors and AOD levels in coincident pixels (10 kilometer x 10 kilometer).

Figure 5: Integrated systems approach to collect and transfer MODIS and other products and NASA-Langley Research Center.

Figure 5 illustrates the integrated systems approach used to collect and transfer the combination of satellite, model, and ground monitor products to the appropriate users and fecasters. NASA, EPA, NOAA, the University of Wisconsin-Madison, AIRNow forecasters, and others collaborated to develop the techniques and prototype systems and the transition to NOAA for full operational status.

Forecasters use the images and data fusion products to understand the factors and influences contributing to a previous episode, thereby improving their skill for future forecasts. This project focused on particulate pollution and the NASA Air Quality program plans to pursue activities with NOAA and EPA to suprt air quality forecasting and forecasting guidance for ozone and other criteria pollutants. More information about this system and the use of satellite products in air quality forecasts is available through the project website and the US Air Quality Smog Blog.

Air Quality Planning and CMAQ

The CMAQ modeling system supports the environmental management community's ability to evaluate the impact of air quity management practices for multiple pollutants at multiple scales. EPA uses CMAQ in its assessments of compliance with the National Ambient Air Quality Standards (NAAQS) and organizations use CMAQ to develop control strategies in state implementation plans. Since some pollutants are transported over large areas in addition to their local production, satellite observations and Earth science global-regional models provide techniques to support improved constraints on the lateral boundary conditions and vertical domain of airuality models.

Researchers from NASA, EPA, and universities are working to evaluate approaches to use Earth science models and satellite observations to provide boundary conditions into the Models-3 CMAQ. One approach provides lateral boundary conditions generated from a global model through a global assimilation of satellite-observed ozone. A second approach uses the results of the global assimilation/regional prediction and adds the direct assimilation of GOES satellite ozone retrievals into CMAQ. In both cases, theroject will conduct a simulation of the SOS99 period and assess whether CMAQ simulations show better performance with the approaches. The primary modeling tool used for the global assimilation is the Regional Air Quality Modeling System (RAQMS), which is a global-to-regional scale air quality modeling and data assimilation system developed at NASA Langley Research Center.

Figure 6: Merged total column ozone prediction for 20Z (4pm EDT) on 7 July 1999; RAQMS analysis of upper atmosphere and CMAQ prediction of lower atmosphere. Courtesy of NASA-Langley Research Center.

Figure 6 shows results from the first phase of this project, where RAQMS global ozone analyses are used to constrain lateral boundary conditions for CMAQ predictions. The figure shs the merged total column ozone prediction for 20Z (4:00 pm) on 7 July 1999. Since CMAQ only extends into the lower-most stratosphere (about 15 kilometers) the total column prediction was obtained by combining the CMAQ prediction of the lower atmosphere with the RAQMS analysis of the upper atmosphere (about 15-60 kilometers).

The merged total column prediction shows a streamer of high total column ozone entering the CMAQ domain from Central Canada along the Great Lakes and a second streamer of high total column ozone tering in the Pacific Northwest. These regions of high column ozone are indications of stratospheric folding events which can lead to enhancements in upper tropospheric ozone. Relatively low total column ozone extends from the Subtropical Pacific associated with the northward transport of tropical marine boundary layer air into the western part of CMAQ domain at this time. Total column ozone enhancements of 30-50 Dobson Units (DU) are evident over the eastern United States. These enhancements are largely associated with situ ozone production within the continental boundary layer, leading to increased surface ozone and elevated AQI at this time.

Figure 7: GOES total column ozone observations for 20Z on 7 July 1999. Similar features as the merged column ozone predictions (ta gaps over Pacific, Western U.S. and Gulf states are associated with clouds). Courtesy of NASA-Langley Research Center.

Figure 7 shows the corresponding GOES total column ozone at 20Z on 7 July 1999. The data gaps as over the Pacific, western United States, and Gulf states are associated with clouds. The GOES observations show very similar features as the merged column ozone predictions and provide initial conformation of the impact of lateral boundary conditions on the CMAQ predictions.

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