GEO-EO-Req ColumnConc for Coverage
Section 2.1.7 Satellite–Based Air Quality Observing Systems
More descriptive explanation of satellite data use is provided relative to other sections as there has been rapid development of applications over the last decade and still changing
An extensive array of satellite-based systems (Table 6) with the capability of measuring atmospheric column total species has been established by United States and European Satellite programs lead by NASA and NOAA in the United States and the European Space Agency (ESA). A suite of satellites including Aqua, Aura, CALIPSO, OCO, Glory, as well as NOAA- 17, NOAA-18 and NPOESS, have either been launched since about the year 2000 or have other near-term proposed launch dates. Collectively, the remote sensing techniques for measuring columns and/or profiles of aerosols (AOD), O3, CO, CO2, CH4, SO2, nitrogen oxides, CFCs, other pollutants, and atmospheric parameters such as temperature and H2O. Most of these satellites have a near-polar orbit allowing for two passes per day over a given location. When taken together, a group of six satellites (Aqua, Aura, CALIPSO, OCO, as well as CloudSat and PARASOL) coined the A-Train is being configured to fly in a formation that crosses the equator a few minutes apart at around 1:30 local time to give a comprehensive picture of earth weather, climate and atmospheric conditions.
Satellite imagery offers the potential to cover broad spatial areas; however, an understanding of their spatial, temporal and measurement limitations is necessary to determine how these systems complement ground based networks and support air quality management assessments. Temporal characterization. The near polar orbiting tracks of most satellites performing trace gas measurements provides wide spatial coverage of reasonable horizontal (10-50 km) resolution, but delivers only twice daily snapshots of a particular species. Consequently, temporal patterns of pollutants as well as a time-integrated measure of pollutant concentrations cannot be delineated explicitly through satellite measurements alone. The Geostationary satellite platforms such as the GOES systems in NOAA do provide near continuous coverage of physical parameters for weather tracking and forecasting purposes. There are proposed campaigns within NASA and across partnership Federal agencies to deploy geostationary platforms with measurement capabilities for trace gases and aerosols to enhance space based characterization of tropospheric air quality (Fishman et al., 2005).
Spatial Characterization. Polar orbiting satellites typically provide horizontal spatial resolution between 10 and 100km, depending on the angle of a particular swath segment. Spatial resolution less than 10km is possible with geostationary platforms. Characterization of elevated pollutants delivered by satellite systems complements of our ground based in-situ measurement networks – especially considering that a considerable fraction of pollutant mass resides well above Earth’s surface. With few exceptions, Satellite data typically represents a total atmospheric column estimate. For certain important trace gases (e.g., NO2, SO2, HCHO) and aerosols, the majority of mass resides in the boundary layer of the lower troposphere, enabling associations linking column data to surface concentrations or emissions fields. For example, reasonable correlations, especially in the Eastern United States, have been developed between concentrations from ground level PM2.5 stations and aerosol optical depths (AOD) from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites (Engel-Cox et al. 2004; Figure 14). The Infusing Satellite Data into Environmental Applications (IDEA, http://idea.ssec.wisc.edu/) site provides daily displays and interpretations of MODIS and surface air quality data. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite (discussed below) provides some ability to resolve aerosol vertical gradients.
Figure 15. Correlation surfaces between MODIS AOD and hourly PM2.5 surface sites from April - September, 2002 (Engel-Cox, et. al, 2004).
In contrast to aerosols, most ozone resides in the stratosphere. Various techniques have been developed to extract the stratospheric signal to yield a tropospheric ozone residual (TOR), based on known homogeneities in the stratosphere and the use of chemical transport models and multiple measurements. Early approaches (Fishman, 1978) before and during the Total Ozone Mapping Spectrometer (TOMS) studies combined LIMB (angled view to characterize stratosphere) and NADIR (downward view, characterizing total column) techniques to derive tropospheric ozone residuals. The 2004 launch of NASA’s Aura mission with multiple ozone sensors is starting to produce more refined tropospheric ozone maps (e.g., Figure 15). However, delineating boundary layer ozone from free tropospheric reservoirs continues to pose significant interpretation challenges.
Figure 16. Daily averaged tropospheric ozone column levels derived from NASA’s OMI in Dobson Units for June 22, 2005 (courtesy, J. Szykman, EPA and J. Fishman, NASA).
Measurement issues. Most satellite air quality observations are based on spectroscopic techniques typically using reflected solar radiation as a broad source of UV through IR electromagnetic radiation (LIDAR aboard CALIPSO does utilize an active laser as the radiation source). While the science of satellite based measurements of trace gases and aerosols is relatively mature, interferences related to surface reflections, cloud attenuation and overlapping spectra of nearby species require adequate filtering and accounting for in processing remote signals. For example, aerosol events episodes associated with clouds often are screened out in developing in applications involving AOD characterizations through MODIS. Correlations between AOD and surface aerosols generally are better in the Eastern U.S. relative to the West because due to excessive surface light scattering from relatively barren land surfaces. Use of Satellite data in air quality management assessments. Satellite data, particularly fire and smoke plume observations and GOES meteorological data, support various air quality forecasting efforts servicing public health advisories. Forecasting is driven by characterizing the environment in current and immediate (1-3 days) future time frames. Air quality assessments require greater confidence in a systems (e.g., a model) response behavior to longer term, and usually much greater, changes in emissions, land use and meteorology; which requires greater confidence in formulation of numerous physical and chemical processes. Despite these differences, research and application products originally catalyzed by forecasting objectives generally overlap well with retrospective air quality assessment needs, the focus of this discussion.
Satellite products complement existing observational platforms and support the air quality assessment process through:
- direct observational evidence of regional and long range intercontinental transport,
- emission inventory improvements through inverse modeling,
- evaluation of Air Quality Models,
- tracking emissions trends (accountability), and
- complementing surface networks through filling of spatial gaps.
As air quality assessments evolve toward embracing more pollutant categories, an attendant need to characterize a variety of spatial (and temporal) scales parallels places demands on developing more compositionally rich characterizations of air pollutants. Satellite technologies combined with partnerships with Federal agencies such as NASA and NOAA are assisting the air quality community by providing data that covers broad spatial regimes in areas lacking ground based monitors and, more importantly, a vertical compliment to our horizontal surface based networks. Although breathing zone monitoring is a rich data source, most pollutant mass resides beyond the representative reach of surface stations. During well mixed conditions with stable pressure systems during the afternoon, pollutant levels aloft often correlate well with surface conditions offering potential for “gap filling” in the surface based networks. Perhaps of greater utility is the use of satellite data to evaluate air quality models used to estimate air quality consequences of future emissions and climate scenarios. Satellite observations can be applied as a constraints on modeled total column mass or emission fields. Satellites support hemispherical and global scale air quality assessments, which are projected to be of increasing importance to North American air quality as both the relative contribution of transported air pollution and air quality-climate interactions increases over the next few decades. The pattern of gradual lowering of air quality standards (Figure 16) also raises the importance of transported air pollution. The 2006 revision of the daily PM2.5 NAAQS from 65 to 35 μg/m3 will increase the relative contribution of trans-oceanic dust transport to violations. Direct observational evidence of long distance transport clearly can be viewed with satellite imagery (Figures 17-18). Satellites often provide the only observation base for evaluating global scale air quality models in regions lacking adequate measurement and emissions inventory resources.
Launched in 2004, NASA’s Aura satellite mission (http://www.nasa.gov/mission_pages/aura/spacecraft/index.html) deploys sensors theoretically capable of measuring all criteria gases, methane, formaldehyde, nitric acid, nitrous oxide, water vapor, radicals (hydroxyl and hydroperoxy) and aerosols – a multiple pollutant space based complement to the NCore multiple pollutant ground based network and intensive field campaigns. NASA’s Orbiting Carbon Observatory (OCO), scheduled to be launched in 2008, will be dedicated to tracking carbon dioxide levels which currently are captured on the Aqua based Atmospheric Infrared Sounder (AIRS) instrument. The Aqua, Terra, Aura and OCO all are part of NASA’s Earth Observation System (EOS). Tropospheric column level ozone for the contiguous United States derived from the Ozone Monitoring Instrument (OMI, Figure 15) provides broad horizontal spatial coverage consistent with global (~ 100km) and regional scale (~ 30 km) Chemical Transport Models (CTM). When used in combination with CTMs, satellite column estimates can be used as an observation driven top-down check and modification through inverse modeling of emission inventories. Satellite data for CO, NO2 and HCHO (Figure 19), as an indicator for biogenic isoprene, have been used for improving emission inventories (Fu et al., 2007; Martin et al., 2003, 2006; As longer term records are developed, satellite imagery offers another means of checking progress of major emission strategy plans as well as illustrating emissions growth in developing parts (East Asia) of the
world (Figures 20 and 21). An August, 2006 incursion of African dust transported across the Atlantic Ocean demonstrates the use of Satellite imagery capturing long range transport events (Figure 18). NASA’s Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission launched in 104 counties violate .084 ppm 294 additional counties violate .075 ppm for a total of 398 135 additional counties violate .070 ppm for a total of 533 63 additional counties violate .065 ppm for a total of 596 22 additional counties violate .060 ppm for a total of 618 21 counties meet .060 ppm for a total of 639
April, 2006 provides both column total and vertically resolved aerosol estimates using an active light source (LIDAR) to quantify light scattering. Resolving vertical gradients provides enhanced support for diagnosing CTM behavior and allows for screening of plumes reaching the surface in developing correlations between surface and satellite observations. CALIPSO builds on the ongoing success of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA’s Terra (EOS AM) and Aqua (EOS PM) satellites which has provided total aerosol column optical depths (AOD) for use in:
- Supporting development of wildfire and prescribed burning emission inventories
(The 2005 NEI will include emissions from fires utilizing MODIS),
- Evaluating ability of air quality models such as CMAQ to characterize total column
aerosol loadings, and
- Complimenting ground based PM2.5 monitors by filling in spatial gaps and adding
intelligence to conceptualize our understanding of aerosol episodes (see http://idea.ssec.wisc.edu/).
- Critical Review - Ray Hoff, Sundar
- Coments on the review
Model Evaluation Section
2. Develop surface based observations to complement satellite based vertical column observations of key emission indicator species. Satellites provide broad spatial coverage of NO2, SO2, HCHO, and CO with potential for evaluating emission estimates and improvements through inverse modeling techniques. This practice has been applied for global modeling efforts, particularly in areas with limited bottom up emissions information (Martin et al., 2003; Fu et al., 2007; Palmer et al., 2006). By comparing observed and calculated total column emissions loadings, satellite data can provide a useful top-down constraint in the emissions evaluation process. Our surface based networks lack adequate spatial coverage of these trace gas species. The combination of ground and satellite based observations leverages the utility of each system by potentially expanding spatial coverage through associations between surface and satellite observations and developing greater confidence in satellite measurements. Formaldehyde serves as an indicator for biogenic isoprene emissions and there are well established relationships between emitted nitrogen oxide and transformed nitrogen dioxide.