K. Chance, X. Liu, C. Chan Miller, G. González Abad, G. Huang, C. Nowlan, A. Souri, R. Suleiman, K. Sun, H. Wang, L. Zhu, P. Zoogman, J. Al-Saadi, J. -C. Antuña-Marrero, J. Carr, R. Chatfield, M. Chin, R. Cohen, D. Edwards, J. Fishman, D. Flittner, J. Geddes, M. Grutter, J. Herman, D. Jacob, S. Janz, J. Joiner, J. Kim, N. Krotkov, B. Lefer, R. Martin, O. Mayol-Bracero, A. Naeger, M. Newchurch, G. Pfister, K. Pickering, R. Pierce, C. Rivera Cárdenas, A. Saiz-Lopez, W. Simpson, E. Spinei, R. J. Spurr, J. Szykman, O. Torres, J. Wang
The NASA/Smithsonian Tropospheric Emissions: Monitoring of Pollution (TEMPO; tempo.si.edu) satellite instrument will measure atmospheric pollution and much more over Greater North America at high temporal resolution (hourly or better in daylight, with selected observations at 10 minute or better sampling) and high spatial resolution (10 km2 at the center of the field of regard). It will measure ozone (O3) profiles (including boundary layer O3), and columns of nitrogen dioxide (NO2), nitrous acid (HNO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), water vapor (H2O), bromine oxide (BrO), iodine oxide (IO), chlorine dioxide (OClO), as well as clouds and aerosols, foliage properties, and ultraviolet B (UVB) radiation. The instrument has been delivered and is awaiting spacecraft integration and launch in 2022. This talk describes a selection of TEMPO applications based on the TEMPO Green Paper living document (http://tempo.si.edu/publications.html).
Applications to air quality and health will be summarized. Other applications presented include: biomass burning and O3 production; aerosol products including synergy with GOES infrared measurements; lightning NOx; soil NOx and fertilizer application; crop and forest damage from O3; chlorophyll and primary productivity; foliage studies; halogens in coastal and lake regions; ship tracks and drilling platform plumes; water vapor studies including atmospheric rivers, hurricanes, and corn sweat; volcanic emissions; air pollution and economic evolution; high-resolution pollution versus traffic patterns; tidal effects on estuarine circulation and outflow plumes; air quality response to power blackouts and other exceptional events.
Aircraft remote sensing of freshwater ecosystems offers federal and state monitoring agencies an ability to meet their assessment requirements by rapidly acquiring information on ecosystem responses to environmental change for water bodies that are below the resolution of space-based platforms. During this study, hyperspectral data were collected over a two-day period from glacial lakes, ponds, and man-made reservoirs in New Hampshire, Massachusetts, Connecticut, and Rhode Island. These lakes ranged from five to greater than 1600 hectares and oligotrophic-mesotrophic to eutrophic and hypereutrophic conditions. Water samples were collected by several New England state agencies coincident with the airborne remote-sensing flights to provide ground reference data for algorithm development and testing. Using an inverse modeling approach remotely sensed reflectances from the near-infrared to red portion of the spectrum were used to develop an empirical model to estimate chlorophyll a concentrations. The accuracy of the algorithm was assessed from the RSM error of predicted and measured chlorophyll values for all lakes sampled. Results showed a strong statistical relationship between measured and predicted values. The predicted chlorophyll concentrations were used to assess the biological condition, trophic status, and recreational risk to human health for the New England lakes and ponds surveyed.
Amber Soja, Jassim Al-Saadi, Louis Giglio, Dave Randall, Chieko Kittaka, George Pouliot, Joseph Kordzi, Sean Raffuse, Thompson Pace, Tom Pierce, Tom Moore, Biswadev Roy, Bradley Pierce, James Szykman
Biomass burning is significant to emission estimates because: (1) it is a major contributor of particulate matter and other pollutants; (2) it is one of the most poorly documented of all sources; (3) it can adversely affect human health; and (4) it has been identified as a significant contributor to climate change through feedbacks with the radiation budget. Additionally, biomass burning can be a significant contributor to a regions inability to achieve the National Ambient Air Quality Standards for PM 2.5 and ozone, particularly on the top 20% worst air quality days. The United States does not have a standard methodology to track fire occurrence or area burned, which are essential components to estimating fire emissions. Satellite imagery is available almost instantaneously and has great potential to enhance emission estimates and their timeliness. This investigation compares satellite-derived fire data to ground-based data to assign statistical error and helps provide confidence in these data. The largest fires are identified by all satellites and their spatial domain is accurately sensed. MODIS provides enhanced spatial and temporal information, and GOES ABBA data are able to capture more small agricultural fires. A methodology is presented that combines these satellite data in Near-Real-Time to produce a product that captures 81 to 92% of the total area burned by wildfire, prescribed, agricultural and rangeland burning. Each satellite possesses distinct temporal and spatial capabilities that permit the detection of unique fires that could be omitted if using data from only one satellite.
We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detections and instantaneous fire size estimates from geostationary GOES sensors. Each technique uses a different approach for estimating trace gas and particulate emissions from active fires. Here we evaluate monthly area burned and CO emission estimates for most of 2006 over the contiguous United States domain common to all four techniques. Two techniques provide global estimates and these are also compared. Overall we find consistency in temporal evolution and spatial patterns but differences in these monthly estimates can be as large as a factor of 10. One set of emission estimates is evaluated by comparing model CO predictions with satellite observations over regions where biomass burning is significant. These emissions are consistent with observations over the US but have a high bias in three out of four regions of large tropical burning. The large-scale evaluations of the magnitudes and characteristics of the differences presented here are a necessary first step toward an ultimate goal of reducing the large uncertainties in biomass burning emission estimates, thereby enhancing environmental monitoring and prediction capabilities.
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.
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.
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.
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