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Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air quality): A Study of how the Urban Landscape Affects Meteorology and Air Quality Through Time

It is our intent through this investigation to help facilitate measures that can be Project ATLANTA (ATlanta Land-use ANalysis: applied to mitigate climatological or air quality Temperature and Air-quality) is a NASA Earth degradation, or to design alternate measures to sustain Observing System (EOS) Interdisciplinary Science or improve the overall urban environment in the future. investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta. The primary objectives for this research effort are: 1) To In the last half of the 20th century, Atlanta, investigate and model the relationship between Atlanta Georgia has risen as the premier commercial, urban growth, land cover change, and the development industrial, and transportation urban area of the of the urban heat island phenomenon through time at southeastern United States. The rapid growth of the nested spatial scales from local to regional; 2) To Atlanta area, particularly within the last 25 years, has investigate and model the relationship between Atlanta made Atlanta one of the fastest growing metropolitan urban growth and land cover change on air quality areas in the United States. The population of the through time at nested spatial scales from local to Atlanta metropolitan area increased 27% between 1970 regional; and 3) To model the overall effects of urban and 1980, and 33% between 1980-1990 (Research development on surface energy budget characteristics Atlanta, Inc., 1993). Concomitant with this high rate of across the Atlanta urban landscape through time at population growth, has been an explosive growth in nested spatial scales from local to regional. Our key retail, industrial, commercial, and transportation goal is to derive a better scientific understanding of how services within the Atlanta region. This has resulted in land cover changes associated with urbanization in the tremendous land cover change dynamics within the Atlanta area, principally in transforming forest lands to metropolitan region, wherein urbanization has urban land covers through time, has, and will, effect consumed vast acreas of land adjacent to the city local and regional climate, surface energy flux, and air proper and has pushed the rural/urban fringe farther quality characteristics. Allied with this goal is the and farther away from the original Atlanta urban core. prospect that the results from this research can be An enormous transition of land from forest and applied by urban planners, environmental managers agriculture to urban land uses has occurred in the and other decision-makers, for determining how Atlanta area in the last 25 years, along with subsequent urbanization has impacted the climate and overall

Quattrochi, Dale A.↗

Gulf of Mexico Air Quality: CALIPSO Support for Gulf of Mexico Air Quality Relating to the Deepwater Horizon Oil Spill

On April 20, 2010, an oil platform belonging to BP exploded and leaked a huge volume of oil into the Gulf of Mexico. In an effort to control the spread of the oil, BP applied dispersants such as Corexit and conducted in-situ burnings of the oil. This catastrophe created a complex chain of events that affected not only the fragile water and land ecosystems, but the humans who breathe the air every day. Thousands of people were exposed to fumes associated with oil vapors from the spill, burning of the oil, and the toxic mixture of dispersants. While aiding in clean-up efforts, local fishermen were directly exposure to fumes when working on the Gulf. A notable amount of Gulf Coast residents were also exposed to the oil fumes as seasonal southeasterly winds blew vapors toward land. The Volatile Organic Compounds (VOC) found in oil vapors include: benzene, toluene, ethyl benzene, xylene, naphthalene, hydrogen sulfide and particulate matter (PM). Increases in water temperature and sunlight due to the summer season allow for these VOCs and PM to evaporate into the air more rapidly. Aside from the VOCs found in oil vapors, the dispersant being used to break up the oil is highly toxic and is thought to be even more toxic than the oil itself (EPA website, 2010). To protect human health, the environment, and to make informed policy decisions relevant to the spill, the EPA Region 6 has continuously monitored the affected areas carefully for levels of pollutants in the outdoor air that are associated with petroleum products and the burning of oil along the coast. In an effort to prevent, prepare for, and respond to future oil spills that occur in and around inland waters of the United States, the EPA has been working with local, state, and federal response partners. Air quality measurements were collected by the EPA at five active monitoring systems stationed along the coast.

Nguyen, Myngoc T.↗

3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

The Clean Air Interstate Rule (CAIR) is expected to reduce transport of air pollutants (e.g. fine sulfate particles) in nonattainment areas in the Eastern United States. CAIR highlights the need for an integrated air quality observational and modeling system to understand sulfate as it moves in multiple dimensions, both spatially and temporally. Here, we demonstrate how results from an air quality model can be combined with a 3d monitoring network to provide decision makers with a tool to help quantify the impact of CAIR reductions in SO2 emissions on regional transport contributions to sulfate concentrations at surface monitors in the Baltimore, MD area, and help improve decision making for strategic implementation plans (SIPs). We sample results from the Community Multiscale Air Quality (CMAQ) model using ensemble back trajectories computed with the NASA Langley Research Center trajectory model to provide Lagrangian time series and vertical profile information, that can be compared with NASA satellite (MODIS), EPA surface, and lidar measurements. Results are used to assess the regional transport contribution to surface SO4 measurements in the Baltimore MSA, and to characterize the dominant source regions for low, medium, and high SO4 episodes.

Fairlie, T. D.↗

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Quattrochi, Dale A.↗

Forecasting with the GEOS-CF System and Other NASA Resources to Support Air Quality Management

Air quality (AQ) is a major and growing concern for public health around the world. Economic development, population growth, and climate change are all expected to exacerbate already poor AQ in many regions. Furthermore, AQ is often only sparsely monitored with reference-grade in-situ instruments. NASA resources and products have the potential to help in addressing this AQ data gap. The GEOS-CF (Goddard Earth Observing System – Composition Forecasting) global atmospheric composition modeling system is run each day at a global scale to provide recent estimates and five-day forecasts at hourly temporal resolution of atmospheric constituents relevant to AQ. NASA satellite missions (along with those of other space agencies) provide remotely-sensed estimates of atmospheric composition relevant to AQ. This paper gives a brief overview of these capabilities, and outlines the efforts underway to combine model forecasts, satellite retrievals, and surface-based measurements to provide more comprehensive and accurate estimates and forecasts of local AQ which will be broadly applicable and accessible globally.

GEOS-CF↗

San Joaquin Valley Health & Air Quality II: Assessing Urban Heat Island Distribution and its Intersections with Air Quality to Understand Converging Vulnerabilities

The city of Stockton, California, located within the San Joaquin Valley (SJV), is a major hub for agricultural production and has endured the continuous threat to community health from nitrogen dioxide (NO 2 ) and increasing temperatures. The convergence of these issues occurs within historically segregated communities that are disproportionately facing health risks related to heat and air quality. Little Manila Rising (LMR), a social and environmental justice (EJ) advocacy non-profit, partnered with NASA DEVELOP for a second term project to evaluate county wide urban heat islands, sociodemographic vulnerability, landcover classification, and the convergence of these variables. We utilized Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI) data to produce a land surface temperature (LST) and Normalized Difference Vegetation Index map. They added Centers for Disease Control (CDC) socioeconomic data from 2020 to identify which communities in Stockton were more susceptible to these environmental factors. Additionally, we used NAIP imagery to create a landcover map differentiating developed infrastructure from tree canopy cover. We discovered that south Stockton, where LMR resides, had the worst convergence of heat, air pollution, low canopy coverage and sociodemographic vulnerability compared to northern and rural parts of the city. This was further substantiated by statistical analysis showing a strong positive relationship between areas of high LST and low vegetation. The results provided LMR with compelling evidence to use in their EJ advocacy, and in their efforts to inform state officials of the discriminatory issues they face.

Urban Heat Islands↗

Forecasting with the GESO-CF System and Other NASA Resources to Support Air Quality Management

Air quality (AQ) is a major and growing concern for public health around the world. Economic development, population growth, and climate change are all expected to exacerbate already poor AQ in many regions. Further-more, AQ is often only sparsely monitored with reference-grade in-situ instruments. NASA resources and products have the potential to help in addressing this AQ data gap. The GEOS-CF (Goddard Earth Observing System –Composition Forecasting) global atmospheric composition modeling system is run each day at a global scale to provide recent estimates and five-day forecasts at hourly temporal resolution of atmospheric constituents relevant to AQ. NASA satellite missions (along with those of other space agencies) provide remotely-sensed estimates of atmospheric composition relevant to AQ. This paper gives a brief over-view of these capabilities, and outlines the efforts underway to combine model forecasts, satellite retrievals, and surface-based measurements to provide more comprehensive and accurate estimates and forecasts of local AQ which will be broadly applicable and accessible globally.

Forecasting↗

An Ensemble Investigation of the Causes for Regional Air-Quality Model Critical Load Exceedances Prediction Variability in European and North American Domains Using Diagnostics From Phase 4 of the Air Quality Model Evaluation International Initiative

We summarize tentative findings from multi air quality model ensembles for the years 2009 and 2010 in Europe (EU), and 2010 and 2016 in North America (NA), under AQMEII-4. The model predictions of sulphur and nitrogen deposition were used to estimate exceedances of critical loads for acidification and eutrophication, to show the extent to which the ensemble members agree in the magnitude and the trend of ecologically meaningful impacts. Model exceedance variability was analyzed using AQMEII-4 diagnostics. Evaluation against concentration and wet deposition observations, coupled with these diagnostics, identified specific process representations as the causes for variability between model predictions and for reduced model performance. All models predicted reductions in ecosystem acidification impacts in North America between the years 2010 and 2016, in accord with SO2 emissions reduction legislation which started in 2010 (SO2 SIP) However, all models in EU and NA domains had net negative biases for wet deposition of sulphur and nitrogen relative to observations. The wet S deposition average mean bias for the NA ensemble was -0.17 eq ha-1 d-1, and for the EU ensemble -1.15 eq ha-1 d-1. The NA daily wet deposition average mean bias for NH4+ was -0.37 eq ha-1d-1; EU -1.19 eq ha-1 d-1. The daily NA wet NO3- deposition average mean bias was -0.24 eq ha-1d-1; EU -0.69 eq ha-1 d-1. The members of the ensemble diverged (factor of 10) in their North American predictions for Ndep and consequently their eutrophication exceedances. The models with the highest eutrophication predictions also predicted the highest levels of gas-phase ammonia dry deposition (standard deviation of ammonia dry deposition flux across ensemble members was larger than the ensemble average). These models also had negative biases of predicted ammonia concentrations; average mean biases of -0.63 (satellite NH3) and -0.85 ppbv (surface NH3) compared to ensemble averages of -0.30 and -0.34 ppbv. Diagnostics showed that these differences resulted from the manner in which bidirectional ammonia fluxes were parameterized within these models. The second largest source of NA eutrophication prediction variability were models with positive biases in particulate ammonium and nitrate concentrations, and higher particle nitrogen deposition levels ( particle ammonium concentration bias +0.35 ug m-3; ensemble bias +0.15 ug m-3). We believe two factors may have led to these latter overestimates: higher levels of fine mode particle nitrate formation compared to other models (due to the use of an inorganic heterogeneous chemistry algorithm which did not take base cation chemistry into account), and updates to particle dry deposition velocities carried out in the absence of concurrent updates to wet scavenging algorithms. The relative importance of dry gas, dry particulate, and wet deposition towards total sulphur and nitrogen deposition totals differed between EU and North American domains, though all models had negative biases in wet deposition as noted above. Parallel and subsequent work suggests that multiphase hydrometeor scavenging may improve model wet deposition performance. An increased research focus is recommended for four model processes: multiphase hydrometeor scavenging, ammonia bidirectional fluxes, base cation chemistry and emissions, and particle dry deposition.

regional air-quality model↗

Great Salt Lake Health and Air Quality: Monitoring Lakebed Exposure and its Impact on Air Quality and Environmental Hazards in the Great Salt Lake Watershed

Water flow into the Great Salt Lake has declined rapidly over the last forty years due to human withdrawals and climate change. As a result of declining lake levels, over 50% of the lakebed is now exposed. Dust storms may grow in frequency and intensity across Northern Utah as lakebed dust becomes airborne under specific meteorological conditions. In our research project, we utilized satellite imagery from Terra and Aqua, Sentinel-5P, CALIPSO, Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI-2, Suomi NPP, ground sensor environmental data, and demographic data to understand the relationship between lake desiccation and dust, and the impact of pollution upon the communities surrounding the Great Salt Lake. By plotting changes in Lake Surface Area against Aerosol Optical Depth (AOD) over our study period (2010-2022), we found an inverse relationship (R2=0.3423) between lake surface area and dust levels within our study area. We conducted a Vertical Feature Mask (VFM) and Extinction Coefficient Plot, from which we identified that during dust events, the aerosol type is mainly polluted dust and the aerosol height is 200 meters from the surface. Lastly, we created bivariate choropleth maps, which demonstrate which census tracts within our study area are most vulnerable to AOD (a proxy for PM2.5 from dust), NO2 and HCHO (precursors to ozone). In summary, our findings revealed that declining lake levels are associated with an increase in intensity of dust events, and these dust events will particularly impact residents of Tooele County and the west side of Salt Lake City. Project resources support partner needs by informing targeted air monitoring efforts, lakebed management practices, and advocacy efforts for GSL stewardship.

Terminal Saline Lake↗

Great Salt Lake Health & Air Quality: Monitoring Lakebed Exposure and its Impact on Air Quality and Environmental Hazards in the Great Salt Lake Watershed

The Great Salt Lake (GSL) is a terminal saline lake located in northern Utah, USA. Water inflow has declined rapidly over the last forty years due to human withdrawals and climate change. Lake levels have been lowered which has exposed over 50% of the lakebed to erosion. There is a public health risk tied to the subsequent increased frequency and intensity of regional dust storms caused by airborne lakebed dust under specific meteorological conditions.

Piper Christian↗

Great Salt Lake Health & Air Quality: Monitoring Lakebed Exposure and its Impact on Air Quality and Environmental Hazards in the Great Salt Lake Watershed

The Great Salt Lake (GSL) is a terminal saline lake located in northern Utah, USA. Water inflow has declined rapidly over the last forty years due to human withdrawals and climate change. Lake levels have been lowered which has exposed over 50% of the lakebed to erosion. There is a public health risk tied to the subsequent increased frequency and intensity of regional dust storms caused by airborne lakebed dust under specific meteorological conditions.

Piper Christian↗

Delaware Basin Health and Air Quality: Spatiotemporal Analysis of Air Pollutants Collected from Ground and Space Instruments Around the Guadalupe Mountains and Carlsbad Caverns National Parks

Nitrogen dioxide (NO2) is a precursor for secondary air pollutants, which are associated with decreased visibility, and decreased ecosystem and respiratory health. NO2 is a growing threat to national parks within the Delaware Basin where nearby oil and gas activity contributes to deteriorating park conditions, implying adverse effects on the local tourism economy and public health. To demonstrate spatial and temporal patterns of air pollution in the parks, we examined average monthly, seasonal, and annual tropospheric column concentrations of NO2 in Carlsbad Caverns (CAVE) and Guadalupe Mountain (GUMO) National Parks. We used both the NASA Ozone Monitoring Instrument (OMI) and the European Space Agency (ESA) Tropospheric Monitoring Instrument (TROPOMI) to map NO2 tropospheric column densities. Using ground-based emissions values from the Environmental Protection Agency National Emissions Inventory (NEI) for two nearby natural gas processing plants (Indian Basin Gas Plant, South Carlsbad Plant), we extrapolated monthly trends from these point sources and compared seasonal emissions levels with the measurements recorded by OMI and TROPOMI. The NEI data show an 8% increase in flaring from 2013–2021. OMI measured a 38.3% NO2 increase over the Delaware Basin, 15.29% increase over CAVE, and 4.26% decrease over GUMO from 2011–2018. TROPOMI measured a -1% NO2 change over the Delaware Basin, 3% over CAVE, and 7% over GUMO from 2018–2020. The analysis indicates a positive correlation between emissions from fossil fuel exploration and NO2 concentrations above CAVE and GUMO. This information will inform National Park Service air quality monitoring and policy efforts to ensure compliance with the Clean Air Act.

Sean Cusick↗