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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

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↗
NASA NTRS2022

The Importance of Internal Climate Variability in Climate Impact Projections

Uncertainty in climate projections is driven by three components: scenario uncertainty, intermodel uncertainty, and internal variability. Although socioeconomic climate impact studies increasingly take into account the first two components, little attention has been paid to the role of internal variability, although underestimating this uncertainty may lead to underestimating the socioeconomic costs of climate change. Using large ensembles from seven coupled general circulation models with a total of 414 model runs, we partition the climate uncertainty in classic dose–response models relating county-level corn yield, mortality, and per-capita gross domestic product to temperature in the continental United States. The partitioning of uncertainty depends on the time frame of projection, the impact model, and the geographic region. Internal variability represents more than 50% of the total climate uncertainty in certain projections, including mortality projections for the early 21st century, although its relative influence decreases over time. We recommend including uncertainty due to internal variability for many projections of temperature-driven impacts, including early-century and midcentury projections, projections in regions with high internal variability such as the Upper Midwest United States, and impacts driven by nonlinear relationships.

climate impacts↗
NASA NTRS2023

Structural Chokepoints Determine the Resilience of Agri-Food Supply Chains in the United States

The agricultural and food systems of the United States are critical for ensuring the stability of both domestic and global food systems. Thus, it is essential to understand the structural resilience of the country’s agri-food supply chains to a suite of threats. Here we employ complex network statistics to identify the spatially resolved structural chokepoints in the agri-food supply chains of the United States. We identify seven chokepoints at county scale: Riverside CA, San Bernardino CA, Los Angeles CA, Shelby TN, Maricopa AZ, San Diego CA and Cook IL; as well as seven chokepoints at freight analysis framework scale: Los Angeles–Long Beach CA, Chicago– Naperville IL, New York–New Jersey NJ, New York–New Jersey NY, Remainder of Texas, Remainder of Pennsylvania, and San Jose–San Francisco–Oakland CA. These structural chokepoints are generally consistent through time (2007, 2012, 2017), particularly for processed food commodities. This study improves our understanding of agri-food supply-chain security and may aid policies aimed at enhancing its resilience.

Agriculture↗
NASA NTRS2023

New York Ecological Conservation: Evaluating Agricultural Conservation Easement Impact Using Earth Observations to Examine Avoided Soil Carbon Loss to Development

Farmland provides ecosystems and communities with services ranging from habitat conservation to food security. As total U.S. farmland continues to decline, agricultural lands near urban areas are especially vulnerable. Our project partners—Finger Lakes Land Trust, Genesee Land Trust, and Saratoga Preserving Land and Nature (PLAN)—can use study results to better profile farmland vulnerability, issuing conservation easements to protect maximum acreage in Saratoga County and the Finger Lakes Region of New York. Multiple existing studies effectively use remote sensing imagery to analyze historical land cover and forecast future change. This study examined soil carbon stocks and land cover change to estimate avoided soil carbon loss. We also predicted farmland vulnerability. We completed these analyses using European Space Agency (ESA) and NASA Earth observations that include Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-2 Multispectral Instrument (MSI), and Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) for nighttime lights data that aided in the land change model analysis. We determined that the conversion of agriculture to development from 1990 to 2022 occurred at rates of 0.91% (Finger Lakes) and 7% (Saratoga). Urban development is predicted to increase surrounding urban centers through 2030 and 2050. We also estimate that between 26.5 and 348,101 kilotons (Finger Lakes) and 3.7 and 58,006 kilotons (Saratoga) of soil carbon losses have been avoided through agricultural easements. Findings from this study will support our partners in determining agricultural conservation easement benefits and prioritizing the acquisition of future easement sites.

Agriculture↗
NASA NTRSDate not supplied

End-user Assessment of the NASA SPoRT GLM Stoplight Product

National Weather Service (NWS) offices monitor and forecast the threat for lightning within their County Warning Areas for various impact-based decision support services (IDSS). These forecasts are provided routinely for aviation operations, but irregularly for large-scale, outdoor events, which typically have varying safety requirements with regards to lightning. Lightning monitoring and forecasting can require synthesizing a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop several products to address these operational challenges during the lifecycle of lightning activity, and conduct evaluations in concentrated (Research-to-Operations/Operations-to-Research) efforts. The product evaluated for this study is the Geostationary Lightning Mapper (GLM) Stoplight product, which addresses lightning safety specifically with regards to lightning recency and cessation. The GLM Stoplight product displays the spatial extent of lightning and uses color-coded pixels to show the recency of lightning in 10-minute increments. This presentation highlights results from an assessment of the GLM Stoplight product by select NWS offices, as well as emergency managers, that took place over a 5-week period from May 1st to June 2nd. Feedback was collected on the GLM Stoplight product and on a new and interactive lightning viewer, which allowed participants to tailor visualization of the product based on their location and desired application. Results will help NASA SPoRT gain a better understanding of how forecasters and emergency managers use lightning data for safety applications. In addition, the assessment will inform research on any necessary modifications to this and future lightning products to assist end users.

Kelley Murphy↗
NASA NTRS2023

Pacific Northwest Health & Air Quality: Monitoring Trends in Air Quality During a Drought Case Study to Improve Public Health Response to Drought Threats

Recent studies have documented a correlation between air quality and drought in the United States, which has been linked with increased aerosols including airborne particulate matter (PM) during drought conditions. This study partnered with local health departments to evaluate trends in air quality in the Pacific Northwest during the evolution of drought conditions using aerosol optical depth (AOD) observations collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellites. These satellite data were analyzed in conjunction with ground-based PM2.5 and PM10 data sourced from the Environmental Protection Agency (EPA)’s network of ground-based monitors and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index. Based on recommendations by local health departments, this study examined air quality trends between 2015 and 2022 in 12 counties within Oregon and Washington that reflected diversity in population density, drought exposure, rural and urban status, and data availability from EPA monitors. Overall, results indicated variation in relationships among drought, satellite, and ground-based air quality data across the study area. This study did not control for the impact of wildfire events on air quality and also did not investigate shorter SPEI aggregation periods, both of which are avenues for future research. This project supplemented research into links between drought and human health and provided health departments with an objective foundation from which they can communicate public health risks to local communities.

Abby Sgan↗
NASA NTRSDate not supplied

Satellite-assisted Evaluation of Irrigation Application Efficiency for Lettuce in the Salinas Valley

The Salinas Valley region of California’s Central Coast is a majorU.S. vegetable producer. Lettuce is a leading commodity, grown on about 100,000 acres with annual value near $1.4B (2022 Monterey County Ag Report). Vegetables crops in the area aretypically well watered and fertilized in pursuit of commercial yield and quality standards. Information on irrigation application efficiency, meanwhile, can enhance waterresource sustainability and mitigate impacts of nitrate infiltrationon groundwater quality. The Crop Consumptive Use Fraction (CCUF), previously recommended by the California Department of Water Resources, is a metric that expresses evapotranspiration (ET) of applied water relative to total applied water. More recently under Assembly Bill 1668 addressing water conservation and drought planning, the metric can be used to help quantify application efficiency to support preparation of agricultural water management plans in the state. This study will report CCUF evaluations from several commercial lettuce plantings in the Salinas Valley during the 2022 dry season (late spring-early fall). The evaluations were derived from satellite-based observations of cropET from the OpenETcloud application, and applied water monitored by in-line flowmetersand supplemented by grower reports of irrigation system runtime. The study will also compare observed (satellite-based) ET with modeled ET from the CropManage irrigationand nutrient management decision-support system operated by Cooperative Extension. Additional study in cool-season vegetables is ongoing in 2023.

Satellite-assisted↗
NASA NTRSDate not supplied

Monitoring Trends in Air Quality During a Drought: Case Study to Improve Public Health Response to Drought Threats

Drought has been an area of distinct concern in the Pacific Northwest since the mid-2010s. Recent studies have documented a correlation between air quality and drought in the United States, which is often observed in increased aerosols including airborne particulate matter (PM). This study partnered with the Oregon Health Authority and Washington State Department of Health to evaluate trends in air quality in the Pacific Northwest during the evolution of drought conditions using aerosol optical depth (AOD) observations collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellites. These satellite data were analyzed in conjunction with ground-based PM2.5 and PM10 data sourced from the Environmental Protection Agency (EPA) Air Quality System’s network of ground-based monitors and the Standardized Precipitation Evapotranspiration Index drought index. Based on recommendations by local health departments, this study examined air quality trends between 2015 and 2022 in 12 counties within Oregon and Washington that reflected diversity in population density, drought exposure, rural and urban status, and data availability from EPA AQS monitors. The findings from this study provided supplemental information to the ongoing efforts by community health stakeholders to study the public health impacts of drought and support public health responses to future drought events.

Taylor West↗
NASA NTRS2024

Leveraging Scientific Community Knowledge for Air Quality Model Chemistry Parameterizations

Air pollution contributes to adverse health outcomes. Approximately 121 million people in the United States—one third of the population—live where National Ambient Air Quality Standards (NAAQS) are violated. In most cases, the criteria pollutants exceeding standards are ozone (O 3 ) and fine particles (PM 2.5 ). In addition, 188 substances known or suspected to cause cancer or other serious health effects are designated as hazardous air pollutants (HAPs). Essentially, all O 3 and significant portions of PM 2.5 and HAPs are produced in the atmosphere through chemical and physical processes. In the case of PM 2.5 , subcomponents formed primarily from precursor gases—sulfate, nitrate, ammonium, and secondary organic aerosol (SOA)—account for 60% of the U.S. county-level annual mean concentration. In addition, 47% of the cancer risk and 25% of the noncancer risk from HAPs have been attributed to atmospheric chemistry rather than direct emissions. In this article, we introduce the role of chemical mechanisms in air quality models, a new atmospheric science community effort, and needs for further mechanism development.

Havala O.T. Pye↗
NASA NTRSDate not supplied

End-User Assessment of the NASA SPoRT Lightning AI Product

The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop products to address operational challenges and enhance safety during the lifecycle of lightning activity, and conduct evaluations in concentrated R2O/O2R efforts. The product evaluated for this study is Lightning Artificial Intelligence (A.I.), which predicts the probability of lightning out to 15 minutes in advance and spatially maps it using filled color contours. Lightning A.I. uses reflectivity, differential reflectivity, and correlation coefficient data from a subset of radars within the NEXRAD network to generate lightning probabilities at approximately 2 km resolution. The domains, spanning 145 x 145 km are centered over NASA-affiliated centers across the CONUS and use radar data which are closest in proximity. Lightning A.I. was developed with intended use by emergency managers at NASA centers. However, National Weather Service (NWS) offices are also often tasked with monitoring and forecasting the threat for lightning within their County Warning Areas for various impact-based decision support services. These forecasts are typically provided for aviation operations and large-scale, outdoor events, which may have varying safety requirements for decision-making based on lightning proximity and recency. The NASA SPoRT center conducted an assessment of the operational uses of Lightning A.I by various collaborative NWS Offices from late July into early September. This assessment included feedback from participants on both the product itself as well as its accessibility within the new, interactive NASA SPoRT Lightning Viewer. This presentation will include background information about Lightning A.I. and highlight results from this assessment. The feedback from the assessment will be used to inform research on any necessary modifications to this and future lightning products to assist end users.

Kelley Murphy↗
NASA NTRS2024

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↗
NASA NTRS2024

Baltimore Energy & Infrastructure: Assessing Urban Heat Vulnerability in Baltimore Neighborhoods to Inform Transportation Resiliency Planning Efforts

Across the world, climate change is altering cities and their local climate systems. Following global trends of rising mean temperatures, Baltimore, Maryland is projected to experience more frequent extreme heat events. Exacerbated by Urban Heat Island (UHI) effects, residents of the city face high temperatures from limited tree canopy, highly paved and impervious surfaces, limited air flow, and high concentrations of localized emissions. Urban heat is dispersed asymmetrically, with historically marginalized populations experiencing disproportionately severe heat. Recognizing the impacts of extreme urban heat, the Maryland Transit Administration (MTA) collaborated with us, the Spring 2024 Goddard Energy and Infrastructure NASA DEVELOP team to assess urban impacts of MTA users and assets and explore opportunities to enhance resiliency planning. We evaluated the feasibility of NASA Earth observations (EOs) in visualizing heat vulnerability in Baltimore City and County. We mapped UHI and extreme heat using remote sensing observations, tailored a Heat Priority Score (HPS) to analyze heat data in tandem with socioeconomic data from American Community Survey (ACS), and utilized SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model to estimate MTA riders’ thermal comfort. NASA EOs served to quantify the distribution and severity of extreme heat at the block group level, which was found to correlate with a lack of vegetation and presence of densely built-up surroundings. The HPS revealed that extreme heat events most negatively impact communities that exhibit social vulnerability through indicators such as age, race, and income. These findings will inform neighborhood resiliency plans for the MTA that can be incorporated into their Adaptation Resiliency Toolbox (ART).

Baltimore,↗
NASA NTRS2024

Bridgeport Urban Development: Leveraging NASA Earth Observations and Sociodemographic Data to Assess Urban Heat Vulnerability and Inform Cool Corridors in Bridgeport, Connecticut

Urban environments face hotter temperatures than suburban and rural areas due to higher concentrations of impervious surfaces, heat-retaining buildings, and lack of green space. Bridgeport, Connecticut, which was formerly a national manufacturing hub, is now the densest and most populous city in the state. Bridgeport experiences hotter temperatures, exposing its residents to more extreme temperatures than the surrounding affluent suburbs. Extreme heat affects the health of those exposed to it and intensifies energy demands. Understanding temperature differences is the first step in effectively directing mitigation efforts. Our partner, Groundwork Bridgeport, along with the Yale Urban Design Workshop, are planning a “cool corridors” project, implementing cooling infrastructure to combat urban heat. We used Landsat 8 Thermal Infrared Sensor and Landsat 9 Thermal Infrared Sensor-2 data to conduct a Land Surface Temperature analysis in Google Earth Engine for the county of Fairfield. A Principal Component Analysis was performed to identify indicators of social vulnerability in Bridgeport. We used the SOlar and LongWave Environmental Irradiance Geometry model to identify felt heat on the block level to inform where the partner should locate their cooling interventions to ensure they are most effective and equitable. We focused on the East Side of Bridgeport, which we found was 10 degrees hotter than other areas of Bridgeport and the neighboring town of Fairfield. We integrated our findings using Earth observations and additional sociodemographic and climate data into final communication products for our partners which will facilitate their selection of candidate locations for their Cool Corridors project.

Silas Kirsch↗
NASA NTRS2024

Big Bend Ecological Forecasting: Integrating Earth Observations Into Invasive Species Management Decisions in Big Bend National Park in Texas

Located in Brewster County Texas, U.S., along the Texas-Mexico border, Big Bend National Park is 3,243 square kilometers of desert, mountains, and rivers. NASA’s MSFC Spring 2024 DEVELOP Team partnered with the National Park Service (NPS), to address the environmental concern of perineal invasive grasses in Big Bend National Park. Buffelgrass (Cenchrus ciliaris), introduced to the park in the 1940’s, poses an ongoing threat, and causes habitat destruction for many of the park’s native ecosystems. Buffelgrass amplifies fire risk in the park, aids in the destruction of historic structures, and alters stream channels. To address the rising concern of Buffelgrass presence, unique advanced spatial technique applications were necessary to construct a habitat suitability model and perform a comprehensive fire risk assessment. A habitat suitability model was developed considering climate, vegetation, and phenological variables, in addition to physical and topographical variables. Subsequently, a fire risk model was developed, taking into account fire history data, accessibility factors, climate trends and predictions, along with developed areas. Multi-Source Land Surface Phenology (LSP) Sentinel-2 and Landsat 8 Operational Land Imager (OLI) imagery were used to predict Buffelgrass hotspot locations throughout the park. These analyses allowed the identification of optimal Buffelgrass habitat and hotspot locations, as well as park zones that reflect the greatest risk for future Buffelgrass invasion and fire risk. The collective results of the habitat suitability model, fire risk assessment, and Buffelgrass hot spot identification will allow the NPS to facilitate efficient mitigation measures and management strategies, and improved resource allocation where it’s most needed.

remote sensing↗
NASA NTRS2024

Monitoring Well Installation Completion Report for Ransom Road Landfill, Vertical Processing Facility, and Environmental Health Facility, Solid Waste Management Units: 003, 077, and 079

The intended purpose of the Monitoring Well Installation project is to support the Kennedy Space Center (KSC) Environmental Remediation Department’s Resource Conservation and Recovery Act Program by installing new monitoring wells. The wells are installed in accordance with the Brevard County Health Department and St. Johns River Water Management Districts rules and guidelines.

Well Installation↗
NASA NTRS2024

Monitoring Well Abandonment Completion Report for KARS Park1, Mobil Service Station, and Hypergol Maintenance Material North Solid Waste Management Units: 084, 093, and 090

The intended purpose of the Monitoring Well Abandonment project is to support the Kennedy Space Center (KSC) Environmental Remediation Department’s Resource Conservation and Recovery Act Program by abandoning monitoring wells throughout KSC that have been identified and prioritized as locations that no longer serve usefulness to program. The monitoring wells were abandoned in accordance with the Brevard County Health Departments and St. Johns River Water Management Districts rules and guidelines.

Timothy M Jellett↗
NASA NTRS2024

Platte River Basin Water Resources II: Predicting Land Cover Change in the Platte River Basin to Select Wetland Protection Sites Vulnerable to Urban Encroachment

The Platte River Basin (PRB) represents a critical dynamic ecosystem where wetlands play a pivotal role as essential habitats for local and migratory birds, as well as various flora and fauna. It also provides many crucial ecosystem services that directly and indirectly benefit human welfare. However, it is threatened by anthropogenic activity, climate change, and urbanization. Our team partnered with Audubon Great Plains, the regional office of a national non-profit organization (NGO), to analyze the future potential development of the region and its potential impact on the wetlands. We utilized remotely sensed data, such as Landsat 8 Operational Land Imager (OLI) and Suomi National Polar Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), as well as NASA Socioeconomic Data and Application Center (SEDAC) data, to simulate urban growth potential up to 2050 using the open-source model FUTure Urban-Regional Environment Simulation (FUTURES) model. Our results for two proposed scenarios (all wetlands are protected, and no wetlands are protected) revealed that at least 56 counties out of 81 in the PRB would experience growth by the year 2050. The results for the first scenario show that there will be no loss of wetlands in the future. However, the results for the second scenario indicate a basin-wide reduction of 43.22 square kilometers (0.58%) in wetland areas, leading to a significant loss of bird habitat, critical for conservation. The results will help Audubon Great Plains' Urban Woods and Prairies Initiative to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies.

FUTURES↗
NASA NTRS2025

Hilo Bay Water Resources: Monitoring Water Quality in Hilo Bay, Hawaii to Support Future Community Planning

Designated as an impaired body of water by both state and federal water quality standards, Hilo Bay, Hawaiʻi is highly susceptible to brown water, a condition where the water becomes murky and is associated with excess levels of bacteria, contaminants, and nutrients. A breakwater in Hilo Bay, which was established to protect Hilo town from tsunamis, interferes with water circulation and prolongs the presence of brown water in the bay. The State of Hawaiʻi issues brown water advisories (BWAs) following flash flood warnings, sewage spills, and other events to indicate a public health concern for those who use Hilo Bay for recreation, cultural purposes, and fishing. Due to the elevated public health risk and ecosystem disturbance that brown water poses to Hilo Bay, we partnered with the Hawaiʻi County Office of Sustainability, Climate, Equity, and Resilience (OSCER) to examine the feasibility of using Earth observations (EO) to monitor water quality in the Hilo Bay region. We leveraged data from Sentinel-2 Multispectral Instrument (MSI), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, and Aqua and Terra Moderate Resolution Imagine Spectroradiometer (MODIS) instruments to identify and assess spatial and temporal patterns of two main water quality parameters, turbidity and chlorophyll-a, during BWAs. We used the Optical Reef and Coastal Area Assessment (ORCAA) tool in Google Earth Engine to process EO data and generate water quality maps and time series. Our study found that increased turbidity levels can be identified by EO data during BWAs. In addition, our map products indicated the presence of several turbidity plumes along the coast, with the highest concentration of turbidity found within Hilo Bay. While chlorophyll-a levels were relatively flat within our study region during BWAs, we found that regional chlorophyll-a patterns could be derived from MODIS chlorophyll-a data in NASA Worldview. Our study’s multi-sensor approach provided valuable insights for how water quality in the Hilo Bay region can be monitored in the future.

remote sensing↗