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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Climate Change Potential Impacts on the Built Environment and Possible Adaptation Strategies

The built environment consists of components that exist at a range of scales from small (e.g., houses, shopping malls) to large (e.g., transportation networks) to highly modified landscapes such as cities. Thus, the impacts of climate change on the built environment may have a multitude of effects on humans and the land. The impact of climate change may be exacerbated by the interaction of different events that singly may be minor, but together may have a synergistic set of impacts that are significant. Also, mechanisms may exist wherein the built environment, particularly in the form of cities, may affect weather and the climate on local and regional scales. Hence, a city may be able to cope with prolonged heat waves, but if this is combined with severe drought, the overall result could be significant or even catastrophic, as accelerating demand for energy to cooling taxes water supplies needed both for energy supply and municipal water needs. This presentation surveys potential climate change impacts on the built environment from the perspective of the National Climate Assessment, and explores adaptation measures that can be employed to mitigate these impacts.

Quattrochi, Dale A.↗
NASA NTRS2017

Updates and Overview of Spaceflight Medical Support in Russia and Kazakhstan

This panel presents recent updates to and a comprehensive overview of the operational medical support provided to ISS crewmembers in Star City, Russia and Kazakhstan as part of UTMB/KBRwyle's Human Health & Performance contract. With the current Soyuz training flow, physician support is required for nominal training evolutions involving pressure changes or other potential physical risks detailed in this presentation. In addition, full-time physician presence in Star City helps to address the disparity in access to health care in these relatively remote practice areas, while also developing and maintaining relationships with host nation resources. A unique part of standard training in Russia also involves survival training in both winter and water environments; logistic details and medical impacts of each of these training scenarios will be discussed. Following support of a successful training flow, UTMB/KBRwyle's Star City Medical Support Group (SCMSG) is also responsible for configuring medical packs in support of Soyuz launches and landings; we will present the rationale for current pack contents within the context of specific operational needs. With respect to contingency events, the group will describe their preparedness to respond appropriately by activating both local and global resources as necessary, detailing a specialized subset of the group who continually work and update these assets, given changes in international infrastructure and other impacts.

Chough, Natacha↗
NASA NTRS2016

Modeling the Urban Impact on Semiarid Surface Climate: A Case Study in Marrakech, Morocco

We combine Landsat and MODIS data in the Simple Biosphere Model to assess the impact of urbanization on surface climate in a semiarid city in North Africa. The model simulates highest temperatures in urban class, with spring average maximum temperature differences to other land cover classes ranging between 1.6 C and 6.0 C. During summer, these maximum temperature differences are smallest (0.5 C) with barelands and highest (8.3 C) with irrigated lawns. This excess heating is simulated above and beyond a seasonal temperature average of about 30 C during spring and 44 C during summer. On annual mean, a full urbanization scenario decreases the carbon fixation by 0.13 MtC and increases the daytime mean surface temperature by 1.3 C. This may boost the city energy consumption by 5.72%. Under a 'smart growth' scenario, whereby the city expands on barelands to cover 50% of the study region and all remaining barelands converted to orchards, the carbon fixation is enhanced by 0.04 MtC with a small daytime temperature increase of 0.2 C. Our results indicate that vegetation can mitigate the urban heating. The hydrological cycle indicates that highest ratio of surface runoff to precipitation (43.8%) occurs in urban areas, versus only 16.7 % for all cover types combined.

Lachir, Asia↗
NASA NTRS2017

Regional Impacts of Urbanization in the United States

We simulate the impact of impervious surface areas (ISA) on the U.S. local and regional climate. At a local scale, we find the urban area warmer than the surrounding vegetation in most cities, except in arid climate cities where urban temperature is cooler for much of the daytime. For all 9 regions studied, simulated results show that the growing season maximum surface temperature difference between urban and the dominant vegetation occurs around mid-day and is strongest in the northern regions. Regional temperature differences of 3.0 C, 3.4 C, and 3.9 C were simulated in the Northeast, Midwest, and Northwest, respectively. In these regions evaporative cooling, during the growing season, creates a stronger urban heat island (UHI). The UHI is less pronounced during winter when vegetation is dormant. Our results suggest that the ISA temperature is set by building material's characteristics and its departure from that of the surrounding vegetation is essentially driven by evaporative cooling. Except when rainfall is small, the highest surface runoff to precipitation ratios are simulated in most cities, especially when precipitation events occur as heavy downpours. In terms of photosynthesis, we provide a detailed distribution of maximum production in the U.S., a needed product for policy and urban planners.

Bounoua, Lahouari↗
NASA NTRS2018

A Method for Mapping Future Urbanization in the United States

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Bounoua, Lahouari↗
NASA NTRS2018

Satellite-Based View of the Aerosol Spatial and Temporal Variability in the Cordoba Region (Argentina) Using over Ten Years of High-Resolution Data

Space-based observations offer a unique opportunity to investigate the atmosphere and its changes over decadal time scales, particularly in regions lacking in situ and/or ground based observations. In this study, we investigate temporal and spatial variability of atmospheric particulate matter (aerosol) over the urban area of Córdoba (central Argentina) using over ten years (2003–2015) of high-resolution (1 km) satellite-based retrievals of aerosol optical depth (AOD). This fine resolution is achieved exploiting the capabilities of a recently developed inversion algorithm (Multiangle implementation of atmospheric correction, MAIAC) applied to the MODIS sensor datasets of the NASA-Terra and -Aqua platforms. Results of this investigation show a clear seasonality of AOD over the investigated area. This is found to be shaped by an intricate superposition of aerosol sources, acting over different spatial scales and affecting the region with different yearly cycles. During late winter and spring (August-October), local as well as near- and long-range transported biomass burning (BB) aerosols enhance the Córdoba aerosol load, and AOD levels reach their maximum values (>0.35 at 0.47 µm). The fine AOD spatial resolution allowed to disclose that, in this period, AOD maxima are found in the rural/agricultural area around the city, reaching up to the city boundaries pinpointing that fires of local and near-range origin play a major role in the AOD enhancement. A reverse spatial AOD gradient is found from December to March, the urban area showing AODs 40–80% higher than in the city surroundings. In fact, during summer, the columnar aerosol load over the Córdoba region is dominated by local (urban and industrial) sources, likely coupled to secondary processes driven by enhanced radiation and mixing effects within a deeper planetary boundary layer (PBL). With the support of modelled AOD data from the Modern-Era Retrospective Analysis for Research and Application (MERRA), we further investigated into the chemical nature of AOD. The results suggest that mineral dust is also an important aerosol component in Córdoba, with maximum impact from November to February. The use of a long-term dataset finally allowed a preliminary assessment of AOD trends over the Córdoba region. For those months in which local sources and secondary processes were found to dominate the AOD (December to March), we found a positive AOD trend in the Córdoba outskirts, mainly in the areas with maximum urbanization/population growth over the investigated decade. Conversely, a negative AOD trend (up to −0.1 per decade) is observed all over the rural area of Córdoba during the BB season, this being attributed to a decrease of fires both at the local and the continental scale.

aerosols↗
NASA NTRS2019

Quantification of CO2 and CH4 emissions over Sacramento, California, based on divergence theorem using aircraft measurements

Emission estimates of carbon dioxide (CO2) and methane (CH4) and the meteorological factors affecting them are investigated over Sacramento, California, using an aircraft equipped with a cavity ring-down greenhouse gas sensor as part of the Alpha Jet Atmospheric eXperiment (AJAX) project. To better constrain the emission fluxes, we designed flights in a cylindrical pattern and computed the emission fluxes from two flights using a kriging method and Gauss’s divergence theorem. Differences in wind treatment and assumptions about background concentrations affect the emission estimates by a factor of 1.5 to 7. The uncertainty is also impacted by meteorological conditions and distance from the emission sources. The vertical layer averaging affects the flux estimate, but the choice of raw wind or mass-balanced wind is more important than the thickness of the vertical averaging for massbalanced wind for both urban and local scales. The importance of vertical mass transfer for flux estimates is examined, and the difference in the total emission estimate with and without vertical mass transfer is found to be small, especially at the local scale. The total flux estimates accounting for the entire circumference are larger than those based solely on measurements made in the downwind region. This indicates that a closed-shape flight profile can better contain total emissions relative to a one-sided curtain flight because most cities have more than one point source and wind direction can change with time and altitude. To reduce the uncertainty of the emission estimate, it is important that the sampling strategy account not only for known source locations but also possible unidentified sources around the city. Our results highlight that aircraft-based measurements using a closed-shape flight pattern are an efficient and useful strategy for identifying emission sources and estimating local- and city-scale greenhouse gas emission fluxes.

Ju-Mee Ryoo↗
NASA NTRS2020

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors Mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗
NASA NTRS2020

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗
NASA NTRSDate not supplied

Quantifying Changes in Urban Albedo with NASA Earth Observations to Reduce the Urban Heat Island Effect in Cambridge, Massachusetts

Elevated temperatures resulting from the urban heat island (UHI) effect can have widespread impacts on human health, infrastructure, and ecosystems. These impacts can be exacerbated by changes in climate and extreme variation in regional temperature. By 2030, experts expect Cambridge, Massachusetts will experience warmer than average temperatures, more heat waves, and triple the number of abnormally warm days above 90°F per year. The NASA DEVELOP Program partnered with the City of Cambridge’s Community Development Department and the American Geophysical Union’s Thriving Earth Exchange to inform ongoing efforts aimed at reducing the impacts of urban heat in the city of Cambridge. The team used scenes obtained from High Resolution Orthoimagery and the National Agriculture Imagery Program in conjunction with building footprint data, to calculate rooftop albedo between 2008 and 2018. Using these results, maps displaying building-specific variation in albedo across Cambridge were created. A nighttime land surface temperature (LST) record for June, July, and August between 2003 and 2019 was constructed using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) nighttime LST product. Lastly, temperature anomalies were calculated for Cambridge using seasonally averaged nighttime LST values obtained from Aqua MODIS to display ‘hot spots’ for summers between 2004 and 2019. The results of this project were then incorporated into an interactive ArcGIS Dashboard. This work will allow end users to explore spatial and temporal trends in albedo, nighttime LST, and temperature anomalies to assess whether the City of Cambridge is successfully reducing the effects of UHIs.

NASA DEVELOP↗
NASA NTRS2020

Tempe Urban Development II: Establishing an Urban Heat Exposure Severity Score for Infrastructure Prioritization in Tempe, Arizona, Using NASA Earth Observations and LiDAR

Located in the northern Sonoran Desert, Tempe, Arizona, features a semi-arid climate with summer daily maximum temperatures regularly exceeding 37.8° C (100.0° F). The area has experienced an increase in surface and air temperatures due to a steep expansion of impervious surfaces and rapid urban development. Urban heat is an increasingly pressing concern for Tempe with hundreds of heat-related deaths and thousands of heat-related hospitalizations over the past 15 years in Maricopa County. Furthermore, urban heat impacts residents’ quality of life and the economic vitality of the city. Recognizing the impacts of extreme urban heat, the City of Tempe collaborated with the Healthy Urban Environments initiative and the Fall 2020 Tempe Urban Development II NASA DEVELOP team to utilize NASA Earth observations to investigate the drivers of highest heat throughout the city. Data from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 8 Operational Land Imager (OLI), and Landsat 8 Thermal Infrared Sensor (TIRS), American Community Survey, and LiDAR data were used to identify areas experiencing the worst heat effects that could be targeted for heat mitigation and adaptation. These areas included the Escalante neighborhood, Alegre Community, University Heights, and around Dwight Park. Additionally, according to our shading analysis, the Gilliland and Escalante neighborhood walksheds do not meet the "good" shading threshold set at 30% by the Maricopa Association of Government.

DEVELOP Project Summary↗
NASA NTRS2020

Tempe Urban Development II: Establishing an Urban Heat Exposure Severity Score for Infrastructure Prioritization in Tempe, Arizona, Using NASA Earth Observations and LiDAR

Located in the northern Sonoran Desert, Tempe, Arizona, features a semi-arid climate with summer daily maximum temperatures regularly exceeding 37.8° C (100.0° F). The area has experienced an increase in surface and air temperatures due to a steep expansion of impervious surfaces and rapid urban development. Urban heat is an increasingly pressing concern for Tempe with hundreds of heat-related deaths and thousands of heat-related hospitalizations over the past 15 years in Maricopa County. Furthermore, urban heat impacts residents’ quality of life and the economic vitality of the city. Recognizing the impacts of extreme urban heat, the City of Tempe collaborated with the Healthy Urban Environments initiative and the Fall 2020 Tempe Urban Development II NASA DEVELOP team to utilize NASA Earth observations to investigate the drivers of heat exposure throughout the city. Data from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 8 Operational Land Imager (OLI), and Landsat 8 Thermal Infrared Sensor (TIRS), American Community Survey, and LiDAR data were used to identify areas experiencing the worst heat effects that could be targeted for heat mitigation and adaptation. These areas included the Escalante neighborhood, Alegre Community, University Heights, and around Dwight Park. Additionally, according to our shading analysis, the Gilliland and Escalante neighborhood walksheds do not meet the "good" shading threshold set at 30% by the Maricopa Association of Government.

DEVELOP Tech Paper↗
NASA NTRSDate not supplied

The Application of Remote Sensing using NASA Earth Observations paired with Sociodemographic Indicators to Identify Communities Most Susceptible to Urban Heat Exposure in Austin, Texas

In recent years, Austin, Texas has experienced an increase in population and urban development. Additionally, the City’s climate—already characterized by periods of extreme heat and drought—continues to change. As temperatures and demand for utilities and cooling resources rise, the number of heat-related deaths and illnesses in socially vulnerable populations (e.g., older, lower-income populations) is expected to increase. The City of Austin, The University of Texas at Austin (UT Austin), and The University of Texas Health Science Center at Houston (UT Health) partnered with NASA DEVELOP to examine the distribution of urban heat throughout the City. This project used land surface temperature, greenness, plant water content, and urban surface material analysis parameters derived from NASA Earth observations from Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The project team produced three different indices to create a spatial analysis for the study area including a social vulnerability index (SoVI), heat exposure index (HEI), and an overall heat priority index (HPI) score. This overall score was determined with a weighted analysis of heat-related environmental variables from NASA Earth observations and socioeconomic data from the 2019 American Community Survey. Based on the HPI score, the project team identified 121 census block groups out of 605 total that are designated as being most at risk of adverse impacts from extreme heat events. To test the sensitivity of the HPI, the team used a Monte Carlo analysis using different approaches for geographic scale, variable inclusion, census uncertainty, and index aggregation. Based on the sensitivity analysis, the resulting HPI score showed the metric was consistent with the baseline HPI. This provided increased confidence the score can be used as a tool to make informed infrastructure improvement plans in targeted areas (e.g., siting of cooling centers) and ensure equitable sustainable development.

Ryan Hammock↗
NASA NTRS2021

The simulation of the impact of the spatial distribution of vegetation on the urban microclimate: A case study in Mostaganem

Increasing vegetation is one of the solutions proposed to mitigate the phenomenon of urban heat islands. The present research aims to study the effect of the spatial distribution of vegetation on the urban microclimate during the summer period. The city of Mostaganem with its Mediterranean climate was chosen as a case study. Based on meteorological data collected on a hot day in July, the study is carried out using the ENVI-met 4.4.5. Scenarios of different vegetation layouts were carried out. Air, mean radiant and surface temperatures are the microclimatic parameters that have been analyzed for each of the scenarios, and in order to study the outdoor thermal comfort, the Predicted Mean Vote (PMV) is chosen as the comfort index, it compares the average value of the votes of a large group of people on the thermal sensation scale. The study revealed that tree alignments can have a cooling effect on the city temperature close to 1.2◦C. However, its impact on reducing the surface temperature can reach up to 4 ◦C. The introduction of vegetation on the site had the overall effect of lowering the air temperature and therefore relatively improving the level of comfort compared to the reference scenario. But, in order to reduce discomfort to an acceptable level during the day, vegetation can be simultaneously accommodated by city parameters such as urban form.

Nora Bachir↗
NASA NTRSDate not supplied

Decoupling the Effects of Anthropogenic Emission Reductions from the Meteorology and Natural Emissions in TROPOMI NO 2 Retrievals During the 2020 COVID-19 Lockdowns

Satellite measurements during the COVID-19 lockdowns that began in 2020 revealed unprecedented reductions in NO 2 tropospheric vertical column densities (VCD). These reductions have largely been attributed to reduced anthropogenic emissions associated with abrupt decreases in road traffic and other power consuming business activities. Although decreased emissions tended to be the main contributor to the observed NO 2 VCD reduction, meteorological variability also played a role. Whereas the observed VCD changes were predominantly negative in places where public health policies were strictly enforced, meteorology had both positive and negative effects over short time intervals. Here, we present results from a global study of the NO 2 reductions aimed at disentangling the meteorological and natural emission variability from the anthropogenic emissions over the world’s most populated megacities. For this study, NASA’s TROPOMI NO 2 algorithm was used in conjunction with the Global Modeling Initiative (GMI) chemical transport model to separate the contributions due emissions and meteorology. A priori NO 2 profiles were generated from two GMI simulations performed for 2020 at a resolution of 0.25° longitude x 0.25° latitude. The first simulation used updated, COVID-impacted NOX emissions based on Forster et al. (2020), while the second simulation used the 2019 emissions with the 2020 meteorology, referred to here as 2020BAU. The 2020BAU data set allowed for the decoupling of the emission component from the meteorology. When compared to the same period in 2019, NO 2 column amounts during the lockdowns were reduced in 35 out of 36 cities. While reduced emissions contributed most to the observed total change in NO 2 during the lockdowns, the effects of meteorology were significant, ranging between 40% (Chennai) and 15% (Beijing). In China, an increase in NO 2 levels due to meteorology were observed in five out of the seven cities considered in the study. Use of different a-priori NO 2 profiles from the two simulations in our TROPOMI retrievals allowed for a determination of retrieval errors that ranged from -1.7% to -11.0%. We used the quality assurance flag > 0.75 to select the highest quality scenes in the study period. Using the GMI, we estimated the sampling biases to be in the range -11% to 10% of the total change for the cities in our study.

Brad Fisher↗
NASA NTRS2022

Global Fine Scale Changes in Ambient NO2 During COVID-19 Lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health(1–9) . A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19(10–20). Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Ground level NO2↗
NASA NTRSDate not supplied

Accelerating TEMPO Air Quality Science Through STAQS

Soon after the launch of Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission, NASA is supporting the Synergistic TEMPO Air Quality Science field study (STAQS) in summer 2023. This study’s main objective is to accelerate science with geostationary air quality observations from TEMPO to better understand its use in air pollution research and applications. Science objectives include, but are not limited to, TEMPO L2 product evaluation, the interpretation of the spatiotemporal evolution of TEMPO data during air quality events, assessment of anthropogenic emissions, contributions to chemical transport modeling, and environmental justice applications. These objectives can be accomplished through the integration of satellite data with systematically repeated high-resolution aircraft- and ground-based measurements in multiple urban environments. The primary urban cities considered include Los Angeles, New York City, and Chicago in June-August 2023. Measurements consist of airborne remote sensing observations of air quality constituents of nitrogen dioxide (NO2), formaldehyde (HCHO), ozone, and aerosols using the GeoCape Airborne Simulator and High-Spectral Resolution Lidar 2/Differential Absorption Lidar (HSRL2/DIAL) on the NASA JSC G-V aircraft, greenhouse gas observations from Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) and High Altitude Lidar Observatory (HALO) on the NASA LaRC G-III aircraft, and ground-based remote sensing and in situ observations of ozone, NO2, and HCHO from the Tropospheric Ozone Lidar Network (TOLNet), Pandora spectrometers, and ground-based monitoring networks. Key partnership studies providing in situ airborne observations include the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) field study on the NASA DC-8 in the same primary target areas as STAQS and Greater New York Oxidant, Tropospheric Halogens, and Aerosol Measurements and Modeling (GOTHAMM) field study on the NSF C-130 near New York City. This presentation will include a current status update of the STAQS mission and an overview of its measurement strategies and science objectives with the goal of promoting continued discussions for building and strengthening collaborations prior to the mission.

Laura Judd↗
NASA NTRSDate not supplied

Employing NASA Earth Observations and Socioeconomic Data to Conduct Site Suitability Analyses on Residential Tree Planting Initiatives in Phoenix, Arizona

Phoenix, Arizona is the hottest large city in the United States with an average summer daytime temperature of 106°F. Temperatures in Phoenix continue to climb due to increasing global greenhouse gas concentrations and regional urbanization. The impacts of high temperatures, including heat-related illnesses and deaths, are disproportionately concentrated in low-income neighborhoods often characterized by little tree canopy, lack of green space, and insufficient access to shade. The City of Phoenix’s Office of Heat Response and Mitigation and Arizona State University’s Urban Climate Research Center, partnered with NASA DEVELOP to identify residential neighborhoods and parcels within qualified census tracts (QCTs) to be prioritized for tree planting initiatives using funding from the American Rescue Plan Act (ARPA). This project conducted analyses using NASA Earth observations, socioeconomic data from the 2019 American Community Survey, and local tree canopy and mobility data. For Earth observations, daytime land surface temperature, vegetation, and land cover were obtained from the Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI). The project team incorporated these data into a heat vulnerability index (HVI) with an emphasis on tree canopy and social vulnerability to rank block groups within QCTs and focused on the resulting top 25 block group HVI scores. These top 25 most vulnerable block groups were then processed through a parcel analysis to determine the feasibility of residential tree planting based on building footprints on each parcel. Within the top 25 block groups, 2,411 parcels were analyzed, and 3,133 existing trees were identified averaging 1.3 trees per parcel with 90% of parcels having 3 trees or less. Homes with 2 trees or fewer were considered high priority for future planting efforts. Based on the City’s goals for increased tree canopy the project team determined that <10,000 additional trees would need to be planted within the most vulnerable 25 block groups. The project findings have helped initiate community engagement efforts and have contributed to the approval of tree planting funds in Phoenix.

Ryan Hammock↗