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At least 19 records

Washington Health & Air Quality: Quantifying Air Quality Parameters and Validating Air Pollution Sources Impacting the Health of Puget Sound Residents Through the Use of NASA and ESA Remote Sensing Data

In the Puget Sound region of Washington, high levels of air pollutants put residents’ health at risk by increasing their likelihood of developing critical respiratory conditions. This project used remotely-sensed data to investigate aerosol optical depth (AOD) from NASA satellite sensors including the Terra and Aqua MODerate Resolution Imaging Spectroradiometer (MODIS) and European Space Agency Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). The team visualized the most recent data in Google Earth Engine (GEE) API to display air pollution trends in Washington State, which will support the Puget Sound Clean Air Agency’s (PSCAA) decision-making processes. The team performed linear regressions using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to form a relationship between ground-level microscopic particles (PM2.5) and AOD in the Puget Sound region, validating the relationship using concentration readings taken from Environmental Protection Agency (EPA) air quality monitors. The team utilized estimated PM2.5 and other satellite data to produce a web-based tool and to evaluate the effectiveness of using such a tool for near real-time air quality monitoring within a particular region. The team found that the tool provides useful supplementary data that fills in the gaps of the PSCAA’s air monitoring network.

Health & Air Quality↗

Washington Health & Air Quality: Quantifying Air Quality Parameters and Validating Air Pollution Sources Impacting the Health of Puget Sound Residents Through the Use of NASA and ESA Remote Sensing Data

In the Puget Sound region of Washington, high levels of air pollutants put residents’ health at risk by increasing their likelihood of developing critical respiratory conditions. This project used remotely-sensed data to investigate aerosol optical depth (AOD) from NASA satellite sensors including the Terra and Aqua MODerate resolution Imaging Spectroradiometer (MODIS) and European Space Agency Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). The team visualized the most recent data in Google Earth Engine (GEE) API to display air pollution trends from Northern California to British Columbia, which will support the Puget Sound Clean Air Agency’s (PSCAA) decision-making processes. The team performed linear regressions using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to form a relationship between ground-level microscopic particles (PM2.5) and AOD in the Puget Sound region, validating the relationship using concentration readings taken from Environmental Protection Agency (EPA) air quality monitors. The team utilized estimated PM2.5 and other satellite data to produce a web-based tool and to evaluate the effectiveness of using such a tool for near real-time air quality monitoring within a particular region. The team found that the tool provides useful supplementary data that fills in the gaps of the PSCAA’s air monitoring network.

Health & Air Quality↗

Oklahoma Health and Air Quality: Mapping Air Quality Using NASA Earth Observations to Investigate Recent Increases in Ozone Concentrations

Tropospheric ozone (O3) is formed by anthropogenic pollutants interacting with sunlight and is considered harmful to human health in high concentrations. In the summer of 2018, the Oklahoma Department of Environmental Quality (DEQ) measured unexpected spikes in O3 in Seiling, Oklahoma, with concentrations exceeding those measured in bustling Oklahoma City and Tulsa. The DEQ tracks air quality using ground monitors and does not utilize Earth observation data in its monitoring or analysis. This project used remotely sensed data to investigate these2018 air quality anomalies, identifying possible causes. We analyzed atmospheric data from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and Sentinel-5P Tropospheric Ozone Monitoring Instrument (TROPOMI) in conjunction with ground-based measurements of tropospheric ozone (O3), nitrogen dioxide (NO2), methane (CH4), carbon monoxide (CO), formaldehyde (HCHO) and aerosol optical depth (AOD). We compared Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model simulations and Earth observation visualizations to pinpoint ozone spike causes. We also generated models to identify contributing factors to variations in ground ozone concentrations in our study area. The results point to a variety of ozone spike causes, primarily from outside of the state, and support the placement of additionalNO2, O3, and CO monitors to the southeast of Seiling. These analyses can help guide the placement of future monitors in the ground monitoring network and inform air quality regulations in Oklahoma.

Carolina Rosales↗

A Satellite-Based Multi-Pollutant Index of Global Air Quality

Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing.

Cooper, Mathew J.↗

Potential Impact of a US Climate Policy and Air Quality Regulations on Future Air Quality and Climate Change

We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that aims to reduce 2050 CO2 emissions to be 50% below 2005 emissions. Using the NASA GISS ModelE2 general circulation model, we look at the impacts for year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL (MARKet ALlocation) for the Purpose of Scenario Exploration), and other US emissions data sets and the rest of the world emissions data sets are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in year 2030 and 2055 but result in positive radiative forcing. Under this scenario, no more emission constraints are added after 2020, and the impacts on air quality and climate change are similar between year 2030 and 2055. Surface particulate matter with a diameter smaller than 2.5 micron PM(sub 2:5) is reduced by 2 approximately μg/m(sup -3) on average over the USA, and surface ozone by approximately 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the USA, mainly due to the PM(sub 2:5) reduction approximately (74 200 lives saved). The air quality regulations reduce the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading to a strong positive radiative forcing (RF) over the USA by both aerosols' direct and indirect forcing: the total RF is approximately 0.04 W m(sup -2) over the globe, and approximately 0.8 W m(sup -2) over the USA. Under the hypothetical climate policy, a future CO2 emissions cut is achieved in part by relying less on coal, and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it could lead to potential climate disbenefits over the USA. In 2055, the US mean total RF is +C02 W m(sup -2) due to positive aerosol direct and indirect forcing, while the global mean total RF is -0.06 W m(sup -2) due to the dominant negative CO2 RF (instantaneous RF). To achieve a regional-scale climate benefit via a climate policy, it is critical (1) to have multinational efforts to reduce greenhouse gas (GHG) emissions and (2) to simultaneously target emission reduction of light-absorbing species (e.g., BC and O3) on top of long-lived species. The latter is very desirable as the resulting climate benefit occurs faster and provides cobenefits to air quality and public health.

Air quality↗

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↗

Application of ESE Data and Tools to Air Quality Management: Services for Helping the Air Quality Community use ESE Data (SHAirED)

The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. Its scope falls within the domain of air quality management and aims to develop a federated air quality information sharing network that includes data from NASA, EPA, US States and others. Project goals were achieved through a access of satellite and ground observation data, web services information technology, interoperability standards, and air quality community collaboration. In contributing to a network of NASA ESE data in support of particulate air quality management, the project will develop access to distributed data, build Web infrastructure, and create tools for data processing and analysis. The key technologies used in the project include emerging web services for developing self describing and modular data access and processing tools, and service oriented architecture for chaining web services together to assemble customized air quality management applications. The technology and tools required for this project were developed within DataFed.net, a shared infrastructure that supports collaborative atmospheric data sharing and processing web services. Much of the collaboration was facilitated through community interactions through the Federation of Earth Science Information Partners (ESIP) Air Quality Workgroup. The main activities during the project that successfully advanced DataFed, enabled air quality applications and established community-oriented infrastructures were: develop access to distributed data (surface and satellite), build Web infrastructure to support data access, processing and analysis create tools for data processing and analysis foster air quality community collaboration and interoperability.

Falke, Stefan↗

Pacific Northwest Health & Air Quality - Utilizing NASA Earth Observations to Analyze Air Quality Impacts from Wildfires in the Pacific Northwest

The Pacific Northwest region of the United States and Canada has become more vulnerable to intense wildfire regimes due to years of fire suppression and climatic changes. Smoke from fires exposes communities to hazardous aerosols and pollutants known to trigger asthma symptoms and exacerbate other respiratory and cardiovascular diseases. In partnership with The Nature Conservancy’s Washington Chapter and the Puget Sound Clean Air Agency, NASA DEVELOP investigated the impacts of wildfire smoke on air quality from 2008 to 2020 using NASA Earth observations. To explore the various dimensions of smoke and its relation to air quality, the team looked at the vertical extent of smoke plumes and the resulting changes in air quality. The team evaluated the potential relationship between plume height of wildfire smoke and fire radiative power using the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites and Terra’s Multi-angle Imaging SpectroRadiometer (MISR) using the MISR INteractive eXplorer (MINX). The team determined that there was no regional relationship between fire radiative power and smoke plume height. To investigate changes in air quality resulting from wildfire smoke, the team utilized data from NASA’s Fire Information for Resource Management System, from the European Space Agency’s Sentinel-5P Tropospheric Monitoring Instrument (TROPOMI), and true color imagery from Landsat 8 Operational Land Imager (OLI). The team created a Google Earth Engine-based (GEE) web tool to visualize changes in atmospheric pollutants and aerosol optical depth. Results of case study fires showed varying increases in pollutant concentrations when compared to a baseline map. The end products provided the partners with tools to quantify plume height using MINX and to visualize recent air quality patterns relating to variations in wildfire extent and severity in the Pacific Northwest

Ani Matevosian↗

Process air quality data

Air quality sampling was conducted. Data for air quality parameters, recorded on written forms, punched cards or magnetic tape, are available for 1972 through 1975. Computer software was developed to (1) calculate several daily statistical measures of location, (2) plot time histories of data or the calculated daily statistics, (3) calculate simple correlation coefficients, and (4) plot scatter diagrams. Computer software was developed for processing air quality data to include time series analysis and goodness of fit tests. Computer software was developed to (1) calculate a larger number of daily statistical measures of location, and a number of daily monthly and yearly measures of location, dispersion, skewness and kurtosis, (2) decompose the extended time series model and (3) perform some goodness of fit tests. The computer program is described, documented and illustrated by examples. Recommendations are made for continuation of the development of research on processing air quality data.

Butler, C. M.↗

Communicating Respiratory Health Risk Among Children using a Global Air Quality Index

Air pollution poses a serious threat to children’s respiratory health around the world. Satellite remote-sensing technology and air quality models can provide pollution data on a global scale, necessary for riskcommunication efforts in regions without ground-based monitoring networks. Several large centers, including NASA, produce global pollution forecasts that may be used alongside air quality indices to communicate local, daily risk information to the public. Here we present a health-based, globally applicable air quality index developed specifically to reflect the respiratory health risks among children exposed to elevated outdoor air pollution. Additive, excess-risk air quality indices were developed using 51 different coefficients derived from time-series health studies evaluating the impacts of ambient fine particulate matter, nitrogen dioxide, and ozone on children's respiratory morbidity outcomes. A total of four indices were created which varied based on whether or not the underlying studies controlled for co-pollutants and in the adjustment of excess risks of individual pollutants. Combined with historical estimates of air pollution provided globally at a 25x25 km2 spatial resolution from the NASA's Goddard Earth Observing System composition forecast (GEOS-CF) model, each of these indices were examined in a global sample of 664 small and 140 large cities for study year 2017. Adjusted indices presented the most normal distributions of locally-scaled index values, which has been shown to improve associations with health risks, while indices based on coefficients controlling for co-pollutants had little effect on index performance. We provide the steps and resources need to apply our final adjusted index at the local level using freely-available forecasting data from the GEOS-CF model, which can provide risk communication information for cities around the world to better inform individual behavior modification to best protect children's respiratory health.

Air Qualilty↗

Environmental Justice Needs-Assessment For Health & Air Quality: Assessing the Needs and Capacity of Organizations Working Towards Health and Environmental Justice Related to Health and Air Quality

Health and air quality are concerns in environmental justice (EJ) work, as air contaminants and their adverse health effects inequitably impact communities that are often underrepresented in research and litigation. Previously, the NASA DEVELOP National Program partnered with organizations that focus on a variety of health and air quality concerns and is now committed to partnering directly with EJ organizations to address inequities in health and air quality through the application of Earth observations. To support the establishment of future partnerships, DEVELOP is working to identify potential partners for further EJ research in the U.S. regarding health and air quality. This project conducted a needs assessment with EJ organizations to quantify their EJ involvement, geospatial capacity, and interest in collaborating with DEVELOP. A broad literature review identified multiple factors influencing health and air quality for potential DEVELOP projects: agriculture, heat, wildfires, industry and transportation infrastructure, and miscellaneous factors (e.g., burning, urban heat island effect, smoke plumes, truck exhaust, and noise). The needs assessment showed that 22% of the organizations interviewed were primarily concerned with transportation infrastructure, 21% with industry, 19% with heat, 10% with miscellaneous factors (e.g., resource mining, COVID-19), 8% with wildfires, 7% with agriculture, and 6% with resource mining. This will help inform the DEVELOP Program's pursuit of EJ projects relating to health and air quality. The team also created a directory for communities impacted by air pollutants to connect with geospatial resources and NASA Applied Sciences personnel for future EJ health and air quality work.

Elizabeth Duran↗

San Joaquin Valley Health & Air Quality: Evaluating the Overlap of Social Vulnerabilities and Air Quality in the San Joaquin Valley Air Pollution Control District

Little Manila Rising (LMR) is a nonprofit in Stockton, California that has been increasingly concerned by the air pollution in their city and the neighboring San Joaquin Valley (SJV). Geographical factors, climate conditions, and anthropogenic activities, such as agriculture burning and vehicle emissions, contribute to the high levels of air pollution in this region. To visualize the distribution of air pollution and social disparities across the SJV, LMR partnered with NASA DEVELOP. The DEVELOP team used Terra and Aqua MODIS, Sentinel-5P TROPOMI, and CALIPSO CALIOP to observe Aerosol Optical Depth (AOD), Nitrogen Dioxide (NO 2 ), and the vertical distribution of pollutants at varying pollution levels, respectively. Additionally, Suomi-NPP VIIRS provided active fire data. By leveraging NASA Earth observations along with sociodemographic and public health data, the DEVELOP team created maps identifying the areas experiencing the highest vulnerabilities and disparities in pollution exposure. The team found that AOD was slightly higher in agricultural regions, while NO 2 was consistently higher along transportation corridors and urban areas. Wildfires dominated the type of detected active fires, and there was high correlation (R 2 = 0.6924) between active fires and burn permits in agricultural tracts. Furthermore, the team identified both high AOD vulnerability and high NO 2 vulnerability in census tracts in South Stockton, an area that has been historically redlined and disinvested in, and where LMR resides. There was also a moderate correlation between air quality reported from the satellites and in-situ ground monitors. These results will support LMR’s organizing strategies for stricter enforcement of air pollution regulations and increased public health equity for community members.

Agricultural Fires↗

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Quattrochi, Dale A.↗