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NASA Health and Air Quality Applications

There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

Air Quality Remote Sensing↗

The Benefit of NASA's Atmosphere Observing System (AOS) Mission Lidar and Polarimeter Observations for Health and Air Quality Applications

The Atmosphere Observing System (AOS) seeks to explore fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. AOS will provide key information to enhance the communities’ ability to improve weather and air quality forecasting today, seasonal to sub-seasonal changes in the near future, and societal challenges resulting from climate change in the decades to come. A fundamental component of the AOS mission is ensuring that health and air quality applications are considered to the greatest extent possible in mission design. As a result, the Applications Impact Team (AIT) was implemented to address this objective. The overarching goal of the AIT is to help improve the capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data becomes available. To support these efforts, we leverage existing and near future mission applications activities and initiatives, such as the NASA CALIPSO, MAIA, TEMPO, and PACE missions to form a framework to enhance health and air quality applications for AOS. The unique synergy between lidar and polarimeter instruments onboard the AOS constellation, as well as diurnally varying observations of aerosol profiles, will provide new opportunities to engage health and air quality stakeholders for forecasting, monitoring, and warning of hazardous events (e.g., wildfire smoke, volcanic ash) that impact human health. Engaging with existing missions helps identify and understand data needs, gaps and opportunities for current and future stakeholders, determine what aerosol data products are of highest value and use, and helps connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS aerosol observations relevant for health and air quality applications, AIT activities and initiatives and how existing aerosol satellite missions and their applications activities can play a critical role in AOS applications development during mission design.

Melanie Follette-Cook↗

Solutions Network Formulation Report. NASA's Potential Contributions for Using Solar Ultraviolet Radiation in Conjunction with Photocatalysis for Urban Air Pollution Mitigation and Increasing Air Quality

This Candidate Solution is based on using NASA Earth science research on atmospheric ozone and aerosols data as a means to predict and evaluate the effectiveness of photocatalytically created surfaces (building materials like glass, tile and cement) for air pollution mitigation purposes. When these surfaces are exposed to near UV light, organic molecules, like air pollutants and smog precursors, will degrade into environmentally friendly compounds. U.S. EPA (Environmental Protection Agency) is responsible for forecasting daily air quality by using the Air Quality Index (AQI) that is provided by AIRNow. EPA is partnered with AIRNow and is responsible for calculating the AQI for five major air pollutants that are regulated by the Clean Air Act. In this Solution, UV irradiance data acquired from the satellite mission Aura and the OMI Surface UV algorithm will be used to help understand both the efficacy and efficiency of the photocatalytic decomposition process these surfaces facilitate, and their ability to reduce air pollutants. Prediction models that estimate photocatalytic function do not exist. NASA UV irradiance data will enable this capability, so that air quality agencies that are run by state and local officials can develop and implement programs that utilize photocatalysis for urban air pollution control and, enable them to make effective decisions about air pollution protection programs.

Underwood, Lauren↗

The Utility of the OMI HCHO/NO2 in Air Quality Decision-Making Activities

I will discuss a novel and practical application of the OMI HCHU and NO2 data products to the "weight of evidence" in the air quality decision-making process (e.g., State Implementation Plan (SIP)) for a city, region, or state to demonstrate that it is making progress toward attainment of the National Ambient Air Quality Standard (NAAQS) for ozone. Any trend, or lack thereof, in the observed OMI HCHO/NO2 may support that an emission control strategy implemented to reduce ozone is or is not occurring for a metropolitan area. In addition, the observed OMI HCHO/NO2 may be used to define new emission control strategies as the photochemical environments of urban areas evolve over time. I will demonstrate the utility of the OMI HCHO/NO2 over the U.S. for air quality applications with support from simulations with both a regional model and a photochemical box model. These results support mission planning of an OMI-like instrument for the proposed GEO-CAPE satellite that has as one of its objectives to study air quality from space. However, I'm attending the meeting as the Aura Deputy Project Scientist, so I don't technically need to present anything to justify the travel.

Duncan, Bryan↗

Stratospheric Intrusion-Influenced Ozone Air Quality Exceedences Investigated in MERRA-2

Ozone near the surface is harmful to human health and is a result of the photochemical reaction with both man-made and natural precursor pollutant sources. Therefore, in order to reduce near surface ozone concentrations, communities must reduce anthropogenic pollution sources. However, the injection of stratospheric ozone into the troposphere, known as a stratospheric intrusion, can also lead to concentrations of ground-level ozone exceeding air quality standards. Stratospheric intrusions are dynamical atmospheric features, however, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of approximately 50 km or smaller. NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (~50 km) with assimilated ozone that characterizes stratospheric ozone on the same spatiotemporal resolution as the meteorology. We show that stratospheric intrusions that impact surface air quality are well represented in the MERRA-2 reanalysis. This is demonstrated through a case study analysis of stratospheric intrusion events which were identified by the United States Environmental Protection Agency (EPA) to impact surface ozone air quality in spring 2012 in Colorado. The stratospheric intrusions are identified in MERRA-2 by the folding of the dynamical tropopause under the jet stream and subsequent isentropic descent of dry, O3-rich stratospheric air towards the surface where ozone air quality exceedences were observed. The MERRA-2 reanalysis can support air quality agencies for more rapid identification of the impact of stratospheric air on ground-level ozone.

Knowland, K. Emma↗

Bayesian modeling of traffic-related air pollutants: A case study of urban transportation and air quality dynamics in Columbia, South Carolina

Traffic emissions significantly impact near-road air quality and public health. This research applies a Bayesian modeling framework to investigate these impacts using high-resolution traffic and air pollutant data from an urban corridor in Columbia, South Carolina. Despite a data collection period truncated by the COVID-19 lockdown, the Bayesian approach successfully identified significant predictors and quantified model uncertainty. Employing Bayesian Model Selection and Averaging enhanced prediction accuracy and evaluated model uncertainty. Findings indicate that higher temperatures and increased moisture levels elevate particulate matter (PM 1.0 , PM 2.5 , PM 10 ) concentrations, while traffic speed significantly affects nitrogen dioxide (NO 2 ) levels. Specifically, higher average traffic speeds (indicative of smoother flow) correspond to lower NO 2 concentrations, suggesting that less congested conditions reduce NO 2 emissions. This study highlights the robustness of Bayesian methods for generating reliable air quality insights even under data-constrained conditions. The findings underscore the importance of traffic flow management (e.g., reducing congestion) for mitigating near-road NO 2 exposure and provide a basis for developing targeted public health strategies.

54 ENVIRONMENTAL SCIENCES↗

WMO Air Quality and Climate Bulletin - No. 2

Ongoing climate change, caused by the accumulation of greenhouse gases in the atmosphere, is happening on a timescale of decades to centuries and is driving environmental changes worldwide. In contrast, the air pollution that occurs near the Earth’s surface happens on a timescale of days to weeks, and across spatial scales that range from local (for example, urban centres) to regional (such as the eastern United States of America, northern India or the Amazon). Despite these wide‑ranging differences, air quality and climate change are strongly interconnected. The WMO Air Quality and Climate Bulletin reports annually on the state of air quality and its connections to climate change, reflecting on the geographical distribution of and changes in the levels of traditional pollutants.

Air quality↗

Long‐Term Impacts of Global Solid Biofuel Emissions on Ambient Air Quality and Human Health for 2000–2019

Globally, solid biofuels (SB) have been widely used for household cooking and energy production for decades due to electricity shortages and socio-economic barriers to adopting renewable energy alternatives. This has detrimental effects on air quality, human health, and climate through trace gas and aerosol emissions. Despite numerous studies, the long-term consequences of SB emissions remain poorly understood. Here, we use the Community Earth System Model and the Community Emissions Data System emission inventory to investigate the SB emission impacts on air quality and human health for 2000–2019. Global SB emission increased the ambient PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) and ozone (O 3 ) concentrations up to 23.61 μg/m 3 and 13.69 ppbv, with significant effects found in India, China, and the Rest of Asia (ROA). Our study estimates total annual premature deaths (APDs) associated with global SB-attributable PM 2.5 and O 3 exposure as 1.11 million [95% confidence interval (95% CI): 1.00–1.22 million] in 2000 up to 1.43 million (95% CI: 1.30–1.56 million) in 2019. China's SB emissions and associated APDs have reduced substantially, whereas India and ROA had a major leap in both estimates in 2019 compared to 2000. China's progress in cutting residential SB emissions accounts for its improvements. Our study urges the reduction of SB usage and emissions to potentially improve overall air quality and human health conditions, especially in highly populated, low- and middle-income countries, where the poor air quality and associated health burden attributable to SB emissions are estimated to be higher.

O 3↗

An Overview of Atmospheric Chemistry and Air Quality Modeling

This presentation will include my personal research experience and an overview of atmospheric chemistry and air quality modeling to the participants of the NASA Student Airborne Research Program (SARP 2017). The presentation will also provide examples on ways to apply airborne observations for chemical transport (CTM) and air quality (AQ) model evaluation. CTM and AQ models are important tools in understanding tropospheric-stratospheric composition, atmospheric chemistry processes, meteorology, and air quality. This presentation will focus on how NASA scientist currently apply CTM and AQ models to better understand these topics. Finally, the importance of airborne observation in evaluating these topics and how in situ and remote sensing observations can be used to evaluate and improve CTM and AQ model predictions will be highlighted.

Atmospheric↗

NASA Earth Observation Systems and Applications for Health and Air Quality

There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

Omar, Ali H.↗

Monitoring Air Quality from Space using AURA Data

Measurements from the Earth Observing System (EOS) AURA mission will provide a unique perspective on air quality monitoring. Ozone, nitrogen dioxide, formaldehyde and aerosols from the Ozone Monitoring Instrument (OMI) and carbon monoxide from the Tropospheric Emission Spectrometer (TES) will be simultaneously measured with the spatial resolution and coverage needed for improving our understanding of air quality. AURA data products useful for air quality monitoring will be given.

Gleason, James F.↗

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↗

Multi-Agency Ensemble Forecast of Wildfire Air Quality in the United States: Toward Community Consensus of Early Warning

Wildfires pose increasing risks to human health and properties in North America. Due to large uncertainties in fire emission, transport, and chemical transformation, it remains challenging to accurately predict air quality during wildfire events, hindering our collective capability to issue effective early warnings to protect public health and welfare. Here we present a new real-time Hazardous Air Quality Ensemble System (HAQES) by leveraging various wildfire smoke forecasts from three U.S. federal agencies (NOAA, NASA, and Navy). Compared to individual models, the HAQES ensemble forecast significantly enhances forecast accuracy. To further enhance forecasting performance, a weighted ensemble forecast approach was introduced and tested. Compared to the unweighted ensemble mean, the multilinear regression weighted ensemble reduced fractional bias by 34% in the major fire regions, false alarm rate by 72%, and increased hit rate by 17%. Finally, we improved the weighted ensemble using quantile regression and weighted regression methods to enhance the forecast of extreme air quality events. The advanced weighted ensemble increased the PM2.5 exceedance hit rate by 55% compared to the ensemble mean. Our findings provide insights into the development of advanced ensemble forecast methods for wildfire air quality, offering a practical way to enhance decision-making support to protect public health.

Yunyao Li↗

Using deep transfer learning and satellite imagery to estimate urban air quality in data-poor regions

Urban air pollution is a critical public health challenge in low-and-middle-income countries (LMICs). At the same time, LMICs tend to be data-poor, lacking adequate infrastructure to monitor air quality (AQ). As LMICs undergo rapid urbanization, the socio-economic burden of poor AQ will be immense. Here we present a globally scalable two-step deep learning (DL) based approach for AQ estimation in LMIC cities that mitigates the need for extensive AQ infrastructure on the ground. We train a DL model that can map satellite imagery to AQ in high-income countries (HICs) with sufficient ground data, and then adapt the model to learn meaningful AQ estimates in LMIC cities using transfer learning. The trained model can explain up to 54% of the variation in the AQ distribution of the target LMIC city without the need for target labels. The approach is demonstrated for Accra in Ghana, Africa, with AQ patterns learned and adapted from two HIC cities, specifically Los Angeles and New York.

54 ENVIRONMENTAL SCIENCES↗

Reinforcement Learning Control for Buildings Co-Optimizing Energy, Comfort, and Indoor Air Quality: An Annual Assessment

Efficient control of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial for optimizing energy use and maintaining indoor comfort in buildings. Traditional control methods, such as PID control, cannot handle energy use trade-offs among multiple components in the building energy system at a supervisory level. Reinforcement learning (RL) presents a promising solution, offering adaptive and data-driven control strategies that optimize performance over time. However, RL also faces several challenges, including the conflicts encountered in co-optimizing energy savings, occupant comfort, and indoor air quality, and the requirement for extensive interactions with the environment in training. We proposed a flexible simulation platform that integrates a hybrid model for RL training and designed an RL agent to control the entire central HVAC system, focusing on co-optimizing energy consumption, thermal comfort, and indoor air quality ($\text{CO}_{2}$ and PM2.5 concentrations). Finally, we evaluated the RL agent's performance over an annual cycle. Our findings indicate that the RL agent can effectively manage the HVAC system with 14.7 % energy savings annually and balance multiple objectives, which demonstrates significant potential for improving HVAC system control and sustainability in buildings.

Guo, Fangzhou↗

Cabin Air Quality On Board Mir and the International Space Station: A Comparison

The maintenance of the cabin atmosphere aboard spacecraft is critical not only to its habitability but also to its function. Ideally, air quality can be maintained by striking a proper balance between the generation and removal of contaminants. Both very dynamic processes, the balance between generation and removal can be difficult to maintain and control because the state of the cabin atmosphere is in constant evolution responding to different perturbations. Typically, maintaining a clean cabin environment on board crewed spacecraft and space habitats is the central function of the environmental control and life support (ECLS) system. While active air quality control equipment is deployed on board every vehicle to remove carbon dioxide, water vapor, and trace chemical components from the cabin atmosphere, perturbations associated with logistics, vehicle construction and maintenance, and ECLS system configuration influence the resulting cabin atmospheric quality. The air-quality data obtained from the International Space Station (ISS) and NASA-Mir programs provides a wealth of information regarding the maintenance of the cabin atmosphere aboard long-lived space habitats. A comparison of the composition of the trace chemical contaminant load is presented. Correlations between ground-based and in-flight operations that influence cabin atmospheric quality are identified and discussed, and observations on cabin atmospheric quality during the NASA-Mir expeditions and the International Space Station are explored.

Macatangay, Ariel↗

Definition of air quality measurements for monitoring space shuttle launches

A description of a recommended air quality monitoring network to characterize the impact on ambient air quality in the Kennedy Space Center (KSC) (area) of space shuttle launch operations is given. Analysis of ground cloud processes and prevalent meteorological conditions indicates that transient HCl depositions can be a cause for concern. The system designed to monitor HCl employs an extensive network of inexpensive detectors combined with a central analysis device. An acid rain network is also recommended. A quantitative measure of projected minimal long-term impact involves the limited monitoring of NOx and particulates. All recommended monitoring is confined ti KSC property.

Thorpe, R. D.↗

Healthy Indoor Air Quality: A Guide to Understanding Pollutants in Extreme Cold Climates

Internal air quality management through commonly supported recommendations in extreme cold weather climates is complicated by cold air infiltration. Air filtration and IAQ monitoring, through central and stand-alone systems can improve internal air quality to the benefit of occupant health and safety. This fact sheet includes reference information for pollutants, sources, health effects, and mitigation strategies.

cold climate↗