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NASA NTRS2021

Quantifying the Impacts of PM2.5 Constituents and Relative Humidity on Visibility Impairment in a Suburban Area of Eastern Asia Using Long-Term In-Situ Measurements.

The deterioration of visibility due to air pollutants and relative humidity has been a serious environmental problem in eastern Asia. In most previous studies, chemical compositions of atmospheric particles were provided using filter-based offline analyses, which were unable to provide long-term and in-situ measurements that resolve sufficient temporal variations of air pollution and meteorology, hindering the resolution of the relationship between air quality and visibility. Here, we present a year-long continuously measured data from a comprehensive suite of online instruments to investigate diurnal and seasonal impacts of the aerosol chemical compositions in PM2.5 on visibility seasonally and diurnally. The measured dry aerosol extinction at λ = 550 nm reached a closure with that predicted by aerosol compositions within 12%. However, the hygroscopic growth of particles under ambient RH could enhance the aerosol extinction by a factor of 2 – 6, matching the perceptive visibility of the public. Particulate ammonium nitrate was most sensitive to reducing visibility, while ammonium sulfate contributed the most to the light extinction. In spring and winter, the monsoon and stagnant air masses reduced the visibility and increased PM2.5 (> 35 μg m-3).The moisture was found to substantially enhance the light extinction under RH = 60 – 90%,reducing visibility by approximately 15 km, largely attributed to hygroscopic inorganic salts.This study serves as a metric to highlight the need to consider the influence of RH, and aqueous reactions in producing secondary inorganic aerosols on atmospheric visibility, underpinning the more accurate mitigation strategies of air pollution.

visibility↗
NASA NTRS2022

Gulf of Mexico Health and Air Quality: Using NASA Earth Observations to Identify Potential Methane Sources for Improved Monitoring of Offshore Oil & Gas Activity in the Gulf of Mexico

The extraction, production, and transportation of oil and gas is a leading contributor to anthropogenic methane emissions via activities such as flaring and venting. The Bureau of Ocean and Energy Management (BOEM) has air quality jurisdiction offshore in the Gulf of Mexico and drafts regulations for criteria pollutants, while the Bureau of Safety and Environmental Enforcement (BSEE) enforces these regulations. Additionally, the non-profit organization SkyTruth monitors natural resources, including methane. BOEM, BSEE, and SkyTruth have partnered with NASA DEVELOP to use Earth observations to identify potential offshore methane sources in the Gulf of Mexico and to validate reported flaring activity. This information will allow BOEM and BSEE to make informed regulations regarding air pollution. Here, we cross-referenced BOEM infrastructure data with Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Radiometer Suite (VIIRS) Nightfire data to validate operator-reported flaring. Sentinel-5p TROPOspheric Monitoring Instrument (TROPOMI) pollutant concentrations were used to validate VIIRS-detected flaring outside of the Gulf of Mexico where operator-reported data is unavailable. Using these methods, we identified the locations of offshore oil and gas infrastructure with known episodic flaring and venting in 2017 in the Gulf of Mexico, as well as offshore of South America and West Africa in 2021. Drawing upon retrieval methods used to detect onshore methane emissions, we proposed an analogous method utilizing sunglint to illuminate methane plumes over the ocean using Sentinel-2 Multispectral Imager (MSI) imagery. We detected two potential methane plumes – one at the Constitution complex in the Gulf of Mexico in July 2017 and one off the Coast of Lagos, West Africa, in July 2021.

Kate Howell↗
NASA NTRSDate not supplied

The INSTEP Monitoring Network: Merging High-and-Low Cost Measurements to Characterize California Wildfires

Despite challenges with data quality and scope, low-cost sensor networks have skyrocketed in popularity over the last 15 years, making air quality data available on refined spatial scales. More recently, studies have leveraged both high and low-quality instruments to create stronger “hybrid” models, with most studies focusing on particulate matter. Low-cost measurements typically represent ground-level emissions only, providing context for human health issues from climate change-driven events such as wildfires. Since low-cost sensors’ capabilities are localized, daily events and microclimates tend to dominate the data rather than larger regional or atmospheric trends. Likewise, their low cost explains their high uncertainty. In contrast, some regulatory-grade instruments produce column measurements as well, providing reliable information on a broader scope. To bridge this gap while expanding into gas-phase measurements, we deployed 12 air quality sensor packages in California, USA during the 2022 wildfire season. These INSTEP (Inexpensive Network Sensor Technology Exploring Pollution) monitors measure carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), and several hydrocarbons including methane (CH4) and formaldehyde (HCHO). Half of the monitors were co-located with remote sensing spectrometers: NASA Pandora and Total Column Carbon Observing Network (TCCON). The overlap in pollutants includes NO2, O3, and HCHO between the INSTEP monitors and the Pandora column measurements. TCCON covers column CO, CO2, and CH4, rounding out our comparison. Most of the monitors were distributed throughout the San Francisco Bay area, and an additional three were located within 100 km of Los Angeles. The sites ranged in geographic and population characteristics, including desert, mountainous, coastal, and urban locations. Since varying environmental conditions such as temperature and pressure are known to challenge sensor performance, we will apply newer sensor “calibration” techniques meant to combat this. We will normalize our sensor signals by z-scoring them prior to applying a single calibration model in the form of multivariate linear regression or an artificial neural network. While this technique has been validated for the hydrocarbon and ozone sensor types (metal oxide), it has not yet been tested on electrochemical and non-dispersive infrared sensors, which are also used in the INSTEP monitors. This will serve as a test to see if this normalization technique – or another – is most effective in accounting for environmental differences among sensors. Related data analysis efforts have found success with a variety of geospatial analysis techniques, including weighted network models in which high-quality instruments are given higher weights than their low-cost counterparts. Our preliminary analysis will focus on kriging, which uses a Gaussian algorithm to assign weights, providing estimated pollution levels at locations between monitors. Smoke trajectory and evolution will also be considered using both measurement types. We also aim to baseline subtract our emission estimates from each region to determine which portion of emissions are regional and local, further characterizing burn differences in northern and southern California fires. Future directions include using INSTEP jointly with TEMPO satellite data, and mobile deployments on aircraft and uncrewed aerial vehicles (UAV).

Low-cost sensors↗
NASA NTRS2022

The Ozone–Climate Penalty Over South America and Africa By 2100

Climate change has the potential to increase surface ozone (O3) concentrations, known as the “ozone–climate penalty”, through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozone–climate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15 ppb (model range 12 to 18 ppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozone–climate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx-limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low-NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozone–climate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario.

Surface ozone↗
NASA NTRS2022

Source and Chemistry of Hydroxymethanesulfonate (HMS) in Fairbanks, Alaska

Fairbanks, Alaska is a subarctic city with fine-particle (PM 2.5 ) concentrations that exceed air quality regulations in winter due to weak dispersion caused by strong atmospheric inversions, local emissions, and the unique chemistry occurring under the cold and dark conditions. Here we report on observations from the winters of 2020 and 2021, motivated by our pilot study which showed exceptionally high concentrations of fine particle hydroxy methane sulfonate (HMS) or related sulfur (IV) species (e.g., sulfite and bisulfite). We deployed an online Particle-Into-Liquid Sampler-Ion Chromatography (PILS-IC) in conjunction with a suite of instruments to determine HMS precursors (HCHO, SO 2 ) and aerosol composition in general, with the goal to characterize the sources and sinks of HMS in wintertime Fairbanks. PM 2.5 HMS comprised a significant fraction of PM 2.5 sulfur (26-41%) and overall PM 2.5 mass concentration (2.8-6.8%) during pollution episodes, substantially higher than what has been observed in other regions, likely due to the exceptionally low temperatures. HMS peaked in January, with lower concentrations in December and February, resulting from changes in precursors as well as meteorological conditions. Strong correlations with inorganic sulfate and organic mass during pollution events suggest HMS is linked to processes responsible for poor air quality episodes. These findings demonstrate unique aspects of air pollution formation in cold and humid atmospheres.

Fine-particle↗
NASA NTRS2023

Impacts of Estimated Plume Rise on PM 2.5 Exceedance Prediction During Extreme Wildfire Events: A Comparison of Three Schemes (Briggs, Freitas, and Sofiev)

Plume height plays a vital role in wildfire smoke dispersion and the subsequent effects on air quality and human health. In this study, we assess the impact of different plume rise schemes on predicting the dispersion of wildfire air pollution and the exceedances of the National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM 2.5 ) during the 2020 western United States wildfire season. Three widely used plume rise schemes (Briggs, 1969; Freitas et al., 2007; Sofiev et al., 2012) are compared within the Community Multiscale Air Quality (CMAQ) modeling framework. The plume heights simulated by these schemes are comparable to the aerosol height observed by the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The performance of the simulations with these schemes varies by fire case and weather conditions. On average, simulations with higher plume injection heights predict lower aerosol optical depth (AOD) and surface PM 2.5 concentrations near the source region but higher AOD and PM 2.5 in downwind regions due to the faster spread of the smoke plume once ejected. The 2-month mean AOD difference caused by different plume rise schemes is approximately 20 %–30 % near the source regions and 5 %–10 % in the downwind regions. Thick smoke blocks sunlight and suppresses photochemical reactions in areas with high AOD. The surface PM 2.5 difference reaches 70 % on the West Coast of the USA, and the difference is lower than 15 % in the downwind regions. Moreover, the plume injection height affects pollution exceedance (>35 µg m−3) predictions. Higher plume heights generally produce larger downwind PM 2.5 exceedance areas. The PM 2.5 exceedance areas predicted by the three schemes largely overlap, suggesting that all schemes perform similarly during large wildfire events when the predicted concentrations are well above the exceedance threshold. At the edges of the smoke plumes, however, there are noticeable differences in the PM 2.5 concentration and predicted PM 2.5 exceedance region. For the whole period of study, the difference in the total number of exceedance days could be as large as 20 d in northern California and 4 d in the downwind regions. This disagreement among the PM 2.5 exceedance forecasts may affect key decision-making regarding early warning of extreme air pollution episodes at local levels during large wildfire events.

Yunyao Li↗
NASA NTRSDate not supplied

Climate Change Impact on Surface Ozone Based on CMIP6 Earth System Models

It is presented an analysis of the effect of climate change on surface ozone (O3) discussing the related penalties and benefits around the globe from the global modeling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. All models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions scenario (SSP3-7.0). Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration varying spatially from -0.2 to -2 ppbv oC-1, with strongest decline over tropical oceanic regions, which is mainly linked to the dominating role of enhanced ozone chemical loss with higher water vapour abudances under a warmer climate. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural Biogenic Volatile Organic Compounds (BVOC) emission sources with a rate ranging regionally from 0.2 to 2 ppbv oC-1, implying a regional surface ozone penalty due to global warming. The individual models show this robustly for south-eastern China and India as well as for regions of Africa but there are inter-model differences in areas within Europe and the United States (US) as well as in South America. The future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

climate change↗
NASA NTRSDate not supplied

Exploring Anomalous PM 2.5 from Wildfires and Dust Storms using Data and Services at NASA GES DISC

The presence of fine particles in the atmosphere with a diameter of less than 2.5 µm, called particulate matter 2.5 (PM 2.5 ), poses a significant threat to human health as a criteria air pollutant. Fortunately, NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) provides easy access to several PM 2.5 concentration products. These datasets include the reanalysis of global hourly and monthly aerosol components including PM 2.5 data from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), as well as 3-hourly real-time ensemble forecasts of PM 2.5 from the Hazardous Air Quality Ensemble System (HAQES). The HAQES products are developed by the George Mason University Air Quality Laboratory as part of NASA's Health Air Quality Applied Science Team (HAQAST). The GES DISC is actively collaborating with scientists in the HAQAST program to further expand air quality data collections. Two new datasets are currently being archived: one is the machine learning-based global hourly PM 2.5 derived from MERRA-2; the other is the localized data (NO 2 , O 3 , and PM 2.5 ) time series derived from NASA's GEOS Composition Forecasting (GEOS-CF) system. In this presentation, we will explore the spatial patterns and long-distance transport characteristics of elevated PM 2.5 during extreme pollution events, such as the June 2023 Canadian wildfires, which are still active at the time of writing; and severe spring dust storms in 2023 over Asia. To gain comprehensive insights, we will utilize various PM 2.5 data in conjunction with satellite-observed aerosol data from TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel-5P. The primary focus of this presentation will be to demonstrate effective use of data tools and services to visualize and explore extreme air pollution phenomena. Additionally, we will provide guidance on how users can download specific data of interest, facilitating further analysis and research in this critical area.

air quality↗
NASA NTRSDate not supplied

Illustrating the Spatiotemporal Complexity of No2 Columns Using A Multi-Perspective Observing System: Moving Toward Geostationary Product Validation and Applications

As a precursor to secondary pollutants like ozone and PM2.5, nitrogen dioxide (NO2) is crucial to understand when addressing air quality issues. However, due to NO2’s short lifetime during the daytime and complexity of emission sources in urbanized regions, interpreting datasets from ground or satellite perspectives alone are challenged by variance in spatial and temporal resolutions. High resolution airborne mapping (< 1 km) of NO2 column densities across morning, midday, and afternoon add a unique perspective toward interpreting satellite data with respect to ground-measurements. This presentation focuses on the interpretation of spatiotemporal complexity of NO2 columns from the Synergistic TEMPO Air Quality Science Study (STAQS). The mission’s goal is to integrate geostationary observations from Tropospheric Emissions: Monitoring of Pollution (TEMPO) with traditional and enhanced air quality monitoring to improve the understanding of air quality science for increased societal benefit. We will demonstrate the interweaved perspective of NO2 columns from ground-based Pandora spectrometers and satellite-based observations (e.g., TROPOMI) as compared to high spatial resolution airborne observations from the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS). This includes the evaluation of each dataset through comparison to each other to identify potential biases in data products and the impact of heterogeneity on these comparisons. Airborne data will also be used as a proxy for geostationary observations with morning, midday, and afternoon raster maps collected over four cities (Los Angeles, Chicago, Toronto, and New York City). Finally, recent research outcomes will be presented to demonstrate how airborne and geostationary observations can be used to evaluate emission inventories and air quality models.

Laura Judd↗
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

Evaluating Diurnal Ozone Emissions: A Comparative Analysis of DSCOVR EPIC, PANDORA, and TOLNet Data for Space-Based Monitoring Assessment: A Case Study by ASDC

Stratospheric ozone occurs naturally in the upper atmosphere, forming a protective layer that shields us from the sun's harmful ultraviolet rays. Tropospheric ozone is not emitted directly into the air but is created by chemical reactions between nitrogen oxides (NOx) and volatile organic compounds (VOC). This reaction happens when pollutants emitted by cars, power plants, industrial boilers, refineries, chemical plants, and other sources chemically react in sunlight [1]. Therefore, increased levels of tropospheric ozone indicate the presence of pollutants in the air. While daily anthropogenic activity causes an increase of ground-level ozone, variation of stratospheric ozone changes happens much slower, so that variation of the total ozone column reflects the variation of the tropospheric column due to natural, e.g., wildfires and anthropogenic air pollution. Both total and tropospheric ozone column products are used in this study. The reflectance spectra measured by the Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) spacecraft are compared with a set of radiative transfer-derived lookup tables for the EPIC filter transmission functions and a wide range of ozone values to retrieve ozone with a maximum resolution of 18 km at the sub-satellite point [2]. EPIC provides total column ozone in level 2 and level 4 products and tropospheric column ozone in level 4 products. Both EPIC Ozone products [2] are available at the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center [3, 4]. Pandora spectrometer instrument measures columnar amounts of trace gases in the atmosphere. These gases (O3, NO2, CH2O) absorb light from the sun at specific wavelengths in the ultraviolet-visible spectrum [5]. Using the theoretical solar spectrum as a reference, Pandora determines trace gas amounts using differential optical absorption spectroscopy (DOAS). Pandora ozone retrievals are available from the Pandonia Global Network [6]. Pandora data from North American major metropolitan areas, New York, NY, Washington DC, Los Angeles, CA, and Mexico City. Tropospheric Ozone Lidar Network (TOLNet) was established in 2012 to provide high spatiotemporal observations of tropospheric ozone to (1) better understand physical processes driving the ozone budget in various meteorological and environmental conditions and (2) validate the tropospheric ozone measurements of space-borne missions [7]. TOLNet data are available at ASDC [8]. While EPIC provides global coverage of ozone retrievals several times daily, temporal resolution may miss some features in daily ozone variations. Ground-based sensors such as Pandora spectrometers and TOLNet lidars provide better temporal resolution while missing continuous spatial coverage. The forthcoming ozone retrieval from the TEMPO mission [9] will provide better spatial and temporal coverage of air quality (including ozone) over North America. This study investigates whether EPIC ozone products can detect diurnal air quality variations and compare ozone temporal development with retrieval by ground-based instruments.

diurnal ozone emissions, DSCOVR EPIC, PANDORA, spa↗
NASA NTRS2023

Decoupling in the Vertical Shape of HCHO During a Sea Breeze Event: the Effect on Trace Gas Satellite Retrievals and Column-to-Surface Translation

The effect of sea breeze circulation on stratification of the vertical formaldehyde (HCHO) concentration vertical profiles is explored using a regional atmospheric chemical transport model (CTM) for three synoptically stagnant days focused on the east coast of the U.S in June 2018. During this event, a significant thermal contrast between the Atlantic Ocean and the terrestrial regions (12–17 °C), observed by moderate resolution imaging spectroradiometer (MODIS) and well-captured by the WRF-CMAQ model (15–18 °C), is conducive to monsoon-like flow, perpendicular to the shorelines, carrying clean marine air masses over the land within a few hundreds of meters above the surface. In contrast, the westerly continental polluted air masses prevail in higher altitudes. These two conflicting flows result in atypical vertical shapes of HCHO concentrations increasing with altitude. This decoupling pattern is so pronounced that we observe total column HCHO negatively correlate with surface concentrations. Comparisons of an accredited global model, GEOS-CF, to surface wind measurements and MODIS skin temperature indicate its poor representation of the sea breeze timing and strength, resulting in GEOS-CF HCHO vertical shapes being drastically different from the WRF-CMAQ. Based on radiative transfer calculations, the differences in the vertical distribution of HCHO between the WRF-CMAQ and that of GEOS-CF in the first 3 km are sufficient to induce a 20–30% error in air mass factors (thus total vertical HCHO column abundances). Through an experiment involving converting HCHO total columns to surface mixing ratios, we demonstrate that GEOS-CF allocates noticeably more HCHO molecules (40–150%) to the surface layer due to the misrepresentation of the vertical shape of HCHO during the sea breeze event. It is known that a significant fraction of the human population lives in coastal areas prone to detrimental effects caused by air pollution, and elevated pollutant concentrations usually occur in synoptically stagnant atmospheric conditions when local circulation patterns come into play; accordingly, our experiments emphasize the importance of the effect a priori profiles can have on satellite-derived applications under such conditions. To ensure that the quantitative representation of satellite-based trace gas retrievals on a daily basis is trustworthy and useable for air quality applications, atmospheric models providing a priori profiles for satellite retrievals should be well-tuned to reproduce complex local circulation such as sea-land breezes.

sea breeze↗
NASA NTRSDate not supplied

Finding Your TEMPO: An Introduction to the Mission, Products, and Data Services for Air Quality Observations over North America

NASA's Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission is the first space-based instrument to monitor major air pollutants across the North American continent every daylight hour at high spatial resolution. TEMPO is an ultraviolet and visible spectrometer that sits on a commercial satellite in a geostationary orbit about 22,000 miles above Earth's equator. This vantage point enables TEMPO to monitor daily variations in ozone, nitrogen dioxide, and other key elements of air pollution from the Atlantic to the Pacific, and from Mexico City and the Yucatan Peninsula to the Canadian oil sands. This webinar will provide an overview of the TEMPO mission and its data products and will show you how to discover and access TEMPO data products using NASA's Earthdata Search. This includes finding documentation, performing searches and filtering, using subsetting/concatenation services in Earthdata Search, and utilizing the Earthdata Forum.

Caroline Nowlan↗
NASA NTRS2024

Spacecraft Maximum Allowable Concentrations for Airborne Contaminants: Revision C

The enclosed table lists official Spacecraft Maximum Allowable Concentrations (SMACs) for selected airborne contaminants. They are based upon experiments conducted at standard pressure and oxygen environments and may or may not be applicable to altered atmospheres. The values listed in this summary document are applicable only to ambient conditions at standard temperature and oxygen (14.7 psi and 21% O2 at 25°C). These are guideline values set by the National Aeronautics and Space Administration (NASA)/Johnson Space Center (JSC) Toxicology Group in cooperation with the National Research Council Committee on Toxicology (NRCCOT), through publication in the peer- reviewed scientific literature, or NASA Technical Memoranda. Based on documented guidance (NRC, 1992; NRC, 2016), NASA has established SMACs for 58 chemical compounds that are particularly relevant to atmospheric contamination of the International Space Station (ISS) and targets of Exploration. Some long-term limits (1000-days) have also been established to support manned deep-space exploration. Summaries of these SMACs are presented in tabular form as part of this publication. This document provides a tabular summary of values that have been previously established based on guidelines established by NASA and the National Research Council’s Committee on Toxicology and vetted and published through the NRCCOT and/or non-NASA scientific literature and NASA Technical Memoranda. Short‐term (1‐ and 24‐hour) SMACs apply to off‐nominal situations, such as accidental releases aboard a spacecraft. These limits permit risk of minor, reversible effects, such as mild mucosal irritation. In contrast, the long‐term SMACs are set to fully protect healthy crewmembers from adverse effects resulting from continuous exposure to specific air pollutants for up to 1000 days. Because allergic reactions or chemical idiosyncrasy to certain airborne pollutants are very difficult to predict, crewmembers with allergies or unusual sensitivity to trace pollutants may not be afforded complete protection, even when long‐term SMACs are not exceeded.

SMACs↗
NASA NTRSDate not supplied

Convective Transport to the Upper Troposphere and Lower Stratosphere Over the Asian Summer Monsoon as Observed During the 2022 ACCLIP Airborne Campaign

Deep convection in the Asian summer monsoon (ASM) rapidly transports boundary layer pollutants including ozone-depleting substances into the upper troposphere and lower stratosphere (UTLS). The confinement of the seasonal anticyclonic circulation in the UTLS over Asia initially traps the pollutants near the tropopause level, but air masses are subsequently transported throughout the global stratosphere and impact Earth’s climate. Characterizing the transport pathways and processes of these pollutants are critical for identifying source regions and quantifying regional contributions to global stratospheric concentrations. The Asian summer monsoon Chemical and Climate Impact Project (ACCLIP) was conducted in summer 2022 using two high-altitude aircraft (NSF NCAR Gulfstream V and the NASA WB-57) to obtain UTLS chemical composition and aerosol distribution for characterizing the impact of the ASM on global chemistry and climate. Backward trajectories from ACCLIP flight tracks were traced through time-varying, satellite-derived global convective cloud top altitude fields to investigate the convective air mass origins of the sampled air parcels. Analyses reveal that air masses lofted by convection within the ASM (South Asian summer monsoon) and near the edge of the of the ASM anticyclone (East Asian summer monsoon) contributed to the airborne observations. In this study, we present a summary of the transport statistics of UTLS air masses sampled during ACCLIP and discuss the implications of these results on our understanding of the role of ASM in global constituent transport.

Convective↗
NASA NTRSDate not supplied

A21I-1875: Leveraging TEMPO Formaldehyde Observations to Assess Surface Air Quality

Surface ozone (O3) pollution is detrimental to human health, crop yields, and ecosystem productivity. Ground-based ozone observations are sparse and surface ozone retrievals from space are challenging. The process of producing ozone from the oxidation of volatile organic compounds (VOCs) in the presence of nitrogen oxides (NOx) results in formaldehyde (HCHO), which can be observed from satellite and by surface-based remote sensing. From limited field campaign observations, column formaldehyde has been shown to exhibit a strong relationship with surface ozone and, therefore, could be an useful proxy for detecting unmonitored regions of elevated ozone pollution. The spatiotemporal characteristics of this relationship are explored using ground-based Pandora spectrometers and airborne remote sensing data with surface ozone monitors across the United States during recent field campaigns over major cities (TRACER-AQ and STAQS). We extend our analysis to take advantage of HCHO column observations from recently launched Tropospheric Emissions: Monitoring of Pollution (TEMPO), a geostationary satellite over North America. TEMPO observations show preliminary promise in mapping regions of elevated surface ozone from space using column HCHO. We demonstrate the use of column HCHO in assessing the strength of the surface monitoring network, and in detecting the extent of regional ozone exceedances.

Prajjwal Rawat↗
NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗
DOE OSTI2014

Optimization of Ventilation Energy Demands and Indoor Air Quality in High-Performance Homes

High-performance homes require that ventilation energy demands and indoor air quality (IAQ) be simultaneously optimized. We attempted to bridge these two areas by conducting tests in a research house located in Oak Ridge, TN, that was 20 months old, energy-efficient (i.e., expected to consume 50% less energy than a house built per the 2006 IRC), tightly-built (i.e., natural ventilation rate ~0.02 h-1), unoccupied, and unfurnished. We identified air pollutants of concern in the test home that could generally serve as indicators of IAQ, and conduced field experiments and computer simulations to determine the effectiveness and energy required by various techniques that lessened the concentration of these contaminants. Formaldehyde was selected as the main pollutant of concern among the contaminants that were sampled in the initial survey because it was the only compound that showed concentrations that were greater than the recommended exposure levels. Field data indicate that concentrations were higher during the summer primarily because emissions from sources rise with increases in temperature. Furthermore, supply ventilation and gas-phase filtration were effective means to reduce formaldehyde concentrations; however, exhaust ventilation had minimal influence on this pollutant. Results from simulations suggest that formaldehyde concentrations obtained while ventilating per ASHRAE 62.2-2010 could be decreased by about 20% from May through September through three strategies: 1) increasing ASHRAE supply ventilation by a factor of two, 2) reducing the thermostat setpoint from 76 to 74 F, or 3) running a gas-phase filtration system while decreasing supply ventilation per ASHRAE by half. In the mixed-humid climate of Oak Ridge, these strategies caused increases in electricity cost of ~$5 to ~$15/month depending on outdoor conditions.

Hun, Diana E↗