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At least 127 records · Page 7

Biomass Burning Airborne and Spaceborne Experiment in the Amazonas (BASE-A)

Results are presented on measurements of the trace gas and particulate matter emissions due to biomass burning during deforestation and grassland fires in South America, conducted as part of the Biomass Burning Airborne and Spaceborne Experiment in the Amazonas in September 1989. Field observations by an instrumented aircraft were used to estimate concentrations of O3, CO2, CO, CH4, and particulate matter. Fires were observed from satellite imagery, and the smoke optical thickness, particle size, and profiles of the extinction coefficient were measured from the aircraft and from the ground. Four smoke plumes were sampled, three vertical profiles were measured, and extensive ground measurements of smoke optical characteristics were carried out for different smoke types. The simultaneous measurements of the trace gases, smoke particles, and the distribution of fires were used to correlate biomass burning with the elevated levels of ozone.

Kaufman, Y. J.↗

The Projected Future Degradation in Air Quality is Caused by More Abundant Natural Aerosols in a Warmer World

Previous studies suggest that greenhouse gas-induced warming can lead to increased fine particulate matter concentrations and degraded air quality. However, significant uncertainties remain regarding the sign and magnitude of the response to warming and the underlying mechanisms. Here, we show that thirteen models from the Coupled Model Intercomparison Project Phase 6 all project an increase in global average concentrations of fine particulate matter in response to rising carbon dioxide concentrations, but the range of increase across models is wide. The two main contributors to this increase are increased abundance of dust and secondary organic aerosols via intensified West African monsoon and enhanced emissions of biogenic volatile organic compounds, respectively. Much of the inter-model spread is related to different treatment of biogenic volatile organic compounds. Our results highlight the importance of natural aerosols in degrading air quality under current warming, while also emphasizing that improved understanding of biogenic volatile organic compounds emissions due to climate change is essential for numerically assessing future air quality.

Climate and Earth system modelling↗

Trace Chemistry

The goals of the trace chemistry group were to identify the processes relevant to aerosol and aerosol precursor formation occurring within aircraft gas turbine engines; that is, within the combustor, turbine, and nozzle. The topics of discussion focused on whether the chemistry of aerosol formation is homogeneous or heterogeneous; what species are important for aerosol and aerosol precursor formation; what modeling/theoretical activities to pursue; what experiments to carry out that both support modeling activities and elucidate fundamental processes; and the role of particulates in aerosol and aerosol precursor formation. The consensus of the group was that attention should be focused on SO2, SO3, and aerosols. Of immediate concern is the measurement of the concentration of the species SO3, SO2, H2SO4 OH, HO2, H2O2, O, NO, NO2, HONO, HNO3, CO, and CO2 and particulates in various engines, both those currently in use and those in development. The recommendation was that concentration measurements should be made at both the combustor exit and the engine exit. At each location the above species were classified into one of four categories of decreasing importance, Priority I through IV, as follows: Combustor exit: Priority I species - SO3:SO2 ratio, SO3, SO2, and particulates; Priority II species: OH and O; Priority III species - NO and NO2; and Priority IV species - CO and CO2. For the Engine exit: Priority I species - SO3:SO2 ratio, SO3, SO2,H2SO4, and particulates; Priority II species: OH,HO2, H2O2, and O; Priority III species - NO, NO2, HONO, and HNO3; and Priority IV species - CO and CO2. Table I summarizes the anticipated concentration range of each of these species. For particulate matter, the quantities of interest are the number density, size distribution, and composition. In order to provide data for validating multidimensional reacting flow models, it would be desirable to make 2-D, time-resolved measurements of the concentrations of the above species and, in addition, of the pressure, temperature, and velocity. A near term goal of the experimental program should be to confirm the nonlinear effects of sulfur speciation, and if present, to provide an explanation for them. It is also desirable to examine if the particulate matter retains any sulfur. The recommendation is to examine the effects on SOx production of variations in fuel-bound sulfur and aromatic content (which may affect the amount of particulates formed). These experiments should help us to understand if there is a coupling between particulate formation and SO, concentration. Similarly, any coupling with NOx can be examined either by introducing NOx into the combustion air or by using fuel-bound nitrogen. Also of immediate urgency is the need to establish and validate a detailed mechanism for sulfur oxidation/aerosol formation, whose chemistry is concluded to be homogeneous, because there is not enough surface area for heterogeneous effects. It is envisaged that this work will involve both experimental and theoretical programs. The experimental work will require, in addition to the measurements described above, fundamental studies in devices such as flow reactors and shock tubes. Complementing this effort should be modeling and theoretical activities. One impediment to the successful modeling of sulfur oxidation is the lack of reliable data for thermodynamic and transport properties for several species, such as aqueous nitric acid, sulfur oxides, and sulfuric acid. Quantum mechanical calculations are recommended as a convenient means of deriving values for these properties. Such calculations would also help establish rate constants for several important reactions for which experimental measurements are inherently fraught with uncertainty. Efforts to implement sufficiently detailed chemistry into computational fluid dynamic codes should be continued. Zero- and one-dimensional flow models are also useful vehicles for elucidating the minimal set of species and reactions that must be included in two- and three-dimensional modeling studies.

Radhakrishnan, Krishnan↗

Comprehensive analysis of airborne contaminants from recent Spacelab missions

The Shuttle experiences unique air contamination problems because of microgravity and the closed environment. Contaminant build-up in the closed atmosphere and the lack of a gravitational settling mechanism have produced some concern in previous missions about the amount of solid and volatile airborne contaminants in the Orbiter and Spacelab. Degradation of air quality in the Orbiter/Spacelab environment, through processes such as chemical contamination, high solid-particulate levels, and high microbial levels, may affect crew performance and health. A comprehensive assessment of the Shuttle air quality was undertaken during STS-40 and STS-42 missions, in which a variety of air sampling and monitoring techniques were employed to determine the contaminant load by characterizing and quantitating airborne contaminants. Data were collected on the airborne concentrations of volatile organic compounds, microorganisms, and particulate matter collected on Orbiter/Spacelab air filters. The results showed that STS-40/42 Orbiter/Spacelab air was toxicologically safe to breathe, except during STS-40 when the Orbiter Refrigerator/Freezer unit was releasing noxious gases in the middeck. On STS-40, the levels of airborne bacteria appeared to increase as the mission progressed; however, this trend was not observed for the STS-42 mission. Particulate matter in the Orbiter/Spacelab air filters was chemically analyzed in order to determine the source of particles. Only small amounts of rat hair and food bar (STS-40) and traces of soiless medium (STS-42) were detected in the Spacelab air filters, indicating that containment for Spacelab experiments was effective.

Matney, M. L.↗

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations.

satellite remote sensing↗

Estimation of Daily PM(sub 10) Concentrations in Italy (2006-2012) Using Finely Resolved Satellite Data, Land Use Variables and Meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particulate Matter/analysis↗

Developing an Air Quality Index for Space Vehicles and Habitats

The development of an adequate tool to help the layperson understand pollution levels in their environment is of high importance. This tool must be able to inform about the levels of pollution in a simple and understandable way but also can be used for decision-making and mitigation activities to protect the health of the exposed population. One of the most useful and up-to-date approaches for characterizing air pollution is the Air Quality Index (AQI). It is an easily-calculated, powerful, data-driven tool that summarizes a complex phenomenon, such as air pollution, in straightforward indicators. The AQI system has been developed in different countries around the world, mainly for outdoor environments, based on the results of risk assessments, epidemiological studies, and current local air pollution regulations and standards. There is a need for such a system in low gravity indoor environments where air quality is of fundamental importance to astronaut health, with concerns encompassing both gaseous contaminants and particulate matter. Earth-based AQIs cannot be extrapolated to microgravity indoor environments due to different aerosol transport characteristics and altered lung deposition in low and partial gravity. The objectives of this work are to explore what areas of expertise, types of research, and data will be required to formulate a spacecraft-specific AQI. An initial dataset is available for this effort, combined from two aerosol sampling experiments, which have characterized airborne particulate matter on the International Space Station (ISS). We outline future research needs for formulating a narrowly focused version of a widely-used metric, namely, an indoor AQI for future space missions.

Sorek-Hamer, Meytar↗

Airborne Measurements of Carbonaceous Aerosols in Southern Africa during the Dry Biomass Burning Season

Particulate matter collected aboard the University of Washington's (UW) Convair-580 research aircrafi over southem Afiica during the dry biomass burning season was analyzed for total carbon (TC), organic carbon (OC), and black carbon (BC) contents using thermal and optical methods. Samples were collected in smoke plumes of burning savanna and in regional haze. A known artifact, produced by the adsorption of organic gases on the quartz filter substrates used to collect the particulate matter samples, comprised a significant portion of the TC collected. Consequently, conclusions derived from the data are greatly dependent on whether or not OC concentrations are corrected for this artifact. For example, the estimated aerosol coalbedo (1 - single scattering albedo (SSA)), which is a measure of aerosol absorption, of the biomass smoke samples is 60% larger using corrected OC concentrations. Thus, the corrected data imply that the biomass smoke is 60% more absorbing than do the uncorrected data. The BC to (corrected) OC mass ratio (BC/OC) of smoke plume samples (0.18 plus or minus 0.06) is lower than that of samples collected in the regional haze (0.25 plus or minus 0.08). The difference may be due to mixing of biomass smoke with background air characterized by a higher BC/OC ratio. A simple source apportionment indicates that biomass smoke contributes about three quarters of the aerosol burden in the regional haze, while other souxes (e.g., fossil fuel burning) contribute the remainder.

Kirchstetter, Thomas W.↗

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the GEOS model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

K Emma Knowland↗

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the GEOS model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

K Emma Knowland↗

Asthma and Air Quality in the Presence of Fires - A Foundation for Public Health Policy in Florida

Outdoor air quality and its associated impacts on respiratory problems in Florida are of public health significance. Air quality in Florida can be poor during the extended wildfire season, threatening persons with compromised respiratory systems each year. Studies have demonstrated that particulate matter, which is generally elevated in the vicinity of wildfires, is associated with increases in hospital admissions and occurrences of acute asthma exacerbations. However, few studies have examined the modifying effect of socio-demographic characteristics of cities or regional areas on the relationship between air quality and health outcomes. In an ongoing university/multi-agency project, asthma hospital/emergency room (patient) data are being used to create a health outcome indicator of human response to environmental air quality. Environmental data are derived from satellite measurements, with special attention being given to the effect of wildfires and prescribed burns on air quality. This presentation will focus on the environmental data sets particulate matter, location of fires, smoke plumes that are being collected and processed for linkage with health data. After this linkage has been performed, space-time models of asthma rates as a function of air quality data and socio-demographic variables will be developed and validated. The Florida Department of Health (FDOH) will work with county health department staff and representatives from the medical community to establish a protocol with triggers for issuing public health advisories/alerts based on the developed and validated health outcome indicators. From this effort, a science-based policy for issuing public health advisories/alerts for asthma relating to air quality will be developed, giving FDOH the ability to (1) predict, with stated levels of uncertainty, case load of hospital admissions based on air quality, (2) reduce asthma exacerbations by forewarning asthmatics to limit outside activities on poor air quality days, (3) apply management practices on the rates of hospital/emergency room visits for asthma, and (4) provide information that would help translate interventions into policy decisions, thereby reducing the economic burden and increasing well being of asthmatics. Further, the results of the study will be incorporated into Florida s Environmental Public Health Tracking (EPHT) program, which is part of the Centers for Disease Control and Prevention's (CDC's) EPHT network.

Crosson, William↗

Emission Characteristics of an Axially Staged Sector Combustor for a Small Core High OPR Subsonic Aircraft Engine

This paper presents the nitrogen oxides, carbon monoxide, and particulate matter emissions of a single sector axially staged combustor sector designed and fabricated by United Technologies Research Center (UTRC) in partnership with NASA under a compact low-emissions combustor contract supported by the NASA Advanced Air Transport Technology (AATT) N+3 project. The test was conducted at NASA Glenn Research Center's CE-5 combustion test facility. The facility provided inlet air temperatures up to 922 K and pressures up to 19.0 bar. The combustor design concept, called Axially Controlled Stoichiometry (ACS), was developed by Pratt & Whitney (P&W) under NASA's Environmentally Responsible Aviation (ERA) program for an N+2 combustor for use in twin-aisle subsonic aircraft engines. Under the N+3 project the ACS combustor was scaled-down for application to small-core N+3 engines for use in single-aisle aircraft. The results show that the NOx and CO emissions characteristics are similar in both the N+2 and N+3 applications. The non-volatile particulate matter (nvPM) emissions trends are similar to CO emissions with an exception at high fuel-air ratio, as inlet air temperature and pressure conditions change from taxi to approach. Three NOx correlation equations are generated to describe theNOx emissions of this combustor. The percentage landing and takeoff (LTO) NOx reduction of the N+3 ACS combustor is between 82% and 89% relative to the ICAO CAEP/6 standard, which meets the NASA N+3 goal of exceeding 80% LTO NOx reduction.

He, Zhuohui J.↗

Using NASA Environmental Data to Enhance Public Health Decision Making

The Universities Space Research Association at the NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this collaboration are to develop high-quality spatial data sets of environmental variables, and deliver the data sets and associated analyses to local, state and federal end-user groups. These data can be linked spatially and temporally to public health data, such as mortality and disease morbidity, for further analysis and decision making. Three daily environmental data sets have been developed for the conterminous U.S. on different spatial resolutions for the time period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be made available to public health professionals, researchers and the general public through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer reviewed publications. To date, two of the data sets have been released to the public in CDC WONDER, Daily Air Temperature and Heat Index for years 1979-2010, and Daily Fine Particulate Matter (PM2.5) air quality measures for years 2003-2008. These data in CDC WONDER can be aggregated to the county-level, state-level, or regional-level as per users need and downloaded in tabular, graphical, and map formats. The summary statistical output are available to web and app developers via the WONDER Application Programming Interface (API). The linkage of these data with the CDC WONDER system provides a significant addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER online system. It also substantially expands public access to NASA environmental data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗

Agricultural Burning and Air Quality over Northern India: A Synergistic Analysis Using NASA's A-Train Satellite Data and Ground Measurements

In the recent years, New Delhi, the capital city of India, has ranked among the most polluted cities in the world regarding its air quality related to the submicron Particulate Matter (PM(sub 2.5)). Using NASA's A-train satellite data (MODIS, OMI, and CALIOP), ground-level PM2.5 measured in New Delhi (2013-2016), and back-trajectory calculations, we show that the PM(sub 2.5). over New Delhi is strongly affected by the agricultural fires in the northwestern Indian states of Punjab and Haryana during the post-monsoon season (October and November). The mass concentration of PM2.5 escalates from ~50 μg m(exp -3) measured prior to the onset of residue burning in early October to as high as 300 μg m(exp -3) (24-hour averaged, 7- day running mean) during the peak burning period in early November. A linear regression analysis reveals that the variations in PM(sub 2.5) over New Delhi can be attributed to the concurrent changes in the satellite retrievals of fire counts and aerosols over the crop burning area. The back-trajectory analysis shows that most clusters (> 80%) of the northwesterly flow near the ground intercepted the crop burning region before arriving at the receptor location in New Delhi; this further corroborates the transport patterns inferred from the satellite data. A 15-year long satellite record (2002-2016) reveals an increasing trend in agricultural fires (~617 per year) and aerosol loading (0.031 and 0.04 per year in aerosol optical depth and UV aerosol index) in November. Increasing levels of crop residue burning and resulting particulate matter pollution at an alarming rate over northern India is a pressing concern demanding corrective measures to substantially reduce or completely diminish the crop burning through an effective residue management system.

Crop Residue Fires↗

Evaluation of Aerosol Data Assimilation and Forecasts in the NASA GEOS Model during the ASIA-AQ Campaign

Fine particulate matter (PM2.5) poses significant risks to human health and the environment by penetrating the lungs and causing respiratory and cardiovascular diseases, making it crucial to understand its sources and behavior for effective air quality management. The Goddard Earth Observing System (GEOS) Forward Processing (FP) system model, operated by the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center, provides real-time weather and aerosol analyses and forecasts. In addition to meteorological data assimilation, the GEOS-FP system also assimilates aerosol using Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Aerosol Robotic Network (AERONET) AOD data. In this study, the aerosol data assimilation and forecasts performance of the GEOS-FP model were evaluated for predicting PM2.5 in Korea using observations from the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. The ASIA-AQ campaign, an international collaborative field study initiative, aims to enhance understanding of local air quality issues and address common challenges in interpreting satellite data and air quality modeling. Conducted in South Korea from February 15 to March 13, 2024, during the high PM2.5 concentration winter season, this campaign provided extensive airborne and ground observations for intensive analysis of PM2.5 model simulations. We demonstrate how the assimilation runs and the forecasting performance of PM2.5 at 24-hour and 48-hour intervals vary. Additionally, we analyzed the differences and characteristics of PM2.5 composition in cases of long-range transport and local emissions. Using ASIA-AQ airborne data, we also examined the vertical profile of fine particulate matter. Through the intensive observations of this campaign, the GEOS model was assessed over South Korea using both in situ and airborne measurements to establish a baseline and identify priorities for future development.

Seunghee Lee↗

Enhanced Monitoring and Forecasting of South Asian Air Quality Episodes with Multi-Sensor Satellite Products and Dispersion Modeling

Air pollution and particulates represent a serious environmental, public health, and overarching societal concern in the Hindu Kush Himalaya (HKH) region of south-central Asia, especially during the boreal winter and spring months. Frequent contributors to poor air quality of the region include dust and particulate matter transport from the Middle East region and western India, persistent nocturnal fog and smog during the stable dry monsoon months, and biomass burning during the pre-monsoon months of boreal spring. Nocturnal and multi-day persistent stable fog and smog events can occur during the stable conditions of the dry monsoon months that lead to hazardous visibility reductions (e.g., at major airports such as Delhi, India)and poor air quality, particularly in urban corridors.Our project goal is therefore to design and implement a robust air quality and chemistry observation and modeling system using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. This system effectively assimilates aerosol and trace gas retrievals from geostationary and polar-orbiting satellites to advance the monitoring and prediction capabilities of air quality and visibility reductions throughout the HKH region. For this presentation, we highlight several[multi-spectral] geostationary satellite products and dispersion modeling capabilities being developed and implemented for improved situational awareness and forecasting of air quality episodes.Launched in December 2018, the Advanced Meteorological Imager (AMI) aboard the Geostationary-Korean Multi-Purpose Satellite-2A (GEO-KOMPSAT-2A, or GK2A) provides 16 channels of multi-spectral information similar to the U.S. GOES-16/17 satellites. Proven community recipes for generating multi-spectral Red-Green-Blue (RGB) composite products to detect specific meteorological phenomena are applied to the AMI data for the HKH region. We implemented four such RGB products consisting of truecolor with Rayleigh correction to aid in smoke detection; dust RGB for monitoring larger particulate matter; nighttime microphysics for fog/smog detection;and natural color fire RGB and the shortwave 3.8 micron channel for fire hot-spot detection.We additionally configured HYSPLIT for dust/sand dispersion and concentration forecasts over HKH. The HYSPLIT dispersion simulations are initially being conducted with two different methodologies: (1) dust/sand lofting based on initializing plume releases from visual inspection of the dust RGB imagery; and (2) dust/sand release and dispersion using the internal HYSPLIT algorithm that determines lofting from input wind speeds and prescribed land use. The goal is to develop a near real-time HYSPLIT modeling solution for routinely simulating the transport and dispersion of dust plumes across the HKH region. This presentation illustrates these products and capabilities for various use cases from the 2019 to 2021 period, highlighting a particularly unhealthy episode during late March 2021 across Nepal.

Remote Sensing↗

Propulsion system filter sizing considerations for the Galileo spacecraft

Filtration capacity of the Galileo propulsion system has been investigated. Ground testing of flight spare components has been conducted to determine the representative number and size distribution of particulate matter collected in flow tests. For these tests and for filter qualification tests, a number of effects were examined. The influence of gravitational particle settling on ground test results vs the flight environment was considered. Centrifugal effects inherent in the test apparatus and/or the propulsion system could have an influence. Variability among particle sizing techniques was explored. The influence of size distribution, particle shape, and density in the choice of a particulate test material was studied. Characteristics for AC Coarse Dust (an industry standard filter test media), microscopic polymer beads, and aluminum oxide particulate test matter are listed. Filtration tests were conducted using AC Coarse Dust and mixtures containing components of AC Coarse Dust. These results are expected to be useful data for filter sizing of future spacecraft.

Jan, Darrell L.↗