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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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7 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Application of Aerosol Hygroscopicity Measured at the Atmospheric Radiation Measurement Program's Southern Great Plains Site to Examine Composition and Evolution

A Differential Mobility Analyzer/Tandem Differential Mobility Analyzer (DMA/TDMA) was used to measure submicron aerosol size distributions, hygroscopicity, and occasionally volatility during the May 2003 Aerosol Intensive Operational Period (IOP) at the Central Facility of the Atmospheric Radiation Measurement Program's Southern Great Plains (ARM SGP) site. Hygroscopic growth factor distributions for particles at eight dry diameters ranging from 0.012 micrometers to 0.600 micrometers were measured throughout the study. For a subset of particle sizes, more detailed measurements were occasionally made in which the relative humidity or temperature to which the aerosol was exposed was varied over a wide range. These measurements, in conjunction with backtrajectory clustering, were used to infer aerosol composition and to gain insight into the processes responsible for evolution. The hygroscopic growth of both the smallest and largest particles analyzed was typically less than that of particles with dry diameters of about 0.100 micrometers. It is speculated that condensation of secondary organic aerosol on nucleation mode particles is largely responsible for the minimal hygroscopic growth observed at the smallest sizes considered. Growth factor distributions of the largest particles characterized typically contained a nonhygroscopic mode believed to be composed primarily of dust. A model was developed to characterize the hygroscopic properties of particles within a size distribution mode through analysis of the fixed size hygroscopic growth measurements. The performance of this model was quantified through comparison of the measured fixed size hygroscopic growth factor distributions with those simulated through convolution of the size-resolved concentration contributed by each of the size modes and the mode-resolved hygroscopicity. This transformation from sizeresolved hygroscopicity to mode-resolved hygroscopicity facilitated examination of changes in the hygroscopic properties of particles within a size distribution mode that accompanied changes in the sizes of those particles. This model was used to examine three specific cases in which the sampled aerosol evolved slowly over a period of hours or days.

Gasparini, Roberto↗
DOE OSTI2023

NCSU HTDMA data

NCSU HTDMA data Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Humidified Tandem Differential Mobility Analyzer; 2 Differential Mobility Analyzers (DMA1 and DMA2). Start Date: 2022-06-01 End Date: 2022-09-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU HTDMA was operated at a sheath-to-sample flow ratio of 5:1 L min−1. The HTDMA was configured to measure hygroscopic growth factors of dry particles with mobility diameters of D = 15, 20, 30, 40, and 50 nm at RH ~ 70%. A complete cycle for all diameters took ~30 minutes. A sample line brought aerosol inside the trailer at 2.5 L min-1, where it was distributed between NCSU RDMA (1.5 L min-1) and NCSU HTDMA (1 L min-1) lines. The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. The sample line entered DMA1 (operated as an electrostatic classifier). Monodisperse particles with certain fractions were humidified with temperature controlled Nafion membrane immersed in water before entering DMA2 (operated in scanning mobility particle sizer). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Particle Flux Measurements during TRACER (TRACER PFM) (Field Campaign Report)

The purpose of this campaign was to deploy an instrument payload collocated with a suite of in situ and remote-sensing aerosol instruments at the urban site at the La Porte, Texas Municipal Airport during the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) in Houston, Texas. The payload was designed to characterize the physicochemical properties, mixing state, and size-resolved vertical fluxes of aerosols. Deployed aerosol instruments associated with the flux measurements included three condensation particle counters (CPCs) with different lower cutoff diameters ( D > 2.5 nm, D > 10 nm, and D > 40 nm), a single-particle soot photometer (SP2) measuring refractory black carbon, and a portable optical particle spectrometer (POPS) measuring the optical size distribution (~180 nm < D < ~5000 nm). A 10-m flux tower hosted a sonic anemometer (SONIC) for vertical velocity measurements. In addition, a humidified tandem differential mobility analyzer (HTDMA) was deployed to measure the growth factors and hygroscopicity parameter of 15-50 nm-sized particles in order to constrain the composition of compounds responsible for modal aerosol growth during new particle formation/growth events. Finally, a radial differential mobility analyzer (RDMA) was deployed to extend the size distribution measurement to 5 nm.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Understanding and Improving Model Representation of Aerosol Optical Properties for a Chinese Haze Event Measured During KORUS-AQ

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM2.5, often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m2 g−1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm−3 in the model vs. observed average of 1.5 g cm−3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

Pablo E. Saide↗
DOE OSTI2024

62°S Witnesses the Transition of Boundary Layer Marine Aerosol Pattern Over the Southern Ocean (50°S–68°S, 63°E– 150°E) During the Spring and Summer: Results From MARCUS (I)

The Atmospheric Radiation Measurement Mobile Facility-2 was installed onboard the research vessel Aurora Australis to measure aerosol properties during the 2017-2018 Measurement of Aerosols, Radiation, and CloUds over the pristine Southern ocean (MARCUS) Experiment, providing unique data on aerosols latitudinal and seasonal variation, including south of 60 degrees S where previous observations are scarce. Data from a Cloud Condensation Nuclei (CCN) counter and Ultra-High-Sensitivity Aerosol Spectrometer show that both the number concentration (N-CCN) and size distribution of CCN-active aerosols, with diameters (D) between 60 nm < D < 1,000 nm are different over the North Southern Ocean (NSO) (50 degrees S-60 degrees S) and the South Southern Ocean (SSO) (62 degrees S-68 degrees S). The average NSO N-CCN at 0.2% and 0.5% supersaturation were 28% and 49% less than that over the SSO. This increase of CCN over the SSO is caused by the increase of aerosols with 60 nm < D < 200 nm, consistent with calculations of Aerosol Scattering Angstrom Exponents derived from a nephelometer. Aerosol hygroscopicity growth factor measured by the Hygroscopic Tandem Differential Mobility Analyzer stayed close to 1.41 for aerosols with 50 nm < D < 250 nm over the SSO, but increased from 1.30 to 1.67 over the NSO, indicating different chemical compositions. Both CCN and Ice Nucleating Particles (INPs) showed a stronger variation with season than with latitude. The variation of heat-labile and presumably proteinacous INPs suggests an increase of ice nucleating-active microbes in summer.

Niu, Qing↗
NASA NTRS2000

Measurements and Modeling of Aerosol Absorption and Single Scattering Albedo at Ambient Relative Hum

Uncertainties in the aerosol single scattering albedo have been identified to be an important source of errors in current large-scale model estimates of the direct aerosol radiative forcing of climate. A number of investigators have obtained estimates of the single scattering albedo from a variety of remote sensing and in situ measurements during aerosol field experiments. During the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX, 1996) for example, estimates of the aerosol single scattering albedo were obtained (1) as a best-fit parameter in comparing radiative flux changes measured by airborne pyranometer to those computed from independently measured aerosol properties; (2) from estimates of the aerosol complex index of refraction derived using a combination of airborne sunphotometer, lidar backscatter and in situ size distribution measurements; and (3) from airborne measurements of aerosol scattering and absorption using nephelometers and absorption photometers. In this paper, we briefly compare the results of the latter two methods for two TARFOX case studies, since those techniques provide height-resolved information about the aerosol single scattering albedo. Estimates of the aerosol single scattering albedo from nephelometer and absorption photometer measurements require knowledge of the scattering and absorption humidification (i.e., the increase in these properties in response to an increase in ambient relative humidity), since both measurements are usually carried out at a relative humidity different from the ambient atmosphere. In principle, the scattering humidification factor can be measured, but there is currently no technique widely available to measure the absorption of an aerosol sample as a function of relative humidity. Frequently, for lack of better knowledge, the absorption humidification is assumed to be unity (meaning that there is no change in aerosol absorption due to an increase in ambient relative humidity). This assumption then enters the estimate of the single scattering albedo at ambient relative humidity. To investigate the validity of this assumption we have carried out modeling studies of the absorption humidification factor, assuming that the aerosols contain an insoluble soot core and a coating which determines its hygroscopic growth behavior. The aerosol optical properties are then computed on the basis of the shell/core particle morphology using a Mie-code for concentric shells. From basic physical principles, it is conceivable that aerosol absorption increases when an atmospheric aerosol particle collects a non-absorbing shell, since the soot core is then exposed to an increased (focused) electric field strength. Indeed, our preliminary modeling studies show that the absorption of an atmospheric aerosol particle composed of a soot core and an aqueous sulfuric acid shell may increase by a factor of 50% due to a change in ambient relative humidity from 30 to 95%. We will show how this increased absorption is a function of the initial particle size and soot mass fraction.

Redemann, J.↗
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↗