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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

High Lapse Rates in AIRS Retrieved Temperatures in Cold Air Outbreaks

The Atmospheric Infrared Sounder (AIRS) experiment, on NASA's Aqua spacecraft, uses a combination of infrared and microwave observations to retrieve cloud and surface properties, plus temperature and water vapor profiles comparable to radiosondes throughout the troposphere, for cloud cover up to 70%. The high spectral resolution of AIRS provides sensitivity to important information about the near-surface atmosphere and underlying surface. A preliminary analysis of AIRS temperature retrievals taken during January 2003 reveals extensive areas of superadiabatic lapse rates in the lowest kilometer of the atmosphere. These areas are found predominantly east of North America over the Gulf Stream, and, off East Asia over the Kuroshio Current. Accompanying the high lapse rates are low air temperatures, large sea-air temperature differences, and low relative humidities. Imagery from a Visible / Near Infrared instrument on the AIRS experiment shows accompanying clouds. These lines of evidence all point to shallow convection in the bottom layer of a cold air mass overlying warm water, with overturning driven by heat flow from ocean to atmosphere. An examination of operational radiosondes at six coastal stations in Japan shows AIRS to be oversensitive to lower tropospheric lapse rates due to systematically warm near-surface air temperatures. The bias in near-surface air temperature is seen to be independent of sea surface temperature, however. AIRS is therefore sensitive to air-sea temperature difference, but with a warm atmospheric bias. A regression fit to radiosondes is used to correct AIRS near-surface retrieved temperatures, and thereby obtain an estimate of the true atmosphere-ocean thermal contrast in five subtropical regions across the north Pacific. Moving eastward, we show a systematic shift in this air-sea temperature differences toward more isothermal conditions. These results, while preliminary, have implications for our understanding of heat flow from ocean to atmosphere. We anticipate future improvements in the AIRS retrieval algorithm will lead to improved understanding of the exchange of sensible and latent heat from ocean to atmosphere, and more realistic near-surface lapse rates.

cold air outbreak↗
NASA NTRS1971

Embryogenesis in 100% O2 at reduced pressure.

Fertile chicken eggs were incubated in an altitude chamber in a near 100% O2 atmosphere at 225 torr. Both N2 and CO2 were kept under 0.5%. Temperature was a standard 37.5 C but a high relative humidity of 90% was required to prevent dehydration. In ten trials involving 382 eggs, hatchability averaged 21% of controls and weight of chicks was 11% less than controls, but embryo mortality was distributed similarly. Low pressure per se and small differences in O2 tension may have affected the results, but similarities to incubation in 21% O2-79% He call attention to absence of nitrogen as a possible explanation.

Weiss, H. S.↗
NASA NTRS2017

The Modern Near-Surface Martian Climate: A Review of In-Situ Meteorological Data from Viking to Curiosity

We analyze the complete set of in-situ meteorological data obtained from the Viking landers in the 1970s to todays Curiosity rover to review our understanding of the modern near-surface climate of Mars, with focus on the dust, CO2 and H2O cycles and their impact on the radiative and thermodynamic conditions near the surface. In particular, we provide values of the highest confidence possible for atmospheric opacity, atmospheric pressure, near-surface air temperature, ground temperature, near-surface wind speed and direction, and near-surface air relative humidity and water vapor content. Then, we study the diurnal, seasonal and interannual variability of these quantities over a span of more than twenty Martian years. Finally, we propose measurements to improve our understanding of the Martian dust and H2O cycles, and discuss the potential for liquid water formation under Mars present day conditions and its implications for future Mars missions.

Martinez, G. M.↗
NASA NTRS2020

Increased Likelihood of Appreciable Afternoon Rainfall Over Wetter or Drier Soils Dependent Upon atmospheric Dynamic Influence

The relationship between morning soil moisture and afternoon rainfall persists as an important yet unresolved challenge in land‐atmosphere interaction study, complicated in part by atmospheric influence. Here, we address this relationship by utilizing NASA's satellite soil moisture and precipitation data for the warm season (June–September) of 2015–2019 over Northern Hemisphere land (0–60°N). Raining days are partitioned into low, medium, and high regimes of atmospheric water vapor convergence. Under the low convergence regime, afternoon rainfall is more likely to occur over wetter soils or higher relative humidity; for days with high moisture convergence, occurrence favors drier soils or lower relative humidity. For each regime, afternoon rainfall occurrence favors warmer morning soil or air temperature. These conclusions are not affected by the threshold magnitude utilized to identify afternoon rainfall events by accumulation, but the threshold value does affect the soil moisture (or relative humidity)‐precipitation relationship when convergence regimes are not considered.

J. Welty↗
NASA NTRS2003

Intercomparison of Latent Heat Fluxes Over Global Oceans

Turbulent fluxes of momentum, moisture, and heat at the air-sea interface are essential for climate studies. Version 2 Goddard Satellite-based Surface Turbulent Fluxes (GSSTF2) has been derived from the Special Sensor Microwave/Imager (SSM/I) radiance measurements. This dataset, covering the period July 1987-December 2000 over global oceans, has a spatial resolution of 1 deg x 1 deg lat-long and a temporal resolution of 1 day. Turbulent fluxes are derived from the SSM/I surface winds and surface air humidity, as well as the 2-m air and sea surface temperatures (SST) of the NCEP/NCAR reanalysis, using a bulk aerodynamic algorithm based on the surface layer similarity theory. The GSSTF2 bulk flux model, and retrieved daily wind stress, latent heat flux, wind speed, and surface air humidity validate well with ship observations of ten field experiments over the tropical and midlatitude oceans during 1991-99. The global distributions of 1988-2000 annual- and seasonal-mean turbulent fluxes show reasonable patterns related to the atmospheric general circulation and seasonal variations. Latent heat fluxes and related input parameters over global oceans during 1992-93 have been compared among GSSTF1 (version 1), GSSTF2, HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data), NCEP/NCAR reanalysis, and one based on COADS (Comprehensive Ocean-Atmosphere Data Set). Our analyses suggest that the GSSTF2 latent heat flux, surface air humidity, surface wind, and SST are quite realistic compared to the other four flux datasets examined. However, significant differences are found among these five flux datasets. The GSSTF2, available at http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/hydrology/hd_gsstf2.O.html, is useful for climate studies.

Chou, Shu-Hsien↗
DOE OSTI2026

Sunlight can turn smoldering pine wood smoke into a glass

Wildfires inject biomass burning organic aerosols (BBOA) into the atmosphere. During their lifetimes of weeks to months, they are exposed to ultraviolet (UV) irradiation. Viscosity and phase behaviour are essential properties for understanding their chemical and climate impacts. Here, we quantify changes in viscosity and phase behavior after UV exposure. After an atmospheric equivalent of 8.7 days of boundary layer UV exposure, BBOA develop a highly viscous (glassy) outer phase with a viscosity at least five orders of magnitude higher than unaged BBOA, which persists up to at least 58% relative humidity. High-resolution mass spectrometry indicates that UV-aging increases oxidation and molecular weight. Using our viscosity results, we predict that UV-aged BBOA are frequently glassy above ~2.5 km and can have viscosities up to eight orders of magnitude higher than unaged particles in some atmospheric regions, which may influence lifetimes of pollutants and brown carbon, and impact stratospheric ozone chemistry.

Golay, Zoe↗
DOE OSTI2023

Vertical Resolution Impacts Explicit Simulation of Deep Convection

Abstract The aggregation of tropical convection greatly influences the mean‐state of the atmosphere, altering humidity distributions, total atmospheric radiative cooling, and cloud amounts. Although studies have demonstrated the sensitivity of convective aggregation to horizontal resolution and domain size, few studies have explored the impact of vertical resolution on convective aggregation. Here, we investigate the impact of vertical resolution on simulations of deep convection and convective aggregation using the System for Atmospheric Modeling convection resolving model. We analyze simulations of tropical radiative‐convective equilibrium with varying vertical levels (32, 64, 128, and 256) across small (100 km), medium (700 km) and large (1,500 km) domains. We demonstrate that relative humidity and cloud fraction decrease with increasing vertical resolution as a result of reduced turbulent mixing. Vertical resolution also influences the occurrence of, onset time, and equilibrium intensity of aggregated convection, and also appears to affect the sensitivity of convective aggregation to domain size. Understanding how simulated convection aggregates, as well as its simulated sensitivity to model formulation, is critical for making and interpreting future predictions of global climate change.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Long-Term Infrasound Sensor Calibration and Characterization

Previous testing has shown that infrasound sensors deployed in the field can exhibit notable deviations from their nominal, lab-based calibrations. These variations may be due to changes in environmental conditions, long-term sensor drift, or other unresolved features. In early 2018, we installed two identical infrasound elements with five infrasound sensors at each element (Chaparral M50A, Chaparral M64LN, CEA/Martec MB2005, CEA/Seismowave MB3a, and Hyperion IFS-5113A). These sensors were accepted or under consideration for use in the International Monitoring System network of the Comprehensive Nuclear-Test-Ban Treaty. Each element had all sensors connected to a single digitizer and port to the atmosphere. We also recorded instrument enclosure air temperature and humidity and external air temperature. Using the MB2005 as the reference, we examine the relative sensor response (both magnitude and phase) as a function of time and frequency and compare it with quarterly laboratory calibrations and environmental conditions. Here, we find that the magnitude response for all sensors exhibits some variability in both the lab and field, with the amplitude variations often >5%. The field-based variations are more severe and occur on both long-term (months) and short-term (hours) timescales. Short-term variability correlates with changes in environmental conditions and is considerable (up to 25%) for the Chaparral M50A and noticeable (∼5%) for the French Alternative Energies and Atomic Energy Commission (CEA) MB3a. Long-term magnitude variability for the Chaparral M50A was up to 50% and does not clearly correlate with environmental conditions. The other sensors show some long-term magnitude offsets, but they have relatively stable responses in the conditions we examined. The MB3a also displays some frequency-dependent magnitude variability and shows a minor dependence on temperature. Phase estimates are stable and near zero for all sensors tested. These results strongly suggest sensor response and variability due to environmental conditions should be considered in future infrasound data interpretation and sensor selection and development.

Fee, David↗
DOE OSTI2025

NCAR-RAL Surface Hydrometeorological Observation Network Data for LASSO-CACTI Overview Paper

This data set contains the 15 minute resolution surface meteorology and soils data from the 15 NCAR/RAL weather stations that were operated around central Argentina during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations) Extended Observing Period (EOP). Data providence, citation, and acknowledgement This ARM data set is a copy of v1.0 of the NCAR data set obtained in June 2024 from https://doi.org/10.26023/KW8Z-F2WX-H0Y. The citation for the original data source is: Gochis, D., et al. 2019. NCAR-RAL Surface Hydrometeorological Observation Network Data. Version 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/KW8Z-F2WX-H0Y Accessed June 2024. In addition to the citation reference and any other acknowledgements, please acknowledge NCAR/EOL in your publications with text such as: “Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/”

air temperature↗
NASA NTRSDate not supplied

Simultaneous lidar profiling of water vapor, aerosol, and wind over the eastern Pacific and implications for observational challenges on clouds, circulation, and climate sensitivity

Moist convective processes and related circulations are key components of the Earth’s climate system. Improving our understanding of moisture and cloud processes over oceans is especially challenging due to observational limitations, but also important due to the large radiative effects of cloud over ocean as well as the ties to local and global-scale circulations. A unique dataset for addressing these topics was collected over 5 flights with the NASA HALO (water vapor DIAL and aerosol HSRL) and DAWN (Doppler wind) lidar systems onboard the NASA DC-8 aircraft during the spring 2019 ADM-Aeolus Cal/Val test flight campaign. High-resolution water vapor, aerosol/cloud, and wind profiles were simultaneously collected and complimented with in situ high-resolution dropsonde measurements of temperature, relative humidity, and wind profiles. Airborne lidar measurements of these key variables captured both large-scale spatial variability across different cloud and atmospheric conditions as well as finer features, providing insight into processes from large-scale circulations down to aerosol/cloud interactions. The 5 flights spanned the northeast Pacific and southwest U.S. from 6 N to 52 N and 112 W to 157 W and captured several features of interest including moist layers from the ascending region of the Hadley circulation, very dry layers above midlatitude marine stratocumulus and cloud-free planetary boundary layers, and cloud top height and spatial variability. High covariance of aerosol and water vapor in the free troposphere was also observed for the first time. Preliminary analysis of these data sets will be presented as they apply to clouds and circulations, supplemented by model reanalysis to inform how regional water vapor structure and large-scale motion may contribute to observed shallow cloud formations and other meteorological processes that underpin our current understanding of how these state variables couple to impact the Earth’s weather and climate systems. The potential of complementary measurements in future field campaigns will also be mentioned.

Brian James Carroll↗
DOE OSTI2022

Thermodynamic Model and Initial Experimental Investigation of Air Dehumidification through Electrically Charged Vapor Capturing Electrostatic Droplets

The removal of water vapor from the air to reduce relative humidity is a well known indoor environmental comfort requirement. Common dehumidification approaches require a substantial amount of energy and usually involve the cooling of atmospheric humid air below its dew point or the use of absorbent/adsorbent materials to extract water vapor out of the air. More recently, researchers investigated the effect of electrostatic forces for enhancing water vapor condensation with the goal to reduce the energy consumption associated with dehumidification. However, the studies are limited, and there is a lack of correlations that can predict the dehumidification rate. In this thesis, a broad theoretical investigation to study the electrostatically enhanced condensation processes was carried out. These processes consist of the use of highly charged particles, preferably highly charged water droplets to attract polar water vapor molecules to their surfaces and promote condensation, a phenomenon known as dielectrophoresis. The electrical charge promotes the reduction of the vapor pressure on the droplets' surface with respect to the saturated pressure predicted by the Kelvin equation on curved surfaces and, consequently, the equilibrium between evaporation and condensation is shifted towards condensation. This investigation resulted in the development of a thermodynamics model, which was able to predict an effective size range of the charged droplets for optimal dehumidification, under ideal conditions. The range resulted in about 2 to 4 m in diameter, while the electrical charge was kept to the maximum limit predicted by the Rayleigh model. A sensitivity analysis on the variation of the size and the charge of the charged droplets was also performed. In terms of dehumidification rates, when six electrospray heads, i.e. the maximum number of heads tested in the experimental campaign, were considered, the model predicted very limited rates, way lower than the target of this research, i.e. a dehumidification rate in terms of relative humidity of 5 % with an air flow rate of 5 cfm. While ways to increase this rate existed, their implementation proved difficult for this initial investigation. According to the requirements predicted by the model, the use of electrosprays appeared the most suitable solution for the production of small but highly charged droplets. The electrospray features and operational modes were studied in detail and an electrospray assembly was designed to be tested in this initial experimental investigation. For this initial investigation, an experimental system was designed and built to validate the thermodynamics model and with the goal to achieve a dehumidification rate of 5 % in terms of relative humidity with an air flow rate of 5 cfm. The experimental system consisted of a wind tunnel test apparatus, dew point sensors, thermocouples for temperature measurements, pressure sensors and other devices. The experimental system was equipped with a computerized data acquisition and storage system. The system was suitable to evaluate the air water content differential before and after the test section where the electrospray heads were installed. The air water content differential was evaluated in terms of the ∆ω/ω_1 ratio, to eliminate the dependence on the dry bulb temperature along the test apparatus. This work presented initial experimental data for electrostatically enhanced dehumidification processes. Working parameters, such as air and water flow rates, high voltage potentials and polarity, deionized water types with different electrical conductivity, were varied to find the best combination for an improved dehumidification. With the set up used and the conditions considered, it was never possible to achieve a 5 % dehumidification rate with 5 cfm. In general, the dehumidification rate was always limited and lower than 1 % for all the air flow rates considered and mainly within the uncertainty of the dew point sensors. These results confirmed the already limited predictions of the thermodynamics model, for ideal conditions and the interesting and promising results obtained in some experimental investigations available in the open literature were not achievable in this thesis. The more probable reasons were the higher air flow rates considered and the complete absence of the use of cooling power, which was mainly implemented to facilitate the vapor condensation.

Morcelli, Stefano↗
DOE OSTI2023

Best Practices for Body Temperature Measurement with Infrared Thermography: External Factors Affecting Accuracy

Infrared thermographs (IRTs) are commonly used during disease pandemics to screen individuals with elevated body temperature (EBT). To address the limited research on external factors affecting IRT accuracy, we conducted benchtop measurements and computer simulations with two IRTs, with or without an external temperature reference source (ETRS) for temperature compensation. The combination of an IRT and an ETRS forms a screening thermograph (ST). We investigated the effects of viewing angle (θ, 0–75°), ETRS set temperature (T ETRS , 30–40 °C), ambient temperature (T atm , 18–32 °C), relative humidity (RH, 15–80%), and working distance (d, 0.4–2.8 m). We discovered that STs exhibited higher accuracy compared to IRTs alone. Across the tested ranges of T atm and RH, both IRTs exhibited absolute measurement errors of less than 0.97 °C, while both STs maintained absolute measurement errors of less than 0.12 °C. The optimal T ETRS for EBT detection was 36–37 °C. When θ was below 30°, the two STs underestimated calibration source (CS) temperature (T CS ) of less than 0.05 °C. The computer simulations showed absolute temperature differences of up to 0.28 °C and 0.04 °C between estimated and theoretical temperatures for IRTs and STs, respectively, considering d of 0.2–3.0 m, T atm of 15–35 °C, and RH of 5–95%. The results highlight the importance of precise calibration and environmental control for reliable temperature readings and suggest proper ranges for these factors, aiming to enhance current standard documents and best practice guidelines. These insights enhance our understanding of IRT performance and their sensitivity to various factors, thereby facilitating the development of best practices for accurate EBT measurement.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impacts of phase state and water content on secondary organic aerosol formation and partitioning (Final Technical Report)

Secondary organic aerosols (SOA) account for a major fraction of particulate matter in the atmosphere, affecting climate, air quality, and public health. SOA formation and evolution are highly complex processes involving both chemical reactions and transport of molecules in air, at particle surfaces, and within particles. The state of the matter, or “phase state,” comprising SOA can vary from a liquid, over an amorphous semi-solid, to a glassy solid, depending on chemical composition, water content, relative humidity (RH), and temperature. The occurrence of glassy and amorphous semi-solid states can pose limitations on the rate of transport of molecules, affecting gas-particle interactions and challenging the treatment of SOA in atmospheric models. The objective of this project was to improve fundamental understanding of the interplay of the phase state of particles and water content on the evolution of SOA formation. We have developed a method to estimate the glass transition temperature (T g ) of organic compounds to predict the phase state and viscosity of SOA. This method has been applied to high resolution mass spectrometry data of various types of SOA, achieving a good agreement with viscosity measurements. In addition, the viscosity estimation method was implemented into a regional model CMAQ to simulate diel and seasonal variations of SOA phase state over the U.S. Applying kinetic multilayer modeling, we analyzed laboratory experiments and ARM field measurements (e.g., HI-SCALE) on kinetic limitations of amine uptake. We have also conducted numerical simulations to estimate equilibration timescales of SOA partitioning. Overall, we have evaluated the impacts of phase state and water content on SOA lifecycle that should contribute to reducing the uncertainty of SOA representation in regional climate and air quality predictions. The project has yielded 17 publications, in which DE-SC0018349 is explicitly acknowledged. Please see the list of publications as below, followed by summary of research activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Hydrochloric acid aerosol and gaseous hydrogen chloride partitioning in a cloud contaminated by solid rocket exhaust

Partitioning of hydrogen chloride between hydrochloric acid aerosol and gaseous HCl in the lower atmosphere was experimentally investigated in a solid rocket exhaust cloud diluted with humid ambient air. Airborne measurements were obtained of gaseous HCl, total HCl, relative humidity and temperature to evaluate the conditions under which aerosol formation occurs in the troposphere in the presence of hygroscopic HCl vapor. Equilibrium predictions of HCl aerosol formation accurately predict the measured HCl partitioning over a range of total HCl concentrations from 0.6 to 16 ppm.

Sebacher, D. I.↗
NASA NTRS1981

Studies on the behavior of ammonia and ammonium salts in the atmosphere (1) - Fractional collection of ammonia gas and particulate ammonium

Methods for the fractional collection of trace amounts of atmospheric ammonia gas and ammonium particles on a two staged glass fiber filter are summarized. A standard glass fiber filter washed with distilled water and dried at 120 to 130 C was used. A second filter was impregnated with a mixture of 3% boric acid and 25% glycerin solution. The blank of glass fiber filters impregnated with a mixture of the above solution was very low for ammonia, i.e. 0.06 micrograms in a filter of 47 mm in diameter. The mean concentrations of ammonia and ammonium in air at Kawasaki, a polluted area, were 7.6 and 2.3 micrograms cu m, and those at Sanriku, an unpolluted area 0.9 and 0.2 micrograms cu m, respectively. Ratios of concentration levels of ammonium to total ammonia in the atmosphere were 0.3 and 0.2 for the polluted and unpolluted areas, respectively. Ammonium salts in air at both areas were not correlated with relative humidity. Variations in time of ammonia concentrations and sources in surrounding areas are also considered.

Kiin, K.↗