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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Cause of a Lower-Tropospheric High-Ozone Layer in Spring Over Hanoi

The ozonesonde observations in Hanoi, Vietnam, over fourteen years since 2004 have confirmed the enhancement in lower tropospheric ozone concentration at about 3 km altitude in the spring season. We investigated the evolution of the ozone enhancement from analysis of meteorological data, backward trajectories, and model sensitivity experiments. In spring, air masses over Hanoi exhibit strong height dependence. At 3km, the high-ozone air masses originate from the land area to the west of Hanoi, while low-ozone air masses below about 1.5 km are from the oceanic area to the east. Above 4 km, the air masses are mostly traced back to the farther west area. The chemical transport model simulations revealed that precursor emissions from biomass burning in the inland Indochina Peninsula have the largest contribution to the lower tropospheric ozone enhancement, which is transported upward and eastward and overhangs the clean air intrusion from the ocean to the east of Hanoi. At this height level, the polluted air has the horizontal extent of about 20 degrees in longitude and latitude. The polluted air observed in Hanoi is transported further east and widely spread over the northern Pacific Ocean.

Hanoi↗
NASA NTRS1984

Biogeochemical cycles: Interactions in global metabolism

A science that chooses the globe as it fundamental biogeophysical unit forces extraordinary conceptual difficulties. The roles of energy flow, matter cycles, carbon cycle, air pollution, global effects, air water interactions are discussed.

Moore, B., III↗
NASA NTRS1987

Physical mechanisms of heat, momentum and turbulence fluxes

In a qualitative way, the physical mechanisms which generate fluxes of heat, momentum, and turbulence in the atmosphere are discussed. This material is presented to acquaint people with the Earth science aspects of turbulence as important processes in the atmosphere. To attempt to describe turbulent fluxes of heat, momentum, and moisture in precise mathematical detail becomes an intractable problem. It is burdened by an eighth order set of equations involving more variables than equations. It is a closure problem which requires complicated assumptions that are not necessarily always satisfied, variable boundary conditions, and sparse observational data. Therefore, we must approach the problem in a simplified manner to obtain any kind of solution involving the variables of shear, stress, and heat, moisture, and momentum fluxes. There are other problems, of course, in which the inclusion of the planetary boundary layer is extremely important. Air pollution studies, air-sea exchanges, mesoscale models, and so on, must account for the planetary layer in very specific terms. Some of the physical mechanisms that are involved in generating fluxes are described.

Theon, John S.↗
NASA NTRS1982

Visibility Studies

Studies conducted by the Environmental Studies Laboratory of the University of Utah embrace investigations of the effects of air pollutants on vegetation; air quality in arid and semi-arid regions surrounding energy developments; and the amount, size and type of particles in the atmosphere. In its visibility studies, the laboratory uses a computer program called RADTMO for Radiative Transfer Models. The program computes the characteristics of scattered radiation in the atmosphere including ozone concentration and aerosol density at various altitudes. Calculations provide information used in determining sky color intensity for visibility modeling under different atmospheric conditions. The laboratory was able to avoid the cost of developing a new computer program by using RADTMO for their calculations.

Source record↗
NASA NTRS2012

A New Retrieval Algorithm for OMI NO2: Tropospheric Results and Comparisons with Measurements and Models

Nitrogen oxides (NOx =NO+NO2) are important atmospheric trace constituents that impact tropospheric air pollution chemistry and air quality. We have developed a new NASA algorithm for the retrieval of stratospheric and tropospheric NO2 vertical column densities using measurements from the nadir-viewing Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. The new products rely on an improved approach to stratospheric NO2 column estimation and stratosphere-troposphere separation and a new monthly NO2 climatology based on the NASA Global Modeling Initiative chemistry-transport model. The retrieval does not rely on daily model profiles, minimizing the influence of a priori information. We evaluate the retrieved tropospheric NO2 columns using surface in situ (e.g., AQS/EPA), ground-based (e.g., DOAS), and airborne measurements (e.g., DISCOVER-AQ). The new, improved OMI tropospheric NO2 product is available at high spatial resolution for the years 200S-present. We believe that this product is valuable for the evaluation of chemistry-transport models, examining the spatial and temporal patterns of NOx emissions, constraining top-down NOx inventories, and for the estimation of NOx lifetimes.

Swartz, W. H.↗
NASA NTRS1974

Airborne survey of major air basins in California

An instrumented aircraft was used to study the chemical and transport properties of air pollution in two major urban centers in California and to survey certain aspects of air pollution within this state. State-of-the-art measurement techniques and sampling procedures are discussed. It is found that meteorological transport mechanisms are better portrayed by vertical pollutant profiles. Airborne measurements define the nature of the mixing layer for atmospheric pollutants. Results show that the pollutants are found to be concentrated in distinct layers up to at least 18,000 feet and the O3 buildup occurring in advected air masses is a result of a continuous photochemical aging of air mass.

Gloria, H. R.↗
NASA NTRS1978

Transport of contaminants in the planetary boundary layer

A planetary boundary layer model is described and used to simulate PBL phenomena including cloud formation and pollution transport in the San Francisco Bay Area. The effect of events in the PBL on air pollution is considered, and governing equations for the average momentum, potential temperature, water vapor mixing ratio, and air contaminants are presented. These equations are derived by integrating the basic equations vertically through the mixed layer. Characteristics of the day selected for simulation are reported, and the results suggest that the diurnally cyclic features of the mesoscale motion, including clouds and air pollution, can be simulated in a readily interpretable way with the model.

Lee, I. Y.↗
NASA NTRS2010

Development of an Instrument Performance Simulation Capability for an Infrared Correlation Radiometer for Troposheric Carbon Monoxide Measurements From Geo

We present the progress toward an analytical performance model of a 2.3 micron infrared correlation radiometer (IRCRg) prototype subsystem for a future geostationary space-borne instrument. The prototype is designed specifically to measure carbon monoxide (CO) from geostationary orbit. NASA's Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission, one of the United States Earth Science and Applications Decadal Survey missions, specifies the use of infrared correlation radiometry to measure CO in two spectral regions for this mission. GEO-CAPE will use the robust IRCR measurement technique at geostationary orbit, nearly 50 times farther away than the Terra/MOPITT orbit, to determine hourly changes in CO across a continental domain. The abundance of CO in Earth's troposphere directly affects the concentration of hydroxyl, which regulates the lifetimes of many tropospheric pollutants. In addition, CO is a precursor to ozone formation; CO is used as a tracer to study the transport of global and regional pollutants; and CO is used as an indicator of both natural and anthropogenic air pollution sources and sinks. We have structured our development project to enable rapid evaluation of future spaceborne instrument designs. The project is part of NASA's Instrument Incubator Program. We describe the architecture of the performance model and the planned evaluation of the performance model using laboratory test data.

OsowskiNeil, Doreen↗
NASA NTRS2021

Communicating Respiratory Health Risk Among Children using a Global Air Quality Index

Air pollution poses a serious threat to children’s respiratory health around the world. Satellite remote-sensing technology and air quality models can provide pollution data on a global scale, necessary for riskcommunication efforts in regions without ground-based monitoring networks. Several large centers, including NASA, produce global pollution forecasts that may be used alongside air quality indices to communicate local, daily risk information to the public. Here we present a health-based, globally applicable air quality index developed specifically to reflect the respiratory health risks among children exposed to elevated outdoor air pollution. Additive, excess-risk air quality indices were developed using 51 different coefficients derived from time-series health studies evaluating the impacts of ambient fine particulate matter, nitrogen dioxide, and ozone on children's respiratory morbidity outcomes. A total of four indices were created which varied based on whether or not the underlying studies controlled for co-pollutants and in the adjustment of excess risks of individual pollutants. Combined with historical estimates of air pollution provided globally at a 25x25 km2 spatial resolution from the NASA's Goddard Earth Observing System composition forecast (GEOS-CF) model, each of these indices were examined in a global sample of 664 small and 140 large cities for study year 2017. Adjusted indices presented the most normal distributions of locally-scaled index values, which has been shown to improve associations with health risks, while indices based on coefficients controlling for co-pollutants had little effect on index performance. We provide the steps and resources need to apply our final adjusted index at the local level using freely-available forecasting data from the GEOS-CF model, which can provide risk communication information for cities around the world to better inform individual behavior modification to best protect children's respiratory health.

Air Qualilty↗
NASA NTRS1977

Characterization of terrestrial service environments - The simultaneous occurrence of combined conditions of solar insolation and climatic variables

Computational methods for occurrences of combined environmental and pollution variables are compared. General statistical data and diurnal statistics on 24 environmental variables are treated. Combinations of variables dealt with include: air temperature, relative humidity, wind speed, total insolation; air temperature and weather event (rain, fog); air pollutant and weather event; wind speed, wind direction, and weather event; air temperature, total insolation, and weather event; air temperature, relative humidity, wind speed, computed direct insolation levels; air temperature, relative humidity, air pollution.

Thomas, R. E.↗
NASA NTRSDate not supplied

Using Machine Learning to Estimate Surface-Level SO2 Concentrations from Satellite-Based Measurements

Sulfur dioxide (SO2) is a criteria air pollutant due to its contributions to aerosol formation, rainfall acidification, and harm to human health. The placement of air quality monitoring sites is typically biased towards urban areas, leaving large areas with very limited monitoring data. The Ozone Monitoring Instrument (OMI) has been used to provide estimates of SO2 vertical column densities (VCDs) globally at spatial resolution of 10s of kms once per day. OMI SO2 VCDs have been previously used to estimate surface SO2 concentrations using chemical transport model (CTM) simulations. The CTMs use estimated emissions and assimilated meteorological data, and simulate the chemical and physical processes that determine the vertical profile of SO2, which can be used to derive a ratio between the surface concentrations and VCDs. These models are complex, computationally expensive, and have large uncertainties in the simulated surface-to-VCD ratio due to biases in emissions and relatively coarse resolution. Machine learning techniques are comparatively easier to use, much less computationally expensive to use after training, and can produce more accurate estimations of surface concentrations than the CTM-based method. The interpretation of machine learning models often poses challenges, and in some cases, non-physical variables unrelated to SO2 are used as predictors. In this work, we create an artificial neural network (ANN) to relate OMI retrievals and archived GEOS-FP boundary layer heights to surface SO2 concentrations from the ChinaHighAirPollutants ChinaHighSO2 dataset (CHAP; Wei et al., 2023) on a seasonal average timescale from 2013-2018. Our model only utilizes five variables that are directly relevant to the satellite retrieval, lifetime, and spatial distribution of SO2. The model was trained on 16 seasons (four of each) with independent validation (one of each season) and testing datasets (one of each season) to avoid overfitting. Our ANN generates surface SO2 concentrations that are sensitive (slope = 0.51) and consistent (r = 0.74) with the CHAP data, but are underpredicted by an average of 1.2 ppbv with a mean absolute error of 2.2 ppbv. These results are better than recent studies utilizing the CTM method. To our knowledge, this is the best performing machine learning model that only uses physical variables to predict surface SO2. Our work demonstrates that a carefully constructed, simple ML model can accurately estimate surface-based SO2 concentrations from satellite VCD measurements, and this technique has future promise to expend to newer, higher resolution satellites and other air pollutants.

SO2, air quality, OMI, machine learning↗
NASA NTRS1974

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 8: Atmosphere

The economic value of an ERS system in the resource area of atmosphere is determined. Benefits which arise from air pollution and cloud observations correlated to ground stations are discussed along with cost savings associated with air pollution monitoring by satellite. Social benefits due to more precise knowledge of the effects of pollution are presented.

Miles, R.↗
NASA NTRS2007

Regional Aerosol Optical Properties and Radiative Impact of the Extreme Smoke Event in the European Arctic in Spring 2006

In spring 2006 a special meteorological situation occurred in the European Arctic region giving record high levels of air pollution. The synoptic situation resulted in extensive transport of pollution predominantly from agricultural fires in Eastern Europe into the Arctic region and record high air-pollution levels were measured at the Zeppelin observatory at Ni-Alesun(78deg 54'N, 11deg 53'E) in the period from 25 April to 12 May. In the present study we investigate the optical properties of the aerosols from this extreme event and we estimate the radiative forcing of this episode. We examine the aerosol optical properties from the source region and into the European Arctic and explore the evolution of the episode and the changes in the optical properties. A number of sites in Eastern Europe, Northern Scandinavia and Svalbard are included in the study. In addition to AOD measurements, we explored lidar measurements from Minsk, ALOMAR (Arctic Lidar Observatory for Middle Atmosphere Research at Andenes) and Ny-Alesund. For the AERONET sites included (Minsk, Toravere, Hornsund) we have further studied the evolution of the aerosol size. Importantly, at Svalbard it is consistency between the AERONET measurements and calculations of single scattering albedo based on aerosol chemical composition. We have found strong agreement between the satellite dally MODIS AOD and the ground-based AOD observations. This agreement is crucial for the radiative forcing calculations. We calculate a strong negative radiative forcing for the most polluted days employing the analysed ground based data, MODIS AOD and a multi-stream model for radiative transfer of solar radiation.

Lund Myhre, C.↗
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 NTRS2024

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity↗
NASA NTRS1979

Electron Spectroscopy for Chemical Analysis (ESCA) study of atmospheric particles

The results of analyses by ESCA (Electron Spectroscopy for Chemical Analysis) on several Nuclepore filters which were exposed during air pollution studies are presented along with correlative measurements by Neutron Activation Analysis and Scanning Electron Microscopy. Samples were exposed during air pollution studies at Norfolk, Virginia and the NASA Kennedy Space Center (KSC). It was demonstrated that with the ESCA technique it was possible to identify the chemical (bonding) state of elements contained in the atmospheric particulate matter collected on Nuclepore filters. Sulfur, nitrogen, mercury, chlorine, alkali, and alkaline earth metal species were identified in the Norfolk samples. ESCA binding energy data for aluminum indicated that three chemically different types of aluminum are present in the launch and background samples from NASA-KSC.

Dillard, J. G.↗
NASA NTRS2021

Global Impact of COVID-19 Restrictions on the Atmospheric Concentrations of Nitrogen Dioxide and Ozone

Social-distancing to combat the COVID-19 pandemic has led to widespread reductions in air pollutant emissions. Quantifying these changes requires a business-as-usual counterfactual that accounts for the synoptic and seasonal variability of air pollutants. We use a machine learning algorithm driven by information from the NASA GEOS-CF model to assess changes in nitrogen dioxide (NO2) and ozone (O3) at 5,756 observation sites in countries from January through June 2020. Reductions in NO2 coincide with timing and intensity of COVID-19 restrictions, ranging from 60% in severely affected cities (e.g., Wuhan, Milan) to little change (e.g., Rio de Janeiro, Taipei). On average, NO2 concentrations were (13-23) % lower than business as usual from February 2020 onward. China experienced the earliest and steepest decline, but concentrations since April have mostly recovered and remained within 5% to the business-as-usual estimate. NO2 reductions in Europe and the US have been more gradual with a halting recovery starting in late March. We estimate that the global NOx (NO+NO2) emission reduction during the first 6 months of 2020 amounted to 3.1 (2.6-3.6) TgN, equivalent to 5.5(4.7-6.4) % of the annual anthropogenic total. The response of surface O3 is complicated by competing influences of non-linear atmospheric chemistry. While surface O3 increased by up to 50% in some locations, we find the overall net impact on daily average O3 between February -June 2020 to be small. However, our analysis indicates a flattening of the O3 diurnal cycle with an increase in nighttime ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production.

Christoph A Keller↗
NASA NTRS1970

Thermodynamics of the internal combustion engine

The ubiquitous automobile has played both the role of hero and villain during the course of its history. At the present time it is being cast as the villain with increasing frequency because it has been indicted as a major source of air pollution. It is just this characterization that is responsible for our renewed interest in the automobile. When we speak of the automobile as a source of air pollution, we really mean the heart of the automobile, the internal combustion engine. The prototype of the modern internal combustion engine was first successfully operated by Nicholas August Otto in 1876. In spite of its long history, the internal combustion engine is still poorly understood in terms of the details of the physical processes that take place during its operations. The internal combustion engine operates on what is known as the Otto cycle, and Otto cycle calculations have been with us for many years. The emphasis in earlier calculations was usually on the performance rather than on the pollution aspects. Performance characteristics can often be estimated reasonably accurately even with a considerable degree of simplification. We are interested in the pollution aspects of the internal combustion engine, and therefore the calculations must be performed with more care. Our extensive experience with equilibrium calculations places us in a position to carry out such careful calculations. We have just recently begun such an analysis, and its objective is the prediction of exhaust gas properties. I will describe our progress by first reviewing the Otto cycle, and then I will illustrate the effect of various assumptions on the calculated results.

Frank J. Zeleznik↗