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At least 73 records · Page 4

Effects of air pollution on thermal structure and dispersion in an urban planetary boundary layer

The short-term effects of urbanization and air pollution on the transport processes in the urban planetary boundary layer (PBL) are studied. The investigation makes use of an unsteady two-dimensional transport model which has been developed by Viskanta et al., (1976). The model predicts pollutant concentrations and temperature in the PBL. The potential effects of urbanization and air pollution on the thermal structure in the urban PBL are considered, taking into account the results of numerical simulations modeling the St. Louis, Missouri metropolitan area.

Viskanta, R.

The Influence of Smoke Particle Properties and Cabin Characteristics on Smoke Detection in Lunar Gravity

Spacecraft fires pose a threat to the success of future Lunar, Martian, and deep space exploration missions. As NASA plans to return humans to the Moon in the next decade, novel mission requirements will present new fire safety challenges. For example, materials that are fire resistant on Earth are expected to burn under planned habitat conditions (elevated oxygen concentrations and reduced cabin pressure) and partial gravity (0.16g). Optimal smoke detector placement will depend on a combination of buoyant plume velocities, induced by partial gravity, and Environmental Control and Life Support Systems (ECLSS) parameters, including particle filtration rates, supply and return placement within the cabin, and forced air velocities. These ECLSS parameters must also address the need for rapid Lunar dust removal, as Lunar dust exposure poses a risk to crew health and hardware functionality. Here, we present progress toward a computational fluid dynamics model to evaluate smoke transport in a Lunar habitat. Recent work has demonstrated that if air supplies are placed on ceilings and returns on the floor, a buoyant smoke layer at the ceiling may disperse over the order of minutes even under low forced flow conditions. We expand upon these results to examine the influence of different supply and return configurations on smoke plume development. Additionally, we also address differences in the transport of smoke particles and Lunar dust by varying particle parameters like size, density, and shape factor. Finally, we discuss ongoing and future experimental efforts to measure smoke particle properties and transport under partial gravity, elevated oxygen, and reduced pressure conditions.

Claire Fortenberry

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES

Application of soot carbonization kinetics to deduce meaningful soot formation rates in premixed flat flames

Soot formation rates measured in fuel-rich premixed flat flames are frequently used to calibrate or validate chemical kinetic models of soot formation. Unfortunately, these flames feature an extended region of soot precursor particle inception and carbonization that complicates interpretation of soot measurements and leads to a fundamental inconsistency in the nature of the soot material that is modeled versus what is being measured when using non-intrusive, optical techniques. In the work presented here, previously reported data on two canonical sooting ethylene-air premixed flames at 1 atm pressure are interpreted via a new analysis approach that combines soot optical dispersion coefficient measurements with soot carbonization kinetics. This analytical approach explicitly accounts for the production of poorly ordered soot precursor particle mass and its carbonization over time in the flames, providing a clear distinction between the formation rate of precursor particles and their transformation into ordered, solid soot particulate mass. In particular, the results of the analysis show that the precursor particles form much earlier in the flame than the majority of the carbonized soot and their formation rate is two to three times faster than that of ordered soot. The results also show that particle agglomeration begins when the particles are at an intermediate state of carbonization. In conclusion, these results offer a valuable new interpretation of these important datasets and should lead to substantial improvements in the development and calibration of quantitative soot models.

Soot formation

Verification by Remote Sensing of an Oil Slick Movement Prediction Model

The author has identified the following significant results. LANDSAT, aircraft, ships, and air-dropped current drogues were deployed to determine current circulation and to track oil slick movement on four different dates in Delaware Bay. Results were used to verify a predictive model for oil slick movement and dispersion. The model predicts the behavior of oil slicks given their size, location, tidal stage (current), weather (wind), and nature of crude. Both LANDSAT satellites provided valuable data on gross circulation patterns and convergent coastal fronts which by capturing oil slicks significantly influence their movement and dispersion.

Klemas, V.

Forecast, Measurement, and Modeling of an Unprecedented Polar Ozone Filament Event over Mauna Loa Observatory, Hawaii

In mid-March 2005 the northern lower stratospheric polar vortex experienced a severe stretching episode, bringing a large polar filament far south of Alaska toward Hawaii. This meridional intrusion of rare extent, coinciding with the polar vortex final warming and breakdown, was followed by a zonal stretching in the wake of the easterly propagating subtropical main flow. This caused polar air to remain over Hawaii for several days before diluting into the subtropics. After being successfully forecasted to pass over Hawaii by the high-resolution potential vorticity advection model Modele Isentrope du transport Meso-echelle de l'Ozone Stratospherique par Advection (MIMOSA), the filament was observed on isentropic surfaces between 415 K and 455 K (17-20 km) by the Jet Propulsion Laboratory stratospheric ozone lidar measurements at Mauna Loa Observatory, Hawaii, between 16 and 19 March 2005. It was materialized as a thin layer of enhanced ozone peaking at 1.6 ppmv in a region where the climatological values usually average 1.0 ppmv. These values were compared to those obtained by the three dimensional Chemistry-Transport Model MIMOSA-CHIM. Agreement between lidar and model was excellent, particularly in the similar appearance of the ozone peak near 435 K (18.5 km) on 16 March, and the persistence of this layer at higher isentropic levels for the following three days. Passive ozone, also modeled by MIMOSA-CHIM, was at about 3-4 ppmv inside the filament while above Hawaii. A detailed history of the modeled chemistry inside the filament suggests that the air mass was still polar ozone- depleted when passing over Hawaii. The filament quickly separated from the main vortex after its Hawaiian overpass. It never reconnected and, in less than 10 days, dispersed entirely in the subtropics.

atmospheric processes

Going With the Flow: Using a Particle Dispersion Model to Reveal Links Between Ocean Ecosystems and Marine Aerosols

Marine biogenic particle contributions to atmospheric aerosol concentrations are not well understood though they are important for determining cloud optical and cloud nucleating properties. Here we examine the relationship between marine aerosol measurements with satellite and model fields of ocean biology and meteorological variables during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). NAAMES consisted of four field campaigns between November 2015 and April 2018 that aligned with the four major phases of the annual phytoplankton bloom cycle. The FLEXPART Lagrangian particle dispersion model is used to connect these variables spatiotemporally to ship-based aerosol. We find that correlations between some aerosol measurements with satellite measured and modelled variables increase with increasing trajectory length. This indicates biological and meteorological processes over the air mass history are influential to measured particle properties. For example, results show organic aerosol mass is driven by biogenic volatile organic compound (VOC) emissions from photosynthesis by phytoplankton stocks during advection into the region. In contrast, primary marine aerosol (PMA) concentrations showed better correlations to variables weighted with shorter air mass residence times, which reflects their localized origin as primary emissions. Evidence also suggest variability in PMA concentrations likely play an important role in VOC emission removal. The removal of VOCs lessen their impact on particle number and mass concentrations. The sensitivity of marine aerosols to the main ecosystem-atmosphere drivers and its dependence on air mass history are to be further discussed.

Kevin J Sanchez

Effluent monitoring of the December 10, 1974, Titan 3-E launch at Air Force Eastern Test Range, Florida

Surface and airborne field measurements of the cloud behavior and effluent dispersion from a solid rocket motor launch vehicle are presented. The measurements were obtained as part of a continuing launch vehicle effluent monitoring program to obtain experimental field measurements in order to evaluate a model used to predict launch vehicle environmental impact. Results show that the model tends to overpredict effluent levels.

Wornom, D. E.

Simulation and Optimization of Vacuum Swing Adsorption Units for Spacesuit Carbon Dioxide and Humidity Control

Controlling carbon dioxide (CO2) and humidity levels in a spacesuit is critical to ensuring both the safety and comfort of an astronaut during extra-vehicular activity (EVA). Traditionally, this has been accomplished utilizing either non-regenerative lithium hydroxide (LiOH) or regenerative but heavy metal oxide (MetOx) canisters which pose a significant weight burden. Although such technology enables air revitalization, the volume requirements to store the waste canisters as well as the mass to transport multiple units become prohibitive as mission durations increase. Consequently, motivation exists toward developing a fully regenerative technology for spacesuit environmental control. The application of solid amine materials with vacuum swing adsorption technology has shown the capacity to control CO2 while concomitantly managing humidity levels through a fully regenerative cycle eliminating constraints imposed with the traditional technologies. Prototype air revitalization units employing this technology have been fabricated in both a rectangular and cylindrical geometry. Experimental results for these test articles have been collected and are described herein. In order to accelerate the developmental efforts, an axially-dispersed plug flow model with an accompanying energy balance has been established and correlated with the experimental data. The experimental and simulation results display good agreement for a variety of flow rates (110-170 ALM), replicated metabolic challenges (100-590 Watts), and atmosphere pressures under consideration for the spacesuit (248 and 760 mm Hg). The testing and model results lend insight into the operational capabilities of these devices as well as the influence the geometry of the device has on performance. In addition, variable metabolic profiles were imposed on the test articles in order to assess the ability of the technology to transition to new metabolic conditions. The advent of the model provides the capacity to apply computer-aided engineering practices to support the ongoing efforts to optimize and mature this technology for future application to space exploration.

Swickrath, Michael J.

Machine Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

Direct air capture (DAC) is a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been studied as DAC sorbent materials because of their structural and chemical diversity. Thermodynamic calculations using classical force fields are often used to evaluate MOFs for their performance in separations such as CO2 capture. Machine-learned force fields (MLFFs) can use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). These descriptions of forces and energies can be used to improve the accuracy of adsorption calculations. In this work, classical models were used to pre-screen MOFs for CO2 capture. DFT calculations were then used to examine the adsorption mechanism. Next, MLFF models were developed for MOFs to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption properties.

Findley, John

NETL Mobile Emissions Laboratory

This presentation was given (virtually) at the workshop on Atmospheric Chemistry and Dispersion Modelling of Non-CO2 Emissions from Carbon Capture at the National Carbon Capture Center on November 21, 2024. The presentation describes capabilities of NETL's new mobile emissions laboratory trailer.

air emissions

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been studied as DAC sorbent materials because of their structural and chemical diversity. Thermodynamic calculations using classical force fields are often used to screen MOFs for their performance in separations such as CO2 capture. Machine-learned force fields (MLFFs) can use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). These descriptions of forces and energies can be used to improve the accuracy of adsorption calculations. In this work, MLFF models were developed for MOFs to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption properties.

Findley, John

One-level modeling for diagnosing surface winds over complex terrain. II - Applicability to short-range forecasting

The Alpert and Getenio (1988) modification of the Mass and Dempsey (1985) one-level sigma-surface model was used to study four synoptic events that included two winter cases (a Cyprus low and a Siberian high) and two summer cases. Results of statistical verification showed that the model is not only capable of diagnosing many details of surface mesoscale flow, but might also be useful for various applications which require operative short-range prediction of the diurnal changes of high-resolution surface flow over complex terrain, for example, in locating wildland fires, determining the dispersion of air pollutants, and predicting changes in wind energy or of surface wind for low-level air flights.

Alpert, P.

Seismic properties of the crust and uppermost mantle of North America

Seismic refraction profiles for the North American continent were compiled. The crustal models compiled data on the upper mantle seismic velocity (P sub n), the crustal thickness (H sub c) and the average seismic velocity of the crystalline crust (V sub p). Compressional wave parameters were compared with shear wave data derived from surface wave dispersion models and indicate an average value for Poisson's ratio of 0.252 for the crust and of 0.273 for the uppermost mantle. Contour maps illustrate lateral variations in crustal thickness, upper mantle velocity and average seismic velocity of the crystalline crust. The distribution of seismic parameters are compared with a smoothed free air anomaly map of North America and indicate that a complidated mechanism of isostatic compensation exists for the North American continent. Several features on the seismic contour maps also correlate with regional magnetic anomalies.

Braile, L. W.

Mixing by barotropic instability in a nonlinear model

A global, nonlinear, equivalent barotropic model is used to study the isentropic mixing of passive tracers by barotropic instability. Basic states are analytical zonal-mean jets representative of the zonal-mean flow in the upper stratosphere, where the observed 4-day wave is thought to be a result of barotropic, and possibly baroclinic, instability. As is known from previous studies, the phase speed and growth rate of the unstable waves is fairly sensitive to the shape of the zonal-mean jet; and the dominant wave mode at saturation is not necessarily the fastest growing mode; but the unstable modes share many features of the observed 4-day wave. Lagrangian trajectories computed from model winds are used to characterize the mixing by the flow. For profiles with both midlatitude and polar modes, mixing is stronger in midlatitude than inside the vortex; but there is little exchange of air across the vortex boundary. There is a minimum in the Lyapunov exponents of the flow and the particle dispersion at the jet maximum. For profiles with only polar unstable modes, there is weak mixing inside the vortex, no mixing outside the vortex, and no exchange of air across the vortex boundary. These results support the theoretical arguments that, whether wave disturbances are generated by local instability or propagate from other regions, the mixing properties of the total flow are determined by the locations of the wave critical lines and that strong gradients of potential vorticity are very resistant to mixing.

Bowman, Kenneth P.

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

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

Yunyao Li

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been well studied as DAC sorbent materials due to their tunable structural and compositional properties. Thermodynamic simulations using force fields are often used to provide predictions of a material’s performance in many separations. However, these force fields often make assumptions about bonds and the physics of the adsorption process. A new class of force fields called machine-learned force fields (MLFFs) use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). In this work, models were developed to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption using MLFFs. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption in several MOFs.

Findley, John

Validation of an Erythema-Weighted UV Model Using Broadband Solar Irradiance Measurements From Eleven U.S. Sites: Preprint

Erythema-weighted UV solar irradiance (UV-E) has a potential impact on human health if the recommended maximum exposure times are exceeded. In spite of this, it is not measured at most sites that measure Global Horizontal Irradiance (GHI). However, since UV-E is highly correlated with GHI and total ozone content it can be estimated from this information with sufficient accuracy to assisst in public health recommendations. The Power Model (PM) provides a simple method to estimate the erythema-weighted UV irradiance (UV-E) from measured GHI, total ozone column and air mass. In this work, the performance of the PM method is assessed using high-quality data from 11 sites in the continental U.S. (part of SURFRAD and SOLRAD networks) and total ozone estimates publicly available from the MERRA-2 re-analysis database. A three year period (2021- 2023) at 1-minute frequency is considered. The results (for time aggregations of 5 and 60 minutes) show a high Pearson's correlations (> 0.99), consistently positive mean bias deviations (below 13%) and dispersions in the 8-19% range at all sites. Relative values are expressed in terms of the corresponding measurement mean. The performance indicators remain consistent across time resolutions (5 or 60 minutes), suggesting that the model's performance is robust and not significantly affected by short-term variability (which is captured by GHI). Spatial patterns reveal higher biases and RMSD in northern and eastern locations. These values represent a significant improvement over widely used satellite-based global UV-E estimates and open the possibility of using the PM with satellite-based GHI estimates for operational UV-E mapping over the contiguous U.S. territory.

14 SOLAR ENERGY