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NASA NTRS2023

A Single-Point Modeling Approach for the Intercomparison and Evaluation of Ozone Dry Deposition Across Chemical Transport Models (Activity 2 of AQMEII4)

A primary sink of air pollutants and their precursors is dry deposition. Dry deposition estimates differ across chemical transport models, yet an understanding of the model spread is incomplete. Here, we introduce Activity 2 of the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4). We examine 18 dry deposition schemes from regional and global chemical transport models as well as standalone models used for impact assessments or process understanding. We configure the schemes as single-point models at eight Northern Hemisphere locations with observed ozone fluxes. Single-point models are driven by a common set of site-specific meteorological and environmental conditions. Five of eight sites have at least 3 years and up to 12 years of ozone fluxes. The interquartile range across models in multiyear mean ozone deposition velocities ranges from a factor of 1.2 to 1.9 annually across sites and tends to be highest during winter compared with summer. No model is within 50 % of observed multiyear averages across all sites and seasons, but some models perform well for some sites and seasons. For the first time, we demonstrate how contributions from depositional pathways vary across models. Models can disagree with respect to relative contributions from the pathways, even when they predict similar deposition velocities, or agree with respect to the relative contributions but predict different deposition velocities. Both stomatal and nonstomatal uptake contribute to the large model spread across sites. Our findings are the beginning of results from AQMEII4 Activity 2, which brings scientists who model air quality and dry deposition together with scientists who measure ozone fluxes to evaluate and improve dry deposition schemes in the chemical transport models used for research, planning, and regulatory purposes.

Dry deposition↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-user Resources, Answers to Faqs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

remote sensing↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-User Resources, Answers to FAQs, and Common Mistakes to Avoid

Duncan, Bryan↗

NASA NTRS2014

Impact of Bay-Breeze Circulations on Surface Air Quality and Boundary Layer Export

Meteorological and air-quality model simulations are analyzed alongside observations to investigate the role of the Chesapeake Bay breeze on surface air quality, pollutant transport, and boundary layer venting. A case study was conducted to understand why a particular day was the only one during an 11-day ship-based field campaign on which surface ozone was not elevated in concentration over the Chesapeake Bay relative to the closest upwind site and why high ozone concentrations were observed aloft by in situ aircraft observations. Results show that southerly winds during the overnight and early-morning hours prevented the advection of air pollutants from the Washington, D.C., and Baltimore, Maryland, metropolitan areas over the surface waters of the bay. A strong and prolonged bay breeze developed during the late morning and early afternoon along the western coastline of the bay. The strength and duration of the bay breeze allowed pollutants to converge, resulting in high concentrations locally near the bay-breeze front within the Baltimore metropolitan area, where they were then lofted to the top of the planetary boundary layer (PBL). Near the top of the PBL, these pollutants were horizontally advected to a region with lower PBL heights, resulting in pollution transport out of the boundary layer and into the free troposphere. This elevated layer of air pollution aloft was transported downwind into New England by early the following morning where it likely mixed down to the surface, affecting air quality as the boundary layer grew.

bay breeze↗

NASA NTRS2013

Implementing Model-Check for Employee and Management Satisfaction

This presentation will discuss methods to which ModelCheck can be implemented to not only improve model quality, but also satisfy both employees and management through different sets of quality checks. This approach allows a standard set of modeling practices to be upheld throughout a company, with minimal interaction required by the end user. The presenter will demonstrate how to create multiple ModelCheck standards, preventing users from evading the system, and how it can improve the quality of drawings and models.

Jones, Corey↗

NASA NTRS2009

Partitioning the LIS/OTD Lightning Climatological Dataset into Separate Ground and Cloud Flash Distributions

Presently, it is not well understood how to best model nitrogen oxides (NOx) emissions from lightning because lightning is highly variable. Peak current, channel length, channel altitude, stroke multiplicity, and the number of flashes that occur in a particular region (i.e., flash density) all influence the amount of lightning NOx produced. Moreover, these 5 variables are not the same for ground and cloud flashes; e.g., cloud flashes normally have lower peak currents, higher altitudes, and higher flash densities than ground flashes [see (Koshak, 2009) for additional details]. Because the existing satellite observations of lightning (Fig. 1) from the Lightning Imaging Sensor/Optical Transient Detector (LIS/OTD) do not distinguish between ground and cloud fashes, which produce different amounts of NOx, it is very difficult to accurately account for the regional/global production of lightning NOx. Hence, the ability to partition the LIS/OTD lightning climatology into separate ground and cloud flash distributions would substantially benefit the atmospheric chemistry modeling community. NOx indirectly influences climate because it controls the concentration of ozone and hydroxyl radicals in the atmosphere. The importance of lightning-produced NOx is empasized throughout the scientific literature (see for example, Huntrieser et al. 1998). In fact, lightning is the most important NOx source in the upper troposphere with a global production rate estimated to vary between 2 and 20 Tg (N)yr(sup -1) (Lee et al., 1997), with more recent estimates of about 6 Tg(N)yr(sup -1) (Martin et al., 2007). In order to make accurate predictions, global chemistry/climate models (as well as regional air quality modells) must more accurately account for the effects of lightning NOx. In particular, the NASA Goddard Institute for Space Studies (GISS) Model E (Schmidt et al., 2005) and the GEOS-CHEM global chemical transport model (Bey et al., 2001) would each benefit from a partitioning of the LIS/OTD lightning climatology. In this study, we introduce a new technique for retrieving the ground flash fraction in a set of N lightning observed from space and that occur within a specific latitude/longitude bin. The method is briefly described and applied to CONUS lightning that have already been partitioned into ground and cloud flashes using independent ground-based observations, in order to assess the accuracy of the retrieval method. The retrieval errors are encouragingly small.

Koshak, W. J.↗

NASA NTRS1996

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.

Ramirez, W. Fred↗

NASA NTRS2012

Estimation of Uncertainties for a Supersonic Retro-Propulsion Model Validation Experiment in a Wind Tunnel

A high-quality model validation experiment was performed in the NASA Langley Research Center Unitary Plan Wind Tunnel to assess the predictive accuracy of computational fluid dynamics (CFD) models for a blunt-body supersonic retro-propulsion configuration at Mach numbers from 2.4 to 4.6. Static and fluctuating surface pressure data were acquired on a 5-inch-diameter test article with a forebody composed of a spherically-blunted, 70-degree half-angle cone and a cylindrical aft body. One non-powered configuration with a smooth outer mold line was tested as well as three different powered, forward-firing nozzle configurations: a centerline nozzle, three nozzles equally spaced around the forebody, and a combination with all four nozzles. A key objective of the experiment was the determination of experimental uncertainties from a range of sources such as random measurement error, flowfield non-uniformity, and model/instrumentation asymmetries. This paper discusses the design of the experiment towards capturing these uncertainties for the baseline non-powered configuration, the methodology utilized in quantifying the various sources of uncertainty, and examples of the uncertainties applied to non-powered and powered experimental results. The analysis showed that flowfield nonuniformity was the dominant contributor to the overall uncertainty a finding in agreement with other experiments that have quantified various sources of uncertainty.

Rhode, Matthew N.↗

NASA NTRS2007

A Review and Analysis of Remote Sensing Capability for Air Quality Measurements as a Potential Decision Support Tool Conducted by the NASA DEVELOP Program

This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities

Ross, A.↗

NASA NTRSDate not supplied

Sub-City-Scale Air Quality Forecasts Combining Models, Satellites, and Surface Measures

Poor air quality is a global major concern, especially in cities with their higher emissions and large numbers of exposed people. Air quality monitoring has traditionally relied on ground-based measurements from a few accurate but expensive regulatory-grade monitors, leading to limited spatial data coverage. More recently, these have been supplemented with other data sources, including satellite observations of pollutants, atmospheric chemistry model simulations, and low-cost monitors allowing for denser spatial data collection at the expense of lower accuracy compared to regulatory-grade monitors. Each of these air quality data sources have their own benefits and drawbacks, and so there is an opportunity to combine these data together while respecting their relative strengths and weaknesses in order to generate a more comprehensive and detailed picture of local air quality. I will present our current work towards such a combination, with a focus on producing higher spatial resolution estimates and near-term forecasts of Nitrogen Dioxide in urban areas in the United States. Our method combines data from the GEOS Composition Forecasting (GEOS-CF) model system, TROPOMI tropospheric NO2 satellite data products, and ground measurements from the EPA regulatory monitoring network using a combination of simple intuitive relationships and machine learning techniques. I will show the performance of this proposed method in several urban areas in the United States, comparing it with baseline approaches using single data sources separately. Overall, we find that combining these disparate datasets together leads to more accurate air quality forecasts in the target areas than is possible using each data source separately.

Air quality↗

NASA NTRS1977

A model to investigate the influence of suspended sediment on the mass transport of a pollutant in open channel flow

An explicit two-dimensional finite difference model, designed to investigate the influence of suspended sediment on the pollutant transport process, is presented. Specific attention is directed toward examining the role of suspended sediment in: (1) the turbulent vertical transport mechanism in a stratified flow, and (2) pollutant uptake due to sorption. Results presented indicate that suspended sediment plays a major role in the pollutant transport process, and subsequently, any meaningful attempt to model the fate of a pollutant in an alluvial channel must account for the presence of a suspended sediment concentration profile. Similarly, the vertical and longitudinal pollutant concentration distributions provided by the model may be utilized to improve upon the predictive capacities of existing water quality models.

Chapman, R. S.↗

NASA NTRS1987

Software reliability models for fault-tolerant avionics computers and related topics

Software reliability research is briefly described. General research topics are reliability growth models, quality of software reliability prediction, the complete monotonicity property of reliability growth, conceptual modelling of software failure behavior, assurance of ultrahigh reliability, and analysis techniques for fault-tolerant systems.

Miller, Douglas R.↗

NASA NTRS1980

Meteorological and air pollution modeling for an urban airport

Results are presented of numerical experiments modeling meteorology, multiple pollutant sources, and nonlinear photochemical reactions for the case of an airport in a large urban area with complex terrain. A planetary boundary-layer model which predicts the mixing depth and generates wind, moisture, and temperature fields was used; it utilizes only surface and synoptic boundary conditions as input data. A version of the Hecht-Seinfeld-Dodge chemical kinetics model is integrated with a new, rapid numerical technique; both the San Francisco Bay Area Air Quality Management District source inventory and the San Jose Airport aircraft inventory are utilized. The air quality model results are presented in contour plots; the combined results illustrate that the highly nonlinear interactions which are present require that the chemistry and meteorology be considered simultaneously to make a valid assessment of the effects of individual sources on regional air quality.

Swan, P. R.↗

NASA NTRS1980

A design tool for estimating passenger ride discomfort within complex ride environments

A series of experimental studies utilizing approximately 2200 test subjects has led to the development of a general empirical model for the prediction of passenger ride discomfort in the presence of complex noise and vibration inputs. The ranges of vibration and noise stimuli used to derive the model included the amplitudes and frequencies that are known to most influence passenger comfort. The ride quality model accounts for the effects of combined axis vibrations (up to three axes simultaneously) and includes corrections for the effect of vibration duration and interior noise. Output of the model consists of an estimate of the passenger discomfort produced by a given noise and/or vibration environment. The discomfort estimate is measured along a continuous scale that spans the range from below discomfort threshold to values of discomfort that are far above discomfort threshold

Leatherwood, J. D.↗

NASA NTRS1982

Advanced technologies applied to reduce the operating costs of small commuter transport aircraft

The application of new aerodynamic, structural, and propulsion technologies to a specified baseline commuter aircraft is studied. The assessment models can be used on a desktop calculator and include a sizing program, operating cost program, and passenger ride qualities model. Evaluation is done with a step-by-step approach and is applied to range, number and type of engines, structure, wing selection, and configuration. A 40 percent direct operating cost saving is anticipated compared to current well established commuter aircraft.

Masefield, O.↗

NASA NTRS2013

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Nitrogen dioxide↗

NASA NTRS2019

Atmospheric Chemistry Modeling and Air Quality Forecasting Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model.We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRSDate not supplied

Hemispheric Airborne Measurements of Air Quality (HAMAQ)

Under NASA’s Earth Venture Suborbital program, Hemispheric Airborne Measurements of Air Quality (HAMAQ) will conduct a series of campaigns in 2028 under the Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary satellite instrument. HAMAQ plans include two deployments, including the Mexico City megalopolis and another North American site yet to be selected. The effort will include two aircraft, NASA’s B777 for in situ sampling and G-III for remote sensing. These aircraft will be used to complete a system of integrated observations, combining satellite observations, ground-based monitoring and research observations with air quality modeling. HAMAQ field intensives will serve multiple objectives to include: improving the use of satellite observations in concert with traditional ground monitoring to inform air quality; assessing emissions to better understand their timing and source apportionment; advancing the development of satellite proxies for air quality; and assessing the factors controlling local air quality in each location sampled. Given the long lead time for this campaign, this poster welcomes discussion from the community on strategies and candidate sites for the second deployment. Given the broad applicability of the HAMAQ science objectives and observing strategy, possible partnerships to extend the pursuit of the larger vision of HAMAQ to also sample in Asia and Europe are of interest.

James H Crawford↗