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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Atmospheric Aerosol Properties and Climate Impacts

This report critically reviews current knowledge about global distributions and properties of atmospheric aerosols, as they relate to aerosol impacts on climate. It assesses possible next steps aimed at substantially reducing uncertainties in aerosol radiative forcing estimates. Current measurement techniques and modeling approaches are summarized, providing context. As a part of the Synthesis and Assessment Product in the Climate Change Science Program, this assessment builds upon recent related assessments, including the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4, 2007) and other Climate Change Science Program reports. The objectives of this report are (1) to promote a consensus about the knowledge base for climate change decision support, and (2) to provide a synthesis and integration of the current knowledge of the climate-relevant impacts of anthropogenic aerosols for policy makers, policy analysts, and general public, both within and outside the U.S government and worldwide.

Chin, Mian↗
NASA NTRS2014

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Light Detection & Ranging (LIDAR)↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRS2017

MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

We present a new approach to retrieve Aerosol Optical Depth (AOD) using the Moderate Resolution Imaging Spectroradiometer (MODIS) over the turbid coastal water. This approach supplements the operational Dark Target (DT) aerosol retrieval algorithm that currently does not conduct AOD retrieval in shallow waters that have visible sediments or sea-floor (i.e., Class 2 waters). Over the global coastal water regions in cloud-free conditions, coastal screening leads to approx. 20% unavailability of AOD retrievals. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 microns to be negligible regardless of water turbidity, and therefore the 2.1 microns reflectance at the top of the atmosphere is sensitive to both change of fine-mode and coarse-mode AODs. By assuming that the aerosol single scattering properties over coastal turbid water are similar to those over the adjacent open-ocean pixels, the new algorithm can derive AOD over these shallow waters. The test algorithm yields approx. 18% more MODIS-AERONET collocated pairs for six AERONET stations in the coastal water regions. Furthermore, comparison of the new retrieval with these AERONET observations show that the new AOD retrievals have equivalent or better accuracy than those retrieved by the MODIS operational algorithm's over coastal land and non-turbid coastal water product. Combining the new retrievals with the existing MODIS operational retrievals yields an overall improvement of AOD over those coastal water regions. Most importantly, this refinement extends the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides. This expanded coverage is crucial for better understanding of impact of anthropogenic aerosol particles on coastal air quality and climate.

Retrieval↗
NASA NTRSDate not supplied

CyanoSCape: Freshwater Phytoplankton and Floating Aquatic Vegetation Biodiversity

In Southern Africa, the impacts of anthropogenic activities on biodiversity and ecosystem services are exacerbated by the climate crisis. Rapid land use change and the lack of emphasis on environmentally sustainable agricultural practices has hindered hydrological processes and compromised riverine and aquatic ecosystems. This poses obvious risks to natural/indigenous aquatic biodiversity and long-term ecosystem sustainability. Phytoplankton serve as the foundation of the freshwater food web with zooplankton as consumers, which feed fish, invertebrates, and so on up the food chain that comprises the biodiversity of the freshwater system that serves as habitat for biodiversity as well. The diversity of phytoplankton (microscopic organisms) includes photosynthesizing bacteria (cyanobacteria), plant-like diatoms, dinoflagellates, and green algae. Nutrient run-off from agricultural fertilizers and urban overflows, warm temperatures, abundant light availability and compromised hydrological systems provide an ideal environment for cyanobacteria to flourish. Increased prevalence of cyanobacteria, due to both natural and anthropogenic causes, can incur significant effects on the biodiversity of the overall phytoplankton assemblage. These bloom forming algae can significantly outcompete other phytoplankton classes in warmer and eutrophic waters where they are quick to dominate the freshwater system. Eutrophication and toxic cyanobacteria blooms (cyanoHABs) in the inland waters of the Greater Cape Floristic Region (GCFR) incur significant effects on the biodiversity of the overall phytoplankton assemblage and provide a favorable environment forthe overgrowth of floating aquatic vegetation (FAV), which is often invasive and associated with reduced aquatic biodiversity. The algal biodiversity of the GCFR’s freshwater systems is not well characterized. Hyperspectral optical observations are expected to facilitate the improvement of current phytoplankton functional type retrievals significantly, as the sensitivity is sufficient that the distinctive, fine spectral features of different phytoplankton groups can be detected. This will enable testing emerging algorithms and inform the development of new algorithms for use with upcoming hyperspectral satellite missions in this decade. Innovations in optical sensor sensitivity and next generation machine learning capabilities considerably enhance the potential for accurate and rapid detection of phytoplankton, namely the presence, extent, and diversity of cyanobacteria present in cyanoHABs and additionally, invasive FAV. Upcoming hyperspectral satellite missions such as NASA’s Surface Biology and Geology (SBG), Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and the European Space Agency’s Copernicus Hyperspectral Imaging Mission (CHIME) will provide imagery with unprecedented spectral and spatial resolution which will further enable the discovery of linkages between the seasonality and dynamics of HABs and FAV. The overarching goal of this project is to utilize hyperspectral data, with recently developed and next-generation algorithms, to determine the biodiversity of freshwater systems phytoplankton assemblage with emphasis on genus level distinction, as well as monitor the prevalence and diversity of FAV.

CyanoSCape↗
NASA NTRSDate not supplied

The Impact of Atmospheric Dynamics and Anthropogenic Very Short-Lived Chlorine Species on the Recovery of Extra-Polar Ozone

The successful implementation of the Montreal Protocol has led to a decrease in the atmospheric abundance of ozone-depleting substances and a slowing in the destruction of the ozone layer. Previous studies have suggested that atmospheric dynamics, or a rise in compounds not regulated by the Montreal Protocol, such as very short-lived chlorine species (VSL Cl), may lead to a slower than expected recovery of the ozone layer. In this presentation, we examine the expected recovery of total column ozone (TCO) and stratospheric column ozone (SCO) to values observed in 1980 using a novel multiple linear regression (MLR) model that involves a month-by-month regression. The MLR model is trained to TCO anomalies from six data records (SBUV v8.7 MOD, SBUV v8.6 COH, WOUDC, GSG, GTO-ECV, MSR-2) over 1979 to 2021 for the Northern Hemisphere (35N – 60N), the Southern Hemisphere (60S – 35S) and the Tropics (20S – 20N), and SCO anomalies from ML-TOMCAT for these same zonal bands. The MLR includes the effect of halogens (equivalent effective stratospheric chlorine (EESC)), total solar irradiance, stratospheric aerosol optical depth, quasi-biennial oscillation, and the El Niño Southern Oscillation as regressors. We also include the effect of atmospheric dynamics such as the Brewer-Dobson Circulation, Arctic Oscillation, and the Antarctic Oscillation, and VSL Cl species in the formulation of EESC. We use a novel approach to the MLR framework, by separating the observed and regressor time series into the respective months (separating all of the Januarys, Februarys, etc.). Then we conduct a regression for each month from 1979 to 2021 for the three zonal bands denoted above. The model results for each month are combined together to achieve a full monthly time series from 1979 to 2021. We use this novel approach to ascertain the effect of atmospheric dynamics on TCO and SCO, since the dynamical proxies affect ozone in a distinctly different manner for various months. In this presentation, we will quantify the role of both the inclusion of VSL Cl species in the formulation of EESC as well as atmospheric dynamics in explaining the slower than expected recovery of extra-polar TCO and SCO over the past decade.

Laura A. McBride↗
DOE OSTI2022

Subsurface stress criticality associated with fluid injection and determined using machine learning

Machine-learning methods and apparatus are disclosed to determine critical state or other parameters related to fluid-driven failure of a terrestrial locale impacted by anthropogenic activities such as hydraulic fracturing, hydrocarbon extraction, wastewater disposal, or geothermal harvesting. Acoustic emission, seismic waves, or other detectable indicators of microscopic processes are sensed. A classifier is trained using time series of microscopic data along with corresponding data of critical state or failure events. In disclosed examples, random forests and artificial neural networks are used, and grid-search or EGO procedures are used for hyperparameter tuning. Once trained, the classifier can be applied to live data from a fluid injection locale in order to assess a frictional state, assess seismic hazard, assess permeability, make predictions regarding a future fluid-driven failure event, or drive engineering solutions for mitigation or remediation. Variations are disclosed.

Johnson, Paul Allan↗
DOE OSTI2021

Anthropogenic–biogenic interaction amplifies warming from emission reduction over the southeastern US

A decline of surface biogenic secondary organic aerosols through the mediation of reduced anthropogenic aerosols has been recognized as an air quality co-benefit of anthropogenic emission control over the southeastern US. However, the climate impacts of this anthropogenic–biogenic interaction remain poorly understood. Here, we identified a substantial decline of summertime aerosol loading aloft over the southeastern US in recent decades through the interaction, which leads to a stronger decline in column-integrated aerosol optical depth and a greater increase in radiative fluxes over the southeastern than northeastern US, different from trends of anthropogenic emissions and near-surface aerosol loading. The anthropogenic–biogenic interaction is shown to explain more than 60% of the coherent increasing trend of 5.3 Wm -2 decade -1 in clear-sky surface downward radiative fluxes. We show that current climate models fail to represent this interaction. The interaction is further projected to amplify the positive radiative forcing from emission control by 42.3% regionally over the southeastern US and globally by 5.4% in 2050 under RCP4.5 compared to 2005. This amplification effect implies greater challenges to achieving the Paris Agreement temperature targets with continuous emission control in future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Estuarine nutrient pollution impact reduction assessment through euphotic zone avoidance/bypass considerations

The feasibility of reducing nutrient pollution impact by redirecting the effluent to depths below the euphotic zone was investigated for the deep estuarine Puget Sound region of the Salish Sea in the Pacific Northwest of America. The hypothesis tested was that the thickness of the outflow layer in deep estuaries may be greater than the euphotic zone depth, allowing a fraction of nutrients to be exported out passively through the layers immediately below. The euphotic zone depth in Puget Sound varies from 8 to 25 m while the depth of the outflow layer can reach up to ≈ 60 m. Outfall relocation strategies were tested on 99% of the anthropogenic nutrient loads currently delivered to Puget Sound. The impact was quantified using the previously established biophysical Salish Sea Model, using gross primary production and exposure to low dissolved oxygen (DO) levels as the metric (< 2 mg/L for hypoxia and < 5 mg/L for impairment). Eliminating nutrient pollution (above natural) from rivers and wastewater reduced hypoxia exposure by 8.1% and 11.2%, respectively. Relocating the outfalls to deeper waters resulted in improvements, but only in the sill-less sub-basins such as Whidbey, where hypoxia and DO impairment exposure decreased (7.9% and 6.8%, respectively). The presence of multiple sills and circulation cells in Puget Sound resulted in increased exposure and rendered nutrient bypass goals unfeasible as originally envisioned. However, an alternate nutrient export pathway was identified through bottom exchange flow out of Puget Sound via Whidbey Basin and Deception Pass. An unexpected reduction in the exchange outflow magnitude (≈ 4%) due additional (22%) freshwater discharged to the estuary bottom was also noted. The potential loss in circulation strength due to rerouting of natural surface freshwater through submerged deep-water outfalls is identified as a new unforeseen anthropogenic impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exploring Randomly Wired Neural Networks for Climate Model Emulation

Exploring the climate impacts of various anthropogenic emissions scenarios is key to making informed decisions for climate change mitigation and adaptation. State-of-the-art Earth system models can provide detailed insight into these impacts but have a large associated computational cost on a per-scenario basis. This large computational burden has driven recent interest in developing cheap machine learning models for the task of climate model emulation. In this paper, we explore the efficacy of randomly wired neural networks for this task. We describe how they can be constructed and compare them with their standard feedforward counterparts using the ClimateBench dataset. Specifically, we replace the serially connected dense layers in multilayer perceptrons, convolutional neural networks, and convolutional long short-term memory networks with randomly wired dense layers and assess the impact on model performance for models with 1 million and 10 million parameters. We find that models with less-complex architectures see the greatest performance improvement with the addition of random wiring (up to 30.4% for multilayer perceptrons). Furthermore, of 24 different model architecture, parameter count, and prediction task combinations, only one had a statistically significant performance deficit in randomly wired networks relative to their standard counterparts, with 14 cases showing statistically significant improvement. We also find no significant difference in prediction speed between networks with standard feedforward dense layers and those with randomly wired layers. These findings indicate that randomly wired neural networks may be suitable direct replacements for traditional dense layers in many standard models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Global Impacts of Gas-Phase Chemistry-Aerosol Interactions on Direct Radiative Forcing by Anthropogenic Aerosols and Ozone

We present here a first global modeling study on the influence of gas-phase chemistry/aerosol interactions on estimates of anthropogenic forcing by tropospheric O3 and aerosols. Concentrations of gas-phase species and sulfate, nitrate, ammonium, black carbon, primary organic carbon, secondary organic carbon, sea salt, and mineral dust aerosols in the preindustrial, present-day, and year 2100 (IPCC SRES A2) atmospheres are simulated online in the Goddard Institute for Space Studies general circulation model II' (GISS GCM II'). With fully coupled chemistry and aerosols, the preindustrial, presentday, and year 2100 global burdens of tropospheric ozone are predicted to be 190, 319, and 519 Tg, respectively. The burdens of sulfate, nitrate, black carbon, and organic carbon are predicted respectively to be 0.32. 0.18, 0.01, 0.33 Tg in preindustrial time, 1.40, 0.48, 0.23, 1.60 Tg in presentday, and 1.37, 1.97, 0.54, 3.31 Tg in year 2100. Anthropogenic O3 is predicted to have a globally and annually averaged present-day forcing of +0.22 W m(sup -2) and year 2100 forcing of +0.57 W m(sup -2) at the top of the atmosphere (TOA). Net anthropogenic TOA forcing by internally mixed sulfate, nitrate, organic carbon, and black carbon aerosols is estimated to be virtually zero in the present-day and +0.34 W m(sup -2) in year 2100, whereas it is predicted to be -0.39 W m(sup -2) in present-day and -0.61 W m(sup -2) in year 2100 if the aerosols are externally mixed. Heterogeneous reactions are shown to be important in affecting anthropogenic forcing. When reactions of N2O5, NO3, NO2, and HO2 on aerosols are accounted for, TOA anthropogenic O3 forcing is less by 20-45% in present-day and by 20-32% in year 2100 at mid to high latitudes in the Northern Hemisphere, as compared with values predicted in the absence of heterogeneous gas aerosol reactions. Mineral dust uptake of HNO3 and O3 is shown to have practically no influence on anthropogenic O3 forcing. Heterogeneous reactions of N2Os, NO3, NO2, and HO2 are predicted to have noticeable impacts on anthropogenic aerosol forcing over industrialized areas, leading to 0-2 W m(sup -2) more anthropogenic aerosol cooling in present-day and 2-8 W m(sup -2) more cooling in year 2100 in these areas as compared with forcings calculated in the absence of heterogeneous reactions. Sea salt uptake of SO2 reduces the magnitude of TOA aerosol cooling by 0.5-1 W m(sup -2) over the oceans around 60 N in the present-day and year 2100 scenarios. Near dust sources, mineral dust uptake of SO2 and HNO3 leads to less anthropogenic aerosol cooling by 0.5-1 W m(sup -2) in the present day and 1-2 W m(sup -2) in year 2100.

Liao, Hong↗
NASA NTRS2022

Responses of Compound Daytime and Nighttime Warm-Dry and Warm-H Events to Individual Anthropogenic Forcings

Daytime heat is often associated with reduced soil moisture and cloud cover, while nighttime heat is connected to high humidity and increased cloud cover. Due to these differing mechanisms, compound daytime and nighttime heat events may respond differently to major anthropogenic forcings (greenhouse gases, anthropogenic aerosols, land-use and land-cover change). Here, we use GISS ModelE2.1-G historical single-forcing runs from 1955 to 2014 to examine how individual anthropogenic forcings affect compound heat events—specifically warm daytime and nighttime temperatures compounded with dry precipitation or high humidity conditions. We show that greenhouse gases alone amplify the natural frequency of warm-dry events by 1.5–5 times and warm-humid events by 2–9 times in tropical and extratropical latitudes. Conversely, aerosols and land-use/land-cover change reduce the frequency of these events, resulting in more modest increases and in some regions, declines, in the historical 'all-forcings' scenario. Individually, aerosol effects are stronger and more widespread compared to land-use, oftentimes reducing the natural frequency of these events by 60%–100%. The responses of these compound events are primarily driven by changes in daytime and nighttime temperatures through large-scale warming via greenhouse gases and cooling from aerosols and land-use/land-cover change. However, changes in warm-dry events are amplified in regions with concurrent precipitation declines (e.g. Central America, Mediterranean regions) and warm-humid events are amplified by global concurrent humidity increases. Additionally, we find differences between daytime and nighttime compound responses in the historical experiment that can be traced back to the individual forcings. In particular, aerosols produce a greater cooling effect on daytime relative to nighttime temperatures, which notably results in a historical reduction of Northern Hemisphere daytime warm-dry events relative to natural conditions. Our analysis provides a more comprehensive understanding of the significant impacts of different anthropogenic climate forcings on daytime and nighttime warm-dry and warm-humid events, informing future risk and impact assessments.

Anthropogenic forcings↗
NASA NTRS2021

Impact of Regional Northern Hemisphere Mid-latitude Anthropogenic Sulfur Dioxide Emissions on Local and Remote Tropospheric Oxidants

The unintended consequences of reductions in regional anthropogenic sulfur dioxide (SO2) emissions implemented to protect human health are poorly understood. SO2 decreases began in the 1970s in the US and Europe and are expected to continue into the future, while recent emissions decreases in China are also projected to continue. In addition to the well-documented climate effects (warming) from reducing aerosols, tropospheric oxidation is impacted via aerosol modification of photolysis rates and radical sinks. Impacts on the hydroxyl radical and other trace constituents directly affect climate and air quality metrics such as surface ozone levels. We use the Geophysical Fluid Dynamics Laboratory Atmospheric Model version 3 nudged towards National Centers for Environmental Prediction (NCEP) reanalysis wind velocities to estimate the impact of SO2 emissions from the US, Europe, and China by differencing a control simulation with an otherwise identical simulation in which 2015 anthropogenic SO2 emissions are set to zero over one of the regions. Springtime sulfate aerosol changes occur both locally to the emission region and also throughout the Northern Hemispheric troposphere, including remote oceanic regions and the Arctic. Hydroperoxy (HO2) radicals are directly removed via heterogeneous chemistry on aerosol surfaces, including sulfate, in the model, and we find that sulfate aerosol produced by SO2 emissions from the three individual northern mid-latitude regions strongly reduces both HO2 and hydroxyl (OH) by up to 10 % year-round throughout most of the troposphere north of 30∘ N latitude. Regional SO2 emissions significantly increase nitrogen oxides (NOx) by about 5 %–8 % throughout most of the free troposphere in the Northern Hemisphere by increasing the NOx lifetime as the heterogeneous sink of HO2 on sulfate aerosol declines. Despite the NOx increases, tropospheric ozone decreases at northern mid-latitudes by 1 %–4 % zonally averaged and by up to 5 ppbv in summertime surface air over China, where the decreases in HO2 and OH suppress O3 production. Since 2015 anthropogenic SO2 emissions in China exceed those in the US or Europe, the oxidative response is greatest for the China perturbation simulation. Chemical effects of aerosols on oxidation (reactive uptake) dominate over radiative effects (photolysis rates), the latter of which are only statistically significant locally for the large perturbation over China. We find that the SO2 emissions decrease in China, which has yet to be fully realized, will have the largest impact on oxidants and related species in the Northern Hemisphere free troposphere compared to future decreases in Europe or the US. Our results bolster previous calls for a multipollutant strategy for air pollution mitigation to avoid the unintended consequence of aerosol removal leading to surface ozone increases that offset or mask surface ozone gains achieved by regulation of other pollutants, especially in countries where current usage of high-sulfur emitting fuels may be phased out in the future.

anthropogenic sulfur dioxide emissions↗
DOE OSTI2020

What goes up must come down: impacts of deposition in a sulfate geoengineering scenario

The problem of reducing the impacts of rising anthropogenic greenhouse gas on warming temperatures has led to the proposal of using stratospheric aerosols to reflect some of the incoming solar radiation back to space. The deliberate injection of sulfur into the stratosphere to form stratospheric sulfate aerosols, emulating volcanoes, will result in sulfate deposition to the surface. We consider here an extreme sulfate geoengineering scenario necessary to maintain temperatures at 2020 levels while greenhouse gas emissions continue to grow unabated. We show that the amount of stratospheric sulfate needed could be globally balanced by the predicted decrease in tropospheric anthropogenic SO 2 emissions, but the spatial distribution would move from industrialized regions to pristine areas. We show how these changes would affect ecosystems differently depending on present day observations of soil pH, which we use to infer the potential for acid-induced aluminum toxicity across the planet.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Measurements of HNO3, SO2 High Resolution Aerosol SO4 (sup 2-), and Selected Aerosol Species Aboard the NASA DC-8 Aircraft: During the Transport and Chemical Evolution Over the Pacific Airborne Mission (TRACE-P)

The UNH investigation during TRACE-P provided measurements of selected acidic gases and aerosol species aboard the NASA DC-8 research aircraft. Our investigation focused on measuring HNO3, SO2, and fine (less than 2 microns) aerosol SO4(sup 2-) with two minute time resolution in near-real-time. We also quantified mixing ratios of aerosol ionic species, and aerosol (210)Pb and (7)Be collected onto bulk filters at better than 10 minute resolution. This suite of measurements contributed extensively to achieving the principal objectives of TRACE-P. In the context of the full data set collected by experimental teams on the DC-8, our observations provide a solid basis for assessing decadal changes in the chemical composition and source strength of Asian continental outflow. This region of the Pacific should be impacted profoundly by Asian emissions at this time with significant degradation of air quality over the next few decades. Atmospheric measurements in the western Pacific region will provide a valuable time series to help quantify the impact of Asian anthropogenic activities. Our data also provide important insight into the chemical and physical processes transforming Asian outflow during transport over the Pacific, particularly uptake and reactions of soluble gases on aerosol particles. In addition, the TRACE-P data set provide strong constraints for assessing and improving the chemical fields simulated by chemical transport models.

Talbot, Robert W.↗
NASA NTRS2018

Ozone Sensitivity to Varying Greenhouse Gases and Ozone-Depleting Substances in CCMI-1 Simulations

Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

CCMI↗