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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Novel Experimental Approach to Understand the Transport of Nanodrugs

Nanoparticle-based drugs offer attractive advantages like targeted delivery to the diseased site and size and shape-controlled properties. Therefore, understanding the particulate flow of the nanodrugs is important for effective delivery, accurate prediction of required dosage, and developing efficient drug delivery platforms for nanodrugs. In this study, the transport of nanodrugs including flow velocity and deposition is investigated using three model metal oxide nanodrugs of different sizes including iron oxide, zinc oxide, and combined Cu-Zn-Fe oxide synthesized via a modified polyol approach. The hydrodynamic size, size, morphology, chemical composition, crystal phase, and surface functional groups of the water-soluble nanodrugs were characterized via dynamic light scattering, transmission electron microscopy, scanning electron microscopy-energy dispersive X-ray, X-ray diffraction, and fourier transform infrared spectroscopy, respectively. Two different biomimetic flow channels with customized surfaces are developed via 3D printing to experimentally monitor the velocity and deposition of the different nanodrugs. A diffusion dominated mechanism of flow is seen in size ranges 92 nm to 110 nm of the nanodrugs, from the experimental velocity and mass loss profiles. The flow velocity analysis also shows that the transport of nanodrugs is controlled by sedimentation processes in the larger size ranges of 110–302 nm. However, the combined overview from experimental mass loss and velocity trends indicates presence of both diffusive and sedimentation forces in the 110–302 nm size ranges. It is also discovered that the nanodrugs with higher positive surface charges are transported faster through the two test channels, which also leads to lower deposition of these nanodrugs on the walls of the flow channels. The results from this study will be valuable in realizing reliable and cost-effective in vitro experimental approaches that can support in vivo methods to predict the flow of new nanodrugs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding Uncertainty in Microstructure Evolution and Constitutive Properties in Additive Process Modeling

Coupled process–microstructure–property modeling, and understanding the sources of uncertainty and their propagation toward error in part property prediction, are key steps toward full utilization of additive manufacturing (AM) for predictable quality part development. The OpenFOAM model for process conditions, the ExaCA model for as-solidified grain structure, and the ExaConstit model for constitutive mechanical properties are used as part of the ExaAM modeling framework to examine a few of the various sources of uncertainty in the modeling workflow. In addition to “random” uncertainty (due to random number generation in the orientations and locations of grains present), the heterogeneous nucleation density N 0 and the mean substrate grain spacing S 0 are varied to examine their impact of grain area development as a function of build height in the simulated microstructure. While mean grain area after 1 mm of build is found to be sensitive to N 0 and S 0 , particularly at small N 0 and large S 0 (despite some convergence toward similar values), the resulting grain shapes and overall textures develop in a reasonably similar manner. As a result of these similar textures, ExaConstit simulation using ExaCA representative volume elements (RVEs) from various permutations of N 0 , S 0 , and location within the build resulted in similar yield stress, stress–strain curve shape, and stress triaxiality distributions. It is concluded that for this particular material and scan pattern, 15 layers is sufficient for ExaCA texture and ExaConstit predicted properties to become relatively independent of additional layer simulation, provided that reasonable estimates for N 0 and S 0 are used. However, additional layers of ExaCA will need to be run to obtain mean grain areas independent of build height and baseplate structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Current State of Light-Duty Electric Vehicle Supply Equipment Costs: An Assessment of Contemporary Understanding

This study uses a hybrid meta-analysis and literature-review approach to understand the current state of knowledge regarding the costs of electric vehicle supply equipment (EVSE). We present a novel way to consider, categorize, and label measures of cost and show cost measure estimates from a sample of 13 recent studies. We find that in general, there is too much variation and too few commonly represented EVSE cost measures to reasonably provide aggregate figures for these measures. We propose a convention for presenting EVSE cost measures that includes the application (commercial or residential), the power level (Level 1, Level 2, DCFC [with further distinction based on rated power capacity]), and the type of cost measure (hardware, installation, operation, and total cost). We contend that providing researchers with standard cost measures will help to advance our knowledge of EVSE costs by ensuring that future work will use common metrics. Establishing common metrics will enable conventional meta-analyses that will make assessments of EVSE costs even more accessible. Additionally, common metrics will make tracking costs more reliable as the technology continues to evolve and become more ubiquitous.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities

CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.

Environmental Sciences & Ecology↗
DOE OSTI2019

Understanding the Significance of Biochemistry in the Storage, Handling, Purification, and Sampling of Amphiphilic Mycolactone

Mycolactone, the amphiphilic macrolide toxin secreted by Mycobacterium ulcerans , plays a significant role in the pathology and manifestations of Buruli ulcer (BU). Consequently, it follows that the toxin is a suitable target for the development of diagnostics and therapeutics for this disease. Yet, several challenges have deterred such development. For one, the lipophilic nature of the toxin makes it difficult to handle and store and contributes to variability associated with laboratory experimentation and purification yields. In this manuscript, we have attempted to incorporate our understanding of the lipophilicity of mycolactone in order to define the optimal methods for the storage, handling, and purification of this toxin. We present a systematic correlation of variability associated with measurement techniques (thin-layer chromatography (TLC), mass spectrometry (MS), and UV-Vis spectrometry), storage conditions, choice of solvents, as well as the impact of each of these on toxin function as assessed by cellular cytotoxicity. We also compared natural mycolactone extracted from bacterial culture with synthesized toxins in laboratory (solvents, buffers) and physiologically relevant (serum) matrices. Our results point to the greater stability of mycolactone in organic, as well as detergent-containing, solvents, regardless of the container material (plastic, glass, or silanized tubes). They also highlight the presence of toxin in samples that may be undetectable by any one technique, suggesting that each detection approach captures different configurations of the molecule with varying specificity and sensitivity. Most importantly, our results demonstrate for the very first time that amphiphilic mycolactone associates with host lipoproteins in serum, and that this association will likely impact our ability to study, diagnose, and treat Buruli ulcers in patients.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Microscopic Understanding of the Ionic Networks of “Water-in-Salt” Electrolytes

“Water-in-salt” electrolytes with excellent electrochemical and physical properties have been extensively investigated. However, the structural understanding of the lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) in water is still lacking. Here, we perform synchrotron X-ray scattering to systemically study the structural variation of TFSI anions in an aqueous solution under a variety of concentrations and temperatures. There are two different solvation structures in the solution: TFSI - solvated structure and TFSI - network. As the concentration increases, the TFSI - solvated structure gradually disappears while the TFSI - network gradually forms. Even at relatively low concentrations, the TFSI - network can be observed. Our experimental results show that these two structures can coexist at a particular concentration, and temperature changes will lead to one structure’s formation or disappearance. Also, the TFSI - network is the key to obtain a stable electrochemical window under relatively high temperatures.

Liu, Xinyi↗
DOE OSTI2016

CALCULATING ROTATING HYDRODYNAMIC AND MAGNETOHYDRODYNAMIC WAVES TO UNDERSTAND MAGNETIC EFFECTS ON DYNAMICAL TIDES

To understand magnetic effects on dynamical tides, we study the rotating magnetohydrodynamic (MHD) flow driven by harmonic forcing. The linear responses are analytically derived in a periodic box under the local WKB approximation. Both the kinetic and Ohmic dissipations at the resonant frequencies are calculated, and the various parameters are investigated. Although magnetic pressure may be negligible compared to thermal pressure, the magnetic field can be important for the first-order perturbation, e.g., dynamical tides. It is found that the magnetic field splits the resonant frequency, namely the rotating hydrodynamic flow has only one resonant frequency, but the rotating MHD flow has two, one positive and the other negative. In the weak field regime the dissipations are asymmetric around the two resonant frequencies and this asymmetry is more striking with a weaker magnetic field. It is also found that both the kinetic and Ohmic dissipations at the resonant frequencies are inversely proportional to the Ekman number and the square of the wavenumber. The dissipation at the resonant frequency on small scales is almost equal to the dissipation at the non-resonant frequencies, namely the resonance takes its effect on the dissipation at intermediate length scales. Moreover, the waves with phase propagation that is perpendicular to the magnetic field are much more damped. It is also interesting to find that the frequency-averaged dissipation is constant. This result suggests that in compact objects, magnetic effects on tidal dissipation should be considered.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

On understanding the nature of collisions of coronal mass ejections observed by Stereo

We attempt to understand the collision characteristics of two coronal mass ejections (CMEs) launched successively from the Sun on 2013 October 25. The estimated kinematics, from three-dimensional (3D) reconstruction techniques applied to observations of CMEs by the SECCHI/Coronagraphic (COR) and Heliospheric Imagers, reveal their collision around 37 R{sub ⊙} from the Sun. In the analysis, we take into account the propagation and expansion speeds, impact direction, and angular size as well as the masses of the CMEs. These parameters are derived from imaging observations, but may suffer from large uncertainties. Therefore, by adopting head-on as well as oblique collision scenarios, we have quantified the range of uncertainties involved in the calculation of the coefficient of restitution for expanding magnetized plasmoids. We show that the large expansion speed of the following CME compared with that of the preceding CME results in a higher probability of super-elastic collision. We also infer that a relative approaching speed of the CMEs lower than the sum of their expansion speeds increases the chance of a super-elastic collision. The analysis under reasonable errors in the observed parameters of the CME reveals a larger probability of occurrence of an inelastic collision for the selected CMEs. We suggest that the collision nature of two CMEs should be discussed in 3D, and the calculated value of the coefficient of restitution may suffer from a large uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Understanding Formation of Young, Distributed Low-mass Stars and Clusters in the W4 Cloud Complex

It is well known that most of the stars form in rich clusters. However, recent Spitzer observations have shown that a significant number of stars also form in the distributed mode; their origin is not well understood. In this work, we aim to investigate clustered and distributed modes of star formation in the W4 complex. To do so, we identified and characterized the young stellar population associated with the region using homogeneous infrared data sets obtained from the Two Micron All Sky Survey, GLIMPSE, MIPS, and Wide-field Infrared Survey Explorer surveys. We make stellar surface density and minimum spanning tree maps to identify young clusters, and use Spitzer images to identify irradiated structures, such as elephant-trunk-like structures (ETLSs) and pillars in the region. The surface density distribution of the young stellar objects (YSOs) reveals three new clusterings and ~50% distributed protostars in the H ii region. The clusters are of low-mass nature but significantly younger than the central cluster IC 1805. We identified ~ 38 ETLSs in the region, a majority of which consist of one or a few stars at their tips. We find that these stars are low-mass (<2 M {sub ⊙}) YSOs, located at the outskirts (>17 pc) of the cluster IC 1805 and are part of the scattered distributed population. We argued that the star formation in the ETLSs of W4 is going on possibly due to the triggering effect of the expanding W4 bubble. Although high-resolution photometric and spectroscopic data would be required to confirm the scenario, nonetheless, we discuss the implications of this scenario for our understanding of distributed low-mass star formation in cloud complexes as opposed to other mechanisms such as turbulent fragmentation and dynamical ejection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Fermi Gamma-Ray Pulsars: Understanding the High-energy Emission from Dissipative Magnetospheres

Based on the Fermi observational data, we reveal meaningful constraints for the dependence of the macroscopic conductivity (σ) of dissipative pulsar magnetosphere models on the corresponding spin-down rate, E-dot . Our models are refinements of the FIDO (Force-free Inside, Dissipative Outside) models, which have dissipative regions that are restricted on the equatorial current sheet outside of the the light-cylinder. Taking into account the observed cutoff energies of all of the Fermi pulsars and assuming that (a) the corresponding γ-ray pulsed emission is due to curvature radiation at the radiation-reaction-limit regime, and (b) this emission is produced at the equatorial current sheet near the light cylinder, we show that the Fermi data provide clear indications about the corresponding accelerating electric-field components. A direct comparison between the Fermi cutoff energies and the model ones reveals that σ increases with E-dot for high E-dot -values, while it saturates for low ones. This comparison indicates also that the corresponding gap width increases toward low E-dot -values. Assuming the Goldreich–Julian flux for the emitting particles, we calculate the total γ-ray luminosity (L {sub γ}). A comparison between the dependence of the Fermi L {sub γ}-values and the model ones on E-dot indicates an increase of the emitting particle multiplicity with E-dot . Our modeling, guided by the Fermi data alone, enhances our understanding of the physical mechanisms behind the high-energy emission in pulsar magnetospheres.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Understanding the Reaction of Nuclear Graphite with Molecular Oxygen

A thorough understanding of oxidation is important when considering the health and integrity of graphite components in graphite reactors. For the next generation of graphite reactors, HTGRs specifically, an unlikely air ingress has been deemed significant enough to have made its way into the licensing applications of many international licensing bodies. While a substantial body of literature exists on nuclear graphite oxidation in the presence of molecular oxygen and significant efforts have been made to characterize oxidation kinetics of various grades, the value of existing information is somewhat limited. Often, multiple competing processes, including reaction kinetics, mass transfer, and microstructural evolution, are lumped together into a single rate expression that limits the ability to translate this information to different conditions. This article reviews the reaction of graphite with molecular oxygen in terms of the reaction kinetics, gas transport, and microstructural evolution of graphite. It also presents the foundations of a model for the graphite-molecular oxygen reaction system that is kinetically independent of graphite grade, and is capable of describing both the bulk and local oxidation rates under a wide range of conditions applicable to air-ingress.

J. Kane, Joshua↗
DOE OSTI2020

Molecular understanding of new-particle formation from α-pinene between -50 and +25 °C

Abstract. Highly oxygenated organic molecules (HOMs) contribute substantially to the formation and growth of atmospheric aerosol particles, which affect air quality, human health and Earth's climate. HOMs are formed by rapid, gas-phase autoxidation of volatile organic compounds (VOCs) such as α-pinene, the most abundant monoterpene in the atmosphere. Due to their abundance and low volatility, HOMs can play an important role in new-particle formation (NPF) and the early growth of atmospheric aerosols, even without any further assistance of other low-volatility compounds such as sulfuric acid. Both the autoxidation reaction forming HOMs and their NPF rates are expected to be strongly dependent on temperature. However, experimental data on both effects are limited. Dedicated experiments were performed at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN to address this question. In this study, we show that a decrease in temperature (from +25 to -50°C) results in a reduced HOM yield and reduced oxidation state of the products, whereas the NPF rates (J1.7 nm) increase substantially. Measurements with two different chemical ionization mass spectrometers (using nitrate and protonated water as reagent ion, respectively) provide the molecular composition of the gaseous oxidation products, and a two-dimensional volatility basis set (2D VBS) model provides their volatility distribution. The HOM yield decreases with temperature from 6.2 % at 25°C to 0.7 % at -50°C. However, there is a strong reduction of the saturation vapor pressure of each oxidation state as the temperature is reduced. Overall, the reduction in volatility with temperature leads to an increase in the nucleation rates by up to 3 orders of magnitude at -50°C compared with 25°C. In addition, the enhancement of the nucleation rates by ions decreases with decreasing temperature, since the neutral molecular clusters have increased stability against evaporation. The resulting data quantify how the interplay between the temperature-dependent oxidation pathways and the associated vapor pressures affect biogenic NPF at the molecular level. Our measurements, therefore, improve our understanding of pure biogenic NPF for a wide range of tropospheric temperatures and precursor concentrations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign

Marine boundary layer clouds play a critical role in Earth's energy balance. Their microphysical and radiative properties are highly impacted by ambient aerosols and dynamic forcings. In this study, we evaluate the representation of these clouds and related aerosol–cloud interaction processes in the single-column version of the E3SM climate model (SCM) against field measurements collected during the NASA ACTIVATE campaign over the western North Atlantic, as well as intercompare results with high-resolution process level models. We show that E3SM SCM reproduces the macrophysical properties of post-frontal boundary layer clouds in a cold-air outbreak (CAO) case well. However, it generates fewer but larger cloud droplets compared to aircraft measurements. Further sensitivity tests show that the underestimation of both aerosol number concentration and vertical velocity variance contributes to this bias. Aerosol–cloud interactions are examined by perturbing prescribed aerosol properties in E3SM SCM with fixed dynamics. Higher aerosol number concentration or hygroscopicity leads to more numerous but smaller cloud droplets, resulting in a stronger cooling via shortwave cloud forcing. This apparent Twomey effect is consistent with prior climate model studies. The cloud liquid water path shows a weakly positive relation with cloud droplet number concentration due to precipitation suppression. This weak aerosol effect on cloud macrophysics may be attributed to the dominant impact of strong dynamical forcing associated with the CAO. Our findings indicate that the SCM framework is a key tool to bridge the gap between climate models, process level models, and field observations to facilitate process level understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Application of PRIM for understanding patterns in carbon dioxide model-observation differences

Reducing uncertainties in regional carbon balances requires a better understanding of CO 2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM), a data-mining method to identify high-density regions for a target-class within an input parameter space, to airborne observations of potential temperature, wind speed, water vapor mixing ratio, and CO 2 dry mol fraction gathered during the Atmospheric Carbon and Transport (ACT)-America Summer 2016 and Winter 2017 campaigns. ACT observations were targeted at expert-designated cases of fair weather and near-frontal warm and cold sector air at atmospheric boundary-layer, lower-, and higher free tropospheric levels (ABL, LFT, and HFT, respectively). We investigate atmospheric characteristics of these pre-defined cases and associated CO 2 model-observation-differences in the mesoscale WRF-Chem model. PRIM results separate winter- and summertime observations as well as observations from ABL, LFT, and HFT with enrichment factors of 4.0–20.5 inside the PRIM box compared to the entire dataset but cannot distinguish between near-frontal warm and cold sector observations in the higher free troposphere. Analyzing of the parameter space constrained by PRIM, we find that large magnitude model observation differences preferentially associated with times when atmospheric conditions are less typical. This association suggests that PRIM could provide a useful tool for isolating atmospheric conditions with large-magnitude and non-Gaussian CO 2 -residuals for targeted transport model evaluation and to potentially improve inversion results during synoptically active periods.

Gerken, Tobias [James Madison Univ., Harrisonburg,↗
DOE OSTI2025

AERO-MAP: a data compilation and modeling approach to understand spatial variability in fine- and coarse-mode aerosol composition

Abstract. Aerosol particles are an important part of the Earth climate system, and their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Particles can interact with incoming solar radiation and outgoing longwave radiation, change cloud properties, affect photochemistry, impact surface air quality, change the albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. High particulate matter concentrations at the surface represent an important public health hazard. There are substantial data sets describing aerosol particles in the literature or in public health databases, but they have not been compiled for easy use by the climate and air quality modeling community. Here, we present a new compilation of PM2.5 and PM10 surface observations, including measurements of aerosol composition, focusing on the spatial variability across different observational stations. Climate modelers are constantly looking for multiple independent lines of evidence to verify their models, and in situ surface concentration measurements, taken at the level of human settlement, present a valuable source of information about aerosols and their human impacts complementarily to the column averages or integrals often retrieved from satellites. We demonstrate a method for comparing the data sets to outputs from global climate models that are the basis for projections of future climate and large-scale aerosol transport patterns that influence local air quality. Annual trends and seasonal cycles are discussed briefly and are included in the compilation. Overall, most of the planet or even the land fraction does not have sufficient observations of surface concentrations – and, especially, particle composition – to characterize and understand the current distribution of particles. Climate models without ammonium nitrate aerosols omit ∼ 10 % of the globally averaged surface concentration of aerosol particles in both PM2.5 and PM10 size fractions, with up to 50 % of the surface concentrations not being included in some regions. In these regions, climate model aerosol forcing projections are likely to be incorrect as they do not include important trends in short-lived climate forcers.

Mahowald, Natalie M. (ORCID:000000022873997X)↗