The Southern Great Plains (SGP) experiences weather that is dramatic and consequential, from hurricanes and floods to heat waves and drought. A changing climate exacerbates these extremes, further stressing infrastructure and seriously impacting the socioeconomic systems of its rapidly growing and diverse 34-million population, as well as the natural environment (e.g., ecology, coastal systems). This poster will outline some of the key climate-related stressors for the SGP, and discusses the process of developing the SGP chapter and its key messages/focus areas, for the U. S. Global Change Research Program’s (GCRP) Fourth National Climate Assessment (NCA4). NCA4 fulfills a congressional mandate to provide comprehensive information on climate change impacts, adaptation, and resiliency, and is the preeminent source for climate change information within the United States. The SCP chapter is new for NCA4, providing more regional context and detail relevant to the region’s public and decision-makers than NCA3 (2014), the former of which amalgamated climate projections and impacts for the northern and southern Great Plains. Furthermore, the chapter incorporates some new ways of evaluating risk, such as risk-based framing, or in providing some more relevant context, by including potential economic impacts, and also in considering case studies of successful adaptations to current climate-related stressors. A team of regional experts consisting of climatologists, researchers, and federal scientists, spanning multiple sectors (agriculture, economy, climate science, tribal professional, infrastructure, health and water resources among others) were selected to develop this chapter. The team solicited expert input from regional stakeholders, and the final chapter underwent multiple rounds of public and governmental review. Each stage of the process and some key outcomes will be described.

MHD wave phenomena have been readily observed in recent years in various magnetic elements found within the solar atmosphere. They are often touted as a possible mechanism in channeling energy to the outer layers of the solar atmosphere. Recent advances in both observational techniques and instrumentation has gradually bridged the gap between observations and theory of these phenomena, as various wave modes have been identified and their properties studied across a wide range of structures. For example, numerous contemporary studies have identified and studied the properties associated with compressible sausage modes in different bandpasses, often employing magnetic pores as a test bed. However, the spatial structuring of the mode within the flux tube, that is, the surface and body characteristics, has thus far been ignored in observational studies. We employed high spatial and temporal resolution observations from a combination of both ground- (ROSA) and space-based (SDO) instrumentation to study several pore datasets, which were observed to support sausage modes. Using a range of techniques, we observed and were able to classify, for the first time, the surface and body characteristics for the wave modes observed within the pores. The most frequently occurring oscillation period in our observations was found to be ~300s, which is consistent with the p-mode spectrum. We find surface modes more frequently in the data. We find frequencies in the range of ~2–12 mHz, with body modes as high as 11 mHz, but we do not find surface modes above 10 mHz. Estimates made for the energetics of these wave modes will also be discussed within the context of our results.

A variety of measurements of methane in the Martian atmosphere have been made over the past 15 years, showing wildly varying indications of methane abundance, location and lifetime in the Martian atmosphere. Attempts have been made to use numerical tools such as general circulation models (GCMs) to identify source locations and timing of methane releases, but these remain inconclusive under the current approach of forward-trajectory plume modeling. Here we present results using a novel, complementary method of localizing methane surface sources by modeling passive tracer trajectories backwards in time from the locations where observations of atmospheric methane have been made. Such back-trajectory modeling employs both GCM modeled winds and a Lagrangian particle dispersion model to isolate potential upwind sources of the observed signals. This approach avoids many of the pitfalls inherent in forward-trajectory modeling approaches such as numerical diffusion and subgrid-scale motion which cannot be captured in the Eulerian framework of a GCM. We have chosen to focus on localization of the detection of methane by the Planetary Fourier Spectrometer near Gale crater around Ls=336° in MY 31. This observation is consistent with a near-coincident enhanced methane ‘spike’ observed by the Mars Science Laboratory TLS instrument. We have chosen to use the Stochastic Time-Inverted Lagrangian Transport (STILT) particle dispersion model in conjunction with the Mars Weather Research and Forecasting (MarsWRF) GCM for our back-trajectory modeling. To date, we have combined MarsWRF output with a more basic trajectory model, which advects particles based on bulk winds, and have found areas of enhanced tracer density to the north of Gale crater at prior times. Incorporation of turbulent processes in the planetary boundary layer will subject these preliminary results into test. And geological context will also be used to constrain the likelihood of these methane source locations.

The American Association for the Advancement of Science’s Leshner Leadership Institute for Public Engagement with Science, founded in 2015, empowers scientists and engineers to develop and implement public engagement activities, mentor other scientists in their communities and promote public engagement within their institutions. Each year the AAAS Leshner Leadership Institute brings together 15 mid-career researchers working on a topic at the nexus of science and society for a week of intensive training, public engagement practice, and planning. During the following year at their home institutions, AAAS Leshner Fellows implement their plans, interact via regular virtual meetings and receive additional support from staff and experts in the field of public engagement. One of the goals of the AAAS Leshner Leadership Institute is to catalyze institutional change: building understanding about, capacity for and support of public engagement within the various institutions with which researchers are affiliated. AAAS Leshner Fellows have sought to identify opportunities for institutional change within a variety of settings, including universities, government agencies and professional societies. This presentation will provide examples of institutional change from the first three cohorts of AAAS Leshner Fellows (2016-17, climate change; 2017-18, infectious disease; 2018-19, food and water security), including the ways in which they have worked to integrate public engagement into the purpose of the institutions, build processes to support public engagement, and empower people within the institutions to participate in public engagement. It will also discuss the opportunities and challenges for encouraging institutional change via a distributed network of individuals who are linked by discipline but not (necessarily) by institution.

The Sun’s chromosphere is a highly dynamic, partially ionized region where spicules (hot jets of plasma) form. Here we present a two-fluid MHD model to study the chromosphere, which includes ion–neutral interaction and frictional heating. Our simulation recovers a magnetic-canopy shape that forms quickly, but it is also quickly disrupted by the formation of a jet. Our simulation produces a shock self-consistently, where the jet is driven by the frictional heating, which is much greater than the ohmic heating. Thus, our simulation demonstrates that the jet could be driven purely by thermal effects due to ion–neutral collisions and not by magnetic reconnection. We plan to improve the model to include photo-chemical effects and radiation.

Okmok volcano on Umnak Island, Alaska is one of the most hazardous, explosive volcanoes in the Aleutians. Most recently, it erupted in 2008. Previous seismic imaging of Okmok’s large caldera system revealed complex magmatic structures in the upper 5 km beneath the caldera but magma transport at larger depths remains poorly constrained due to reduced imaging resolution. Using receiver function analysis of waveforms, we aim to chart sharp boundaries in the crust beneath Okmok and the surrounding region in order to understand its deeper crustal magmatic system. We have calculated receiver functions for M6 and larger teleseismic earthquakes between 2008 and 2021 recorded by permanent networks AV and AK, and between 2015-2016 at temporary network 5F. We observe Ps arrivals that are consistent with a Moho depth of ~40km, particularly at stations outside the caldera. At some stations, we observe that receiver functions calculated for incoming rays pointing towards the volcano are different from those pointing away from the volcano. However, there is significant variability in the receiver functions, even for overlapping ray paths in the mid-to-deep crust (> 10 km). This suggests complex crustal structure with heterogeneity that may be spatially localized beneath individual stations. Furthermore, receiver functions for stations inside Okmok caldera are more reverberatory than those outside the caldera, indicating that the structure, likely predominantly in the upper crust, beneath these two regions is different.

The Cabled Observatory Vent Imaging Sonar, otherwise known as COVIS, has acquired several months of plume centerlines and strengths for several vents in the ASHES vent field of Axial Seamount. COVIS was initially installed at ASHES vent field in July 2018 and acquired imaging data throughout July-September 2018 and since July 2019. COVIS uses acoustic imaging to monitor the strength and behavior of the plumes formed above black smokers and diffuse discharge sites in an approximately 40 m by 40 m region which includes Inferno and Mushroom vents. Preliminary observations suggest that the plumes above Inferno are highly variable; sometimes a distinct rising column is seen to expand with height while other times there is little acoustic evidence for a plume at all. Potential explanations range from variable discharge rates to variable discharge salinity driving collapsing plumes to extremes in bottom currents. The obvious simple explanation of bent plumes produced by extreme bottom currents is unsatisfactory as such bent (even horizontal) plumes should be visible in the acoustic imaging data. Initial explorations of the impact of near seawater salinity variations suggest this is a plausible explanation for variations in plume maximum height independent of heat content. However, the paucity of recent or continuous salinity and temperature sampling on Inferno limits the certainty of interpretations suggesting variations in venting. In contrast to the variable plumes, the sulfide mounds of the region (Inferno, Mushroom, Hell and Phoenix) appear as consistent (stable) silhouettes in the acoustic images. On Inferno, we can even see indications of the thin chimneys on top of the mound from which primary venting occurs. Preliminary work is focused on refining the classification of acoustic returns between rock, sulfide, and water to see if we can track the growth (and collapse) of the actively venting chimneys.

In November 2017, the High Resolution Ensemble Forecast version 2 (HREFv2) system was implemented by the U.S. National Oceanic and Atmospheric Administration (NOAA). The HREFv2 is NCEP’s first operational convection-allowing model (CAM) ensemble and runs twice daily at ~3-km horizontal grid spacing. Coinciding with the operationalization of the HREFv2, the NOAA National Weather Service’s Storm Prediction Center (SPC) launched its HREF Ensemble Viewer (https://www.spc.noaa.gov/exper/href), a public web display for real-time HREF data. In addition to products traditionally used in operational forecasting, the HREF Ensemble Viewer also employs post-processing and visualization techniques which leverage the convective structures explicitly modeled in CAM ensembles. This presentation describes and illustrates products from the SPC viewer unique to CAM ensembles which are targeted at forecasting convective storm coverage, intensity, and evolution. A key aspect of HREF’s ensemble design is membership diversity with respect to model cores and parameterization schemes, in conjunction with a time-lagging approach. Verification is performed on ensemble fields related to explicitly modeled convection for various modified configurations of the HREF membership, illustrating how each dimension of membership diversity contributes to the system’s skill in forecasting convective evolution. These results help to illuminate potential tradeoffs entailed in configuring future HREF iterations beyond version 2 as CAMs using new dynamical cores and parameterization schemes become available.

The rhizosphere is a complex system in which many diverse and heterogeneous small-scale components (e.g, plant roots, fluids, microbes, and mineral surfaces) interact with one another, often in nonlinear ways, giving rise to emergent system behaviors. Ecosystem-scale perturbations, such as nitrogen limitation or drought, drive changes in micro-environments through a cascade of complex interacting processes, leading to a bidirectional feedback across scales between microbial and plant habitats at the microscale and ecosystem function at the macroscale. We are developing a conceptual and numerical framework for multiscale simulation of organic carbon transport, transformation, and disposition in the soil-microbe-plant continuum. The conceptual model comprises a set of directed graphs, with nodes representing system processes and states and edges representing process-state relationships. The graphs are coded in the graphviz syntax enabling dynamic web visualization. Graph nodes are hyperlinked to metadata pages summarizing current understanding of each process or state and its representation in current numerical codes. This conceptual model is available via a git repository and can guide identification of opportunities for coupling (data exchange) between codes operating at different length scales. The numerical implementation of the conceptual model is based on execution of integrated data processing and multiscale modeling scientific workflows. The numerical framework is enabled by a recent development in information technology known as orchestration, a class of solutions to problems of deployment and execution of cloud-oriented software. Orchestration technology is well-suited to automating complex scientific workflows, both in model-coupling efforts and experimental analysis pipelines. Here it is used to flexibly define workflow steps based on precedent events (such as arrival of a new model output in the data repository). It is being applied to integrate several community software packages spanning scales from molecules to ecosystems, linked to experimental data from the Environmental Molecular Sciences Laboratory (a national scientific user facility), to address critical scientific questions related to soil nutrient cycling.

In upland soils in humid climates, mineral stabilization of organic matter (OM) on millennial scales is often driven by the abundance of poorly crystalline, metastable chemical weathering products. Studies of volcanic ash soils have demonstrated that these metastable materials transform into increasingly crystalline minerals at advanced stages of weathering, so that the overall affinity of mineral surfaces for OM declines with time. However, the abundance of clay-sized (<2 𝜇m diameter) particles tends to increase with weathering, enhancing soil specific surface area (SSA) and potentially compensating for the loss of mineral affinity for OM. As a first step towards understanding the net effects of these simultaneous transformations on OM stabilization, we compared the coverage of SSA by OM in A and B horizons of ash-derived soils sampled along an elevation gradient in Veracruz, Mexico. N2 adsorption isotherms and Brunauer–Emmett–Teller (BET) theory were used to estimate SSA of bulk soil versus samples from which OM had been removed via combustion (muffling) and chemical oxidation (bleaching). In addition to comparing the effectiveness of the OM removal treatments, we characterized the extent to which the treatments altered the mineral matrix and introduced errors into the estimates of mineral SSA. Pore size distribution was estimated via density functional theory as a complement to the BET analysis. N2-accessible SSA ranged from 9 to 105 m2 g-1 after removal of OM, with muffling yielding higher values than bleaching for most samples. The probable loss of SSA associated with mineral transformations (e.g., of Fe oxides) at high temperatures during muffling was evidently offset by the more thorough removal of OM by that treatment. Although SSA tended to increase with weathering status, relative coverage of SSA by OM was relatively consistent across profiles and tended to be greater on average in A horizons (bleaching: 45% SSA covered, muffling: 51%) than in B horizons (bleaching: 28%, muffling: 34%). The apparent lack of OM coverage of SSA in the B horizon of the most weathered soil (0% of 60 m2 g-1 covered) underscores the overall importance of mineral reactivity in determining OM stabilization. Future work will extend these analyses to examine land-use effects on SSA coverage by OM.

Estimating material properties of natural materials is a goal shared between near-surface exploration, infrastructure management, and even conservation of historic sites. Existing methods (e.g., seismic, ultrasonics, and direct testing) for characterizing these properties of interest are not yet available at the desired scale or configuration. GPR is an established method for characterizing the physical configuration of these sites by mapping subsurface features. A new analysis method applying seismic and image processing attribute analysis to GPR data has promising results for material identification and possibly characterization. To further explore this capacity, an experiment to characterize concrete laboratory specimens using GPR was performed. Creating a unique data set, GPR scans and attribute analyses are paired with direct testing of the samples. A variety of attributes and regression analyses have been able to predict porosity of the samples from the mean instantaneous GPR amplitudes with some success (R2 = 0.8). Density and compressive strength are more difficult to predict from the GPR data, but porosity is an excellent proxy property that can be related to other physical properties using secondary relationships. By continuing to explore these relationships and test them on GPR data for other materials (stone, brick, etc.), the results could be extended and refined to provide fine-scale estimation of important properties to characterize reservoirs, basins, and other geological or anthropogenic features of interest.

Using samples from the South Pole Ice Core (SPC14), we present new bubble number-density (BND) measurements and a modeled temperature history reconstruction for the South Pole site back through ~18.5 ka. Additionally, we show that 3D micro-CT sample imagery can accurately quantify BND, enabling more rapid and efficient future analyses. Using sampling and imaging techniques previously established for analyses of the WAIS Divide ice core (Spencer et al., 2006; Fegyveresi et al., 2016), we measured BND as well as other bubble characteristics from just below pore close-off depth starting at ~160 m, down to ~1200 m, at 20-meter intervals (53 total samples), with typical values ranging between 800 and 900 bubbles cm-3 over this interval. These values are higher than any previously recorded for ice-core BND, indicative of both colder average temperatures, and higher average accumulation rates at South Pole. Below ~1100 m, we noted significant bubble loss owing to the onset of clathrate-hydrate formation. Using micro-CT technology, we also tested the use of 3D imagery to accurately measure and evaluate BND as a supplement and future alternative to painstaking thin-section measurements. We imaged a secondary set of ice-core samples at 100-meter intervals starting at 200 m, and across the sample total depth range. Once corrected for cut- and micro-bubbles, our results show comparable values and thus similar trends to the thin-section data. For our temperature model, we determined an accumulation record using both measured annual layer thicknesses as well as estimated d15N-derived firn-column thicknesses estimates. Our temperature reconstruction was calculated using the model developed by Spencer et al. (2006), and using a South Pole site-specific bubble-to-grain ratio (G) of 1.6. the reconstruction reveals a warming across the glacial-interglacial transition of ~7°C, with a relatively stable trend through the Holocene (< 0.4°C warming). These results are in close agreement with those reported by other independent paleothermometers (i.e. isotope- and firn-derived reconstructions). Results of our temperature reconstruction also reveal that using 3D micro-CT imagery in place of traditional thin-section techniques produces comparable results, but with even greater accuracy, and lower measures of uncertainty.

Over half of the global population experiences water scarcity for at least one month during the year. Such situations of household water insecurity (HWI), where household water provisioning is reduced in such a way that affordability, adequacy, reliability, or safety is compromised to threaten human well-being, can be the result of complex interactions between humans and the water systems in which they live. To advance understanding regarding the cause-and-effect relationships between variable hydrological conditions and how humans experience domestic water provisioning, we conduct a systematic literature review to synthesize existing research and identify knowledge gaps of seasonal climate and hydrological influence on HWI. We incorporate a socio-ecological framework of drinking water services as well as process-based hydrological information to interpret results. Following the PRISMA 2020 systematic review guidelines, we retained 67 studies for final analysis. Examining studies by country as well as Major Freshwater Habitat, we find most study sites have been in sub-Saharan Africa (n=61, 89.7%) and in areas characterized by Tropical and Subtropical Coastal Rivers (n=37, 54.4%). Discussion of seasonality has centered on bimodal rainy/dry seasons; pre-monsoon, monsoon, and post-monsoon seasons; seasonal droughts and floods; winter snow and ice conditions; and seasonal migration. Water infrastructure, household characteristics, institutional factors, and water sharing practices mediate seasonal influences, either ameliorating or exacerbating its effects. To date, there have been few HWI seasonality studies in East Asia and the Pacific, Middle East and North Africa, North America, and Europe and Central Asia, and no studies in areas of Temperate Floodplain Rivers and Wetlands and Temperate Upland Rivers. Additionally, despite efforts to incorporate seasonality, most studies are cross-sectional, demonstrating an urgent need for more longitudinal studies to better characterize HWI within and between years. With climate change expected to disproportionately affect the portion of the global population that relies on seasonally varying environmental resources, it is critical to address these research gaps to ensure availability and sustainable management of water for all.

Greater landward velocities were recorded after 6 megathrust earthquakes in subduction zone regions adjacent to the ruptured portion. Previous explanations invoked either increased slip deficit accumulation or plate bending during postseismic relaxation, with different implications for seismic hazard. We investigate whether bending can be expected to reproduce this observed enhanced landward motion (ELM). We use 3D quasi-dynamic finite element models with periodic earthquakes. We find that afterslip downdip of the brittle megathrust exclusively produces enhanced trenchward surface motion in the overriding plate. Viscous relaxation produces ELM when a depth limit is imposed on afterslip. This landward motion results primarily from in-plane elastic bending of the overriding plate due to trenchward viscous flow in the mantle wedge near the rupture. Modeled ELM is, however, incompatible with the observations, which are an order of magnitude greater and last longer after the earthquake. Varying mantle viscosity, plate elasticity, maximum afterslip depth, earthquake size, and megathrust locking outside of the rupture does not significantly change this conclusion. The observed ELM consequently appears to reflect faster slip deficit accumulation, implying a greater seismic hazard in lateral segments of the subduction zone.

The efficient development of shale gas reservoirs requires an accurate understanding of methane gas transport in the matrix whose pore size is mainly in the nanoscale range. As a result, continuum-based approaches may be inadequate in simulating flow in such systems. Molecular dynamics (MD) simulations are capable of capturing the relevant microscale physics with high fidelity, albeit at a substantial computational cost. This high expense restricts MD simulations to rather small systems and computational domains, which may not be representative of complex hierarchical nature of shale reservoirs. To bridge this gap, we use a particle-based approach, the lattice Boltzmann method (LBM), as a suitable means to capture the physics of transport at microscale and simulate large complex domains. In this work, the multiple-relaxation-time (MRT)-LBM is used to study methane transport in nano-size pores. The adsorption effect and non-ideal gas behavior are incorporated using the pseudopotential model and appropriate force terms. The optimal values of the LB free parameters are determined for a nano-slit pore using reference velocity and density profiles from MD simulations. A preconditioning scheme is proposed to improve the stability of LBM in the presence of force terms. In this scheme, steady-state profiles obtained in the absence of regularization are used as the initial condition for simulation runs that include the regularization step. The results show how roughness adversely affects gas-transport in nanopores. The stability of the proposed framework makes it a potential approach for studying methane transport in more complex nano-porous media and translating transport behavior across scales.

Iran is suffering from a state of water bankruptcy. Several factors have contributed to the current water resources bankruptcy, ranging from anthropogenic impacts, such as an inefficient agricultural sector and aggressive withdrawal of groundwater, to climatological impacts. This presentation suggests that water resources mismanagement in Iran should be evaluated beyond the policy-makers decisions, as it recognizes that the bankruptcy has been intensified due to the structural and institutional form of the political system in Iran. This study discusses the roots of the water bankruptcy and identifies four major shortcomings caused by the political system: (1) the absence of public engagement due to the lack of a democratic and decentralized structure; (2) adopting ideological policies in domestic and foreign affairs; (3) conflicts of interest and the multiplicity of governmental policy-makers and sectors; and (4) a state-controlled, resource-dependent economy. Through the development of a generic causal model, this study recommends a systematic transition towards a democratic, decentralized, non-ideological, and economically diverse political governance as the necessary–but not necessarily sufficient–adaptive and sustainable solution for mitigating the impacts of water resources bankruptcy in Iran. The insights highlighted in this presentation could be employed to inform water resources decision-makers and political actors in other non-democratic and ideological political structures struggling with a water resources crisis or bankruptcy.

Quantifying the orientation and magnitude of tectonic stresses is essential to better understand active crustal deformation and faulting in the Hikurangi Subduction Margin (HSM), North Island, New Zealand. In this study, We estimate the horizontal stress magnitudes (Shmin and SHmax ) utilizing leak-off test (LOTs) data, borehole breakout widths measured from borehole image logs, and rock unconfined compressive strengths (UCS) derived from empirical relationships using P-wave velocity wireline logs. Stress field results are used to infer the tectonic regime experienced in the region where three boreholes, Makareao-1, Kauhauroa-5, and Tuhara-1A, are drilled. Relative stress magnitudes in Makareao-1 at 260-900 m TVDss (True vertical depth from sea level) suggest thrust or strike-slip tectonics (SHmax≥ Shmin= Sv). Moving east to Kauhauroa-5, the stress results report a gradual transition from shallow normal/strike-slip tectonics (Sv > Shmin) to thrust or strike-slip tectonics (SHmax> Sv≥ Shmin) at depth. Further east again, at borehole Tuhara-1A, stress results suggest normal/strike-slip tectonics (Sv≥SHmax> Shmin) from 555-2264 m TVDss. The tectonic regimes in individual boreholes are consistent with fault interpretations of seismic reflection profiles from this region. These three boreholes are located within the hangingwall of active, NE-SW striking thrust faults and from borehole breakout azimuths we find a mean SHmax orientation of 065° ± 17° (NE-SW) for the deeper parts of these boreholes. The SHmax orientation is broadly compatible with maximum contraction directions determined from campaign GPS and sub-parallel to far-field relative Pacific-Australian plate motion. This, combined with our stress magnitude observations in Makareao- 1 and Kauhauroa-5 suggests these NE-SW striking faults predominantly experience strike and/or oblique slip despite appearing in seismic profiles as thrust faults. We suggest that these faults originated as thrust faults during older stages of subduction along this margin, which over time have become reactivated in a more strike-slip manner.

The Global Burden of Disease attributes millions of premature deaths to ambient air pollution each year, making it one of the largest environmental health risks faced by society. This mortality is largely due to exposure to fine particulate matter (PM2.5). In the United States, the Environmental Protection Agency estimated that 50.5 million people lived in counties with PM2.5 concentrations above the level of the National Ambient Air Quality Standards in 2020. PM2.5 levels can be derived from satellite aerosol optical depth (AOD) measurements providing comprehensive spatial and temporal coverage. However, the chemical composition of PM2.5 affects the mechanisms by which adverse health effects occur, and thus there is a pressing need for linking satellite data with high-resolution atmospheric modeling of PM2.5 composition. In order to better inform public health policy and decision-making, we aim to estimate near-real-time (NRT) surface PM2.5 composition informed by satellite AOD measurements and chemical transport modeling for the first time. Here, we demonstrate this framework for hindcast estimates in year 2021. NRT AOD is collected from multi-source remote sensing data including Moderate Resolution Imaging Spectroradiometer (MODIS; Aqua and Terra), the Visible Infrared Imaging Radiometer Suite (VIIRS; Dark Target and Deep Blue), and Multi-Angle Imaging SpectroRadiometer (MISR). The data obtained from these products are combined into daily, 10-km AOD estimates and used to scale simulated total PM2.5. GEOS-Chem (v13.1.2) nested regional simulations are run over North America with GEOS-Forward Processing (FP) assimilated meteorology at resolution 0.25° lat. x0.3125° lon. (approximately 20-30km) to simulate daily AOD and get an initial estimate of PM2.5 composition. This estimate is interpolated into the 10-km grid and multiplied with the satellite-adjusted total PM2.5 composition to produce concentrations of each PM2.5 species. This satellite-constrained chemical transport model framework estimates of PM2.5 will ultimately be evaluated against observations and compared to estimates using standard satellite products to inform future use of this framework to predict ambient air pollution health risks in true near-real-time.