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At least 1,711 records · Page 95

Influence of crustal dust and sea spray supermicron particle concentrations and acidity on inorganic NO 3 − aerosol during the 2013 Southern Oxidant and Aerosol Study

Inorganic aerosol composition was measured in the southeastern United States, a region that exhibits high aerosol mass loading during the summer, as part of the 2013 Southern Oxidant and Aerosol Study (SOAS) campaign. Measurements using a Monitor for AeRosols and GAses (MARGA) revealed two periods of high aerosol nitrate (NO 3 − ) concentrations during the campaign. These periods of high nitrate were correlated with increased concentrations of supermicron crustal and sea spray aerosol species, particularly Na + and Ca 2+ , and with a shift towards aerosol with larger (1 to 2.5 μm) diameters. We suggest this nitrate aerosol forms by multiphase reactions of HNO 3 and particles, reactions that are facilitated by transport of crustal dust and sea spray aerosol from a source within the United States. The observed high aerosol acidity prevents the formation of NH 4 NO 3 , the inorganic nitrogen species often dominant in fine-mode aerosol at higher pH. In addition, calculation of the rate of the heterogeneous uptake of HNO 3 on mineral aerosol supports the conclusion that aerosol NO 3 − is produced primarily by this process, and is likely limited by the availability of mineral cation-containing aerosol surface area. Modeling of NO 3 − and HNO 3 by thermodynamic equilibrium models (ISORROPIA II and E-AIM) reveals the importance of including mineral cations in the southeastern United States to accurately balance ion species and predict gas–aerosol phase partitioning.

54 ENVIRONMENTAL SCIENCES↗

Molecular composition and volatility of isoprene photochemical oxidation secondary organic aerosol under low- and high-NO<sub><i>x</i></sub> conditions

Abstract. We present measurements of secondary organic aerosol (SOA) formation from isoprene photochemical oxidation in an environmental simulation chamber at a variety of oxidant conditions and using dry neutral seed particles to suppress acid-catalyzed multiphase chemistry. A high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) utilizing iodide-adduct ionization coupled to the Filter Inlet for Gases and Aerosols (FIGAERO) allowed for simultaneous online sampling of the gas and particle composition. Under high-HO2 and low-NO conditions, highly oxygenated (O : C ≥ 1) C5 compounds were major components (∼ 50 %) of SOA. The SOA composition and effective volatility evolved both as a function of time and as a function of input NO concentrations. Organic nitrates increased in both the gas and particle phases as input NO increased, but the dominant non-nitrate particle-phase components monotonically decreased. We use comparisons of measured and predicted gas-particle partitioning of individual components to assess the validity of literature-based group-contribution methods for estimating saturation vapor concentrations. While there is evidence for equilibrium partitioning being achieved on the chamber residence timescale (5.2 h) for some individual components, significant errors in group-contribution methods are revealed. In addition, > 30 % of the SOA mass, detected as low-molecular-weight semivolatile compounds, cannot be reconciled with equilibrium partitioning. These compounds desorb from the FIGAERO at unexpectedly high temperatures given their molecular composition, which is indicative of thermal decomposition of effectively lower-volatility components such as larger molecular weight oligomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Secondary sulfate is internally mixed with sea spray aerosol and organic aerosol in the winter Arctic

Abstract. Few measurements of aerosol chemical composition have been made during the winter–spring transition (following polar sunrise) to constrain Arctic aerosol–cloud–climate feedbacks. Herein, we report the first measurements of individual particle chemical composition near Utqiaġvik (Barrow), Alaska, in winter (seven sample days in January and February 2014). Individual particles were analyzed by computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy (CCSEM-EDX, 24 847 particles), Raman microspectroscopy (300 particles), and scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy (STXM-NEXAFS, 290 particles). Sea spray aerosol (SSA) was observed in all samples, with fresh and aged SSA comprising 99 %, by number, of 2.5–7.5 µm diameter particles, 65–95 % from 0.5–2.5 µm, and 50–60 % from 0.1–0.5 µm, indicating SSA is the dominant contributor to accumulation and coarse-mode aerosol during the winter. The aged SSA particles were characterized by reduced chlorine content with 94 %, by number, internally mixed with secondary sulfate (39 %, by number, internally mixed with both nitrate and sulfate), indicative of multiphase aging reactions during transport. There was a large number fraction (40 % of 1.0–4.0 µm diameter particles) of aged SSA during periods when particles were transported from near Prudhoe Bay, consistent with pollutant emissions from the oil fields participating in atmospheric processing of aerosol particles. Organic carbon and sulfate particles were observed in all samples and comprised 40–50 %, by number, of 0.1–0.4 µm diameter particles, indicative of Arctic haze influence. Soot was internally mixed with organic and sulfate components. All sulfate was mixed with organic carbon or SSA particles. Therefore, aerosol sources in the Alaskan Arctic and resulting aerosol chemical mixing states need to be considered when predicting aerosol climate effects, particularly cloud formation, in the winter Arctic.

54 ENVIRONMENTAL SCIENCES↗

Analysis of secondary organic aerosol simulation bias in the Community Earth System Model (CESM2.1)

Organic aerosol (OA) has been considered as one of the most important uncertainties in climate modeling due to the complexity in presenting its chemical production and depletion mechanisms. To better understand the capability of climate models and probe into the associated uncertainties in simulating OA, we evaluate the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 (CAM6) with comprehensive tropospheric and stratospheric chemistry representation (CAM6-Chem) through a long-term simulation (1988–2019) with observations collected from multiple datasets in the United States. We find that CESM generally reproduces the interannual variation and seasonal cycle of OA mass concentration at surface layer with a correlation of 0.40 compared to ground observations and systematically overestimates (69%) in summer and underestimates (-19%) in winter. Through a series of sensitivity simulations, we reveal that modeling bias is primarily related to the dominant fraction of monoterpene-formed secondary organic aerosol (SOA), and a strong positive correlation of 0.67 is found between monoterpene emission and modeling bias in the eastern US during summer. In terms of vertical profile, the model prominently underestimates OA and monoterpene concentrations by 37%–99% and 82%–99%, respectively, in the upper air (>500 m) as validated against aircraft observations. Our study suggests that the current volatility basis set (VBS) scheme applied in CESM might be parameterized with monoterpene SOA yields that are too high, which subsequently results in strong SOA production near the emission source area. We also find that the model has difficulty in reproducing the decreasing trend of surface OA in the southeastern US probably because of employing pure gas VBS to represent isoprene SOA which is in reality mainly formed through multiphase chemistry; thus, the influence of aerosol acidity and sulfate particle change on isoprene SOA formation has not been fully considered in the model. This study reveals the urgent need to improve the SOA modeling in climate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Global simulations of monoterpene-derived peroxy radical fates and the distributions of highly oxygenated organic molecules (HOMs) and accretion products

Abstract. We evaluate monoterpene-derived peroxy radical (MT-RO2) unimolecular autoxidation and self- and cross-reactions with other RO2 species in the GEOS-Chem global chemical transport model. The formation of associated highly oxygenated organic molecules (HOMs) and accretion products are tracked in competition with other bimolecular reactions. Autoxidation is the dominant fate up to 6–8 km for first-generation MT-RO2, which can undergo unimolecular H shifts. Reaction with NO can be a more common fate for H-shift rate constants < 0.1 s−1 or at altitudes higher than 8 km due to the imposed Arrhenius temperature dependence of unimolecular H shifts. For MT-derived HOM-RO2, generated by multistep autoxidation of first-generation MT-RO2, reaction with other RO2 species is predicted to be the major fate throughout most of the boreal and tropical forest regions, whereas reaction with NO dominates in the temperate and subtropical forests of the Northern Hemisphere. The newly added reactions result in an approximate 4 % global average decrease in HO2 and RO2, mainly due to faster self-/cross-reactions of MT-RO2, but the impact upon HO2, OH, and NOx abundances is only important in the planetary boundary layer (PBL) over portions of tropical forests. Predicted HOM concentrations in MT-rich regions and seasons can exceed total organic aerosol predicted by the standard version of the GEOS-Chem model depending on the parameters used. Comparisons to observations reveal that large uncertainties remain for key reaction parameters and processes, especially with respect to the photochemical lifetime and volatility of HOMs as well as the rates and branching of associated RO2 accretion products. Further observations and laboratory studies related to MT-RO2-derived HOMs and gas-phase RO2 accretion product formation kinetics – especially their atmospheric fate, such as gas–particle partitioning, multiphase chemistry, and net secondary organic aerosol formation – are needed.

54 ENVIRONMENTAL SCIENCES↗

Observation-constrained kinetic modeling of isoprene SOA formation in the atmosphere

Isoprene has the largest global non-methane hydrocarbon emission, and the oxidation of isoprene plays a crucial role in the formation of secondary organic aerosol (SOA). Two primary processes are known to contribute to SOA formation from isoprene oxidation: (1) the reactive uptake of isoprene-derived epoxides on acidic or aqueous particle surfaces and (2) the absorptive gas–particle partitioning of low-volatility oxidation products. In this study, we developed a new multiphase condensed isoprene oxidation mechanism that includes these processes with key molecular intermediates and products. The new mechanism was applied to simulate isoprene gas-phase oxidation products and SOA formation from previously published chamber experiments under a variety of conditions and atmospheric observations during the Southern Oxidant and Aerosol Studies (SOAS) field campaign. Our results show that SOA formation from most of the chamber experiments is reasonably reproduced using our mechanism, except when the concentration ratios of initial nitric oxide to isoprene exceed ~ 2, the formed SOA is significantly underpredicted. The SOAS simulations also reasonably agree with the measurements regarding the diurnal pattern and concentrations of different product categories, while the total isoprene SOA remains underestimated. The molecular compositions of the modeled SOA indicate that multifunctional low-volatility products contribute to isoprene SOA more significantly than previously thought, with a median mass contribution of ~ 57 % to the total modeled isoprene SOA. However, this contribution is intricately intertwined with IEPOX-derived SOA (IEPOX: isoprene-derived epoxydiols), posing challenges for their differentiation using bulk aerosol composition analysis (e.g., the aerosol mass spectrometer with positive matrix factorization). Furthermore, the SOA from these pathways may vary greatly, mainly dependent on the volatility estimation and treatment of particle-phase processes (i.e., photolysis and hydrolysis). Our findings emphasize that the various pathways to produce these low-volatility species should be considered in models to more accurately predict isoprene SOA formation. The new condensed isoprene chemical mechanism can be further incorporated into regional-scale air quality models, such as the Community Multiscale Air Quality Modelling System (CMAQ), to assess isoprene SOA formation on a larger scale.

54 ENVIRONMENTAL SCIENCES↗

Chemical aging of single and multicomponent biomass burning aerosol surrogate-particles by OH: Implications for cloud condensation nucleus activity

Multiphase OH and O₃ oxidation reactions with atmospheric organic aerosol (OA) can influence particle physicochemical properties including composition, morphology, and lifetime. Chemical aging of initially insoluble or low soluble single-component OA by OH and O₃ can increase their water-solubility and hygroscopicity, making them more active as cloud condensation nuclei (CCN) and susceptible to wet deposition. However, an outstanding problem is whether the effects of chemical aging on their CCN activity are preserved when mixed with other organic or inorganic compounds exhibiting greater water-solubility. In this work, the CCN activity of laboratory-generated biomass burning aerosol (BBA) surrogate-particles exposed to OH and O₃ is evaluated by determining the hygroscopicity parameter, κ, as a function of particle type, mixing state, and OH/O₃ exposure applying a CCN counter (CCNc) coupled to an aerosol flow reactor (AFR). Levoglucosan (LEV), 4-methyl-5-nitrocatechol (MNC), and potassium sulfate (KS) serve as representative BBA compounds that exhibit different hygroscopicity, water solubility, chemical functionalities, and reactivity with OH radicals, and thus exemplify the complexity of mixed inorganic/organic aerosol in the atmosphere. The CCN activities of all of the particles were unaffected by O₃ exposure. Following exposure to OH, κ of MNC was enhanced by an order of magnitude, from 0.009 to ~0.1, indicating that chemically-aged MNC particles are better CCN and more prone to wet deposition than pure MNC particles. No significant enhancement in κ was observed for pure LEV particles following OH exposure. κ of the internally-mixed particles was not affected by OH oxidation. Furthermore, the CCN activity of OH exposed MNC-coated KS particles is similar to the OH unexposed atomized 1:1 by mass MNC: KS binary-component particles. Our results strongly suggest that when OA is dominated by water-soluble organic carbon (WSOC) or inorganic ions, chemical aging has no significant impact on OA hygroscopicity. The organic compounds exhibiting low solubility behave as if they are infinitely soluble when mixed with a sufficient amount of water-soluble compounds. At and beyond this point, the particles' CCN activity is governed entirely by the water-soluble fraction and not influenced by the oxidized organic fraction. Our results have important implications for heterogeneous oxidation and its impact on cloud formation given that atmospheric aerosol is a complex mixture of organic and inorganic compounds exhibiting a wide-range of solubilities.

54 ENVIRONMENTAL SCIENCES↗

Ion mobility spectrometry–mass spectrometry (IMS–MS) for on- and offline analysis of atmospheric gas and aerosol species

Abstract. Measurement techniques that provide molecular-level information are needed to elucidate the multiphase processes that produce secondary organic aerosol (SOA) species in the atmosphere. Here we demonstrate the application of ion mobility spectrometry-mass spectrometry (IMS–MS) to the simultaneous characterization of the elemental composition and molecular structures of organic species in the gas and particulate phases. Molecular ions of gas-phase organic species are measured online with IMS–MS after ionization with a custom-built nitrate chemical ionization (CI) source. This CI–IMS–MS technique is used to obtain time-resolved measurements (5 min) of highly oxidized organic molecules during the 2013 Southern Oxidant and Aerosol Study (SOAS) ambient field campaign in the forested SE US. The ambient IMS–MS signals are consistent with laboratory IMS–MS spectra obtained from single-component carboxylic acids and multicomponent mixtures of isoprene and monoterpene oxidation products. Mass-mobility correlations in the 2-D IMS–MS space provide a means of identifying ions with similar molecular structures within complex mass spectra and are used to separate and identify monoterpene oxidation products in the ambient data that are produced from different chemical pathways. Water-soluble organic carbon (WSOC) constituents of fine aerosol particles that are not resolvable with standard analytical separation methods, such as liquid chromatography (LC), are shown to be separable with IMS–MS coupled to an electrospray ionization (ESI) source. The capability to use ion mobility to differentiate between isomers is demonstrated for organosulfates derived from the reactive uptake of isomers of isoprene epoxydiols (IEPOX) onto wet acidic sulfate aerosol. Controlled fragmentation of precursor ions by collisionally induced dissociation (CID) in the transfer region between the IMS and the MS is used to validate MS peak assignments, elucidate structures of oligomers, and confirm the presence of the organosulfate functional group.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

Numerical simulations are essential tools for understanding the complex hydrologic response of Arctic regions to a warming climate. However, strong coupling among thermal and hydrological processes on the surface and in the subsurface and the significant role that subtle variations in surface topography have in regulating flow direction and surface storage lead to significant uncertainties. Careful model evaluation against field observations is thus important to build confidence.We evaluate the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations from polygonal tundra at the Barrow Environmental Observatory. ATS couples a multiphase, 3D representation of subsurface thermal hydrology with representations of overland nonisothermal flows, snow processes, and surface energy balance. We simulated thermal hydrology of a 3D ice-wedge polygon with geometry that is abstracted but broadly consistent with the surface microtopography at our study site. The simulations were forced by meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of parameters appearing in the soil evaporation model, the 3-year simulations agreed reasonably well with snow depth, summer water table elevations in the polygon center, and high-frequency soil temperature measurements at several depths in the trough, rim, and center of the polygon. Upscaled evaporation is in good agreement with flux tower observations. The simulations were found to be sensitive to parameters in the bare soil evaporation model, snowpack, and the lateral saturated hydraulic conductivity.Timing of fall freeze-up was found to be sensitive to initial snow density, illustrating the importance of including snow aging effects. The study provides new support for an emerging class of integrated surface/subsurface permafrost simulators.

54 ENVIRONMENTAL SCIENCES↗

AMORE-Isoprene v1.0: a new reduced mechanism for gas-phase isoprene oxidation

Abstract. Gas-phase oxidation of isoprene by ozone (O3) and the hydroxyl (OH) and nitrate (NO3) radicals significantly impacts tropospheric oxidant levels and secondary organic aerosol formation. The most comprehensive and up-to-date chemical mechanism for isoprene oxidation consists of several hundred species and over 800 reactions. Therefore, the computational expense of including the entire mechanism in large-scale atmospheric chemical transport models is usually prohibitive, and most models employ reduced isoprene mechanisms ranging in size from ∼ 10 to ∼ 200 species. We have developed a new reduced isoprene oxidation mechanism using a directed-graph path-based automated model reduction approach, with minimal manual adjustment of the output mechanism. The approach takes as inputs a full isoprene oxidation mechanism, the environmental parameter space, and a list of priority species which are protected from elimination during the reduction process. Our reduced mechanism, AMORE-Isoprene (where AMORE stands for Automated Model Reduction), consists of 12 species which are unique to the isoprene mechanism as well as 22 reactions. We demonstrate its performance in a box model in comparison with experimental data from the literature and other current isoprene oxidation mechanisms. AMORE-Isoprene's performance with respect to predicting the time evolution of isoprene oxidation products, including isoprene epoxydiols (IEPOX) and formaldehyde, is favorable compared with other similarly sized mechanisms. When AMORE-Isoprene is included in the Community Regional Atmospheric Chemistry Multiphase Mechanism 1.0 (CRACMM1AMORE) in the Community Multiscale Air Quality Model (CMAQ, v5.3.3), O3 and formaldehyde agreement with Environmental Protection Agency (EPA) Air Quality System observations is improved. O3 bias is reduced by 3.4 ppb under daytime conditions for O3 concentrations over 50 ppb. Formaldehyde bias is reduced by 0.26 ppb on average for all formaldehyde measurements compared with the base CRACMM1. There was no significant change in computation time between CRACMM1AMORE and the base CRACMM. AMORE-Isoprene shows a 35 % improvement in agreement between simulated IEPOX concentrations and chamber data over the base CRACMM1 mechanism when compared in the Framework for 0-D Atmospheric Modeling (F0AM) box model framework. This work demonstrates a new highly reduced isoprene mechanism and shows the potential value of automated model reduction for complex reaction systems.

58 GEOSCIENCES↗

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗

Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators

Alquimia v1.0 is a generic interface to geochemical solvers that facilitates development of multiphysics simulators by enabling code coupling, prototyping and benchmarking. The interface enforces the function arguments and their types for setting up, solving, serving up output data and carrying out other common auxiliary tasks while providing a set of structures for data transfer between the multiphysics code driving the simulation and the geochemical solver. Alquimia relies on a single-cell approach that permits operator splitting coupling and parallel computation. We describe the implementation in Alquimia of two widely used open-source codes that perform geochemical calculations: PFLOTRAN and CrunchFlow. We then exemplify its use for the implementation and simulation of reactive transport in porous media by two open-source flow and transport simulators: Amanzi and ParFlow. We also demonstrate its use for the simulation of coupled processes in novel multiphysics applications including the effect of multiphase flow on reaction rates at the pore scale with OpenFOAM, the role of complex biogeochemical processes in land surface models such as the E3SM Land Model (ELM) and the impact of surface–subsurface hydrological interactions on hydrogeochemical export from watersheds with the Advanced Terrestrial Simulator (ATS). These applications make it apparent that the availability of a well-defined yet flexible interface has the potential to improve the software development workflow, freeing up resources to focus on advances in process models and mechanistic understanding of coupled problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying shallow subsurface water and heat dynamics using coupled hydrological-thermal-geophysical inversion

Improving our ability to estimate the parameters that control water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. The objectives of this study are to develop and test a new inversion scheme to simultaneously estimate subsurface hydrological, thermal and petrophysical parameters using hydrological, thermal and electrical resistivity tomography (ERT) data. The inversion scheme &ndash; which is based on a nonisothermal, multiphase hydrological model &ndash; provides the desired subsurface property estimates in high spatiotemporal resolution. A particularly novel aspect of the inversion scheme is the explicit incorporation of the dependence of the subsurface electrical resistivity on both moisture and temperature. The scheme was applied to synthetic case studies, as well as to real datasets that were autonomously collected at a biogeochemical field study site in Rifle, Colorado. At the Rifle site, the coupled hydrological-thermal-geophysical inversion approach well predicted the matric potential, temperature and apparent resistivity with the Nash&ndash;Sutcliffe efficiency criterion greater than 0.92. Synthetic studies found that neglecting the subsurface temperature variability, and its effect on the electrical resistivity in the hydrogeophysical inversion, may lead to an incorrect estimation of the hydrological parameters. The approach is expected to be especially useful for the increasing number of studies that are taking advantage of autonomously collected ERT and soil measurements to explore complex terrestrial system dynamics.

58 GEOSCIENCES↗

Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape

Vast carbon stocks stored in permafrost soils of Arctic tundra are under risk of release to the atmosphere under warming climate scenarios. Ice-wedge polygons in the low-gradient polygonal tundra create a complex mosaic of microtopographic features. This microtopography plays a critical role in regulating the fine-scale variability in thermal and hydrological regimes in the polygonal tundra landscape underlain by continuous permafrost. Modeling of thermal regimes of this sensitive ecosystem is essential for understanding the landscape behavior under the current as well as changing climate. Here, we present an end-to-end effort for high-resolution numerical modeling of thermal hydrology at real-world field sites, utilizing the best available data to characterize and parameterize the models. We also develop approaches to model the thermal hydrology of polygonal tundra and apply them at four study sites near Barrow, Alaska, spanning across low to transitional to high-centered polygons, representing a broad polygonal tundra landscape. A multiphase subsurface thermal hydrology model (PFLOTRAN) was developed and applied to study the thermal regimes at four sites. Using a high-resolution lidar digital elevation model (DEM), microtopographic features of the landscape were characterized and represented in the high-resolution model mesh. The best available soil data from field observations and literature were utilized to represent the complex heterogeneous subsurface in the numerical model. Simulation results demonstrate the ability of the developed modeling approach to capture &ndash; without recourse to model calibration &ndash; several aspects of the complex thermal regimes across the sites, and provide insights into the critical role of polygonal tundra microtopography in regulating the thermal dynamics of the carbon-rich permafrost soils. Moreover, areas of significant disagreement between model results and observations highlight the importance of field-based observations of soil thermal and hydraulic properties for modeling-based studies of permafrost thermal dynamics, and provide motivation and guidance for future observations that will help address model and data gaps affecting our current understanding of the system.

54 ENVIRONMENTAL SCIENCES↗

Transfer learning of neural surrogates on multifidelity groundwater simulations

Multifidelity data used in the paper published in Advances in Water Resources 206 (2025) 105140, https://doi.org/10.1016/j.advwatres.2025.105140 The code used to process the data is openly available on GitHub at https://github.com/Model-Reduction-and-UQ-Group/Transfer_Learning_K_reconstruction Computationally inexpensive surrogates of process-based models, such as deep neural networks, enable ensemble-based computations used in risk assessment, data assimilation, etc. However, generation of large datasets required to train a neural network can be as expensive as the ensemble simulations themselves. We ameliorate this challenge by using data from multifidelity (MF) groundwater simulations and transfer learning (TL) to reduce data generation costs while maintaining model accuracy. As a computational example, we train a deep convolutional neural network (CNN) to reconstruct permeability fields from saturation maps derived from a multiphase flow model. Starting with very low- and low-fidelity data generated on increasingly coarse meshes, we pretrain the CNN, followed by output-layer training and fine-tuning using only a limited number of high-fidelity samples. We demonstrate the surrogate’s robustness when interpreting low-quality inputs—such as interpolated maps or data affected by noise—which has strong implications for the applicability in practical hydrogeological scenarios. This multilevel MF-TL strategy achieves a favorable trade-off between computational efficiency and predictive accuracy, significantly outperforming high-fidelity-only approaches under the same computational budget.

Chiofalo, Alessia [University of Bologna] (ORCID:0↗

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis: Modeling Archive

This dataset contains an ensemble of thermal-hydro soil parameters including porosity, thermal conductivity, thermal conductivity shape parameters, and residual saturation of peat and mineral soil. The ensemble was generated using a Null-Space Monte Carlo analysis of parameter uncertainty based on a calibration to soil temperatures collected at the Barrow Environmental Observatory site by the NGEE team. The micro-topography of ice wedge polygons present at the site is included in the analysis using three 1D column models to represent polygon center, rim and trough features. The Arctic Terrestrial Simulator (ATS) was used in the calibration to model multiphase thermal and hydrological processes in the subsurface. This dataset includes one zipped file, one pdf file, and one csv file.This Modeling Archive is in support of an NGEE Arctic publication. The citation for that publication can be found within the references section.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Computer program determines chemical composition of physical system at equilibrium

FORTRAN 4 digital computer program calculates equilibrium composition of complex, multiphase chemical systems. This is a free energy minimization method with solution of the problem reduced to mathematical operations, without concern for the chemistry involved. Also certain thermodynamic properties are determined as byproducts of the main calculations.

Kwong, S. S.↗