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DOE OSTI2022

Mechanisms for the Generation of Complex Fracture Networks: Observations From Slant Core, Analog Models, and Outcrop

We use observations of hydraulic fractures in core, outcrop attributes of natural hydraulic fractures, and analogue models, to address how hydraulic fracture networks evolve. A slant core from the Wolfcamp Formation—an unconventional shale hydrocarbon reservoir in the Permian Basin of West Texas—collected within 18 m and 30 m of two hydraulically stimulated horizontal wells, provided an opportunity to examine hydraulic fractures directly. In approximately 183 m of core, 309 calcite-sealed natural opening-mode fractures and 375 hydraulic fractures were identified. Many hydraulic fractures in the core show complex morphology, including twist-hackle segmentation, diversion, and bifurcation; these structures most commonly develop at lithological bed boundaries and mechanical heterogeneities such as natural fractures and concretions. An outcrop of bed-parallel pavements in the Cretaceous Boquillas Formation in West Texas contains opening-mode fractures that likely formed by natural hydraulic fracturing. Fracture traces provide evidence of twist-hackle segmentation, and are typically associated with bed boundaries and preexisting bed-parallel stylolites. A laboratory study of hydraulic fracturing of 33 synthetic blocks of gypsum and hydrostone revealed fracture steps, diversions, twist hackles, and multiple overlapping fractures together with information on fracture growth directions. These complexities in the fracture network were dominantly nucleated at inclusions used to simulate pre-existing fractures, and as a result of mechanical heterogeneity introduced by the wellbore and perforations. Collectively, our results show that complex fracture networks are produced in hydraulic fracturing of self-sourced reservoir strata. Mechanical stratigraphic boundaries and other heterogeneities are likely to enhance fracture network complexity through the processes of segmentation, diversion, and bifurcation. These processes create multiple fracture strands, resulting in an increased number of hydraulic fractures over those initiated, thereby increasing total fracture surface area. Our study provides insight into hydraulic fracture network propagation, and has applications for evaluation, completion, production, and fracture modeling of unconventional reservoirs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Multi-Size Proppant Pumping Schedule of Hydraulic Fracturing: Application to a MP-PIC Model of Unconventional Reservoir for Enhanced Gas Production

Slickwater hydraulic fracturing is becoming a prevalent approach to economically recovering shale hydrocarbon. It is very important to understand the proppant’s transport behavior during slickwater hydraulic fracturing treatment for effective creation of a desired propped fracture geometry. The currently available models are either oversimplified or have been performed at limited length scales to avoid high computational requirements. Another limitation is that the currently available hydraulic fracturing simulators are developed using only single-sized proppant particles. Motivated by this, in this work, a computationally efficient, three-dimensional, multiphase particle-in-cell (MP-PIC) model was employed to simulate the multi-size proppant transport in a field-scale geometry using the Eulerian–Lagrangian framework. Instead of tracking each particle, groups of particles (called parcels) are tracked, which allows one to simulate the proppant transport in field-scale geometries at an affordable computational cost. Then, we found from our sensitivity study that pumping schedules significantly affect propped fracture surface area and average fracture conductivity, thereby influencing shale gas production. Motivated by these results, we propose an optimization framework using the MP-PIC model to design the multi-size proppant pumping schedule that maximizes shale gas production from unconventional reservoirs for given fracturing resources.

42 ENGINEERING↗

DOE OSTI2025

Optical Fiber H2 Sensor Operating in Harsh Environments of Subsurface H2 Storage Reservoirs

Monitoring hydrogen concentration in the subsurface storage reservoirs is vital to ensure the integrity and safety of the storage facilities. An optical fiber hydrogen sensor consisting of a palladium-based sensing layer and a protective polymer layer was developed and evaluated in simulated subsurface hydrogen storage conditions. The developed optical fiber hydrogen sensor has demonstrated successful sensing performance at ~80 °C, ~1,000 psi, and ~100% RH. In addition, the sensor was exposed to real subsurface microbial samples in the harsh environments to monitor microbially induced changes in hydrogen concentration. The sensor has shown stable H2 sensing responses in the replicated underground hydrogen storage conditions without deterioration or loss of H2 sensitivity in the presence of biological samples.

filter layer↗

DOE OSTI2021

A Type–Curve Approach for Evaluating Aquifer Properties by Interpreting Shallow Strain Measured During Well Tests

Strains occur at shallow depths in response to pressure changes during well tests in an underlying aquifer, and recent developments in instrumentation have made it feasible to measure essentially the full strain tensor. Simulations using poroelastic analyses indicate that shallow normal strains are approximately proportional to the logarithm of time when a well is injecting into or pumping from a deep aquifer or reservoir. The drawdown is also a linear function of log time, as shown by the classic Cooper-Jacob type-curve analysis. The time when the semilog straight line intercepts the zero-strain axis is similar to the time determined from the Cooper-Jacob pressure analysis, and it can be used to estimate hydraulic diffusivity, suggesting that horizontal strain data can be used directly to estimate aquifer properties. This approach was validated using measurements from shallow (30-m deep) borehole strainmeters during an injection test at a 530-m-deep sandstone aquifer/reservoir in Oklahoma. The results show intercept times for the shallow normal strain data are essentially the same as for deep pressure data from an equivalent radial distance. The slopes of the semilog plots of the pressure and the strain increase at the same time, suggesting that they both respond to a lateral aquifer boundary. Significantly, though, strain was measured at shallow depths while the pressure data were measured at 530-m depth. This suggests that strain data from shallow depths could be an effective way to improve the characterization of an underlying aquifer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2022

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

The 2005 Intergovernmental Panel on Climate Change (IPCC) Special Report on CCS raised the profile of CO2 capture and storage (CCS) as an important technology for reducing greenhouse gas (GHG) emissions. CCS is now recognized as a key component of most climate change mitigation scenarios. Since publication of that report the international research, development, and deployment (RD&D) community has advanced key technical aspects, clarified regulatory requirements, explored value chain and infrastructure solutions, and developed incentive paradigms to enable and promote large-scale deployment of CCS. These efforts have included research to better characterize geologic storage resources, to improve injection performance and storage efficiency, to assess and manage subsurface environmental risks, and to advance monitoring technologies to assure system conformance. These efforts have helped to build confidence in the viability of geologic carbon storage (GCS), but stakeholder concerns about long-term risks and liability associated with GCS remain a hurdle to broad acceptance and large-scale deployment of CCS. Since 2010, the U.S. DOE’s National Risk Assessment Partnership (NRAP) – a research collaboration between five contributing national laboratories – has worked to establish and demonstrate methods and tools to quantify and manage the subsurface environmental risks associated with GCS, amidst uncertainty. This work supports the Office of Fossil Energy and Carbon Management Carbon Transport and Storage Program’s goal of advancing safe and secure commercial-scale GCS deployment. To address the technical challenge of simulating the physical response of the GCS site to large-scale CO2 injection, NRAP has adopted an approach that relies on coupling computationally efficient reduced-order and/or data-driven proxy models of important system components (i.e., storage reservoir, sealing caprock, leakage pathways, intermediate formations, overlying groundwater aquifers, and the atmosphere) in integrated assessment framework. That integrated model of the physical system is complemented with fit-for purpose functionality to support site characterization and risk-related decisions. The recently released NRAP Phase II toolset includes the Open-Source Integrated Assessment Model (NRAP-Open-IAM) for evaluation of trends in leakage risk and potential impact, tools to support monitoring design optimization (Designs for Risk Evaluation and Management – DREAM v3.0 and Passive Seismic Monitoring Tool - PSMT), and tools for state of stress evaluation (State-of-Stress Analysis Tool - SOSAT) and forecasting induced seismicity risk. The NRAP team has also released a pair of reports describing conceptual workflows to incorporate physics-based, quantitative risk assessment into many of the design, planning, operation, and closure decisions for GCS projects. An online catalogue highlights published studies where these tools and methods are demonstrated. In this presentation, the utility of these products to assess risks and address key stakeholder questions will be highlighted through examples, and related insights about the safety and security of geologic carbon storage in qualified storage sites will be discussed. The prospect of rapid, large-scale deployment of GCS technology to aggressively reduce anthropogenic CO2 emissions requires careful consideration of interference between multiple commercial-scale storage projects within a basin. Going forward, NRAP is expanding and adapting site-scale risk quantification tools and methods to enable assessment of risks and inform management decisions for basin-scale deployment. Increasingly, this work will leverage next-generation approaches for surrogate modelling, fast prediction, and advanced visualization enabled by machine learning and artificial intelligence to promote virtual learning, scenario evaluation, and augment risk-based decision making.

quantitative risk assessment, geologic carbon stor↗

DOE OSTI2024

Stochastic reconstruction of fracture network pattern using spatial point processes

Fracture spatial patterns can strongly affect fluid flow in the subsurface. Proximity and distribution of fractures control reservoir flow behavior over various length scales. In many studies, however, simplified geometrical patterns are generated for fractures which may lead to unrealistic subsurface models. Here we introduce a new method for characterization and modeling of fracture spatial patterns based on outcrop observations. We use Ripley's K-function to characterize the arrangement of fracture barycenters and intersection points over various length scales. In addition, we use semivariograms to quantify spatial correlation in fracture intensity maps. Using this information, we develop a stochastic algorithm that generates two-dimensional fracture network realizations with spatial properties similar to those of a real fracture network measured in the field. Numerical simulation models indicate that the generated fracture realizations exhibit similar flow behaviors as that of the original fracture network. Furthermore, such modeling tools expand and improve our capability in building representative fracture models and in quantification of uncertainty in naturally and hydraulically fractured reservoirs.

58 GEOSCIENCES↗

DOE OSTI2023

Corrosive Influence of Carbon Dioxide on Crack Initiation in Quartz: Comparison With Liquid Water and Vacuum Environments

The stimulation of crack growth in quartz and siliceous materials by injecting carbon dioxide (CO 2 ) represents a key technology in long-term carbon storage and in the development of natural gas wells. While this technology is widely used, the molecular impact of CO 2 interactions on the solid matrix is only incompletely understood. In this work, we employ reactive molecular dynamics simulations to study how the CO 2 fluid environment affects the mechanical properties of pre-cracked single-crystal quartz. The thermodynamic conditions of interest are those relevant to subsurface reservoirs. We report how structural properties of quartz—bond length distribution and crack tip shape—evolve upon introduction of a fluid. These properties are directly related to macroscopic quantities of the global stress-strain curves, thus reaffirming the inherent coupling across multiple scales for fluid-solid interactions in the subsurface. Here, we find that CO 2 reduces the fracture toughness of quartz by 12.1% compared to that of quartz in vacuum, thereby promoting crack growth and enhancing fluid transport in the subsurface.

58 GEOSCIENCES↗

DOE OSTI2023

SALSA_python (SALSython) v1

SALSA_python (Semi-Analytical Leakage Solutions for Aquifers) is a software that computed semi-analytical solutions for hydraulic head and brine leakage in multilayered aquifer–aquitard systems with geologic pressure forcing. It can simulate brine leakage into aquifers in a multi-aquifer-aquitard system with multiple injection and leaky wells. This situation is encountered in underground CO2 storage wherein brine leakage from pressurized reservoirs into aquifers is of concern. SALSA_python calls the original SALSA[1] subroutines in python by using the salsa2.so library. This enables the incorporation and coupling of SALSA computations into existing python-based codes and tools. SALSA_python is available for Linux and Mac operating systems. [1] Cihan, A., Oldenburg, C. M., & Birkholzer, J. T. (2022). Leakage from coexisting geologic forcing and injection-induced pressurization: A semi-analytical solution for multilayered aquifers with multiple wells. Water Resources Research, 58, e2022WR032343.

Bhuvankar, Pramod↗

DOE OSTI2023

Utah FORGE: Documentation on Discrete Fracture Network and Fracture Propagation Modelling

This dataset includes reports and a slide presentation on discrete fracture network (DFN) generation and hydraulic fracture modeling at the Utah FORGE site. It details the characterization of natural fractures using well log and core data, as well as stochastic modeling techniques. The reports describe simulations of hydraulic fracture propagation, fluid-mechanical interactions, and induced microseismicity. The dataset also includes history-matching of net pressure and analyses of fracture growth in naturally fractured geothermal reservoirs. The slides summarize key findings and future research directions.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗

DOE OSTI2024

Aitken Mode Aerosols Buffer Decoupled Mid‐Latitude Boundary Layer Clouds Against Precipitation Depletion

Aerosol-cloud-precipitation interactions are a leading source of uncertainty in estimating climate sensitivity. Remote marine boundary layers where accumulation mode (~100–400 nm diameter) aerosol concentrations are relatively low are very susceptible to aerosol changes. These regions also experience heightened Aitken mode aerosol (~10–100 nm) concentrations associated with ocean biology. Aitken aerosols may significantly influence cloud properties and evolution by replenishing cloud condensation nuclei and droplet number lost through precipitation (i.e., Aitken buffering). We use a large-eddy simulation with an Aitken-mode enabled microphysics scheme to examine the role of Aitken buffering in a mid-latitude decoupled boundary layer cloud regime observed on 15 July 2017 during the Aerosol and Cloud Experiments in the Eastern North Atlantic flight campaign: cumulus rising into stratocumulus under elevated Aitken concentrations (~100–200 mg -1 ). In situ measurements are used to constrain and evaluate this case study. Our simulation accurately captures observed aerosol-cloud-precipitation interactions and reveals time-evolving processes driving regime development and evolution. Aitken activation into the accumulation mode in the cumulus layer provides a reservoir for turbulence and convection to carry accumulation aerosols into the drizzling stratocumulus layer above. Further Aitken activation occurs aloft in the stratocumulus layer. Together, these activation events buffer this cloud regime against precipitation removal, reducing cloud break-up and associated increases in heterogeneity. We examine cloud evolution sensitivity to initial aerosol conditions. With halved accumulation number, Aitken aerosols restore accumulation concentrations, maintain droplet number similar to original values, and prevent cloud break-up. Without Aitken aerosols, precipitation-driven cloud break-up occurs rapidly. In this regime, Aitken buffering sustains brighter, more homogeneous clouds for longer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A Boundary Element Model for Assessing Large‐Scale Pressurization in Faulted Geological Storage Systems

Assessing large-scale pressurization at the regional scale—a possible outcome of large subsurface storage applications such as wastewater injection and geological carbon sequestration—presents significant computational challenges. These challenges are particularly pronounced when accounting for complex geologic structures with multiple reservoir and caprock layers, fault zones, and wells. This study introduces a computationally efficient model that integrates single-phase semi-analytical solutions with a boundary element (BE) approach. The model simulates pressure propagation in multilayered 3D systems, including vertical faults, caprock, basement, and confining units. We apply this new model to a representative scenario involving CO 2 injection near a partially sealing fault with verification against an independent two-phase flow model. Results demonstrate that our model accurately captures far-field pressure responses and that, outside the CO 2 plume zone, pressure predictions from single-phase and two-phase models are nearly identical. This supports the use of single-phase models like ours for efficient estimation of far-field pressure changes. Additionally, we demonstrate its effectiveness at a large scale, incorporating multiple wells and faults. With its ability to represent multiple wells, fault zones, and geological heterogeneity, our model is well suited for assessments of basin-scale pressurization. Its computational efficiency also makes it a promising tool for integration with optimization frameworks aimed at designing and managing injection strategies in faulted storage systems.

Cihan, A. [Lawrence Berkeley National Laboratory (↗

DOE OSTI2025

Spatiotemporal Energy Cascade in Three-Dimensional Magnetohydrodynamic Turbulence

We present a new scale decomposition method to investigate turbulence in wavenumber-frequency space. Using 3D magnetohydrodynamic turbulence simulations, we show that magnetic fluctuations with time scales longer than the nonlinear time exhibit an inverse cascade toward even smaller frequencies. Low frequency magnetic fluctuations support turbulence, acting as an energy reservoir that is converted into plasma kinetic energy, the latter cascading toward large wavenumbers and frequencies, where it is dissipated. Our results shed new light on the spatiotemporal properties of turbulence, potentially explaining the origin and role of low frequency turbulent fluctuations in the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Thermal extremes in regulated river systems under climate change: an application to the southeastern U.S. rivers

High river temperatures, or “thermal extremes”, can cause fish mortality and thermoelectric powerplant derating. Under climate change, projected higher air temperature and stronger surface energy fluxes will lead to increased water temperatures, exacerbating thermal extremes. However, cold hypolimnetic releases from thermally stratified reservoirs can depress tailwater temperatures and therefore alleviate thermal extremes. Thermal extremes are more harmful when they coincide with low flows, which we refer to as “hydrologic hot-dry events”. To assess multisectoral impacts of climate change over large regions, we evaluate thermal events according to three impact attributes: duration (D), intensity (I), and severity (S). We apply an established model framework to simulate streamflow and stream temperature over the southeastern US regulated river system. We quantify climate change impacts (by the 2080s under RCP8.5) by comparing historical and future periods and quantify regulation impacts by comparing unregulated and regulated scenarios. We find that climate change will exacerbate thermal extremes (all three metrics) in both unregulated and regulated scenarios, albeit less in the regulated scenario. Thermal mitigation from reservoir regulation will be stronger under climate change, decreasing the three metrics compared to the unregulated case. Even so, thermal extremes in the regulated scenario will still be more severe under climate change, and only 12.2%, 19.7%, and 26.0% of D, I, and S can be mitigated by reservoirs. Despite stronger reservoir stratification, the number of regulated river segments that experience simultaneous high temperature and low flow events (hydrologic hot-dry events) will increase by 21.4% by the 2080s under RCP8.5. These events will have a median annual duration of 10.3 days/year, over 10 times the historical value.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Impact of Floating PV (FPV) System on Water Evaporation: Case Study of an Open Loop Reservoir in North Carolina

Fresh water scarcity is becoming one of the important concerns worldwide. This situation of water scarcity is further exacerbated by the increase in water evaporation due to climate change. This manuscript will address this concern by considering the impact of floating photovoltaics (FPVs) systems on water evaporation. The installation of PV modules on the water bodies can help reduce the water evaporation rate from reservoirs by reducing the evaporating area of the water surface. This work evaluates the effect of FPV on water evaporation rates in the TuckerTown reservoir located in North Carolina state of United States. Meteorological data, such as mean temperature and dew-point, are used to calculate the rate of the water evaporation by Linacre method. The simulation results for the TuckerTown case study showed that the aggregated avoided evaporated volume for one year is 9 million gallons.

14 SOLAR ENERGY↗

DOE OSTI2021

On the Generation of Weddell Sea Polynyas in a High-Resolution Earth System Model

Larger Weddell Sea polynyas (WSPs), differentiated in this study from the smaller Maud Rise Polynyas (MRPs), forming to the east of the prime meridian in the proximity of the Maud Rise seamount, have last been observed in the 1970s. We investigate WSPs that grow realistically out of MRPs in a high-resolution (HR) preindustrial simulation with the Energy Exascale Earth System Model version 0.1. The formation of MRPs requires HR to simulate the detailed flow around Maud Rise, while the realistic formation of WSPs requires a model to produce MRPs. Furthermore, WSPs tend to follow periods of a prolonged build-up of a heat reservoir at depth and weakly negative wind-stress curl in association with the core of the southern hemisphere westerlies at an anomalously northern position. While this scenario also leads to drier conditions over the central Weddell Sea, which some literature claims to be a necessary condition for the formation of WSPs, our model results indicate that open-ocean polynyas do not occur during periods of weakly negative wind-stress curl despite drier atmospheric conditions. Our study supports the hypothesis noted in earlier studies that a shift from a weakly negative to a strongly negative wind-stress curl over the Weddell Sea is a prerequisite for WSPs to form, together with a large heat reservoir at depth. However, the ultimate trigger is a pronounced MRP; whose associated convection creates high surface salinity anomalies that propagate westward with the flow of the Weddell Gyre. If large enough, these anomalies trigger the formation of a WSP and a pulse of newly formed Antarctic Bottom Water.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Observation of Road Salt Aerosol Driving Inland Wintertime Atmospheric Chlorine Chemistry

Inland sources of particulate chloride for atmospheric nitryl chloride (ClNO2) formation remain unknown and unquantified, hindering air quality assessments. Globally each winter, tens of millions of tons of road salt are spread on roadways for deicing. Here, we identify road salt aerosol as the primary chloride aerosol source, accounting for 80–100% of ClNO 2 formation, at an inland urban area in the wintertime. This study provides experimental evidence of the connection between road salt and air quality through the production of this important reservoir for nitrogen oxides and chlorine radicals, which significantly impact atmospheric composition and pollutant fates. A numerical model was employed to quantify the contributions of chloride sources to ClNO 2 production. The traditional method for simulating ClNO 2 considers chloride to be homogeneously distributed across the atmospheric particle population; yet, we show that only a fraction of the particulate surface area contains chloride. Our new single-particle parametrization considers this heterogeneity, dramatically lowering overestimations of ClNO 2 levels that have been routinely reported using the prevailing methods. The identification of road salt as a ClNO 2 source links this common deicing practice to atmospheric composition and air quality in the urban wintertime environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗