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At least 1,297 records · Page 72
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DOE OSTI2021

ARM Aerosol Measurement Science Group 2019 Strategic Planning Workshop Report

This report summarizes the results of a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility workshop held in November 2019 to advance a science-based strategy for ARM’s aerosol measurement program. This was the second such workshop since the Aerosol Measurement Science Group (AMSG) was chartered in 2015 to enhance coordination of ARM observations of aerosols and atmospheric trace gases with the needs of ARM users. The results presented here reflect the AMSG’s focus in recent years on science-based strategies that will contribute to the increased use of ARM data to fulfill its mission of improving process representations and predictability in climate models. Sessions held during the workshop range from interfacing with models through aerosol sampling strategies to calibration protocols and data products. The AMSG workshops have been designed to recommend actions that will enable ARM to evolve and continue to meet its mission. To that end, the AMSG will develop an actionable plan from the recommendations outlined here. Some are well defined and can reasonably be accomplished in the short term. Others are less definite or of a larger scope that calls for a longer-term implementation. Further discussion will be required to develop and prioritize actionable items related to such areas. Task teams comprising the appropriate expertise and perspective from the AMSG and other members of the community will be formed to achieve this outcome. Some particular topics are recognized as high priority, so plans are underway to develop task teams and to hold follow-on discussions to address them. Four areas currently being considered for short, focused discussion are 1) aerosol measurements on the North Slope of Alaska, 2) improving data usability for modeling, 3) strategies for advancing remote sensing, vertical profiling, and distributed measurements of aerosols, and 4) aerosol sampling strategies at existing ARM sites to provide intensive modes of operation to promote data usage for process and modeling studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Wildland fire behavior is significantly influenced by environmental factors such as slope steepness, wind speed, and fuel type. Understanding these interactions is critical for improving predictive models and fire management. This study explores how slope steepness and cross-slope wind speed influence fire spread dynamics in various fuel bed types. Simulations are conducted using a physics-based wildland fire model, HIGRAD/FIRETEC, across six slope angles (0–50 %), four cross-slope wind speeds (4–10 m s –1 ), and three fuel bed types (grass, shrubland, and forest). Representative cases are additionally compared with FARSITE fireline evolution. Fire behavior is categorized into distinct propagation types based on spread characteristics and analyzed. The fire propagation angle, which indicates deviation from the wind direction, generally increases with steeper slopes and decreases with stronger cross-slope winds. Secondary upslope propagation is observed in shrubland under moderate slopes, while secondary downwind propagation occurs in all fuel beds at higher wind speeds. These findings highlight fire spread characteristics that differ from predictions by traditional models like Rothermel’s. By capturing complex propagation patterns and dynamics, this study demonstrates the value of a physics-based, atmosphere-fire coupled model for accurate wildland fire prediction. Incorporating secondary propagations and the influence of fuel bed complexities into predictive models can improve the accuracy of fire spread forecasts, enabling more effective fire management and risk mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

The wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multiphase Processing of the Water-Soluble and Insoluble Phases of Biomass Burning Organic Aerosol

Biomass burning is one of the most significant sources of organic aerosol in the atmosphere. Biomass burning organic aerosol (BBOA) has been observed to undergo liquid– liquid phase separation (LLPS) to give core–shell morphology with the hydrophobic phase encapsulating the hydrophilic phase, potentially impacting the evolution of light-absorbing components, i.e., brown carbon (BrC), through multiphase processes. Here, we demonstrate how multiphase processing differs between the watersoluble (i.e., hydrophilic) and insoluble (i.e., hydrophobic) phases of BBOA in terms of reactive uptake of ozone in a coated-wall flow tube. Effects of relative humidity (RH) and ultraviolet (UV) irradiation were investigated. Experimental timeseries were used to inform simulations using multilayer kinetic modeling. Among non-irradiated thin films, the uptake coefficient was greatest for the water-soluble phase at 75% RH (3 × 10 –5 , corresponding to a diffusion coefficient of BrC, D BrC , of 3 × 10 –9 cm 2 s –1 ) and least for the same phase at 0% RH (1 × 10 –5 , corresponding to D BrC of 1 × 10 –10 cm 2 s –1 ). The uptake coefficient for the water-insoluble phase fell between these two (about 1.5 × 10 –5 ), regardless of RH, and the corresponding D BrC increased only slightly (8 × 10 –10 cm 2 s –1 at 0% RH to 9 × 10 –10 cm 2 s –1 at 75% RH). The uptake coefficients of both phases at 0% RH decreased significantly after UV irradiation, consistent with a transition from viscous liquid to solid and supported by qualitative microscopy observations. Modeling multiphase ozone oxidation of primary BrC components in the atmosphere demonstrated, first, that LLPS may extend the lifetime of water-soluble BBOA encapsulated by water-insoluble species by a factor of 1.5 at moderate to high RH and, also, that UV irradiation may extend the lifetime of both phases by more than a factor of 2.5.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating the Trustworthiness of Explainable Artificial Intelligence (XAI) Methods Applied to Regression Predictions of Arctic Sea Ice Motion

Abstract Recent advances in explainable artificial intelligence (XAI) methods show promise for understanding predictions made by machine learning (ML) models. XAI explains how the input features are relevant or important for the model predictions. We train linear regression (LR) and convolutional neural network (CNN) models to make 1-day predictions of sea ice velocity in the Arctic from inputs of present-day wind velocity and previous-day ice velocity and concentration. We apply XAI methods to the CNN and compare explanations to variance explained by LR. We confirm the feasibility of using a novel XAI method [i.e., global layerwise relevance propagation (LRP)] to understand ML model predictions of sea ice motion by comparing it to established techniques. We investigate a suite of linear, perturbation-based, and propagation-based XAI methods in both local and global forms. Outputs from different explainability methods are generally consistent in showing that wind speed is the input feature with the highest contribution to ML predictions of ice motion, and we discuss inconsistencies in the spatial variability of the explanations. Additionally, we show that the CNN relies on both linear and nonlinear relationships between the inputs and uses nonlocal information to make predictions. LRP shows that wind speed over land is highly relevant for predicting ice motion offshore. This provides a framework to show how knowledge of environmental variables (i.e., wind) on land could be useful for predicting other properties (i.e., sea ice velocity) elsewhere. Significance Statement Explainable artificial intelligence (XAI) is useful for understanding predictions made by machine learning models. Our research establishes trustability in a novel implementation of an explainable AI method known as layerwise relevance propagation for Earth science applications. To do this, we provide a comparative evaluation of a suite of explainable AI methods applied to machine learning models that make 1-day predictions of Arctic sea ice velocity. We use explainable AI outputs to understand how the input features are used by the machine learning to predict ice motion. Additionally, we show that a convolutional neural network uses nonlinear and nonlocal information in making its predictions. We take advantage of the nonlocality to investigate the extent to which knowledge of wind on land is useful for predicting sea ice velocity elsewhere.

Hoffman, Lauren [Scripps Institution of Oceanograp↗
DOE OSTI2025

Propagation and Periodicity of Mars's Northern Annular Mode Modulates the Dust Cycle

Abstract We document the propagation of annular modes—zonally symmetric patterns of variability—in Mars's atmosphere using a reanalysis dataset. Mars's Northern Annular Mode (MNAM) sees anomalies of zonal‐mean zonal wind emerge near the subtropics and migrate poleward with a period of 150 days, similarly to Earth's Southern Annular Mode. The mechanism of propagation involves the interaction of the two leading empirical orthogonal functions that define the MNAM. Moreover, the propagation encourages alternating bands of surface wind stress to migrate polewards with a 150‐day period. In addition, a 150‐day periodicity in anomalous column dust optical depth most likely emerges in response to extrema of the MNAM. The combination of the impact of the MNAM's internally forced periodicity on the surface wind stress and the seasonal cycle may contribute to the inter‐annual variability of global dust events, as suggested by a Monte Carlo estimate that correctly approximates the observed incidence of global dust events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Global net climate effects of anthropogenic reactive nitrogen

Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times, contributing to widespread eutrophication and air pollution. Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of –0.34 [–0.20, –0.50] W m –2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N 2 O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud Properties and Boundary Layer Stability Above Southern Ocean Sea Ice and Coastal Antarctica

Significant variability in climate predictions originates from the simulated cloud cover over the Southern Ocean. Historically, Southern Ocean cloud and aerosol properties have been less studied than their northern hemisphere counterparts, and cloud-sea-ice interactions over the Southern Ocean also remain largely unexamined. We used data from combined radar, lidar, radiometer, radiosonde, and ERA5 reanalysis profiles to investigate cloud property relationships to cloud temperature, sea-ice concentration, and boundary layer stability. Our findings show correlations between both cloud macrophysical properties and radiative effects and sea-ice concentration, and that the marine atmospheric boundary layer is more stable over higher sea-ice concentrations. Mixed-phase cloud frequency of occurrence was highest over the sea-ice zone at 15%, three times higher than over cold water south of the Antarctic Polar Front. For temperatures greater than –15°C, low-level, single-layer clouds were more likely to precipitate ice if they were coupled to cold-water or sea-ice surfaces than if they were decoupled from these surfaces, with the highest percentage of clouds precipitating ice observed over sea ice. These findings suggest a surface source of ice-nucleating particles at high southern latitudes that increases cloud glaciation probability. We discuss the implications of our results for future studies into the relationship between cloud properties, aerosols, sea ice, and boundary layer stability at high latitudes over the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Observations of greenhouse gases as climate indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO<:sub>2 GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Investigating Tropical Versus Extratropical Influences on the Southern Hemisphere Tropical Edge in the Unified Model

Abstract Since the late 1970s, observations have shown a widening of the tropical Hadley cell (HC) circulation. State‐of‐the‐art climate models reproduce the general trend along with a projected continuous expansion. Discrepancies in expansion rates of observation‐ and model‐based studies have been attributed to differences in applied methods, natural variability and model shortcomings. Furthermore, the driving influence of tropical or extratropical processes on these changes is not well understood. All of this highlights the dynamical mechanisms and the region of origin controlling the tropical width are still insufficiently understood. Here we examine the influence of systematic model biases of the atmosphere‐only Unified Model (UM) onto the simulation of the Southern Hemisphere (SH) tropical edge. We utilize nudged experiments with prescribed sea surface temperatures, where potential temperature and horizontal winds are relaxed back to ERA‐Interim reanalysis for a 20‐year period in selected regions. Correcting model biases in the tropics and extratropics separately allows us to dissect the dominant remote impacts of present model errors onto the SH tropical edge simulation. The experiments are applied to established tropical width metrics ranging from near‐surface to upper‐level metrics capturing the poleward flank of the HC. We find both regions work remotely to reduce errors in the UM fields and location of the tropical edge. Surprisingly, correcting the extratropical biases, south of 45°S, more consistently improves the tropical width across the metrics and seasons than nudging the tropics (10°N–10°S). These findings demonstrate the substantial role of extratropical influences in locating the SH tropical edge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Variability of Eastern North Atlantic Summertime Marine Boundary Layer Clouds and Aerosols Across Different Synoptic Regimes Identified With Multiple Conditions

Abstract This study estimates the meteorological covariations of aerosol and marine boundary layer (MBL) cloud properties in the eastern North Atlantic (ENA) region, characterized by diverse synoptic conditions. Using a deep‐learning‐based clustering model with mid‐level and surface daily meteorological data, we identify seven distinct synoptic regimes during the summer from 2016 to 2021. Our analysis, incorporating reanalysis data and satellite retrievals, shows that surface aerosols and MBL clouds exhibit clear regime‐dependent characteristics, whereas lower tropospheric aerosols do not. This discrepancy likely arises from synoptic regimes determined by daily large‐scale conditions, which may overlook air mass histories that predominantly dictate lower tropospheric aerosol conditions. Focusing on three regimes dominated by northerly winds, we analyze the Atmospheric Radiation Measurement Program (ARM) ENA observations on Graciosa Island in the Azores. In the subtropical anticyclone regime, fewer cumulus clouds and more single‐layer stratocumulus clouds with light drizzle are observed, along with the highest cloud droplet number concentration (Nd), surface cloud condensation nuclei (CCN) and surface aerosol levels. The post‐trough regime features more broken or multi‐layer stratocumulus clouds with slightly higher surface rain rate, and lower Nd and surface CCN levels. The weak trough regime is characterized by the deepest MBL clouds, primarily cumulus and broken stratocumulus clouds, with the strongest surface rain rate and the lowest Nd, surface CCN and surface aerosol levels, indicating strong wet scavenging. These findings highlight the importance of considering the covariation of cloud and aerosol properties driven by large‐scale regimes when assessing aerosol indirect effects using observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Photochemical and Cloud and Aerosol Aqueous Contributions to Regionally-Emitted Shipping and Biogenic Non-Sea-Salt Sulfate Aerosol in Coastal California

Aerosol nonsea-salt sulfate (NSS sulfate) forms in the atmosphere by secondary reactions of emissions from marine phytoplankton and shipping, with gas-phase as well as cloud and aerosol aqueous reactions controlling production. Twelve months of Atmospheric Radiation Measurements (ARM) during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) at Scripps Pier in La Jolla, California, showed the highest NSS sulfate mass concentrations occurred for the northwesterly back-trajectories over 64% of the year, with an average of 0.90 μg/m 3 that contributed 76% of annual NSS sulfate concentration. Multiple Linear Regression (MLR) and a refractory black carbon tracer method attributed 76–80% of the regionally emitted sulfur dioxide (SO 2 ) sources of submicron NSS sulfate to marine biogenic emissions and 20–24% to shipping emissions. MLR for oxidation processes explained 21% of the variability with Downwelling Shortwave Radiation (DSW) driving photochemical reactions to account for 34% of annual regional sulfate production, Upwind Cloud Vertical Fraction (UCVF) controlling cloud-associated oxidation to account for 29%, and relative humidity (RH) describing aerosol-phase oxidation to account for 36%. NSS sulfate was correlated moderately to UCVF during April-June and August but to RH in October-January. These findings show the apportionment of SO 2 emissions to biogenic and shipping sources and provide observational constraints for the mechanisms for sulfate production from SO 2 in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments

We demonstrate the combination of three Doppler lidars (DLs), a water vapor differential absorption lidar and a temperature rotational Raman lidar for the investigation of the interactions between the land-surface and the atmospheric boundary layer. This combination of scanning lidars was operated for the first time during the Land-Atmosphere Feedback Experiment at the Atmospheric Radiation Measurement program's Southern Great Plain site, Oklahoma, USA, in August 2017, and provided simultaneous surface layer profiles of horizontal wind, humidity and temperature. The horizontal wind profiles were determined using the dual-Doppler method with two DLs. The scans were performed above four towers providing atmospheric variables and fluxes. These combined lidar data allowed for the estimation of the friction velocity as well as the surface latent and sensible heat fluxes. For this purpose, profiles calculated with Monin-Obukhov similarity theory were fitted with the Levenberg-Marquardt nonlinear least squares curve-fitting method to the measured surface-layer lidar profiles. We present case studies of three 50-min periods to illustrate the new method. The measurements resulted in friction velocities of 0.31, 0.29, and 0.38 ms –1 , sensible surface heat fluxes of 312.1, 234.1, and 183.3 Wm –2 and latent surface heat fluxes of 251.8, 227.3, and 274.4 Wm –2 . These values were compared with the in-situ measurements of the towers. Considering the sampling differences and the error analyses, the results agree within 25.1%, 42.5%, and 28.8%, respectively, demonstrating that this synergy of scanning active remote sensing systems can be used to derive surface fluxes with reasonable accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Diurnal variation of the fair-weather atmospheric electric field in Binchuan, China

With the purpose of understanding the variation of fair-weather atmospheric electric field, the vertical component of atmospheric electric field (recorded as Ez) has been measured in the town Binchuan (25°50'N, 100°34'E, 1438.7 m asl) of Dali city, Yunnan, China from June 14, 2017 to December 1, 2020. Automatic measured visual range is used as a proxy of aerosol concentration. The mean diurnal variation curve of the fair-weather Ez in Binchuan, having two peaks occurred at around 9LT and 20LT, shows little correlation with the well-known Carnegie Curve and other two high-latitude sites' Curves. While strong negative correlation between fair-weather Ez and visual range is found, indicating the variation of fair-weather is dominated by aerosol concentration. The main source of aerosol concentration variation probably sunrise and sunset effect. We support our findings by comparing Ez, visual range with sunrise and sunset times. The peaks (troughs) of Ez (visual range) are proved to have weak correlations with anthropogenic pollution through comparing the Ez, visual range under workdays and holidays.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantitative Characterization of Hyper-Local Atmospheric Greenhouse Gas Sources

Atmospheric greenhouse gas (GHG) emissions are often characterized using stationary, tower-based sensors. Ground based sensors reside in the turbulent boundary layer and are subject to intense concentration impulses from hyper-local (<100m) point sources of emissions. These high frequency spikes are often filtered out in broader emission flux studies, losing valuable information about how hyper-local sources influence receptors. In this study, we investigated how empirical atmospheric data can be used to locate and quantify a concurrently measured hyper-local point source in a dense urban setting. An eddy covariance style tower and a low-cost sensor tower were deployed in various locations around an urban, hyper-local CO2/CH4 emissions source (a continuously measured restaurant exhaust vent). A model using different processing and statistical techniques was built to examine the most effective procedures for source isolation, directional location, and emission quantification. Using excess concentrations above a minimum baseline, we identify the source using bivariate polar plots and quantify the relationship between source size, receptor distance, and statistical proxies. Furthermore, we find that varying statistical thresholds allows for identification of less influential sources which are drowned out by larger or closer sources. Finally, we show that large sources can be effectively characterized using low-cost sensors, a valuable outcome informing how networks for monitoring larger areas could be implemented. This work may provide a basis for source identification and monitoring protocols for networks that feature sensors influenced by hyper-local point sources, subject to site-specific assumptions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerosol Composition, Mixing State, and Phase State of Free Tropospheric Particles and Their Role in Ice Cloud Formation

The prediction of ice cloud formation in the atmosphere remains challenging. Free tropospheric aerosols can act as ice nucleating particles (INPs), affecting cloud properties and precipitation. The physicochemical properties of free tropospheric particles are modified upon long-range transport by different atmospheric processes. These modifications affect the ice formation potential of individual particles. We investigated free tropospheric particles collected at the remote Pico Mountain Observatory at 2225m a.s.l. in the North Atlantic Ocean using multimodal microspectroscopy and chemical imaging techniques. We probed their ice nucleation activity using an ice nucleation stage interfaced with an environmental scanning electron microscope. Retroplume analysis, chemical imaging, and micro-spectroscopy analysis indicated that the size-resolved chemical composition, mixing state, and phase state of the articles with similar aging times but different transport patterns were substantially different. Relative humidity-dependent glass transition temperatures estimated from meteorological conditions were consistent with the observed organic component of the particles' phase. More viscous (solid and semi-solid-like) particles are more ice active in deposition mode at temperature ranging from 205-220 K than those less viscous particles. Finally, this study provides a better understanding of the phase and mixing state of long range transported free tropospheric aerosols and their role in ice cloud formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SPRUCE Precipitation Chemistry and Bulk Atmospheric Deposition Beginning in 2013

This data set reports the chemistry of precipitation water that was collected at the SPRUCE site located in the S1 bog and calculated values of bulk atmospheric deposition of solutes in precipitation. Sample collection and analyses started during December of 2013 and will continue for the duration of the experiment. Precipitation samples were collected year round on an event-basis from up to three individual collectors. Samples were either composited or individually analyzed, depending on the total volume of water available relative to the amount needed to complete all laboratory analyses. Funnel/bottle collectors were used to collect rainfall and buckets were used to collect snowfall and mixed precipitation. Samples were analyzed for pH, specific conductivity, nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen), cation concentrations (calcium, magnesium), anion concentrations (chloride, sulfate), total organic carbon concentrations, and natural-abundance stable isotopes of water (δ18O-H2O and δD-H2O). Bulk deposition was calculated by multiplying rainfall amount by solute concentration for ammonium, nitrate, soluble reactive phosphorus (SRP), total nitrogen, calcium, magnesium, chloride, sulfate, and total organic carbon. All measurements were made at the 8.1-ha S1 bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).

54 ENVIRONMENTAL SCIENCES↗