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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Comparing Life Histories of the Shortest-Lived Turtle Known (Chicken Turtles, Deirochelys reticularia ) with Long-Lived Blanding's Turtles ( Emydoidea blandingii )

Evolutionary theories predict major differences in life-history trait values of long- and short-lived organisms. Such comparisons have not been possible for chelonians because no shortlived turtle was known until research revealed that chicken turtles (Deirochelys reticularia; DR) have a maximum longevity of 21 yrs. Life-history trait values of DR females are 1) age at maturity of females = 5–6 yrs; 2) clutches per season = 1.6; 3) annual fecundity = 6–8 female eggs per female; 4) average juvenile survivorship from age 1 to maturity = 0.60; and 5) low average annual adult survivorship = 0.66. We compared DR with the very long-lived Blanding’s turtles (Emydoidea blandingii; EB) in Michigan. Over 14 yrs with no mortality (the minimum age at maturity of EB), the maximum potential fecundity produced by a single female embryo and her mature female offspring was 5 female eggs for EB and 1040 eggs for DR. Comparisons of life table output for approximately stable populations of DR and EB resulted in cohort generation times of 7 and 37 yrs, respectively. The life-history prediction that short-lived organisms should produce smaller offspring was not supported. Average wet mass of eggs is 10 g (8.4–11.3 g) for DR and 12 g (10–14 g) for EB; and average wet mass of hatchlings is 7.3 g (6–9 g) for DR and 9.3 g (6–13 g) for EB. Both differences are smaller than expected based on the difference in longevity. Here, short-lived female DR have an unusual tactic of investing in high fecundity and making substantial body sizespecific investment in large eggs, which may reflect why juvenile survivorship had greater influence on population change rates than did adult survivorship. In contrast, adult survivorship had the greatest influence on population change rates of EB. Comparison of cohorts of 1000 female DR and EB hatchlings highlights the differences in life histories of short- and long-lived turtles: all DR would be dead by the time the last female EB had reached maturity at 21 yrs of age.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Measurement of Volatile Compounds for Real-Time Analysis of Soil Microbial Metabolic Response to Simulated Snowmelt

Snowmelt dynamics are a significant determinant of microbial metabolism in soil and regulate global biogeochemical cycles of carbon and nutrients by creating seasonal variations in soil redox and nutrient pools. With an increasing concern that climate change accelerates both snowmelt timing and rate, obtaining an accurate characterization of microbial response to snowmelt is important for understanding biogeochemical cycles intertwined with soil. However, observing microbial metabolism and its dynamics non-destructively remains a major challenge for systems such as soil. Microbial volatile compounds (mVCs) emitted from soil represent information-dense signatures and when assayed non-destructively using state-of-the-art instrumentation such as Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) provide time resolved insights into the metabolism of active microbiomes. In this study, we used PTR-TOF-MS to investigate the metabolic trajectory of microbiomes from a subalpine forest soil, and their response to a simulated wet-up event akin to snowmelt. Using an information theory approach based on the partitioning of mutual information, we identified mVC metabolite pairs with robust interactions, including those that were non-linear and with time lags. The biological context for these mVC interactions was evaluated by projecting the connections onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) network of known metabolic pathways. Simulated snowmelt resulted in a rapid increase in the production of trimethylamine (TMA) suggesting that anaerobic degradation of quaternary amine osmo/cryoprotectants, such as glycine betaine, may be important contributors to this resource pulse. Unique and synergistic connections between intermediates of methylotrophic pathways such as dimethylamine, formaldehyde and methanol were observed upon wet-up and indicate that the initial pulse of TMA was likely transformed into these intermediates by methylotrophs. Increases in ammonia oxidation signatures (transformation of hydroxylamine to nitrite) were observed in parallel, and while the relative role of nitrifiers or methylotrophs cannot be confirmed, the inferred connection to TMA oxidation suggests either a direct or indirect coupling between these processes. Overall, it appears that such mVC time-series from PTR-TOF-MS combined with causal inference represents an attractive approach to non-destructively observe soil microbial metabolism and its response to environmental perturbation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Application Potential of a Dew-Point Cooling Tower in Selected Energy Intensive Applications in Temperate Climate

In the article, the application potential of the dew-point cooling tower (DPCT) in selected energy-intensive applications in temperate climates was analyzed and discussed. The applications selected for analysis are power generation with natural gas turbines and chilled water air conditioning systems. The study is based on a mathematical model derived from a modified ε-NTU model. The model was validated against experimental results and showed satisfactory agreement with the experimental data. DPCT was compared with a typical cooling tower limited by the wet-bulb temperature (wet-bulb cooling tower, WBCT). The simulation results showed that DPCT is able to provide significant energy savings in energy-intensive applications; therefore, its application potential in temperate climates can be considered justified. In the case of gas turbines, DPCT was able to generate 2 to 10 percentage points more capacity than operating on outdoor air and 1.8 to 5 percentage points more than operating with WBCT. In the case of air conditioning systems, the system equipped with DPCT achieved EERs (energy efficiency ratios) higher by 1 to 7.2 compared to dry cooling and by 0.3 to 5.1 compared to systems equipped with WBCT. The annual energy savings obtained by the system with DPCT were 14.7 MWh compared to WBCT and 30 MWh compared to dry cooling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Implementation and Performance Evaluation of a Community-Scale Adobe Evaporative Cooling Chamber for Vegetable Preservation

The construction of evaporative coolers in remote areas can increase the longevity of vegetables, improving food security and the local economy of small farmers in remote, impoverished communities without access to electricity. This work presents a 1:1 scale prototype of an 8 m 3 (2.1 × 2.1 × 2.3 m) stabilized adobe evaporative cooler, with a design based on the appropriate technology framework, and it was built as a chamber using double adobe walls, filled with wet sand, to induce evaporative cooling. Furthermore, the paper presents the prototype’s performance evaluation. The tests were carried out in the dry and wet states, with different volumes of water. The results show good performance compared with other prototypes, although the optimum watering volume could not be determined because of the high climate variance (outside temperature and humidity) that prevented the repetition of the experiments in identical operating conditions. Stabilized adobe proved to be a good choice for use in the cooler, even when subject to moisture accumulation, indicating an estimated long lifetime for the cooler. The data obtained about the efficiency of evaporative cooling show that the cooler, as expected, has its best performance on the hottest and driest days, reducing the internal temperature (up to 13.24 °C) and managing to keep the internal humidity. The cost, efficiency, durability, and replicability make the proposed evaporative cooler a feasible solution for food preservation.

42 ENGINEERING↗
DOE OSTI2020

Restoring Pre-Industrial CO2 Levels While Achieving Sustainable Development Goals

Unless humanity achieves United Nations Sustainable Development Goals (SDGs) by 2030 and restores the relatively stable climate of pre-industrial CO2 levels (as early as 2140), species extinctions, starvation, drought/floods, and violence will exacerbate mass migrations. This paper presents conceptual designs and techno-economic analyses to calculate sustainable limits for growing high-protein seafood and macroalgae-for-biofuel. We review the availability of wet solid waste and outline the mass balance of carbon and plant nutrients passing through a hydrothermal liquefaction process. The paper reviews the availability of dry solid waste and dry biomass for bioenergy with CO2 capture and storage (BECCS) while generating Allam Cycle electricity. Sufficient wet-waste biomass supports quickly building hydrothermal liquefaction facilities. Macroalgae-for-biofuel technology can be developed and straightforwardly implemented on SDG-achieving high protein seafood infrastructure. The analyses indicate a potential for (1) 0.5 billion tonnes/yr of seafood; (2) 20 million barrels/day of biofuel from solid waste; (3) more biocrude oil from macroalgae than current fossil oil; and (4) sequestration of 28 to 38 billion tonnes/yr of bio-CO2. Carbon dioxide removal (CDR) costs are between 25–33% of those for BECCS with pre-2019 technology or the projected cost of air-capture CDR.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sensitivity Analysis of Fluid–Fluid Interfacial Area, Phase Saturation and Phase Connectivity on Relative Permeability Estimation Using Machine Learning Algorithms

Recent studies have shown that relative permeability can be modeled as a state function which is independent of flow direction and dependent upon phase saturation (S), phase connectivity (X), and fluid–fluid interfacial area (A). This study evaluates the impact of each of the three state parameters (S, X, and A) in the estimation of relative permeability. The relative importance of the three state parameters in four separate quadrants of S-X-A space was evaluated using a machine learning algorithm (out-of-bag predictor importance method). The results show that relative permeability is sensitive to all the three parameters, S, X, and A, with varying magnitudes in each of the four quadrants at a constant value of wettability. We observe that the wetting-phase relative permeability is most sensitive to saturation, while the non-wetting phase is most sensitive to phase connectivity. Although the least important, fluid–fluid interfacial area is still important to make the relative permeability a more exact state function.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Modeling the Effects of Global Change on Ecosystem Processes in a Tropical Rainforest

Ongoing land-use change and climate change in wet tropical forests can potentially drive shifts in tree species composition, representing a change in individual species within a functional group, tropical evergreen trees. The impacts on the global carbon cycle are potentially large, but unclear. We explored the differential effects of species within this functional group, in comparison with the effects of climate change, using the Century model as a research tool. Simulating effects of individual tree species on biome-level biogeochemical cycles constituted a novel application for Century. Background and Objectives: A unique, long-term, replicated field experiment containing five evergreen tree species in monodominant stands under similar environmental conditions in a Costa Rican wet forest provided data for model evaluation. Our objectives were to gain insights about this forest’s biogeochemical cycles and effects of tree species within this functional group, in comparison with climate change. Materials and Methods: We calibrated Century, using long-term meteorological, soil, and plant data from the field-based experiment. In modeling experiments, we evaluated effects on forest biogeochemistry of eight plant traits that were both observed and modeled. Climate-change simulation experiments represented two climate-change aspects observed in this region. Results: Model calibration revealed that unmodeled soil processes would be required to sustain observed P budgets. In species-traits experiments, three separate plant traits (leaf death rate, leaf C:N, and allocation to fine roots) resulted in modeled biomass C stock changes of >50%, compared with a maximum 21% change in the climate-change experiments. Conclusions: Modeled ecosystem properties and processes in Century were sensitive to changes in plant traits and nutrient limitations to productivity. Realistic model output was attainable for some species, but unusual plant traits thwarted predictions for one species. Including more plant traits and soil processes could increase realism, but less-complex models provide an accessible means for exploring plant-soil-atmosphere interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A “Graft to” Electrospun Zwitterionic Bilayer Membrane for the Separation of Hydraulic Fracturing-Produced Water via Membrane Distillation

Simultaneous fouling and pore wetting of the membrane during membrane distillation (MD) is a major concern. In this work, an electrospun bilayer membrane for enhancing fouling and wetting resistance has been developed for treating hydraulic fracture-produced water (PW) by MD. These PWs can contain over 200,000 ppm total dissolved solids, organic compounds and surfactants. The membrane consists of an omniphobic surface that faces the permeate stream and a hydrophilic surface that faces the feed stream. The omniphobic surface was decorated by growing nanoparticles, followed by silanization to lower the surface energy. An epoxied zwitterionic polymer was grafted onto the membrane surface that faces the feed stream to form a tight antifouling hydration layer. The membrane was challenged with an aqueous NaCl solution containing sodium dodecyl sulfate (SDS), an ampholyte and crude oil. In the presence of SDS and crude oil, the membrane was stable and displayed salt rejection (>99.9%). Further, the decrease was much less than the base polyvinylidene difluoride (PVDF) electrospun membrane. The membranes were also challenged with actual PW. Our results highlight the importance of tuning the properties of the membrane surface that faces the feed and permeate streams in order to maximize membrane stability, flux and salt rejection.

omniphobic↗
DOE OSTI2022

Soil Metabolomics Predict Microbial Taxa as Biomarkers of Moisture Status in Soils from a Tidal Wetland

We present observations from a laboratory-controlled study on the impacts of extreme wetting and drying on a wetland soil microbiome. Our approach was to experimentally challenge the soil microbiome to understand impacts on anaerobic carbon cycling processes as the system transitions from dryness to saturation and vice-versa. Specifically, we tested for impacts on stress responses related to shifts from wet to drought conditions. We used a combination of high-resolution data for small organic chemical compounds (metabolites) and biological (community structure based on 16S rRNA gene sequencing) features. Using a robust correlation-independent data approach, we further tested the predictive power of soil metabolites for the presence or absence of taxa. Here, we demonstrate that taking an untargeted, multidimensional data approach to the interpretation of metabolomics has the potential to indicate the causative pathways selecting for the observed bacterial community structure in soils.

16S rRNA gene↗
DOE OSTI2023

Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

Barajas-Olalde, César↗
DOE OSTI2025

Wettability of Two-Dimensional Carbon Allotropes from Molecular Simulations

Force-field Monte Carlo and Molecular Dynamics simulations are used to compare wetting behaviors of model carbon sheets mimicking neat graphene, its saturated derivative, graphane, and related planar allotropes penta-graphene, γ-graphyne, and ψ-graphene in contact with aqueous droplets or an aqueous film confined between parallel carbon sheets. Atomistic and area-integrated surface/water potentials are found to be essentially equivalent in capturing moderate differences between the wetting free energies of tested substrates. Despite notable differences in mechanical and electric properties of distinct allotropes, the predicted allotrope/water contact angles span a narrow window of weakly hydrophilic values. Contact angles in the range of 80 ± 10° indicate modest hydration repulsion incapable of competing with van der Waals attraction between carbon particles. Poor dispersibility in neat water is hence a common feature of studied materials.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map

Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery

Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (p < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, p < 0.001, D = 0.99; KS test 2019 vs. 2021, p < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.

Barker, Matthew I. (ORCID:0000000252864930)↗
DOE OSTI2020

MicroRNAs as diagnostic and prognostic biomarkers of age-related macular degeneration: advances and limitations

A main cause of vision loss in the elderly is age-related macular degeneration (AMD). Among the cellular, biochemical, and molecular changes linked to this disease, inflammation and angiogenesis appear as being crucial in AMD pathogenesis and progression. There are two forms of the disease: dry AMD, accounting for 80–90% of cases, and wet AMD. The disease usually begins as dry AMD associated with retinal pigment epithelium and photoreceptor degeneration, whereas wet AMD is associated with choroidal neovascularization resulting in severe vision impairment. The new vessels are largely malformed, leading to blood and fluid leakage within the disrupted tissue, which provokes inflammation and scar formation and results in retinal damage and detachment. MicroRNAs are dysregulated in AMD and may facilitate the early detection of the disease and monitoring disease progression. Two recent reviews of microRNAs in AMD had indicated weaknesses or limitations in four earlier investigations. Studies in the last three years have shown considerable progress in overcoming some of these concerns and identifying specific microRNAs as biomarkers for AMD. Further large-scale studies are warranted using appropriate statistical methods to take into account gender and age disparity in the study populations and confounding factors such as smoking status.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

MicroRNAs in laser-induced choroidal neovascularization in mice and rats: their expression and potential therapeutic targets

Choroidal neovascularization characterizes wet age-related macular degeneration. Choroidal neovascularization formation involves a primarily angiogenic process that is combined with both inflammation and proteolysis. A primary cause of choroidal neovascularization pathogenesis is alterations in pro- and anti-angiogenic factors derived from the retinal pigment epithelium, with vascular endothelium growth factor being mainly responsible for both clinical and experimental choroidal neovascularization. MicroRNAs (miRNAs) which are short, non-coding, endogenous RNA molecules have a major role in regulating various pathological processes, including inflammation and angiogenesis. A review of recent studies with the mouse laser-induced choroidal neovascularization model has shown alterations in miRNA expression in choroidal neovascularization tissues and could be potential therapeutic targets for wet age-related macular degeneration. Upregulation of miR-505 (days 1 and 3 post-laser), miR-155 (day 14) occurred in retina; miR-342-5p (days 3 and 7), miR-126-3p (day 14) in choroid; miR-23a, miR-24, miR-27a (day 7) in retina/choroid; miR-505 (days 1 and 3) in retinal pigment epithelium/choroid; downregulation of miR-155 (days 1 and 3), miR-29a, miR-29b, miR-29c (day 5), miR-93 (day 14), miR-126 (day 14) occurred in retinal pigment epithelium/choroid. Therapies using miRNA mimics or inhibitors were found to decrease choroidal neovascularization lesions. Choroidal neovascularization development was reduced by overexpression of miR-155, miR-188-5p, miR-(5,B,7), miR-126-3p, miR-342-5p, miR-93, miR-126, miR-195a-3p, miR24, miR-21, miR-31, miR-150, and miR-184, or suppression of miR-505, miR-126-3p, miR155, and miR-23/27. Further studies are warranted to determine miRNA expression in mouse laser-induced choroidal neovascularization models in order to validate and extend the reported findings. Important experimental variables need to be standardized; these include the strain and age of animals, gender, number and position of laser burns to the eye, laser parameters to induce choroidal neovascularization lesions including wavelength, power, spot size, and duration.

therapeutic targets↗
DOE OSTI2020

Model bias in simulating major chemical components of PM 2.5 in China

High concentrations of PM 2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) in China have caused severe visibility degradation. Accurate simulations of PM 2.5 and its chemical components are essential for evaluating the effectiveness of pollution control strategies and the health and climate impacts of air pollution. In this study, we compared the GEOS-Chem model simulations with comprehensive datasets for organic aerosol (OA), sulfate, nitrate, and ammonium in China. Model results are evaluated spatially and temporally against observations. The new OA scheme with a simplified secondary organic aerosol (SOA) parameterization significantly improves the OA simulations in polluted urban areas, highlighting the important contributions of anthropogenic SOA from semivolatile and intermediate-volatility organic compounds. The model underestimates sulfate and overestimates nitrate for most of the sites throughout the year. More significant underestimation of sulfate occurs in winter, while the overestimation of nitrate is extremely large in summer. The model is unable to capture some of the main features in the diurnal pattern of the PM 2.5 chemical components, suggesting inaccuracies in the presented processes. Potential model adjustments that may lead to a better representation of the boundary layer height, the precursor emissions, hydroxyl radical concentrations, the heterogeneous formation of sulfate and nitrate, and the wet deposition of nitric acid and nitrate have been tested in the sensitivity analysis. The results show that uncertainties in chemistry perhaps dominate the model biases. The proper implementation of heterogeneous sulfate formation and the good estimates of the concentrations of sulfur dioxide, hydroxyl radical, and aerosol liquid water are essential for the improvement of the sulfate simulation. The update of the heterogeneous uptake coefficient of nitrogen dioxide significantly reduces the modeled concentrations of nitrate. However, the large overestimation of nitrate concentrations remains in summer for all tested cases. The possible bias in the chemical production and the wet deposition of nitrate cannot fully explain the model overestimation of nitrate, suggesting issues related to the atmospheric removal of nitric acid and nitrate. A better understanding of the atmospheric nitrogen budget, in particular, the role of the photolysis of particulate nitrate, is needed for future model developments. Moreover, the results suggest that the remaining underestimation of OA in the model is associated with the underrepresented production of SOA.

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

Aerosol responses to precipitation along North American air trajectories arriving at Bermuda

North American pollution outflow is ubiquitous over the western North Atlantic Ocean, especially in winter, making this location a suitable natural laboratory for investigating the impact of precipitation on aerosol particles along air mass trajectories. We take advantage of observational data collected at Bermuda to seasonally assess the sensitivity of aerosol mass concentrations and volume size distributions to accumulated precipitation along trajectories (APT). The mass concentration of particulate matter with aerodynamic diameter less than 2.5 µm normalized by the enhancement of carbon monoxide above background (PM 2.5 /ΔCO) at Bermuda was used to estimate the degree of aerosol loss during transport to Bermuda. Results for December–February (DJF) show that most trajectories come from North America and have the highest APTs, resulting in a significant reduction (by 53 %) in PM 2.5 /ΔCO under high-APT conditions (> 13.5 mm) relative to low-APT conditions (< 0.9 mm). Moreover, PM 2.5 /ΔCO was most sensitive to increases in APT up to 5 mm (–0.044 µg m –3 ppbv –1 mm –1 ) and less sensitive to increases in APT over 5 mm. While anthropogenic PM 2.5 constituents (e.g., black carbon, sulfate, organic carbon) decrease with high APT, sea salt, in contrast, was comparable between high- and low-APT conditions owing to enhanced local wind and sea salt emissions in high-APT conditions. The greater sensitivity of the fine-mode volume concentrations (versus coarse mode) to wet scavenging is evident from AErosol RObotic NETwork (AERONET) volume size distribution data. A combination of GEOS-Chem model simulations of the 210 Pb submicron aerosol tracer and its gaseous precursor 222 Rn reveals that (i) surface aerosol particles at Bermuda are most impacted by wet scavenging in winter and spring (due to large-scale precipitation) with a maximum in March, whereas convective scavenging plays a substantial role in summer; and (ii) North American 222 Rn tracer emissions contribute most to surface 210 Pb concentrations at Bermuda in winter (~75 %–80 %), indicating that air masses arriving at Bermuda experience large-scale precipitation scavenging while traveling from North America. A case study flight from the ACTIVATE field campaign on 22 February 2020 reveals a significant reduction in aerosol number and volume concentrations during air mass transport off the US East Coast associated with increased cloud fraction and precipitation. These results highlight the sensitivity of remote marine boundary layer aerosol characteristics to precipitation along trajectories, especially when the air mass source is continental outflow from polluted regions like the US East Coast.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗