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DOE OSTI2024

Mechanisms of Polyethylene Terephthalate Pellet Fragmentation into Nanoplastics and Assimilable Carbons by Wastewater Comamonas

Comamonadaceae bacteria are enriched on poly(ethylene terephthalate) (PET) microplastics in wastewaters and urban rivers, but the PET-degrading mechanisms remain unclear. Here, we investigated these mechanisms with Comamonas testosteroniKF-1, a wastewater isolate, by combining microscopy, spectroscopy, proteomics, protein modeling, and genetic engineering. Compared to minor dents on PET films, scanning electron microscopy revealed significant fragmentation of PET pellets, resulting in a 3.5-fold increase in the abundance of small nanoparticles (<100 nm) during 30-day cultivation. Infrared spectroscopy captured primarily hydrolytic cleavage in the fragmented pellet particles. Solution analysis further demonstrated double hydrolysis of a PET oligomer, bis(2-hydroxyethyl) terephthalate, to the bioavailable monomer terephthalate. Supplementation with acetate, a common wastewater co-substrate, promoted cell growth and PET fragmentation. Of the multiple hydrolases encoded in the genome, intracellular proteomics detected only one, which was found in both acetate-only and PET-only conditions. Homology modeling of this hydrolase structure illustrated substrate binding analogous to reported PET hydrolases, despite dissimilar sequences. Mutants lacking this hydrolase gene were incapable of PET oligomer hydrolysis and had a 21% decrease in PET fragmentation; re-insertion of the gene restored both functions. Thus, we have identified constitutive production of a key PET-degrading hydrolase in wastewater Comamonas, which could be exploited for plastic bioconversion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Dynamic Evolution of Mass and Physical Properties of Atmospheric Organic Aerosol under Solar Irradiance

Organic aerosol (OA) particles constitute a substantial fraction of sub-micron particulate mass in the atmosphere and play a critical role in climate system. OA undergoes dynamic aging processes in the atmosphere, with photolytic aging induced by ultraviolet solar irradiance being an important yet poorly characterized mechanism. Knowledge gaps persist regarding the role of volatility transformations during photolytic aging on the OA mass decay kinetics and the evolution of climate-relevant properties, such as hygroscopicity, hindering the model evaluation of OA spatiotemporal distributions and atmospheric budgets. In this study, we conduct isothermal photolytic aging experiments on both laboratory-generated secondary organic aerosols and ambient-collected particles from urban Atlanta, utilizing a high-sensitivity Quartz Crystal Microbalance. Our results reveal that photolytic aging reduces 40–66% of the low-volatility OA mass with lifetimes ranging from 8 to 200 hours under solar irradiance, and 44–92% of the photolytic mass loss is through slow evaporation of semi- or intermediate-volatile products, kinetically limited by their volatility. We observe up to ±50% changes in OA hygroscopicity with the transformation of fresh OA to photo-recalcitrant low-volatility products, associated with changes in oxygen-to-carbon ratio and molecular weight. A kinetic model incorporating photolytic volatility transformation provides a cohesive explanation for the observed photolysis-induced changes in mass, volatility, and hygroscopicity. Our results can help constrain model representation of the dynamic evolutions of mass and climate-relevant properties during photolytic aging processes of the ambient OA, improving our understanding of OA atmospheric behavior and climate impact.

Bai, Bin↗
DOE OSTI2021

Modeling Volatility-Based Aerosol Phase State Predictions in the Amazon Rainforest

Organic aerosol (OA) is a complex matrix of various constituents—fresh (primary organic aerosols—POA) and aged via oxidation (secondary organic aerosols—SOA), generated from biogenic, anthropogenic, and biomass burning sources. The viscosity of OA can be critical in influencing new particle formation, reactive uptake processes that impact evaporation-growth kinetics, and the lifetime of particles in the atmosphere. We report this work utilizes a well-defined relationship between volatility and viscosity for pure compounds, which we incorporated within the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to simulate the phase state and viscosity of bulk OA during the dry-to-wet transition season (September–October) in the Amazon rainforest during 2014. Our simulations indicate spatial and temporal heterogeneity in aerosol phase state often not captured by global-scale models. We show the strong role of water associated with organic aerosol ($w_s$) as the dominant factor that can be used to quantitatively estimate OA viscosity. Analysis of WRF-Chem simulations across the entire atmospheric column indicates a strong inverse log-linear relationship between $w_s$ and OA viscosity with a correlation coefficient approaching 1, in the background and biomass burning-influenced conditions. At high altitudes where relative humidity (RH) and temperatures are low, our simulations indicate that OA exists in a semisolid-/solid-like phase state, consistent with previous studies. OA hygroscopicity is strongly correlated (ca. –0.8) with OA viscosity at RH ca. 30–50%, but this RH range is found mostly at low OA concentrations and the middle troposphere (ca. 6–10 km altitudes) in our simulated domain. OA hygroscopicity is uncorrelated with viscosity at higher-RH (near surface) and lower-RH (upper troposphere) regimes. At the urban site near surface, where day–night differences in RH are significant, RH is found to drive the phase state. At the background forested site near surface, where day–night RH differences are small, biomass burning-influenced OA is semisolid and a significant OA associated with background conditions is liquid-like. Simulations indicate a long tail of OA viscosity frequency distributions extending in the semisolid/solid regimes over background biogenic-influenced conditions due to the role of low-volatility OA components such as monoterpene oxidation products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Low-Rate Cycling Regeneration Sustains NMC811–Graphite Battery Performance through Extreme Ultrafast Charging

Urban air mobility (UAM) systems, such as electric vertical takeoff and landing (eVTOL) aircraft, require batteries capable of extreme ultrafast charging to support high-frequency operations. Here, in this work, we evaluate the electrochemical stability of NMC811–graphite full cells using a complex mixed-modal protocol designed to simulate the aggressive turnaround demands of UAM missions. We demonstrate that incorporating a periodic low-rate (0.3C) “regeneration” cycle enables cells to maintain 96% capacity retention over 900 cycles, despite repeated exposure to ultrafast pulses. To validate the efficacy of this regeneration mechanism, we performed simplified control experiments comparing continuous 10C charging against a 10C–0.3C interleaved protocol. Advanced characterization reveals that while mechanical particle fracture is pervasive at these rates, the regeneration cycles decelerate the electrochemical degradation by resolving spatially heterogeneous Ni oxidation states and relaxing lithium-ion concentration gradients. These findings provide a vital mechanistic framework for battery operation, proving that restorative charging can effectively delay and mitigate failure in demanding UAM applications.

batteries↗
DOE OSTI2025

Nearby Sites Show Similar Upwind Sources and Differing Semivolatile Concentrations in Coastal Aerosol Particles

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized aerosol composition using measurements at two sites within 3 km (Scripps Pier and Mt. Soledad) from 15 February 2023 to 14 February 2024. Comparing the two sites shows the strong influence of upwind sources that results in similar monthly compositions at both sites. The seasonal changes in chemical mass concentrations were largely driven by the upwind source regions, with coastal northwesterly back-trajectories occurring 63−65% of the year and bringing submicrometer mass concentrations that were lower than the EPCAPE average for all trajectories at each site. In contrast, refractory black carbon (rBC) and nonrefractory (NR)-organics and nitrate mass concentrations exceeded EPCAPE average concentrations for back-trajectories from urban areas such as Los Angeles-Long Beach. For hourly measurements, NR-organics and non-sea-salt (NSS)-sulfate mass concentrations at Mt. Soledad were correlated strongly (r = 0.73−0.82) to those measured at Scripps Pier, but NR-nitrate was correlated only moderately (r = 0.63). The explanation for the lower correlation of NR-nitrate is both emissions between the sites and semivolatility, with semivolatility accounting for site-to-site changes in daily averages of +0.01 μg m −3 per percentage site-to-site difference in relative humidity and −0.07 μg m −3 per degree Celsius site-to-site difference in temperature. On average, comparing Scripps Pier to Mt. Soledad, NR-nitrate was higher by 29% because of relative humidity and lower by −26% because of temperature. NR-nitrate and rBC mass concentrations at Scripps Pier for nighttime were 13−15% higher than those for daytime because land breezes brought higher inland concentrations. Concentrations of rBC were 52% higher at Mt. Soledad than those measured at Scripps Pier, accompanied by increases in tracers for brake wear because of traffic on the steep roads within 10 m of that site. The implications are that these nearby sites had comparable monthly concentrations of measured components due to their similar backtrajectories, but hourly and daily concentration differences supported quantification of the meteorological effects from relative humidity and temperature on semivolatile NR-nitrate as well as minor differences from land−sea breezes and local emissions.

Aerosols↗
DOE OSTI2023

Contesting with the Ganges Water Machine in South Asia: Theory versus Reality

Recently, there has been much interest in how to manage the water resources of the Ganges River Basin (GRB), the cradle of Asian civilization, currently supporting >500 million people. This also includes cleaning up the Ganges river, regarded as one of the most polluted mega-rivers of the world. Historically, the transboundary Ganges river and its tributaries, flowing through India, Nepal, and Bangladesh, have become extensively polluted and disrupted, mostly because of river engineering and increased discharge of industrial and urban waste. Compounding the problem, in the past few decades, intense groundwater abstraction from the GRB aquifers has led to unprecedented groundwater level depletion in some locations. At present, the GRB groundwater levels are strongly influenced by depth-dependent abstraction, which is predicted to intensify in the future, given the increasing water demand. Therefore, with impending climate change, designing the coupled river water–groundwater management necessary to meet the goal for sustainable access to clean water for a huge population, has become an arduous challenge.

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

TROPOMI NO 2 in the United States: A Detailed Look at the Annual Averages, Weekly Cycles, Effects of Temperature, and Correlation With Surface NO 2 Concentrations

Abstract Observing the spatial heterogeneities of NO 2 air pollution is an important first step in quantifying NO X emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO 2 pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO 2 columns by day‐of‐the‐week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2‐m temperatures and NO 2 column amounts and find that NO 2 is larger on the hottest days (>32°C) as compared to warm days (26°C–32°C), which is in contrast to a general decrease in NO 2 with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO 2 data to annual surface‐level concentrations yields relatively strong correlation ( R 2 = 0.66). These new developments make TROPOMI NO 2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling Water Quality in Watersheds: From Here to the Next Generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and (peri-)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Will Anthropogenic Warming Increase Evapotranspiration? Examining Irrigation Water Demand Implications of Climate Change in California

Abstract Climate modeling studies and observations do not fully agree on the implications of anthropogenic warming for evapotranspiration (ET), a major component of the water cycle and driver of irrigation water demand. Here, we use California as a testbed to assess the ET impacts of changing atmospheric conditions induced by climate change on irrigated systems. Our analysis of irrigated agricultural and urban regions shows that warmer atmospheric temperatures have minimal implications for ET rates and irrigation water demands—about one percent change per degree Celsius warming (∼1% °C −1 ). By explicitly modeling irrigation, we control for the confounding effect of climate‐driven soil moisture changes and directly estimate water demand implications. Our attribution analysis of the drivers of ET response to global anthropogenic warming shows that as the atmospheric temperature and vapor pressure deficit depart from the ideal conditions for transpiration, regulation of stomata resistance by stressed vegetation almost completely offsets the expected increase in ET rates that would otherwise result from abiotic processes alone. We further show that anthropogenic warming of the atmosphere has minimal implications for mean relative humidity (<1.7% °C −1 ) and the surface available energy (<0.2% °C −1 ), which are critical drivers of ET. This study corroborates the growing evidence that plant physiological changes moderate the degree to which changes in potential ET are realized as actual ET.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Estimation of Possible Primary Biological Particle Emissions and Rupture Events at the Southern Great Plains ARM Site

We use 10 years of data from the Department of Energy (DoE) Atmospheric Radiation Measurements (ARM) United States Southern Great Plains (SGP) site with nearby regional pollen and fungal spore measurements to indirectly estimate the seasonal influence of these two primary biological aerosol particles (PBAP). We estimate possible primary emissions of larger PBAP and PBAP rupture events, which form submicron organic aerosol during precipitation or high relative humidity. High pollen counts at two urban stations near SGP occur during late winter/early spring (day of year (DOY) 50–120) and late summer (DOY 240–310). Around 4–19 days per year show possible pollen events (PPE) when near-surface lidar observations of daily linear particle depolarization ratio >0.1 are coincident with high organic aerosol fraction. For PPE days with rainfall, aerosol size distribution observations show enhanced submicron particle concentrations consistent with pollen rupture events. For fungal spores, high fungal spore counts occur during late spring/early summer (DOY 110–195) and late summer/autumn (DOY 220–340). Based on size distribution observations, up to 7% of days have possible fungal spore rupture events (PFE) with higher aerosol number count specifically over the range expected for fungal spore fragment mobility diameter (20–50 nm). These short-lived PFE correlate with rainfall or occur after prolonged exposure to rainfall (e.g., >10 h). While the SGP site lacks direct measurements of bioaerosol and large particle sizes, this analysis suggests that PBAP primary emissions and rupture events could occur about 32 days per year, representing an important component of the aerosol budget during seasonal emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Determining Spatial Scales of Soil Moisture—Cloud Coupling Pathways Using Semi-Idealized Simulations

The spatial scales of land-atmosphere interactions over heterogeneous, realistic soil moisture patterns are critical to improve our understanding of land-atmosphere interactions. However, these scales are poorly quantified. We use high-resolution numerical experiments to quantify the spatial scales for a selected day during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign in Oklahoma. A semi-idealized approach (removing background winds and surface topography while retaining the real-world data for other boundary conditions) enables examination of the local influence from the surface. Simulations that apply uniform surface, variable land cover with uniform soil moisture, and variable land cover with variable soil moisture are then compared. Land cover variations, especially water and urban surfaces, create two variance peaks in the surface sensible heat flux in the scales >10 km (meso-β) and <6 km (meso-γ). Both peaks are enhanced by the observation-based soil moisture distribution that has most of its variance in the meso-β scale. Atmospheric response in the meso-β scale is hydrostatic with weak vertical motion. The land cover variations induce secondary circulations in the scales of 2.5–6 km. The additional soil moisture variability intensifies extreme circulations over dry soil patches and sharp sensible heat flux gradients, slightly extending the characteristic scales to 2.5–9 km. While their areal coverage is small, soil moisture variations on such “hotspots” lead to substantially larger convective cloud structure and domain-mean rainfall, calling for a consideration of their non-linear effect in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantifying the Value of Technology and Policy Innovation in Water Resource Portfolios

Abstract Recent water infrastructure planning models demonstrate that explicitly accounting for hydrological changes in long‐term water planning reduces costs and increases system robustness. However, current models do not consider the effects of other changes occurring in the system over long time horizons, namely technology and policy innovation. By leveraging state‐of‐the‐art dynamic control techniques, we propose a suite of tools that explicitly relate hydrologic change, technology innovation, and policy interventions to system‐level water costs. We design robust and cost‐optimal strategies for water supply expansion under hydrological variability and hundreds of plausible innovation states, for example, treatment cost and diversification improvements, deployment times, and demand reduction campaigns. Our approach circumvents the need to pre‐assign probabilities to innovation scenarios and, instead, directly calculates the effects of technology, policy, and hydrology variations on system cost and planning strategies to identify avenues of impactful innovation. These tools can support technology development hubs, urban, state, and federal water planners in anticipating cost implications of technology and policy innovation at the local level, and prioritizing high‐impact innovation goals based on quantitative targets. Results for the case study of Santa Barbara, California identify high‐value innovation attributes for the city as well as combinations of innovation attributes across technologies and policies, and quantify their potential utility cost reductions.

13 HYDRO ENERGY↗
DOE OSTI2023

Closing in on Hydrologic Predictive Accuracy: Combining the Strengths of High-Fidelity and Physics-Agnostic Models

Applications of process-based models (PBM) for predictions are confounded by multiple uncertainties and computational burdens, resulting in appreciable errors. A novel modeling framework combining a high-fidelity PBM with surrogate and machine learning (ML) models is developed to tackle these challenges and applied for streamflow prediction. A surrogate model permits high computational efficiency of a PBM solution at a minimum loss of its accuracy. A novel probabilistic ML model partitions the PBM-surrogate prediction errors into reducible and irreducible types, quantifying their distributions that arise due to both explicitly perceived uncertainties (such as parametric) or those that are entirely hidden to the modeler (not included or unexpected). Using this approach, we demonstrate a substantial improvement of streamflow predictive accuracy for a case study urbanized watershed. Such a framework provides an efficient solution combining the strengths of high-fidelity and physics-agnostic models for a wide range of prediction problems in geosciences.

58 GEOSCIENCES↗
DOE OSTI2024

The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

We present a variable-resolution global chemistry-climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban-to-rural chemical regimes, mesoscale convective systems, and land-surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi-decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25-km uniform-resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal-to-diurnal cycles and extremes, notably reducing the central US dry-and-warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process-level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land-biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Toward a Universal Model of Hyporheic Exchange and Nutrient Cycling in Streams

In this paper we demonstrate that several ubiquitous hyporheic exchange mechanisms can be represented simply as a one-dimensional diffusion process, where the diffusivity decays exponentially with depth into the streambed. Based on a meta-analysis of 106 previously published laboratory measurements of hyporheic exchange (capturing a range of bed morphologies, hydraulic conditions, streambed properties, and experimental approaches) we find that the reference diffusivity and mixing length-scale are functions of the permeability Reynolds Number and Schmidt Number. These dimensionless numbers, in turn, can be estimated for a particular stream from the median grain size of the streambed and the stream's depth, slope, and temperature. Application of these results to a seminal study of nitrate removal in 72 headwater streams across the United States, reveals: (a) streams draining urban and agricultural landscapes have a diminished capacity for in-stream and in-bed mixing along with smaller subsurface storage zones compared to streams draining reference landscapes; (b) under steady-state conditions nitrate uptake in the streambed is primarily biologically controlled; and (c) median reaction timescales for nitrate removal in the hyporheic zone are 0.5 and 20 hr for uptake by assimilation and denitrification, respectively. While further research is needed, the simplicity and extensibility of the framework described here should facilitate cross-disciplinary discussions and inform reach-scale studies of pollutant fate and transport and their scale-up to watersheds and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Photolytic Degradation of Water‐Soluble Organic Carbon in Snowmelts: Changes in Molecular Characteristics, Brown Carbon Chromophores, and Radiative Effects

Abstract Water‐soluble organic carbon (WSOC) deposited in ambient snowpack play key roles in regional carbon cycle and surface energy budget, but the impacts of photo‐induced processes on its optical and chemical properties are poorly understood yet. In this study, melted samples of the seasonal snow collected from northern Xinjiang, northwestern China, were exposed to ultraviolet (UV) radiation to investigate the photolytic transformations of WSOC. Molecular characteristics and chemical composition of WSOC and its brown carbon (BrC) constituents were investigated using high‐performance liquid chromatography interfaced with a photodiode array detector and a high‐resolution mass spectrometer. Upon illumination, formation of nitrogen‐ and sulfur‐containing species with high molecular weight was observed in snow samples influenced by soil‐ and plant‐derived organics. In contrast, the representative sample collected from remote region showed the lowest molecular diversity and photolytic reactivity among all samples, in which no identified BrC chromophores decomposed upon illumination. Approximately 65% of chromophores in urban samples endured UV irradiation. However, most of BrC composed of phenolic/lignin‐derived compounds and flavonoids disappeared in the illuminated samples containing WSOC from soil‐ and plant‐related sources. Effects of the photochemical degradation of WSOC on the potential modulation of snow albedo were estimated. Apparent half‐lives of WSOC estimated as albedo reduction in 300–400 nm indicated 0.1–0.4 atmospheric equivalent days, which are shorter than typical photolysis half‐lives of ambient biomass smoke aerosol. This study provides new insights into the roles of WSOC in snow photochemistry and snow surface energy balance.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Remotely Sensed High‐Resolution Soil Moisture and Evapotranspiration: Bridging the Gap Between Science and Society

This paper reviews the current state of high‐resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high‐resolution remote sensing using visible, near‐infrared, thermal‐infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio‐geo‐physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily). Still, the state‐of‐the‐science products have their challenges and limitations, which we detail across data, retrieval algorithms, and applications. We describe the roles of these data in advancing 10 application areas: drought assessment, food security, precision agriculture, soil salinization, wildfire modeling, dust monitoring, flood forecasting, urban water, energy, and ecosystem management, ecohydrology, and biodiversity conservation. We discuss that future scientific advancement should focus on developing open‐access, high‐resolution (3–30 m), sub‐daily SM and ET products, enabling the evaluation of hydrological processes at finer scales and revolutionizing the societal applications in data‐limited regions of the world, especially the Global South for socio‐economic development.

54 ENVIRONMENTAL SCIENCES↗