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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Soil Sensors in Agriculture: From Unsustainable to Biodegradable

Commercially available bi-metallic temperature sensors have long exploited differential thermal expansions between materials to produce an actuation-induced readout from a bi-metal helix. When dispersed in agricultural land, electronic components are used to transmit information at the cost of an increased environmental footprint. This paper briefly recaps the proposed sensor, which employs a biodegradable bi-material helix composed of a polymer and metal. Proposed polymer sheetings of cellulose acetate and polylactic acid are characterized via TGA, DMA, and DSC to evaluate plasticizer content, shrinkage, and an appropriate sensor work-use range. Finally, the deflection of non-biodegradable bi-polymer strips is quantified for various combinations to determine if bi-polymer deflection is possible.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Displacement Analysis of Geothermal Field Based on PSInSAR And SOM Clustering Algorithms A Case Study of Brady Field, Nevada—USA

The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is –19 mm/yr with an average value of –6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NGEE Arctic, Canopy Spectral Reflectance, Utqiagvik (Barrow), Alaska, 2014-2016

Measurements of full-spectrum (i.e. 350-2500 nm) canopy spectral reflectance of Arctic plant species within the BEO, Barrow, Alaska. Spectra were collected using Spectra Vista Corporation (SVC) HR-2014i and Spectral Evolution (SE) PSR+ instruments mounted on a tripod or monopod together with a Spectralon white plate to calibrate each measurement under variable illumination conditions. Data were collected in Utqiagvik (Barrow), Alaska during the 2014 to 2016 period. Data package includes processed spectra (*.csv) files and original instrument output and processing files (*.zip).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗
DOE OSTI2025

Investigation of the Sensitivity of Tropical Cyclogenesis to Aerosol Intervention

Abstract As risks from tropical cyclones (TCs) are fueled by climate change escalation, there is an urgent need for transformational solutions to complement traditional approaches. Seeding TCs using aerosols can be a promising method to reduce cyclone intensity, supported by theoretical understanding of the microphysical effects of aerosols on TC clouds. The ideal time to intervene effectively in TCs is likely during their initial stage, before TC wind speeds reach their peak. However, studies exploring potential aerosol effects on TC formation remain scarce. This study investigates how a TC embryo responds to the addition of aerosols of varying sizes using the Weather Research & Forecasting (WRF) model coupled with a spectral‐bin microphysics model. We found that aerosols of different sizes and concentrations distinctively affect the pre‐TC vortex's microstructure and dynamics. Fine and ultrafine aerosols enhance the latent heat of condensation, freezing, deposition, and riming, initially intensifying the vortex. However, this results in enhancement of the cold pool, thereby reducing inflow and surface fluxes, subsequently weakening the vortex. Coarse aerosols produce the opposite effect to that of fine and ultrafine aerosols. Coarse aerosols lead to a slower initial acceleration owing to enhanced warm rain. However, the resulting weaker cold pool is insufficient to effectively reduce the strength of the vortex at the later stage. This study provides critical insights into how aerosols of varying sizes and concentrations modulate the energy cascade and impact the evolution of a TC embryo, laying the groundwork for further research on TC risk management through aerosol intervention.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effects of Wind Shear and Aerosol Conditions on the Organization of Precipitating Marine Stratocumulus Clouds

Here this study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (N d ). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that N d is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low N d characterizes the open cellular structure with a high in-cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open-cell clouds produce larger and deeper cold pools compared to closed-cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mixotrophic microbes create carbon tipping points under warming

Mixotrophs are ubiquitous and integral to microbial food webs, but their impacts on the dynamics and functioning of broader ecosystems are largely unresolved. Here, we show that mixotrophy produces a unique type of food web module that exhibits unusual ecological dynamics, with surprising consequences for carbon flux under warming. We develop a generalizable model of a mixotrophic food web module that incorporates dynamic switching between phototrophy and phagotrophy to assess ecological dynamics and total system CO 2 flux. We find that warming switches mixotrophic systems between alternative stable carbon states—including a phototrophy-dominant carbon sink state, a phagotrophy-dominant carbon source state and cycling between these two. Moreover, warming always shifts this mixotrophic system from a carbon sink state to a carbon source state, but a coordinated increase in nutrients can erase early warning signals of this transition and expand hysteresis. This suggests that mixotrophs can generate critical carbon tipping points under warming that will be more abrupt and less reversible when combined with increased nutrient levels, having widespread implications for ecosystem functioning in the face of rapid global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Community structure – Ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. In this work, we test these assertions using methane (CH 4 )-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH 4 oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development of a Miniaturized Mobile Mapping System for In-Row, Under-Canopy Phenotyping

This paper focuses on the development of a miniaturized mobile mapping platform with advantages over current agricultural phenotyping systems in terms of acquiring data that facilitate under-canopy plant trait extraction. The system is based on an unmanned ground vehicle (UGV) for in-row, under-canopy data acquisition to deliver accurately georeferenced 2D and 3D products. The paper addresses three main aspects pertaining to the UGV development: (a) architecture of the UGV mobile mapping system (MMS), (b) quality assessment of acquired data in terms of georeferencing information as well as derived 3D point cloud, and (c) ability to derive phenotypic plant traits using data acquired by the UGV MMS. The experimental results from this study demonstrate the ability of the UGV MMS to acquire dense and accurate data over agricultural fields that would facilitate highly accurate plant phenotyping (better than above-canopy platforms such as unmanned aerial systems and high-clearance tractors). Plant centers and plant count with an accuracy in the 90% range have been achieved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Summertime Carbonaceous Aerosol in Interior Versus Coastal Northern Alaska

Abstract Rapid warming is likely increasing primary production and wildfire occurrence in the Arctic. Projected changes in carbonaceous aerosols during the summer will impact atmospheric chemistry and climate, but our understanding of these processes is limited by sparse observations. Here, we characterize carbonaceous aerosol in Alaska, USA: Toolik Field Station in the Interior and the Atmospheric Radiation Measurement facility at Utqiaġvik on the Arctic coast, during the summers of 2022 and 2023. We estimated PM 2.5 and PM 10 concentrations using laser light scattering (PurpleAir sensors) and examined total carbon (TC) and its organic carbon (OC) and elemental carbon (EC) fractions in total suspended particles (TSP). We investigated the dominant sources of carbonaceous aerosol using air mass backward‐trajectories from the NOAA HYSPLIT model and radiocarbon source apportionment of TC. TC concentrations were about twice as high in the Interior compared to the coast, with contemporary sources dominating at both Toolik (95%–99%) and Utqiaġvik (86%–89%) over minor contributions from fossil sources. Elevated PM, TC, OC, and EC concentrations coincided with major boreal forest fire activity in North America that brought smoke to the region. The radiocarbon signature of EC measured at Toolik during these wildfire events indicated that over 90% of the EC came from contemporary sources. Our measurements demonstrate the potential for Arctic aerosol concentrations to respond significantly to climate warming‐induced changes to the landscape and emphasize the need for continuous atmospheric monitoring to advance our understanding of this rapidly changing environment.

Welch, Allison M. [Department of Earth System Scie↗
DOE OSTI2022

Trust and consequences: Role of community science, perceptions, values, and environmental justice in risk communication

Risk communication is often viewed as imparting information and perhaps as a two-way dialogue. Risk communication inadequacies on the part of both “communicator” and “community members” can lead to adverse consequences and amplify environmental justice disparities. The paper suggests a transformational approach where risk communicators must learn to trust community experts and their knowledge base (and act upon it), where risk information imparted by risk communicators addresses what communities are most concerned about (as well as risk from specific chemicals or radionuclides), and where risk information and assessments address underlying issues and disparities, as well as cultural traditions (among others). Providing risk probabilities is no longer sufficient; western science may not be enough, and community and native scientific knowledge is needed. Risk communication (or information transfer) for environmental risks that are ongoing usually applies to low-income, minority communities—people living in dense inner cities, rural communities, Native American communities—or to people living near a risky facility. Communication within this context requires mutual trust, listening and respect, as well as acceptance of indigenous and community knowledge as equally valuable. Examples are given to illustrate a community perspective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Regionalized Life-Cycle Water Impacts of Microalgal-Based Biofuels in the United States

While algal biofuels have the potential to reduce the national reliance on fossil fuels, high water consumption associated with algal biomass cultivation represents a major concern potentially compromising the sustainable commercialization of this technology. This study focuses on quantifying the water footprint (WF) and water scarcity footprint (WSF) of renewable diesel derived from algal biomass and provides insights into where algal cultivation is less water-intensive than traditional ethanol and biodiesel feedstocks. Results are generated with an engineering process model developed to predict the life-cycle water consumption, considering green, blue, and gray water, of algae facilities across the United States at a high spatiotemporal resolution. The total WFs for Florida and Arizona are determined to be 13.1 and 17.6 m 3 GJ –1 , respectively. The blue WF in Arizona is shown to be 8.5 times larger than in Florida, while the green WF is 4.5 times smaller, but when combined into a total WF, there is just a 26% difference between the two locations. The analysis reveals that the total life-cycle WFs of algal renewable diesel are smaller than the optimal WFs of corn ethanol and soybean biodiesel. Algal systems benefit from higher growth rates and offer the opportunity to manage wastewater streams, therefore generating smaller green and gray WFs than those of conventional biofuels. Here, the WSF analysis identifies the Gulf Coast as the most suitable region for algal cultivation, with cultivation in the western US shown to exacerbate local water stress levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Unified Interpretation of Variability in Precipitation Isotope Ratios

Abstract Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here, we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al., we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation ( δ p ) from monthly mean hydrologic variables. The model accurately simulates the spatial and seasonal variability in δ p within a state-of-the-art climate model and permits a simple decomposition of δ p variability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics, δ p is mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation between δ p and temperature (i.e., the temperature effect). At low latitudes, δ p is mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation between δ p and precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by the variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes. Significance Statement The isotopic composition of precipitation has long been used to make inferences about past climates based on its observed relationship with precipitation in the tropics and with temperature at higher latitudes. These relationships—known as the “amount effect” and “temperature effect,” respectively—have been attributed to many different mechanisms, most of which are thought to operate at either high or low latitudes but not both. Here, we present a unified framework for interpreting the isotope variability that can explain the latitude dependence of the temperature and amount effects despite making no distinction between high and low latitudes. Although our results are generally consistent with certain interpretations of the amount effect, they suggest that the temperature effect is widely misunderstood.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A multiscale landscape approach for prioritizing river and stream protection and restoration actions

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Chapter 21: Sustainable Technologies for Seaweed Conversion to Biofuels and Bioproducts

Seaweeds are attractive candidates to supply the future sustainable, photosynthetic, bioenergy feedstocks thanks to their cultivation promise in offshore marine farms, with year-round production, and no external nutrient requirements. Despite this potential, there are significant challenges associated with realizing both the cultivation and harvesting logistics, as well as in developing an efficient conversion platform to fuels and products. Effective and scalable and economically viable conversion processes tailored to a seaweed are discussed in detail and gaps on identified needs for yield and efficiency improvements. Among the conversion processes discussed here, anaerobic fermentation of seaweeds to bioenergy products, including organic acids and biomass, is promising to disrupt the current bioenergy landscape.

anaerobic digestion↗
DOE OSTI2022

Can disposable masks be worn more than once?

Disposable facemasks are a primary tool to prevent the transmission of SARS-COV-2 during the COVID-19 pandemic. However, plastic waste generated from their disposal represents a significant environmental problem that can be reduced by maximizing the service life of disposable masks. We evaluated the effect of repeated wearing on the fitted filtration efficiency (FFE) of N95, KF94, KN95, and procedure/surgical masks. The FFEs of masks were compared following extended wearing with and without washing. Results reveal that most disposable facemasks can retain a high level of their baseline FFE after extended wearing, even after 40 h of wearing. Laundering disposable masks degraded FFE in some instances. We conclude that the durability of disposable facemask performance is considerably longer than their intended single use indication, suggesting that reusing disposable masks is a safe means of reducing plastic waste in the environment.

54 ENVIRONMENTAL SCIENCES↗