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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Surface Water Microbial Community Response to the Biocide 2,2-Dibromo-3-Nitrilopropionamide, Used in Unconventional Oil and Gas Extraction

Production of unconventional oil and gas continues to rise, but the effects of high-density hydraulic fracturing (HF) activity near aquatic ecosystems are not fully understood. A commonly used biocide in HF, 2,2-dibromo-3-nitrilopropionamide (DBNPA), was studied in microcosms of HF-impacted (HF+) versus HF-unimpacted (HF-) surface water streams to (i) compare the microbial community response, (ii) investigate DBNPA degradation products based on past HF exposure, and (iii) compare the microbial community response differences and similarities between the HF biocides DBNPA and glutaraldehyde. The microbial community responded to DBNPA differently in HF-impacted versus HF-unimpacted microcosms in terms of the number of 16S rRNA gene copies quantified, alpha and beta diversity, and differential abundance analyses of microbial community composition through time. The differences in microbial community changes affected degradation dynamics. HF-impacted microbial communities were more sensitive to DBNPA, causing the biocide and by-products of the degradation to persist for longer than in HF-unimpacted microcosms. A total of 17 DBNPA by-products were detected, many of them not widely known as DBNPA by-products. Many of the brominated by-products detected that are believed to be uncharacterized may pose environmental and health impacts. Similar taxa were able to tolerate glutaraldehyde and DBNPA; however, DBNPA was not as effective for microbial control, as indicated by a smaller overall decrease of 16S rRNA gene copies/ml after exposure to the biocide, and a more diverse set of taxa was able to tolerate it. These findings suggest that past HF activity in streams can affect the microbial community response to environmental perturbation such as that caused by the biocide DBNPA. IMPORTANCE Unconventional oil and gas activity can affect pH, total organic carbon, and microbial communities in surface water, altering their ability to respond to new environmental and/or anthropogenic perturbations. These findings demonstrate that 2,2-dibromo-3-nitrilopropionamide (DBNPA), a common hydraulic fracturing (HF) biocide, affects microbial communities differently as a consequence of past HF exposure, persisting longer in HF-impacted (HF+) waters. These findings also demonstrate that DBNPA has low efficacy in environmental microbial communities regardless of HF impact. These findings are of interest, as understanding microbial responses is key for formulating remediation strategies in unconventional oil and gas (UOG)-impacted environments. Moreover, some DBNPA degradation by-products are even more toxic and recalcitrant than DBNPA itself, and this work identifies novel brominated degradation by-products formed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Machine Learning Bias Correction on Large–Scale Environment of High–Impact Weather Systems in E3SM Atmosphere Model

Large–scale dynamical and thermodynamical processes are common environmental drivers of high–impact weather systems causing extreme weather events. However, such large–scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high–impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large–scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ~1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high–impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large–scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias–corrected large–scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large–scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large–scale storm environments simulated by low–resolution climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Root and Leaf Traits of Alfalfa Exhibit Distinct Responses to Soil Microbial Communities and Environmental Stresses

Ongoing climate change is negatively impacting crop productivity globally. Past research has highlighted that a diverse soil microbial community and variation in plant traits for resource acquisition can mitigate the negative impacts of climate change factors on crop productivity. This study investigates the effects of two major environmental stressors—drought and salinity stress, on plant productivity, biomass allocation, and root and leaf trait responses under distinct soil microbial diversities. Our results showed that salinity stress had stronger negative impacts on plant productivity than drought stress. Shoot biomass decreased by 30% and 32.5% under drought and salinity stress, respectively, whereas the root biomass decreased by 32% only under salinity stress. Soil microbial diversity did not affect plant productivity. Next, root traits were mainly impacted by drought and salinity stress, whereas leaf traits were impacted by both environmental stresses and soil microbial diversity. Specific root length and specific root area decreased under drought, and root tissue density was minimal under salinity stress. Root traits were not affected by soil microbial communities. In contrast, the leaf nitrogen content increased, whereas pheophytin content (a breakdown product of chlorophyll) decreased when plants were grown in diverse microbial communities under environmental stresses, especially drought. These results highlight the importance of soil microbial diversity in impacting plant traits in response to environmental stresses. We showed that the soil microbial diversity influences both aboveground and belowground plant traits, indicating the need for better management practices to conserve and promote soil microbial diversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The efficacy and ecological impact of mercury sorbents on the physiology and reproductive fitness of Daphnia magna

Environmental mercury (Hg) contamination threatens ecosystems due to its bioaccumulation and toxicity. Effective and sustainable remediation strategies are essential, with carbon-based sorbents like biochar (BC) and activated carbon (AC) gaining attention for their high adsorption capacity and cost-effectiveness. However, their ecological impacts remain poorly understood. This study evaluates the Hg removal efficacy and ecological effects of three sorbents—BC, granular AC (GAC), and AC fiber (ACF)—in a flow-through column system with and without Hg additions. We tested Hg removal at two concentrations (1 and 4 µg/L Hg) and assessed chronic exposure effects on a sentinel and sensitive freshwater organism, Daphnia magna, over 30 days of exposure to the columns’ effluent. GAC removed 100 % of Hg, while BC and ACF achieved 99 % removal. The ACF + 4 µg/L Hg effluent induced 70 % lethality in D. magna after nearly three weeks of exposure, while the GAC effluent significantly reduced fecundity, even in the absence of Hg exposure. In contrast, the BC effluent enhanced reproductive output, likely due to inputs of carbon and nitrogen in the effluent. These findings highlight the need to balance Hg removal efficacy with ecological safety, emphasizing the importance of considering both remediation effectiveness and potential environmental impacts.

Activated carbon↗
DOE OSTI2022

Achieving American Leadership in the Grid Storage Supply Chain Factsheet

To meet growing demand for long duration energy storage, domestic manufacturing will have to increase significantly. The use of renewables is rapidly increasing, and the adaption of electric vehicles is on the rise, which will require the national grid to not only produce and deliver electricity, but also store it reliably and cost-effectively. The International Energy Agency (IEA) recently released a report showing that to reach a goal of net-zero emissions by 2050, grid storage will need to grow to almost 2,500 gigawatt hours (GWh) in less than a decade. Currently, across the globe, battery technologies provide over 30 GWh of grid storage(BloombergNEF, 2020) while pumped storage hydropower (PSH)provides 160 gigawatts (GW) of long-duration energy storage (LDES) (PSH) (U.S. Department of Energy, 2020). This fact sheet summarizes strategies to address key vulnerabilities in the grid storage supply chain, the United States. These strategies include: • Developing domestic, sustainable manufacturing and recycling capabilities along the energy storage supply chain. • Maximizing the use of domestic resources by focusing on second-life and recycling technologies. • Enabling the diversification and deployment of grid storage technologies through targeted research activities. Addressing these opportunities will have significant impacts with respect to increasing well-paying skilled domestic jobs, improving the gross domestic product (GDP), and ensuring minimal environmental and climate impacts.

Source record↗
DOE OSTI2021

Energize: An Interactive Evaluation Tool for Engaging the General Public with Energy Decision Making - Final Report

The public has an ever-increasing interest in the economic, environmental, and social impacts of global energy production. To support informed decision making, the scientific community has a responsibility to communicate reliable and straight-forward information to the general public, in an engaging way, regarding energy systems and how choices made at different stages of an energy technology life cycle can impact the cost, amount of materials used, and waste produced. Our objective is to enhance public engagement via an interactive electrical energy game (Energ!ze) through which players interact with one another in their quest to develop an electrical energy portfolio that optimizes economic (e.g., company profit), environmental (e.g., reduced CO 2 emissions), and social (e.g., public opinion) impacts. The design and development of Energ!ze was an iterative process involving an interdisciplinary team of engineers, discipline-based scientists, computer scientists, and education experts. The development objectives were two-fold: (1) Accurate and quantifiable modeling of electrical energy systems and (2) Engaging and interactive user interface within the construct of the game narrative. The major game mechanics in the current playable Energ!ze version focus on economic metrics, and the database is scaffolded to add environmental and social metrics for future versions. This report details the outcome of the funding period (Section 2 and 3) and describes the development process, along with recommendations for future development (Section 4).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Precipitation trends determine future occurrences of compound hot–dry events

Compound hot–dry events—co-occurring hot and dry extremes—frequently cause damages to human and natural systems, often exceeding separate impacts from heatwaves and droughts. Strong increases in the occurrence of these events are projected with warming, but associated uncertainties remain large and poorly understood. Here, using climate model large ensembles, we show that mean precipitation trends exclusively modulate the future occurrence of compound hot–dry events over land. This occurs because local warming will be large enough that future droughts will always coincide with at least moderately hot extremes, even in a 2°C warmer world. By contrast, precipitation trends are often weak and equivocal in sign, depending on the model, region and internal climate variability. Therefore, constraining regional precipitation trends will also constrain future compound hot–dry events. These results help to assess future frequencies of other compound extremes characterized by strongly different trends in the drivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Grassland ecosystem type drives AM fungal diversity and functional guild distribution in North American grasslands

Nutrient exchange forms the basis of the ancient symbiotic relationship that occurs between most land plants and arbuscular mycorrhizal (AM) fungi. Plants provide carbon (C) to AM fungi and fungi provide the plant with nutrients such as nitrogen (N) and phosphorous (P). Nutrient addition can alter this symbiotic coupling in key ways, such as reducing AM fungal root colonization and changing the AM fungal community composition. However, environmental parameters that differentiate ecosystems and drive plant distribution patterns (e.g., pH, moisture), are also known to impact AM fungal communities. Identifying the relative contribution of environmental factors impacting AM fungal distribution patterns is important for predicting biogeochemical cycling patterns and plant-microbe relationships across ecosystems. Here, to evaluate the relative impacts of local environmental conditions and long-term nutrient addition on AM fungal abundance and composition across grasslands, we studied experimental plots amended for 10 years with N, P, or N and P fertilizer in different grassland ecosystem types, including tallgrass prairie, montane, shortgrass prairie, and desert grasslands. Contrary to our hypothesis, we found ecosystem type, not nutrient treatment, was the main driver of AM fungal root colonization, diversity, and community composition, even when accounting for site-specific nutrient limitations. We identified several important environmental drivers of grassland ecosystem AM fungal distribution patterns, including aridity, mean annual temperature, root moisture, and soil pH. This work provides empirical evidence for niche partitioning strategies of AM fungal functional guilds and emphasizes the importance of long-term, large scale research projects to provide ecologically relevant context to nutrient addition studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Coal-dependent Communities in Transition: Identifying Best Practices to Ensure Equitable Outcomes

The U.S. coal industry is experiencing a sharp increase in the numbers of retired and/or decommissioned coal-fired power plants across the U.S. In the years between 2010-2019, around 102 gigawatts (GW) of coal-fired generating capacity has been announced to be decommissioned, representing more than 546 coal-fired power plant units, and an additional 17 GW is planned to be decommissioned by 2025. This change in the energy production landscape presents an impact on the social, environmental, and economic prospects of coal-dependent communities. This report examined the role of communities in the coal power plant decommissioning process and provided community-identified best practices to ensure an equitable process. The experiences of four coal-dependent communities—Wise County, VA, Muskegon, MI, Anderson County, TN, and Becker, MN—are presented as case studies to understand the impacts of the decommissioning process, and associated best practices, from the communities’ perspective. The report results highlight the need to recognize that the decommissioning decision-making process must be community-based to be equitable. Each community’s input is key to the transition away from coal power because there is no one-size-fits-all development plan. In other words, each community’s trajectory through the decommissioning process—from the retirement decision-making stage to the final site redevelopment phase—is unique because each community has distinct needs and wants from the energy transition. What is best for one community may not be suited for another. Ultimately, the framework for site development and community revitalization post-decommissioning cannot be universal because each community’s profile—from a social, cultural, and economic perspective—is different. Community impacts of power plant decommissioning are not limited to job and revenue losses. Communities are likely to be impacted culturally, socially, environmentally, and have long-term health-based impacts that should be acknowledged and addressed in post-retirement plans. Commonly identified decommissioning best practices include: Early and continued engagement throughout, with a number of mediums for communication and feedback (e.g., in-person sessions, virtual meetings, written comment opportunities); Early planning of post-decommissioning projects to replace lost jobs, revenue, and economic activity; Recognition (and mitigation, if possible) of social impacts on the community due to plant closure; Transparency throughout the process, with trusted information being provided about the decommissioning process and timeline; potential impacts on the workforce, economy, and environment; and the feasibility of alternative site uses; Identification of funding sources, technical experts, and/or strategic partnerships to support decommissioning and the affected communities upfront; and, Acknowledgment of communities as stakeholders who have a role in the conversation and right to determine their futures. Three key areas for assisting coal-dependent communities affected by the energy transition: Technical assistance: assessment of site feasibility for alternative uses or to repower with new technologies; Cross-partnership engagement and collaboration: facilitate knowledge-sharing of “lessons learned” about the decommissioning process between communities and provide guidance for decision-making processes; and, Financial assistance: access to grant and/or loan programs to assist with redevelopment survey, bolster community economic security through job creation, and cover environmental clean-up costs. Technical assistance, cross-partnership engagement, and financial aid can be mobilized to help communities throughout various stages of the decommissioning process, including the retirement decision, the site reclamation phase, and eventual revitalization of the site and surrounding community.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Forest fire threatens global carbon sinks and population centres under rising atmospheric water demand

Levels of fire activity and severity that are unprecedented in the instrumental record have recently been observed in forested regions around the world. Using a large sample of daily fire events and hourly climate data, here we show that fire activity in all global forest biomes responds strongly and predictably to exceedance of thresholds in atmospheric water demand, as measured by maximum daily vapour pressure deficit. The climatology of vapour pressure deficit can therefore be reliably used to predict forest fire risk under projected future climates. We find that climate change is projected to lead to widespread increases in risk, with at least 30 additional days above critical thresholds for fire activity in forest biomes on every continent by 2100 under rising emissions scenarios. Escalating forest fire risk threatens catastrophic carbon losses in the Amazon and major population health impacts from wildfire smoke in south Asia and east Africa.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Contrasting Community Assembly Forces Drive Microbial Structural and Potential Functional Responses to Precipitation in an Incipient Soil System

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

16S amplicon sequencing↗
DOE OSTI2021

Cost Efficiency of Environmental DNA as Compared to Conventional Methods for Biodiversity Monitoring Purposes at Marine Energy Sites

The installation of marine energy systems may affect marine environments, and by extension, marine fish communities. Therefore, biomonitoring is an integral part of assessing impacts on species. Environmental DNA (eDNA) provides a noninvasive alternative to conventional monitoring surveys and the possibility of a more accurate assessment of species richness. Yet, its cost efficiency compared to traditional methods of monitoring is relatively unknown, especially when applied to monitoring around tidal, wave, and offshore wind energy installations. For this study, 202 peer-reviewed journal articles were dissected to inventory the diversity of supplies used for collecting and processing eDNA samples and to compile the average cost of eDNA surveys. Information collected included the type, volume, and brand of containers used in sampling; material, size, and brand of filters; and extraction methods. Cost information was gathered for the most common supplies, and a total cost was estimated for a hypothetical eDNA survey in Sequim Bay, WA, to compare with traditional methods of surveying such as beach seining and scuba surveys. The results showed a higher-than-expected diversity of supplies to collect and process eDNA samples. The most common supplies were 1 L Nalgene bottles at an average cost of 7.96 USD for collecting samples, 0.45 µm glass fiber Merck Millipore filters at an average cost of 1.51 USD for filtering samples, and the Qiagen DNeasy Blood and Tissue kit at 3.54 USD per sample for extracting DNA. When compared to beach seine and scuba surveys, eDNA surveys undertaken by senior researchers are less expensive for both initial surveys with all new materials as well as for follow-up surveys reusing some of the supplies. However, when surveys are done solely by students, eDNA surveys are more expensive than scuba surveys when no prior supplies are available and more than both beach seine and scuba surveys for follow-up surveys reusing supplies. In a professional sphere, where surveys are less often conducted by teams of students only, eDNA surveys are an effective and less-costly alternative to conventional methods. We anticipate that the development and refinement of eDNA methodology will continue to decrease surveying costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Constructing a spatiotemporally coherent long-term PM2.5 concentration dataset over China during 1980–2019 using a machine learning approach

The lack of long-term observations and satellite retrievals of health-damaging fine particulate matter in China has demanded the estimates of historical PM 2.5 (particulate matter less than 2.5 µm in diameter) concentrations. This study constructs a gridded near-surface PM 2.5 concentration dataset across China covering 1980–2019 using the space-time random forest model with atmospheric visibility observations and other auxiliary data. The modeled daily PM2.5 concentrations are in excellent agreement with ground measurements during 2015–2019, with a coefficient of determination of 0.95 and mean relative error of 12%. Besides the atmospheric visibility which explains 30% of total importance of variables in the model, both emissions and meteorological conditions are also essential factors affecting PM2.5 predictions. From 1980 to 2014, the model-predicted PM2.5 concentrations increased constantly with the maximum growth rate of 5–10 µg/m3/decade over eastern China. Due to the clean air actions, PM 2.5 concentrations have decreased effectively at a rate over 50 µg/m 3 /decade in the North China Plain and 20–50 µg/m 3 /decade over eastern China during 2014–2019. The newly generated dataset of 1-degree gridded PM 2.5 concentrations for the past 40 years across China provides a useful means for investigating interannual and decadal environmental and climate impacts related to aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Need for and Path to Harmonized Life Cycle Assessment and Techno-Economic Assessment for Carbon Dioxide Capture and Utilization

The use of carbon dioxide as a feedstock for a broad range of products can help mitigate the effects of climate change through long-term removal of carbon or as part of a circular carbon economy. Research on capture and conversion technologies has intensified in recent years, and the interest in deploying these technologies is growing fast. However, sound understanding of the environmental and economic impacts of these technologies is required to drive fast deployment and avoid unintended consequences. Life cycle assessments (LCAs) and techno-economic assessments (TEAs) are useful tools to quantify environmental and economic metrics; however, these tools can be very flexible in how they are applied, with the potential to produce significantly different results depending on how the boundaries and assumptions are defined. Built on ISO standards for generic LCAs, several guidance documents have emerged recently from the Global CO 2 Initiative, the National Energy Technology Laboratory, and the National Renewable Energy Laboratory that further define assessment specifications for carbon capture and utilization. Overall agreement in the approaches is noted with differences largely based on the intended use cases. As a results, further guidance is needed for assessments of early-stage technologies, reporting details, and reporting for policymakers and nontechnical decision-makers.

09 BIOMASS FUELS↗
DOE OSTI2023

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Accurate determination of genotypic variance of cell wall characteristics of a Populus trichocarpa pedigree using high-throughput pyrolysis-molecular beam mass spectrometry

Abstract Background Pyrolysis-molecular beam mass spectrometry (py-MBMS) analysis of a pedigree of Populus trichocarpa was performed to study the phenotypic plasticity and heritability of lignin content and lignin monomer composition. Instrumental and microspatial environmental variability were observed in the spectral features and corrected to reveal underlying genetic variance of biomass composition. Results Lignin-derived ions (including m/z 124, 154, 168, 194, 210 and others) were highly impacted by microspatial environmental variation which demonstrates phenotypic plasticity of lignin composition in Populus trichocarpa biomass. Broad-sense heritability of lignin composition after correcting for microspatial and instrumental variation was determined to be H 2 = 0.56 based on py-MBMS ions known to derive from lignin. Heritability of lignin monomeric syringyl/guaiacyl ratio ( S / G ) was H 2 = 0.81. Broad-sense heritability was also high (up to H 2 = 0.79) for ions derived from other components of the biomass including phenolics (e.g., salicylates) and C5 sugars (e.g., xylose). Lignin and phenolic ion abundances were primarily driven by maternal effects, and paternal effects were either similar or stronger for the most heritable carbohydrate-derived ions. Conclusions We have shown that many biopolymer-derived ions from py-MBMS show substantial phenotypic plasticity in response to microenvironmental variation in plantations. Nevertheless, broad-sense heritability for biomass composition can be quite high after correcting for spatial environmental variation. This work outlines the importance in accounting for instrumental and microspatial environmental variation in biomass composition data for applications in heritability measurements and genomic selection for breeding poplar for renewable fuels and materials.

09 BIOMASS FUELS↗
DOE OSTI2019

Circular Economy - A challenge and an opportunity for Process Systems Engineering

Rising populations put huge stresses on natural resources. Extraction and depletion of raw materials and waste created throughout the supply chain of products have enormous environmental and socioeconomic impacts. One way to reduce these impacts is through the move towards the circular economy (CE). CE aims to solve resource, waste, and emission challenges confronting society by creating a production-to-consumption total supply chain that is restorative, regenerative, and environmentally benign. This article highlights research challenges and identifies process systems engineering (PSE) research opportunities to assist in the understanding, analysis and optimization of CE supply chains. A motivating example on the supply chain of coffee is introduced to illustrate the challenges of the transition towards a CE and to propose PSE research opportunities.

42 ENGINEERING↗
DOE OSTI2022

Environmental effects on aerosol–cloud interaction in non-precipitating marine boundary layer (MBL) clouds over the eastern North Atlantic

Abstract. Over the eastern North Atlantic (ENA) ocean, a total of 20 non-precipitating single-layer marine boundary layer (MBL) stratus and stratocumulus cloud cases are selected to investigate the impacts of the environmental variables on the aerosol–cloud interaction (ACIr) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during 2016–2018. The ACIr represents the relative change in cloud droplet effective radius re with respect to the relative change in cloud condensation nuclei (CCN) number concentration at 0.2 % supersaturation (NCCN,0.2 %) in the stratified water vapor environment. The ACIr values vary from −0.01 to 0.22 with increasing sub-cloud boundary layer precipitable water vapor (PWVBL) conditions, indicating that re is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher Nc and PWVBL. The principal component analysis shows that the most pronounced pattern during the selected cases is the co-variations in the MBL conditions characterized by the vertical component of turbulence kinetic energy (TKEw), the decoupling index (Di), and PWVBL. The environmental effects on ACIr emerge after the data are stratified into different TKEw regimes. The ACIr values, under both lower and higher PWVBL conditions, more than double from the low-TKEw to high-TKEw regime. This can be explained by the fact that stronger boundary layer turbulence maintains a well-mixed MBL, strengthening the connection between cloud microphysical properties and the below-cloud CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size spectra and consequently results in an enlargement of re. The enhanced activation of CCN and the cloud droplet condensational growth induced by the higher below-cloud CCN loading can effectively decrease re, which jointly presents as the increased ACIr. This study examines the importance of environmental effects on the ACIr assessments and provides observational constraints to future model evaluations of aerosol–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗