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At least 1,333 records · Page 74

Seeing the forest for the trees: implementing dynamic representation of forest management and forest carbon in a long-term global multisector model

Abstract Studies have found that understanding forest management is critical in understanding the interaction between the carbon cycle and the integrated human-Earth system. This makes effectively representing forest management decisions such as planting and harvesting important. Here, we implement a novel dynamic forest harvest model in a global state of the art multi-sector dynamics model, namely the Global Change Analysis Model (GCAM). We implement an approach that explicitly tracks forest age and generates rotation ages for forest harvest that are responsive to changes in wood prices, changes in forest age and regional preferences for forest rotation. Furthermore, the forest sector in GCAM competes for investment with other land use types in the future years based on expected profit. Our baseline scenario results indicate that with the new forest harvest model, the current global wood product demand in GCAM can be met with minimal loss of old growth forest through the age-based harvest decisions. We find that economic pressure for deforestation and consequent loss of forest carbon is a bigger driver of global forest change than wood harvests, especially in developing regions. Under alternative scenarios where an economic value is placed on carbon across the terrestrial and energy systems, while there is an increase in forest plantations, there can be corresponding decreases in forest cover in some regions as forest land competes with land for bio-energy crops. When the carbon in forests is assigned a price, we find that the average rotation age for wood harvests can be reduced across regions to harvest forests in a more carbon efficient manner.

54 ENVIRONMENTAL SCIENCES↗

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Hennessy, Eleanor M. (ORCID:0000000294715765)↗

Provincial-scale assessment of direct air capture to meet China’s climate neutrality goal under limited bioenergy supply

China has large, estimated potential for direct air carbon capture and storage (DACCS) but its deployment locations and impacts at the subnational scale remain unclear. This is largely because higher spatial resolution studies on carbon dioxide removal (CDR) in China have focused mainly on bioenergy with carbon capture and storage. This study uses a spatially detailed integrated energy-economy-climate model to evaluate DACCS for 31 provinces in China as the country pursues its goal of climate neutrality by 2060. We find that DACCS could expand China’s negative emissions capacity, particularly under sustainability-minded limits on bioenergy supply that are informed by bottom-up studies. But providing low-carbon electricity for multiple GtCO 2 yr -1 DACCS may require over 600 GW of additional wind and solar capacity nationwide and comprise up to 30% of electricity demand in China’s northern provinces. Investment requirements for DACCS range from 330 to 530 billion dollars by 2060 but could be repaid manyfold in the form of avoided mitigation costs, which DACCS deployment could reduce by up to $6 trillion over the same period. Enhanced efforts to lower residual CO 2 emissions that must be offset with CDR under a net-zero paradigm reduce but do not eliminate the use of DACCS for mitigation. For decision-makers and the energy-economy models guiding them, our results highlight the value of expanding beyond the current reliance on biomass for negative emissions in China.

54 ENVIRONMENTAL SCIENCES↗

Projected increases in tropical cyclone-induced U.S. electric power outage risk

Abstract While power outages caused by tropical cyclones (TCs) already pose a great threat to coastal communities, how—and why—these risks will change in a warming climate is poorly understood. To address this need, we develop a robust machine learning model to capture TC-induced power outage risk. When applied to 900 000 synthetic TCs downscaled from simulated historical and future climate conditions under a strong warming scenario, we find outage risk in the United States and Puerto Rico is expected to increase broadly by the end of the century, with some states seeing increases of 60% and higher. Further, we discover that rising rainfall rates will play an increasingly important role in TC-induced power outage risk as the climate changes, explaining more than 50% of the projected change in risk in some regions. These insights are important for guiding decision-makers in their future outage risk investment and mitigation plans.

Grid Resilience↗

Field-scale mapping of California crop water productivity to inform water management in critically overdrafted groundwater basins

Crop water productivity (CWP) metrics can reveal how the dynamics of crop production and water use change across space and time. We use field-scale satellite inputs from 2016–2021 to estimate potential water savings for four crops (almonds, grapes, walnuts, and citrus—which collectively account for approximately one-third of California’s cropland area), within critically overdrafted groundwater sub-basins of California’s San Joaquin Valley. These annual estimates of field-level water savings potential are based on locally achievable CWP values for each crop type. Our findings show considerable spatial variation in CWP and potential water savings within each sub-basin. We find that increasing CWP to peak efficiency (defined as improving fields to the 95th percentile of observed CWP) for four crops could meet up to 36% of the estimated annual overdraft in San Joaquin Valley. For comparison, fallowing 5% of the four crop type fields in the same study area could potentially reduce annual overdraft by 11%. By delivering results at the field scale, our work can inform targeted interventions by irrigation district managers and more efficient allocation of state incentives for improved water management. For example, we estimate that state grant funding for water efficiency upgrades could have amplified potential water savings threefold by targeting investments to the least efficient fields.

54 ENVIRONMENTAL SCIENCES↗

Measuring impacts of California agri-environmental programs using field-scale satellite data

In the past decade, California has invested over $\$$200 million in direct grants to growers to support the adoption of agricultural practices that save water and/or improve soil health while also reducing greenhouse gas emissions. Ex-post evaluation of agri-environmental outcomes of these grant programs, however, is limited. We use satellite data to monitor changes in field-level consumptive water use and greenness (i.e. normalized difference vegetation index), a proxy for agricultural productivity, for the most frequently funded crop-types (almonds, grapes, and walnuts) in two California Department of Food and Agriculture programs. Nearly 600 fields receiving funding during the 2014–2022 period were analyzed using two causal inference methods. Fields that received grants to both upgrade irrigation systems and install irrigation water management sensors showed reduced consumptive water use and greenness by an average of 3.5% and 4.2%, respectively (significant at the 10% level). In contrast, we find that the adoption of only irrigation water management sensors, which are designed to inform irrigation scheduling and management, resulted in an average increase of 4.1% and 4.8% in consumptive water use and greenness respectively (significant at the 5% level). We find negligible effects for either consumptive water use or greenness when both pump efficiency upgrades and sensors were implemented. We further find that grants for compost addition and cover cropping led to small greenness increases of 1.7% and 2.8% respectively (significant at the 10% level) and had insignificant effects on consumptive water use. Our analysis of five agri-environmental program interventions reveals that several practice outcomes may be at odds with stated program goals of reducing water use while maintaining or improving agricultural productivity.

agriculture↗

Assessing the impact of demand response on peak demand in a developing country: The case of Ghana

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response refers to consumer actions that change the utility load profile in a way that reduces costs or improves grid security by applying price signals and automated load shedding technologies. The methodologies that are used to achieve demand response can hardly be applicable in developing countries. Peak pricing of electricity, for instance, can hardly be implemented in many developing countries as high prices would disproportionately affect the many low-income households who do not have the capacity to take action to avoid paying high peak prices. This study aims to develop demand response methodology that can be applied in developing countries to achieve residential peak demand reduction. We use a consumer preference survey to develop a methodology suitable for developing countries. The method of diversified demand is used with energy audit and monitored data to estimate the potential peak load reduction and its cost-effectiveness for Ghana. Results show that peak reduction of 15-210 MW is expected by 2040 with a positive return on investment of 2-22% for all designed scenarios.

Diawuo, FA↗

Accelerating the development of new solar absorbers by photoemission characterization coupled with density functional theory

Abstract The expectation to progress towards Terawatts production by solar technologies requires continuous development of new materials to improve efficiency and lower the cost of devices beyond what is currently available at industrial level. At the same time, the turnaround time to make the investment worthwhile is progressively shrinking. Whereas traditional absorbers have developed in a timeframe spanning decades, there is an expectation that emerging materials will be converted into industrially relevant reality in a much shorter timeframe. Thus, it becomes necessary to develop new approaches and techniques that could accelerate decision-making steps on whether further research on a material is worth pursuing or not. In this review, we will provide an overview of the photoemission characterization methods and theoretical approaches that have been developed in the past decades to accelerate the transfer of emerging solar absorbers into efficient devices.

14 SOLAR ENERGY↗

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Magnesium- and intermetallic alloys-based hydrides for energy storage: modelling, synthesis and properties

Hydrides based on magnesium and intermetallic compounds provide a viable solution to the challenge of energy storage from renewable sources, thanks to their ability to absorb and desorb hydrogen in a reversible way with a proper tuning of pressure and temperature conditions. Therefore, they are expected to play an important role in the clean energy transition and in the deployment of hydrogen as an efficient energy vector. This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, reports on the latest activities of the working group ‘Magnesium- and Intermetallic alloys-based Hydrides for Energy Storage’. The following topics are covered by the review: multiscale modelling of hydrides and hydrogen sorption mechanisms; synthesis and processing techniques; catalysts for hydrogen sorption in Mg; Mg-based nanostructures and new compounds; hydrides based on intermetallic TiFe alloys, high entropy alloys, Laves phases, and Pd-containing alloys. Finally, an outlook is presented on current worldwide investments and future research directions for hydrogen-based energy storage.

Energy storage↗

Digital coded exposure formation of frames from event-based imagery

Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into existence. However, the process for forming frames from event-driven imagery has not been studied in detail. This work presents a principled digital coded exposure approach for forming frames from event-driven imagery that is inspired by the physics exploited in a conventional camera featuring a shutter. The technique described in this work provides a fundamental tool for understanding the temporal information content that contributes to the formation of a frame from event-driven imagery data. Event-driven imagery allows for the application of arbitrary virtual digital shutter functions to form the final frame on a pixel-by-pixel basis. The proposed approach allows for the careful control of the spatio-temporal information that is captured in the frame. Furthermore, unlike a conventional physical camera, event-driven imagery can be formed into any variety of possible frames in post-processing after the data is captured. Furthermore, unlike a conventional physical camera, coded-exposure virtual shutter functions can assume arbitrary values including positive, negative, real, and complex values. The coded exposure approach also enables the ability to perform applications of industrial interest such as digital stroboscopy without any additional hardware. The ability to form frames from event-driven imagery in a principled manner opens up new possibilities in the ability to use conventional frame-based image processing techniques on event-driven imagery.

47 OTHER INSTRUMENTATION↗

Techno-economic analysis of synthetic fuel production from existing nuclear power plants across the United States

Abstract Low carbon synfuel can reduce dependence on fossil fuels like diesel and jet fuel, and, with large-scale cost-effective production, contribute to global transportation sector decarbonization, Simultaneously, nuclear power plants are struggling economically due to falling wholesale electricity prices. Converting existing nuclear plants for synfuel production could preserve these low-carbon assets and enable large-scale synfuel production, yet no comprehensive technoeconomic analysis exists. This study evaluates the potential of integrating synthetic fuel production with five US nuclear plants, considering electricity and fuel markets and carbon dioxide source access. Such integration could enhance nuclear plant profitability by up to $792 million and offer a 10% return on investment over 20 years. The hydrogen production tax credit from the 2022 Inflation Reduction Act is crucial, comprising 75% of revenues on average. Carbon feedstock transportation has the highest cost at 35%, followed closely by synfuel production capital costs. Incentive policies are thus key for the decarbonization of the transportation sector and the economic importance of the geographic location of Integrated Energy Systems.

Garrouste, Marisol (ORCID:0000000168388644)↗

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗

White-tailed deer responses to acoustic predator cues are contingent upon past land use and contemporary fire regime

Prey can assess the immediate risk of predation by detecting cues of predator presence, and it is expected that prey should invest in costly antipredator behaviors when a cue of predator presence is detected. Features of the habitat in which the cue is detected, such as vegetative concealment, serve as indirect cues of risk and can mediate how prey respond to direct cues of predator presence. Past agricultural land use and contemporary fire regimes are common disturbances that may modify prey perceptions of risk and could, therefore, alter prey responses to direct cues of predator presence. Here we examined whether the overlap of these two disturbances affected white-tailed deer (Odocoileus virginianus) responses to cues of predator presence by measuring deer vigilance and foraging bout duration in response to coyote (Canis latrans) vocalizations across 20 woodlands that varied in past land use and contemporary fire regime. Frequent fire regimes consistently increased deer visibility to predators across both land-use history contexts. Deer exhibited no behavioral response to the predator cue in habitats containing infrequent fire regimes or agricultural legacies. Deer responded to the cue in frequently burned woodlands without agricultural legacies through increased vigilance and time spent at a foraging location. These findings reveal that land-use legacies and contemporary fire regimes can mediate how prey respond to direct cues of risk. They also suggest that prey may balance the uncertainty associated with cues of predation risk with the urgency of responding to a potential attack by being vigilant and remaining in place.

60 APPLIED LIFE SCIENCES↗

Viability, behavior, and color expression in the offspring of matings between common wall lizard Podarcis muralis color morphs

Abstract Color polymorphisms are widely studied to identify the mechanisms responsible for the origin and maintenance of phenotypic variability in nature. Two of the mechanisms of balancing selection currently thought to explain the long-term persistence of polymorphisms are the evolution of alternative phenotypic optima through correlational selection on suites of traits including color and heterosis. Both of these mechanisms can generate differences in offspring viability and fitness arising from different morph combinations. Here, we examined the effect of parental morph combination on fertilization success, embryonic viability, newborn quality, antipredator, and foraging behavior, as well as inter-annual survival by conducting controlled matings in a polymorphic lacertid Podarcis muralis, where color morphs are frequently assumed to reflect alternative phenotypic optima (e.g., alternative reproductive strategies). Juveniles were kept in outdoor tubs for a year in order to study inter-annual growth, survival, and morph inheritance. In agreement with a previous genome-wide association analysis, morph frequencies in the year-old juveniles matched the frequencies expected if orange and yellow expressions depended on recessive homozygosity at 2 separate loci. Our findings also agree with previous literature reporting higher reproductive output of heavy females and the higher overall viability of heavy newborn lizards, but we found no evidence for the existence of alternative breeding investment strategies in female morphs, or morph-combination effects on offspring viability and behavior. We conclude that inter-morph breeding remains entirely viable and genetic incompatibilities are of little significance for the maintenance of discrete color morphs in P. muralis from the Pyrenees.

Abalos, Javier↗

Open Hardware in Science: The Benefits of Open Electronics

Abstract Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; (II) scientific institutions, by improving access to customizable high-end technologies, sustainability, visibility, and interdisciplinary collaboration potential; and (III) the scientific community, by improving transparency and reproducibility, helping decouple research capacity from funding, increasing innovation, and improving collaboration potential among researchers and the public. We further discuss how current barriers like poor awareness, knowledge access, and time investments can be resolved by increased documentation and collaboration, and provide guidelines for academics to enter this emerging field. We highlight that open electronics are a promising and powerful tool to help scientific research to become more innovative and reproducible and offer a key practical solution to improve democratic access to science.

Oellermann, Michael (ORCID:0000000153926737)↗

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗

Environment-specific virocell metabolic reprogramming

Abstract Viruses impact microbial systems through killing hosts, horizontal gene transfer, and altering cellular metabolism, consequently impacting nutrient cycles. A virus-infected cell, a “virocell,” is distinct from its uninfected sister cell as the virus commandeers cellular machinery to produce viruses rather than replicate cells. Problematically, virocell responses to the nutrient-limited conditions that abound in nature are poorly understood. Here we used a systems biology approach to investigate virocell metabolic reprogramming under nutrient limitation. Using transcriptomics, proteomics, lipidomics, and endo- and exo-metabolomics, we assessed how low phosphate (low-P) conditions impacted virocells of a marine Pseudoalteromonas host when independently infected by two unrelated phages (HP1 and HS2). With the combined stresses of infection and nutrient limitation, a set of nested responses were observed. First, low-P imposed common cellular responses on all cells (virocells and uninfected cells), including activating the canonical P-stress response, and decreasing transcription, translation, and extracellular organic matter consumption. Second, low-P imposed infection-specific responses (for both virocells), including enhancing nitrogen assimilation and fatty acid degradation, and decreasing extracellular lipid relative abundance. Third, low-P suggested virocell-specific strategies. Specifically, HS2-virocells regulated gene expression by increasing transcription and ribosomal protein production, whereas HP1-virocells accumulated host proteins, decreased extracellular peptide relative abundance, and invested in broader energy and resource acquisition. These results suggest that although environmental conditions shape metabolism in common ways regardless of infection, virocell-specific strategies exist to support viral replication during nutrient limitation, and a framework now exists for identifying metabolic strategies of nutrient-limited virocells in nature.

59 BASIC BIOLOGICAL SCIENCES↗