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DOE OSTI2025

Estimating the Impacts of Increasing Temperatures and the Efficacy of Climate Adaptation Strategies in Urban Microclimates with Deep Learning

As urbanization and climate change progress, understanding and addressing urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in the urban core can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, modeling the urban microclimate is an ongoing field of research typically burdened by an imprecise description of the built environment, incomplete observational records, significant computational cost, and a lack of high-resolution estimates of the impacts of increasing temperatures. Here, we present computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to a neighborhood in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50 %. The corresponding increase in winter gas heating offsets the summer cooling benefit in the current climate, but total annual energy use from combined heating and cooling with electric heat pumps benefits from the engineered heat mitigation strategies under both current and future climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Assisted migration in a warmer and drier climate: less climate buffering capacity, less facilitation and more fires at temperate latitudes?

Assisted tree migration has been proposed as a conceptual solution to mitigate lags in biotic responses to anthropogenic climate change. The rationale behind this concept is that tree species currently growing under warmer and drier climates will be more resistant and resilient to the new climatic conditions than tree species naturally growing in currently wetter and colder climates. However, we hypothesize that, by being more stress‐tolerant to warmer and drier conditions, translocated species should exhibit different functional attributes, which could induce important ecological and societal costs and overcome the desired benefits of maintaining wood production and other ecosystem services. We used principal component analysis (PCA) to analyze variation in seven traits of 106 tree and tall shrub species from contrasting latitudinal distributions in western North America and Europe to predict the potential functional changes of forest ecosystems due to the translocation of tree species from low to high latitudes. We show that species from both continents differed primarily by their position on the leaf economy spectrum (LES) and their size traits. Even though, in Europe, differences in LES were significantly correlated to species southern latitudinal positions, in both continents differences in size traits were significantly correlated to latitude. These results suggest that assisted migration by translocating more conservative species of shorter stature in currently cooler climates should decrease the buffering capacity of forest canopies, decrease facilitation for understory species, and increase wildfire risks, whose effects have the potential to accelerate climate warming through negative atmospheric feedback processes. As an alternative solution to assisted migration that may accelerate rather than mitigate climate change, we recommend that foresters gradually diversify the vertical structure and layering of the existing forest canopy to maintain a sustainable water cycle and energy balance between the soil, the tree and the atmosphere without increasing the wildfire risk.

Environmental Sciences & Ecology↗

DOE OSTI2023

Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models

Abstract A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO 2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Emergent Constrained Projections of Mean and Extreme Warming in China

Reliable regional temperature projections including heat extremes are essential for climate change adaptation and mitigation. Taking China as an example, simple averages from Coupled Model Intercomparison Project Phase 6 (CMIP6) models project high warming due to sampling many high climate sensitivities in the ensemble. Here, we develop an emergent constraint (EC) framework to obtain constrained mean and daily maximum temperature (TXx) warming over China by using observed global warming and local residual warming. The constrained annual mean and TXx warming over China (2.33°C [1.61–3.05°C] and 2.31°C [1.21–2.99°C]) are 0.65°C [0.04–1.76°C] and 0.63°C [–0.50–2.39°C], respectively, lower than raw projections (2.98°C [1.85–4.22°C] and 2.94°C [2.04–4.39°C]) for 2080–2099 under the intermediate-emission scenario. Approximately half model uncertainty is reduced after constraint. The land area (population) experiencing temperature extremes in our metric is 78% (85%) of the raw projections. Our results imply a lower impact of extreme heat than implied by current raw CMIP6 projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity

Abstract Earth is currently undergoing a global increase in atmospheric vapor pressure deficit (VPD), a trend which is expected to continue as climate warms. This phenomenon has been associated with productivity decreases in ecosystems and yield penalties in crops, with these losses attributed to photosynthetic limitations arising from decreased stomatal conductance. Such VPD increases, however, have occurred over decades, which raises the possibility that stomatal acclimation to VPD plays an important role in determining plant productivity under high VPD. Furthermore, evidence points to more far‐ranging and complex effects of elevated VPD on plant physiology, extending to the anatomical, biochemical, and developmental levels, which could vary substantially across species. Because these complex effects are typically not considered in modeling frameworks, we conducted a quantitative literature review documenting temperature‐independent VPD effects on 112 species and 59 traits and physiological variables, in order to develop an integrated and mechanistic physiological framework. We found that VPD increase reduced yield and primary productivity, an effect that was partially mediated by stomatal acclimation, and also linked with changes in leaf anatomy, nutrient, and hormonal status. The productivity decrease was also associated with negative effects on reproductive development, and changes in architecture and growth rates that could decrease the evaporative surface or minimize embolism risk. Cross‐species quantitative relationships were found between levels of VPD increase and trait responses, and we found differences across plant groups, indicating that future VPD impacts will depend on community assembly and crop functional diversity. Our analysis confirms predictions arising from the hydraulic corollary to Darcy's law, outlines a systemic physiological framework of plant responses to rising VPD, and provides recommendations for future research to better understand and mitigate VPD‐mediated climate change effects on ecosystems and agro‐systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The short-term comprehensive impact of the phase-out of global coal combustion on air pollution and climate change

With the continuous intensification of global warming, the reduction and ultimate phase-out of coal combustion is an inevitable trend in the future global energy transformation. This study comprehensively analyzed the impact of phasing out coal combustion on global emissions and concentrations of air pollutants, radiative fluxes, meteorology and climate using Community Earth System Model 2 (CESM2). The results indicate that after the global phase-out of coal combustion, there is a marked decrease in the concentrations of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ) and fine particulate matter (PM 2.5 ), with some regions experiencing a reduction of exceeding 50%. There is no significant change in global ozone (O 3 ) concentration. There are decreasing AOD and positive radiative fluxes globally in the short term, though the cloud contributes minor negative radiative fluxes. The global air temperature may increase by approximately (0.02 ± 0.15) °C on average with regional and seasonal variations, and the precipitation may potentially increase by approximately (2.7 ± 40.6) mm yr −1 globally and over 20% in equatorial regions in the short term. But combined with the decreasing trend of cloud water content in the Northern Hemisphere, it indicates a potential increase in the extremity of precipitation events. In conclusion, this study provides references for global control of air pollution, mitigation strategies of climate change, and transformation of energy structures under the objective of “carbon neutrality”, such as focusing on the negative climate impacts of exacerbating regional warming and increasing extreme precipitation resulting from the rapid reduction of aerosols in the short term.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Kent Island Boundary Layer Field Campaign Report

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations about the impacts of climate change and associated mitigation and adaptation measures. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) was conducted to study the interactions among the earth’s surface, the atmospheric boundary layer (ABL), aerosols, atmospheric composition, clouds, radiation, and precipitation at each experimental site, and to examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. In this activity we performed weekly soundings, alternating between day and night from Kent Island, to get low-frequency, long-term observations of ABL/lower tropospheric thermodynamic structure. However, during the CoURAGE intensive operational period (IOP), we performed high-frequency sampling (2x/day), at times coinciding with CoURAGE IOP soundings at the main site. The short-term, high-frequency sounding information that was launched at 12Z and 18Z was to complement the longer-term data set.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Pervasive alterations to snow-dominated ecosystem functions under climate change

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. So our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Design and Assessment of a Novel Approach for Ecosystem Warming Experiments in High‐Energy Tidal Wetlands

Abstract Coastal salt marshes have an important role in climate change adaptation and mitigation. Direct and indirect responses to warming are expected to vary along the marsh elevation gradient, making ecosystem responses to warming at this marine‐terrestrial ecotone uncertain. The Marsh Ecosystem Response to Increased Temperatures (MERIT) experiment was established in 2018 on the North Sea coast of Germany. Experimental plots are evenly distributed over three elevational marsh zones (pioneer, low marsh, and high marsh) and include three temperature treatments (ambient, +1.5°C, +3.0°C). MERIT's novel design combines active warming (horizontal surface warming cables and vertical soil warming pins) with passive, partially covered domes. For performance assessment, temperature deltas between ambient and warmed plots were calculated and evaluated at seasonal, daily, and diurnal timescales. We used Linear Mixed Models with Residual Maximum Likelihood for evaluating warming treatment effects and constraining environmental factors. MERIT was effective at ecosystem warming in this high‐energy environment both above‐ and belowground. Mixed models show that warming treatment dominates temperature differences belowground and at the soil surface, along with factors such as wind speed, flooding duration, and solar radiation. Aboveground warming was lower than belowground warming, but the dome design minimized issues seen in other open‐top chamber experiments. The combination of passive aboveground warming with feedback‐controlled active surface and belowground heating provides a setup for understanding warming effects on tidal ecosystems without altering the natural impacts of wind, radiation, and tidal inundations at high‐energy coastlines. Our design creates opportunities to expand future warming experiments to remote locations and technically challenging environments.

Environmental Sciences & Ecology↗

DOE OSTI2024

Projected income data under different shared socioeconomic pathways for Washington state

Abstract High-resolution income projections under different Shared Socioeconomic Pathways (SSPs) are essential for the climate change research communities to devise climate change adaptation and mitigation strategies. To generate income projections for Washington state, we obtain state-level GDP per capita projections and convert them into projected annual household income. The resulting state-level income projections are subsequently downscaled to the census block-level based on the Longitudinal Origin-Destination Employment Statistics (LODES) dataset. For accuracy assessment, we downscale historical income data from state- level to block- and block group-level and compare the downscaled results against the actual income data from LODES. County-level accuracy assessment is also conducted based on American Community Survey. The results demonstrate a good agreement (Average R 2 of 0.67, 0.8, and 0.99 for block-, block group-, and county-level, respectively) between the downscaled income data and the reference data, thereby validating the methodology employed. Our approach is applicable to other states for income projections, which can be utilized by a broader audience, including those involved in demographic analysis, economic research, and urban planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Correlative Surface Imaging Reveals Chemical Signatures for Bacterial Hotspots on Plant Roots

The rhizosphere is arguably the most complex microbial habitat on earth, comprising an integrated network of plant roots, soil and a highly diverse microbial community (the rhizosphere microbiome)1. Understanding, predicting and controlling plant-microbe interactions in the rhizosphere will allow us to harness the plant microbiome as a means to increase or restore plant ecosystem productivity, improve plant responses to a wide range of environmental perturbations, and mitigate effects of climate change by designing ecosystems for long-term soil carbon storage1. To this end, it is imperative to develop new molecular approaches with high spatial resolution to capture interactions at the plant-microbe, microbe-microbe, and plant-plant interfaces. In this work, we designed an imaging sample holder that allows integrated surface imaging tools to map the same locations of a plant root-microbe interface with submicron lateral resolutions, providing novel in vivo analysis of root-microbe interactions. Specifically, confocal fluorescence microscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS), and scanning electron microscope (SEM) were used for the first time for correlative imaging of the Brachypodium distachyon root and its interaction with Pseudomonas SW25, a typical plant growth-promoting soil bacterium. Imaging data suggest that the root surface is inhomogeneous and that the interaction between Pseudomonas and Brachypodium roots was confined to only few spots along the sampled root segments and that the bacterial attachment spots were enriched in Na- and S-related and high-mass organic species. We conclude that attachment of the Pseudomonas cells to the root surface is outcompeted by strong root-soil mineral interactions but facilitated by formation of extracellular polymeric substances (EPS).

Plant root, Plant growth-promoting bacteria, soil,↗

DOE OSTI2021

CO2 Electrolyzer to Produce Formic Acid Using Flue Gas at Industry Relevant Current Density

The electrochemical conversion of carbon dioxide (CO2) into valuable fuels and feedstocks has gained great attention recently due to the global urgency to mitigate the rapid climate change. A wide variety of chemicals can be obtained through the electrochemical CO2 reduction reaction (CO2RR). Among all the chemicals generated through CO2RR, formic acid has attracted great interest because of its wide applications in silage preservation in agriculture, as an antibacterial agent in animal food additives, as a chemical additive in leather and tanning processing, as a chemical component in textile dyeing and finishing, as a reagent in pharmaceutical and chemical synthesis, and as deicing agents and a component in drilling fluids. Recently, the use of formic acid as a feedstock for biorefineries has also attracted increasing interest.

Yang, Hongzhou↗

DOE OSTI2024

SimCCS 3.0 User GUIDE

Carbon Capture and Storage (CCS) is an important technology aimed at reducing CO 2 emissions and contributing to the mitigation strategies of climate change. The process involves three main steps: CO 2 capture, transport, and storage. Specifically, CO 2 is captured from industrial facilities, such as coal-fired power plants and natural gas processing plants. It is then transported through infrastructure networks, such as pipelines, rails, and ships, and injected into underground geological formations, such as depleted oil and gas reservoirs or deep saline aquifers, for permanent storage. The entire CCS value chain encompasses multiple components, including CO 2 sources, transport networks, and storage sites. The proper design of CCS transport infrastructure is an essential step for the deployment of CCS technology. However, the design is not a trivial process, as it presents many challenges and requires consideration of numerous economic, social, and environmental factors.

42 ENGINEERING↗

DOE OSTI2021

Impacts of Biofuel Blending on MCCI Ignition Delay with Review of Methods for Defining Cycle-by-Cycle Ignition Points from Noisy Cylinder Pressure Data

Conventional diesel combustion, also known as Mixing-Controlled Compression Ignition (MCCI), is expected to be the primary power source for medium- and heavy-duty vehicles for decades to come. Displacing petroleum-based ultra-low-sulfur diesel (ULSD) as much as possible with low-net-carbon biofuels will become necessary to help mitigate effects on climate change. Neat biofuels may have difficulty meeting current diesel fuel standards but blends of 30% biofuel in ULSD show potential as ‘drop-in’ fuels. These blends must not make significant changes to the combustion phasing of the MCCI process if they are to be used interchangeably with neat ULSD. An important aspect of MCCI phasing is the ignition delay (ID), i.e. the time between the start of fuel injection and the initial premixed autoignition that initiates the MCCI process. Bench experiments can evaluate the expected ignition delay of a fuel via cetane number (CN) or alternative methods such as the indicated cetane number (ICN); however, neither CN nor ICN correlate perfectly with the ignition delay measured in actual engine experiments. Furthermore, there is no standardized methodology on how to quantify MCCI ignition delay from engine cylinder pressure measurements, creating difficulties in cross-study comparison. In this study, several engine ignition delay calculation methods are evaluated for robustness in deriving ignition delay on both a cycle-averaged and cycle-to-cycle basis. Eight biofuel blends with varying ICN, oxygen concentration and other fuel properties were used to study the different methods. This yields a thorough analysis of how certain biofuel blends affect ignition delay and the entire MCCI process, as well as a thorough evaluation of the differences between the ID calculation methods. Many of these methods are equally valid, but the choice of method has a significant impact on the resulting ID, which must be carefully considered when evaluating results across multiple studies.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Impacts of Biofuel Blending on MCCI Ignition Delay with Review of Methods for Defining Cycle-by-Cycle Ignition Points from Noisy Cylinder Pressure Data: Preprint

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Source apportionment of VOCs, IVOCs and SVOCs by positive matrix factorization in suburban Livermore, California

Abstract. Gas- and particle-phase molecular markers provide highly specific information about the sources and atmospheric processes that contribute to air pollution. In urban areas, major sources of pollution are changing as regulation selectively mitigates some pollution sources and climate change impacts the surrounding environment. In this study, a comprehensive thermal desorption aerosol gas chromatograph (cTAG) was used to measure volatile, intermediate-volatility and semivolatile molecular markers every other hour over a 10 d period from 11 to 21 April 2018 in suburban Livermore, California. Source apportionment via positive matrix factorization (PMF) was performed to identify major sources of pollution. The PMF analysis identified 13 components, including emissions from gasoline, consumer products, biomass burning, secondary oxidation, aged regional transport and several factors associated with single compounds or specific events with unique compositions. The gasoline factor had a distinct morning peak in concentration but lacked a corresponding evening peak, suggesting commute-related traffic emissions are dominated by cold starts in residential areas. More monoterpene and monoterpenoid mass was assigned to consumer product emissions than biogenic sources, underscoring the increasing importance of volatile chemical products to urban emissions. Daytime isoprene concentrations were controlled by biogenic sunlight- and temperature-dependent processes, mediated by strong midday mixing, but gasoline was found to be the dominant and likely only source of isoprene at night. Biomass burning markers indicated residential wood burning activity remained an important pollution source even in the springtime. This study demonstrates that specific high-time-resolution molecular marker measurements across a wide range of volatility enable more comprehensive pollution source profiles than a narrower volatility range would allow.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Machine learning for modern power distribution systems: Progress and perspectives

The application of machine learning (ML) to power and energy systems (PES) is being researched at an astounding rate, resulting in a significant number of recent additions to the literature. As the infrastructure of electric power systems evolves, so does interest in deploying ML techniques to PES. However, despite growing interest, the limited number of reported real-world applications suggests that the gap between research and practice is yet to be fully bridged. To help highlight areas where this gap could be narrowed, this article discusses the challenges and opportunities in developing and adapting ML techniques for modern electric power systems, with a particular focus on power distribution systems. These systems play a crucial role in transforming the electric power sector and accommodating emerging distributed technologies to mitigate the impacts of climate change and accelerate the transition to a sustainable energy future. The objective of this article is not to provide an exhaustive overview of the state-of-the-art in the literature, but rather to make the topic accessible to readers with an engineering or computer science background and an interest in the field of ML for PES, thereby encouraging cross-disciplinary research in this rapidly developing field. To this end, the article discusses the ways in which ML can contribute to addressing the evolving operational challenges facing power distribution systems and identifies relevant application areas that exemplify the potential for ML to make near-term contributions. At the same time, key considerations for the practical implementation of ML in power distribution systems are discussed, along with suggestions for several potential future directions.

Marković, Marija (ORCID:0000000247839837)↗

DOE OSTI2021

Sensitivity of Riparian Buffer Designs to Climate Change—Nutrient and Sediment Loading to Streams: A Case Study in the Albemarle-Pamlico River Basins (USA) Using HAWQS

Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient and sediment loadings to streams. We designed 135 simulation scenarios starting with the six baselines RBZs (grass, urban, two-zone forest, three-zone forest, wildlife, and naturalized) in three 12-digit Hydrologic Unit Code watersheds within the Albemarle-Pamlico river basin (USA). Using the hydrologic and water quality system (HAWQS), we assessed the sensitivity of the designs to five water quality indicator (WQI) parameters: dissolved oxygen (DO), total phosphorous (TP), total nitrogen (TN), sediment (SD), and biochemical oxygen demand (BD). To understand the climate mitigation potential of RBZs, we identified a subset of future climate change projection models of air temperature and precipitation using EPA’s Locating and Selecting Scenarios Online tool. Analyses revealed optimal RBZ designs for the three watersheds. In terms of watershed ecosystem services sustainability, the optimal Urban RBZ in contemporary climate (1983–2018) reduced SD from 61–96%, TN from 34–55%, TP from 9–48%, and BD from 53–99%, and raised DO from 4–10% with respect to No-RBZ in the three watersheds. The late century’s (2070–2099) extreme mean annual climate changes significantly increased the projected SD and BD; however, the addition of urban RBZs was projected to offset the climate change reducing SD from 28–94% and BD from 69–93% in the watersheds. All other types of RBZs are also projected to fully mitigate the climate change impacts on WQI parameters except three-zone RBZ.

54 ENVIRONMENTAL SCIENCES↗