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DOE OSTI2021

The evolving role of geothermal energy for decarbonizing the United States

Geothermal energy is often referred to as a niche technology that is too localized, too small or too expensive to make much of a difference in how renewable energy will be supplied in a fully decarbonized future. As a result, geothermal energy has been undervalued in terms of what it could provide to complement, rather than compete with, electricity generation from wind, solar photovoltaic, concentrating solar power and other renewables. Geothermal energy systems are fully dispatchable and can provide baseload or load-following electric power or heat suitable for a wide range of applications including supplying district heating for communities and cities, and heating and cooling of individual buildings. The focus of our study is on the potential of utilizing geothermal energy for providing heat for buildings and industry at lower temperatures, a substitute for the combustion of fossil fuels. Because heating represents about 20% (20 EJ per year) of the annual primary energy consumption in the U.S.—with most of it coming from burning natural gas, oil and/or propane in furnaces—deploying geothermal heating on a national scale could have a significant impact on lowering carbon emissions. In heating-dominated states in the U.S. Northern Tier, heating often is among the largest contributors to the state's carbon footprint. This review begins with a discussion of the motivation and rationale behind considering geothermal as a key low-carbon heating option for the U.S. The study summarizes the U.S. geothermal resource and describes the applications and main engineering components of using geothermal energy for heating and cooling, electric power generation, and co-generation using district heating, geothermal heat pumps, and power conversion with steam flashing and organic Rankine plants. Environmental benefits and impacts are described. An extensive discussion of geologic and thermal-hydraulic aspects of the subsurface is included in the review because of their critical role in determining reservoir designs at specific sites to ensure sufficient productivity that is both safe and economically viable. Models for estimating levelized costs of district heating are used to show how costs are affected by reservoir performance, infrastructure capital costs, and financial parameters. Here, the review concludes with an assessment of technical subsurface issues associated with reservoir performance and the economic requirements for providing geothermal heating in district heating systems at a sufficient scale to have an impact on decarbonizing the U.S.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Environmental Life Cycle Assessment of small water resource recovery facilities: Comparison of mechanical and lagoon systems

Small water resource recovery facilities (WRRFs) serving communities with populations of less than 10,000 people account for 70% of centralized wastewater treatment systems in the United States. Here, with growing interest globally in improving the sustainability of these systems, this study evaluated the environmental life cycle impact and land use tradeoffs of different lagoon and mechanical WRRFs across the diverse climate of Nebraska. Life cycle inventory including construction and operations was collected for 35 existing systems representing a range of commonly used mechanical WRRFs: oxidation ditch, extended aeration, and sequencing batch reactors, and lagoon treatment systems: complete retention, irrigation, and controlled discharge lagoons.

42 ENGINEERING↗

DOE OSTI2021

The three-dimensional construction of leaves is coordinated with water use efficiency in conifers

Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential for predicting physiological impacts due to environmental variation. Here, using synchrotron-generated microtomography imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus on Pinus , the richest conifer genus. We show that intrinsic water use efficiency (WUE i ) is positively driven by leaf vein volume. Needle-like leaves of Pinus , as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUE i . Our results clarify how the three-dimensional organisation of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suite of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

CELAVI (Circular Economy Lifecycle Assessment and VIsualization) [SWR-20-87]

A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. The primary goal of CELAVI is to help answer questions about how material flows and environmental and economic impacts of energy systems might change if the circularity of energy systems increases.

Eberle, Annika↗

DOE OSTI2022

CELAVI (Circular Economy Lifecycle Assessment and VIsualization) v.1.3.1 9/30/2022 [SWR-20-87]

Eberle, Annika↗

DOE OSTI2020

Oak Ridge National Laboratory Annual Sustainability Report 2020

A sustainability report is an annual document published by a company or organization about the economic, environmental, and social impacts that result from its everyday activities. A sustainability report also presents the organization’s values and governance model and demonstrates the link between its strategy and its commitment to a sustainable economy. Sustainability reporting enables organizations to consider their effects on a wide range of sustainability issues, enabling them to be more transparent about the risks and opportunities they face.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

How Earth System Models Can Inform Key Dimensions of Marine Food Security in the Alaskan Arctic

The Arctic is home to several groups of Indigenous Peoples, each with distinct ways of interacting with their environment and ways of life. Arctic, Indigenous Peoples’ food sovereignty is tightly linked with food security. Subsistence harvesting activities provide nutritious and culturally vital foods for Alaska Native households and communities. Climate change is causing rapid and more unpredictable shifts in environmental conditions that impact three of the key aspects of food security, availability, stability, and accessibility. While communities monitor the abundance and health of food webs and environments as part of subsistence harvest practices, anticipating major transformations and changes in these systems is challenging. We explored the potential of Earth System Model output in helping anticipate or project physical or ecosystem changes relevant to Alaska Indigenous peoples’ food security needs. Through examples of model products, that provide measures of accessibility and availability of marine resources, we show that modern models, such as the Energy Exascale Earth System Model presented here, can provide estimates of a broad suite of variables relevant to food security. We investigate how Earth System Model output could contribute to exploring questions related to aspects of Arctic food security such as accessibility and availability and highlight present model shortcomings that, if addressed, would move Earth System Models closer to being a useful tool for understanding environmentally driven changes to the availability and accessibility of harvestable food resources. Our example model-derived food security indicators illustrate how Earth System Model output could be combined with relevant, non-model, information sources; These model products are meant only as a starting point and a tool for engaging community members and to present, in an accessible way, the model’s potential utility, or current lack thereof, to rights holders and stakeholders concerned about food security. We are hopeful that with example products in hand, additional model development efforts will have a higher likelihood of success in achieving an iterative discussion with stakeholders regarding feasible and desired products.

Gibson, Georgina A.↗

DOE OSTI2024

Wastewater reuse benefits for municipal complete retention lagoons: Life cycle assessment and dynamic modeling

Complete retention lagoons with wastewater reuse for agricultural purposes may offer sustainability advantages over alternative systems for small communities in semiarid regions. This study quantifies the environmental life cycle impact of adopting agriculture water reuse systems using case study data to estimate operating and building infrastructure impacts and spatial–temporal modeling to quantify resource trade-offs. Water reuse system benefits are highly dependent on supply–storage–demand dynamics. The relative size of irrigated agricultural land to the lagoon size was the most significant factor influencing site water application rates. The benefits are sensitive to changes in air emissions occurring from the agricultural land and further emphasize the importance of proper fertilizer management when adopting water reuse systems. Wastewater reuse from complete retention lagoons reduce life cycle GHG emissions, primarily through excavation reductions, offset fertilizer use, and especially from increased crop yields from wastewater reuse at previously rainfed sites.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Toxicology and Biodegradability of Blendstocks for Mixing Controlled Compression Ignition Combustion: Literature Review of Available Data

The goal of the U.S. Department of Energy’s Co-Optima project is to develop an understanding of potential biomass-derived blendstocks for use in the transportation sector. This report documents the estimated environmental and toxicological impact of potential bioblendstocks for mixing controlled compression ignition (MCCI) engines. The candidate molecules were: 2-nonanol; n-undecane; 2,6,10-trimethyldodecane; 5-ethyl-4-propylnonane; hexylhexanoate; methyldecanoate; dibutoxymethane; 4-butoxyheptane; dipentylether; renewable diesel; and soy biodiesel. To provide a robust comparison, diesel surrogate molecules were also considered: α-methylnaphthalene; decahydronaphthalene; 2,2,4,4,6,8,8-heptamethylnonane; n-butylcyclohexane; n-hexadecane; tetralin; and n-dodecylbenzene. The intent of this work was not to provide absolute answers and remove any molecules from consideration, but to provide more robust data for each molecule that can be used in subsequent evaluations. Little literature data was available for many of the molecules, both potential blendstocks and diesel surrogates, so a quantitative structural activity relationship (QSAR) approach was used to provide input into the relevant models. This assessment included an evaluation of compartment partitioning in the event of an accidental chemical spill, fate and transport indicators, estimated biodegradability, and human and environmental toxicology. The higher molecular weight and longer hydrocarbon chain lengths of these MCCI molecules reduce water solubility and mobility. Generally, the oxygenated molecules improved biodegradability metrics. The hydrocarbons farnesane and 5-Et-4-PrNonane are not predicted to be biodegradable. Human acute toxicity was found to be slightly to non-toxic for the MCCI blendstocks and the diesel surrogates. 2-Nonanol, undecane, MeDecanoate, dibutoxymethane, and dipentylether were likely developmental toxicants. Although poorly water soluble, all the compounds, whether Co-Optima blendstocks or diesel surrogates, showed significant toxicity to D. magna. The oxygenated blendstocks were less likely to bioaccumulate than the non-oxygenated blendstocks, which behaved similar to the diesel surrogates. Overall, this predicted analysis showed that the MCCI blendstocks are very similar to their diesel counterparts. No significant showstoppers were found that would indicate concern moving forward with additional research into these potential fuels. The results presented were based solely on predictive models and serve to provide information going forward for continued evaluation of these molecules.

09 BIOMASS FUELS↗

DOE OSTI2023

Evaluating the sustainability of the 2017 US biofuel industry with an integrated techno-economic analysis and life cycle assessment

The United States produced more than 66.2 billion Liters of biofuel, primarily in the form of corn ethanol (61 billion Liters) and soybean biodiesel (6 billion Liters), for the transportation industry in 2017. No work currently exists that evaluates both the economic and environmental outcomes of this industry with adequate geospatial resolution and national scope. In this study, a model framework is constructed to perform Techno-Economic Analysis and Life Cycle Assessment using high-resolution input datasets to provide a granular estimation of corn ethanol and soybean biodiesel sustainability performance in most counties in the United States in 2017 (the most recent year for which data is available). Results show a total life cycle, greenhouse gas emission volume of 99.5 million Mg CO 2-eq produced in 2017 by these two biofuels (94.8 million Mg from corn ethanol, and 4.7 million Mg from soybean biodiesel), excluding indirect land use change emissions. Further, this volume corresponds to a combined carbon intensity of 65.3 gCO 2-eq /MJ, which is a greenhouse gas improvement compared to petroleum-based gasoline (the carbon intensity of conventional gasoline is 93.0 gCO 2-eq /MJ). However, these biofuels are produced at an additional economic cost ($1.8 billion over the displaced gas/diesel). Additionally, these biofuels generate unfavorable impacts in other environmental categories when compared to petroleum-based fuels, particularly in areas of water, land, and nitrogen intensity. This work enables stakeholders to assess the specific value of biofuels as a means of emission reduction and determine if the attained improvements are worth the associated opportunity costs.

09 BIOMASS FUELS↗

DOE OSTI2026

Satellite Metallicity Enhancement I: Suppressed Star Formation, Stellar Mass Loss, and Enriched Inflow of DESI and EAGLE Galaxies around Massive Clusters

Environmental effects are a primary driver of elevated gas-phase metallicities in galaxies around massive clusters, but the underlying physical mechanisms for this satellite metallicity enhancement (SME) are still unclear. Using the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, we present the first measurement of the average SME as a function of projected cluster-centric distance. The resulting profile reveals three distinct regimes: a steep decline from the cluster center, a plateau near the cluster boundary, and an extended downturn across several cluster radii. Remarkably, the complex shape and amplitude of this observed SME profile are successfully reproduced in the EAGLE cosmological simulation. Drawing insights from EAGLE, we develop a novel satellite chemical evolution model to decompose the observed SME into physical contributions from suppressed star formation, stellar mass loss, and enriched gas inflow. Our analysis shows that continuous accretion of enriched intracluster medium dominates the SME plateau within the cluster virial radius, while mass loss and quenching jointly drive the rapid metallicity decline in the cluster core. Our method disentangles the impacts of three environmental processes on galactic chemical enrichment in the cosmic web, providing a powerful framework for understanding cluster galaxy evolution with current and future spectroscopic surveys.

Lin, Yuanye [Shanghai Jiao Tong U.; Shanghai Jiaot↗

DOE OSTI2025

Agricultural Management Legacy Effects on Switchgrass Growth and Soil Carbon Gains

Switchgrass ( Panicum virgatum L.) is a native North American grass currently considered a high-potential bioenergy feedstock crop. However, previous reports questioned its effectiveness in generating soil organic carbon (SOC) gains, with resultant uncertainty regarding the monoculture switchgrass's impact on the environmental sustainability of bioenergy agriculture. We hypothesize that the inconsistencies in past SOC accrual results might be due, in part, to differences in prior land management among the systems subsequently planted to switchgrass. To test this hypothesis, we measured SOC and other soil properties, root biomass, and switchgrass growth in an experimental site with a 30-year history of contrasting tillage and N-fertilization treatments, 7 years after switchgrass establishment. We determined switchgrass' monthly gross primary production (GPP) for six consecutive years and conducted deep soil sampling. Nitrogen fertilization expectedly stimulated switchgrass growth; however, a tendency for better plant growth was also observed under unfertilized settings in the former no-till soil. In topsoil, SOC significantly increased from 2007 to 2023 in fertilized treatments of both tillage histories, with the greatest increase observed in fertilized no-till. Fertilized no-till also had the highest particulate organic matter content in the topsoil, with no differences among the treatments observed in deeper soil layers. However, regardless of fertilization, the tillage history had a strong effect on stratification with depth of SOC, total N, and microbial biomass C. Results suggested that historic and ongoing N fertilization had a substantial impact on switchgrass growth and soil characteristics, while tillage legacy had a much weaker, but still discernible, effect.

bioenergy crop production system↗

DOE OSTI2020

Climate Sensitivity of Peatland Methane Emissions Mediated by Seasonal Hydrologic Dynamics

Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Peatland emissions are projected to increase under climate change, as rising temperatures and shifting precipitation accelerate microbial metabolic pathways favorable for CH 4 production. However, how these changing environmental factors will impact peatland emissions over the long term remains unknown. Here, we investigate a novel data set spanning an exceptionally long 11 years to analyze the influence of soil temperature and water table elevation on peatland CH 4 emissions. We show that higher water tables dampen the springtime increases in CH 4 emissions as well as their subsequent decreases during late summer to fall. These results imply that any hydroclimatological changes in northern peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if temperature remains unchanged. Furthermore, advancing hydrological understanding in peatland watersheds will be crucial for improving predictions of CH 4 emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Improving Gas Reactor Design with Complex Non-Standard Reaction Mechanisms in a Reactive Flow Model

Fluorinated gases are critical to a number of high-technology industries including semiconductor manufacturing and related processes such as flat panel display, LED, and photovoltaic manufacturing. These fluorinated gases have very high global warming potentials (GWPs) and, unfortunately are chemically very stable, in some cases lasting for thousands of years in the atmosphere. For environmental reasons, it is imperative that the release of these gases be minimized, but existing methods to destroy them requires a significant amount of energy. The goal of this project was to develop a more energy efficient method of destroying these high GWP gases using computational fluid dynamics, but the computational requirements are significant. In this project, we bring together resources available at the national labs, including high-performance computing hardware and modern computational methods, in order to explore an industrially important problem with key environmental and economic impact. In this project, we examined the state-of-the-art models for the physical processes involved, and made subtle changes to arrive at alternative formulations considerably better suited for computation and study. We examined several representative scenarios and developed a set of analyses techniques and tools that could be used to explore the systems in much greater detail. This exploratory project has demonstrated to ALZETA that HPC can indeed provide a unique view into their complex engineering problem - one that is simply inaccessible by any other means. The tools allow us to explore the details of the chemical process, and allow one to construct "what-if" scenarios to address shortcomings of the physical device in its current operating modes. However, as with many sources of completely new information, many new questions are illuminated with this capability. It will take considerable time, effort and experience before we learn to probe the solutions, pose operating scenarios and confirm modifications to the device that lead to real engineering advances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Colorado (Pueblo) Regional DAC Hub TA-1: Feasibility (Phase 0a) (Final Technical Report)

This project supports the U.S. Department of Energy's (DOE) mission to reduce the environmental and climate impacts of fossil fuels and industrial processes, contributing to the goal of achieving net-zero emissions across the U.S. economy. The primary objective is to conduct a feasibility study for a Regional Direct Air Capture (DAC) Hub in the Southern Colorado region, northeast of Pueblo. The geographic construct of this hub is based on the Denver-Julesburg Basin – a geological area where a significant number of geological storage studies have been conducted (See Figure 1). The project will leverage the work of Project Eos, a CarbonSAFE Phase III study led by the Colorado School of Mines and CarbonAmerica. The DAC Hub aims to capture, store, and/or utilize at least 1,000,000 tonnes of CO 2 from the atmosphere annually. To achieve this, the project team is designing a system with an initial capacity of 100,000 tonnes per year. This feasibility-stage project will formulate the Regional DAC Hub concept and team to conduct the relevant analysis, networking and community stakeholder engagement necessary to advance the project to the design stage.

42 ENGINEERING↗

DOE OSTI2020

From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world

Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon-climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool-based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool-based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. In this study, we propose a novel conceptual framework to explore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interactions within the Soil Environment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Connecting Global Modes of Variability to Climate in High Mountain Asia

Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.

54 ENVIRONMENTAL SCIENCES↗