The Global Change Analysis Model (GCAM) is an open source, publicly available market equilibrium integrated assessment model, which integrates human and natural earth systems science. GCAM examines the multisector dynamics between the socioeconomic, energy, water, land, climate, and emissions systems at 5-year time steps through 2100 and operates with a spatial resolution of 32 economic regions, 283 land regions, and 233 water basins. The model has been developed at Pacific Northwest National Laboratory’s Joint Global Change Research Institute (PNNL JGCRI) for over 30 years and has been used to explore questions related to energy transition, decarbonization and carbon mitigation, technology development and policies, air pollution, energy/water/food nexus, climate impacts, and many others. The GCAM community also continues to develop versions of GCAM with state-level detail in larger countries such as GCAM-USA, GCAM-China, GCAM-Canada, and others. This presentation will give an overview of GCAM, the range of analyses that have been conducted using the model, and how GCAM can supplement traditional ISSST analyses.

Wildfires are a significant threat in California, burning more than 1.7 million acres per year and costing the state billions of dollars. In addition to directly damaging homes and infrastructure, fires can destabilize soil, leading to debris flows when significant precipitation events occur in recently burned areas. Electric utilities own and operate infrastructure located in areas that are vulnerable to both wildfires and post-fire debris flows. While in recent years there has been a focus on understanding the risks of wildfire ignition caused by power infrastructure and identifying the responsible electric utilities to mitigate these risks, there has been little work to understand the vulnerability of utilities themselves to wildfires and post-fire debris flows. This is partly due to the complex nature of these hazards, defined by multiple disciplines and dynamics. In this work we assess the vulnerability of transmission lines, electric substations, and power generation facilities in California to wildfires and post-fire debris flows. We assess wildfire risk by overlaying geospatial power infrastructure data with wildfire probability from Cal Adapt and post-fire debris flow threat levels from recent modeling efforts. We assess risk in today’s climate and in the future. To understand uncertainty in future climate impacts, we use two climate models: the Canadian Earth Systems Model, which produces an average prediction of future climate and the Hadley Centre Global Environment Model, which produces a warmer, drier estimate. In conjunction with both climate models, we use two representative concentration pathways (RCPs): RCP 4.5, representing a future in which greenhouse gas emissions begin to decrease in the mid-21st century, and RCP 8.5, in which emissions increase through the end of the century. We assess risks at the state level and identify vulnerable electric utility companies. We find that under current conditions, electric utility assets in Northern California are most vulnerable, being located in areas with up to 40% fire probability compared to the state average of roughly 10%, and high risk for post-fire debris flow. Under future conditions, we find that fire risk to assets may increase substantially in the Sierra Nevada and Northern Coast regions, and post-fire debris flow risk may increase substantially in the coastal ranges and North Central California. However, there is large uncertainty in future risks across climate scenarios. While many electric utility companies have primarily low-risk power infrastructure assets, we find that some smaller utilities may be particularly vulnerable due to the majority of their transmission lines and substations being located in high risk areas. Power generation is also vulnerable to wildfire and post-fire debris flow, with geothermal, hydro, and nuclear power plants in the state facing the highest risks in current and future climate scenarios. These results provide a basis for decision-making around the allocation of resources for infrastructure resilience to wildfire impacts.

Decarbonizing the U.S. electric power sector will require massive deployment of clean energy infrastructure, including utility-scale solar photovoltaics (solar PV) and other renewables. This deployment, though, must comply with local zoning ordinances, which impose a nationwide patchwork of restrictions on where deployment can actually occur. While zoning restrictions on deployment may be developed for legitimate purposes to protect public health and safety, they could impede or increase the costs of decarbonization of the electric power sector, but no research in this area exists. We quantify the role of utility-scale solar zoning ordinances on power sector decarbonization across the Great Lakes region (Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin) by integrating a first-of-a-kind database of 6,300 rural community zoning ordinances into a power system planning model. Our results indicate zoning ordinances can play a pivotal role in shaping sub-regional and regional decarbonization outcomes. Relative to no ordinances, solar zoning ordinances reduce total available capacity of solar PV by 52% (or 1.6 TW) across our region. Currently, however, the biggest zoning barrier to deployment is zoning ordinances which are silent on utility-scale solar, often interpreted as a de facto ban. This absence of guidelines decreases available capacity by 31% across the region and up to 59% at the state level. Outright bans—by explicitly disallowing solar—contributes another 6% reduction across the region and up to 13% reduction at the state level. Deployment restrictions translate to up to 4 GW greater investment needs and 5.6% greater PV investment costs to achieve a 10% PV generation target. Starker shifts occur at the state level, e.g. Wisconsin sees a 40% reduction in PV investments due to zoning restrictions; these investments shift to other states with laxer ordinances, e.g. Illinois. Our results underscore the need for planning that aligns local zoning laws with state and regional decarbonization objectives.

Thailand has established a target of carbon neutrality by 2050. Reaching this goal will require coordinated efforts across the energy system at both the national and subnational levels. Robust decarbonization scenarios incorporating current plans and targets, additional measures needed, and trade-offs between strategies can help stakeholders make informed decisions in the face of uncertainty. Through iterative engagement with decision makers, we develop and analyze carbon neutral scenarios for Thailand that incorporate Bangkok’s role using a global integrated assessment model. We find that Thailand can reach carbon neutrality through power sector decarbonization, energy efficiency and widespread electrification in the buildings, industry, and transportation sectors, and advanced technologies including carbon capture and storage. Negative emissions technologies will also be needed to offset Thailand and Bangkok’s hardest-to-abate CO2 emissions. Bangkok, as a major population and economic center, contributes significantly to Thailand’s energy demand and emissions and can therefore play an important role in climate change mitigation. Accordingly, our results underscore the importance of subnational climate action in meeting Thailand’s carbon neutral goal. These insights can help energy system stakeholders identify priorities, consider tradeoffs, and make decisions that will impact Bangkok and Thailand’s long-term climate change mitigation potential. We also note that Thailand's carbon neutral 2050 pathway is based on a targeted emissions reduction of 40% by 2030 as stated in Thailand’s NDC. However, Thailand’s unconditional NDC is only 30% in 2030. Thus, Thailand may need international support to achieve carbon neutrality by 2050 through the pathways investigated here.

Electric vehicles (EVs) have significant sustainability impacts, not only in terms of shifting their primary energy source from fossil fuels to electricity, but also due to differences in their material supply chains and manufacturing processes.

This study investigates the effect of the 2022 Inflation Reduction Act (IRA) incentives on U.S. electric vehicle battery industry in terms of supply chain decisions and technology choices, specifically examining the dynamics of different chemistry choices and production geographies from the perspective of cost minimization. Using the BatPaC model, we explore a number of scenarios based on potential future market developments to analyze the effect of the various subsidies.

We find that the total value of all IRA incentives exceeds the total production cost of EV batteries in the United States. Though the total possible amount of incentives in pure dollar quantities is slightly larger for batteries with the Nickel Manganese Cobalt Oxide (NMC) chemistry, the Lithium Iron Phosphate (LFP) chemistry continues to dominate on a dollar per kWh basis due to its markedly lower manufacturing cost, as well as the lower number of critical minerals needed to meet the critical mineral requirement. Furthermore, these incentives can render U.S. batteries competitive even without meeting critical mineral requirements: the $45 per kilowatt-hour (kWh) incentive to produce battery cells, modules, and packs domestically is sufficient to be competitive with current modeled production in China. However, direct credits for critical minerals extraction and processing have very limited relative effect on the cost of battery manufacturing, rendering them less important in terms of shifting their geography of production from the perspective of an automaker trying to claim vehicle-based tax credits based on their supply chain.

Our analysis underscores the impact (or lack thereof) of upstream credits for critical minerals and components, prompting a re-evaluation of the feasibility of relocating challenging segments within the supply chain and their subsequent environmental, security, and economic implications. This research provides crucial insights for policymakers and industry stakeholders navigating the transformed EV supply chain landscape post-IRA implementation.

A core drawback of conventional life cycle assessment (LCA) is its failure to account for the temporal dynamics of the technological and environmental background in which a technology is assumed to operate. The temporal implications of the background system can be particularly relevant when evaluating systems in an early stage of development as they usually require time-intensive research and development effort. The use of static life cycle inventory databases can also result in the misrepresentation of the environmental impacts of technologies with operational lifetimes spanning decades since temporal changes in the background system, such as the decarbonization of the electrical grid, are not commonly accounted for. In a context where achieving near-term climate targets depends heavily on advancing technologies currently at a low technology readiness level, capturing the systematic changes in background dynamics and supply chains is critical for the accurate assessment of technology potential and effective decision-making.

This study explores the application of prospective LCA (pLCA) to evaluate the environmental impacts of sustainable aviation fuel pathways. Specifically, the research focuses on comparing two pathways: one involving the conversion of corn grain-derived ethanol to a jet fuel blendstock and the other converting algal oil to jet fuel through hydrotreating esters and fatty acids. The pLCA model leverages data on shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) to transform life cycle inventories of key sectors, such as power, cement, steel, and transportation fuels, across different futuristic scenarios. Data for life cycle inventory transformation includes outputs from a “middle of the road” SSP, which aligns with the objectives of the Paris Agreement, and a RCP assuming a global mean surface temperature of 1.6°C (RCP 2.6) by 2100. The transformed pLCA database is then coupled to engineering process models of the SAF systems to simulate the well-to-wake life cycle greenhouse gas (GHGs) emissions over their lifetime. Moreover, potential tax credits derived from reducing GHGs over time will be evaluated through techno-economic analysis.

The preliminary pLCA underscores the significance of incorporating supply chain dynamics into LCA. Results reveal that conventional (static) LCA methods may provide a distorted view of environmental impacts compared to dynamic LCA. For instance, results challenge the notion that algal-based jet fuel has a higher global warming potential (58 g CO2E MJ-1) than the ethanol-to-jet pathway (53 g CO2E MJ-1), if static LCA methods are used. Results from the pLCA demonstrate that algal jet fuel eventually achieves a lower life cycle carbon intensity than corn-derived jet fuel, with estimated GHG emissions of 27 g CO2E MJ-1 ¬¬¬and 39 g CO2E MJ-1 by 2050 respectively. The change in emissions observed in the algal pathway is primarily due to reductions in the carbon intensity of the electrical grid. Based on reductions in GHG emissions, both pathways are potentially eligible for tax credits under current policies. In conclusion, preliminary work emphasizes the importance of considering background system dynamics when evaluating energy-intensive technologies such as SAF pathways and underscores the importance of comprehensive and dynamic LCA methodologies in shaping informed decision-making and policy development.

Limiting global warming to the greatest extent possible is critical for reducing the adverse effects of climate change on humanity and the planet. To achieve long-term temperature mitigation targets, such as 1.5℃ or 2℃, it is crucial to reckon not only with the total emissions reductions required but also with the anticipated "committed" greenhouse gas (GHG) emissions from existing infrastructure. While data on the former is more accessible, information on the latter is often confined to snapshot publications with limited transparency on geographic or technological scales.

In this study, we introduce a comprehensive bottom-up model of "committed" energy supplies for the United States, aimed at informing climate policy decision-making. This work addresses critical questions about the existing energy system, allowing us to estimate the size of the remaining gap between locked-in US emissions from existing infrastructure and modeled emissions trajectories leading to 1.5℃ and 2℃ targets. The model incorporates facility-level lifecycle emissions for both fossil and non-fossil sources, utilizing well-level data for natural gas and oil, and power plant data for coal, renewables, and biomass. Designed for regular updates to accommodate additional energy projects or early retirements, the model ensures relevance and accuracy over time.

Utilizing this model, we analyze the GHG emissions gap across various project-relevant timescales, comparing locked-in US emissions with pathways to 1.5℃ and 2℃ targets based on the latest models from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Our findings reveal that, while some space exists between the modeled scenario pathway and already locked-in emissions over certain lifetime scales, a minimal number of new fossil energy projects could entirely eliminate this window. Additionally, Monte Carlo analysis is employed to illustrate the robustness of our conclusions to uncertainties in model parameters.

This committed energy system model serves as a core input to the recently-published "climate test" decision-support tool. This tool is specifically designed for policymakers tasked with evaluating individual fossil infrastructure projects and their alignment with climate targets under US law. Together, these tools empower government agencies to make scientifically informed and climate-protective decisions for our energy future, facilitating our collective efforts to realize overarching climate goals.

This paper presents a political-industrial ecology analysis of an emerging petrochemical corridor in Appalachia. Within Appalachia, various ethane “cracker” plants are under construction, or are being permitted, to transform ethane by-products from hydraulicly fractured shale gas in the Marcellus and Utica shales into plastics. Political-industrial ecology is a nascent field of geography that embeds resource metabolisms within their broader political economic contexts. I advance the field by presenting a “metabolic tour” of the petrochemical supply chain that analyzes how petrochemicals forge and transform human-environmental relationships along the chain. The political-industrial ecology analysis links these developments in the former steel belt to the growing environmental burdens of plastics, highlighting how record state subsidies are facilitating these linkages. Further, the systems perspective afforded by a political-industrial ecology view reveals three notable findings. First, the footprint of the corridor extends well beyond the Ohio River Valley to Canada, the US Gulf Coast and international markets in Europe and Asia. Second, the corridor is a significant step towards establishing more globally integrated markets for ethane and natural gas. Third, the analysis illustrates the myriad of environmental systems and communities interlinked through the corridor, which can serve as a roadmap for facilitating cumulative impact analysis, a key gap in environmental impact and justice scholarship.

Solar energy is widely viewed as one of our best tools to combat climate change, reduce carbon emissions, and save money -- but solar projects (both thermal and photovoltaic) typically don't fit into the same mold as most energy efficiency projects. This paper will discuss the basics of how solar generation fits into the energy sector, and the successes and challenges of including solar projects in a major utility’s ratepayer funded energy efficiency program.

The paper will start by addressing the need to innovate and work collaboratively with major utilities and utility commissions in order to find pathways to include renewables in energy efficiency programs in ways that will work for all parties. Renewable energy such as solar PV is at a once in a lifetime moment with the passage of the Inflation Reduction Act, and utilities are looking to meet lofty goals for saving energy at a time when the low hanging fruit such as lighting retrofits are beginning to sunset.

Integrating solar PV projects into ratepayer funded programs can be a challenge, but this real world example of how it was done benefitted from close collaboration between the utility, implementer, and 3rd party evaluator. The program was developed to ensure that the program would be cost effective and allayed concerns about the “death spiral” for the utility. The paper will review lessons learned from several years of experience covering numerous projects and adjustments made during evaluation and implementation.

This study explores how cities can reach energy sector net-zero greenhouse gas (GHG) goals from a life cycle perspective. Although life cycle assessment (LCA) is recognized in academia and industry as a holistic means of accounting for emissions along the entire supply chain of a product or process, it has not yet been widely applied to US climate policy. City GHG inventories largely adhere to the Scoping system suggested by the GHG Protocol, which omits upstream and downstream emissions from energy resources. Because the GHG emissions associated with most renewable energy resources are entirely from upstream and/or downstream activities and not direct combustion of fuel, the GHG Protocol method underestimates energy-related emissions and is not conducive to optimizing the energy transition to maximize GHG reductions. Maximizing GHG reductions on a life cycle basis avoids burden shifting from one geographic location or economic sector to another to ensure genuine net benefits.

This analysis focuses on the pledges made in the 2021 Austin Climate Equity Plan to reach net-zero community-wide GHG emissions in Austin, Texas by 2040. The scope of the study covers the energy sector within the geographic bounds of the city, including residential, commercial, and industrial demand for electricity and thermal power, excluding liquid fuels for transportation. We also account for projected fluctuations in energy demand and energy storage requirements due to electrification initiatives, efficiency upgrades, and population increase. Geospatially relevant data from literature, governmental, and NGO sources, along with original research results, are used to estimate life cycle GHG emissions for different energy resources and associated infrastructure using a parametric, bottom-up approach. This is compared against the bottom-up production-based and top-down consumption-based GHG inventories that have been provided by the city of Austin. Modelling accounts for uncertainty and dynamism of inputs with sensitivity analysis of key parameters. Recommendations for specific technologies over alternative options are provided with context for decision-makers to understand tradeoffs. The results demonstrate the value in LCA to aide in developing climate policy and provide a framework for other cities to consider adopting.

The University of Massachusetts Lowell, in collaboration with National Grid and the City of Lowell, has embarked on a pioneering geothermal energy pilot project, emphasizing the use of ground source heat pump (GSHP) systems. This initiative, a part of the state’s goal to achieve net-zero emissions by 2050, focuses on using the Earth's thermal properties to provide efficient heating and cooling. The start of this project provides an excellent opportunity to evaluate the environmental impact of the university's geothermal plant and its contribution to decarbonization efforts at a critical point in global climate change mitigation. Previous research indicates that GSHP systems offer significant environmental advantages over traditional heating and cooling methods, reducing carbon emissions, energy use, and fossil fuel dependence. Their ability to maintain stable ground temperatures leads to consistent energy efficiency and a lower environmental footprint, making them crucial for sustainable development and climate change mitigation.

Our primary objective in this study is to conduct a comprehensive Life Cycle Assessment (LCA) of UMass Lowell's GSHP systems. We are utilizing open-source Brightway2 and Ecoinvent 3.5 datasets for this cradle-to-grave assessment, which involves comparing the GSHP system with traditional air conditioning (AC) systems in terms of carbon intensity and other environmental impacts. The analysis covers various life stages of the GSHP system, from raw material extraction through construction, operation, and eventual decommissioning, with a particular focus on configurations in campus commercial buildings.

Currently, we are in the phase of collecting life cycle inventory data, where we plan to integrate machine learning (ML) tools. This integration aims to improve the accuracy of our environmental impact evaluation by uncovering patterns and insights within the data for a more comprehensive and precise LCA. Moreover, we are employing ML tools for sensitivity analysis to gain deeper insights into how different parameters impact the LCA results, enabling us to identify key factors for effective environmental impact reduction strategies more accurately. Our methodological approach includes a thorough life cycle analysis, encompassing both Midpoint and Endpoint categories in impact assessment. The study combines primary data from the UMass Lowell project with secondary data to provide a holistic evaluation of the GSHP system’s environmental footprint.

The expected outcome of this research is to establish a new standard for future GSHP projects through a detailed LCA. It will quantify the GSHP system's carbon footprint and GHG emissions and suggest ways to reduce them, such as low-carbon drilling and energy-efficient operations. By comparing the environmental impact of the GSHP system with conventional AC systems, we aim to underscore the potential of geothermal energy in reducing carbon emissions and promoting sustainable heating practices. The findings are expected to significantly contribute to UMass Lowell's sustainability initiatives, support National Grid's net-zero emission goals, and aid the global effort to mitigate climate change.

The effects of climate change are impacting all sectors of the economy worldwide. Changes in weather patterns and extreme weather events have resulted in frequent and prolonged power outages, underscoring the vulnerability of centralized power systems. This emphasizes a critical necessity to boost community resilience. Adapting school buildings to climate change can play a pivotal role, given their importance in providing essential social services, especially during and after extreme weather events, such as hurricanes, heat waves, or ice storms.

Here, we show the potential of school buildings as energy resilience hubs for communities and the trade-offs between costs, technical considerations, and environmental performance. Importantly, it highlights the need for customized design strategies across diverse climate zones, as a one-size-fits-all approach proves inadequate.

Although energy resilience in the built environment has received increased attention from researchers, it must be effectively incorporated into building codes and design practices. The energy-resilience-environmental nexus needs to be more studied, with techno-economic and environmental analyses often limited to operational costs and carbon emissions, neglecting embodied carbon and other environmental impacts throughout the system's life cycle.

Examining how passive design strategies impact the energy and environmental performance of school buildings, especially during power outages, sheds light on the resiliency and sustainability of this type of infrastructure. Our approach utilizes reference models of schools for various U.S. climate zones to develop the energy models and estimate the energy demand. Then, a building-integrated photovoltaics (BIPV) plus storage system is incorporated into the design to enhance the system's energy resilience. Finally, the environmental profile of the system is evaluated through a life cycle assessment. As a result, we assess the effectiveness of these strategies in terms of costs, technical performance, and environmental footprint, encompassing not only carbon emissions but also other environmental factors. Indeed, the case study of an elementary school building in Puerto Rico shows that using BIPV leads to a one-third reduction in the carbon footprint and similar improvements in other environmental impact categories like ozone layer depletion and ozone formation. However, some impact categories, including eutrophication, ecotoxicity, and mineral scarcity, show higher values attributed to PV module and battery cell production. The embodied impact burden varies significantly, accounting for 16% of global warming, 33% of freshwater eutrophication, and 88% of mineral resource scarcity. This underscores the importance of adopting a comprehensive life cycle approach, particularly the growing significance of embodied impacts in energy-efficient and resilient buildings.

The implications of this research extend to informing future building codes, design practices, and policy frameworks. By understanding the relationship between passive design strategies, energy resilience, and environmental impact, stakeholders can make informed decisions to enhance the overall resilience of the built environment.

Decarbonization technologies are a solution to reducing greenhouse gas emissions and mitigating climate change. However, the decarbonization transition will undoubtedly be mineral-intensive with critical minerals, like cobalt, lithium, and nickel, serving as the backbone of many decarbonization technologies. Mining is the primary acquisition method for critical minerals but wields many environmental and social effects – both positive (i.e. job opportunities and boosting the local economy1) and negative (i.e. land degradation2, reduced water quality3, and community displacement2). Life cycle analysis (LCA) is a tool that can assess effects and sustainability. However, there are significant gaps and a lack of structure in how LCAs of mineral mining are completed (e.g., inappropriate data sources, inconsistent system boundaries, indicators, and functional units). Overall, there is no standardized framework for critical mineral mining LCAs, which complicates comparisons, decision-making, and policy design.

We propose a critical mineral mining LCA framework using the standard four life-cycle phases.4 We conduct an LCA of a proposed copper-nickel mine in Minnesota, the first non-ferrous mine in the state, to guide development and application of the framework.

Several aspects of this LCA demonstrate the framework. For example, we employ two functional units, one ton of mineral equivalent and one year of mining operation. We define the system boundary to encompass mining operations and reclamation. We used foreground system processing and site information from legal documents as an appropriate, open data source. We use Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) Model5, and literature for background system inventory data.

We calculated energy use, water use, and greenhouse emissions of the proposed mine. Mineral refining processes (beneficiation and hydrometallurgical) and wastewater treatment account for most of the energy and water consumption, representing 81% and 94% of the total energy and water burdens, respectively. However, refining and wastewater treatment processes only comprise 52% of the greenhouse gas (GHG) emissions. Land clearing and blasting contribute 40% of GHG emissions. Land clearing will release 6.7 billion kg of CO2 into the atmosphere, 35% of total GHGs.

Carrying out this LCA using publicly available information identified challenges and gaps in completing mining LCAs that must be addressed using new, local, and timely data sources. For example, water pollutant emissions and biodiversity changes are prominent mining environmental effects. We describe an approach to improving mining LCA coverage of these important effects as part of developing a standard LCA framework for critical minerals mining. The framework will enable better comparisons, decision-making, and policy design. The standardized framework will offer a template for critical mineral mining LCAs conducted by other researchers and allow comparison of mines and LCA results.

References:

1. Hosseinpour, M., et al. Evaluation of positive and negative impacts of mining on sustainable... (2022).

2. Wilson, S. A., et al. Livelihood impacts of iron ore mining-induced... (2022).

3. Uugwanga, M. N. & Kgabi, N. A. Heavy metal pollution index of surface and groundwater… (2021).

4. International Standards Organization. ISO 14040:2006 (2006).

5. Argonne National Laboratory. (2021).

To mitigate climate change and preserve resources for future generations, the economy is investing in a profound industrial transition. These transition efforts can be grouped into two broad categories: efforts to turn away from fossil-based energy sources with greater energy efficiency and efforts to use materials more efficiently. The development of industrial symbioses in which the energy and material waste flows of one industry are managed such that they serve as inputs to complementary industries constitute a promising avenue to potentially combine both energy and material efficiencies measures. But when trade-offs arise between increasing material efficiency or energy efficiency, or between energy and resources recovery, how should these choices be optimized? A case can be made that a single indicator of resource use should guide the design of industrial symbioses. There does exist a single indicator from thermodynamics that can quantify the “quality” of both material and energy resources by linking these to the notion of work: exergy. This approach has not commonly been used for several historical and fundamental reasons. Yet it seems important to find ways of communicating what thermodynamics has to say about the increasing consumption of resources and their dispersions. Is an exergy indicator relevant and practical in guiding the optimisation of an industrial symbiosis? Our study focuses on a tire production company. Through a material and energy flow analysis, the use flows and waste flows are quantified and translated into exergy flows. We represent the loss of exergy throughout the production cycle and end-of-life transformation. A linear optimisation model then selects the technological mixes and operation parameters that minimizes the total exergy losses. We conduct a comparative analysis between optimizing the industrial symbiosis using exergy, relative to using other sustainability and efficiency indicators. In our work, we provide a unified exergy indicator for energetic and material resources as well as an optimisation tool based on constraints which represents the reality of goods-producing companies in their environmental objectives, leading them to a more sustainable ecological transition. Our other aim is to furnish information to guide the target audience on the requirements needed to use the indicator. This method can then be used in any industry that aims to improve efficiency in resource use.

The transition from fossil to renewable energy sources is a key lever to mitigate greenhouse gas (GHG) emissions and restrict global temperature to below 1.5C above pre-industrial levels. Yet growth trajectory and predicted ultimate scale could lead to PV becoming one of the largest global industries with enormous annual GHG emissions from manufacturing, even while lowering carbon emissions compared to the incumbent energy sources they displace. Prior studies have calculated a payback time for those upfront GHG emissions. While simple to calculate and communicate, the usefulness of the payback time and similar metrics are limited because they treat all GHG emissions as equal no matter when emitted, and yet we know there is greater impact on climate from emissions earlier within a given timeframe. Herein we will demonstrate how low carbon manufacturing, even for an already low carbon energy source like PV, can yield significant additional climate benefits, as measured by reduced future temperature change.

Temperature increase resulting from GHG emissions can be quantified by the absolute global warming potential (AGTP) metric. The AGTP metric reveals that the temperature-increase caused by a GHG emission pulse is directly proportional to the lifetime of the GHG in the atmosphere. Consequently, emission of a GHG occurring earlier in a given timeframe will remain longer within that timeframe and, thereby, induce a greater temperature increase than an equal mass of GHG emitted later in that timeframe. If a societal goal is to reduce future temperature increase, earlier GHG emission reductions (e.g., in the manufacturing stage of a technology’s life cycle) are of higher value than later.

We use PV illustratively to exemplify how the AGTP metric can be applied to quantify temperature mitigation potential of low carbon manufacturing of RE systems considering the net impact of when GHGs are emitted and avoided over their life cycle. The methods presented herein can be applied to any product with lower-carbon manufacturing alternatives. Whereas we demonstrate that all PV provides net AGTP benefits over their 30-year lifetime, shifting from high to low-carbon PV manufacturing increases the net AGTP benefit by up to 175% points under US-average grid and solar insolation conditions.

Many plans for reducing greenhouse gas emissions envision future electricity systems that are heavily reliant on energy supplied by wind and solar resources. Recent studies examine how the capacities of energy infrastructure required to reliably meet electricity demand in wind- and solar-heavy energy systems will be determined by fluctuations in these renewable resources. Better understanding of the characteristics of these fluctuations and their effects on potential future energy systems can inform the development and deployment of technologies that reduce the costs of reliably providing electricity. In this work, we examine fluctuations in wind and solar energy resources from 1980–2020 with high temporal and geographical resolution across the coterminous United States. We then evaluate potential approaches for supplementing wind and solar energy to address this variability. We find that while wind and solar resource availabilities vary according to season and geography, the most stressful meteorological patterns for energy system infrastructures have some common characteristics. We characterize how the costs and availabilities of other technologies affect the cost-optimal capacities and operation of physical energy infrastructure in systems with high penetrations of wind and solar energy. Finally, we conclude that while all modeled methods require substantial investment, strategic combinations of geographical resource aggregation, energy storage, supplemental non-wind/solar generation, and demand management can help reduce the overbuilding of physical infrastructure and lower energy costs.