Direct air capture (DAC) of CO2 is seen as an important technology for reaching net zero by mitigating hard-to-abate emissions and, in the long term, as a strategy for removing built-up anthropogenic CO2 for a net-negative carbon economy. To spur development in DAC, the DOE is funding the development of four DAC hubs that will capture 1 million tonnes of CO2 annually [1]. DAC processes may require a combination of heat and electricity, but an all-electric plant is generally preferred, so that the plant itself does not produce CO2 and can be run using low-carbon electricity sources.

Most proposed all-electric DAC processes require around 1.2 megawatt-hours of electricity [2]. This creates a major barrier for a 1 million-tonne DAC process, as it would require 1.2 terawatt-hours of electricity, which is equivalent to roughly 10% of the energy generated by Maine [3]. A load of this size would require significant upgrades to the electrical grid, such as enhanced substations and transmission lines. Further, the increased electrical load may lead to unforeseen increases in energy costs and create reliability issues for nearby consumers. Here, we utilize methods provided by Regional Transmission Organizations (RTOs) to analyze these costs for a variety of prospective DAC projects [4].

From an environmental perspective, large DAC loads have the potential to siphon large portions of low-carbon electricity from the grid, increasing their consequential emissions and reducing their efficacy. Depending on how the low-carbon electricity is replaced, this could fully negate the carbon removal potential of a DAC hub. To assess these impacts, this work will use data from the Energy Information Administration to calculate the consequential emissions associated with reducing renewable energy availability for the grid. In combination, the environmental and economic impacts will be used to evaluate existing analyses of DAC to determine how these factors affect the cost of carbon removal.

1. US Department of Energy, U.S. Department of Energy Announces $52.5 Million to Catalyze Commercial Carbon Dioxide Removal Technology, 2024, https://www.energy.gov/fecm/articles/us-department-energy-announces-525-million-catalyze-commercial-carbon-dioxide-0.

2. Herzog, H., et al., Getting Real about Capturing Carbon from the Air, One Earth, 2024.

3. Energy Information Administration, Electricity data browser - Net Generation for all sectors 2023.

4. Midcontinent Independent System Operator, Transmission and Substation Project Cost Estimation Guide for MTEP 2018, https://cdn.misoenergy.org/Transmission-and-Substation-Project-Cost-Estimation-Guide-for-MTEP-2018144804.pdf.

Background and Motivation

In the U.S., approximately 3% of the electricity load is consumed by municipal wastewater treatment processes aimed at removing organic matter and nutrients. Despite this energy expenditure, the significant chemical energy embedded in these organic materials and nutrients remains largely unrecovered due to current technological limitations. Therefore, the paradigm for wastewater treatment has shifted to water resource recovery that enables water reuse, nutrient recovery, and energy recovery.

Methods

To enhance the environmental performance of emerging water resource recovery technologies, prospective life cycle assessment (LCA) is a suitable method that can be utilized(1,2). Prospective LCA involves analyzing emerging technologies at early development stages, where environmental insights can guide significant modifications(3). In this study, we evaluated the environmental impacts and the cost of an intelligent water resource recovery system with prospective LCA and technoeconomic analysis (TEA). The intelligent water resource recovery system integrates solar steam generation to concentrate water that undergoes coupled aerobic-anoxic nitrous decomposition operation with phosphorus removal (CANDO+P). This process recovers energy and nutrients. Meanwhile, evaporated steam condenses and is recovered. Sensors monitor system performance in real-time, feeding data to machine learning algorithms for process control and optimization. We gather data from experiments, including operational parameters, material inputs, energy usage, and economic inputs, to build detailed models for LCA and TEA. Prospective LCA evaluates the environmental impacts of photothermal material production, the benefits of adopting CANDO+P, the footprint of sensor production and deployment, and energy usage, with potential reductions in the system's overall environmental impacts through improved monitoring and control. Similarly, TEA assesses the cost-effectiveness of photothermal materials, quantifies the economic value of energy and nutrient recovery, and analyzes the cost savings from improved monitoring and control.

Significance

By leveraging the combined strengths of LCA and TEA tools, it helps to enable a holistic perspective on innovation, resulting in the creation of systems that outperform conventional wastewater treatment systems in both environmental impact and cost-effectiveness. This ultimately supports global efforts to address water resource challenges and transition toward a sustainable development.

Reference:

(1) Hellweg, S.; Milà I Canals, L. Emerging Approaches, Challenges and Opportunities in Life Cycle Assessment. Science 2014, 344 (6188), 1109–1113. https://doi.org/10.1126/science.1248361.

(2) Bergerson, J. A.; Brandt, A.; Cresko, J.; Carbajales‐Dale, M.; MacLean, H. L.; Matthews, H. S.; McCoy, S.; McManus, M.; Miller, S. A.; Morrow, W. R.; Posen, I. D.; Seager, T.; Skone, T.; Sleep, S. Life Cycle Assessment of Emerging Technologies: Evaluation Techniques at Different Stages of Market and Technical Maturity. J of Industrial Ecology 2020, 24 (1), 11–25. https://doi.org/10.1111/jiec.12954.

(3) Arvidsson, R.; Tillman, A.; Sandén, B. A.; Janssen, M.; Nordelöf, A.; Kushnir, D.; Molander, S. Environmental Assessment of Emerging Technologies: Recommendations for Prospective LCA. J of Industrial Ecology 2018, 22 (6), 1286–1294. https://doi.org/10.1111/jiec.12690.

Zero-emission vehicles are a key component of California’s clean energy strategy. Currently, transportation accounts for 30-40% of California’s greenhouse gas emissions. As ZEVs do not require the use of fuels that carry high emissions, the transition towards ZEVs has the potential to drastically decrease these hazardous emissions (Current California GHG Emission Inventory Data | California Air Resources Board). To help accelerate the transition, California enacted executive order N-79-20, which aims for 100% of new passenger vehicle sales to be zero-emission vehicles by 2035 - now just a decade away. This is an ambitious goal that will require a better understanding of the intricacies involved in the consumer mindset and market surrounding ZEV uptake. To this end, we are conducting a set of interviews with prominent ZEV planners across the twelve transit districts in California. The interviewees include local community organizers, representatives of transportation authorities, authors of ZEV adoption plans, and more. The goal of these interviews is to identify the major factors - be that policy, community organizing, financial incentives, access, infrastructure availability, community mindset, etc. - that have helped enhance or limit ZEV adoption across different communities in California. To identify which communities upon which to focus, we used ZEV registration and vehicle population data along with CalEnviro Screen data to identify over- and under-performing zip codes. We classified under and over-performing zip codes as locations with higher (or lower) than expected uptake of ZEVs based on factors such as income, education level, housing burden, and poverty levels. Additionally, we are continuing to research the influence of factors such as linguistic isolation and local air pollution health impacts on ZEV uptake. Moving forward we plan to continue our interviews and surveys with additional county and city representatives, as well as planning and non-profit organizations that collaborate on ZEV plans. We expect that influencing factors and responses will differ based on the community, with certain strategies being more effective in smaller, more remote communities and other strategies being more effective in larger, more urban communities. Ultimately, we anticipate that this research will provide further insight into the planning and implementation of incentives, rules, policies, and practices that positively influence the uptake of zero-emission vehicles in pursuit of state and federal climate goals.

This study examines the implications of policy requirements on the three-pillar methods of greenhouse gas (GHG) analysis in the context of low-carbon hydrogen production in the USA. The three-pillar incremental generation, geographical matching, and temporary matching approach provide a comprehensive framework for establishing Energy Attributes Certificates - EAC facilities for hydrogen production. Recent policy developments, including tax incentives and regulatory standards, are analyzed to understand their impact on the adoption and optimization of low-carbon hydrogen technologies. The findings highlight the critical role of policy in shaping the GHG emissions profile of hydrogen production while leveraging available resources and technologies to ensure sustainable and economically viable hydrogen solutions are adopted. This research contributes to providing insights concerning the Clean Hydrogen Production Reduction Act (45V) for the three pillars of H2 production, and a broader discourse on hydrogen decarbonization pathways, and the transition to a low-carbon energy future.

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. 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.

We use the absolute global warming potential (AGTP) metric to quantify the temperature increase resulting from GHG emissions. 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 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 (i.e., in the manufacturing stage of PV) are of higher value than later. We apply the AGTP metric to quantify temperature mitigation potential of low carbon manufacturing of PV systems considering the net impact of when GHGs are emitted and avoided over their life cycle. We explore the potential for decarbonization over the PV supply chain by accounting for various manufacturing sites, two PV technologies (silicon and CdTe), six high and low-carbon sources of electricity (used in manufacturing) and eight high and low-carbon pathways to produce multi- and mono-crystalline silicon feedstock.

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 208% points under US-average grid and solar insolation conditions. Decreasing electricity intensity of PV manufacturing and shifting to less CO2 intensive sources of electricity will generate significant increases in the net AGTP benefit, even if pursued alone. While low-carbon CdTe generates 170% greater net AGTP benefit than high-carbon mono-Si PV, this benefit diminishes to just 1% when Si PV manufacturers use less CO2-intensive sources of electricity. Based on these findings, we recommend strategies for PV manufactures to most effectively decarbonize their supply chain even if they are located in geographies which rely on high-carbon electricity. Additionally, we identify strategies to address the most important gaps in the lifecycle inventory (LCI) and increase the data transparency over the PV supply chain. The increased data transparency will enable LCA practitioners to more robustly quantify the climate benefit of a transition to terawatt of PV, quantify the impact of different material choices and energy mixes across various manufacturing pathways and assess the ability of PV modules with various designs to meet policy goals defined in the ultra-low carbon PV standard for the US market.

Vehicle electrification is a cornerstone strategy for decarbonizing the light duty vehicle (LDV) fleet. Aggressive fleet electrification targets aligning with a net-zero trajectory will place an increasing strain on associated battery supply chains [1], [2]. Despite the current overcapacity in battery supply[3], researchers have raised concerns over the feasibility of scaling the supply of batteries to keep pace with the projected global demand of the LDV sector, especially in light of geopolitical risks over securing critical minerals[2] and competing demand for batteries from other sectors[4] (e.g. stationary storage, electronics). As uncertainties are large[1], [3], strategic allocation of battery capacity is essential to address any possible future battery supply chain risks as well as reduce the socio-environmental impacts of battery production[5], [6].

This study determines strategies for deployment of a limited battery capacity in the U.S. LDV sector to afford the largest reduction in life cycle greenhouse gas (GHG) emissions by model-year. The study evaluates the prospective life cycle GHG emissions of the U.S. LDV fleet using a bottom-up approach, accounting for often-neglected characteristics such as vehicle classes, powertrain architectures, regional differences impacting energy consumption (e.g., drive-cycle, ambient temperatures) and background modified inventories impacting the production characteristics of sectors that feed into the LDV life cycle such as electricity, fuel and steel. The study focuses on three powertrain technologies (hybrid, plug-in hybrid, and battery electric vehicles), different ranges and powertrain architectures (e.g. series, parallel, power-split) and five vehicle classes (from compact car up to pickup truck) and four model-years (2023, 2030, 2040 and 2050). The study integrates the latest U.S. vehicle characteristics as obtained from the 2023 vehicle technology assessment[7] by Argonne National Laboratory as well as other relevant attributes (drive cycle, electricity grid) in the Carculator lifecycle assessment model[8]. The modeling leverages the Premise[9] background modified inventories to evaluate the impacts per vehicle type under different policy scenarios (business-as-usual, or 66% chance of remaining within 2oC and 1.5oC above pre-industrial levels). The vehicle lifecycle modeling is then coupled with a linear optimization model to determine how different prospective amounts of battery capacity supply should be optimally allocated across new LDV sales in each county to minimize the resulting life cycle GHG emissions per model-year.

The results reveal considerable tradeoffs between efficient battery allocation and the GHG mitigation potential of electrified powertrains across vehicle, temporal and spatial markets. The average midsize BEV with a 300-mile range requires 6 times the battery capacity of a plugin hybrid vehicle with a 35-mile range, and 70 times the battery capacity of a parallel hybrid electric vehicle, to mitigate only 1.5 and 3 times the emissions mitigated by these powertrains compared to a gasoline internal combustion engine vehicle (ICEVG). The spatial analysis highlights large variations of these tradeoffs across U.S. counties and market segments.

The optimization results establish that if only 30% of the battery capacity required for full fleet electrification of a model-year fleet is available, hybrid and plugin hybrid electric vehicles should be prioritized over BEV deployment as a way to remove the largest number of ICEVGs from the fleet. With such strategies in place, half of the 2023 and 2050 model-year life cycle GHG emissions would be mitigated. If a larger supply of batteries is available for each model year, BEV deployment becomes more suitable and necessary to minimize model-year GHG emissions, starting from urban counties with clean electricity grids. These findings challenge the efficacy of uniform BEV-focused policies, advocating for more flexible, adaptive fleet electrification strategies.

References

[1] C. Xu, Q. Dai, L. Gaines, M. Hu, A. Tukker, and B. Steubing, “Future material demand for automotive lithium-based batteries,” Commun. Mater., vol. 1, no. 1, Art. no. 1, Dec. 2020, doi: 10.1038/s43246-020-00095-x.

[2] International Energy Agency, “Energy Technology Perspectives 2023,” Energy Technol. Perspect., 2023.

[3] “BNEF Electric Vehicles Outlook 2024.” Accessed: Aug. 08, 2024. [Online]. Available: https://assets.bbhub.io/professional/sites/24/847354_BNEF_EVO2024_ExecutiveSummary.pdf

[4] D. Gohlke et al., “Quantification of Commercially Planned Battery Component Supply in North America through 2035,” ANL--24/14, 2319242, 187735, Mar. 2024. doi: 10.2172/2319242.

[5] B. Tarabay, A. Milovanoff, A. F. N. Abdul-Manan, J. McKechnie, H. L. MacLean, and I. D. Posen, “New cathodes now, recycling later: Dynamic scenarios to reduce battery material use and greenhouse gas emissions from U.S. light-duty electric vehicle fleet,” Resour. Conserv. Recycl., vol. 196, p. 107028, Sep. 2023, doi: 10.1016/j.resconrec.2023.107028.

[6] F. Degen, M. Mitterfellner, and A. Kampker, “Comparative life cycle assessment of lithium-ion, sodium-ion, and solid-state battery cells for electric vehicles,” J. Ind. Ecol., vol. 1, no. 16, 2024, doi: 10.1111/jiec.13594.

[7] E. Islam et al., “Detailed Simulation Study to Evaluate Future Transportation Decarbonization Potential,” ANL/TAPS--23/3, 2279172, 186057, Oct. 2023. doi: 10.2172/2279172.

[8] R. Sacchi and C. Mutel, Carculator: prospective environmental and economic life cycle assessment of vehicles. (Dec. 18, 2019). Zenodo. doi: 10.5281/ZENODO.3778259.

[9] R. Sacchi et al., “PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models,” Renew. Sustain. Energy Rev., vol. 160, p. 112311, May 2022, doi: 10.1016/j.rser.2022.112311.