Linking Life Cycle and Integrated Assessment Modeling to Evaluate Technologies in an Evolving System Context: A Power-to-Hydrogen Case Study for the United States.

Carbon-neutral hydrogen (H2) can reduce emissions from hard-to-electrify sectors and contribute to a net-zero greenhouse gas economy by 2050. Power-to-hydrogen (PtH2) technologies based on clean electricity can provide such H2, yet their carbon intensities alone do not provide sufficient basis to judge their potential contribution to a sustainable and just energy transition. Introducing a prospective life cycle assessment framework to decipher the non-linear relationships between future technology and energy system dynamics over time, we showcase its relevance to inform research, development, demonstration, and deployment by comparing two PtH2 technologies to steam methane reforming (SMR) across a series of environmental and resource-use metrics. We find that the system transitions in the power, cement, steel, and fuel sectors move impacts for both PtH2 technologies to equal or lower levels by 2100 compared to 2020 per kg of H2 except for metal depletion. The decarbonization of the United States power sector by 2035 allows PtH2 to reach parity with SMR at 10 kg of CO2e/kg H2 between 2030 and 2050. Updated H2 radiative forcing and leakage levels only marginally affect these results. Biomass carbon removal and storage power technologies enable carbon-negative H2 after 2040 at about -15 kg of CO2e/kg H2. Still, both PtH2 processes exhibit higher impacts across most other metrics, some of which are worsened by the decarbonization of the power sector. Observed increases in metal depletion and eco- and human toxicity levels can be reduced via PtH2 energy and material use efficiency improvements, but the power sector decarbonization routes also warrant further review and cradle-to-grave assessments to show tradeoffs from a systems perspective.

A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data.

The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements. These databases, often referred to as inventories, can be used for a wide variety of environmental reporting and modeling purposes to characterize conditions in the United States. Yet, users are often challenged to find, retrieve, and interpret these data due to the unique schemes employed for data management, which could result in erroneous estimations or double-counting of emissions. To address these challenges, a system called Standardized Emission and Waste Inventories (StEWI) has been created. The system consists of four python modules that provide rapid access to USEPA inventory data in standard formats and permit filtering and combination of these inventory data. When accessed through StEWI, reported emissions of carbon dioxide to air and ammonia to water are reduced approximately two- and four-fold, respectively, to avoid duplicate reporting. StEWI will greatly facilitate the use of USEPA inventory data in chemical release and exposure modeling and life cycle assessment tools, among other things. To date, StEWI has been used to build the recent USEEIO model and the baseline electricity life cycle inventory database for the Federal LCA Commons.

Derivation and assessment of regional electricity generation emission factors in the USA.

Purpose: Electricity production is one of the largest sources of environmental emissions-especially greenhouse gases (GHGs)-in the USA. Emission factors (EFs) vary from region to region, which requires the use of spatially relevant EF data for electricity production while performing life cycle assessments (LCAs). Uncertainty information, which is sought by LCA practitioners, is rarely supplied with available life cycle inventories (LCIs). Methods: To address these challenges, we present a method for collecting data from different sources for electricity generation and environmental emissions; discuss the challenges involved in agglomerating such data; provide relevant suggestions and solutions to merge the information; and calculate EFs for electricity generation processes from various fuel sources for different spatial regions and spatial resolutions. The EFs from the US 2016 Electricity Life Cycle Inventory (eLCI) are analyzed and explored in this study. We also explore the method of uncertainty information derivation for the EFs. Results and discussion: We explore the EFs from different technologies across Emissions & Generation Resource Integrated Database (eGRID) regions in the USA. We find that for certain eGRID regions, the same electricity production technology may have worse emissions. This may be a result of the age of the plants in the region, the quality of fuel used, or other underlying factors. Region-wise life cycle impact assessment (LCIA) ISO 14040 impacts for total generation mix activities provide an overview of the total sustainability profile of electricity production in a particular region, rather than only global warming potential (GWP). We also find that, for different LCIA impacts, several eGRID regions are consistently worse than the US average LCIA impact for every unit of electricity generated. Conclusion: This work describes the development of an electricity production LCI at different spatial resolutions by combining and harmonizing information from several databases. The inventory consists of emissions, fuel inputs, and electricity and steam outputs from different electricity production technologies located across various regions of the USA. This LCI for electricity production in the USA will prove to be an enormous resource for all LCA researchers-considering the detailed sources of the information and the breadth of emissions covered by it.