ArticleData in brief2025
Life cycle inventory dataset for energy production and storage technologies: Standardized metrics for environmental modeling.
Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The presented dataset provides the results of a comprehensive inventory of Life Cycle Assessments (LCA) for multiple energy production and storage technologies. Unlike conventional LCA studies, which often provide case-specific data that are difficult to apply in the analysis and design of energy systems, this work delivers standardized values, expressed per unit of installed capacity (kW), and, where relevant, per unit of operational energy output (kWh). These normalized metrics are essential for the integration of environmental considerations into energy system modeling and optimization. The dataset is the result of a comprehensive review of peer-reviewed studies, institutional reports, industrial data, and existing LCA databases. Robust average values were derived by consolidating information from multiple sources, thereby addressing a key gap in the literature whereby heterogeneous and fragmented data can make their practical application problematic. Minimum and maximum estimates are also reported to characterize the variability across technologies and datasets, providing a more comprehensive understanding of the underlying uncertainty. Unlike existing LCA databases, which are often paywalls, and can have highly detailed but less accessible data, this method provides aggregated and user-friendly parameters that are ready for direct use. The inventory covers such technologies as photovoltaic systems, energy storage solutions, hydrogen production, internal combustion engines, boilers, heat pumps, and organic Rankine cycles, as well as energy carriers, including natural gas, electricity, hydrogen, and biomass. Environmental impacts are reported across multiple midpoint categories, such as the global warming potential, mineral and metal depletion, land and water use, particulate matter, acidification, eutrophication, ecotoxicity, ionizing radiation, human toxicity, and the ozone depletion potential. The dataset, which was drawn up according to International Reference Life Cycle Data System (ILCD), ReCiPe Life Cycle Impact Assessment Method (ReCiPe), and Intergovernmental Panel on Climate Change Global Warming Potential (IPCC GWP) guidelines, ensures consistency and comparability across technologies. Moreover, the dataset, which is provided as an open-access Excel Workbook, is readily applicable to environmental assessments, optimization studies, and energy planning in energy communities and smart grids, to support informed decisions for sustainable energy transitions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.