Graphene has emerged as an important nanomaterial owing to its remarkable physicochemical properties and wide-ranging applications. However, the increasing diversity and scale of graphene production raise concerns regarding energy demand, resource consumption, greenhouse gas emissions, toxicity, and other environmental burdens. Life cycle assessment (LCA) provides a systematic framework for evaluating these impacts, although LCA studies of graphene production remain relatively limited and methodologically heterogeneous. This critical review systematically examines published LCA studies of conventional and emerging graphene-production routes, including chemical vapor deposition, electrochemical production, chemical oxidation–reduction, epitaxial growth, thermal and sonication exfoliation, flash joule heating, biomass-derived processes, biological fabrication, wet jet milling, and laser-assisted approaches. Published studies were identified using a structured literature-search-and-screening procedure, and their system boundaries, functional units, energy and material requirements, and reported environmental impact indicators were critically compared. Across the reviewed literature, electricity consumption, carbon and chemical feedstocks, solvent use, and process scale are considered key factors determining environmental performance. Conventional synthesis routes can exhibit substantial energy or chemical burdens, whereas waste-derived, bio-based, and mechanical approaches offer opportunities for reducing environmental impacts. Flash joule heating and optimized wet jet milling demonstrate particularly promising environmental performance under the conditions reported in the available studies. However, direct comparisons between production routes remain constrained by differences in functional units, system boundaries, energy source, production scales, and impact-assessment methodologies. Future LCA studies should therefore prioritize harmonized assessment frameworks, transparent inventory reporting, industrial-scale data, and sensitivity analyses to support robust identification of environmentally preferable graphene-production pathways.
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Elmaghrabi et al. (2026) studied this question.
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