Characterisation model approach for LCA to estimate land use impacts on pollinator abundance and illustrative characterisation factorsAlejandre, E. M., Potts, S. G. ORCID: https://orcid.org/0000-0002-2045-980X, Guinée, J. B. and van Bodegom, P. M. ORCID: https://orcid.org/0000-0003-0771-4500 (2022) Characterisation model approach for LCA to estimate land use impacts on pollinator abundance and illustrative characterisation factors. Journal of Cleaner Production, 346. 131043. ISSN 0959-6526
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1016/j.jclepro.2022.131043 Abstract/SummaryThis study presents the first approach to characterise relative land use impacts on pollinator abundance for life cycle assessment (LCA). Pollinators make an essential contribution to global crop production and in recent years evidence of declines has raised concerns on how land use, among other factors, affects pollinators. Our novel method assesses land use impacts on pollinator abundance and proposes a new impact category that is compatible with the current framework of life cycle impact assessment (LCIA). While a systematic literature research showed the existence of multiple models that could assess pollinator abundance impacts, their parameterization is too complicated for applications in LCA. Therefore, a simplified method based on expert knowledge is presented. The practical application of the method is illustrated through the connection to, and characterisation of, relevant land use types derived from the widely used LCA database, ecoinvent. The illustrative characterisation factors demonstrate that key differences among land use types can be reflected through the proposed approach. Further development of robust characterisation factors through a larger sample of pollinator abundance estimates, and improvements to the model, such as considerations of spatial differentiation, will contribute to the identification of impacts of agricultural practices in LCA studies, helping prevent further pollinator abundance decline.
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