A Life Cycle Impact Assessment method was developed to evaluate the environmental impact associated with salinity on biodiversity in a Spanish coastal wetland. The developed characterization factor consists of a fate and an effect factor and equals 3.16 × 10(-1) ± 1.84 × 10(-1) PAF · m(3) · yr · m(-3) (PAF: Potentially Affected Fraction of species) indicating a "potential loss of 0.32 m(3) ecosystem" for a water consumption rate of 1 m(3) · yr(-1). As a result of groundwater consumption with a rate of 1 m(3) · yr(-1), the PAF in the lost cubic meter of ecosystem equals 0.05, which has been proposed as the maximum tolerable effect to keep the ecosystem intact. The fate factor was calculated from seasonal water balances of the wetland Albufera de Adra. The effect factor was obtained from the fitted curve of the potentially affected fraction of native wetland species due to salinity and can be applied to other wetlands with similar species composition. In order to test the applicability of the characterization factor, an assessment of water consumption of greenhouse crops in the area was conducted as a case study. Results converted into ecosystem quality damage using the ReCiPe method were compared to other categories. While tomatoes are responsible for up to 30% of the impact of increased salinity due to water consumption on ecosystem quality in the studied area, melons have the largest impact per tonne produced.
This paper presents the inclusion of new, relevant impact categories for agriculture life cycle assessments. We performed a specific case study with a focus on the applicability of spatially explicit characterization factors. The main goals were to provide a detailed evaluation of these new impact category methods, compare the results with commonly used methods (ReCiPe and USEtox) and demonstrate how these new methods can help improve environmental assessment in agriculture. As an overall conclusion, the newly developed impact categories helped fill the most important gaps related to land use, water consumption, pesticide toxicity, and nontoxic emissions linked to fertilizer use. We also found that including biodiversity damage due to land use and the effect of water consumption on wetlands represented a scientific advance toward more realistic environmental assessment of agricultural practices. Likewise, the dynamic crop model for assessing human toxicity from pesticide residue in food can lead to better practice in pesticide application. In further life cycle assessment (LCA) method developments, common end point units and normalization units should be agreed upon to make it possible to compare different impacts and methods. In addition, the application of site-specific characterization factors allowed us to be more accurate regarding inventory data and to identify precisely where background flows acquire high relevance.
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