Soil quality, properties and functions in Life Cycle Assessment: an evaluation of models

Soils are key resources, providing essential ecosystem services and functions for supporting both human and ecosystem needs. Intensification and expansion of human activities has been putting a dramatic pressure on land throughout history. In the last 15 years, substantial efforts have been made to incorporate the impacts on land derived from production processes from a life cycle perspective, in order to improve the comparison of the environmental performance of products. It is critical for Life Cycle Assessment (LCA) the use of robust models that enable evaluating the effects of land use on soils. The present study performs a systematic, qualitative evaluation of up-to-date models that relate land occupation and land transformation to soil impact indicators in terms of soil properties, functions and threats. We evaluated both single and multi-indicators models against criteria including scientific soundness, stakeholders’ acceptance, reproducibility, as well as the applicability of models from the perspective of LCA practitioners. The study additionally proposes a new land use cause-effect chain to appraise the impacts of land use on soils. We identified a heterogeneous set of soil-related models, with relevant improvements in terms of applicability, robustness and completeness as compared to previous analyses. Trade-offs were frequent between the relevance of the modeled impact processes and model’s applicability. We identified several research needs, which include: adopting a common land use cause-effect chain and land use classification; accounting for different land management and land use intensities; assessing the added value of multi-indicators for comprehensively account for impacts; ensuring consistency from midpoint to endpoint, especially for biodiversity impacts; providing guidance to calculate normalization factors; and assessing the uncertainty of models results. Building consensus in the LCA community is essential to secure the comparability of models and setup robust practices for further developments.

VIDAL LEGAZ Beatriz;  MAIA DE SOUZA Danielle;  TEIXEIRA Ricardo F.M.;  ANTON Assumpcio;  PUTMAN Ben;  SALA Serenella; 

2016-11-02

ELSEVIER SCI LTD

JRC100277

0959-6526,   

http://www.sciencedirect.com/science/article/pii/S0959652616305418,    https://publications.jrc.ec.europa.eu/repository/handle/JRC100277,   

10.1016/j.jclepro.2016.05.077,