Review of inventory data in life cycle assessment applied in production of fresh tomato in greenhouse

Interest in the life cycle assessment (LCA) methodology to determine the environmental performance of agricultural products has increased in recent years. However, the application of LCA is sometimes limited by the lack of accurate, precise, and complete inventory data. In this study, we reviewed publications related to the LCA of fresh tomato production in greenhouses to provide an overview of the inventory data and identify opportunities for a more complete assessment of the environmental impact of tomato production. Among the reviewed publications, thirty-six papers were chosen for in-depth investigation. Additionally, the inventory data from seventeen of them were rigorously investigated, analyzed, and classified to be applied in the LCA of greenhouse tomato production. The selected papers cover forty-three scenarios involving the production of fresh greenhouse tomatoes in various regions. This review underlines the variations in inventory data among the studies and highlights inventory inputs that are commonly not considered in most assessments. In addition, the tomato production datasets of the commercial database Ecoinvent are discussed, and a recommendation on the usage of this database is provided. It is expected that future LCAs will disclose their inventory data in greater detail to improve transparency and help stakeholders in forming a more complete and informed opinion regarding LCA inventory content and its results. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This study reviews publications related to the LCA of fresh tomato production in greenhouses, provides an overview of inventory data, and identifies opportunities for a more complete assessment of the environmental impact of tomato production. Rigorously investigated, analyzed, and classified inventory data from selected papers highlights variations and commonly overlooked inputs, aiming to improve transparency and stakeholder understanding in future LCAs.