# Life Cycle Assessment of Land Use Trade-Offs in Indoor Vertical Farming +
## 2 Materials and Methods
### Life Cycle Assessment
#### 2.3.2 Life Cycle Inventory  
This study was built upon the inventory used by [PERSON], [PERSON] et al. (2022) [7], incorporating modifications and updated data. The infrastructure, equipment (including the photovoltaic system), consumables, water, and nutrients remained consistent with the original study. Life Cycle Inventory activity data were collected either on site or  
Figure 1: System boundaries “grower to grocer” include Construction, Installation, Cultivation, Packaging and Delivery processes for 1 kg-packed fresh leaf microgreens bag.  
through estimates provided by facility operators and modeled with LCA for Experts v.10.9.0.20. The databases used to access background data were a combination of Sphera and ecoinvent v.3.9.1, supplemented by Agribalsye v.3.0.1. Assumptions and limitations regarding these processes, along with detailed lists of their specific inputs, are provided in the Supplementary Material. Details of the modified processes and updates to data inputs compared to the previous work are given hereafter.  
The energy mix reported in the inventory represents the average production mix used in Portugal from January 2024, which consisted of 5.0% natural gas, 3.8% fossil Combined Heat and Power, 38% hydro, 28% wind, 6.7% bioenergy, 10% solar, and 7.9% pumped storage, according to the Portuguese National Energy Association [37]. As indicated in the ecoinvent database, there was a 4.4% loss taken into consideration for the non-photovoltaic energy vectors as a result of the conversion from high voltage to low voltage [37].  
The \"GLO: market for rape seed, organic\" dataset from ecoinvent was chosen as the most appropriate option for modeling the seeds production due to its similarity to broccoli, as both belong to the Brassica plant family. This specific input reflects the _Brassica napus_ species. This dataset replaced the previous model's dataset, \"Cauliflower seed, conventional, at production site/FR U\" from Agribalsye, which had been rebuilt on ecoinvent using equivalent flows. Despite cauliflower also belonging to the same plant family, the earlier study's dataset replication used equations to address the lack of an input flow, introducing additional variability to the model. By opting for the rape seed dataset, this study aims to reduce uncertainty associated with seeds, which were identified as the most significant input from the environmental point of view in the previous paper.  
The \"Coconut fiber, at regional storehouse/kg\" dataset was selected for modeling substrate production. The dataset was copied from Agribalsye and replicated on ecoinvent introducing a key modification: coconut fiber was reclassified as a by-product. This reclassification shifts the environmental burden associated with its production to the coconut, unlike in the previous model. However, the processes involving husk transformation and transportation were still included in the assessment.  
The organic waste produced by the harvesting process was counted as \"AT: Open window composting (incl. compost application and crediting) BOKU/Sphera\", while in the previous study it had been allocated either to generic municipal solid waste or as a circular, locally used byproduct for compost production.  
Input flows to account for the direct land use were considered. The chosen flows were \"Urban, continuously built (regionalized, PT) [Occupation]\", applied to both the preparation and work areas.