Development of a simulation-based decision support workflow for the implementation of Building-Integrated Agriculture (BIA) in urban contexts

摘要

Providing healthy food for the world's growing urban population is a recognized global challenge and it is likely that current modes of conventional, large-scale farming will over time be increasingly complemented by local, urban farming practices. Apart from its acknowledged social benefits, urban farming is also widely viewed as a more resource-efficient alternative to conventional remote farming. Especially indoor, soilless cultivation in urban areas is being portrayed as a particularly sustainable solution. However, as this technique relies on controlled environments, its ongoing operation can be quite energy intensive and related carbon emissions should be carefully weighed against reduced emissions, such as those from transportation. To further this goal, this article presents a simulation-based environmental analysis workflow for Building-Integrated Agriculture (BIA) in urban contexts, that includes detailed solar radiation, water and energy specific models. The aim of the workflow is to guide the User through decision-making on the potentialities of implementing BIA in a given neighborhood while maximizing crop yields and minimizing water and energy consumption. The workflow was applied to three hi-tech urban farming scenarios in Lisbon, Portugal: a polycarbonate Rooftop Greenhouse (RG), a Vertical Farm (VF) with windows and skylights on the top floor of a reinforced-concrete building as well as a completely opaque VF with no penetration of natural light on the ground floor of a reinforced-concrete building. Global Warming Potential (GWP) related to water, transportation and operational energy of these three case studies were compared to GWP of (i) the currently existing supply chain for tomato, and (ii) a hypothetical low-tech unconditioned rooftop urban farm. Results show that the RG and the top floor VF had the best overall environmental performance, respectively cutting greenhouse gas emissions in half and in three in comparison with the existing supply chain for tomato. By allowing this preliminary assessment of alternative farm locations and properties, the workflow provides the user with actionable information for early-stage holistic assessment of BIA projects. (C) 2017 Elsevier Ltd. All rights reserved.