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Prospective Environmental Assessment of Urban Agriculture Emerging-Systems

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Urban agriculture’s contribution to environmental sustainability

A temporally explicit environmental impact assessment elucidates the significant role of urban agriculture for a future food supply.

Climate Change and Environment
Food and Natural Resources

Urban agriculture is the cultivation, processing and distribution of food in or around urban areas. It includes a complex and diverse mix of food production such as vertical farming and green rooftops. Compared to more traditional agricultural systems in terms of energy and water use, it has emerged as a more sustainable alternative for producing food. Being able to quantify the effective contribution that urban agriculture will make to the environmental sustainability of cities requires the capacity both to evaluate its environmental impacts in the future and to compare them to the impacts of traditional agriculture in the same future context. In line with this need, the EU-funded PROTEAN project, with the support of the Marie Skłodowska-Curie Actions (MSCA) programme, aimed to develop prospective life cycle databases to calculate future life cycle impacts of food production. “And in this way, [PROTEAN will] enable the comparison of food production via conventional agriculture and via urban agriculture, all in the future context,” explains Angelica Mendoza, MSCA fellow.

Creating life cycle databases

At its core, PROTEAN sought to provide a systematic method for coupling two sets of data for prospective life cycle databases. The first data set came from internationally relevant models dedicated to the calculation of climate change scenarios under different socio-economic pathways, the so-called integrated assessment models. The second set of data describes the life cycle of product systems, the so-called life cycle inventory (LCI) databases. “Coupling the two supports the calculation of more robust prospective life cycle assessments (LCAs), as the prospective LCI databases account for changes in major economic sectors expected in the future,” adds Mendoza.

Pivotal information for urban planners and policymakers

“We first found there was an enormous societal need for quantifying future impacts of products, as we are striving to manage the climate crisis and other exceeded planetary boundaries” confirms Mendoza. Further, PROTEAN realised that few quantitative tools could provide such assessment; from there, the importance of developing prospective LCI databases and prospective LCAs further was evident. “We also learned that not only was the temporal dimension important, but the spatial dimension was also particularly important for the case of peri-urban agriculture,” adds Mendoza. The geographical display of inventory flows and impacts serves an important function in understanding urban resilience, global sustainability and multifunctionality of urban agriculture as a nature-based solution. This is vital information for urban planners and policymakers. “Thus, we ended up applying and developing further the methodologies of regionalised-prospective LCA,” confirms Mendoza.

The added value of peri-urban agriculture

PROTEAN focused on applications of the methodological development for the metropolitan area of Barcelona. “We realised that primary data, i.e. data from the field, is scarce and scattered, and therefore we believe that in the short-to-medium term, calibrating our models with primary data is essential to verify conclusions,” notes Mendoza. In the longer term, the project aims to complete the assessment of the increase of peri-urban agriculture areas, as proposed by the Urbanistic Development Plan for the metropolitan area. “We hope in this spatio-temporal LCA we can understand the added value of peri-urban agriculture with respect to imported food and its role within the circularity of the city,” concludes Mendoza.


PROTEAN, urban agriculture, life cycle databases, food production, traditional agricultural systems, integrated assessment models, peri-urban agriculture, life cycle inventory, LCA, LCI

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