Exploring Trade-Offs between Potential Economic, Social and Environmental Outcomes of Urban Agriculture in Adelaide, Australia and the Kathmandu Valley, Nepal

Abstract

Urban Agriculture (UA) is widely presented as a feature of sustainable cities, with various claims around economic, social, and/or environmental benefits. However, the extent to which these different benefits may reinforce or compete with one another is not clear. This paper presents an integrated modelling framework using proxy measures for economic benefit (the net margin, NM), social benefit (the full-time farmer employment equivalent (FTE) per consumer) and environmental benefit (reduction in carbon dioxide emissions, CO2). The model is applied in two divergent development scenarios, including Adelaide, Australia, and the Kathmandu Valley, Nepal, to study the characteristic features of UA in different settings. Two-stage optimisation is used to explore trade-offs and synergies when pursuing different objectives (NM, FTE and CO2). The model seeks the optimal farming area and selects from three levels of mechanisation (non-mechanised, garden tiller and garden cultivator), two purposes (gardening and commercial), two crop value categories (mixed and mid- to high-value vegetables) and two market mechanisms (wholesale vs. retail). The results of the optimisation provide insights into the key features of a UA system depending on the objective(s) being pursued, which we believe is a novel approach to justify UA research. For instance, the model favours a commercial UA form (in which both land and labour are costed) with a larger area when pursuing an economic objective, whereas it favours a gardening form of UA when aiming to maximise participation in the food system, with the preferred area depending on the extent to which either the economic or environmental objective is also being pursued. In Adelaide, the model favours commercial UA for the best-case profit and carbon emissions, and gardening for FTE maximisation. In the Kathmandu Valley, the model chooses the gardening UA within the given model assumptions.