The concept of vertical farming is nearly twenty years old, however, there are only a few experimental prototypes despite its many advantages compared to conventional agriculture. Significantly, financial uncertainty has been identified as the largest barrier to the realization of a ‘real' vertical farm. Some specialists have provided ways to calculate costs and return on investment, however, most of them are superficial with calculations based on particular contextual circumstances. To move the concept forwards a reliable and flexible estimating tool, specific to this new building typology, is clearly required. A computational system, software named VFer, has therefore been developed by the authors to provide such a solution. This paper examines this highly flexible, customised system and results from several typical vertical farm configurations in three mega-cities (Shanghai, London and Washington DC) are used to elucidate the potential economic return of vertical farms.

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Vertical farming is a new branch of urban agriculture using indoor vertical space and soil-less cultivation technology to obtain agricultural products. Despite its many advantages over traditional farming, it still faces some challenges and obstacles, including high energy consumption and costs, as well as uncertainty and a lack of social acceptance. This study aims to investigate the influence of public acceptance on micro-vertical farming based on the deconstructed theory of planned behavior model. This model is adopted for statistical analysis to reveal the factors and their weights in influencing people’s behavioral intentions. The results indicate that the overall mean of the public’s behavioral intentions to use vertical farming is 3.9, which is above neutral (M = 3.00) but less than positive (M = 4.00). Differences in age, education level, and the living area of the public have significantly impacted behavioral intentions. Meanwhile, the statistical results support the hypotheses concerning the behavioral attitudes, subjective norms, and perceived behavioral control of the model, and also demonstrate that their decomposed belief structures considerably influence the public’s behavioral intentions to use vertical farming. Notably, perceived usefulness is the most critical driving factor in planting using vertical farming. The findings of this study contribute to better predictions of the effects of different elements of behavioral intention on vertical farming at the urban scale, which may provide a basis for decision making in the development of sustainable urban agriculture.

Living wall systems have been widely recognized as one of the promising approaches for building applications due to their aesthetic value and ecological benefits. Compared with outdoor living wall systems, indoor living wall systems (ILWS) play a more vital role in indoor air quality. The aim of this study is to investigate the effects of ILWS on indoor air quality. In an office building, two parallel corridors were selected as comparative groups. A 10.6 m2 ILWS was installed on the sidewall of the west corridor while the east corridor was empty. Some important parameters, including indoor air temperature, relative humidity, concentrations of carbon dioxide (CO2), and particulate matter (PM) were obtained based on the actual environment monitoring. According to the statistical analysis of the data, there were significant differences in the concentrations of CO2 and PMs in the corridors with and without ILWS, which indicated that CO2 and PM2.5 removal rate ranged from 12% to 17% and 8% to 14%, respectively. The temperature difference is quite small (0.13 °C on average), while relative humidity slightly increased by 3.1–6.4% with the presence of the ILWS.