Since the introduction of neoclassical economic theory, material wealth and accumulation have been linked to hedonic wellbeing. In turn, Utilitarian notions have generated the belief that infinite growth is not only good but necessary for society to prosper. Unsurprisingly, this belief system has supported the considerable depletion of natural resources and has not always led to social equitability or environmental justice, two pillars of sustainable development. Given these limitations, this paper looks into eudaimonic wellbeing, as defined by Stoicism. The latter originating in Classical Greece and Ancient Rome, has been used throughout the centuries to discuss and support the flourishing of individuals, but has rarely been applied to collective wellbeing. Consequently, we explore whether, and to what extent, this virtue-based philosophy can answer questions regarding the value and the role of material acquisition in societal development, as directed by sustainable policy. We propose the idea that the Stoic emphasis on prudence, self-control, courage and justice, as the only means to achieve “happiness”, is intrinsically linked to sustainable wellbeing and that its principles can be used to demonstrate that society does not require limitless growth to flourish.

Abstract:We built an emission inventory (EI) for the megacity of Bogotá, Colombia for 2012, which for the first time augments traditional industrial and mobile sources by including commercial sources, biogenic sources, and resuspended dust. We characterized the methodologies for estimating each source annually, and allocated the sources to hourly and 1 km 2 spatial resolution for use as inputs for air quality modeling purposes. A resuspended particulate matter (RPM) emission estimate was developed using the first measurements of road dust loadings and silt content for the city. Results show that mobile sources dominate emissions of CO 2 (80%), CO (99%), VOC (68%), NO x (95%), and SO 2 (85%). However, the newly estimated RPM comprises 90% of total PM 10 emissions, which are at least onefold larger than the PM 10 emissions from combustion processes. The 2012 EI was implemented in a chemical transport model (CTM) in order to understand the pollutants' fate and transport. Model evaluation was conducted against observations from the city's air quality monitoring network in two different periods. Modeling results for O 3 concentrations showed a good agreement, with mean fractional bias (MFB) of +11%, and a mean fractional error (MFE) of +35% with observations, but simulated PM 10 concentrations were strongly biased high (MFB +57%, MFE +68%), which was likely due to RPM emissions being overestimated. NO x , CO, and SO 2 were also biased high by the model, which was probably due to emissions not reflecting current fleet conditions. Future work aims to revise emission factors for mobile sources, which are the main sources of pollutants to the atmosphere.