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In this paper, we develop a decisional framework and a mathematical model for the sustainable design of biodiesel supply chain networks (BSCND). We consider a broad group of sustainable aims, i.e. standard economic goals (revenue and logistics costs of BSCND), environmental issues based on a biodiesel production life cycle assessment (LCA), and the social incidental aspects (e.g. crime control, political stability, and community attitude, among others). The framework begins with a simulation of the biodiesel production system, feeding later, with suitable input parameters and suitable solutions, and a macro-location model designed to establish the regional positioning of biofuel conversion plants. Optimal regions are used as initial feasible solution space for the proposed micro-location model. In this part of the framework, we introduce an adaptation of Extended Goal Programming to rank the best municipalities (definitive locations) emphasizing the social aspects under consideration. The framework application is set up in the following Colombian context: first generation biodiesel production from palm oil feedstock. Our computational results indicate that the Colombian city of Rionegro (in the Santader region) is the most sustainable location for a new biodiesel plant. [ABSTRACT FROM AUTHOR]

The global contribution of all kinds of organizations to greenhouse gas (GHG) emissions is noteworthy. Calculating, reporting, reducing, and compensating for carbon footprints are the appropriate steps to take to guide companies toward a path that is compatible with their country's objectives for the fulfillment of the Paris Agreement. In Latin American countries, carbon footprint reporting is limited and incipient. This paper aims to start closing this gap by assessing the carbon footprint of a university operating in the city of Bogotá, Colombia. Based on a city input-output table (IOT) nested in a multiregional input-output (MRIO) table framework, we estimate the three categories of the carbon footprint (scopes 1, 2, and 3) identified by the Greenhouse Gas Protocol using an improved multiregional tiered hybrid analysis of the university's energy and other input expenditures. Our results show that 94% of the entire institution's footprint is attributed to scope 3, which represents indirect emissions linked to the upstream value chain. The results allow us to identify emission hotspots and their impact on the supply chain, which can be helpful for reducing costs and encouraging organizations, users, and suppliers to make more sustainable decisions. [ABSTRACT FROM AUTHOR]