Abstract Daniel Enrique Cort?s Borda
In today?s globalized market, the lack of knowledge about how the impacts distribute among nations hinders the design of effective policies for reducing the environmental degradation at a global scale. The aim of this thesis is to combine macroeconomic models with multi-objective optimization to facilitate the quantification of environmental loads, the fair allocation of responsibilities, and the design of effective public policies aiming at sustainability. To these end here we propose quantitative methods based on environmentally extended input-output models to study the contribution of nations to the global environmental pressures by examining the life cycle of products consumed worldwide; the trade-embodied environmental loads; and the equity with which impacts are distributed. Findings may help to design effective policies ensuring a fair allocation of responsibilities. This thesis also proposes a systematic multi-objective optimization approach for simultaneously minimizing the environmental impacts and maximizing the output of an economy. The bi-criteria linear programming model identifies key sectors with significant impact contribution and low output. Results show that, with the existing technologies, the environmental impacts could be lowered in higher proportion than the economic output by controlling adequately the demand of sectors. Moreover, this thesis proposes a method based on linear-programming to facilitate decision-making in environmental studies in an inverse manner. That is, given a set of solutions, this method finds the lower and upper limits of the intervals within which the weights to be attached to the indicators must fall, so that the selected alternative becomes optimal. Thereby, decision makers are not required to provide weights beforehand that could lead to biased results.
Download: