Marginal technology based on consequential life cycle assessment. The case of Colombia

Abstract

Electricity data is one of the key factors in life cycle assessment (LCA). There are two different approaches to model electricity and to apply average or marginal data in LCA studies. Marginal data is used in consequential whereas average data is considered in attributional studies. The aim of this study is to provide the long-term marginal technology for electricity power generation in Colombia until 2030. This technology is one capable of responding to small changes in demand on the market and is an important issue when assessing the environmental impacts of providing electricity. Colombia is a developing country with a national power grid, which historically has been dominated by Hydropower rather than fossil fuels. This particularity makes Colombian national power grid vulnerable to climatic variations; therefore, the country needs to introduce renewable resources into the power grid. This study uses consequential life cycle assessment and data from Colombian national plans for capacity changes in the power grid. The results show that whereas marginal electricity technology would most probably be Hydropower, Wind and Solar power are projected to reach more than 1% of the national power grid by 2030.