ECOS 2023: Environmental life cycle assessment of a hydropower plant in Bolivia

Abstract

Hydropower technologies are usually related to low-carbon emissions; however, detail discussion of a different number of environmental concerns is not properly done at the moment especially considering the lifetime phases. There is also a lack of evaluations when comparing with conventional technologies and when comparing with traditional Environmental Impact Assessments (EIA). In this context, this paper explored the environmental impacts using the LCA methodology of a hydropower plant to identify which lifetime phases damage more in health, ecosystems and resource areas of protection. A comparison between the impacts with the grid conventional electricity generation and a comparison with the results of the conventional EIA method are also presented. A database of a cascade hydropower in the tropical region is built using as a case study, the Bolivian project named “Ivirizu” with 290.21 MW of power capacity. Reservoir hydropower plant, campsite and road are analyzed. Data collection considered materials transportation, grave production, construction, maintenance, operation and disposal step. Data was obtained directly from the Governmental energy corporations and Ecoinvent database. Biogenic emissions were determined using the model proposed by Hertwich, 2013. ReCiPe 2016 method was employed to calculate the mid-point and end-points environmental impacts. The construction phase was found to impact most. This phase impacts on the resources depletion by 98.16%. This due to diesel is mainly required during the construction phase. This phase also impacts in 71.17% in human health mainly. The operation has 34.31% of contribution of impacts in ecosystems. This is due to high levels of water consumption during electric generation. The damage on resources is reduced in 63.32 % while hydropower lifetime is increased up to 150 years. Hydropower electricity has more than 79.00% less impacts compared with grid electricity. LCA results could contribute significantly in traditional EIA by providing quantitative information.