Quantifying biodiversity impacts of hydropower electricity production within the framework of Life Cycle Assessment

Abstract

The United Nations developed 17 Sustainable Development Goals (SDGs) for the transition into a more sustainable world. One of the central aspects of the SDGs is the provisioning of sustainable energy, covered by SDG 7 (Affordable and clean energy). Hydropower, the largest source of renewable electricity production, has a huge potential to contribute to the fulfilment of SDG 7. As the SDGs can be viewed as a network, fulfilment of the SDG 7 targets can lead to positive synergies and negative trade-offs with other SDGs. Due to relatively low CO2 emissions, compared to other energy technologies, hydropower electricity production can help to fulfil SDG 13 (Climate action). However, due to land use and land use change, freshwater habitat alteration and water quality degradation, hydropower electricity production may negatively affect terrestrial and aquatic biodiversity. This can lead to negative trade-offs with SDG 6 (Clean water and sanitation) and SDG 15 (Life on land). Life Cycle Assessment (LCA) is a tool that is used to analyse the environmental impacts of a product or process throughout all its life cycle stages. Hence, LCA can help to identify locations where hydropower electricity production will have the lowest biodiversity impact. However, due to a lack of methods, so far no LCA study has accounted for biodiversity impacts of hydropower electricity production. This PhD work was part of the “Towards sustainable renewable energy production (SURE): Developing a Life Cycle Impact Assessment framework for biodiversity impacts” project, and aimed to advance and develop operational LCA related methods for the assessment of biodiversity impacts of hydropower electricity production in LCA. The assessment of biodiversity impacts of hydropower electricity production in LCA requires sitespecific Life Cycle Inventory (LCI) data. In Chapter 2, the first net land occupation LCI parameters for existing Norwegian hydropower reservoirs are provided. The underlying model uses satellite images to account for the natural water surface area before dam construction. The newly developed method has the potential for global application to all reservoirs where annual electricity production is reported. The net land occupation values from Chapter 2 enabled a calculation of net water consumption values for Norwegian hydropower reservoirs in Chapter 3. To quantify this water consumption, an evaporation model with global coverage was used, having again the potential for global application. In the Life Cycle Impact Assessment (LCIA) step, characterization factors (CFs) are required, to transform the calculated land occupation and water consumption LCI values into potential biodiversity impacts. For the LCIA impact category “water stress”, so far no CFs existed that could quantify the aquatic biodiversity impact of water consumption in a recently (in geological time) glaciated region like Norway. Therefore, the first spatially-explicit CFs quantifying biodiversity impacts of water consumption in a post-glaciated region were developed in Chapter 3. The novelty behind these CFs is that they include Species-discharge relationships (SDR), which account for local variation in fish fauna by delineating regions with the same postglacial freshwater fish immigration history. Inside the LCIA impact category “land stress”, so far no CFs covering land use change from terrestrial to aquatic habitat existed, even though this may be a major environmental change occurring during reservoir creation. Therefore, in Chapter 4, the first global CFs that quantify the potential future biodiversity impact of inundating terrestrial habitat area were developed. To follow current recommendations from the Life Cycle Initiative hosted by UN Environment and to enhance comparability, the CFs are based on an adaptation of the methodology developed by Chaudhary et al. 2015. In Chapter 5, a global and spatially explicit assessment of terrestrial and freshwater biodiversity impacts of potential future hydropower reservoirs is performed. This is done by combining a highresolution, technical assessment of the future ecological economic hydropower potential (Gernaat et al. 2017) with the developed LCA models in this thesis and existing methodology. The results reveal that carefully selecting future hydropower reservoir locations can significantly avoid future biodiversity impacts and can in turn help to achieve the development of sustainable renewable energy. In summary, this thesis contributes models to the research community that now allow the assessment of damages on ecosystem quality from hydropower electricity production (and additional stressors) within LCA, especially regarding the impact categories “water stress” and “land stress”. However, it is not possible to assess all relevant biodiversity impacts (yet), wherefore further methodological developments are needed.