• Energy Research

AbstractGlobal biodiversity loss is most severe in freshwaters, particularly in river ecosystems. Hydropower is one of the main culprits. While being promoted as a carbon free source of renewable energy, hydropower disrupts the flow, habitats, and biota of rivers. Environmental policies and programs seek to mitigate the damage hydropower causes. Any policy action aiming at making the utilization of our rivers more sustainable must be ecologically, economically, and legally feasible. We show that the interdisciplinary feasibility of mitigation measures divides existing facilities into three categories (i) large facilities in which biodiversity mitigation measures are needed but electricity generation and balancing the electricity grid should remain as their main focus, (ii) small facilities in which dam removal and full scale river restoration measures can be taken by assisting the facilities to seize operations, preferably just before their next big investments, and (iii) medium facilities where benefits and trade‐offs associated with alternative paths should be analyzed case‐by‐case to determine the most feasible path forward. Policy action is feasible in all three categories but in different ways: requiring fish passes in the case of large facilities, helping remove dams and restoring the rivers in the case of small facilities, and focusing cost–benefit analysis efforts on the non‐trivial group of the medium sized facilities.

Abstract Sound cost-benefit analysis should acknowledge differences in the spatial distribution of cost-bearers, environmental effects and beneficiaries. Where the first two are often well-known by policymakers, identifying the area of affected beneficiaries through a common spatial distribution of values is still under debate. Using general rules for the spatial distribution of values has obvious appeal for cost-benefit analysis. With a five-country contingent valuation dataset of water quality, we study the performance of international benefit transfer at different spatial scales, making use of the EU regional statistics for NUTS 1, NUTS 2 and NUTS 3 levels. Unit value transfers yield the smallest transfer errors on average. For function transfers, spatially explicit models yield lower transfer errors. However, caution should be exercised in choosing a proxy for substitutes, as the choice of an intuitive proxy can cause unintuitive predictions. The choice between the NUTS 2 and 3 regional level statistics induces, on average, almost no difference in transfer errors when used as policy site data. However, a blind choice of transfer function form can have large effects on aggregate WTP estimates on the national and regional level when significant non-use values are present.