| Popis: |
The principle of Energy Efficiency First (EE1st) is gaining traction in the political debate. As set out in previous reports of ENEFIRST, the principle aims to consider and prioritise investments in demand side resources (e.g. building retrofits) whenever these cost less or deliver more value than default energy infrastructure (e.g. networks). Meanwhile, energy efficiency is increasingly associated with a variety of environmental, economic, and social benefits known as multiple impacts (MIs). It is often argued that taking thorough account of the EE1st principle in energy-related investment and policymaking means to incorporate MIs in the decision-making process to ensure a fair comparison of resource options. This concerns various decision-making instances – including the impact assessments prepared by the European Commission, infrastructure planning conducted by regulated network companies, up to individual building owners when assessing the costs and benefits of different building renovation options. However, a theoretical account of how the concepts of EE1st and MIs fit together is still missing. The objective of this paper is twofold. First, based on an expert workshop and a literature review, it aims to integrate the theoretical state of knowledge on the concepts of EE1st and MIs. This involves questions of how various MIs can be aggregated in the form of cost-benefit analysis (CBA), multi-criteria analysis (MCA) and other frameworks to inform decisions on what resource options actually provide greater value. We argue that, in itself, each of these frameworks has important limitations, which is why none of them can replace human judgement. For instance, CBA has inherent problems in coming up with robust monetary estimates of individual MIs, while MCA struggles with ensuring objectivity and representative stakeholder involvement. Another important issue is how the evaluation perspective (societal, private, etc.) affects the selection of MIs that should ideally be taken into account in quantitative assessments. Each of these perspectives is shown to have distinct application areas and practitioners should make sure to apply a consistent perspective when quantifying and aggregating MIs to compare resource options in the scope of EE1st. The second objective of this report is to address the ongoing lack of quantitative evidence on individual MIs, especially in the context of the EE1st principle. We substantiate the previously developed ENEFIRST scenarioswith bottom-up estimates of MIs. The key idea behind this so-called socio-environmental assessment is to move away from the previously used indicator of energy system cost that is limited to capital costs, fuel costs and other financial metrics. By investigating two selected types of MIs, we obtain a more comprehensive picture of the true societal value of end-use energy efficiency in the building sector. One type of MIs investigated are air pollution and climate change impacts. Even though the ENEFIRST scenarios are all set to reach the common objective of net-zero greenhouse gas emissions by the year 2050, we find significant differences in cumulative emissions and ensuing costs from both air pollutants and greenhouse gases. The inclusion of these cost estimates significantly enhances the cost-effectiveness of energy efficiency measures from a societal viewpoint. Another type of MIs in this assessment are indoor comfort improvements. A new method was developed to quantify comfort gains as a result of building retrofits for the entire building stocks of individual Member States. The results indicate significant comfort gains for countries with poor efficiency of the building stock in the base year. As a result of the modelled retrofit measures, the share of poorly heated floor space below 18°C can be reduced by more than 30 percentage points, with ensuing benefits for health, well-being and workforce productivity. In conclusion, any model-based assessment or scenarios in the scope of the EE1st principle should be substantiated with quantitative and qualitative estimates of different MIs to ensure a fair comparison of demand and supply side resources and thus to enable informed decisions on technology investment. |
