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Mit der Nachhaltigkeitsanleihe NRW erschließt das Land das international wachsende Segment des nachhaltigen Investments für die Kreditfinanzierung des Landeshaushalts. Ziel der vorliegenden Studie ist es, die Bewertung positiver Nachhaltigkeitseffekte für die in 2016 emittierte Nachhaltigkeitsanleihe NRW zu erproben und Handlungsempfehlungen zur Bewertung zukünftiger Nachhaltigkeitsanleihen zu entwickeln. Für eine umfassende Nachhaltigkeitsanalyse ist aufgrund der Vielschichtigkeit der finanzierten Projekte und fehlender Standards zur Bewertung sozialer Kriterien eine umfangreiche Untersuchung erforderlich, wodurch sie für eine regelmäßige und standardisierte Wirkungsanalyse zukünftiger Anleihen nicht in Frage kommt. Stattdessen verfolgt die vorliegende Studie einen pragmatischen Ansatz zur Bewertung. Der Fokus liegt auf der Evaluation der potenziellen Treibhausgas-Minderung (THG-Minderung), da deren Bewertung sich derzeit als Standard für eine Wirkungsanalyse solcher Anleihen abzeichnet. Darüber hinaus werden die nächsten Schritte für eine Weiterentwicklung der Methodik und des Indikatorensets im Rahmen zukünftiger Wirkungsanalysen aufgezeigt.
Ziel der vorliegenden Studie ist es, positive Nachhaltigkeitseffekte für die in 2017 emittierte Nachhaltigskeitsanleihe NRW zu bewerten. Die Studie baut dabei auf der Wirkungsanalyse der zweiten Nachhaltigskeitsanleihe NRW auf. Diese Studie war auf die Abschätzung von Treibhausgas-Minderungspotenzialen (THG-Minderungen) fokussiert. Der Fokus der vorliegenden Studie liegt ebenfalls auf der Evaluation der potenziellen THG-Minderung, da deren Bewertung sich derzeit als Standard für eine Wirkungsanalyse solcher Anleihen abzeichnet.
The European Horizon 2020-project COMBI ("Calculating and Operationalising the Multiple Benefits of Energy Efficiency in Europe") aims at estimating the energy and non-energy impacts that a realisation of the EU energy efficiency potential would have in the year 2030. The project goal is to cover the most important technical potentials identified for the EU27 by 2030 and to come up with consistent estimates for the most relevant impacts: air pollution (and its effects on human health, eco-systems/crops, buildings), social welfare (including disposable income, comfort, health and productivity), biotic and abiotic resources, the energy system and energy security and the macro economy (employment, economic growth and the public budget). This paper describes the overall project research design, envisaged methodologies, the most critical methodological challenges with such an ex-ante evaluation and with aggregating the multiple impacts. The project collects data for a set of 30 energy efficiency improvement actions grouped by energy services covering all sectors and EU countries. Based on this, multiple impacts will be quantified with separate methodological approaches, following methods used in the respective literature and developing them where necessary. The paper outlines the approaches taken by COMBI: socio-economic modelling for air pollution and social welfare, resource modelling for biotic/abiotic and economically unused resources, General Equilibrium modelling for long-run macroeconomic effects and other models for short-run effects, and the LEAP model for energy system modelling. Finally, impacts will be aggregated, where possible in monetary terms. Specific challenges of this step include double-counting issues, metrics, within and cross-country/regional variability of effects and context-specificity.
Improvements in energy efficiency have numerous impacts additional to energy and greenhouse gas savings. This paper presents key findings and policy recommendations of the COMBI project ("Calculating and Operationalising the Multiple Benefits of Energy Efficiency in Europe").
This project aimed at quantifying the energy and non-energy impacts that a realisation of the EU energy efficiency potential would have in 2030. It covered the most relevant technical energy efficiency improvement actions in buildings, transport and industry.
Quantified impacts include reduced air pollution (and its effects on human health, eco-systems), improved social welfare (health, productivity), saved biotic and abiotic resources, effects on the energy system and energy security, and the economy (employment, GDP, public budgets and energy/EU-ETS prices). The paper shows that a more ambitious energy efficiency policy in Europe would lead to substantial impacts: overall, in 2030 alone, monetized multiple impacts (MI) would amount to 61 bn Euros per year in 2030, i.e. corresponding to approx. 50% of energy cost savings (131 bn Euros).
Consequently, the conservative CBA approach of COMBI yields that including MI quantifications to energy efficiency impact assessments would increase the benefit side by at least 50-70%. As this analysis excludes numerous impacts that could either not be quantified or monetized or where any double-counting potential exists, actual benefits may be much larger.
Based on these findings, the paper formulates several recommendations for EU policy making:
(1) the inclusion of MI into the assessment of policy instruments and scenarios,
(2) the need of reliable MI quantifications for policy design and target setting,
(3) the use of MI for encouraging inter-departmental and cross-sectoral cooperation in policy making to pursue common goals, and
(4) the importance of MI evaluations for their communication and promotion to decision-makers, stakeholders, investors and the general public.
The implementation of energy efficiency improvement actions not only yields energy and greenhouse gas emission savings, but also leads to other multiple impacts such as air pollution reductions and subsequent health and eco-system effects, resource impacts, economic effects on labour markets, aggregate demand and energy prices or on energy security. While many of these impacts have been studied in previous research, this work quantifies them in one consistent framework based on a common underlying bottom-up funded energy efficiency scenario across the EU. These scenario data are used to quantify multiple impacts by energy efficiency improvement action and for all EU28 member states using existing approaches and partially further developing methodologies. Where possible, impacts are integrated into cost-benefit analyses. We find that with a conservative estimate, multiple impacts sum up to a size of at least 50% of energy cost savings, with substantial impacts coming from e.g., air pollution, energy poverty reduction and economic impacts.
Footprint calculators are efficient tools to monitor the environmental impact of private consumption. We present the results of an analysis of data entered into an online Material Footprint calculator undertaken to identify the socioeconomic drivers of the Material Footprint in different areas of consumption, from housing to holidaymaking. We developed regression models to reveal (1) the impact of socioeconomic characteristics on Material Footprints of private households and (2) correlations between the components of Material Footprints for different arrays of consumption. Our results show that an increasing Material Footprint in one array of consumption comes with an increasing Material Footprint in all other arrays, with the exception of housing and holidaymaking. The socioeconomic characteristics of users have a significant impact on their Material Footprints. However, this impact varies by the array of consumption. Households only exhibit generally bigger Material Footprints as a result of higher incomes and larger dwellings. We conclude that indicators which strive to monitor resource efficiency should survey disaggregated data in order to classify the resource use to different population groups and arrays of consumption.
Green Information Systems in general, and footprint calculators in particular, are promising feedback tools to assist people in adopting sustainable behaviour. Therefore, a Material Footprint model for use in an online footprint calculator was developed by identifying the most important predictors of the Material Footprint of the calculator's users. By means of statistical learning, the analysis revealed that 22 of the 95 predictors identified accounted for 74% of the variance in Material Footprints. Ten predictors out of the 95, mainly from the mobility domain, were capable of showing a prediction accuracy of 61%. The authors conclude that 22 predictors from the areas of mobility, housing and nutrition, as well as sociodemographic information, accurately predict a person's Material Footprint. The short and concise Material Footprint model may help developers and researchers to enhance their information systems with additional items while ensuring the data quality of such applications.
Resource use of wind farms in the German North Sea : the example of Alpha Ventus and Bard Offshore I
(2013)
The German government aims to obtain at least 40 percent of its electricity from renewable sources by 2030. One of the central steps to reach this target is the construction of deep sea offshore wind farms. The paper presents a material intensity analysis of the offshore wind farms "Alpha Ventus" and "Bard Offshore I" under consideration of the grid connection. An additional onshore scenario is considered for comparison. The results show that offshore wind farms have higher resource consumption than onshore farms. In general, and in respect to the resource use of other energy systems, both can be tagged as resource efficient.
The concept Material Input per Service Unit (MIPS) was developed 20 years ago as a measure for the overall natural resource use of products and services. The material intensity analysis is used to calculate the material footprint of any economic activities in production and consumption. Environmental assessment has developed extensive databases for life cycle inventories, which can additionally be adopted for material intensity analysis. Based on practical experience in measuring material footprints on the micro level, this paper presents the current state of research and methodology development: it shows the international discussions on the importance of accounting methodologies to measure progress in resource efficiency. The MIPS approach is presented and its micro level application for assessing value chains, supporting business management, and operationalizing sustainability strategies is discussed. Linkages to output-oriented Life Cycle Assessment as well as to Material Flow Analysis (MFA) at the macro level are pointed out. Finally we come to the conclusion that the MIPS approach provides relevant knowledge on resource and energy input at the micro level for fact-based decision-making in science, policy, business, and consumption.