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This article describes the development and application of a generic approach to the comparative assessment of risks related to the production of organic chemicals by petrochemical processes versus white biotechnology. White biotechnology, also referred to as industrial biotechnology, typically uses bio‐based feedstocks instead of the fossil raw materials used in the petrochemical sector. The purpose of this study was to investigate whether the production of chemicals by means of white biotechnology has lower conventional risks than their production by petrochemical processes. Conventional risks are the risks of well‐established processes, and not those related to genetically modified microorganisms and plants. Our approach combines classical risk assessment methods (largely based on toxicology), as developed by the life cycle assessment (LCA) community, with statistics on technological disasters, accidents, and work‐related illnesses. Moreover, it covers the total process chain for both petrochemical and bio‐based products from cradle to grave. The approach was applied to five products: the plastics polytrimethylene terephthalate (PTT), polyhydroxyalkanoates (PHA), polyethylene terephthalate (PET), polyethylene (PE), and ethanol. Our results show that the conventional risks related to the white biotechnology products studied are lower than those of the petrochemical products. However, considering the uncertainties with respect to the ranges of input data, the (incomplete) coverage of emissions by the environmental priority strategies (EPS) 2000 method, and the uncertainties of the assumptions made in this study (i.e., large to very large), the differences in results between bio‐based and petrochemical products fall into the uncertainty range. Because of this, future research is necessary to decrease the uncertainties before we can conclude that the conventional risks of biotechnologically produced chemicals are lower than those of fossil‐fuel‐derived chemicals.

This paper aims to unravel the effects of both policies and autonomous developments driving the changes of final energy consumption for the European Union (EU28) and its member states complemented with an in-depth analysis of two EU member states, Germany and Poland, for the period of 2000 to 2015 by the logarithmic mean Divisia index methodology (LMDI). We examine the influences on the changes in final energy consumption for each of the five main demand sectors at aggregated level and at a more detailed level of residential end-uses, transport modes and industrial sub-sectors. With the second level, we provide insights into the effects of policies from a European and national perspective. Our analysis shows that final energy consumption in the EU28 is primarily influenced by an increase in energy efficiency in industry followed by households. For the latter, the energy savings were mainly realised in space heating. The main counteracting drivers were increasing economic activity and the rising demand for higher comfort and social factors, such as a declining household size. Germany shows relatively low energy efficiency improvements in industry, but strong energy efficiency gains in households followed by transport. Poland's transport, however, is responsible for a strong increase in final energy consumption mainly through increased activity, while here the sector industry—despite strong effects of increased activity—in total shows a significant reduction in energy consumption through energy efficiency improvements.

AbstractIncentives, both rewards and punishments, are effective instruments that have been embedded in electricity product designs to reduce electricity consumption. Reducing electricity consumption can considerably contribute to climate change mitigation. To better understand consumer preferences for incentive‐based electricity products, a choice experiment using choice‐based conjoint analysis was conducted among a representative sample of Swiss electricity consumers. Based on stated preferences for different product attributes, four consumer segments were identified. While two segments (49.6%) stated preference for incentive‐based products, two other segments were less accepting of incentive components (particularly of penalties). We further explain the segments' preferences using psychographic characteristics, combining measures from psychology and behavioral economics. Precisely, environmental values and emotions, energy saving intentions and motives, perceived product attractiveness, as well as loss and risk aversion, and comparative optimism bias best described the segments. We align our findings with previous segmentation studies and argue for a stronger integration of behavioral economics in the environmental discourse. We further discuss the usefulness of consumer segmentation to develop tailored strategies that effectively target consumers' preferences and needs.

In this paper, we develop a quantitative indicator approach including 20 indicators to measure the multiple benefits of energy efficiency (MB-EE). The MB-EEs are classified into three groups: environmental (e.g. energy savings, emissions), economic (e.g. GDP, employment), and social (health, energy poverty) aspects. We explain the methodological approach, the underlying data sources and limitations. The indicator set has been applied to 29 countries (EU28 plus Norway) for the period 2000 to 2015, proving that it allows to conduct in-depth comparisons of developments and differences across Europe. The indicator set also supports the design of well-suited energy policies by allowing to take into account, on an informed basis, more of the multiple impacts of energy efficiency. For example, our analysis of the effect of energy savings for the period 2000 to 2015 in Germany shows GHG savings of about 158 MtCO2eq., about 30,000 avoided deaths due to less air pollution, a reduction of Germany's import dependency by 5.8 percentage points and a growth of GDP by around 0.3% per year for the period 2010 to 2015) as a consequence of improved energy efficiency. To conclude, the presented approach allows to comprehensively and regularly assess policies in terms of their MB-EEs.

Energy efficiency programmes (EEPs) are schemes operated by utilities or other bodies in order to incentivize energy efficiency improvement, in particular by adoption of energy-efficient products and typically by means of an economic reward. Ample experience has been gained, especially in the U.S., where EEPs have been in use for decades, with the rationale of avoiding additional energy supply by improving energy efficiency. More recently, EEPs have been implemented in Europe and in Switzerland. This review paper presents insights from the U.S., the EU and especially from Switzerland, with a focus on levelised programme cost of saved energy (LPC) as a key performance indicator. These LPC values, which take the perspective of the programme operator, are typically low to very low compared to the cost of electricity supply, thereby representing an important argument in favour of their use. The country examples show that EEPs are being effectively and successfully put into practice, for example, in Switzerland both as (i) a national tender-based scheme (called ProKilowatt) and in the form of a (ii) utility-operated obligation-based scheme (in Geneva). EEPs not only call for diligent implementation but also for suitable legal settings, e.g., in the form of mandatory energy efficiency savings targets (as realised for energy efficiency obligations, EEOs) in combination with programme cost recovery. The main criticism of EEPs is the free-rider effect, which needs to be minimised. On the other hand, EEPs are accompanied by significant co-benefits (environmental, health-related and social) and spillover effects. In their currently prevalent form, EEPs allow one to effectively save energy at a (very) low cost ("low-hanging fruit"). They can hence play an important role in fostering the energy transition; however, they should be implemented as part of a policy portfolio, in combination with other policy instruments.