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The industrial sector is important to study in terms of improved energy efficiency, being one of the major energy-using sectors and responsible for a major share of CO2 emissions.The energy end-use (EEU) in the industrial sector is complex in general as processes are intertwined and interrelated. Moreover, bottom-up data of EEU on an aggregated level is scarce.Data for total energy supply like electricity, oil, coal, and natural gas exists but bottom-up data of what processes these energy carriers are used in, and moreover, where the major potential for implementation of energy efficiency measures (EEMs) exists, is less prevalent.This holds in particular for industrial small and medium-sized enterprises (SMEs). This makes policy formulation and design for industry a great challenge. Knowledge on where and how energy is used, as well as where opportunities for improvement exist, may provide good support for developing the most effective policies. Therefore, the aim of this study has been to present and compare available bottom-up energy data for industrial SMEs in four countries, namely Belgium, Italy, Japan and Sweden. Results show that the existence and quality of bottom-up EEU data differs largely between the countries and the development of a general taxonomy of structuring EEU data as well as EEMs is needed. Without the development of such a general taxonomy, the deployment level of EEMs and carbon dioxide emission reductions is unlikely to ever reach its full potential as knowledge is missing on how large the potential is, in which processes the major potential is found, how far industry has reached in terms of deployment levels, and in which areas future energy policies are needed. In conclusion, this paper of EEU and EEM in industrial SMEs addresses the high importance of future research in creating a harmonized data categorization, as this will greatly support the transition towards sustainable industrial energy systems.

Climate change, due to anthropogenic emissions of greenhouse gases, is driving policymakers to make decisions to promote more efficient energy use. Improved industrial energy efficiency is said to play a key role in the transition to more carbon-neutral energy systems. In most countries, industrial small and medium-sized enterprises (SMEs) represent 95% or more of the total number of companies. Thus, SMEs, apart from using energy, are a major driver in the economy with regard to innovation, GDP growth, employment, investments, exports, etc. Despite this, research and policy activities related to SMEs have been scarce, calling for contributions in the field. Therefore, the aim of this paper is to critically assess how adequate energy efficiency policy programmes for industrial SMEs could be designed. Results show that scientific publications in the field differ in scope and origin, but a major emphasis of the scientific papers has been on barriers to and drivers for energy efficiency. Scientific contributions from studies of energy policy programmes primarily cover energy audit programmes and show that the major energy efficiency measures from industrial SMEs are found in support processes. The review further reveals an imbalance in geographic scope of the papers within the field, where a vast majority of the papers emanate from Europe, calling for scientific publications from other parts of the world. The study synthesizes the findings into a general method on how to design efficiency programs for the sector.

To improve the accuracy, reliability, and representativeness of emission factors, 10 European laboratories worked together to study the influence of 20 parameters on the measurement of light-vehicle emission factors on chassis dynamometer of 4 main categories: driving patterns, vehicle-related parameters, vehicle sampling, and laboratory-related parameters. The results are based on (1) literature synthesis, (2) approximately 2700 specific tests with 183 vehicles, and (3) the reprocessing of more than 900 tests. These tests concern the regulated atmospheric pollutants and pre-Euro to Euro 4 vehicles. Of the 20 parameters analyzed, 7 seemed to have no effect, 7 were qualitatively influential, and 6 were highly influential (gearshift strategy, vehicle mileage, ambient temperature, humidity, dilution ratio, and driving cycle). The first four of the six were able to have correction factors developed for them. The results allow for the design of recommendations or guidelines for the emission factor measurement method.

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