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Policy and industry decision makers place high priority on the contribution of biomass to the emerging low carbon, circular economy. Optimisation of performance, from the perspectives of environmental, social and economic sustainability and resource efficiency, is essential to successful development and operation of biomass value chains. The complexity of value chains, which comprise interrelated stages from land use to conversion and multiple end products, presents challenges.To date, decision makers have approached from the viewpoints of single market sectors or issues, such as market shares of bioeconomy and reduction of carbon emissions to mitigate climate change. This approach does not achieve a full understanding of value chains and their competitive priorities, limits consumer awareness, and poses risks of sub-optimal performance and under-development of potential local capacity.This paper presents a conceptual framework that combines value chain analysis and competitive priority theory with indicators suitable to measure, monitor and interpret sustainability and resource efficiency at value chain level. The case of biomass Combined Heat and Power (CHP) is used to illustrate how optimisation strategies can be focused to address challenges in value chain stages which will lead to better performance and uptake of sustainably sourced, widely accepted biomass options. Highlights •Biomass is a key component in policy for low carbon and circular economy.•Decision makers are increasingly exploring varied, innovative value chains with high complexity.•They face challenges with sustainability, fragmented metrics, and decisions often lack coherent systems thinking.•This prevents developing optimisation strategies to overcome challenges and create value at local level.•This paper combines value chain and competitive priority theory to assess performance and enable efficient decision making.

European policy states that by 2020 at least 20% of final energy consumption should come from renewable energy sources. Biomass as a renewable energy source cannot be disregarded in order to attain this target. In this study a macro screening approach is developed to determine potential locations for biomass valorization in a specified region. The approach consists of five steps: (1) criteria determination, (2) data gathering, (3) weight assignment, (4) final score, (5) spatial representation. The resulting outcome provides a first well balanced scan of the possibilities for energy production using regional biomass. This way policy makers and investors can be supported and motivated to study the possibilities of building energy production plants at specific locations in more detail, which can be described as a ‘micro-screening’. In our case study the approach is applied to determine the potentially interesting locations to establish a biomass project. The region has been limited to the forty-four communities in the province of Limburg (Belgium). The macro screening approach has shown to be very effective since the amount of interesting locations has been reduced drastically.

In this paper, the technical and economic advantages of combining conversion technologies into a multi-dimensional plant primarily using regional biomass residues are investigated. The main objective is to show how locally available biomass can be used more effi ciently as a source for renew- able energy and bio-based products. Therefore, not only is the theoretical perspective considered, but also a reality check for the local situation is taken into account. Although industrial attitude toward biorefi neries is positive, the effi cient production of a portfolio of bio-based products has not yet been implemented. A biorefi nery concept for Moerdijk (the Netherlands) was developed, focusing on grass refi ning, production of pyrolysis oil, biodiesel production, and bio-LNG production. Grass refi ning is the most experimental technique of all proposed conversion techniques. In terms of development, pyroly- sis oil and bio-LNG production are in the demonstration phase. Anaerobic digestion and biodiesel production are proven techniques. It is shown that this concept allows for synergies with regard to the utilization of residue fl ows from internal processes. Furthermore, it is demonstrated that by integrat- ing different conversion technologies, an economically feasible concept can be developed in which technologies, currently residing in a demonstration phase, can also be brought to the market. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

Biomass as a renewable energy source has many advantages and is therefore recognized as one of the main renewable energy sources to be deployed in order to attain the target of 20% renewable energy use of final energy consumption by 2020 in Europe. In this paper the concept of a biomass Energy Conversion Park (ECP) is introduced. A biomass ECP can be defined as a synergetic, multi-dimensional biomass conversion site with a highly integrated set of conversion technologies in which a multitude of regionally available biomass (residue) sources are converted into energy and materials. A techno-economic assessment is performed on a case study in the Netherlands to illustrate the concept and to comparatively assess the highly integrated system with two mono-dimensional models. The three evaluated models consist of (1) digestion of the organic fraction of municipal solid waste, (2) co-digestion of manure and co-substrates, and (3) integration. From a socio-economic point of view it can be concluded that it is economically and energetically more interesting to invest in the integrated model than in two separate models. The integration is economically feasible and environmental benefits can be realized. For example, the integrated model allows the implementation of a co-digester. Unmanaged manure would otherwise represent a constant pollution risk. However, from an investor's standpoint one should firstly invest in the municipal solid waste digester since the net present value (NPV) of this mono-dimensional model is higher than that of the multi-dimensional model. A sensitivity analysis is performed to identify the most influencing parameters. Our results are of interest for companies involved in the conversion of biomass. The conclusions are useful for policy makers when deciding on policy instruments concerning manure processing or biogas production. (C) 2012 Elsevier Ltd. All rights reserved.

During the execution of the project Floating Automotive Data Collection (FADC), various traffic conditions were recorded using in-vehicle measurements. A series of reference measurements were performed on a fixed route in Belgium in real traffic circumstances, including motorway, rural and city traffic. Three vehicles were used for the reference measurements: a passenger car, a delivery van, and a delivery truck. An on-board device recorded vehicle speed and GPS position on second-basis. The resulting speed profiles were used as input in the vehicle emission simulation programme VeTESS to estimate fuel consumption and emissions of certain vehicles driving according to these speed profiles. The goal of these calculations was to quantify the effect of preventing traffic jams. From the simulations it was concluded that a reduction in average speed does not necessarily lead to higher fuel consumption. Actually when average speed is reduced from speeds above 100 km/h down to 80 or 60 km/h, fuel consumption can even be expected to decrease. Of course traffic jams are more about low average speeds. The simulations showed that when average speed drops below 30 or 40 km/h, fuel consumption increases significantly. Emissions of NOx, CO and HC also increase in this case. So concerning fuel consumption and emissions it is indeed worth the effort to prevent traffic jams and slow traffic and to improve the traffic flow. The role of traffic jam detection is very important to take measures to improve the traffic flow and this way save fuel and reduce emissions.

During the execution of the project Floating Automotive Data Collection (FADC), various traffic conditions were recorded using in-vehicle measurements. A series of reference measurements were performed on a fixed route in Belgium in real traffic circumstances, including motorway, rural and city traffic. Three vehicles were used for the reference measurements: a passenger car, a delivery van, and a delivery truck. An on-board device recorded vehicle speed and GPS position on second-basis. The resuiting speed profiles were used as input in the vehicle emission simulation program VeTESS to estimate fuel consumption and emissions of certain vehicles driving according to these speed profiles. Goal of these calculations was to quantify the effect of preventing traffic jams. From the simulations it was concluded that a reduction in average speed, does not necessarily lead to higher fuel consumption. Actually when average speed is reduced from speeds above 100km/h down to 80 or 60km/h, fuel consumption can even be expected to decrease. Of course traffic jams are more about low average speeds. The simulations showed that when average speed drops below 30 or 40km/h, fuel consumption increases significantly. Emissions of NOx, CO and HC also increase in this case. So concerning fuel consumption and emissions it is I indeed worth the effort to prevent traffic jams and slow traffic and to improve the traffic flow. The role of traffic jam detection is very important to take measures to improve the traffic flow and this way save fuel and reduce emissions.

In the EU 5th framework project DECADE (2001–2003), a new methodology has been developed to calculate in detail the engine power required to drive a given vehicle over any particular route. It includes the rapidly changing (transient) demands placed on the engine, an area that has proved an obstacle to accurate simulations in the past. Together with the associated speed profiles, the actual power demands allow a detailed calculation of emissions and ambient air concentrations in street canyons. This makes the methodology a valuable tool for detailed assessments of the ambient air quality impact of e.g., street design (traffic lights, road bumps, busy crossings), driving patterns, driving behaviour and fleet composition.