IntroductionThe target set by the EU Renewable Energy Directive (2009/28/EC) [1] requires a 20% energy share from renewable sources by 2020. Thus, exploring alternative, environmentally benign and energy efficient systems has become the focus of governmental policies and industrial as well as academic research.Biogas is a renewable energy source that can be produced from the anaerobic digestion (AD) of biomass, such as sewage sludge, municipal solid waste, agricultural wastes, and energy crops. Biogas consists of around 50-60% methane (CH4), 40-50% carbon dioxide (CO2) and some minor constituents, such as hydrogen sulphide (H2S) and water. The use of biogas for energy production could displace fossil fuels, reduce greenhouse gas emissions and decrease dependence on imported energy [2].Upgraded biogas, termed bio-methane, is typically composed of ~97% CH 4 and ~3% CO 2 , and is converted to the same standard as natural gas through removal of CO 2 (upgrading) and other impurities (cleaning).Another route for upgrading biogas to bio-methane involves the chemical transformation of CO 2 to CH 4 by 2 the Sabatier reaction (equation 1); the hydrogen (H 2 ) in the reaction is usually obtained from water (H 2 O) electrolysis (equation 2). This combined pathway could have an important impact on the global carbon cycle [3]. There are various utilization pathways for both raw and upgraded forms of biogas [4]; commercial methods include electricity and heat generation via combined heat and power (CHP) units, electricity generation via fuel cells, and conversion to mechanical energy for transport via internal combustion engines (ICEs). Bio-methane can be injected into the gas grid, and/or converted to compressed renewable natural gas or liquefied renewable natural gas (referred to in this paper as CNG and LNG respectively) to serve as a transport fuel. Biogas can also be reformed to syngas (CO and H2) for liquid fuel production via Fischer Tropsch (FT) synthesis (see [5] for further details).As with any new energy system, countries are faced with ongoing challenges when designing the most optimum pathway to ensure sustainable development and sufficient energy supply [6]. In practice, many European countries have successfully integrated biogas into their energy sectors via different utilization routes. The annual energy production from biogas is around 42 TWh in Germany (the highest production in the EU), 9 TWh in UK, and 2.8 TWh in France; in each of these countries the biogas is mainly used for electricity generation [7]. Sweden produces around 1.7 TWh from biogas and 44% of biogas production is upgraded to bio-methane and used as vehicle fuel [8]. In Italy, biogas is mainly used for power generation while other pathways such as grid injection and CHP require further exploration [9]. However, although there are various options for biogas utilization, there is limited guidance in the literature on the selection of the optimum route. A number of papers focus specifically on biogas utilization as a vehicle fuel [9, 10] while oth...
Atmospheric pressure non-thermal plasma activated catalysis for the removal of NOx using hydrocarbon selective catalytic reduction has been studied utilising toluene and n-octane as the hydrocarbon reductant. When the plasma was combined with an Ag/Al2O3catalyst a strong enhancement in activity was observed when compared with conventional thermal activation with high conversions of both NOx and hydrocarbons obtained at temperature ≤250 C, where the silver catalyst is normally inactive. Importantly, in the absence of an external heat source, significant activity was obtained at 25 o C. This low temperature activity provides the basis for applying non thermal plasmas to activate emission control catalysts during cold start conditions which remains an important issue for mobile and stationary applications.
This paper presents the approach to functional test automation of services (black-box testing) and service architectures (grey-box testing) that has been developed within the MIDAS project and is accessible on the MIDAS SaaS. In particular, the algorithms and techniques adopted for addressing input and oracle generation, dynamic scheduling, and session planning issues supporting service functional test automation are illustrated. More specifically, the paper details: (i) the test input generation based on formal methods and temporal logic specifications, (ii) the test oracle generation based on service formal specifications, (iii) the dynamic scheduling of test cases based on probabilistic graphical reasoning, and (iv) the reactive, evidence-based planning of test sessions with on the fly generation of new test cases. Finally, the utilisation of the MIDAS prototype for the functional test of operational services and service architectures in the healthcare industry is reported and assessed. A planned evolution of the technology deals with the testing and troubleshooting of distributed systems that integrate connected objects (IoT).
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