Food miles or carbon emissions? Exploring labeling preference for food transport footprint with a stated choice study

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO2 and food miles valuations are much correlated. CO2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO2 label at least as much and sometimes more than the food miles label.

Prediction of failure and fracture mechanisms of polymeric composites using finite element analysis. Part 1:Particulate filled composites

Micro-mechanical analysis of polymeric composites provides a powerful means for the quantitative assessment of their bulk behavior. In this paper we describe a robust finite element model (FEM) for the micro-structural modeling of the behavior of particulate filled polymer composites under external loads. The developed model is applied to simulate stress distribution in polymer composites containing particulate fillers. Quantitative information about the magnitude and location of maximum stress concentrations obtained from these simulations is used to predict the dominant failure and crack growth mechanisms in these composites. The model predictions are compared with the available experimental data and also with the values found using other methods reported in the literature. These comparisons show the range of the validity of the developed model and its predictive potential.

Water efficiency as a means of reducing carbon emissions in Northern Ireland (NI) Water

The water and sewerage sectors' combined emissions account for just over 1% of total UK emissions, while household water heating accounts for a further 5%. Energy use, particularly electricity, is the largest source of emissions in the sector. Water efficiency measures should therefore result in reduced emissions from a lower demand for water and wastewater treatment and pumping, as well as from decreased domestic water heating. Northern Ireland Water (NI Water) is actively pursuing measures to reduce its carbon footprint. This paper investigated the carbon impacts of implementing a household water efficiency programme in Northern Ireland. Assuming water savings of 59.6 L/prop/day and 15% uptake among households, carbon savings of 0.6% of NI Water's current net operational emissions are achievable from reduced treatment and pumping. Adding the carbon savings from reduced household water heating gives savings equivalent to 6.2% of current net operational emissions. Cost savings to NI Water are estimated as 300,000 per year. The cost of the water efficiency devices is approximately 1.6 million, but may be higher depending on the number of devices distributed relative to the number installed. This paper has shown clear carbon benefits to water efficiency, but further research is needed to examine social and cost impacts. © IWA Publishing 2013.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Electric vehicles and opportunities to displace tailgate emissions using Smart Charging controls

Under the European Union Renewable Energy Directive each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. This paper investigates the impact of the 10% electric vehicle target in Ireland in 2020 using a dynamic programming based long term generation expansion planning model. The model developed optimizes power dispatch using hourly electricity demand curves up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. Two distinct scenarios are analysed based on a peak and off-peak charging regimes in order to simulate the effects of the electric vehicles charging in 2020. The importance and influence of the charging regimes on the amount of energy used and tailgate emissions displaced is then determined.

Modelling Cohesive-Frictional Particulate Solids for Bulk Handling Applications

Many powders and particulate solids are cohesive in nature and the strength often exhibits dependence on the consolidation stress. As a result, the stress history in the material leading up to a handling scenario needs to be considered when evaluating its handleability. This paper outlines the development of a DEM contact model accounting for plasticity and adhesion force, which is shown to be suitable for modelling the stress history dependent cohesive strength. The model was used to simulate the confined consolidation and the subsequent unconfined loading of iron ore fines with particle sizes up to 1.18mm. The predicted flow function was found to be comparable to the experimental results. 

Understanding aerospace composite components' supply chain carbon emissions

This paper examines a large structural component and its supply chain. The component is representative of that used in the production of civil transport aircraft and is manufactured from carbon fibre epoxy resin prepreg, using traditional hand layup and autoclave cure. Life cycle assessment (LCA) is used to predict the component’s production carbon emissions. The results determine the distribution of carbon emissions within the supply chain, identifying the dominant production processes as carbon fibre manufacture and composite part manufacture. The elevated temperature processes of material and part creation, and the associated electricity usage, have a significant impact on the overall production emissions footprint. The paper also demonstrates the calculation of emissions footprint sensitivity to the geographic location and associated energy sources of the supply chain. The results verify that the proposed methodology is capable of quantitatively linking component and supply chain specifics to manufacturing processes and thus identifying the design drivers for carbon emissions in the manufacturing life of the component.