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Diesel engine exhausts from a common rail 3.0 L F1C diesel engine were analyzed at two different load conditions of the WLTC testing cycle downstream of both the diesel particulate filter (DPF) and selective catalytic reactor (SCR) to verify their effect on the characteristics of carbon particulate matter. An array of chemical, physical and spectroscopic techniques (gas chromatography coupled with mass spectrometry (GC-MS), mobility analyzer, UV-Visible absorption and fluorescence spectroscopy) was applied for characterizing polycyclic aromatic hydrocarbons (PAH), heavy aromatic compounds and soot, constituting the particulate matter (PM) sampled from the exhaust. The engine was operated in half load (HL) (188 Nm, representing the more common condition for engine in urban traffic) and full load (FL) (452 Nm, representing the best performance of the engine operation) conditions, at the same engine speed (2000 rpm). Soot formation was enhanced in HL condition, with respect to FL, but, just because of the much lower soot amount, the after-treatment systems in this last condition resulted to be less efficient in the soot abatement. Indeed, the abatement through DPF was about 40% lower in the FL condition with respect to HL condition, and any significant further concentration decrease was found after SCR, in both conditions. By contrast, PAH concentration after DPF abatement was found to be higher in the HL with respect to FL condition. A further PAH concentration decrease of about 30% was found after the SCR in the HL condition whereas in FL the reduction was only about 5-6%. Also the heavy aromatic compounds having molecular weight above the GC-MS detection limit (300 u), were mitigated by SCR. Therefore, SCR did not cause a further soot reduction, whereas it was effective in largely reducing PAH and heavy aromatics emissions, especially in the lower temperature condition featuring the half-load condition, when combustion efficiency is worse. Moreover, SCR system reduced the emission of small particles probably due to an enhanced agglomeration of particles, with beneficial effect on the harmfulness to human health.

This paper aims at reviewing the life cycle assessment (LCA) literature on second generation bioethanol based on lignocellulosic biomass and at identifying issues to be resolved for good LCA practice. Reviews are carried out on respective LCA studies published over the last six years. We use the classification of lignocellulosic biomass to define system boundaries, so that the comparison among LCA results can be thoroughly assessed based on identified system components. A basis for attributing environmental burden for different biomass feedstocks is also suggested. Despite the non-homogeneous systems, we conclude that second generation bioethanol performs better than fossil fuel at least for the two most studied impact categories, net energy output and global warming. For the latter category, carbon sequestration at the biomass generation stage can even consistently offset the GHG emissions from all parts of the life cycle chains at high ethanol percentage (≥85%). The aspect of biogenic carbon and agrochemical input for energy crops and biomass residues, and the effect of removal of the latter from soil have not been treated consistently. In contrast, the exclusion of upstream chain of biomass waste feedstocks is observed in practice. The bioethanol conversion process is mostly based on simultaneous saccharification and co-fermentation, characterized by high yield and low energy input. In this regard, the LCA results tend to under estimate the real impacts of the current technology. The choice of allocation methods strongly influences the final results, particularly when economic value is used as a reference. Substitution of avoided burden seems to be the most popular allocation method in practice, followed by partition based on mass, energy, and economic values.

Green tea catechins mixed with caffeine have been proposed as adjuvants for maintaining or enhancing energy expenditure and for increasing fat oxidation, in the context of prevention and treatment of obesity. These catechins-caffeine mixtures seem to counteract the decrease in metabolic rate that occurs during weight loss. Their effects are of particular importance during weight maintenance after weight loss. Other metabolic targets may be fat absorption and the gut microbiota composition, but these effects still need further investigation in combination with weight loss. Limitations for the effects of green tea catechins are moderating factors such as genetic predisposition related to COMT-activity, habitual caffeine intake, and ingestion combined with dietary protein. In conclusion, a mixture of green tea catechins and caffeine has a beneficial effect on body-weight management, especially by sustained energy expenditure, fat oxidation, and preservation of fat free body-mass, after energy restriction induced body-weight loss, when taking the limitations into account.

While the harmful effects of alcohol abuse are well documented, experimental and clinical data support a potential benefit of light to moderate alcohol consumption. Cross-sectional studies have suggested an association between alcohol consumption and multiple sclerosis (MS) disability. In the absence of prospective, longitudinal studies, the causal nature of this relationship cannot be established. It remains possible that patients with increased disability progression reduce their alcohol intake. Even though there is substantial evidence for anti-inflammatory effects of low-to-moderate doses of alcohol, the associations need to be interpreted very cautiously. This study discusses the current state of knowledge about MS and alcohol consumption, and the limitations in conducting research with retrospective data in patients with MS.

Due to the increasing awareness of climate change, depletion of natural resources, and increasing world population, companies in the agri-food sector need to redesign their existing supply chains and take into account both the economic and environmental impact of their operations. In practice not all the required information is available in advance due to various sources of uncertainty in agri-food supply chains. In this research a multi-objective two-stage stochastic programming model is proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in agri-food supply chains. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. The results of the optimizations show that accounting for stochasticity in important model parameters can reduce the difference between expected and realized economic performance by approximately 4% on average. Moreover, this paper demonstrates that including stochastic model parameters can reduce the environmental impact without compromising the current economic performance. Given the assumptions in the setup of the case study and the available information, it is concluded that applying a 2-stage stochastic programming approach for production planning decisions can lead to improved economic and environmental performance in an agri-food supply chain. New findings in real-life case studies are needed to get profound insights and understanding on the impact of uncertainty on production planning decisions in sustainable agri-food supply chains.

Sustainability is commonly assessed along environmental, societal, economic and technological dimensions. A crucial aspect of sustainability is that inter-generational equality must be ensured. This requires that sustainability is attained in the here and now as well as into the future. Therefore, what is perceived as 'sustainable' changes as a function of societal opinion and technological and scientific progress. A concept that describes the ability of systems to change is adaptive capacity. Literature suggests that the ability of systems to adapt is an integral part of sustainable development. This paper demonstrates that indicators measuring adaptive capacity are underrepresented in current urban water sustainability studies. Furthermore, it is discussed under which sustainability dimensions adaptive capacity indicators are lacking and why. Of the >90 indicators analysed, only nine are adaptive capacity indicators, of which six are socio-cultural, two technological, one economical and none environmental. This infrequent use of adaptive capacity indicators in sustainability assessments led to the conclusion that the challenge of dynamic and uncertain urban water systems is, with the exception of the socio-cultural dimension, not yet sufficiently reflected in the application of urban water sustainability indicators. This raises concerns about the progress towards urban water systems that can transform as a response variation and change. Therefore, research should focus on developing methods and indicators that can define, evaluate and quantify adaptive capacity under the economic, environmental and technical dimension of sustainability. Furthermore, it should be evaluated whether sustainability frameworks that focus on the control processes of urban water systems are more suitable for measuring adaptive capacity, than the assessments along environmental, economic, socio-cultural and technological dimensions.

European consumers are willing to pay more for “green” electricity, as they highly value renewable energy sources for the contribution to combating climate change. There is a push for getting higher levels of sustainability, leading to a differentiation of Europe‘s electricity market. In this differentiation, the large potential of wind energy is recognized. More specifically, North Sea countries prefer to plan wind arrays (far) out at sea. This article offers a review of the main arguments for offshore wind energy, described in comparison with its onshore counterpart. It is stated that offshore wind farms (OWFs) generate “dark green” electricity as they mitigate greenhouse gas emissions and contribute to the protection of (some) marine life. Applying an informational governance framework, this article further assesses whether this dark green message has been exploited through further differentiation of the electricity market, and provides an analysis of why this is not (yet) the case. It is concluded that the dominant discourse in onshore wind power development hinders a favorable ecological differentiation toward offshore wind power.

Biomass is considered one of the most important options in the transition to a sustainable energy system with reduced greenhouse gas (GHG) emissions and increased security of enegry supply. In order to facilitate this transition with targeted policies and implementation strategies, it is of vital importance to understand the economic benefits, uncertainties and risks of this transition. This article presents a quantification of the economic impacts on value added, employment shares and the trade balance as well as required biomass and avoided primary energy and greenhouse gases related to large scale biomass deployment on a country level (the Netherlands) for different future scenarios to 2030. This is done by using the macro-economic computable general equilibrium (CGE) model LEITAP, capable of quantifying direct and indirect effects of a bio-based economy combined with a spread sheet tool to address underlying technological details. Although the combined approach has limitations, the results of the projections show that substitution of fossil energy carriers by biomass, could have positive economic effects, as well as reducing GHG emissions and fossil energy requirement. Key factors to achieve these targets are enhanced technological development and the import of sustainable biomass resources to the Netherlands. (C) 2013 Elsevier Ltd. All rights reserved.