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Abstract Anaerobic digestion of animal by-products was investigated in batch and semi-continuously fed, reactor experiments at 55 °C and for some experiments also at 37 °C. Separate or mixed by-products from pigs were tested. The methane potential measured by batch assays for meat- and bone flour, fat, blood, hair, meat, ribs, raw waste were: 225, 497, 487, 561, 582, 575, 359, 619 dm 3 kg −1 respectively, corresponding to 50–100% of the calculated theoretical methane potential. Dilution of the by-products had a positive effect on the specific methane yield with the highest dilutions giving the best results. High concentrations of long-chain fatty acids and ammonia in the by-products were found to inhibit the biogas process at concentrations higher than 5 g lipids dm −3 and 7 g N dm −3 respectively. Pretreatment (pasteurization: 70 °C, sterilization: 133 °C, and alkali hydrolysis (NaOH) had no effect on achieved methane yields. Mesophilic digestion was more stable than thermophilic digestion, and higher methane yield was noticed at high waste concentrations. The lower yield at thermophilic temperature and high waste concentration was due to ammonia inhibition. Co-digestion of 5% pork by-products mixed with pig manure at 37 °C showed 40% higher methane production compared to digestion of manure alone.

Ethylene oxide production process is one of the highest energy consumers in chemical industry, and therefore even a slight improvement in its overall efficiency can have a significant impact on the sustainability of the process. Efficiency improvement can be carried out using the exergy-aided pinch analysis outlined in this paper. The overall exergy loss distribution in different unit operations of an ethylene oxide process was first evaluated and mapped out in the form of “visualized exergetic process flowsheet”. An initial analysis of the four main functional blocks of the process showed that the exothermic reaction block contained the largest exergy loss (6043 and 428 kJ/kg of internal and external losses, respectively) which can be reduced by isothermal mixing, as well as increasing reaction temperature and reduction in pressure drop. The absorption block was also estimated to have the second highest contribution with total exergy losses of 3640 kJ/kg which were mainly due to the cooling column. These losses were then recommended to be reduced by improvements in the concentration and temperature gradients along the tower. Following the block-wise analysis, exergy analysis was then carried out for individual unit operations in each block to pinpoint the main sources of thermal exergetic inefficiency. Thermal solutions to reduce losses were also proposed in accordance with the identified sources of inefficiency, leading to a comprehensive list of cold and hot process streams that could be introduced to reduce losses. Finally, pinch analysis was brought into action to estimate the minimum energy requirements, to select utilities, and to design heat exchanger network. Thus, the methodology used in this work took advantage of both exergy and pinch analyses. The combined thermal-exergy-based pinch approach helped to set energy targets so that all the thermal possible solutions supported by exergy analysis were considered, preventing exclusion of any hot or cold process stream with high potential for heat integration during pinch analysis. Results indicated that the minimum cold utility requirement could be reduced from 601.64 MW (obtained via conventional pinch analysis) to 577.82 MW through screening of streams by the combined methodology.

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.

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.

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.

Abstract This work assesses the impacts of aggressive driving behavior on pollutants emissions and energy consumption at a city level. Furthermore, it performs an economic analysis considering the potential avoided emissions and fuel savings and discusses potential policy measures to address this topic. The results showed that aggressive driving significantly impacts energy consumption and emissions, with energy consumption increasing by more than ∼200% and emissions by 330% for aggressive driving compared to non-aggressive driving (in MJ/km and in g/km, respectively). This increment was found to be even higher for diesel vehicles than for gasoline vehicles. On the contrary, gasoline vehicles showed higher percentages of increase for most emissions (CO, NOx and NO). Results also revealed that aggressive driving impacts are higher for local streets when examining the city level. Moreover, the economic analysis showed that significant cost reductions may be achieved by avoiding aggressive driving, reaching up to 52.5 k€ on a daily basis. In conclusion, this study is of particular relevance to policy makers and urban planners, enabling to obtain a comprehensive overview of the impacts of aggressive driving behaviors at a city level and providing new insights to perform further developments and to assess the feasibility of the implementation of policy measures.

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.

Wood biomass is turned into industrial fuel through chipping. The efficiency of chipping depends on many factors, including chipper knife wear. Chipper knife wear was determined through a long-term follow-up study, conducted at a waste wood recycling yard. Knife wear determined a sharp drop of productivity (>20%) and a severe decay in product quality. Dry sharpening with a grinder mitigated this effect, but it could not replace proper wet sharpening. Increasing the frequency of wet sharpening sessions determined a moderate increase of knife depreciation cost, but it could drastically enhance machine performance and reduce biomass processing cost. Since benefits largely exceed costs, increasing the frequency of wet sharpening sessions may be an effective measure for reducing overall chipping cost. If the main goal of a chipper operator is to increase productivity and/or decrease fuel consumption, then managing knife wear should be a primary target. (C) 2014 Elsevier Ltd. All rights reserved.