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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.

The most widely used process for hydrogen production is steam methane reforming. It can be carried out using a membrane reactor in which simultaneous hydrogen production and purification occur. Mathematical modeling of these reactors plays a key role in the selection of the design and operating parameters that yield high performance for the reactor. This review study discusses, synthesizes, and compares different mathematical modeling studies on the packed bed membrane reactors for hydrogen production from methane found in the literature. Different approaches used in these modeling studies for the hydrogen permeation steps, reaction kinetic expressions, phases involved (pseudo-homogeneous and heterogeneous), and spatial dimensions (one, two, and three dimensional) are given.

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.

Intention of this work is to investigate the opportunity and feasibility of energy efficient networking in Home and Building automation protocols. Wired HBAS have traditionally devoted a relatively little attention to this point, especially if compared to wireless networks. This paper will try to address the issue by evaluating the introduction of power state switching in a real scenario and proposing the concept of functional and spatial adjacency among packets.

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.

Activity pacing (AP) is a concept that is central to many chronic pain theories and treatments, yet there remains confusion regarding its definition and effects.To review the current knowledge concerning AP and integrate this knowledge in a manner that allows for a clear definition and useful directions for future research.A narrative review of the major theoretical approaches to AP and of the empirical evidence regarding the effects of AP interventions, followed by an integrative discussion.The concept of AP is derived from 2 main traditions: operant and energy conservation. Although there are common elements across these traditions, significant conceptual and practical differences exist, which has led to confusion. Little empirical evidence exists concerning the efficacy of AP as a treatment for chronic pain.Future research on AP should be based on a clear theoretical foundation, consider the context in which the AP behavior occurs and the type of pacing problem ("underactivity" vs. "overactivity"), and should examine the impact of AP treatment on multiple clinical outcomes. We provide a provisional definition of AP and specific recommendations that we believe will move the field forward.