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Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.

ABSTRACTThe California generation fleet manages the existing variability and uncertainty in the demand for electric power (load). When wind power is added, the dispatchable generators manage the variability and uncertainty of the net load (load minus wind power). The variability and uncertainty of the load and the net load are compared when 8790 MW of wind power are added to the California power system, a level expected when California achieves its 33% renewable portfolio standard, using a data set of 26,296 h of synchronous historic load and modeled historic wind power output. Variability was calculated as the rate of change in power generated by wind farms or consumed by the load from 1 h to the next (MW/h). Uncertainty was calculated as the 1 h ahead forecast error [MW] of the wind power or of the load. The data show that wind power adds no additional variability than is already present in the load variability. However, wind power adds additional uncertainty through increased forecast errors in the net load compared with the load. Forecast errors in the net load increase 18.7% for negative forecast errors (actual less than forecast) and 5.4% for positive forecast errors (actual greater than forecast). The increase in negative forecast errors occurs only during the afternoon hours when negative load forecasts and positive wind forecasts are strongly correlated. Managing the integration of wind power in the California power system should focus on reducing wind power forecast uncertainty for wind ramp ups during the afternoon hours. Copyright © 2013 John Wiley & Sons, Ltd.

Abstract This study develops a novel sustainability assessment methodology for energy systems using life-cycle emission factors and sustainability indicators. Here, the global warming and environmental impact dimensions of the sustainability assessment methodology are examined in detail. A comparative analysis shows that a wind-battery system produces fewer potential global warming, stratospheric ozone depletion, air pollution, and water pollution impacts compared to a gas-fired system. The wind-battery system generates 13% of the life-cycle GHG emissions and 22% of the life-cycle ozone-depleting substance emissions of a gas-fired power plant. Nitrous oxide contributes more than 90% of the stratospheric ozone depletion potential of gas-fired and wind-battery systems.

Abstract In the present study, Loblolly pine biomass residue was converted to bio-oil in a two-step process, consisting of 1) fast pyrolysis in the presence of zeolite ZSM-5 as a catalyst to produce pyrolysis oil, 2) hydrogenation of pyrolysis oil using formic acid as the hydrogen source in presence of Ru/activated carbon catalyst. Pyrolysis oils were analyzed by 13C, 31P and HSQC-NMR and the results revealed that the zeolite-induced catalytic fast pyrolysis process led to effective demethoxylation, producing more catechol and p-hydroxy-phenyl hydroxyl groups in the bio-oils, resulting in a decrease in the methoxyl group content by about 85 % and rich aromatic structures in the pyrolysis oils. The properties of pyrolysis oil with and without zeolite were in the bio-oil range. Hydrogenated pyrolysis oil showed that 79 % of the aromatic protons are eliminated and 87 % of protons are aliphatic in nature, with no oxygen attached to the α-carbon.

For zero‐defect wave soldering of double‐sided and multilayer printed circuit boards, the copper through‐hole‐plating must be impervious to gas generated in the laminate for the period of a few seconds while the solder is molten. The kinetics of the gas evolution during soldering have been related quantitatively to the integrity of the plated copper. This in turn is related to the quality of the electroless copper (evaluated using the backlighting test), the nature and distribution of the catalyst (evaluated using X‐ray photoelectron spectroscopy) and the methods and effectiveness of the hole‐wall preparation (evaluated using scanning electron microscopy). The relevance of laboratory measurements has been confirmed on a wide range of industrial production plating lines.

The industrial sector accounts for 17% of end-use energy in the UK, and 54% globally. Therefore, there is substantial scope for simulating and assessing potential energy retrofit options for industrial buildings. Building Energy Modelling (BEM) applied to industrial buildings poses a complex but important opportunity for reducing global energy demand, due to years of renovation and expansion. Large and complex industrial buildings make modelling existing geometry for BEM difficult and time consuming. This paper presents a potential solution for quickly capturing and processing as-built geometry of a factory to be utilized in BEM. Laser scans were captured from the interior of an industrial facility to produce a Point Cloud. The existing capabilities of a Point Cloud processing software were assessed to identify the potential development opportunities to automate the conversion of Point Clouds to building geometry for BEM applications. In conclusion, scope exists for increasing the speed of 3D geometry creation of an existing industrial building for application in BEM and subsequent thermal simulation.

Abstract Space–time kinetics calculations for CANDU ® 1 reactors are routinely performed using the Improved Quasistatic (IQS) method. The IQS method calculates kinetics parameters such as the effective delayed-neutron fraction and generation time using adjoint weighting. In the current implementation of IQS, the direct flux, as well as the adjoint, is calculated using a two-group cell-homogenized reactor model which is inadequate for capturing the effect of the softer energy spectrum of the delayed neutrons. Additionally, there may also be fine spatial effects that are lost because the intra-cell adjoint shape is ignored. The purpose of this work is to compare the kinetics parameters calculated using the two-group cell-homogenized model with those calculated using lattice-level fine-group heterogeneous adjoint weighting and to assess whether the differences are large enough to justify further work on incorporating lattice-level adjoint weighting into the IQS method. A second goal is to evaluate whether the use of a fine-group cell-homogenized lattice-level adjoint, such as is the current practice for Light Water Reactors (LWRs), is sufficient to capture the lattice effects in question. It is found that, for CANDU lattices, the generation time is almost unaffected by the type of adjoint used to calculate it, but that the effective delayed-neutron fraction is affected by the type of adjoint used. The effective delayed-neutron fraction calculated using the two-group cell-homogenized adjoint is 5.2% higher than the “best” effective delayed-neutron fraction value obtained using the detailed lattice-level fine-group heterogeneous adjoint. The effective delayed-neutron fraction calculated using the fine-group cell-homogenized adjoint is only 1.7% higher than the “best” effective delayed-neutron fraction value but is still not equal to it. This situation is different from that encountered in LWRs where weighting by a fine-group cell-homogenized adjoint is sufficient to calculate the correct effective delayed-neutron fraction. It is concluded that lattice-level weighting with a detailed fine-group heterogeneous adjoint is desirable for the correct calculation of the effective delayed-neutron fraction in CANDU lattices.