Developing a systematic framework for consistent allocation in LCA

Purpose

Multifunctionality in life-cycle assessment (LCA) is solved with allocation, for which many different procedures are available. Lack of sufficient guidance and difficulties to identify the correct allocation approach cause a large number of combinations of methods to exist in scientific literature. This paper reviews allocation procedures for recycling situations, with the aim to identify a systematic approach to apply allocation.

Methods

Assumptions and definitions for the most important terms related to multifunctionality and recycling in LCA are given. The most relevant allocation procedures are identified from literature. These procedures are expressed in mathematical formulas and schemes and arranged in a systematic framework based on the underlying objectives and assumptions of the procedures.

Results and discussion

If the LCA goal asks for an attributional approach, multifunctionality can be solved by applying system expansion—i.e. including the co-functions in the functional unit—or partitioning. The cut-off approach is a form of partitioning, attributing all the impacts to the functional unit. If the LCA goal asks for a consequential approach, substitution is applied, for which three methods are identified: the end-of-life recycling method and the waste mining method, which are combined in the 50/50 method. We propose to merge these methods in a new formula: the market price-based substitution method. The inclusion of economic values and maintaining a strict separation between attributional and consequential LCA are considered to increase realism and consistency of the LCA method.

Conclusions and perspectives

We identified the most pertinent allocation procedures—for recycling as well as co-production and energy recovery—and expressed them in mathematical formulas and schemes. Based on the underlying objectives of the allocation procedures, we positioned them in a systematic and consistent framework, relating the procedures to the LCA goal definition and an attributional or consequential approach. We identified a new substitution method that replaces the three existing methods in consequential LCA. Further research should test the validity of the systematic framework and the market price-based substitution method by means of case studies.

     

A tractable revenue management model for capacity allocation and overbooking over an airline network

In this paper, we develop a revenue management model to jointly make the capacity allocation and overbooking decisions over an airline network. The crucial observation behind our model is that if the penalty cost of denying boarding to the reservations were given by a separable function, then the optimality equation for the joint capacity allocation and overbooking problem would decompose by the itineraries. We exploit this observation by building an approximation to the penalty cost that is separable by the numbers of reservations for different itineraries. In this case, we can obtain an approximate solution to the optimality equation by plugging the separable approximation into the boundary condition of the optimality equation. Our computational experiments compare our approach with a standard deterministic linear programming formulation, as well as a recent joint capacity allocation and overbooking model. When compared with the standard deterministic linear programming formulation, our approach can provide significant profit improvements. On the other hand, when compared with the recent joint capacity allocation and overbooking model, our approach can provide similar profit performance with substantially shorter runtimes.     

Carbon mass balance evaluation of cellulase production on soluble and insoluble substrates

A methodology is described and applied for performing carbon mass balances across cellulase enzyme production processes using both soluble sugar and insoluble cellulose substrates. The fungus Trichoderma reesei was grown on either glucose, lactose, or cellulose in aerobic batch mode, and the evolution of the main carbonaceous components (cell mass, cellulose, soluble protein, adsorbed protein, sugars, and carbon dioxide) was followed. A variety of analytical techniques were utilized to measure these components, including (i) gravimetric analysis, (ii) near-infrared spectroscopy, (iii) bicinchoninic acid based soluble protein measurement, (iv) gas mass spectrometry and flow rate, (v) CHNS/O elemental analyses, and (vi) high-performance liquid chromatography. The combined set of measurements allowed carbon mass balances across the cellulase production process to be assessed to determine the consistency of the underlying kinetic data. Results demonstrate the capability to determine the levels and distribution of all major carbonaceous components during the cellulase production process on both soluble and insoluble substrates. Average carbon mass balance closures were near 100% during early stages (<72 h) of the cultivations using glucose, lactose, or cellulose as the substrates, but carbon mass closures trended high later in the cultivation. Analysis of carbon allocation results suggests that an error in the gas mass flow rate measurement was the primary cause for carbon mass balance closures to exceed 110% late in the process.     

Generation of an Industry-specific Physico-chemical Allocation Matrix. Application in the Dairy Industry and Implications for Systems Analysis (9 pp)

Background, Aims and Scope Allocation is required when quantifying environmental impacts of individual products from multi-product manufacturing plants. The International Organization for Standardization (ISO) recommends in ISO 14041 that allocation should reflect underlying physical relationships between inputs and outputs, or in the absence of such knowledge, allocation should reflect other relationships (e.g. economic value). Economic allocation is generally recommended if process specific information on the manufacturing process is lacking. In this paper, a physico-chemical allocation matrix, based on industry-specific data from the dairy industry, is developed and discussed as an alternative allocation method. Methods Operational data from 17 dairy manufacturing plants was used to develop an industry specific physico-chemical allocation matrix. Through an extensive process of substraction/substitution, it is possible to determine average resource use (e.g. electricity, thermal energy, water, etc) and wastewater emissions for individual dairy products within multi-product manufacturing plants. The average operational data for individual products were normalised to maintain industry confidentiality and then used as an industry specific allocation matrix. The quantity of raw milk required per product is based on the milk solids basis to account for dairy by-products that would otherwise be neglected. Results and Discussion Applying fixed type allocation methods (e.g. economic) for all input and outputs based on the quantity of product introduces order of magnitude sized deviations from physico-chemical allocation in some cases. The error associated with the quality of the whole of factory plant data or truncation error associated with setting system boundaries is insignificant in comparison. The profound effects of the results on systems analysis are discussed. The results raise concerns about using economic allocation as a default when allocating intra-industry sectoral flows (i.e. mass and process energy) in the absence of detailed technical information. It is recommended that economic allocation is better suited as a default for reflecting inter-industry sectoral flows. Conclusion The study highlights the importance of accurate causal allocation procedures that reflect industry-specific production methods. Generation of industry-specific allocation matrices is possible through a process of substitution/subtraction and optimisation. Allocation using such matrices overcomes the inherit bias of mass, process energy or price allocations for a multi-product manufacturing plant and gives a more realistic indication of resource use or emissions per product. The approach appears to be advantageous for resource use or emissions allocation if data is only available on a whole of factory basis for several plants with a similar level of technology. Recommendation and Perspective The industry specific allocation matrix approach will assist with allocation in multi-product LCAs where the level of technology in an industry is similar. The matrix will also benefit dairy manufacturing companies and help them more accurately allocate resources and impacts (i.e. costs) to different products within the one plant. It is recommended that similar physico-chemical allocation matrices be developed for other industry sectors with a view of ultimately coupling them with input-output analysis.     

Life cycle assessment of biofuels: Energy and greenhouse gas balances

The promotion of biofuels as energy for transportation in the industrialized countries is mainly driven by the perspective of oil depletion, the concerns about energy security and global warming. However due to sustainability constraints, biofuels will replace only 10 to 15% of fossil liquid fuels in the transport sector. Several governments have defined a minimum target of GHG emissions reduction for those biofuels that will be eligible to public incentives, for example a 35% emissions reduction in case of biofuels in Members States of the European Union. This article points out the significant biases in estimating GHG balances of biofuels stemming from modelling choices about system definition and boundaries, functional unit, reference systems and allocation methods. The extent to which these choices influence the results is investigated. After performing a comparison and constructive criticism of various modelling choices, the LCA of wheat-to-bioethanol is used as an illustrative case where bioethanol is blended with gasoline at various percentages (E5, E10 and E85). The performance of these substitution options is evaluated as well. The results show a large difference in the reduction of the GHG emissions with a high sensitivity to the following factors: the method used to allocate the impacts between the co-products, the type of reference systems, the choice of the functional unit and the type of blend. The authors come out with some recommendations for basing the estimation of energy and GHG balances of biofuels on principles such as transparency, consistency and accuracy.     

Measuring preferences on environmental damages in LCIA. Part 2: choice and allocation questions in panel methods

Background, aim, and scope  Within life cycle impact assessment (LCIA), ‘panel methods’ has become a common term to denominate methods that elicit and measure stakeholders’ stated preferences on environmental impact categories. Such panel procedures use different question formats to elicit information on weighting across impact categories from the stakeholders. The two most frequently used question formats are score allocation and choice between alternatives. The differences between these two question formats were analyzed in order to give advice on how to frame future panel procedures. Materials and methods  A choice-based weighting procedure (choice experiment) for the three damage categories of human health, ecosystems quality, and resources was developed and executed. A logistic regression model was applied in order to estimate the weighting factors for the polled sample. Results from this choice-based procedure were compared to the results from an allocation-based procedure described in part 1 of this paper. Results  When weighting factors are elicited by score allocation questions, panelists tend to distribute the scores more equally. A factor of 1.5 between the least and the most weighted damage category was found. Weighting factors from a choice experiment were more spread, i.e., the most important category was weighted considerably higher, whereas the other two categories were weighted less. Thus, for the choice experiment, the range between the most and the least weighted categories was considerably bigger—by about a factor of 4. Discussion  A comparison of the two procedures revealed that the weighting of environmental damage categories is considerably influenced by the question of format. The reason for these variations may be different cognitive routines that are applied. In addition, several advantages and shortcomings of choice experiments are discussed. Conclusions  The developed, choice-based procedure provided meaningful results. Thus, choice experiments, often used for the monetary valuation of environmental goods, can also be applied in LCIA to elicit nonmonetary weighting factors. Recommendations and perspectives  Choice experiments form a new interesting approach for weighting procedures in the future as they have some advantages over the often used score allocation methods. They are simple and more realistic than other procedures, as panelists have practiced in choice tasks from everyday life. We, therefore, recommend such choice-based procedures for future panel studies.

Credit Assignment during Movement Reinforcement Learning

We often need to learn how to move based on a single performance measure that reflects the overall success of our movements. However, movements have many properties, such as their trajectories, speeds and timing of end-points, thus the brain needs to decide which properties of movements should be improved; it needs to solve the credit assignment problem. Currently, little is known about how humans solve credit assignment problems in the context of reinforcement learning. Here we tested how human participants solve such problems during a trajectory-learning task. Without an explicitly-defined target movement, participants made hand reaches and received monetary rewards as feedback on a trial-by-trial basis. The curvature and direction of the attempted reach trajectories determined the monetary rewards received in a manner that can be manipulated experimentally. Based on the history of action-reward pairs, participants quickly solved the credit assignment problem and learned the implicit payoff function. A Bayesian credit-assignment model with built-in forgetting accurately predicts their trial-by-trial learning.     

Solving the multifunctionality dilemma in biorefineries with a novel hybrid mass–energy allocation method

Processing biomass into multifunctional products can contribute to food, feed, and energy security while also mitigating climate change. However, biorefinery products nevertheless impact the environment, and this influence needs to be properly assessed to minimize the burden. Life cycle assessment (LCA) is often used to calculate environmental footprints of products, but distributing the burdens among the different biorefinery products is a challenge. A particular complexity arises when the outputs are a combination of energy carrying no mass, and mass carrying no energy, where neither an allocation based on mass nor on energy would be appropriate. A novel hybrid mass–energy (HMEN) allocation scheme for dealing with multifunctionality problems in biorefineries was developed and applied to five biorefinery concepts. The results were compared to results of other allocation methods in LCA. The reductions in energy use and GHG emissions from using the biorefinery's biofuels were also quantified. HMEN fairly distributed impacts among biorefinery products and did not change the order of the products in terms of the level of the pollution caused. The allocation factors for HMEN fell between mass and economic allocation factors and were comparable to energy allocation factors. Where the mass or the energy allocation failed to attribute burdens, HMEN addressed this shortcoming by assigning impacts to nonmass or to nonenergy products. Under the partitioning methods and regardless of the feedstock used, bioethanol reduced GHG by 72–98% relative to gasoline. The GHG savings were 196% under the substitution method, but no GHG savings occurred for sugar beet bioethanol under the surplus method. Bioethanol from cellulosic crops had lower energy use and GHG emissions than from sugar beet, regardless of the allocation method used. HMEN solves multifunctional problems in biorefineries and can be applied to other complex refinery systems. LCA practitioners are encouraged to further test this method in other case studies.     

Resolving the root of the avian mitogenomic tree by breaking up long branches

Incomplete taxon sampling has been a major problem in resolving the early divergences in birds. Five new mitochondrial genomes are reported here (brush-turkey, lyrebird, suboscine flycatcher, turkey vulture, and a gull) and three break up long branches that tended to attract the distant reptilian outgroup. These long branches were to galliforms, and to oscine and suboscine passeriformes. Breaking these long branches leaves the root, as inferred by maximum likelihood and Bayesian phylogenetic analyses, between paleognaths and neognaths. This means that morphological, nuclear, and mitochondrial data are now in agreement on the position of the root of the avian tree and we can, move on to other questions. An overview is then given of the deepest divisions in the mitogenomic tree inferred from complete mitochondrial genomes. The strict monophyly of both the galloanseres and the passerines is strongly supported, leaving the deep six-way split within Neoaves as the next major question for which resolution is still lacking. Incomplete taxon sampling was also a problem for Neoaves, and although some resolution is now available there are still problems because current phylogenetic methods still fail to account for real features of DNA sequence evolution.     

Adaptive weighted learning for unbalanced multicategory classification

Summary .  In multicategory classification, standard techniques typically treat all classes equally. This treatment can be problematic when the dataset is unbalanced in the sense that certain classes have very small class proportions compared to others. The minority classes may be ignored or discounted during the classification process due to their small proportions. This can be a serious problem if those minority classes are important. In this article, we study the problem of unbalanced classification and propose new criteria to measure classification accuracy. Moreover, we propose three different weighted learning procedures, two one-step weighted procedures, as well as one adaptive weighted procedure. We demonstrate the advantages of the new procedures, using multicategory support vector machines, through simulated and real datasets. Our results indicate that the proposed methodology can handle unbalanced classification problems effectively.     

Dynamic motion planning of 3D human locomotion using gradient-based optimization

Since humans can walk with an infinite variety of postures and limb movements, there is no unique solution to the modeling problem to predict human gait motions. Accordingly, we test herein the hypothesis that the redundancy of human walking mechanisms makes solving for human joint profiles and force time histories an indeterminate problem best solved by inverse dynamics and optimization methods. A new optimization-based human-modeling framework is thus described for predicting three-dimensional human gait motions on level and inclined planes. The basic unknowns in the framework are the joint motion time histories of a 25-degree-of-freedom human model and its six global degrees of freedom. The joint motion histories are calculated by minimizing an objective function such as deviation of the trunk from upright posture that relates to the human model's performance. A variety of important constraints are imposed on the optimization problem, including (1) satisfaction of dynamic equilibrium equations by requiring the model's zero moment point (ZMP) to lie within the instantaneous geometrical base of support, (2) foot collision avoidance, (3) limits on ground-foot friction, and (4) vanishing yawing moment. Analytical forms of objective and constraint functions are presented and discussed for the proposed human-modeling framework in which the resulting optimization problems are solved using gradient-based mathematical programming techniques. When the framework is applied to the modeling of bipedal locomotion on level and inclined planes, acyclic human walking motions that are smooth and realistic as opposed to less natural robotic motions are obtained. The aspects of the modeling framework requiring further investigation and refinement, as well as potential applications of the framework in biomechanics, are discussed.     

Alternative approach to species identification of Actaea racemosa L. (syn. Cimicifuga racemosa (L.) Nutt., black cohosh) herbal starting material: UV spectroscopy coupled with LDA

The North American Actaea racemosa L. (syn. Cimicifuga racemosa (L.) Nutt., commonly known as black cohosh), considered to be a more “natural” alternative to conventional therapies, is used to relieve menopausal symptoms. The high demand for plant material has led to problems with substitution/adulteration of raw material of wholesale origin. The authenticity of the starting material is crucial for the herbal product’s efficacy and safety, and tests on identity and substitution are integral parts of cGMP guidelines. Consequently, there is a need for economical and easy-applicable test procedures. The aim of this study is to reveal the capability of the well-established UV spectroscopy coupled with a multivariate classification procedure to serve as a tool for the identification of A. racemosa. We built a classification model applying linear discriminant analysis (LDA) to distinguish between A. racemosa and its common substitutes. The model showed a high level of accuracy predicting 100% of the samples correctly. Our results indicate that UV spectroscopy shows potential for the development of possible additional authentication methods for this herbal starting material.     

Boundary conditions at the cartilage-synovial fluid interface for joint lubrication and theoretical verifications

The objective of this study is to establish and verify the set of boundary conditions at the interface between a biphasic mixture (articular cartilage) and a Newtonian or non-Newtonian fluid (synovial fluid) such that a set of well-posed mathematical problems may be formulated to investigate joint lubrication problems. A "pseudo-no-slip" kinematic boundary condition is proposed based upon the principle that the conditions at the interface between mixtures or mixtures and fluids must reduce to those boundary conditions in single phase continuum mechanics. From this proposed kinematic boundary condition, and balances of mass, momentum and energy, the boundary conditions at the interface between a biphasic mixture and a Newtonian or non-Newtonian fluid are mathematically derived. Based upon these general results, the appropriate boundary conditions needed in modeling the cartilage-synovial fluid-cartilage lubrication problem are deduced. For two simple cases where a Newtonian viscous fluid is forced to flow (with imposed Couette or Poiseuille flow conditions) over a porous-permeable biphasic material of relatively low permeability, the well known empirical Taylor slip condition may be derived using matched asymptotic analysis of the boundary layer at the interface.     

Simple nonsingular control approach to fed-batch fermentation optimization

Determination of the optimal feed rate for fed-batch fermentation is normally a problem in singular control with a state inequality constraint and as such is, in general, difficult to solve, especially for those described by a large number of dynamic mass balance equations. In this article we use a new set of state variables and the culture volume as the control variable. In this way the problem is converted to one of nonsingular control with the magnitude and rate constraints on the manipulated variable and can be numerically solved by a gradient-based technique, thus avoiding the difficulty associated with singular control problems. Examples are given to illustrate the method.     

污染环境中可再生资源的最优收获问题

探讨了污染环境下双种群的最优收获问题．利用Pontryagin极大值原理得到一种最优分配方案——处理资源种群体内毒素的努力度与收获资源种群的努力度的分配方案,使经营者的经济收入达到最大,同时也得到次最优均衡解。     

From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers

An Internet hosting center hosts services on its server ensemble. The center must allocate servers dynamically amongst services to maximize revenue earned from hosting fees. The finite server ensemble, unpredictable request arrival behavior and server reallocation cost make server allocation optimization difficult. Server allocation closely resembles honeybee forager allocation amongst flower patches to optimize nectar influx. The resemblance inspires a honeybee biomimetic algorithm. This paper describes details of the honeybee self-organizing model in terms of information flow and feedback, analyzes the homology between the two problems and derives the resulting biomimetic algorithm for hosting centers. The algorithm is assessed for effectiveness and adaptiveness by comparative testing against benchmark and conventional algorithms. Computational results indicate that the new algorithm is highly adaptive to widely varying external environments and quite competitive against benchmark assessment algorithms. Other swarm intelligence applications are briefly surveyed, and some general speculations are offered regarding their various degrees of success.     

Generally applicable fed-batch culture concept based on the detection of metabolic state by on-line balancing

In many microorganisms, flux limitations in oxidative metabolism lead to the formation of overflow metabolites even under fully aerobic conditions. This can be avoided if the specific growth rate is controlled at a low enough value. This is usually accomplished by controlling the substrate feeding profile in a fed-batch process. The present work proposes a control concept which is based on the on-line detection of metabolic state by on-line calculation of mass and elemental balances. The advantages of this method are: 1) the check of measurement consistency based on all of the available measurements, 2) the minimum requirement of a priori knowledge of metabolism, and 3) the exclusive use of simple and established on-line techniques which do not require direct measurement of the metabolite in question. The control concept has been linked to a simple adaptive controller and applied to fed-batch cultures of S. cerevisiae and E. coli, organisms which express different overflow metabolites, ethanol and acetic acid, respectively. Oxidative and oxidoreductive states of S. cerevisiae and E. coli cultures were detected with high precision. As demonstrated by the formation of acetic acid in E. coli cultures, metabolic states could be correctly distinguished for systems for which traditional methods, such as respiratory quotient (RQ), are insensitive. Hence, it could be shown that the control concept allowed avoidance of overflow metabolite formation and operation at maximum oxidative biomass productivity and oxidative conversion of substrate into biomass. Based on mass and elemental balances, the proposed method additionally provides a richness of additional information, such as yield coefficients and estimation of concentrations and specific conversion rates. These data certainly help the operator to additionally evaluate the state of the process on-line.     

PCB assembly scheduling with alternative nozzle types for one component type

The placement machine is the bottleneck of a printed circuit board (PCB) assembly line. The type of machine considered in this paper is the beam-type placement machine that can simultaneously pick up several components from feeders. It is assumed that the number of nozzle types (NTs) is less than the number of heads on the beam. The objective of the PCB assembly scheduling for a single placement machine is to minimize the cycle time based on the average machine operation time instead of the travelling distance. To minimize the cycle time, the number of turns and the number of pickups should be minimized. The PCB assembly scheduling is hierarchically decomposed into four problems: the nozzle assignment problem, the head allocation problem, the component type (CT) grouping problem and the pickup clustering problem, which are optimized successively and iteratively. First, the nozzle assignment problem considering alternative NTs for one CT is dealt with by the proposed genetic algorithm. For a given nozzle assignment solution, the head allocation problem is solved by a previously greedy heuristic to minimize the number of turns.Then, the CT grouping problem and the pickup clustering problem are solved by a proposed greedy heuristic and a modified agglomerative hierarchical clustering approach, respectively, to minimize the number of pickups. Numerical experiments are carried out to examine the performances of these proposed heuristic approaches. The importance of considering alternative NTs for one CT for the cycle time is also confirmed.     

Utilization of mass–energy balance regularities in the analysis of continuous-culture data

Material and energy balances for continuous-culture processes are described based on the facts that the heat of reaction per electron transferred to oxygen for a wide variety of organic molecules, the number of available electrons per carbon atom in biomass, and the weight fraction carbon in biomass are relatively constant. Energy requirements for growth and maintenance are investigated and related to the biomass energetic yield. The consistency of experimental data is examined using material and energy balances and the regularities identified above. When extracellular products are absent, the consistency of yield models containing separate terms for growth and maintenance may be investigated using organic substrate consumption, biomass production, oxygen consumption (or heat evolution), and carbon dioxide evolution rate data for a series of dilution rates. The consistency of continuous-culture data in the published literature is examined.