Application of a multidisciplinary approach for the evaluation of traceability of extra virgin olive oil

In this work, a multidisciplinary approach for the evaluation of extra virgin olive oil traceability (geographical provenience and botanical differentiation) is presented. Conventional techniques such as major chemical component determination (triacylglycerols, TAG and fatty acids) and other novel approaches as stable isotopic ratio (¹³C/¹²C in combination with ¹⁸O/¹⁶O) and thermal properties obtained from cooling curves and their deconvoluted peaks by means of differential scanning calorimetry were compared. Fifty‐three samples from different Italian regions, diverse cultivars, and two Mediterranean areas (Italy and Croatia) were analyzed with all the three techniques. The oils exhibited different values especially for δ¹⁸O and thermal properties of the deconvoluted peaks of crystallization according to Italian regions and/or cultivars. Data were treated by means of linear discriminant analysis inserting all parameters as predictors in models where the potentiality to discriminate oils was tested. All models revealed a good resolution among categories with selected TAG, δ¹⁸O values, and thermal properties of the deconvoluted peak set at the highest temperature exhibiting the highest weight for the discriminant functions. These findings could give strength to the utilization of new analytical techniques supporting those traditionally employed, also sustained by proper chemometric procedures, as suitable for the resolution of extra virgin olive traceability. Practical applications: Consumers' awareness of extra virgin olive oil traceability has recently increased the interest for new methods that can assess its geographical and botanical origins and new findings in this sector represent a key factor affecting the purchases in non‐producer countries. Multidisciplinary approaches supported by chemometric procedures enable the building of large databases and classification models for the determination of the provenience of extra virgin olive oil.     

Calorimetry of edible oils: Isothermal freezing curve for assessing extra‐virgin olive oil storage history

The calorimetric method described here investigates the solid‐liquid phase transitions in a Tuscan extra‐virgin olive oil in order to evaluate the changes induced by light exposition. The parameters of the freezing and the melting curves show high sensitivity to oil quality degradation, in agreement with the data from routine tests at disposal. Possible applications of the method are discussed.     

Automated ultrasound‐assisted method for the determination of the oxidative stability of virgin olive oil

A fast and automated method is proposed for determining the oxidative stability of virgin olive oil by using ultrasound. The ultrasound microprobe (3 mm in diameter) was directly immersed into the olive oil sample contained in a test tube. The most influential variables in the oxidation process, namely pulse amplitude, duty cycle, irradiation time, and sample amount, were optimized. The oil absorbance at 270 nm was continuously monitored by oil recirculation through a 0.1‐mm path length flow cell connected to a fiber optic microspectrometer. This short path length allowed the direct monitoring of absorbance without needing any sample dilution. The ultrasound energy was applied during 35 min, and the resulting increase in absorbance was continuously monitored. The difference between the final and the initial absorbance at 270 nm of a set of virgin olive oil samples was closely correlated with their oxidative stability calculated by the Rancimat method (R² = 0.9915). The resulting equation enabled the prediction of the oxidative stability of virgin olive oil in a short period of time (35 min), by using a simple, inexpensive, automatic and easy‐to‐use system.     

Energy in chemical manufacturing processes: gate‐to‐gate information for life cycle assessment

Gate‐to‐gate process energy for 86 chemical manufacturing processes is presented. The estimation of the process energy follows design‐based methodology. Results show that the gate‐to‐gate process energy for half of organic chemicals ranges from 0 to 4 MJ per kg, and for half of inorganic chemicals ranges from ?1 to 3 MJ per kg. The main energy source in both organic and inorganic processes is steam energy followed by potential recovered energy. In organic chemicals, the fractions of heating oil and electricity use are relatively low, but these fractions are higher in the inorganic chemicals than in the organic chemicals. Furthermore, about 50% of the energy consumed in chemical processes is used for purifying the product, byproduct or recycled stream, which indicates that there are large opportunities for improving the process energy in chemical processes. The information presented in this study is very important for those in the life cycle assessment community in order for them to identify inaccurate information or information not based on actual process design. However, the range for the entire range of chemicals is very substantial and thus reflects the need of the life cycle inventory to separately evaluate the chemistry and degree of purity for chemical products. Copyright © 2003 Society of Chemical Industry     

Exploiting olive oil mill effluents as a renewable resource for production of biodegradable polymers through a combined anaerobic–aerobic process

BACKGROUND: The performance of a three‐stage process for polyhydroxyalkanoate (PHA) bioproduction from olive oil mill effluents (OME) has been investigated. In the first anaerobic stage OME were fermented in a packed bed biofilm reactor into volatile fatty acids (VFAs). This VFA‐rich effluent was fed to the second stage, operated in an aerobic sequencing batch reactor (SBR), to enrich mixed cultures able to store PHAs. Finally, the storage response of the selected consortia was exploited in the third aerobic stage, operated in batch conditions. RESULTS: The anaerobic stage increased the VFA percentage in the OME from 18% to ～32% of the overall chemical oxygen demand (COD). A biomass with high storage response was successfully enriched in the SBR fed with the fermented OME at an organic load rate of 8.5 gCOD L^?1 d^?1, with maximum storage rate and yield (146 mgCOD gCOD^?1 h^?1 and 0.36 COD COD^?1, respectively) very similar to those obtained with a synthetic VFA mixture. By means of denaturing gradient gel electrophoresis (DGGE) analysis, different bacterial strains were identified during the two SBR runs: Lampropedia hyalina and Candidatus Meganema perideroedes, with the synthetic feed or the fermented OMEs, respectively. In the third stage, operated at increasing loads, the maximum concentration of the PHA produced increased linearly with the substrate fed. Moreover, about half of the stored PHAs were produced from substrates other than VFAs, mostly alcohols. CONCLUSION: The results obtained indicate that the process is effective for simultaneous treatment of OME and their valorization as a renewable resource for PHA production. Copyright © 2009 Society of Chemical Industry     

Model‐based design of a plant‐wide control strategy for a continuous pharmaceutical plant

The design of an effective plant‐wide control strategy is a key challenge for the development of future continuous pharmaceutical processes. This article presents a case study for the design of a plant‐wide control structure for a system inspired by an end‐to‐end continuous pharmaceutical pilot plant. A hierarchical decomposition strategy is used to classify control objectives. A plant‐wide dynamic model of the process is used to generate parametric sensitivities, which provide a basis for the synthesis of control loops. Simulations for selected disturbances illustrate that the critical quality attributes (CQAs) of the final product can be kept close to specification in the presence of significant and persistent disturbances. Furthermore, it is illustrated how selected CQAs of the final product can be brought simultaneously to a new setpoint while maintaining the remaining CQAs at a constant value during this transition. The latter result shows flexibility to control CQAs independently of each other. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3671–3685, 2013     

Novel operability‐based approach for process design and intensification: Application to a membrane reactor for direct methane aromatization

This article introduces a novel operability‐based approach for process design and intensification of energy systems described by nonlinear models. This approach is applied to a membrane reactor (MR) for the direct methane aromatization (DMA) conversion to benzene and hydrogen. The proposed method broadens the scope of the traditional path of the operability approaches for design and control, mainly oriented to obtain the achievable output set (AOS) from the available input set, and compare the computed AOS to a desired output set. In particular, an optimization algorithm based on nonlinear programming tools is formulated for the calculation of the desired input set that is feasible considering process constraints and intensification targets. Results on the application of the operability method as a tool for process intensification show reduction of the DMA‐MR footprint (≈77% reactor volume and 80% membrane area reduction) for an equivalent level of performance, when compared to the base case. This case study indicates that the novel approach can be a powerful tool for process intensification of membrane reactors and other complex chemical processes. © 2016 American Institute of Chemical Engineers AIChE J, 63: 975–983, 2017     

Optimal design of sustainable cellulosic biofuel supply chains: Multiobjective optimization coupled with life cycle assessment and input–output analysis

This article addresses the optimal design and planning of cellulosic ethanol supply chains under economic, environmental, and social objectives. The economic objective is measured by the total annualized cost, the environmental objective is measured by the life cycle greenhouse gas emissions, and the social objective is measured by the number of accrued local jobs. A multiobjective mixed‐integer linear programming (mo‐MILP) model is developed that accounts for major characteristics of cellulosic ethanol supply chains, including supply seasonality and geographical diversity, biomass degradation, feedstock density, diverse conversion pathways and byproducts, infrastructure compatibility, demand distribution, regional economy, and government incentives. Aspen Plus models for biorefineries with different feedstocks and conversion pathways are built to provide detailed techno‐economic and emission analysis results for the mo‐MILP model, which simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The mo‐MILP problem is solved with an ε‐constraint method; and the resulting Pareto‐optimal curves reveal the tradeoff between the economic, environmental, and social dimensions of the sustainable biofuel supply chains. The proposed approach is illustrated through two case studies for the state of Illinois. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

A bi‐criterion optimization approach for the design and planning of hydrogen supply chains for vehicle use

In this article, we address the design of hydrogen supply chains for vehicle use with economic and environmental concerns. Given a set of available technologies to produce, store, and deliver hydrogen, the problem consists of determining the optimal design of the production‐distribution network capable of satisfying a predefined hydrogen demand. The design task is formulated as a bi‐criterion mixed‐integer linear programming (MILP) problem, which simultaneously accounts for the minimization of cost and environmental impact. The environmental impact is measured through the contribution to climate change made by the hydrogen network operation. The emissions considered in the analysis are those associated with the entire life cycle of the process, and are quantified according to the principles of Life Cycle Assessment (LCA). To expedite the search of the Pareto solutions of the problem, we introduce a bi‐level algorithm that exploits its specific structure. A case study that addresses the optimal design of the hydrogen infrastructure needed to fulfill the expected hydrogen demand in Great Britain is introduced to illustrate the capabilities of the proposed approach. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

A methodology for simultaneous process and product design in the formulated consumer products industry: The case study of the detergent business

In this work we present a mathematical optimization based methodology for simultaneous formulae and process design in the consumer product business applied to the case of the laundry detergent. The design of a new detergent is formulated as a modified pooling problem including process, performance, processability and environmental constraints. This new features add a number of nonlinearities related to the modeling of the different aspects of the process and customer acceptance. The problem becomes a multiobjective optimization problem that is solved using the ?-constraint method with global optimization techniques to minimize of the environmental impact while minimizing the production cost for a couple of case studies. As future work, further process, product and legal constraints can be added to make the problem more realistic.     

A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT‐γ Mie approach

Molecular‐level decisions are increasingly recognized as an integral part of process design. Finding the optimal process performance requires the integrated optimization of process and solvent chemical structure, leading to a challenging mixed‐integer nonlinear programming (MINLP) problem. The formulation of such problems when using a group contribution version of the statistical associating fluid theory, SAFT‐γ Mie, to predict the physical properties of the relevant mixtures reliably over process conditions is presented. To solve the challenging MINLP, a novel hierarchical methodology for integrated process and solvent design (hierarchical optimization) is presented. Reduced models of the process units are developed and used to generate a set of initial guesses for the MINLP solution. The methodology is applied to the design of a physical absorption process to separate carbon dioxide from methane, using a broad selection of ethers as the molecular design space. The solvents with best process performance are found to be poly(oxymethylene)dimethylethers. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3249–3269, 2015     

On a new measure for the integration of process design and control: the disturbance resiliency index

The paper introduces a new measure for the integration of design and control. The measure is termed as a Disturbance Resiliency Index and reflects on the ability of the process to reject disturbances and prevent saturation in the manipulated variables. The paper presents the mathematical formulation for general nonlinear systems. The measure is defined mathematically and a set of properties and theorems are proved to enable its use. It is applicable both for steady state and dynamic systems. For a large number of systems and networks the application of the theory yields analytical expressions that one can study and analyze. In other cases, it yields bounding expressions that one can embed in optimization formulations and mathematical models. The paper contains several illustrations on the application of the measure on reaction systems, separation problems and heat exchanger networks.     

Reaction network flux analysis: Optimization‐based evaluation of reaction pathways for biorenewables processing

Even though biomass is attracting increasing interest as a raw material in the chemical and the fuel industries, only few biobased production processes are yet established. At the same time a lot of new catalytic routes are proposed, but their potential in biorefinery applications is hard to predict. Reaction network flux analysis (RNFA) is introduced as a novel, rapid screening method which bridges the gap between chemo‐ or biocatalysis and process design by (1) systematically identifying and (2) subsequently analyzing and ranking the large number of alternative reaction pathways based on limited data. This optimization‐based method helps to detect promising production routes as well as bottlenecks in possible pathways. The potential and the application of the RNFA methodology will be demonstrated by means of a case study for the production of the potential biofuel 3‐methyl‐tetrahydrofuran (3‐MTHF) from the platform chemical itaconic acid (IA). © 2011 American Institute of Chemical Engineers AIChE J, 58: 1788–1801, 2012     

Dimensional analysis of a novel low‐pressure device for the production of size‐tunable nanoemulsions

A novel low pressure device was used to generate nanoemulsions of methyl methacrylate. This device is based on a strong elongational flow known to be more efficient than the shear flow for dispersive mixing. The influence of process parameters (pressure drop number of cycles, number and size of holes) and composition parameters (monomer fraction, surfactant concentration, etc) on droplet size has shown that the average droplet size can be tailored in the range 30–200 nm by adjusting these parameters. The objective of the present paper is to find correlations that relate the obtained droplet size to the studied process and composition parameters. This model is based on a dimensional analysis using the Buckingham theorem in order to determine appropriate dimensionless numbers. This approach represents a first step for scaling up the device besides giving a set of parameters allowing to achieve a given droplet size. © 2014 American Institute of Chemical Engineers AIChE J, 61: 23–30, 2015