Aarón David Bojarski

Incorporating environmental impacts and regulations in a holistic supply chains modeling: An LCA approach

Abstract Corporate approaches to improve environmental performance cannot be undertaken in isolation, so a concerted effort along the supply chain (SC) entities is needed which poses another important challenge to managers. This work addresses the optimization of SC planning and design considering economical and environmental issues. The strategic decisions considered in the model are facility location, processing technology selection and production–distribution planning. A life cycle assessment (LCA) approach is envisaged to incorporate the environmental aspects of the model. IMPACT 2002+ methodology is selected to perform the impact assessment within the SC thus providing a feasible implementation of a combined midpoint–endpoint evaluation. The proposed approach reduces the value-subjectivity inherent to the assignment of weights in the calculation of an overall environmental impact by considering endpoint damage categories as objective function. Additionally, the model performs an impact mapping along the comprising SC nodes and activities. Such mapping allows to focus financial efforts to reduce environmental burdens to the most promising subjects. Furthermore, consideration of CO 2 trading scheme and temporal distribution of environmental interventions are also included with the intention of providing a tool that may be utilized to evaluate current regulatory policies or pursue more effective ones. The mathematical formulation of this problem becomes a multi-objective MILP (moMILP). Criteria selected for the objective function are damage categories impacts, overall impact factor and net present value (NPV). Main advantages of this model are highlighted through a realistic case study of maleic anhydride SC production and distribution network.

Advanced simulation environment for clean power production in IGCC plants

Oxygen-blown biomass integrated gasification combined cycle (IGCC) plants are one of the most promising options for clean energy generation with CO2 abatement potential. However, the integrated nature of IGCC leads to difficult design problems. In this study, we present an advanced simulation environment for the preliminary design and retrofit of IGCC plants. We describe the modelling approach, the model validation strategy and the plant behaviour, as determined by sensitivity analyses. The simulation environment uses Pareto curves to examine various co-gasification and co-production case studies in terms of technical, economic and environmental performance. It serves as a decision support tool in the design stage, which can be used to explore ways to improve plant performance and to analyse the influence of raw materials and the unit’s operational parameters. The test and validation results are discussed.

Modelling and sensitivity analysis of ATAD

Several authors have pointed out the need to identify the optimum operating conditions (OCs) of autothermal thermophilic aerobic digestion (ATAD). This study proves the hypothesis that the OCs have the potential to substantially improve the energy efficiency and plant capacity of established ATAD systems. As ATAD is a semi-batch process, its energy efficiency has to be optimized via dynamic optimization (DO). This methodology requires an adequate mathematical model, and appropriate selection of optimization variables. The paper presents an improved mathematical ATAD model based on previous models found in the literature. A global sensitivity analysis (GSA) was performed in order to identify variables with significant influence upon energy efficiency and plant capacity, thus paving the way for the DO of ATAD systems. The results of the GSA show that reactor volume, reactor temperature, and aeration flowrate are significant variables, which is consistent with reported literature. The results of the GSA also show that both energy efficiency and plant capacity of ATAD systems can be substantially improved by altering reactor volume and OCs.

Mapping environmental issues within supply chains: a LCA based approach

Abstract This work addresses the optimization of Supply Chain (SC) planning and design considering economical and environmental issues. The SC operations model applied does not require a superstructure definition a priori for the material flows. The strategic decisions considered in the model are facility location and equipment allocation. For the environmental aspects of the problem a Life Cycle Assessment (LCA) approach is applied. IMPACT 2002+ methodology is selected to perform the impact assessment within the SC since it proposes a feasible implementation of a combined midpoint-endpoint evaluation. No aggregation of damage categories and analysis of partial environmental impacts for each of echelon are performed. The formulation leads to a multi-criteria MILP program. The criteria adopted as objective functions are damage categories impacts, overall impact factor and net present value (NPV). The main advantages of this model are highlighted through a case study of a maleic anhydride SC.

Raw Materials Supply

The pressure on reducing environmental footprint is facilitating the emergence of energy supply chains that have biomass as main feedstock. For the development of efficient energy supply chains from biomass it is required to properly integrate the various elements that comprise such systems (e.g., biomass supply, pre-treatment facilities and technologies for biomass to energy and/or fuels conversion). Additionally, it is recognised that a concerted effort is required, embracing the different supply chain entities, in order to correctly estimate environmental burdens and to propose effective environmental strategies. This chapter proposes the use of a mathematical modelling approach as an analytical tool that can support decision-making towards accomplishing the design and planning of efficient multiple source—multiple product bio-energy supply chains. The mathematical formulation of this problem becomes a multi-objective MILP (moMILP). Criteria selected for the objective function are the net present value (NPV) and the overall environmental impact, which is computed using the Impact 2002+ indicator. The main advantages of this approach are highlighted through a case study of a biomass-based supply chain that comprises different components geographically distributed over Spain. For comparison purposes, such a supply chain is contrasted to one embracing coal usage.

Enhanced modeling and integrated simulation of gasification and purification gas units targeted to clean power production

This work presents a structured and validated conceptual model of an integrated gasification combined cycle (IGCC) power plant. A pressurized entrained flow (PRENFLO) gasifier, subsequent gas cleaning operations for fly ashes, ammonia, and sulfur compounds removal, heat recovery steam generator (HRSG) and combined cycle unit operations have been modeled in steady state. The model has been developed using Aspen Hysys® and Aspen Plus®. Parts of it have been developed in Matlab, which is mainly used for artificial neural network (ANN) training and parameters estimation Predicted results of clean gas composition and generated power present a good agreement with industrial data. This study is aimed at obtaining a support tool for optimal solutions assessment of different gasification plant configurations, under different input data sets.

Modelling Syngas Generation

Syngas generation refers to the production of a synthetic or synthesis gas that is mainly composed of CO and H2, in different proportions according to the generation process used and the raw material composition. Gasification is the referred technique to produce syngas. It can be used for different purposes, such as power and/or heat generation or for chemicals and fuels production. This chapter describes, we comment the generalities of syngas and its main characteristics and properties, also discuss its possible sources and focus on biomass waste and its co-gasification with coal and petcoke. Then, gasification modelling most common approaches are mentioned. A thermochemical equilibrium model is presented here as the model used for gasification plant conceptual design. Through sensitivity analysis technique, the effects of the reactor temperature and pressure are seen in syngas composition. This chapter enumerates the major hypothesis assumed in this syngas generation step, which must be inevitably applied in modelling and optimizing the entire gasification plant.

Evaluating long-term contamination in soils amended with sewage sludge

Sewage sludge application on agricultural fields is a managing practice of increasing use because of its benefits to soil and crops. However, if not well controlled, sludge application may lead to soil contamination. In Europe, threshold values for sewage sludge amendment have only been derived for heavy metals; and there is not any legal limitation for persistent organic pollutants (POPs) concentration in sewage sludge. In order to evaluate the fate of these contaminants in the soil matrix, a multimedia model was developed and executed for a case-study. The model, which was applied to different POPs, was used to predict the transport between soil phases (air, water, organic matter and mineral matter) based on fugacity values.

Global Clean Gas Process Synthesis and Optimisation

This chapter begins with an introduction to the different possible metrics related to clean gas process synthesis and its subsequent usage. Latter, the different techniques for tackling with multiple criteria are presented, emphasising the use of multi-criteria decision analysis (MCDA) and multi-objective optimisation (MOO). The different criteria elected here for optimisation are described and later used as key performance indicators (KPI) for the proposed scenarios, in chapter “ Selection of Best Designs for Specific Applications”. Finally, a case study related to the operation of an IGCC plant considering coal–petcoke or natural gas as a fuel is assessed applying the optimization concepts introduced here and taking into account the operation considerations developed in this and in previous chapters.

Towards an ontological infrastructure for chemical batch process management

In todays highly competitive marketplace, supply chain (SC) and product development activities should be coordinated and synchronized so that market demand, product release and capacity requirements are matched in a financially sustainable fashion. In this work, an integrated model is developed which incorporates simultaneous treatment of SC design-planning and R&D decisions in the pharmaceutical industry. Moreover, the aforementioned cross-functional model embeds a capital budgeting formulation enabling the quantitative assessment of the firms’ value. The model also considers the endogenous uncertainty associated with product test outcomes during the development process. To tackle this problem, a scenario based multi-stage stochastic mixed integer linear programming (MILP) formulation is proposed. This model includes risk constraints which allow finding optimal solutions within accepted risk levels. A decomposition technique is applied in order to reduce the computational effort required for the solution of the monolithic model, thus facilitating the solution of realistic industrial problems of moderate scale.Chemical batch process management, regardless of the level where its analysis is focused (such as pre-formulation and new process development, supply chain management, scheduling, process control, fault analysis, etc.) implies the collection and exploitation of huge amounts of data, which should be viewed as sources of information. Consequently, the information infrastructure which supports different activities by streamlining information gathering, data integration, model development and decision making is a crucial component towards process improvement/optimization. In this work it a Batch Process Ontology (BaPrOn) is presented, wherein different concepts regarding batch processes are categorized, and the relationships between them are examined and structured. Properties and relationships are introduced in agreement with ISA-88 standard, which provides a solid and transparent framework for integrating batch-related information.