Debalina Sengupta

Sustainability in the context of process engineering

Computational process design for sustainability using various available techniques is still limited to computer-aided design featuring process optimization of energy and material flow plus minimizing greenhouse gas emission and water conservation. Sustainable process demands more, such as minimizing the impacts from other harmful emissions, discharges, waste creation, economic, and societal impacts. We have proposed an overall sustainability footprint, which in theory represents impacts of a process on all three domains of sustainability. This perspective article provides a critical analysis of attaining sustainability by minimizing this sustainability footprint using impact data as indicators. We also propose the use of the integration of the sustainability footprint in the computer-aided process design itself, rather than checking the impacts after the data have been collected on actual process options designed ahead of the analyses.

A review of biodiesel production from microalgae

As the search for alternatives to fossil fuels continues, microalgae have emerged as a promising renewable feedstock for biodiesel. Many species contain high lipid concentrations and require simple cultivation—including reduced freshwater and land area needs—compared to traditional crops used for biofuels. Recently, technological advancements have brought microalgae biodiesel closer to becoming economically feasible through increased efficiency of the cultivation, harvesting, pretreatment, lipid extraction, and transesterification subsystems. The metabolism of microalgae can be favorably manipulated to increase lipid productivity through environmental stressors, and “green” techniques such as using flue gas as a carbon source and wastewater as a media replacement can lower the environmental impact of biodiesel production. Through life cycle assessment and the creation of process models, valuable insights have been made into the energy and material sinks of the manufacturing process, helping to identify methods to successfully scale up microalgae biodiesel production. Several companies are already exploring the microalgae industry, offsetting operating costs through isolation of co-products and careful unit operation selection. With numerous examples drawn from industry and the literature, this review provides a practical approach for creating a microalgae biodiesel facility.

Using national inventories for estimating environmental impacts of products from industrial sectors: a case study of ethanol and gasoline

PurposeIn order to understand the environmental outcomes associated with the life cycle of a product, to compare these outcomes across products, or to design more sustainable supply chains, it is often desirable to estimate results for a reference supply chain representative of the conditions for a sector in a specific region. This paper, by examining ethanol and gasoline production processes, explains how choices made in the calculation of sector-representative emission factors can have a significant effect on the emission estimates used in life cycle assessments.MethodsThis study estimates reference emission factors for United States dry-grind corn ethanol production and gasoline production processes suitable for use in baseline life cycle assessment unit processes. Based on facility-specific emissions and activity rates from the United States National Emissions Inventory, the Energy Information Administration, and an ethanol industry trade publication, the average emissions per unit energy content of fuel are computed using three different approaches. The Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI) characterization factors are used to estimate impact potentials for six environmental and three human health categories. Sector-specific direct emissions and impact potentials are compared across the three approaches and between the two sectors. The system boundary for this analysis is limited to the fuel production stage of these transportation fuel lifecycles.Results and discussionFindings from this work suggest that average emission factors based on total emissions and total production may significantly under estimate actual process emissions due to reporting thresholds and otherwise unreported emissions.ConclusionsBecause of the potential for unreported emissions in regional inventories, it is more appropriate to estimate sector reference emission factors based on matched sets of facility or process level emissions and activity rates than to use aggregated totals. This study demonstrates a method which can be used for inventory development in cases where multiple facilities producing the same product are involved.

Sustainability Measurement for Technology and Business Systems: Use of Currently Available Tools for Quantification

This chapter provides a review of the current state of the art in sustainability indicators or metrics for business and technology scales. These are the two scales at which the scientists and engineers have the most control over sustainability performance. At the business scale the purpose is to ensure investments to be secure and profitable, and for business to provide adequate support for the environment and the society. Three measurement systems are analyzed: the Global Reporting Initiative, the Dow Jones Sustainability Index, and an emerging method developed by the American Institute of Chemical engineers (AIChE), the first two being widely used. Of the technology systems, we cover the ones provided by the professional societies. The indicator system suggested by the Institution of Chemical Engineering (UK) explicitly lists the indicators under environmental, societal, and economic categories, but the AIChE system lists the most important technical indicators. Environmental Impact Assessment (EIA) and Life Cycle Assessment techniques are also presented to provide the context and tools needed for sustainability assessment at these scales.

A Process Integration Approach to the Optimization of CO2 Utilization via Tri-Reforming of Methane

Abstract Dry reforming of methane (DRM) utilizes two greenhouse gases; carbon dioxide (CO 2 ) and methane (CH 4 ) to produce a syngas mixture of carbon monoxide (CO) and hydrogen (H 2 ), which is a very important precursor for the production of a variety of valuable chemicals and liquid fuels. Although DRM offers important advantages for sequestering CO 2 , its utilization is challenged by certain critical process limitations such as carbon deposition, high energy requirements and low quality of H 2 :CO ratio. Due to these limitations, DRM process has always been a grey area demanding more research for its successful implementation at an industrial scale. Much of the work recently reported in the literature suggests the utilization of the combination of the conventional reforming technologies like steam reforming (SRM) and partial oxidation (POX) to tackle these limitations. The objective of this work is to develop a process integration approach to the optimization of a process involving DRM, SRM, and POX. As an extension to our previous work involving the optimization of the various operating parameter’s involved in Tri-Reforming (Challiwala et al. 2017), this work is aimed at mass and heat integration of the overall process to determine important benchmarks and to couple the reforming system with the rest of the process. Detailed kinetic and thermodynamic aspects are used to provide a high-fidelity model of the reforming system. The results from the thermodynamic study have been validated by using different combinations of the Langmuir-Hinshelwood-Hougen-Watson (LHHW) based kinetic models pertaining to DRM, POX and SRM processes individually. In particular, the major advancement in this work shows that the combination of individual kinetic models of different systems could be compatible to each other to predict the behaviour of the combined DRM/SRM/POX system and to exploit synergism with mass and energy from the rest of the industrial process. Validation of the results shows excellent agreement between thermodynamic and kinetic product profiles. In addition to this, the combined kinetic model was used to simulate a pseudo-homogeneous fixed bed reformer reactor in MATLAB® and further extended in COMSOL® simulation package to investigate the effect of the transport resistances present in the system under localized conditions of the catalyst bed. The proposed work is carried out at different scales and is conducive to multi-scale system integration and optimization.

Using module-based learning methods to introduce sustainable manufacturing in engineering curriculum

Purpose Sustainable manufacturing may be defined as the creation of manufactured products that use processes that are non-polluting, conserve energy and natural resources, and are economically sound and safe for employees, communities and consumers. Recently, there have been several industrial and governmental endeavors to launch sustainable manufacturing initiatives. To support such initiatives and to prepare the next generation of scientists and engineers, academic institutions have a responsibility to introduce educational programs and tools in the area of sustainable manufacturing. The purpose of this paper is to report on the approach, progress and contributions of a US National Science Foundation-sponsored project titled: “The Sustainable Manufacturing Advances in Research and Technology Coordination Network (SMART CN)”. Design/methodology/approach The project aims to bridge the gap between the academic knowledge discovery and industrial technology innovation for sustainable manufacturing. Toward this goal, various research and educational activities have been undertaken to introduce Sustainable Manufacturing Case Studies for use by academic instructors to a diverse group of undergraduate, graduate and industry professionals. Findings In this paper, the need for education on sustainable manufacturing has been focused upon, followed by approaches toward addressing these needs, concluding with examples of case studies developed through the SMART-CN project framework. Originality/value This work provides the engineering community with structured modules for introducing the topic of sustainable manufacturing in the curriculum.

Statistical Algorithms for Sustainability Measurement and Decision Making

Sustainability assertions are holistic in nature because they represent commentaries on the impacts of process and products on three dimensions of sustainability: environmental, economic, and societal. A large number of indicators (or metrics) may be used to observe the sustainability behavior of a process or product system. Because of the complex way these indicators interact with each other in influencing system performance, it is useful to construct a holistic measure to observe sustainability performance. The Euclidean distance, composed of the indicator values representing a system, was introduced as such a measure, and has been called the sustainability footprint. In this chapter detailed computations are shown on a test system to illustrate how the sustainability footprint is calculated and how it is used to compare among competing alternatives of a system in terms of sustainability. This method based on Euclidean distance is compared with other proposed methods for indicator aggregation, such as Vector Space Theory, Canberra distance, zCanberra distance, and Mahalanobis distance. In addition, two other objectives are achieved. First, by applying the principal component analysis, the redundant indicators are identified, and second, the rank order of the indicators in terms of their contribution to sustainability is calculated. This information will be helpful in improving sustainability performance at the redesign stage based on the relative contributions of the indicators and their controllability.

Case Studies in Sustainability Decision Making

Treatment of indicator data for computing sustainability footprints of systems is shown in detail in this chapter. Three representative systems have been chosen for sustainability assessment. Sustainability footprint is the Euclidean distance of a system, De, from a reference point of the same system, where De is characterized by chosen indicators . Thus for comparing different process options of a system, this distance gives an overall sustainability performance of the contending options. These three cases show how the calculations are made for obtaining the footprints. Additionally these cases also deal with statistical analysis of the covariance data of the indicator values to arrive at two important findings: first which of the indicators are necessary and sufficient for decision making and second, of the necessary indicators what are the rank orders of the indicators in terms of importance.

Incorporating Systems Thinking in the Engineering Design Curriculum: Path Forward for Sustainability Education

Systems thinking is the engineering technique that disaggregates complex technical, social, economic, and environmental problems into basic elements, studies their interrelations, evaluates these interactions through the aid of mathematics, and synthesizes the various elements into a complete and integrated system. Systems science and engineering has typically dealt with establishing common sets of features and functions that describe the system and its behavior, analyze them, and provide solutions for efficient operation of these systems. The specific nature of sustainable systems is very complex. The definition of sustainability encompasses economic, environmental, and societal aspects, which are deemed to work in a way such that the present and future generations are able to meet their needs. This article explores the need to introduce sustainability into the engineering curriculum and explains one method for doing so with an example.

Systems, Indicators, and Sustainability Assessment

Sustainability is related to a defined system. Sustainability assessment of a system is a determination of the sustainability performance of the system compared to a similar system with the same attributes. Indicators are representatives of the attributes that characterize the system. Since sustainability consists of three interacting dimensions: environmental, economic, and societal, a Venn diagram representation shows the classification of the intersections that can be represented by chosen indicators. For example, a three dimensional indicator will be placed at the intersection of the three dimensions. In this chapter we show how indicator dimensionality can be determined. We also recognize the types of systems—global, regional, business, and technology—to which an assessment can be applied. A general framework for implementing such an assessment of a system sustainability is presented. The same framework is applicable to a system belonging to any of the four system types. The specific indicators that adequately characterize one type of system are necessarily different from those of another type of system. Once the set of indicators is satisfactorily decided upon, data collections can begin for conducting an assessment using the framework.