Please use this identifier to cite or link to this item: https://doi.org/10.1021/ie802006w
Title: Optimization of recovery processes for multiple economic and environmental objectives
Authors: Lee, E.S.-Q.
Rangaiah, G.P. 
Issue Date: 19-Aug-2009
Source: Lee, E.S.-Q., Rangaiah, G.P. (2009-08-19). Optimization of recovery processes for multiple economic and environmental objectives. Industrial and Engineering Chemistry Research 48 (16) : 7662-7681. ScholarBank@NUS Repository. https://doi.org/10.1021/ie802006w
Abstract: Of the three spheres of sustainability-economic development, environmental stewardship, and societal equity, only the first two are quantifiable based on process variables. While economic criteria such as profit before taxes, payback period, and net present worth are well established, environmental objectives are recent and there is no general consensus on aggregation methods for calculating environmental impact. Many contributing factors have been identified for environmental impacts: impact on humans, ecosystem-terrestrial and aquatic, and local/global temperatures-global warming and ozone depletion, as well as photochemical oxidation, acid rain, and eutrophication. However, reported studies have used one aggregate environmental index as the objective in process design besides one economic objective. Hence, feasibility and usefulness of process optimization for more than two economic and environmental objectives is studied. Two case studies: a VOC (volatile organic component) recovery system and a solvent recovery system are chosen and optimized for both economic and environmental objectives using the elitist nondominated sorting genetic algorithm. The contributing factors to the environmental impacts are optimized individually or grouped into a few indices where appropriate. The objectives chosen for each round of optimization is two, several, or more, with at least one economic and one environmental objective. As they are partially or totally conflicting, Pareto- optimal solutions are obtained. These elucidate the trade-offs present, and the decision maker would be better equipped in choosing the best solution. The net flow method is then used to identify the best Pareto-optimal solution, whereby the decision maker's preference has to be declared. Pareto-optimal solutions and the best Pareto-optimal solution for the two case studies are presented and discussed. Insights gained from considering a number of environmental objectives for process optimization are highlighted. © 2009 American Chemical Society.
Source Title: Industrial and Engineering Chemistry Research
URI: http://scholarbank.nus.edu.sg/handle/10635/64354
ISSN: 08885885
DOI: 10.1021/ie802006w
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

18
checked on Dec 6, 2017

WEB OF SCIENCETM
Citations

15
checked on Nov 21, 2017

Page view(s)

32
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.