Assessment of power generation from natural gas and biomass to enhance environmental sustainability of a polyol ether production process for rigid foam polyurethane synthesis

Ali Ghannadzadeh*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Web of Science)

Abstract

Polyol ether production process can result in emission of extremely hazardous substances besides it requires high energy demand which can also cause environmental impacts. This paper presents an exergy-aided life cycle assessment (LCA) to pinpoint avoidable key causes of the environmental unsustainability in the period of clean energy transition, and enhance the sustainability as much as achievable. The power generation system is pinpointed as the mitigable key source of the unsustainability of the polyol ether production under the strict process constraints imposed by the energy transition. Then, a set of possible scenarios supported by Monte Carlo simulations are defined, resulting in reducing environmental impacts from 7.17 to 7.11 MJ equivalent of nonrenewable energy sources according to the Cumulative Exergy Demand or from the dimensionless normalized results of 3.43E-04 to 2.98E-04 according to ReCiPe. Moreover, LCA is advantageous to quantify precisely environmental impacts of each chemical component, showing that CO2 has much more adverse impacts on human health than the hazardous substances. Additionally, LCA reveals that natural gas can even be less sustainable than residual fuel oil in terms of freshwater ecotoxicity (75%), marine ecotoxicity (51%), terrestrial acidification (27%), human toxicity (43%), particulate matter formation (18%), and fossil depletion (64%) impacts. (C) 2017 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)846-858
Number of pages13
JournalRenewable Energy
Volume115
DOIs
Publication statusPublished - Jan 2018
Externally publishedYes

Keywords

  • Polyol ether
  • Rigid foam polyurethane
  • Biomass
  • Life cycle assessment
  • Exergy
  • Monte Carlo simulation

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