TY - JOUR
T1 - Synthesis of carbon integration networks coupled with hydrate suppression and dehydration options
AU - Klaimi, Rachid
AU - Alnouri, Sabla Y.
AU - Al-Mohannadi, Dhabia
AU - Zeaiter, Joseph
AU - Linke, Patrick
N1 - Publisher Copyright:
© 2018 Walter de Gruyter GmbH, Berlin/Boston.
PY - 2018/12/19
Y1 - 2018/12/19
N2 - The excessive increase in carbon dioxide emissions through the past several decades has raised global climate change concerns. As such, environmental policy makers have been looking into the implementation of efficient strategies that would ultimately reduce greenhouse gas (GHG) emission levels, and meet strict emissions targets. As part of a national emission reduction strategy, the reduction of carbon-dioxide emissions from industrial activities has been proven to be very significant. This instigated the need for a systematic carbon integration approach that can yield cost-effective carbon integration networks, while meeting prescribed carbon dioxide emission reduction targets in industrial cities. A novel carbon integration methodology has been previously proposed as a carbon network source-sink mapping approach using a Mixed Integer Nonlinear Program (MINLP), and was found to be very effective to devise emission control strategies in industrial cities. This paper aims to further improve the design process of carbon integration networks, by coupling carbon integration networks with hydrate suppression/moisture removal options. This was found vital for the prevention of any potential hazards that are associated with the transportation of carbon dioxide in pipelines, such as hydrate formation and various corrosion effects, which may result from moisture retention. An extensive analysis of carbon capture, dehydration, inhibition, compression, and transmission options have all been incorporated into the network design process, in the course of determining cost-optimal solutions for carbon dioxide networks. The proposed approach has been illustrated using an industrial city case study.
AB - The excessive increase in carbon dioxide emissions through the past several decades has raised global climate change concerns. As such, environmental policy makers have been looking into the implementation of efficient strategies that would ultimately reduce greenhouse gas (GHG) emission levels, and meet strict emissions targets. As part of a national emission reduction strategy, the reduction of carbon-dioxide emissions from industrial activities has been proven to be very significant. This instigated the need for a systematic carbon integration approach that can yield cost-effective carbon integration networks, while meeting prescribed carbon dioxide emission reduction targets in industrial cities. A novel carbon integration methodology has been previously proposed as a carbon network source-sink mapping approach using a Mixed Integer Nonlinear Program (MINLP), and was found to be very effective to devise emission control strategies in industrial cities. This paper aims to further improve the design process of carbon integration networks, by coupling carbon integration networks with hydrate suppression/moisture removal options. This was found vital for the prevention of any potential hazards that are associated with the transportation of carbon dioxide in pipelines, such as hydrate formation and various corrosion effects, which may result from moisture retention. An extensive analysis of carbon capture, dehydration, inhibition, compression, and transmission options have all been incorporated into the network design process, in the course of determining cost-optimal solutions for carbon dioxide networks. The proposed approach has been illustrated using an industrial city case study.
KW - Carbon integration
KW - Hydrates
KW - Industrial cities
KW - Moisture content
KW - Network design
UR - http://www.scopus.com/inward/record.url?scp=85049175061&partnerID=8YFLogxK
U2 - 10.1515/cppm-2018-0019
DO - 10.1515/cppm-2018-0019
M3 - Article
AN - SCOPUS:85049175061
SN - 1934-2659
VL - 13
JO - Chemical Product and Process Modeling
JF - Chemical Product and Process Modeling
IS - 4
M1 - 20180019
ER -