Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications

Carbon capture and storage processes are sought to play a major role in reducing carbon emissions from large point sources. Petroleum refineries, in particular, produce several streams that are CO2-rich, including fluidized catalytic cracking, steam methane reforming, and natural gas combustion proc...

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Autores principales:	Adhish Chandra Saketh Madugula, Darshan Sachde, Susan D. Hovorka, Timothy A. Meckel, Tracy J. Benson
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Carbon Capture Compression Dehydration Regression Refinery Chemical engineering TP155-156
Acceso en línea:	https://doaj.org/article/8dfa4eb22b614e49b62be209f699ba90
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spelling	oai:doaj.org-article:8dfa4eb22b614e49b62be209f699ba902021-11-18T04:52:55ZEstimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications2666-821110.1016/j.ceja.2021.100162https://doaj.org/article/8dfa4eb22b614e49b62be209f699ba902021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666821121000788https://doaj.org/toc/2666-8211Carbon capture and storage processes are sought to play a major role in reducing carbon emissions from large point sources. Petroleum refineries, in particular, produce several streams that are CO2-rich, including fluidized catalytic cracking, steam methane reforming, and natural gas combustion processes that generate heat for refinery operations. Of these, stationary combustion processes account for nearly two-thirds of all CO2 generated within a refinery. In this work, a regression analysis was performed to correlate the size and power requirements for the combined capture, compression, and dehydration process dependent upon a refinery's operating capacity. Refinery capacity and CO2 generation data from 128 U.S. refineries were normalized, and a linear regression model was developed. A capture, compression, and dehydration process model was developed using Aspen HYSYS for delivery of CO2 (10–15 wt. % in steam) to pipeline specifications (500 ppm H2O, 15.2 MPa). Predicted CO2 emissions were 0.1 to 7.7 % of actual emissions, depending on whether a refinery had a low, medium, or high carbon emission/capacity ratio.Adhish Chandra Saketh MadugulaDarshan SachdeSusan D. HovorkaTimothy A. MeckelTracy J. BensonElsevierarticleCarbonCaptureCompressionDehydrationRegressionRefineryChemical engineeringTP155-156ENChemical Engineering Journal Advances, Vol 8, Iss , Pp 100162- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Carbon Capture Compression Dehydration Regression Refinery Chemical engineering TP155-156
spellingShingle	Carbon Capture Compression Dehydration Regression Refinery Chemical engineering TP155-156 Adhish Chandra Saketh Madugula Darshan Sachde Susan D. Hovorka Timothy A. Meckel Tracy J. Benson Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
description	Carbon capture and storage processes are sought to play a major role in reducing carbon emissions from large point sources. Petroleum refineries, in particular, produce several streams that are CO2-rich, including fluidized catalytic cracking, steam methane reforming, and natural gas combustion processes that generate heat for refinery operations. Of these, stationary combustion processes account for nearly two-thirds of all CO2 generated within a refinery. In this work, a regression analysis was performed to correlate the size and power requirements for the combined capture, compression, and dehydration process dependent upon a refinery's operating capacity. Refinery capacity and CO2 generation data from 128 U.S. refineries were normalized, and a linear regression model was developed. A capture, compression, and dehydration process model was developed using Aspen HYSYS for delivery of CO2 (10–15 wt. % in steam) to pipeline specifications (500 ppm H2O, 15.2 MPa). Predicted CO2 emissions were 0.1 to 7.7 % of actual emissions, depending on whether a refinery had a low, medium, or high carbon emission/capacity ratio.
format	article
author	Adhish Chandra Saketh Madugula Darshan Sachde Susan D. Hovorka Timothy A. Meckel Tracy J. Benson
author_facet	Adhish Chandra Saketh Madugula Darshan Sachde Susan D. Hovorka Timothy A. Meckel Tracy J. Benson
author_sort	Adhish Chandra Saketh Madugula
title	Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
title_short	Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
title_full	Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
title_fullStr	Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
title_full_unstemmed	Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
title_sort	estimation of co₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/8dfa4eb22b614e49b62be209f699ba90
work_keys_str_mv	AT adhishchandrasakethmadugula estimationofco2emissionsfrompetroleumrefineriesbasedonthetotaloperablecapacityforcarboncaptureapplications AT darshansachde estimationofco2emissionsfrompetroleumrefineriesbasedonthetotaloperablecapacityforcarboncaptureapplications AT susandhovorka estimationofco2emissionsfrompetroleumrefineriesbasedonthetotaloperablecapacityforcarboncaptureapplications AT timothyameckel estimationofco2emissionsfrompetroleumrefineriesbasedonthetotaloperablecapacityforcarboncaptureapplications AT tracyjbenson estimationofco2emissionsfrompetroleumrefineriesbasedonthetotaloperablecapacityforcarboncaptureapplications
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Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications

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