Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models

Sludge management in petroleum refineries is a costly and complex challenge, posing environmental risks and health hazards for humans. This study explores sludge incineration as a viable energy recovery method, using a case study from an Iranian refinery. Analysis of 15 sludge samples via bomb calor...

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Main Authors: Seyyed Roohollah Masoomi, Mohammad Gheibi, Reza Moezzi, Kourosh Behzadian, Atiyeh Ardakanian, Farzad Piadeh, Andres Annuk
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:ChemEngineering
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Online Access:https://www.mdpi.com/2305-7084/9/3/51
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author Seyyed Roohollah Masoomi
Mohammad Gheibi
Reza Moezzi
Kourosh Behzadian
Atiyeh Ardakanian
Farzad Piadeh
Andres Annuk
author_facet Seyyed Roohollah Masoomi
Mohammad Gheibi
Reza Moezzi
Kourosh Behzadian
Atiyeh Ardakanian
Farzad Piadeh
Andres Annuk
author_sort Seyyed Roohollah Masoomi
collection DOAJ
description Sludge management in petroleum refineries is a costly and complex challenge, posing environmental risks and health hazards for humans. This study explores sludge incineration as a viable energy recovery method, using a case study from an Iranian refinery. Analysis of 15 sludge samples via bomb calorimetry revealed an average heat value of 3100 kcal/kg, which declines with increased moisture content, while higher chemical oxygen demand (COD) enhances energy yield. Over five years, 4000 tonnes of accumulated sludge presented an energy potential of 12,400 Gcal. Statistical modeling, including polynomial regression and response surface methodology (RSM), mapped sludge storage profiles and predicted calorific values based on COD and moisture variations. The results indicate anaerobic digestion at greater depths reduces organic matter, lowering energy potential. Differential scanning calorimetry (DSC) analysis confirmed key thermal transitions, supporting sludge incineration as an effective waste-to-energy strategy. Implementing this approach within a circular economy framework can optimize refinery waste management while reducing pollution, though proper combustion byproduct control is essential for sustainability and regulatory compliance.
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publishDate 2025-05-01
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series ChemEngineering
spelling doaj-art-e00cf8b9246d47efa0e87f6f76986e5e2025-08-20T03:26:25ZengMDPI AGChemEngineering2305-70842025-05-01935110.3390/chemengineering9030051Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs ModelsSeyyed Roohollah Masoomi0Mohammad Gheibi1Reza Moezzi2Kourosh Behzadian3Atiyeh Ardakanian4Farzad Piadeh5Andres Annuk6Department of Environmental Engineering, Civil and Environmental Engineering Faculty, Tarbiat Modares University, Tehran 1411713116, IranInstitute for Nanomaterials Advanced Technologies and Innovation, Technical University of Liberec, Studentská 1402/2, 461 17 Liberec, Czech RepublicFaculty of Mechatronics, Informatics and Interdisciplinary Studies, Technical University of Liberec, 461 17 Liberec, Czech RepublicSmart Infrastructure and Green Technologies Research Group, School of Computing and Engineering, University of West London, London W5 5RF, UKSmart Infrastructure and Green Technologies Research Group, School of Computing and Engineering, University of West London, London W5 5RF, UKCentre for Research Engineering, School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UKInstitute of Forestry and Engineering, Estonian University of Life Sciences, 51006 Tartu, EstoniaSludge management in petroleum refineries is a costly and complex challenge, posing environmental risks and health hazards for humans. This study explores sludge incineration as a viable energy recovery method, using a case study from an Iranian refinery. Analysis of 15 sludge samples via bomb calorimetry revealed an average heat value of 3100 kcal/kg, which declines with increased moisture content, while higher chemical oxygen demand (COD) enhances energy yield. Over five years, 4000 tonnes of accumulated sludge presented an energy potential of 12,400 Gcal. Statistical modeling, including polynomial regression and response surface methodology (RSM), mapped sludge storage profiles and predicted calorific values based on COD and moisture variations. The results indicate anaerobic digestion at greater depths reduces organic matter, lowering energy potential. Differential scanning calorimetry (DSC) analysis confirmed key thermal transitions, supporting sludge incineration as an effective waste-to-energy strategy. Implementing this approach within a circular economy framework can optimize refinery waste management while reducing pollution, though proper combustion byproduct control is essential for sustainability and regulatory compliance.https://www.mdpi.com/2305-7084/9/3/51incinerationsludge managementsustainabilitywaste–energy nexusresponse surface methodologyartificial intelligence
spellingShingle Seyyed Roohollah Masoomi
Mohammad Gheibi
Reza Moezzi
Kourosh Behzadian
Atiyeh Ardakanian
Farzad Piadeh
Andres Annuk
Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models
ChemEngineering
incineration
sludge management
sustainability
waste–energy nexus
response surface methodology
artificial intelligence
title Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models
title_full Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models
title_fullStr Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models
title_full_unstemmed Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models
title_short Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models
title_sort waste to energy potential of petroleum refinery sludge statistical optimization machine learning and life cycle costs models
topic incineration
sludge management
sustainability
waste–energy nexus
response surface methodology
artificial intelligence
url https://www.mdpi.com/2305-7084/9/3/51
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