P-Graph Approach to Planning Biochar-Based Carbon Management Networks

Biochar application to soil is a potentially scalable carbon sequestration strategy. In practice, the amount of biochar that can be added to soil is constrained by the presence of contaminants such as salts, heavy metals, or dioxins. Process Systems Engineering (PSE) and Process Integration (PI) met...

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Main Authors: Kathleen B. Aviso, John Ismael A. Arogo, Antonio Louis O. Coronel, Christian Marco J. Janairo, Dominic C. Y. Foo, Raymond R. Tan
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2018-08-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/437
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spelling doaj-42c63f70f6cf4913be4ba1910e7093382021-02-17T21:00:49ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162018-08-017010.3303/CET1870007P-Graph Approach to Planning Biochar-Based Carbon Management Networks Kathleen B. AvisoJohn Ismael A. ArogoAntonio Louis O. CoronelChristian Marco J. JanairoDominic C. Y. FooRaymond R. TanBiochar application to soil is a potentially scalable carbon sequestration strategy. In practice, the amount of biochar that can be added to soil is constrained by the presence of contaminants such as salts, heavy metals, or dioxins. Process Systems Engineering (PSE) and Process Integration (PI) methods can be developed to optimize the reduction of greenhouse gas (GHG) emissions in such biochar-based Carbon Management Networks (CMNs). Previous works have proposed Mathematical Programming (MP) and Pinch Analysis (PA) approaches to the planning of these systems but are subject to the inherent methodological limitations. In this work, an alternative approach using Process Graph (P-graph) is developed, based on the source-sink matching problem being treated as a special Process Network Synthesis (PNS) problem. A case study is solved to illustrate the P-graph approach. In particular, optimal and near-optimal solutions are generated for the problem, which in real applications presents improved flexibility for purposes of practical decision support. https://www.cetjournal.it/index.php/cet/article/view/437
collection DOAJ
language English
format Article
sources DOAJ
author Kathleen B. Aviso
John Ismael A. Arogo
Antonio Louis O. Coronel
Christian Marco J. Janairo
Dominic C. Y. Foo
Raymond R. Tan
spellingShingle Kathleen B. Aviso
John Ismael A. Arogo
Antonio Louis O. Coronel
Christian Marco J. Janairo
Dominic C. Y. Foo
Raymond R. Tan
P-Graph Approach to Planning Biochar-Based Carbon Management Networks
Chemical Engineering Transactions
author_facet Kathleen B. Aviso
John Ismael A. Arogo
Antonio Louis O. Coronel
Christian Marco J. Janairo
Dominic C. Y. Foo
Raymond R. Tan
author_sort Kathleen B. Aviso
title P-Graph Approach to Planning Biochar-Based Carbon Management Networks
title_short P-Graph Approach to Planning Biochar-Based Carbon Management Networks
title_full P-Graph Approach to Planning Biochar-Based Carbon Management Networks
title_fullStr P-Graph Approach to Planning Biochar-Based Carbon Management Networks
title_full_unstemmed P-Graph Approach to Planning Biochar-Based Carbon Management Networks
title_sort p-graph approach to planning biochar-based carbon management networks
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2018-08-01
description Biochar application to soil is a potentially scalable carbon sequestration strategy. In practice, the amount of biochar that can be added to soil is constrained by the presence of contaminants such as salts, heavy metals, or dioxins. Process Systems Engineering (PSE) and Process Integration (PI) methods can be developed to optimize the reduction of greenhouse gas (GHG) emissions in such biochar-based Carbon Management Networks (CMNs). Previous works have proposed Mathematical Programming (MP) and Pinch Analysis (PA) approaches to the planning of these systems but are subject to the inherent methodological limitations. In this work, an alternative approach using Process Graph (P-graph) is developed, based on the source-sink matching problem being treated as a special Process Network Synthesis (PNS) problem. A case study is solved to illustrate the P-graph approach. In particular, optimal and near-optimal solutions are generated for the problem, which in real applications presents improved flexibility for purposes of practical decision support.
url https://www.cetjournal.it/index.php/cet/article/view/437
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