Hunting Hotspots - A framework to assess the effectiveness of using environmentally extended input-output models as a method to identify CO2-eq hotspots in the upstream supply chain of a company
(2023) In Master Thesis Series in Environmental Studies and Sustainability Science MESM02 20231LUCSUS (Lund University Centre for Sustainability Studies)
- Abstract
- Industry’s indirect upstream greenhouse gas (GHG) emissions contribute significantly to climate change. To identify and reduce them, some companies conduct a hotspot analysis using an environmentally extended input-output (EEIO) model (often utilizing EXIOBASE database). Despite the widespread use of EEIO models to identify hotspots in industry, their effectiveness in estimating GHG emissions has not yet been investigated. Therefore, this thesis explores what effectiveness constitutes in this context and compares the strengths and weaknesses of EEIO (and EXIOBASE) with alternative methods, such as using supplier-specific, average-data and hybrid methods (and other common EEIO databases: Eora, GTAP, WIOD). Using a mixed methods model of... (More)
- Industry’s indirect upstream greenhouse gas (GHG) emissions contribute significantly to climate change. To identify and reduce them, some companies conduct a hotspot analysis using an environmentally extended input-output (EEIO) model (often utilizing EXIOBASE database). Despite the widespread use of EEIO models to identify hotspots in industry, their effectiveness in estimating GHG emissions has not yet been investigated. Therefore, this thesis explores what effectiveness constitutes in this context and compares the strengths and weaknesses of EEIO (and EXIOBASE) with alternative methods, such as using supplier-specific, average-data and hybrid methods (and other common EEIO databases: Eora, GTAP, WIOD). Using a mixed methods model of literature research, systematized literature review, and expert interviews, the results lead to an effectiveness framework with three dimensions and a precondition to determine its applicability. Finally, practical implications provide guidance for companies on how to apply it to positively contribute to carbon management and combating climate change. (Less)
- Abstract (German)
- Die indirekten vorgelagerten Treibhausgasemissionen der Industrie tragen erheblich zum Klimawandel bei. Um diese zu ermitteln und zu reduzieren, führen einige Unternehmen eine Hotspot-Analyse unter Verwendung eines umweltbezogenen erweiterten Input-Output-Modells (EEIO) durch (häufig unter Verwendung der Datenbank EXIOBASE). Obwohl EEIO-Modelle zur Identifizierung von Hotspots in der Industrie weit verbreitet sind, wurde ihre Effektivität bei der Schätzung von Treibhausgasemissionen noch nicht untersucht. Daher wird in dieser Arbeit untersucht, was Effektivität in diesem Zusammenhang bedeutet, und es werden die Stärken und Schwächen von EEIO (und EXIOBASE) mit alternativen Methoden verglichen, wie z. B. der Verwendung von... (More)
- Die indirekten vorgelagerten Treibhausgasemissionen der Industrie tragen erheblich zum Klimawandel bei. Um diese zu ermitteln und zu reduzieren, führen einige Unternehmen eine Hotspot-Analyse unter Verwendung eines umweltbezogenen erweiterten Input-Output-Modells (EEIO) durch (häufig unter Verwendung der Datenbank EXIOBASE). Obwohl EEIO-Modelle zur Identifizierung von Hotspots in der Industrie weit verbreitet sind, wurde ihre Effektivität bei der Schätzung von Treibhausgasemissionen noch nicht untersucht. Daher wird in dieser Arbeit untersucht, was Effektivität in diesem Zusammenhang bedeutet, und es werden die Stärken und Schwächen von EEIO (und EXIOBASE) mit alternativen Methoden verglichen, wie z. B. der Verwendung von anbieterspezifischen, durchschnittlichen Daten und hybriden Methoden (und andere gängige EEIO-Datenbanken: Eora, GTAP, WIOD). Unter Verwendung eines gemischten Methodenmodells aus Literaturrecherche, systematischem Literaturüberblick und Experteninterviews führen die Ergebnisse zu einem Effektivitätsrahmen mit drei Dimensionen und einer Voraussetzung zur Bestimmung seiner Anwendbarkeit. Schließlich bieten praktische Implikationen eine Gebrauchsanweisung für Unternehmen, wie sie ihn anwenden können, um einen positiven Beitrag zum Kohlenstoffmanagement und zur Bekämpfung des Klimawandels zu leisten. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9120894
- author
- Bauer, Elisa Anni LU
- supervisor
-
- Murray Scown LU
- organization
- course
- MESM02 20231
- year
- 2023
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- GHG emissions, Effectiveness, Hotspot analysis, Environmentally Extended Input-Output, Sustainability Science
- publication/series
- Master Thesis Series in Environmental Studies and Sustainability Science
- report number
- 2023:028
- language
- English
- id
- 9120894
- date added to LUP
- 2023-06-12 08:11:13
- date last changed
- 2023-06-12 08:11:13
@misc{9120894, abstract = {{Industry’s indirect upstream greenhouse gas (GHG) emissions contribute significantly to climate change. To identify and reduce them, some companies conduct a hotspot analysis using an environmentally extended input-output (EEIO) model (often utilizing EXIOBASE database). Despite the widespread use of EEIO models to identify hotspots in industry, their effectiveness in estimating GHG emissions has not yet been investigated. Therefore, this thesis explores what effectiveness constitutes in this context and compares the strengths and weaknesses of EEIO (and EXIOBASE) with alternative methods, such as using supplier-specific, average-data and hybrid methods (and other common EEIO databases: Eora, GTAP, WIOD). Using a mixed methods model of literature research, systematized literature review, and expert interviews, the results lead to an effectiveness framework with three dimensions and a precondition to determine its applicability. Finally, practical implications provide guidance for companies on how to apply it to positively contribute to carbon management and combating climate change.}}, author = {{Bauer, Elisa Anni}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master Thesis Series in Environmental Studies and Sustainability Science}}, title = {{Hunting Hotspots - A framework to assess the effectiveness of using environmentally extended input-output models as a method to identify CO2-eq hotspots in the upstream supply chain of a company}}, year = {{2023}}, }