Meeting emission targets under uncertainty

The case of Finnish non-emission-trading sector

A. Hast (Corresponding Author), Tommi Ekholm, Ilkka Savolainen

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)

Abstract

The European Union (EU) has set a target to reduce its greenhouse gas (GHG) emissions at least 10 % below the 2005 levels by 2020 in the non-Emission Trading Sector (non-ETS). As part of this, each Member State has a binding national emission limitation target for the non-ETS sector. Finland’s target, examined as a case study in this paper, is to reduce emissions at least 16 % below 2005 levels by 2020. The objective of this study is to find cost optimal mitigation portfolios that meet Finland’s reduction target and to analyze the risks of not attaining the emission target or exceeding the assumed costs. The question was addressed with a stochastic optimization model, Stochastic Optimization of non-ETS Emissions (SONETS) selecting separate mitigation measures that meet the target on expectation. The results show that optimal portfolios include relatively high uncertainty both in costs and achieved reductions. The prices of crude oil and diesel, and the abatement cost of reducing hydrofluorocarbon (HFC) emissions seem to account for the majority of uncertainty regarding total costs. The baseline predictions for various non-ETS subsectors (such as transport and agriculture) were found to have the greatest contribution to the uncertainty of attaining emission target. The results also show that some abatement actions are chosen in nearly all efficient portfolios, while other actions are seldom chosen. For example replacing oil burners in the end of technical life time or recovery of methane (CH4) from waste are often chosen whereas ban of landfilling of organic waste is chosen extremely seldom. It also seems that the results are somewhat sensitive to the inclusion or exclusion of the interdependencies of mitigation measures.
Original languageEnglish
Pages (from-to)637-658
JournalMitigation and Adaptation Strategies for Global Change
Volume18
Issue number5
DOIs
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

Fingerprint

cost
hydrofluorocarbon
abatement cost
diesel
crude oil
European Union
greenhouse gas
mitigation
methane
agriculture
oil
prediction
mitigation measure
organic waste
price

Keywords

  • Cost-efficiency
  • GHG emission reduction measure
  • non-ETS sector
  • portfolio
  • risk
  • Stochastic optimization

Cite this

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title = "Meeting emission targets under uncertainty: The case of Finnish non-emission-trading sector",
abstract = "The European Union (EU) has set a target to reduce its greenhouse gas (GHG) emissions at least 10 {\%} below the 2005 levels by 2020 in the non-Emission Trading Sector (non-ETS). As part of this, each Member State has a binding national emission limitation target for the non-ETS sector. Finland’s target, examined as a case study in this paper, is to reduce emissions at least 16 {\%} below 2005 levels by 2020. The objective of this study is to find cost optimal mitigation portfolios that meet Finland’s reduction target and to analyze the risks of not attaining the emission target or exceeding the assumed costs. The question was addressed with a stochastic optimization model, Stochastic Optimization of non-ETS Emissions (SONETS) selecting separate mitigation measures that meet the target on expectation. The results show that optimal portfolios include relatively high uncertainty both in costs and achieved reductions. The prices of crude oil and diesel, and the abatement cost of reducing hydrofluorocarbon (HFC) emissions seem to account for the majority of uncertainty regarding total costs. The baseline predictions for various non-ETS subsectors (such as transport and agriculture) were found to have the greatest contribution to the uncertainty of attaining emission target. The results also show that some abatement actions are chosen in nearly all efficient portfolios, while other actions are seldom chosen. For example replacing oil burners in the end of technical life time or recovery of methane (CH4) from waste are often chosen whereas ban of landfilling of organic waste is chosen extremely seldom. It also seems that the results are somewhat sensitive to the inclusion or exclusion of the interdependencies of mitigation measures.",
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Meeting emission targets under uncertainty : The case of Finnish non-emission-trading sector. / Hast, A. (Corresponding Author); Ekholm, Tommi; Savolainen, Ilkka.

In: Mitigation and Adaptation Strategies for Global Change, Vol. 18, No. 5, 2013, p. 637-658.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

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T2 - The case of Finnish non-emission-trading sector

AU - Hast, A.

AU - Ekholm, Tommi

AU - Savolainen, Ilkka

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N2 - The European Union (EU) has set a target to reduce its greenhouse gas (GHG) emissions at least 10 % below the 2005 levels by 2020 in the non-Emission Trading Sector (non-ETS). As part of this, each Member State has a binding national emission limitation target for the non-ETS sector. Finland’s target, examined as a case study in this paper, is to reduce emissions at least 16 % below 2005 levels by 2020. The objective of this study is to find cost optimal mitigation portfolios that meet Finland’s reduction target and to analyze the risks of not attaining the emission target or exceeding the assumed costs. The question was addressed with a stochastic optimization model, Stochastic Optimization of non-ETS Emissions (SONETS) selecting separate mitigation measures that meet the target on expectation. The results show that optimal portfolios include relatively high uncertainty both in costs and achieved reductions. The prices of crude oil and diesel, and the abatement cost of reducing hydrofluorocarbon (HFC) emissions seem to account for the majority of uncertainty regarding total costs. The baseline predictions for various non-ETS subsectors (such as transport and agriculture) were found to have the greatest contribution to the uncertainty of attaining emission target. The results also show that some abatement actions are chosen in nearly all efficient portfolios, while other actions are seldom chosen. For example replacing oil burners in the end of technical life time or recovery of methane (CH4) from waste are often chosen whereas ban of landfilling of organic waste is chosen extremely seldom. It also seems that the results are somewhat sensitive to the inclusion or exclusion of the interdependencies of mitigation measures.

AB - The European Union (EU) has set a target to reduce its greenhouse gas (GHG) emissions at least 10 % below the 2005 levels by 2020 in the non-Emission Trading Sector (non-ETS). As part of this, each Member State has a binding national emission limitation target for the non-ETS sector. Finland’s target, examined as a case study in this paper, is to reduce emissions at least 16 % below 2005 levels by 2020. The objective of this study is to find cost optimal mitigation portfolios that meet Finland’s reduction target and to analyze the risks of not attaining the emission target or exceeding the assumed costs. The question was addressed with a stochastic optimization model, Stochastic Optimization of non-ETS Emissions (SONETS) selecting separate mitigation measures that meet the target on expectation. The results show that optimal portfolios include relatively high uncertainty both in costs and achieved reductions. The prices of crude oil and diesel, and the abatement cost of reducing hydrofluorocarbon (HFC) emissions seem to account for the majority of uncertainty regarding total costs. The baseline predictions for various non-ETS subsectors (such as transport and agriculture) were found to have the greatest contribution to the uncertainty of attaining emission target. The results also show that some abatement actions are chosen in nearly all efficient portfolios, while other actions are seldom chosen. For example replacing oil burners in the end of technical life time or recovery of methane (CH4) from waste are often chosen whereas ban of landfilling of organic waste is chosen extremely seldom. It also seems that the results are somewhat sensitive to the inclusion or exclusion of the interdependencies of mitigation measures.

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JO - Mitigation and Adaptation Strategies for Global Change

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ER -