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Uncertainty in an emissions-constrained world

Author

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  • Matthias Jonas
  • Gregg Marland
  • Volker Krey
  • Fabian Wagner
  • Zbigniew Nahorski

Abstract

Our study focuses on uncertainty in greenhouse gas (GHG) emissions from anthropogenic sources, including land use and land-use change activities. We aim to understand the relevance of diagnostic (retrospective) and prognostic (prospective) uncertainty in an emissions-temperature setting that seeks to constrain global warming and to link uncertainty consistently across temporal scales. We discuss diagnostic and prognostic uncertainty in a systems setting that allows any country to understand its national and near-term mitigation and adaptation efforts in a globally consistent and long-term context. Cumulative emissions are not only constrained and globally binding but exhibit quantitative uncertainty; and whether or not compliance with an agreed temperature target will be achieved is also uncertain. To facilitate discussions, we focus on two countries, the USA and China. While our study addresses whether or not future increase in global temperature can be kept below 2, 3, or 4 °C targets, its primary aim is to use those targets to demonstrate the relevance of both diagnostic and prognostic uncertainty. We show how to combine diagnostic and prognostic uncertainty to take more educated (precautionary) decisions for reducing emissions toward an agreed temperature target; and how to perceive combined diagnostic and prognostic uncertainty-related risk. Diagnostic uncertainty is the uncertainty contained in inventoried emission estimates and relates to the risk that true GHG emissions are greater than inventoried emission estimates reported in a specified year; prognostic uncertainty refers to cumulative emissions between a start year and a future target year, and relates to the risk that an agreed temperature target is exceeded. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Matthias Jonas & Gregg Marland & Volker Krey & Fabian Wagner & Zbigniew Nahorski, 2014. "Uncertainty in an emissions-constrained world," Climatic Change, Springer, vol. 124(3), pages 459-476, June.
  • Handle: RePEc:spr:climat:v:124:y:2014:i:3:p:459-476
    DOI: 10.1007/s10584-014-1103-6
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    References listed on IDEAS

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    1. David G. Victor, 2009. "Global warming: why the 2 °C goal is a political delusion," Nature, Nature, vol. 459(7249), pages 909-909, June.
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    Cited by:

    1. Khrystyna Boychuk & Rostyslav Bun, 2014. "Regional spatial inventories (cadastres) of GHG emissions in the Energy sector: Accounting for uncertainty," Climatic Change, Springer, vol. 124(3), pages 561-574, June.
    2. Shan, Yuli & Liu, Zhu & Guan, Dabo, 2016. "CO2 emissions from China’s lime industry," Applied Energy, Elsevier, vol. 166(C), pages 245-252.
    3. Emily McGlynn & Serena Li & Michael Berger & Meredith Amend & Kandice Harper, 2022. "Addressing uncertainty and bias in land use, land use change, and forestry greenhouse gas inventories," Climatic Change, Springer, vol. 170(1), pages 1-25, January.
    4. Jörg Verstraete, 2019. "Solving the general map overlay problem using a fuzzy inference system designed for spatial disaggregation," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 1101-1122, August.
    5. Liu, Xiaoyu & Duan, Zhiyuan & Shan, Yuli & Duan, Haiyan & Wang, Shuo & Song, Junnian & Wang, Xian'en, 2019. "Low-carbon developments in Northeast China: Evidence from cities," Applied Energy, Elsevier, vol. 236(C), pages 1019-1033.
    6. Tomohiro Oda & Rostyslav Bun & Vitaliy Kinakh & Petro Topylko & Mariia Halushchak & Gregg Marland & Thomas Lauvaux & Matthias Jonas & Shamil Maksyutov & Zbigniew Nahorski & Myroslava Lesiv & Olha Dany, 2019. "Errors and uncertainties in a gridded carbon dioxide emissions inventory," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 1007-1050, August.

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