A bottom-up approach to improve local-scale understanding and decision making in responding to climate change

A. Jakeman, S. El-Sawah, J. Guillaume, Tatiana Filatova

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

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Abstract

To forecast the energy consumtion and carbon emissions in China, this paper established an input-output model with 17 sectors on the macroeconomy level, and an agentbased model on the microeconomy level simulating firms’ innovations in each sector. Results show that due to the uncertainty of innovation, the peak years of energy and emission are also uncertain. The energy peak year will subject to a normal distribution from 2025 to 2036; while the distribution of emission peak year is also identified as a normal distribution from 2024 to 2033. The year with the maximum probability for energy peak will be 2031 with the probability of 23.57%; and 2029 will be the year with the maximum probality 33.51% for emission peak. Taking the average of 50 simulations, it is indicated that the energy peak will be 5146Mtce in 2029 with a decline by 2050 to 4086Mtce, and the emission peak will be 2.7GtC in 2029 with a decline by 2050 to 2.05GtC.
Original languageEnglish
Title of host publicationOur common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France
EditorsChristopher Field, Jean Jouzel, Hervé Le Treut
Place of PublicationParis, France
Pages560-
Publication statusPublished - 7 Jul 2015

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Normal distribution
Climate change
Innovation
Decision making
Carbon

Keywords

  • METIS-311700
  • IR-97163

Cite this

Jakeman, A., El-Sawah, S., Guillaume, J., & Filatova, T. (2015). A bottom-up approach to improve local-scale understanding and decision making in responding to climate change. In C. Field, J. Jouzel, & H. Le Treut (Eds.), Our common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France (pp. 560-). Paris, France.
Jakeman, A. ; El-Sawah, S. ; Guillaume, J. ; Filatova, Tatiana. / A bottom-up approach to improve local-scale understanding and decision making in responding to climate change. Our common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France. editor / Christopher Field ; Jean Jouzel ; Hervé Le Treut. Paris, France, 2015. pp. 560-
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title = "A bottom-up approach to improve local-scale understanding and decision making in responding to climate change",
abstract = "To forecast the energy consumtion and carbon emissions in China, this paper established an input-output model with 17 sectors on the macroeconomy level, and an agentbased model on the microeconomy level simulating firms’ innovations in each sector. Results show that due to the uncertainty of innovation, the peak years of energy and emission are also uncertain. The energy peak year will subject to a normal distribution from 2025 to 2036; while the distribution of emission peak year is also identified as a normal distribution from 2024 to 2033. The year with the maximum probability for energy peak will be 2031 with the probability of 23.57{\%}; and 2029 will be the year with the maximum probality 33.51{\%} for emission peak. Taking the average of 50 simulations, it is indicated that the energy peak will be 5146Mtce in 2029 with a decline by 2050 to 4086Mtce, and the emission peak will be 2.7GtC in 2029 with a decline by 2050 to 2.05GtC.",
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Jakeman, A, El-Sawah, S, Guillaume, J & Filatova, T 2015, A bottom-up approach to improve local-scale understanding and decision making in responding to climate change. in C Field, J Jouzel & H Le Treut (eds), Our common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France. Paris, France, pp. 560-.

A bottom-up approach to improve local-scale understanding and decision making in responding to climate change. / Jakeman, A.; El-Sawah, S.; Guillaume, J.; Filatova, Tatiana.

Our common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France. ed. / Christopher Field; Jean Jouzel; Hervé Le Treut. Paris, France, 2015. p. 560-.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

TY - GEN

T1 - A bottom-up approach to improve local-scale understanding and decision making in responding to climate change

AU - Jakeman, A.

AU - El-Sawah, S.

AU - Guillaume, J.

AU - Filatova, Tatiana

N1 - P-3322-06

PY - 2015/7/7

Y1 - 2015/7/7

N2 - To forecast the energy consumtion and carbon emissions in China, this paper established an input-output model with 17 sectors on the macroeconomy level, and an agentbased model on the microeconomy level simulating firms’ innovations in each sector. Results show that due to the uncertainty of innovation, the peak years of energy and emission are also uncertain. The energy peak year will subject to a normal distribution from 2025 to 2036; while the distribution of emission peak year is also identified as a normal distribution from 2024 to 2033. The year with the maximum probability for energy peak will be 2031 with the probability of 23.57%; and 2029 will be the year with the maximum probality 33.51% for emission peak. Taking the average of 50 simulations, it is indicated that the energy peak will be 5146Mtce in 2029 with a decline by 2050 to 4086Mtce, and the emission peak will be 2.7GtC in 2029 with a decline by 2050 to 2.05GtC.

AB - To forecast the energy consumtion and carbon emissions in China, this paper established an input-output model with 17 sectors on the macroeconomy level, and an agentbased model on the microeconomy level simulating firms’ innovations in each sector. Results show that due to the uncertainty of innovation, the peak years of energy and emission are also uncertain. The energy peak year will subject to a normal distribution from 2025 to 2036; while the distribution of emission peak year is also identified as a normal distribution from 2024 to 2033. The year with the maximum probability for energy peak will be 2031 with the probability of 23.57%; and 2029 will be the year with the maximum probality 33.51% for emission peak. Taking the average of 50 simulations, it is indicated that the energy peak will be 5146Mtce in 2029 with a decline by 2050 to 4086Mtce, and the emission peak will be 2.7GtC in 2029 with a decline by 2050 to 2.05GtC.

KW - METIS-311700

KW - IR-97163

M3 - Conference contribution

SP - 560-

BT - Our common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France

A2 - Field, Christopher

A2 - Jouzel, Jean

A2 - Le Treut, Hervé

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Jakeman A, El-Sawah S, Guillaume J, Filatova T. A bottom-up approach to improve local-scale understanding and decision making in responding to climate change. In Field C, Jouzel J, Le Treut H, editors, Our common future under climate change: International Scienfitic Conference, 7-10 July 2015, Paris, France. Paris, France. 2015. p. 560-