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Mitigation and Adaptation Strategies for Global Change

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01-01-2022 | Original article

The impact of climate change on global energy use

Authors: Hongliang Zhang, Jianhong E. Mu, Bruce A. McCarl, Jialing Yu

Published in: Mitigation and Adaptation Strategies for Global Change | Issue 1/2022

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Abstract

This paper presents a global analysis of the link between annual total energy use and temperature. A statistical model is used to estimate this link based on a panel dataset from 147 countries over the years 1990–2015. Results show that rich and poor countries exhibit differential response functions to temperature changes for annual total energy use. Unmitigated climate change by 2095 is projected to increase global total energy use on average by 24.0% relative to a baseline coupled with income and population growth without climate change. Poor countries are projected to face a larger increase in their energy use than rich countries over the years 2016–2095 and thus the projected impacts of future global warming on total energy use vary spatially—low-income countries will face significant increases, while cooler countries will experience reductions. Policy-makers need to incorporate socioeconomic factors and climate uncertainty into the projection of future climate change impacts on global energy use.

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The 21 global climate models we used in this study are ACCESS1-0, bcc-csm1-1, BNU-ESM, CanESM2, CCSM4, CESM1-BGC, CNRM-CM5, CSIRO-Mk3-6–0, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, inmcm4, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC-ESM-CHEM, MIROC-ESM, MIROC5, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, and NorESM1-M.

Energy use data in our sample is from 1990 to 2015. We choose the year 2014 because energy use data in 2015 are missing (unavailable) for many countries.

Specifically, we cluster observations at the country level, so the resampled observations are from the same countries in different years, accounting for autocorrelation over time.

To evaluate the contributions of uncertainty factors, we used the variance-decomposition method (Wallach et al. 2015) to construct the share of total variation associated with each factor as \({V}_{i}=\frac{Var[E(Y|{X}_{i}]}{Var(Y)}\), where V_i is the percent of total variation from the ith factor, Y is global energy use, X_i is the ith uncertainty factor, E(∙) is the expectation operator, and Var(∙) is the total variance.

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Title: The impact of climate change on global energy use
Authors: Hongliang Zhang
Jianhong E. Mu
Bruce A. McCarl
Jialing Yu
Publication date: 01-01-2022
Publisher: Springer Netherlands
Published in: Mitigation and Adaptation Strategies for Global Change / Issue 1/2022
Print ISSN: 1381-2386
Electronic ISSN: 1573-1596
DOI: https://doi.org/10.1007/s11027-021-09986-x

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