Energy, economy, and emissions: A non-linear state space approach to projections
arxiv(2023)
摘要
We propose a non-linear state-space model to examine the relationship between
CO_2 emissions, energy sources, and macroeconomic activity, using data from
1971 to 2019. CO_2 emissions are modeled as a weighted sum of fossil fuel
use, with emission conversion factors that evolve over time to reflect
technological changes. GDP is expressed as the outcome of linearly increasing
energy efficiency and total energy consumption. The model is estimated using
CO_2 data from the Global Carbon Budget, GDP statistics from the World Bank,
and energy data from the International Energy Agency (IEA). Projections for
CO_2 emissions and GDP from 2020 to 2100 from the model are based on energy
scenarios from the Shared Socioeconomic Pathways (SSP) and the IEA's Net Zero
roadmap. Emissions projections from the model are consistent with these
scenarios but predict lower GDP growth. An alternative model version, assuming
exponential energy efficiency improvement, produces GDP growth rates more in
line with the benchmark projections. Our results imply that if internationally
agreed net-zero objectives are to be fulfilled and economic growth is to follow
SSP or IEA scenarios, then drastic changes in energy efficiency, not consistent
with historical trends, are needed.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要