Global Energy and Climate Model: Scenario analysis of future energy trends

The IEA's Global Energy and Climate Model (GEC Model) provides comprehensive projections for energy supply, demand, and emissions, focusing on achieving net zero CO2 emissions by 2050 through various scenarios.

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Quick Facts
Report location: source PDF
Language: English
Publisher: International Energy Agency
Time horizon: 2050
Geographic scope: Global

Methods

The research method involves a hybrid modeling approach that combines detailed bottom-up and top-down analyses. The GEC Model integrates various energy sectors, utilizing extensive data on energy supply, demand, and emissions. It employs econometric models to project future trends and assess the impacts of different scenarios on energy systems.

(Generated with the help of GPT-4)

Key Insights

The International Energy Agency (IEA) has developed the Global Energy and Climate (GEC) Model to analyze energy systems and project future energy trends. This model integrates various energy sectors, including oil, gas, coal, and renewables, and assesses the impacts of policies and technologies on energy demand, supply, and emissions. The GEC Model employs a hybrid approach, combining elements from previous models to create detailed sector-by-sector and region-by-region scenarios. It explores three main scenarios: the Stated Policies Scenario (STEPS), the Announced Pledges Scenario (APS), and the Net Zero Emissions by 2050 Scenario (NZE). Each scenario reflects different assumptions about policy implementation and technological advancements. The model emphasizes the importance of government actions in shaping energy futures and includes assessments of energy access, employment, and investment needs. The GEC Model is designed to provide insights into the pathways necessary for achieving climate goals while ensuring energy security and affordability. It covers 27 regions globally and utilizes extensive data from various sources, including the IEA's own databases and external collaborations.

(Generated with the help of GPT-4)

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Last modified: 2024/11/09 16:53 by davidpjonker