Insights from adding transportation sector detail into an economy-wide model: The case of the ADAGE CGE model

Cai, Yan; Woollacott, Jared; Beach, Robert; Rafelski, Lauren Elmegreen; Ramig, Christopher; Shelby, Michael

doi:10.1016/j.eneco.2023.106710

Cited by 4 publications

(2 citation statements)

References 42 publications

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“…The "top-down" macro forecasting approach analyzes the impact of changes in population, economy, and other social aspects on regional carbon emissions, though offering limited detail on individual energy consumption sectors and energy varieties. Representative models include the computable general equilibrium (CGE) [26,27], stochastic impacts by regression on population affluence and technology (STIRPAT) [28,29], and the logarithmic mean divisia index (LMDI) models [30][31][32]. Usman et al [33] applied the STIRPAT model to explore the correlation between nuclear energy and the ecological footprint.…”

Section: Introductionmentioning

confidence: 99%

Carbon Emission Prediction and the Reduction Pathway in Industrial Parks: A Scenario Analysis Based on the Integration of the LEAP Model with LMDI Decomposition

Feng,

Xu,

Gao

et al. 2023

Energies

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Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the “top-down” and “bottom-up” prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park’s development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks.

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Section: Introductionmentioning

confidence: 99%

Carbon Emission Prediction and the Reduction Pathway in Industrial Parks: A Scenario Analysis Based on the Integration of the LEAP Model with LMDI Decomposition

Feng,

Xu,

Gao

et al. 2023

Energies

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show abstract

“…To conduct our analysis, we will employ a computable general equilibrium (CGE) model, which is a widely-used method for evaluating the economic impacts of policy changes at both micro and macro levels [30][31][32]. What sets the CGE model apart from other approaches is its ability to capture the complex interactions and feedback effects between various economic sectors, including energy markets, and measure the distributional impacts across different income groups [33,34].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Carbon Emission Trading on Renewable Energy: A Comparative Analysis Based on the CGE Model

Huang,

Du,

Jin

et al. 2023

Sustainability

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This study examines the effects of carbon emission trading on renewable energy consumption in China. The research applies the CEEEA2.0 model to simulate the economic, energy, and environmental impacts of carbon trading from 2018 to 2030. The CEEEA2.0 model is a recursive dynamic computable general equilibrium model that incorporates multiple households, sectors, and an energy and environment module. Four scenarios are considered: the Business as Usual (BaU) scenario, the Emission Trading Scheme (ETS)-benchmark scenario, and the ETS-strengthened and ETS-enhanced scenarios. The findings reveal that carbon emission trading positively influences electricity consumption, resulting in a higher preference for renewable energy due to reduced price disparities between renewable sources and fossil fuels. Consequently, electricity generation from renewable sources increases in all scenarios compared to the BaU scenario. However, the share of renewable energy is not substantially affected by carbon emission trading due to the complex interplay of factors, including substitution and income effects. The study further highlights that carbon trading significantly reduces coal usage and partially increases the overall proportion of renewable energy. These results underscore the significance of establishing ambitious carbon reduction targets and continual efforts to shift towards clean energy sources.

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A penny saved is a penny earned: Exploring the synergistic effect between carbon trading and energy carbon-content tax

Wen,

Jia

2023

Journal of Cleaner Production

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Insights from adding transportation sector detail into an economy-wide model: The case of the ADAGE CGE model

Cited by 4 publications

References 42 publications

Carbon Emission Prediction and the Reduction Pathway in Industrial Parks: A Scenario Analysis Based on the Integration of the LEAP Model with LMDI Decomposition

Carbon Emission Prediction and the Reduction Pathway in Industrial Parks: A Scenario Analysis Based on the Integration of the LEAP Model with LMDI Decomposition

The Impact of Carbon Emission Trading on Renewable Energy: A Comparative Analysis Based on the CGE Model

A penny saved is a penny earned: Exploring the synergistic effect between carbon trading and energy carbon-content tax

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