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[Study of Peak Carbon Emission of a City in Yangtze River Delta Based on LEAP Model].
Yang, Feng; Zhang, Gui-Chi; Sun, Ji; Xie, Fang-Jian; Chuai, Xiao-Wei; Sun, Rui-Ling.
Afiliação
  • Yang F; Nanjing Institute of Ecological and Environmental Protection Sciences, Nanjing 210019, China.
  • Zhang GC; Nanjing Institute of Ecological and Environmental Protection Sciences, Nanjing 210019, China.
  • Sun J; Guoxin International Engineering Consulting Group Co., Ltd., Nanjing 210019, China.
  • Xie FJ; Nanjing Institute of Ecological and Environmental Protection Sciences, Nanjing 210019, China.
  • Chuai XW; School of Geography and Ocean Sciences, Nanjing University, Nanjing 210023, China.
  • Sun RL; Nanjing Institute of Ecological and Environmental Protection Sciences, Nanjing 210019, China.
Huan Jing Ke Xue ; 45(1): 104-114, 2024 Jan 08.
Article em Zh | MEDLINE | ID: mdl-38216462
ABSTRACT
Based on the LEAP model framework, a LEAP-X sub-sector calculation model suitable for X City was constructed in this study. Four scenarios including a baseline scenario, low-carbon scenario, enhanced low-carbon scenario, and peak in 2023 scenario were set up to predict and analyze the carbon emission situation. The calculation and analysis results showed that it could achieve the carbon peak before 2030 only under the enhanced low-carbon scenario and peak in 2023 scenario. The peak year of the enhanced low-carbon scenario was around 2025 with a peak carbon emission of approximately 170 million tons, but the peak time may actually be delayed. Industry was the largest sector of carbon emissions, and the petrochemical industry was the largest portion of industry, the proportion of which was always maintained at approximately 30% under different scenarios. However, the proportion of power generation and steel industry decreased annually, whereas the proportion of the net imported power gradually increased. Industrial structure optimization and energy structure adjustment were the main driving factors of carbon peak in X City. Carbon emissions per unit of GDP will fall by approximately 41% in 2030 compared with that in 2020 under the enhanced low-carbon scenario.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Huan Jing Ke Xue Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Huan Jing Ke Xue Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China
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