4.7 Article

Scenario analysis of urban GHG peak and mitigation co-benefits: A case study of Xiamen City, China

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 171, Issue -, Pages 972-983

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.10.040

Keywords

Urban GHG emissions; CO2 peak; Scenario analysis; Co-benefits; LEAP

Funding

  1. National Natural Science Foundation of China [71573242, 71273252, 41371392]
  2. Natural Science Foundation of Fujian Province [2017J01468]
  3. Fujian Science and Technology Support Program for Provincial Universities [JK2015025]

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Because cities are key to Chinese GHG management, a LEAP-based model integrating energy-related and non-energy related sectors was developed to study urban CO2 and GHG peak volume and time. Using Xiamen City as a case study, the future GHG emissions trends from 2015 to 2050 was simulated under three scenarios, namely a business-as-usual scenario (BAU), an emission-controlled scenario (EC), and a reinforced mitigation scenario (RM). Results show that Xiamen City will peak its total GHG emissions in 2039 under EC scenario and 2034 under RM scenario, while there might not be an obvious GHG peak under BAU scenario before 2050. Total CO2 emissions will peak at the same year as the GHG emissions peak year under EC and RM scenarios. Our research also indicates that population and economic growth has a significant impact on the city's CO2 and GHG peak, and Xiamen might reach the CO2 peak later than the national goal due to clean energy supply limitations and continued rapid growth. Lack of favorable conditions for large-scale renewable energy development and relatively high price of natural gas are the main obstacles for CO2 and GHG reduction in Xiamen City. In the future, greater attention on multi-sector reduction strategies is needed, including transforming industrial structure, expanding public transport while limiting private car growth, controlling per capita residential living area, improving public building energy efficiency, and reducing and reusing waste. (C) 2017 Elsevier Ltd. All rights reserved.

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