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Analysis of carbon emission drivers and peak carbon forecasts for island economies

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  • Wang, Geng
  • Feng, Yan

Abstract

Sea islands are an essential support for expanding the blue economic space, and the study of the carbon emissions of Changhai County's island economies and their carbon peaking time is of great significance for achieving the goal of building an ecological low-carbon demonstration island with northern characteristics in Changhai County. In this study, the Logarithmic Mean Divisia Index (LMDI) method was used to explore the three main drivers affecting the carbon emissions of the island economies in Changhai County. The carbon emissions of Changhai County in 2012–2019 were estimated through the system dynamics model. The low-carbon development path and possible carbon peak time of Changhai County in 2020–2035 were predicted. The results show that: ①The urban system is the first positive driver of carbon emissions, followed by the residential system, and finally, the fishery system, the energy structure effect is the main positive driving effect affecting carbon emissions, and the population effect always shows a negative inhibitory impact on carbon emissions. ②The activities on the islands of Changhai County in 2012–2019 cumulatively produced 167.53 × 104 t of carbon emissions, 46.83 × 104 t of carbon sinks, and their net carbon emissions were 120.69 × 104 t. The results of the future scenario projections show that neither non-intervention nor a single policy of only adjusting land use and transport can achieve minor carbon emissions and that the best path for future low-carbon development in Changhai County is to develop all kinds of activities in a low-carbon (L) mode. ④Among the future forecast scenarios, Scenario 5 is an ideal model for the fastest way to achieve carbon peak, which generates 318.39 × 104 t of carbon emissions, and the cumulative emission reduction reaches 26.37 × 104 t.

Suggested Citation

  • Wang, Geng & Feng, Yan, 2024. "Analysis of carbon emission drivers and peak carbon forecasts for island economies," Ecological Modelling, Elsevier, vol. 489(C).
    • Handle: RePEc:eee:ecomod:v:489:y:2024:i:c:s0304380023003411
    DOI: 10.1016/j.ecolmodel.2023.110611
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