Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 831, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2022.154909
Keywords
China's total carbon dioxide emissions; Forest carbon sinks; Carbon neutrality; Extreme learning machine; Aquila optimizer
Categories
Funding
- Hebei Province Science and Technology Soft Plan Project [21554001D]
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In the context of global climate governance, China, as the largest carbon emitter, carries significant responsibility for reducing emissions. Research shows that China has the potential to achieve net-zero carbon dioxide emissions by 2060 through reducing emissions and increasing forest carbon sinks.
In the context of global climate governance, as the biggest carbon emitter, China bears momentous responsibility for mitigating emissions. Especially after the carbon neutrality target is proposed, it is urgent for China to seek a feasible pathway to achieve net-zero carbon dioxide (CO2) emissions by 2060. With the aims of exploring the net-zero emission pathways, an integrated prediction model incorporating the extreme learning machine (ELM) network, the Aquila optimizer (AO) technique, and the Elastic Net (EN) regression method is constructed. Then the prediction model is employed to project CO2 emissions and forest carbon sinks during 2021-2060 under the nine designed scenarios. The simulation results reveal that China has the potential to achieve net-zero CO2 emissions by 2060 under the combined effects of reducing emissions and increasing forest carbon sinks. Specifically, the total CO2 emissions will be peaked at 11441 million tons CO2 (MtCO(2)) in 2029. The post-peak carbon reduction rate should be 8% per year, and the average annual forest carbon sink is required to be 209.45 TgC/year during 2021-2060. In addition, in accordance with the optimal carbon neutrality pathway, the GDP per capita growth rate should be maintained at 5.5% during the period of 2021-2030, China's urbanization rate should be increased to 72% in 2030, and the total energy consumption should be limited to a peak value of 6000 million tons of coal equivalent (Mtce) in 2030.
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