Abstract
<p indent=0mm>Cities account for more than 70% of global carbon emissions and play an important role in mitigating climate change and achieving carbon peak and carbon neutrality. As the Paris Agreement emphasizes the need to reach global peaking of greenhouse gas emissions as soon as possible, it is significant to predict carbon emissions at the city level. However, the current COVID-19 pandemic has dramatically impacted global socioeconomic development and carbon emissions, downplaying the reference value for most urban carbon emission prediction models. In fact, existing studies on urban carbon emission prediction have also suffered from some shortcomings, such as unclear analyses of the impact of the pandemic, single scenario prediction, unified setting of growth rates, and failure to provide decision support for the government’s carbon peak work. Therefore, a multi-scenario study on urban carbon emission prediction and carbon peak in the post-pandemic period would provide local governments with scientific data to make their carbon peak action plan. To that end, we set five-carbon emission scenarios: bussiness as usual (BAU), high emissions (HE), extremely high emissions (EHE), low emissions (LE) and extremely low emissions (ELE). Based on the Monte Carlo method, we adjust the probabilities of different periods and different carbon emission scenarios to simulate uncertain evolution of carbon emissions as well as carbon emission reduction. Combining with multi-scenario analyses with the Mann-Kendall trend test and Theil Sen’s trend slope estimation method, we predict carbon emissions of the Pearl River Delta Urban Agglomeration (PRD) from 2021 to 2035 and analyze the evolution path of PRD’s carbon emissions as well as its potential for carbon peak and carbon emission reduction from 2006 to 2035. Discussions are made on the possibility of achieving conditional areas’ carbon peak goal in 2025 in Guangdong and China’s carbon peak goal in 2030. We find that: (1) Carbon emissions of PRD increased rapidly from 2006 to 2016. Dynamic simulation shows that carbon emissions a significant peak in 2020 and decrease to 248.85 M~270.06 Mt in 2035. Carbon intensity decreases by 84.18%–85.21% from 2006 to 2035. Based on the emission reduction of the BAU scenario, the cumulative carbon emission reduction potential of the LE scenario and ELE scenario is as high as 304.86 M and 587.22 Mt from 2021 to 2035. Carbon emission reduction potential based on dynamic simulation of random combination scenario is between −81.68 and 128.25 Mt, with a probability of 67.65% to achieve further emission reduction. The probability of reducing 27.44 Mt carbon emissions is the largest. (2) Shenzhen, Zhuhai, Huizhou and Dongguan are four cities that show an inverted “U” shaped evolution path to achieve carbon peak. All of them reach the carbon peak no later than 2020. From 2006 to 2035, especially after the carbon peak, carbon emissions of these cities will decrease significantly. Their carbon emissions will reduce by 14.15 M–15.40 Mt, 9.17 M–9.94 Mt, 24.07 M–26.08 Mt and 22.36 M–24.24 Mt in 2035, respectively. The cumulative carbon emission reduction potential from 2021 to 2035 is −7.99 M–8.69 Mt, −3.48 M–4.87 Mt, −5.97 M–15.39 Mt and −8.77 M–12.62 Mt, respectively. However, being earlier to reach a carbon peak reduces their carbon emission reduction potential from 2021 to 2035. (3) Guangzhou, Foshan, Zhongshan, Jiangmen and Zhaoqing are five cities that could potentially reach carbon peaks but with divergent evolution paths. Some scenarios are at risk of not reaching a carbon peak. The possibility for Guangzhou, Foshan and Zhongshan to achieve the carbon peak target of conditional areas in Guangdong Province in 2025 is more than 96.01%, while that for Jiangmen and Zhaoqing is less than 20.08%. Moreover, there is a possibility of 2.04% for Jiangmen and Zhaoqing not to reach a carbon peak. In 2035, the emission reduction of the five cities will be 56.90 M–61.87 Mt, 44.35 M–48.16 Mt, 23.92 M–25.91 Mt, 33.78 M–36.58 Mt and 20.15 M–21.88 Mt, respectively. The cumulative carbon emission reduction potential of these cities from 2021 to 2035 is significant, which is −23.75M–26.60 Mt, −17.51 M–<sc>22.17 Mt,</sc> −6.64 M–12.19 Mt, −7.57 M–17.82 Mt and −3.86 M–11.79 Mt, respectively. (4) Being earlier to reach a carbon peak is conducive for cities to reduce carbon emissions. The curve of cumulative carbon emission reduction potential shows that the marginal potential of carbon emission reduction increases with time. So early adoption of emission reduction measures and early realization of carbon peak will promote carbon emission reduction. When making action plans for carbon peak, we should prevent cities from reaching false carbon peak during the platform period, pay attention to the demonstration and acceleration effect of carbon peak cities with relatively high carbon emissions, and explore the carbon emission reduction potential of cities that have difficulties in reaching carbon peak by optimizing their energy structure and utilization efficiency.
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