Greenhouse gases, especially carbon dioxide (CO2) emissions, are viewed as one of the core causes of climate change, and it has become one of the most important environmental problems in the world. This paper attempts to investigate the relation between CO2 emissions and economic growth, industry structure, urbanization, research and development (R&D) investment, actual use of foreign capital, and growth rate of energy consumption in China between 2000 and 2018. This study is important for China as it has pledged to peak its carbon dioxide emissions (CO2) by 2030 and achieve carbon neutrality by 2060. We apply a suite of machine learning algorithms on the training set of data, 2000–2015, and predict the levels of CO2 emissions for the testing set, 2016–2018. Employing rmse for model selection, results show that the nonlinear model of k-nearest neighbors (KNN) model performs the best among linear models, nonlinear models, ensemble models, and artificial neural networks for the present dataset. Using KNN model, sensitivity analysis of CO2 emissions around its centroid position was conducted. The findings indicate that not all provinces should develop its industrialization. Some provinces should stay at relatively mild industrialization stage while selected others should develop theirs as quickly as possible. It is because CO2 emissions will eventually decrease after saturation point. In terms of urbanization, there is an optimal range for a province. At the optimal range, the CO2 emissions would be at a minimum, and it is likely a result of technological innovation in energy usage and efficiency. Moreover, China should increase its R&D investment intensity from the present level as it will decrease CO2 emissions. If R&D reinvestment is associated with actual use of foreign capital, policy makers should prioritize the use of foreign capital for R&D investment on green technology. Last, economic growth requires consuming energy. However, policy makers must refrain from consuming energy beyond a certain optimal growth rate. The above findings provide a guide to policy makers to achieve dual-carbon strategy while sustaining economic development.
Based on the theory of “Non-Economic Promotion Championship,” this paper takes Appraisal-And-Commendation (AAC) policy of National Civilised City (NCC) program in China as the research object, and analyses the influence and mechanism of the NCC on carbon emissions from the perspective of energy demand. We find that NCC reduces carbon emissions significantly, and this reduction effect continues to expand over time. Furthermore, the NCC reduces carbon emissions through two mechanisms: First, the NCC reduces carbon emissions by slowing urbanisation. This mechanism mainly functions in big cities, megacities, and super cities, and does not function in small and medium cities. Second, the NCC reduces carbon emissions by promoting industrial restructuring from secondary industry to tertiary industry. This carbon reduction effect is a pure structural adjustment effect, regardless of any effects on technological level and productivity. Moreover, there are regional differences in the reduction of carbon emissions by NCC through industrial restructuring in two dimensions: In the first dimension, compared with the western region and the northeast region, the eastern and central regions are more able and willing to reduce carbon emissions through industrial restructuring. In the second dimension, compared with the northern region, the southern region is more likely to reduce carbon emissions through industrial restructuring.
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