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Low-carbon innovation plays an essential role in carbon reduction worldwide. This study investigates the nexus between low-carbon innovation, economic growth, and carbon emissions by the dynamic spatial Durbin model from 2007 to 2020. First, the Moran index results verify the provincial spatial agglomeration of carbon emissions. High-emission provinces concentrate in major economic zones and energy extraction areas. Second, the effect decomposition results show that long-term and short-term effects are consistent. Low-carbon innovation has a significant mitigation effect on carbon emissions in local regions, which effect, however, is not significant in the adjacent areas. The environmental Kuznets curve hypothesis is validated locally, but all provinces and cities have not reached the inflection point of the environmental Kuznets curve, and the linkage effect in adjacent regions remains insignificant. The above results have been tested to be robust. Third, the results of the mechanism analysis show that environmental policies, absorptive capacity, and financial development play a moderating role in the relationship between low-carbon innovation and carbon emissions. Finally, the heterogeneity test showed significant differences between Eastern, Central, and Western. The direct effect of low-carbon innovation exists in Eastern and central regions; the spillover effect of low-carbon innovation is only in the eastern region. In addition, corresponding measures are proposed based on the conclusions. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) emission reduction has become an important concern worldwide. During the past century, human activities have been a significant cause of the increase in the level of greenhouse gases. Past research mainly focuses on evaluating the nexus between unidimensional population factors and CO2 emissions, while few prior studies in a developing country have reported the impact of multidimensional demographic factors on CO2 emissions. As an initial attempt, this study investigates the short- and long-run associations between population factors, low-carbon innovation, and carbon dioxide emissions (CO2) for a panel consisting of 285 cities by employing the pooled mean group (PMG) estimator under the framework of the panel autoregressive distributed lag (ARDL) model. Our main findings are as follows: (1) Population size and population density could increase CO2 emissions, while population quality and low-carbon innovation were essential factors that alleviate carbon emission pressure in the long run. (2) Economic development, foreign direct investment, and industrial development were found to be factors causing the increase in carbon emissions. (3) The split-sample analysis demonstrated that the improvement of population quality still has a positive and significant long-run effect on environmental quality. Simultaneously, low-carbon innovation could realize the enormous dividends of carbon emission reduction in the long run, especially in existing relatively larger CO2 emission areas. Finally, the paper presents important policy implications. [ABSTRACT FROM AUTHOR]

This study first attempts to use the parameterized quadratic directional distance function (DDF) approach to calculate China's provincial carbon abatement cost and carbon reduction potential (CRP) under different scenarios from 2000 to 2017. Afterward, considering three different scenarios, we analyze the spatio-temporal characteristics and the dynamic evolution pattern of CRP. We also employ spatial Durbin model (SDM) to investigate the influencing factors of CRP. The results are obtained as follows: (1) CRP across the three scenarios varies considerably across provinces and different-located groups. CRP higher areas are mainly located in the economically developed eastern coastal regions, while most provinces with low CRP are concentrated in the western region. (2) Provinces with a similar CRP showed a significant geographic agglomeration, and the agglomeration effect was strengthened first and then weakened. Simultaneously, the local spatial distribution of moderation carbon reduction potential (MCRP), fairness carbon reduction potential (FCRP), and efficiency carbon reduction potential (ECRP) shows a slight spatial polarization feature. (3) Through the SDM analysis and spillover effect decomposition, we find that improvement of regional CRP not only depends on economic development, industrial structure adjustment, and energy efficiency elevation, but also involves energy structure optimization, low-carbon innovation, and population. The low-carbon innovation provides critical support for local CRP under the efficiency scenario but restrains the local CRP under the fairness scenario. Therefore, the central government should emphasize local conditions and the ex-ante scenario assessment, strengthen regional interactive governance, optimize energy efficiency, and promote the application of clean energy to enhance CRP. [ABSTRACT FROM AUTHOR]