Impact of population agglomeration in big cities on carbon emissions

Yi, Yanchun; Qi, Ji; Chen, Dong

doi:10.1007/s11356-022-21722-9

Cited by 35 publications

(8 citation statements)

References 38 publications

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“…Investigations into how the urbanization rate affects carbon emissions have also been conducted. According to some studies, growing urbanization could cause a rise in carbon emissions because of the industrial structure, transportation effects 36 , and road energy use 37,38 , but this impact varies by region 39 . For example, the urbanization rate exerts little effect on the carbon emissions in Organisation for Economic Co-operation and Development (OECD) countries 40,41 .…”

Section: Spatiotemporal Differences In and Influencing Effects Of Per...mentioning

confidence: 99%

Spatiotemporal differences in and influencing effects of per-capita carbon emissions in China based on population-related factors

Zhang,

Li,

Tong

2023

Sci Rep

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Intensive human activities and resource consumption in China have led to increasing carbon emissions, placing enormous pressure on achieving sustainable development goals. Nonetheless, the effects of population-related factors and carbon emissions remain controversial. This study focuses on the spatiotemporal differences in and influencing effects of per-capita carbon emissions using 2010–2019 panel data covering 30 regions in China. Differing from previous studies, population-related factors are employed to classify the 30 regions into 4 classes, and kernel density estimation, σ convergence and spatial econometric models are used to analyse the spatiotemporal differences in and influencing effects of per-capita carbon emissions. The results demonstrate that overall per-capita carbon emissions rose, but there was heterogeneity in the change in per-capita carbon emissions in the 4 classes of regions. The difference in regional per-capita carbon emissions has been widening, but the change rate of the difference stabilized. Overall, per-capita carbon emissions are heavily affected by household size; however, the driving forces behind per-capita carbon emissions in the 4 classes of regions vary. These results suggest that precise and coordinated governance of carbon emissions and reverting to the traditional household structure should be considered to meet the dual carbon goal.

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Section: Spatiotemporal Differences In and Influencing Effects Of Per...mentioning

confidence: 99%

Spatiotemporal differences in and influencing effects of per-capita carbon emissions in China based on population-related factors

Zhang,

Li,

Tong

2023

Sci Rep

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show abstract

“…In urban agglomeration literature, many studies have explored the effects of urban agglomeration on the commuting distance or time (e.g., [23]), transport carbon emissions (e.g., [24]) and on urban air pollution [25]. The study show that high density of agglomeration reduces commuting distances [17], motorised travels and urban air pollution.…”

Section: Effect Of Urban Agglomeration On Air Pollutionmentioning

confidence: 96%

How does road accessibility increase air pollution in the Yangtze River Delta Region, China ?-Evidence from digital elevation model and points-of-interest data

Tao

2023

Preprint

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Empirical evidences on how urban road accessibility affects air pollution is scarce for the specific Yangtze River Delta (YRD) region that is characterised by high density in economic activities and rapid urban expansion. Using novel Digital Elevation Model (DEM), road network and points-of-interest (POI) datasets to measure road accessibility, moderating and mediating effect models then were conducted to explore direct and indirect effects of road accessibility on environmental externality expressed by air pollution through urban connection and urban agglomeration. When exploiting exogenous variable in urban populations, the result of moderating effect model shows that road accessibility decreases air quality-to-connection elasticity by around -5.2% which indicates that road accessibility increases air pollution through internal connection. However, the finding of mediating effect model indicates that road accessibility slightly improves air quality through decreasing urban agglomeration. The findings of this paper suggest that high levels of road accessibility may have negative consequence for live-ability of YRD cities because of current urban internal connection and urban decision makers should consider the improvement of urban connection for obtaining better air quality.

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“…Their results demonstrated that there was a significant positive correlation between population aging and carbon emissions in China. Using the panel data of 207 large cities in China from 2005 to 2018, Yi et al [26] explored the impact of population agglomeration on urban carbon emissions. They confirmed that population agglomeration significantly raised urban carbon emissions.…”

Section: Factors Influencing Carbon Emissionsmentioning

confidence: 99%

Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China

Xian-pu

Song

2023

Sustainability

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While artificial intelligence (AI) has had a great impact on the global economy, it has also brought new hope and opportunities for environmental protection. In this context, the authors of this paper collected balanced panel data for 30 Chinese provinces during 2006–2019 and studied the impact of AI development on local carbon emissions by using a two-way fixed-effect model. The results show that AI has significantly lowered carbon emissions. Using a series of robustness tests and instrumental variable (IV) analysis, it was found that the results are still reliable. Furthermore, mechanism analysis revealed that AI mainly reduces carbon emissions by improving energy structure and technological innovation. The lower the dependence on fossil energy, the higher technological innovation becomes, and the better the carbon reduction effect of AI. In addition, the regional heterogeneity test detected that the emission reduction effect of AI is best in the East, followed by the West, and not significant in the Central region. Therefore, to fully exploit the positive effects of AI on carbon emissions, this paper suggests accelerating intelligent transformation, formulating differentiated AI development strategies, promoting the green transformation of energy usage, and strengthening local human capital accumulation.

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Impact of population agglomeration in big cities on carbon emissions

Cited by 35 publications

References 38 publications

Spatiotemporal differences in and influencing effects of per-capita carbon emissions in China based on population-related factors

Spatiotemporal differences in and influencing effects of per-capita carbon emissions in China based on population-related factors

How does road accessibility increase air pollution in the Yangtze River Delta Region, China ?-Evidence from digital elevation model and points-of-interest data

Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China

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