Abstract
This study attempts to analyze the impact of population, property, technology, energy factors, and spatial agglomeration in the logistics industry on carbon emissions. To achieve the goal of peak carbon and carbon neutrality, the relationship between influencing factors and carbon emissions was analyzed based on panel data from the logistics industry for 30 provinces in China from 2003 to 2017 using an improved STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model and a spatial lag model (SLM). The results show that population, property, technology, and energy factors in the logistics industry all have different degrees of influence on carbon emissions, wherein population, energy, and property have a greater influence, which implies that carbon emission reduction policies can be carried out considering the relevant aspects. In addition, under the influence of spatial agglomeration, the degree of influence of freight mileage (FM), total fixed-asset investment (TFAI), and industry population (IPOP) on carbon emissions decreases, and the degree of influence of energy intensity (EI) and industry per capita GDP (IPCG) increases. This suggests that corresponding emission reduction policies should be formulated for large urban areas based on technological innovation, infrastructure, and talent training, while smaller urban areas can focus on developing new energy and industrial economies. These findings help to complement the existing literature and provide policymakers with some insights related to urban logistics development.
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Data availability
The datasets generated during the current study are available in the repository of the National Bureau of Statistics of China and China Emission Accounts and Dataset (CEADs), http://www.stats.gov.cn/. https://www.ceads.net/.
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Acknowledgements
I am very grateful to the editors and anonymous reviewers for reviewing this paper.
Funding
This work was supported by the project supported by the National Social Science Fund of China (17BGL136). The authors are grateful for the receipt of these funds.
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Xiaopeng Guo: conceptualization, supervision, methodology, writing (original draft), funding acquisition, and writing (review and editing).
Dandan Wang: statistical analysis, literature search, data acquisition, validation, and visualization.
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Guo, X., Wang, D. Analysis of the spatial relevance and influencing factors of carbon emissions in the logistics industry from China. Environ Sci Pollut Res 29, 2672–2684 (2022). https://doi.org/10.1007/s11356-021-15742-0
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DOI: https://doi.org/10.1007/s11356-021-15742-0