Multi-scale analysis of China’s transportation carbon emissions based on nighttime light data-Reference-Cited by-同舟云学术

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Multi-scale analysis of China’s transportation carbon emissions based on nighttime light data

Published:2023-02-24 Issue:18 Volume:30 Page:52266-52287
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Wang Yiping,Wu Qunqi,Song Jingni^ORCID

Funder

the National Natural Science Foundation of China

the Social Science Foundation of Shaanxi

the Philosophy and Social Sciences Major Theoretical and Practical Issues Research Program of Shaanxi

Shaanxi Provincial Postdoctoral Science Fund

the Fundamental Research Funds for the Central Universities, CHD

Natural Science Foundation of Shaanxi Province

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-023-25963-0.pdf

Reference92 articles.

1. Aren S (2017) Investigating the effect of carbon leakage on the environmental Kuznets curve using luminosity data. Environ Dev Econ 22(6):747–770. https://doi.org/10.1017/S1355770X17000249

2. Bai CQ, Chen YB, Yi X, Feng C (2019) Decoupling and decomposition analysis of transportation carbon emissions at the provincial level in China: perspective from the 11th and 12th Five-Year Plan periods. Environ Sci Pollut Res 26:15039–15056. https://doi.org/10.1007/s11356-019-04774-2

3. Bennett MM, Smith LC (2017) Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics. Remote Sens Environ 192:176–197. https://doi.org/10.1016/j.rse.2017.01.005

4. Chen SR, Zhang S, Yuan CW (2019) China’s transportation economy development and carbon environmental efficiency evaluation. China J Highw Trans 32(1):154–161. https://doi.org/10.19721/j.cnki.1001-7372.2019.01.017

5. Chen YB, Yin GW, Liu K (2021) Regional differences in the industrial water use efficiency of China: the spatial spillover effect and relevant factors. Resour Conserv Recycl 167:105239. https://doi.org/10.1016/j.resconrec.2020.105239

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