Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 158

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China

Open access
Li, Jianbao, Huang, Xianjin, Kwan, Mei-Po, Yang, Hong, Chuai, Xiaowei·2018·Journal of Cleaner Production

Abstract

Cities have been one of the most important areas of CO2 emissions. It is increasingly important to research the effect of urbanization on CO2 emissions, especially in large emerging and developing economies, due to the indispensable need for understanding the effect of urbanization on CO2 emissions, evaluating carbon reduction tasks and providing the scientific basis for low-carbon urbanization. Utilizing a balanced panel dataset in the Yangtze River Delta (YRD), China, during the period of 2000–2010, this paper employed data envelopment analysis (DEA) window analysis and a spatial lag panel Tobit model to investigate the effect of urbanization on CO2 emissions efficiency (the ratio of the target CO2 emissions to the actual CO2 emissions). The results show that the average CO2 emissions efficiency was 0.959 in 2010, and CO2 emissions efficiency ranged from 0.816 to 1 and exhibited spatial clustering in the region. The larger potential of CO2 emissions reduction appeared in Zhenjiang and Yangzhou, indicating that more CO2 emissions reduction tasks should be allocated to these two cities. Urbanization has negative effects on improving CO2 emissions efficiency, and there is a U-curve relation between CO2 emissions efficiency and urbanization, indicating that CO2 emissions efficiency decreases at the early stage of urbanization, then increases when urbanization reach a high level. There is spatial spillover effect among the prefecture-level cities, suggesting that different prefecture-level governments should coordinate with each other to improve CO2 emissions efficiency in the whole area. Gross domestic product (GDP) per capita also plays a markedly positive role in improving CO2 emissions efficiency. This research highlights the effect of urbanization on CO2 emissions efficiency and the importance of improving CO2 emissions efficiency in developing countries.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jclepro.2018.03.198

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 158

Metadata

Authors
Li, J., Huang, X., Kwan, M.-P., Yang, H., & Chuai, X.
Venue
Journal of Cleaner Production
Publisher
Elsevier BV
Published
2018-07
Volume
188
Pages
38-48
ISSN
0959-6526 (ISSN-L)
OpenAlex
W2790770414
Cited by
158
References
1
FWCI
28.21
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China. https://app.cochat.ai/papers/10.1016/j.jclepro.2018.03.198
The paper
Li, J., Huang, X., Kwan, M.-P., Yang, H., & Chuai, X. (2018). The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.03.198

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.