Evidence map›Paper›PMID 33210249›Full record

ArticleEnvironmental science and pollution research international2021

Spatial effects of carbon emission intensity and regional development in China.

Yingdong Wang, Yueming Zheng

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Achieving Carbon Neutrality through Urban Planning and Design.International journal of environmental research and public health · 2023
    Article
  5. How Big Data Affect Urban Low-Carbon Transformation-A Quasi-Natural Experiment from China.International journal of environmental research and public health · 2022
    Article
  6. Temporal-Spatial Evolution and Driving Factors of Global Carbon Emission Efficiency.International journal of environmental research and public health · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yingdong WangCollege of Literature Law & Economics, Wuhan University of Science & Technology, Wuhan, 430065, Hubei, China.
Yueming ZhengCollege of Literature Law & Economics, Wuhan University of Science & Technology, Wuhan, 430065, Hubei, China. wenfaxueyuan18@163.com.

Funding

innovation and entrepreneurship training programs for Chinese college students 201910488002Xinnovation and entrepreneurship training programs for Chinese graduate students JCX201958
6 · The paper itself

Abstract

Due to the imbalance of technological level and industrial structure in regional economic development, the same carbon source can bring differentiated carbon emission levels in different regions, thus making the carbon emission show significant regional differences. In order to explore the regional differences in China's provincial carbon emission intensity and the effect of relevant influencing factors, this paper combines EKC model and STIRPAT model to conduct research. Using carbon emission intensity and other influencing factors of China's 30 provinces ranging from 2005 to 2017 to construct a panel data, the authors use exploratory spatial data analysis and Spatial Durbin Model to study the spatial effect of carbon emission intensity in China's provincial regions and the impact of different development factors on carbon emission intensity. The results show that from 2005 to 2017, China's carbon emission intensity gradually declined from east to west and from south to north. The inter-provincial carbon emission intensity of China presents an agglomeration effect in space, and the agglomeration effect gradually weakens with time. In addition, reducing energy intensity can reduce carbon emission intensity to a large extent. By optimizing industrial structure, increasing the degree of foreign trade and promoting financial development, carbon emission intensity can also be inhibited. Therefore, reducing the energy intensity of various industries and establishing inter-regional carbon emission cooperation mechanism will be effective to control the carbon emission intensity.

Indexed as

CarbonCarbon DioxideChinaEconomic DevelopmentIndustryCarbonCarbon DioxideCarbon emission intensityEconomic developmentEnergy intensityEnvironmental Kuznets curveExploratory spatial data analysisSpatial Durbin Model

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.