Evidence map›Paper›PMID 35897474›Full record

ArticleInternational journal of environmental research and public health2022

The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation.

Ruijing Zheng, Yu Cheng, Haimeng Liu, Wei Chen, Xiaodong Chen, Yaping Wang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Horizontal COInternational journal of environmental research and public health · 2023
    Article
  3. Article
  4. 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

6 authors.

Ruijing ZhengCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.
Yu ChengCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.ORCID 0000-0002-2510-6114
Haimeng LiuInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0003-0390-9140
Wei ChenCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.ORCID 0000-0003-4153-9873
Xiaodong ChenCollege of Management, Sichuan Anticultural University, Chengdu 611130, China.
Yaping WangCollege of Geography and Environment, Shandong Normal University, Jinan 250358, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urban agglomerations have become the core areas for carbon reduction in China since they account for around 75% of its total emissions. Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and the Pearl River Delta (PRD), which are its most important poles of regional development and technological innovation, are key to achieving China's carbon peak emissions target. Based on the panel data of these three major urban agglomerations from 2003 to 2017, this study estimated the carbon emission efficiency (CEE) by the super-efficiency slacks-based measure (super-SBM) model and analyzed its spatiotemporal distribution pattern. The Dagum Gini coefficient was used to evaluate the difference in CEE between the three major agglomerations, while panel data models were established to analyze the impact of technological innovation on the three agglomerations. The overall CEE showed an upward trend during the study period, with significant spatial and temporal variations. Additionally, the main source of urban agglomeration difference in CEE evolved from inter-regional net differences to intensity of transvariation. While technological innovations are expected to significantly improve CEE, their effect varies among urban agglomerations. These results provide policymakers with insights on the collaborative planning of urban agglomerations and the low-carbon economy.

Indexed as

CarbonInventionsBeijingChinaCitiesEconomic DevelopmentEfficiencyRiversCarboncarbon emission efficiencypanel data modelsspatiotemporal patternsuper-SBM modeltechnological innovationurban agglomerations

Identifiers

PMID35897474
PMCPMC9332555

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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.