Evidence map›Paper›PMID 37020108›Full record

ArticleScientific reports2023

Spatial correlation between producer services agglomeration and carbon emissions in the Yangtze River Economic Belt based on point-of-interest.

Peng Zeng, Lingjie Shang, Mengkun Xing

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

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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

3 authors.

Peng ZengSchool of Ethnology and Sociology, Guangxi University for Nationalities, Nanning, 530006, China. zengpengfast@163.com.
Lingjie ShangSchool of Economics, Guangxi University for Nationalities, Nanning, 530006, China.
Mengkun XingSchool of Ethnology and Sociology, Guangxi University for Nationalities, Nanning, 530006, China.

Funding

National Social Science Fund of China No. 20&ZD157
6 · The paper itself

Abstract

Agglomeration of the industry significantly impacts economic performance and environmental sustainability. In line with its strategic context of striving to achieve carbon reduction targets, China is making efforts to optimize the producer services landscape to reduce carbon emissions. Understanding the spatial correlation between industrial agglomeration and carbon emissions is particularly crucial against this background. Based on POI and remote sensing data of China's Yangtze River Economic Belt (YREB), the paper adopts the mean nearest neighbor analysis, kernel density analysis, and standard deviation ellipse to portray the agglomeration of producer services. Then uses Moran's I to present the spatial distribution characteristics of carbon emissions. Accordingly, the spatial heterogeneity of producer services agglomeration and carbon emissions is showed using the Geographic detector so as to provide strong support for industrial structure optimization and sustainable development. Here are some of the conclusions drawn from the study: (1) Producer services are a significant state of agglomeration in the provincial capitals and some central cities, with similar agglomeration patterns. (2) Carbon emissions exhibits significant spatial aggregation characteristics, with the spatial distribution pattern of "High west-Low east". (3) Wholesale and retail services industry is the primary risk factor that causes spatial differentiation of carbon emission intensity, "leasing and business services industry-wholesale and retail services industry" is the key interaction factor of the spatial differentiation. (4) Carbon emissions shows a downward trend followed by an upward trend as producer services agglomeration increases.

Identifiers

PMID37020108
PMCPMC10076268

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