Evidence map›Paper›PMID 41390350›Full record

ArticleCarbon balance and management2025

Spatiotemporal evolution and analysis of influencing factors of low-carbon economy in China's Yangtze River Delta based on nighttime light remote sensing data.

Jianglin Jiang

Abstract read
In one paragraph

Article in Carbon balance and management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Jianglin JiangShaoxing Institute of Technology, No.2799 Qunxian Middle Road, Shaoxing city, China. jiangjl@usx.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of a low-carbon economy is essential for current economic growth. To gain a comprehensive understanding of the spatiotemporal evolution of low-carbon economy development in China's Yangtze River Delta and to clarify its influencing factors, this research employs spatial analysis methods such as kernel density estimation, Moran's I, spatial Markov chains, and the spatiotemporal geographically weighted regression model. The study draws the following conclusions: (1) The overall development of the low-carbon economy in the region is improving, though there are notable spatial and temporal differences between cities. In recent years, the number of cities with high levels of low-carbon development has steadily increased, yet provincial disparities remain, with Anhui Province facing the most prominent development challenges. (2) Low-carbon economy development in the Yangtze River Delta shows clear spatial clustering and migration patterns. The number of cities in a low-low agglomeration state remains stable, while the number of high-high agglomeration cities has slightly decreased. Spatially, cities with high-high agglomeration are concentrated in the eastern part of the region, while low-low agglomeration is mainly found in the west. (3) Various factors influence the development of the low-carbon economy in the Yangtze River Delta. The average regression coefficients for industrial upgrading, government intervention, technological advancement, education, and economic development are all positive, the effect of human capital shows stage-specific characteristics.

Indexed as

Influencing factorsLow-carbon economyNighttime light remote sensing dataSpatiotemporal evolutionYangtze River Delta

Identifiers

PMID41390350
PMCPMC12729195

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.