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.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Urban-scale and urban cluster-scale: how population agglomeration shapes carbon emission intensity.Carbon balance and management · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.