ArticleScientific reports2025
Study on the spatial and temporal evolution characteristics and spatial influencing factors of carbon emission intensity in commercial land.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Retracted
Authors and funding
2 authors.
Funding
Abstract
Under China's dual carbon strategy, the supporting role of commercial land in achieving this goal should be reconsidered. This paper uses Kernel density estimation and Markov chain analysis to examine the trends in carbon emission intensity of commercial land in China. Furthermore, using cold and hot spot analysis from a spatial perspective, this study explores the regional differences in carbon emissions intensity of inter-provincial commercial use, and uses spatial econometric models to analyze the influencing factors of these differences. The study reveals: (1) The center of the kernel density function gradually shifts to the right, exhibiting an evolutionary characteristic of "widening narrowing";(2) The results of traditional Markov chain analysis indicate that there is a high probability of upward flow in carbon emission intensity of inter-provincial commercial land in China, but there is also a trend of gradually strengthening carbon emission intensity of inter-provincial commercial land. The spatial Markov chain analysis results show that there is a strong spillover effect on the carbon emission intensity of commercial land between provinces with adjacent relationships; (3) From 2005 to 2022, China's commercial land carbon emission intensity showed a significant positive correlation across the country, withhot spots concentrated in the eastern developed regions and expanding to key cities in central and western China, while cold spots were mainly found in western and northeastern provinces. (4) Factors such as population density, the proportion of the secondary industry, per capita GDP, the proportion of science and technology expenditure, and energy intensity significantly influence the carbon emission intensity of commercial land, with notable regional differences. The findings can provide technical support and scientific evidence for the planning of commercial land use in China and the country's efforts to achieve a zero-carbon development strategy.
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.