Evidence map›Paper›PMID 42151280›Full record

ArticleScientific reports2026

Elucidating carbon emission responses to land-use transition using the Kaya-LMDI model: a case study of Hainan, China.

Chunlan Zhao, Yingce Li, Linyuan Wu, Wenxing Du

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Chunlan ZhaoCollege of Geography and Environmental Science, Hainan Normal University, Haikou, 571158, China.
Yingce LiCollege of Geography and Environmental Science, Hainan Normal University, Haikou, 571158, China.
Linyuan WuCollege of Geography and Environmental Science, Hainan Normal University, Haikou, 571158, China.
Wenxing DuCollege of Geography and Environmental Science, Hainan Normal University, Haikou, 571158, China. duwx@hainnu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Land-use transition (LUT), a pivotal vector for anthropogenic intervention in the carbon cycle, profoundly influences the formation and evolution of regional carbon emission patterns. This study focuses on Hainan, China's sole tropical island, and establishes a model accounting for carbon emissions associated with LUT based on related remote-sensing data, socioeconomic statistics, and energy consumption-related data between 2000 and 2025. We combine spatial autocorrelation analysis, an extended logarithmic mean Divisia index decomposition model, and the Tapio decoupling model to systematically elucidate the spatiotemporal features of LUT-associated carbon emissions, their driving factors, and their decoupling relation with economic growth. Notably, Hainan Province features an LUT involving decreasing and increasing proportions of carbon-sink land and carbon-source land, respectively, with construction land expansion being the primary transition mode driving carbon emission growth. The associated carbon emission response features a spatial differentiation pattern of high values concentrated in the north and west and low values localized in the south and east. In addition, carbon sources and sinks demonstrate considerable spatial agglomeration. Economic output is the core driver promoting carbon emission growth, with improvements in land-use efficiency and energy intensity being critical for carbon emission mitigation. During the examined period, the correlation between LUT-associated carbon emissions and economic growth evolves from weak to strong decoupling, demonstrating the remarkable efficacy of peak carbon and carbon neutrality goals in guiding emission reduction-focused LUT. Overall, this research provides a scientific basis for coordinating LUT and low-carbon development in the Hainan Free Trade Port initiative.

Indexed as

Carbon emission kaya identityLand-use transitionLMDI decomposition modelPressure–state–response modelTapio decoupling model

Identifiers

PMID42151280
PMCPMC13381873

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LicenceCC BY-NC-ND
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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.