Evidence map›Paper›PMID 42675097›Full record

ArticleScientific reports2026

Artificial intelligence and environmental sustainability: a nonlinear analysis of the load capacity factor in OECD countries.

Heng Luo, LianPing Zhang, Ying Sun, Li Zhang

Abstract read
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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Heng LuoJilin University of Chemical Technology, Jilin, China.
LianPing ZhangJiangxi Institute of Fashion Technology, Nanchang, Jiangxi, China.
Ying SunJilin University of Chemical Technology, Jilin, China. 2398596174@qq.com.ORCID https://orcid.org/0009-0008-7911-9034
Li ZhangZhenkou Township People's Government, Fuzhou, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amid the rapid expansion of artificial intelligence (AI) and growing concerns over ecological constraints, understanding the environmental consequences of emerging technologies has become increasingly important. This study investigates the nonlinear relationship between AI and environmental sustainability, which is proxied by the Load Capacity Factor (LCF), while considering the moderating effect of trade openness. Based on panel data from OECD countries between 1993 and 2023, the empirical results indicate a significant U-shaped relationship between AI and LCF. Specifically, AI initially reduces LCF but enhances environmental sustainability after exceeding a certain threshold. Moreover, trade openness is shown to flatten the U-shaped curve and shift its turning point. These findings provide meaningful policy insights for integrating digital transformation with sustainable development objectives.

Indexed as

Artificial intelligenceEnvironmental sustainabilitynonlinear nexusOECDTrade openness

Identifiers

PMID42675097
PMCPMC13530151

What OpenQuestion holds

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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.