Evidence map›Paper›PMID 41741589›Full record

ArticleScientific reports2026

Reveal the deployable solar energy potential and emission reduction benefits in the arid areas of Xinjiang.

Nuo Li, Wenjie Yu, Kexin Liu, Yihang Zhou, Hanlu Zhang, Haiwei 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

6 authors.

Nuo LiCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830046, China.
Wenjie YuCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830046, China. yuwenjie@xju.edu.cn.
Kexin LiuCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830046, China.
Yihang ZhouSchool of Intelligence Science and Technology, Xinjiang University, Urumqi, 830046, China.
Hanlu ZhangCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830046, China.
Haiwei ZhangCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830046, China. zhanghw@xju.edu.cn.

Funding

the Basic Research Projects for Universities in the Autonomous Region XJEDU2025P007
6 · The paper itself

Abstract

Photovoltaic (PV) development in arid regions faces challenges such as sparse observational data, insufficient consideration of natural environmental heterogeneity, and a disconnect between site suitability assessments and actual power generation potential. To address these issues, this study integrates ERA5-Land reanalysis data, ESA CCI land cover data, DEM terrain data, and PV site information to construct a land suitability factor ranging from 0 to 1. Coupled with the Photovoltaic Library Python model(PVLIB-Python), a comprehensive assessment framework is established, spanning from site suitability to power generation potential and emission reduction benefits.Results show that Xinjiang’s theoretical PV generation potential from 2015 to 2025 averages approximately 113.5 PWh per year. After applying land suitability constraints, the technical potential decreases to 71.4 PWh annually, representing about 63% of the theoretical potential. Spatially, suitability follows a pattern of “concentration in basins and dispersion in mountainous areas,” with highly suitable zones mainly located in the central-western Tarim Basin, the Hami Basin, and the southern edge of the Junggar Basin.Based on the calculated technical potential, annual PV deployment could achieve around 53.5 billion tonnes of CO2 emission reductions.Incorporating environmental benefits significantly lowers the levelized cost of energy (LCOE) for PV systems, demonstrating considerable net social value. This study provides quantitative evidence to support the scientific planning of PV power stations in Xinjiang and the formulation of carbon neutrality pathways.

Indexed as

Emissions Reduction BenefitsGeographic Information System(GIS)Photovoltaic Power GenerationTechnical Potential

Identifiers

PMID41741589
PMCPMC13031888

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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.