Evidence map›Paper›PMID 40011514›Full record

ArticleScientific reports2025

Study on energy-autonomous technology for energy consumption performance and climate adaptation in independent public toilets based on DesignBuilder simulation.

Dapeng Bi, Zhonghua Zhao, Qunwu Huang, Yiping Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Dapeng BiSchool of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
Zhonghua ZhaoTianjin Renai College, Tianjin, 301636, China. cn123004@tjrac.edu.cn.
Qunwu HuangSchool of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
Yiping WangSchool of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To enhance energy efficiency and climatic adaptation, this study explores the potential of energy-autonomous technology (EAT) in independent public toilets. Many public toilets today suffer from significant resource wastage due to reliance on external electricity, water, and sewage systems. EAT aims to address these issues by efficiently managing toilet energy requirements. Using DesignBuilder software, we simulated and analyzed energy consumption under various climatic conditions. The results highlight that Nanning, with its strong sun irradiation and mild temperatures, exhibits a daily peak energy use of around 3.25 kWh, making it ideal for implementing such technologies. In sunny but colder locations like Xining, there are also notable advantages. Tianjin, with an effective heat gain of approximately 3,090 MJ, demonstrates significant annual energy generation. Significant emission reductions were observed in Lhasa, emphasizing the environmental benefits of EAT. This research contributes academically by providing a comprehensive analysis of EAT performance in different climates, filling a gap in the existing literature regarding the application of EAT in public toilets. Practically, it offers a novel solution for promoting hygienic facilities in water-scarce or underdeveloped areas, where access to conventional sanitation is limited. From a policy perspective, our findings support the adoption of renewable energy strategies that align with broader environmental goals, such as reducing CO

Indexed as

Climate adaptationEnergy-autonomous technology (EAT)Energy consumption simulationPublic toilet

Identifiers

PMID40011514
PMCPMC11865608

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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.