Evidence map›Paper›PMID 40238836›Full record

ArticlePloS one2025

Carbon emissions accounting and uncertainty analysis in campus settings: A case study of a university in Sichuan, China.

Chen Yang, Tong Yao, Dong Shiming, Wenjie Jiang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Chen YangSichuan University Jinjiang College, Meishan, China.
Tong YaoSichuan Tourism University, Cheng Du, Sichuan, China.
Dong ShimingSichuan University, Cheng Du, China.
Wenjie JiangSchool of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang, China.ORCID 0009-0003-5090-4219

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Within the context of advancing global sustainable development goals, universities are recognized as leaders in energy conservation and emissions reduction within the education sector. Universities should actively engage in the accounting and analysis of carbon emissions. This study uses Sichuan University Jinjiang College(Hereafter referred to as J University) in Sichuan, China, as a case study, where the campus's carbon emissions for the year 2023 were calculated using the Emission Factor Method and the Delphi Method. The uncertainty associated with these emissions was further explored using Monte Carlo simulation. The results indicate that the net carbon emissions of J University amounted to 44,584.33 tons of CO2 equivalent (tCO2e), with per capita emissions of 1.89 tCO2e. The primary sources of campus carbon emissions, in descending order, include electricity (18879.94tCO2e), natural gas (8647.25tCO2e), business travel (5224.55tCO2e), campus commuting (3852.33tCO2e), food (3444.67tCO2e), and thermal energy (2566.63tCO2e). Among these sources, the carbon emissions from electricity, natural gas, and thermal energy were closely correlated with seasonal and regional factors. The uncertainties related to commuting and business travel had the most significant impact on the overall carbon emissions accounting for the campus. The study presents a framework for campus carbon emission accounting, providing a concrete case study for future researchers in this field. In particular, an in-depth exploration of statistical uncertainties is conducted, offering a scientific basis for the accurate calculation of carbon emissions in future studies.

Indexed as

CarbonCarbon DioxideChinaEnvironmental MonitoringHumansMonte Carlo MethodUncertaintyUniversitiesCarbonCarbon Dioxide

Identifiers

PMID40238836
PMCPMC12002547

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.