Evidence map›Paper›PMID 34841101›Full record

ArticleHeliyon2021

Development of a system dynamics model for dioxin flow and its application to the energy sector.

Chao-Heng Tseng, Ling-Ling Chen, Shang-Ming Su

Abstract read
In one paragraph

Article in Heliyon, 2021. 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

3 authors.

Chao-Heng TsengInstitute of Environment Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.
Ling-Ling ChenInstitute of Environment Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.
Shang-Ming SuInstitute of Environment Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dioxin pollution has been problematic in Taiwan. Although the government has established emission standards and emission inventory to control dioxin pollution, such efforts only apply to pollution emissions; no attempt has been made to understand the flow of dioxins in different environmental media. In this study, the STELLA software was used to model the flow pattern of dioxins in various media. This model and the RAIDAR model established by the Canadian Environmental Model Research Center were used to simulate dioxin flow in Taiwan, and their results were compared with the measured values. The accuracies of the RAIDAR and STELLA models were 63.92% and 49.78%, respectively. This shows that the simulation with the STELLA model provided results closer to the measured values and that the error was less than ten times that of the RAIDAR model, indicating that the proposed model is predictive. In addition, we used the results of a system dynamics model for dioxin flow and an air resource co-benefits (ARCoB) model to apply the obtained results to the energy sector to quantify the co-benefits of reducing dioxin, greenhouse gas, and air pollutant emissions on the basis of the policy target for the year 2030. The total co-benefits of natural gas and renewable energy (RE) scenarios were US$9.63 billion and US$12.57 billion, respectively; the benefit-cost ratios were 2.89 and 20.67, respectively. The development of an RE policy as an alternative to a coal-fired power generation policy will contribute to the best co-benefits of integrated reductions and will also contribute to human health.

Indexed as

ARCoB modelCo-benefitDioxin flowEnergy sectorSTELLASystem dynamics model

Identifiers

PMID34841101
PMCPMC8605426

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.