Evidence map›Paper›PMID 33241499›Full record

ArticleEnvironmental science and pollution research international2021

Effect of triangular roof angle on dispersion of gaseous pollutants and particulate matter.

Xiaoxiao Zhang, Chunmei Wang, Xiaoping Liu, Taotao Zhou, Changfa Tao, Qin Shi

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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5 · Who and what money

Authors and funding

6 authors.

Xiaoxiao ZhangSchool of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, 230009, Anhui, China.
Chunmei WangSchool of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, 230009, Anhui, China.
Xiaoping LiuSchool of Civil Engineering, Hefei University of Technology, No. 193, Tunxi Road, Hefei, 230009, Anhui, China.
Taotao ZhouSchool of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, 230009, Anhui, China. zhoutt@hfut.edu.cn.ORCID http://orcid.org/0000-0001-9331-839X
Changfa TaoSchool of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, 230009, Anhui, China. chftao84@hfut.edu.cn.
Qin ShiSchool of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, 230009, Anhui, China.

Funding

Fundamental Research Funds for the Central Universities PA2020GDKC0017National Key R&D Program of China 2018YFC0810600National Natural Science Foundation of China 51906055National Natural Science Foundation of China U1933131Natural Science Foundation of Anhui Province 2008085ME166
6 · The paper itself

Abstract

The Euler-Lagrangian method is adopted to simulate the dispersion of gaseous pollutants and particulate matter (PM) in isolated street canyons, and the influences of the roof angle on the flow structures and distributions of gaseous pollutants and PM are analyzed in detail. Numerical simulation results indicate that gaseous pollutants and PM in the canyons present three typical single main clockwise vortex, transition vortex, and double vortex structures, which are identified at increasing roof slopes. Gaseous pollutants and PM demonstrate the lowest concentration of pollutants when a single vortex structure exists. The concentration of gaseous pollutants and PM reaches the highest value in pedestrian-level areas when the flow field is in a transitional vortex structure. Unlike gaseous pollutants, the concentration of PM does not always decrease with increasing altitude, and higher PM concentrations sometimes occur in the mid-level areas of the canyon. A small roof incline angle is generally recommended for discharging gaseous pollutants and PM.

Indexed as

Air PollutantsEnvironmental PollutantsEnvironmental MonitoringGasesModels, TheoreticalParticulate MatterVehicle EmissionsWindAir PollutantsEnvironmental PollutantsGasesParticulate MatterVehicle EmissionsEuler–Lagrangian methodFlow fieldNumerical simulationPollutant diffusionRoof angleStreet canyons

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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.