Evidence map›Paper›PMID 35329210›Full record

ArticleInternational journal of environmental research and public health2022

Numerical Investigations of Urban Pollutant Dispersion and Building Intake Fraction with Various 3D Building Configurations and Tree Plantings.

Qingman Li, Jie Liang, Qun Wang, Yuntong Chen, Hongyu Yang, Hong Ling, Zhiwen Luo, Jian Hang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Verification of the Perception of the Local Community concerning Air Quality Using ADMS-Roads Modeling.International journal of environmental research and public health · 2022
    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

8 authors.

Qingman LiSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China.
Jie LiangSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China.
Qun WangDepartment of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.ORCID 0000-0002-9166-6144
Yuntong ChenSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China.
Hongyu YangSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China.
Hong LingSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China.ORCID 0000-0001-6231-2470
Zhiwen LuoSchool of Construction Management and Engineering, University of Reading, Whiteknights, Reading RG6 6AH, UK.ORCID 0000-0002-2082-3958
Jian HangSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid urbanisation and rising vehicular emissions aggravate urban air pollution. Outdoor pollutants could diffuse indoors through infiltration or ventilation, leading to residents’ exposure. This study performed CFD simulations with a standard k-ε model to investigate the impacts of building configurations and tree planting on airflows, pollutant (CO) dispersion, and personal exposure in 3D urban micro-environments (aspect ratio = H/W = 30 m, building packing density λp = λf = 0.25) under neutral atmospheric conditions. The numerical models are well validated by wind tunnel data. The impacts of open space, central high-rise building and tree planting (leaf area density LAD= 1 m2/m3) with four approaching wind directions (parallel 0° and non-parallel 15°, 30°, 45°) are explored. Building intake fraction <P_IF> is adopted for exposure assessment. The change rates of <P_IF> demonstrate the impacts of different urban layouts on the traffic exhaust exposure on residents. The results show that open space increases the spatially-averaged velocity ratio (VR) for the whole area by 0.40−2.27%. Central high-rise building (2H) can increase wind speed by 4.73−23.36% and decrease the CO concentration by 4.39−23.00%. Central open space and high-rise building decrease <P_IF> under all four wind directions, by 6.56−16.08% and 9.59−24.70%, respectively. Tree planting reduces wind speed in all cases, raising <P_IF> by 14.89−50.19%. This work could provide helpful scientific references for public health and sustainable urban planning.

Indexed as

Air PollutantsAir PollutionEnvironmental PollutantsCitiesEnvironmental MonitoringModels, TheoreticalTreesVehicle EmissionsAir PollutantsEnvironmental PollutantsVehicle EmissionsCFD simulationopen spacepersonal intake fractionpollutant dispersionurban tree plantingventilation

Identifiers

PMID35329210
PMCPMC8951778

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.