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Atmosphere 2018, 9(2), 39; https://doi.org/10.3390/atmos9020039

Prediction of Wind Environment and Indoor/Outdoor Relationships for PM2.5 in Different Building–Tree Grouping Patterns

1
College of Landscape Architecture & Arts, Northwest A&F University, Yangling 712100, China
2
Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
Received: 26 October 2017 / Revised: 9 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
(This article belongs to the Special Issue Recent Advances in Urban Ventilation Assessment and Flow Modelling)
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Abstract

Airflow behavior and indoor/outdoor PM2.5 dispersion in different building–tree grouping patterns depend significantly on the building–tree layouts and orientation towards the prevailing wind. By using a standard k-ε model and a revised generalized drift flux model, this study evaluated airflow fields and indoor/outdoor relationships for PM2.5 resulting from partly wind-induced natural ventilation in four hypothetical building–tree grouping patterns. Results showed that: (1) Patterns provide a variety of natural ventilation potential that relies on the wind influence, and buildings that deflect wind on the windward facade and separate airflow on the leeward facade have better ventilation potential; (2) Patterns where buildings and trees form a central space and a windward opening side towards the prevailing wind offer the best ventilation conditions; (3) Under the assumption that transported pollution sources are diluted through the inlet, the aerodynamics and deposition effects of trees cause the lower floors of a multi-storey building to be exposed to lower PM2.5 compared with upper floors, and lower indoor PM2.5 values were found close to the tree canopy; (4) Wind pressure differences across each flat showed a poor correlation (R2 = 0.059), with indoor PM2.5 concentrations; and (5) Patterns with the long facade of buildings and trees perpendicular to the prevailing wind have the lowest indoor PM2.5 concentrations. View Full-Text
Keywords: wind environment; Natural Ventilation Potential (NVP); PM2.5; building–tree grouping patterns; Computational Fluid Dynamics (CFD) wind environment; Natural Ventilation Potential (NVP); PM2.5; building–tree grouping patterns; Computational Fluid Dynamics (CFD)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Hong, B.; Qin, H.; Lin, B. Prediction of Wind Environment and Indoor/Outdoor Relationships for PM2.5 in Different Building–Tree Grouping Patterns. Atmosphere 2018, 9, 39.

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