Numerical simulations of the effects of green infrastructure on PM2.5 dispersion in an urban park in Bangkok, Thailand.
Heliyon
; 8(9): e10475, 2022 Sep.
Article
em En
| MEDLINE
| ID: mdl-36097489
Traffic emission has been identified as one of the dominant sources of fine particulate matter (PM2.5) in Thailand, and urban green spaces have the capacity to mitigate air pollution. Taking Bangkok as the study area, one of the most polluted cities in Thailand, this study investigated the effect of vegetation on PM2.5 concentration at three different sites with different vegetation characteristics in Chatuchak Park, an urban park located in Bangkok. Sensors were installed at the park to measure PM2.5 and metrological parameters at the roadside and different distances inside the park away from the road, and the ENVI-met model was run to simulate PM2.5 concentration in the three study sites. The result shows that PM2.5 concentration behind the vegetation barrier was reduced 34% on average compared to the concentration next to the road at the three sites. The effect of vegetation on meteorological factors was clearly seen near the park border with a hedgerow grown along the border. The order of influence of meteorological factors on PM2.5 concentration was relative humidity > potential temperature > wind speed > wind direction. Two scenarios including changes in weather patterns and types of vegetation that affect PM2.5 concentration were studied. Changing in the wind direction from oblique to perpendicular to the park had no significant effect on PM2.5 concentration as long as there is a dense hedgerow along the park border. Comparing to the current vegetation, sparse vegetation with less leaf area density and higher crown base heights had lower impact to mitigate PM2.5 concentration in the park. Our study provides information on vegetation and landscape strategies which can provide good air quality in the urban parks for better park design in the future.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Heliyon
Ano de publicação:
2022
Tipo de documento:
Article