Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/221629
Title: IMPACT OF PLANT EVAPOTRANSPIRATION RATE AND ALBEDO ON TEMPERATURE REDUCTION IN THE TROPICAL ENVIRONMENT
Authors: CHIAM ZHI QUAN
Keywords: Building
PFM
Project and Facilities Management
Wong Nyuk Hien
2014/2015 PFM
Mean Radiant Temperature
Plant Evapotranspiration Rate
Rooftop Greenery
Shrub Albedo
Issue Date: 25-Jun-2015
Citation: CHIAM ZHI QUAN (2015-06-25). IMPACT OF PLANT EVAPOTRANSPIRATION RATE AND ALBEDO ON TEMPERATURE REDUCTION IN THE TROPICAL ENVIRONMENT. ScholarBank@NUS Repository.
Abstract: Rapid urbanization has caused a major shift in population from rural to urban areas. It has brought about adverse impacts to the environment such as global warming and Urban Heat Island effect. The implementation of urban greenery is one of the widely adopted mitigation strategies to Urban Heat Island effect. Many studies have shown that urban greenery are effective in reducing ambient temperature (ta) and surface temperature (ts). However, there are limited studies on the effect of rooftop greenery on the reduction of mean radiant temperature (tmrt). This study focuses on quantifying the effects of plant evapotranspiration rate (ET) and shrub albedo (SA) on tmrt with specifics to rooftop greenery. Field measurements was conducted to collect data on tmrt, ET and SA. Three plots of rooftop greenery were set up at the roof of School of Design and Environment 1 in the National University of Singapore from May 2014 to December 2014. Data collected shows that tmrt, ta, and ts are generally lower than concrete roof. 525 data points were used for regression modeling to compare ET and SA with tmrt. A R2 of 0.851 was achieved, highlighting their strong correlation. The tmrt prediction model proposed was validated with 150 data points and is able to estimate tmrt with sufficient accuracy. Further sensitivity analysis performed provided the range of ET and SA required to achieve the desired tmrt reduction. The tmrt prediction model can be used with the range tables to guide plant selection process in rooftop greenery design
URI: https://scholarbank.nus.edu.sg/handle/10635/221629
Appears in Collections:Bachelor's Theses

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