A Methodology for Calculating Cooling from Vegetation Evapotranspiration for Use in Urban Space Microclimate Simulations

Abstract

Vegetation affects the urban space microclimate in many ways, almost all of them being highly beneficial. At the level of city block, street or individual building, cooling from evapotranspiration is one of the most significant effects of vegetation with an impact on urban microclimate. However, this effect is difficult to be quantified in energy simulations. A tool that would contribute to the integration of fully parameterized vegetation effects into environmental analysis software for buildings and urban spaces would be of great usefulness. To this end, this work proposes a methodology that attempts to quantify evapotranspiration from single trees and vegetation ground cover. Of great importance is the simplicity in its implementation, as well as the minimum and easily obtained user input requirements.

This methodology is primarily based on the Pennman-Monteith evapotranspiration equation, as modified by the Food and Agriculture Organization of the UN. By a combination of collecting data for vegetation parameters from literature and incorporating equations for estimating some of the physical tree properties necessary as input to this method, a tool is assembled. Several tree species were categorized and included as options when calculating the cooling effect of vegetation in a system, based on this research. Evapotranspiration is then calculated depending on the specific tree species selected and the environmental data entered. The inclusion of the results in CFD environmental analysis is demonstrated.

Variations in the calculation method are applied, depending on the desired time-step of the simulation. Thus, the tool can be used either in static or dynamic form, according to the available data and required accuracy. A web version of the tool in its static instance has been created, as a form-based webpage. An executable version will provide hourly calculations of evapotranspiration by importing weather data files and dynamically altering the equations according to the environmental variables, plotting the results in graphs.