*** DaylightGuide - A tool for personalized daylight recommendations for the home office ***
Authors: V.C.A.J. de Kok, J. van Duijnhoven, J. Christoffersen

Corresponding author: J. van Duijnhoven

Contact information: j.v.duijnhoven1@tue.nl

*** General Introduction ***
The Excel file presents the tool, DaylightGuide, that was developed by Verena de Kok as part of the Smart Buildings and Cities Engineering Doctorate program at Eindhoven University of Technology. 

The DaylightGuide tool (1) asks for input about the user’s home office setup , (2) provides insights in the daylighting conditions in the home office, and (3) presents recommendations for optimizing daylight in the home office. (Day)light metrics that are presented are melanopic Equivalent Daylight Illuminance (m-EDI), Daylight Glare Probability (DGP), spatial Daylight Autonomy (sDA), and Useful Daylight Illuminance (UDI). In the tool, these metrics are referred to as the daylight targets. The tool also provides recommendations for optimizing the daylight targets. The tool is developed for use in The Netherlands.

The tool is made open-access such that anyone interested in the daylighting conditions in their home office can use it. Both an English and a Dutch version of the tool are available. A tutorial video on how to use the tool can be found here: https://youtu.be/Ti8-LJasX5U 

*** Methodological information ***
To establish this tool, three steps were taken. First, a questionnaire study was conducted to make an inventory of Dutch home office space characteristics, with a special focus on characteristics that contribute to the indoor daylight distribution. Second, based on these office characteristics, parametric simulation models were developed and annual daylight simulations were conducted using Radiance. The parameters used in the simulations were: the type of window, the orientation of the window, the density of the outside area surrounding the home office, the glazing area of the window, the color of the walls in the home office space, the placement of the window with respect to the occupant, and the distance between the workplace and the window. In specific, simulations were conducted to retrieve m-EDI, DGP, sDA, and UDI values. Third, the simulation results were processed such that the annual data were averaged per month for daytime working hours (i.e., 08.00-18.00). The data were processed to show, for each month of the year, the percentage of work hours during which a certain target was met. This analysis was done for each daylight metric. The processed dataset is included in the tool; information can be found in the next section. 

To use this tool, an Excel desktop version is required. For optional functionality, it is advised to open the tool on a large computer screen and on full-screen mode. 

*** Data specific information ***
The processed simulation dataset can be found by unhiding the “data” tab. An explanation will follow below on the specific data each column includes.
Column A “office_number” – shows a number for each unique set of home office setup parameters. In total, there are 6144 unique setups. 
Column B “façade_type” – specifies if it is a home office with a window in a vertical façade, or a home office with a pitched roof window.
Column C “win_orient” – specifies the orientation of the window; either north, east, south or west.
Coumn D “area_density” – specifies if the density of the environment surrounding the home office was either low or high. Low density meant an obstruction 10 degrees respective to the window. High density meant an obstruction of 45 degrees respective to the window. 
Column E “win_dim” – specifies the glazing area of the window, ranging from 0.5 m2 to 4.0 m2. The window was always centralized in the wall. 
Column F “wall_properties” – specifies if the color of the simulated interior walls was white, or a non-white color (simulated as grey). For the white wall we used the reflection coefficients  R:0.7672 G:0.7765 B:0.7191. For the grey wall, we used the reflection coefficients: R:0.2253 G:0.2161 B:0.1981
Column G “month” – specifies the month of the year, ranging from 1 (January) to 12 (December).
Column H “window_position – specifies the position of the window, written in text, relative to a an occupant’s workplace; either in front of them, behind them, on their left side or on their right side.
Column I “distance_window” – specifies the distance between the occupant’s workplace and the window, ranging from 0.5 meter to 3.0 meter.
Column J “DGP_035_final” – specifies for each month the percentage of the work hours that the DGP is smaller than 0.35. 
Column K “DGP_035_040_final” – specifies for each month the percentage of the work hours that the DGP is between 0.35 and 0.40. 
Column L “DGP_040_045_final” – specifies for each month the percentage of the work hours that the DGP is between 0.40 and 0.45.
Column M “DGP_045_final” – specifies for each month the percentage of the work hours that the DGP is between larger than 0.45. 
Column N “meledi_20_final” – specifies for each month the percentage of the work hours that the melanopic EDI  is equal to, or larger than 250 lux.
Column O “sDA” – specifies the spatial Daylight Autonomy as a percentage. 
Column P “UDI_100_300_final” – specifies for each month the percentage of the work hours that the UDI is between 100 and 300 lux.
Column Q “UDI_300_3000_final” – specifies for each month the percentage of the work hours that the UDI is between 300 and 3000 lux.
Column R “UDI_less_100_final” – specifies for each month the percentage of the work hours that the UDI is smaller than 100 lux.
Column S “UDI_more_3000_final” – specifies for each month the percentage of the work hours that the UDI is larger than 3000 lux.
 

