Lecture Theater Survey by Amalia Vrana

UCL LECTURE THEATERS SURVEY The importance of openings in learning conditions

CONTENTS 1.INTRODUCTION 6 2. LITERATURE REVIEW 2.1. Thermal Comfort: 7 2.2. Illumination and views 7 2.3. Ventilation: 8 2.4. GENERAL DESIGN 9

3. METHODOLOGY 9 3.1 SURVEYS 9 3.2 STATISTICAL ANALYSIS 3.2.1 First categorization- Windows/no windows 9

3.2.2 Development of lecture theater archetypes

4. RESULTS 12

4.1.THERMAL COMFORT 12 4.2. VENTILATION 14 4.3. LIGHTING 15 4.4 GENERAL DESIGN 4.5 SCATTER PLOTS 4.6 USING CATEGORIZATION AND ARCHETYPES 19

5. DISCUSSION 21

5.1. INTERPRETATION OF RESULTS

5.1.1 Thermal Comfort 21 5.1.2. Ventilation 21 5.1.3. Lighting 22 5.1.4. General Design 22 5.2. LIMITATIONS 22

6. CONCLUSION 22 7. BIBLIOGRAPHY 24 8. APPENDIX 26

1.INTRODUCTION Over the last decades, there has been extensive research globally on how thermal conditions and indoor environment quality (IEQ) may affect human perception, with studies and experiments being conducted in various types of buildings. That stems from the need to design healthy and comfortable buildings, optimal working and learning environments, while making them as much energy efficient as possible. Within the frame of this report focus will be given on how windows influence internal conditions of lecture theaters at UCL. More specifically, aim of the report is:

To investigate whether and how the existence of openings -and their position, size and orientation- in lecture theaters of UCL may influence thermal comfort or visibility levels during winter months, resulting to an impact on students’ concentration. Openings are one of the most common architectural element. From the smallest private house to the largest public building, the use of openings plays a significant role in making the indoor space inviting and lively. But, what about lecture theaters? Are openings always indispensable for making a “good” lecture theater? Over the last decades there have been several studies examining how windows affect human performance and comfort. Experiments have been conducted in several types of buildings, such as schools and offices examining the concentration level, performance or productivity of users relatively to the existence of openings. There are controversial views on the subject, such as O Konnor (1999) and Harrigan(1999) who indicated that there is indeed a positive correlation between windows and performance of students. On the contrary, Romney (1975) suggested that windows do not affect learning performance. The objectives of the study are as follows: a. to compare indoor conditions and human responses (actual vote) between lecture theaters with and without windows. b. to statistically analyze correlations between different variables that can affect students’ concentration and are connected to the existence of openings c. To categorize lecture theaters in different typologies -archetypes- and thus, d. make assumptions on how windows can help in increasing students’ concentration and comfort in terms of the learning environment or suggestions for improvement if the results prove a negative impact. There are many different types of openings, but the basic purposes regardless of size and shape are the following: • Direct contact with the external environment, nature - view • Penetration of natural light- daylight • Supply of fresh air Thus, they can affect overall comfort in a building by affecting: o Temperature of the indoor environment, o visibility levels depending on the amount of lighting that enters the indoor space and, o Natural ventilation-infiltration*.

2.LITERATURE REVIEW The literature review will be structured according to the three categories mentioned above. Main purpose of the research was to analyze the basic trends and studies regarding the existence of windows and how they affect users. The aim is to identify the findings in each category-variable, something that will help in making assumptions later on.

2.1. Thermal Comfort:

Openings, as mentioned before, can also influence air temperature and therefore, thermal comfort of users. Being near windows can affect the objective in two ways: • Lower temperature near windows during winter (lower mean radiant temperature): feeling of cold • Higher temperatures near windows during summer (higher mean radiant temperature) : overheating Taking into account that this study is narrowed for winter months, the essay will mainly focus on possible differences in students’ comfort and concentration near windows, as a result of lower radiant temperatures. Furthermore, windows can also affect thermal comfort by influencing the air temperature in case they are used for ventilation, i.e. by letting cold external air come into the space. Experts claim that changes in air temperature to levels outside the comfort zone can lead to under performance, and that applies to both warmer and colder than neutral environments (Hancock et al. 2015). Furthermore, Lan et al. (2011) support that the PMV range from -0.5 to 0.0, i.e. slightly cold, is the ideal condition in terms of temperature for maximum performance. This view has been supported by Cui and al. (2013), who proved that colder environments are more suitable for maintaining a good performance. Additionally, as Mishra and Ramgopal (2015) mention in their work, several studies conducted at schools and offices have shown that performance peaks around 21°C. They also discuss the experiment of Pelper and Warner; when temperature rose from 16.7°C to 26.7°C, speed and errors decreased by 7% and 17% respectively, whereas when the temperature increased in uncomfortable levels again (33°C) there was an increase in both speed and errors (Mishra & Ramgopal 2015). The present study seeks to investigate in what extend windows influence internal temperature and whether this impact is negative or positive -because as stated in literature cooler environments are usually preferred in terms of learning.

2.2. Illumination and views

Direct contact with daylight may constitute the most essential feature of indoor space. Natural light is always preferable than artificial lighting but, in the case of lecture theaters, one can argue that not only are the openings not indispensable, but also they may be distracting for the users –something that is clearly unwanted in the case of a lecture theater. There are different views and opinions described in literature. To begin with, research has proved that students in classrooms with natural daylight have a significant advantage in terms of learning. During the experiment of Heschong Mahone Group (1999 cited in Schneider, 2002) students in classes with natural daylight progressed at a faster rate in math and reading tests (20 and 26 per cent respectively) compared to their fellow students in classrooms with no daylight.

On the other hand, Lang (1996, cited in Fleming & Storr, 1999) suggests that the optimum learning environment is achieved with a combination of natural and artificial lighting. He outlines the negative aspects of daylight, such as glare. Later studies, though, indicate that the productivity and satisfaction -this time of employers- increases near openings, especially when the openings’ orientation is south, east or west – i.e. towards the sides which receive the biggest amount of sun (Cai and Marmot, 2013). In their study, they concluded that not only performance and productivity, but also thermal comfort increased in proximity to windows. Moreover, they determined that natural light and view affect far more positively the participants, than the existence of discomfort glare or distractions coming from a specific window (Cai et al. 2013). Another fact supporting positive impacts of windows is that they are voted as the most important factor for overall comfort in a building (Aries et al. 2010). Nonetheless, in the same paper there was again a clear relation between distance from the window and comfort; the longer the distance, the least the participant had problems with glare or overheating.

2.3. Ventilation:

Ventilation, natural or mechanical, is a very important aspect for healthy buildings. It is worth mentioning that the existence of openings should not be associated with the existence of adequate natural ventilation. There is a strong likelihood that their size might be insufficient for ventilation the space1, or their direction might not take advantage of prevailing winds. Subsequently, a room with openings may be worst in terms of ventilation than a closed room supported by mechanical ventilation. Nonetheless, windows are indeed the main architectural element that can supply indoor space with fresh air. Fresh air, when provided, can remove mold, bacteria, but also CO2 emissions accumulated by human respiration, that especially in classrooms can reach very high levels -4000ppm at maximum occupancy2 (Clements-Croome et al. 2008). There have been several studies proving that all the above contaminants and generally poor air quality, can influence human performance. Indeed, Smedje and Norback (1999, cited in Schneider, 2002, p.3) found that increased levels of airborne bacteria or mold in the air can affect asthma episodes leading to an increase in absenteeism. Moreover, an experiment conducted by Rosen and Richardson (1999) proved that there is a connection between indoor air quality and absenteeism. The experiment took place in Sweden and it examined two school establishments for a 3 year period. The second year of the experiment, a system of mechanical ventilation was applied to both examined schools, leading in a decrease in absenteeism of approximately 4% for that year (Rosén & Richardson 1999). As far as students’ opinion on the learning environment is concerned, it seems that ventilation and air-conditioning are the major factors that influence students’ concentration and performance, according to their votes (Clatworthy & Kooymans 2001). It is notable that in the same research, natural lighting was ranked 17th out of 25 selected factors. On the contrary, in a similar survey of Fleming and Storr (1999) ventilation was ranked 7th and natural light 6th (in terms of their importance in relation to learning conditions).

1 Window minimun sizes for adequeate levels of air flow are given by CIBSE AM10 for one-sided and cross

ventilation 2 The benchmark given by CIBSE is maximum 2000ppm

Having said that, one can easily understand that there are controversial studies and opinions on whether opening have a positive or negative impact on concentration and productivity. Because of the complexity of the variables that can be influenced because of the existence of openings, it is difficult to have solid results, because of different conditions and participants. Nonetheless, within this report there will be an attempt to clarify if windows have an negative, positive or neutral impact on UCL studentsâ&#x20AC;&#x2122; concentration.

2.4. General Design Finally, general design is another parameter that can be influenced by the existence of windows, usually in a positive way as windows upgrade aesthetically the architectural space. Yarbrough (2001), examined different parameters that can influence architectural design (daylighting, views, colour schemes etc) and found a strong correlation between architectural design and studentsâ&#x20AC;&#x2122; achievements. The study concerned elementary schools in Georgia, US. From the literature review, it is clear that there are many parameters that can affect concentration, in some cases controversial. Thus, it needs to be clarified in what extend each of these variables affects concentration, but also what is the correlation with the existence of windows. For that reason they must be examined separately and subsequently, the main structure of the next chapters will be based on them.

3. METHODOLOGY This report is part of a broader study concerning thermal conditions of lecture theaters at UCL, conducted by IEDE. For the realization of this study 38 lecture theaters were examined, following the process described below.

3.1 SURVEYS

The survey period lasted one month -October to November- and included: 1. Monitoring survey: HOBO data loggers were used(see appendix for specifications). The monitoring was conducted during different lectures. Dry bulb temperature, RH and light intensity were measured with an interval of 10 minutes. The duration of each lecture varies -from 90 minutes to 2 hours. 2. Physical survey: height, width and length of LTs were measured. Moreover, UCL estates provided the architectural drawings of each LT for further analysis3. 3. Questionnaire survey: While the monitoring surveys were conducted, questionnaires were given to students with questions relevant to the indoor environment and quality of the lecture theater (see appendix for questionnaire). There were a total of 2,633 participants out of the 3,862 students asked, i.e. a response rate of 68.2%. Students were also asked to note their seating position, which will be used later in order to compare discrepancies in voting in regard to where the student was seating4.

3 It should be noted that not all lecture theatersâ&#x20AC;&#x2122; drawings where available 4 This constitute another limitation during the data analysis, as many of the participants did not note their seat position

WINDOWS NO WINDOWS

Chandler 118 window Chandler G10 window Drayton B03 Ricardo LT window Drayton B20 Jevons LT window Gordon Square (24) 105 window Gordon Street (25) D103 window Gordon Street (25) Maths 500 window Gordon Street (25) Maths 505 window Medawar G02 Watson LT window Pearson (North East Entrance) G22 LT window Physics A1/3 window Roberts 309 window Roberts 421 window Roberts 508 window South Wing 9 Garwood LT window Wilkins Gustave Tuck LT WINDOW Anatomy G04 Gavin de Beer LT NO window Anatomy G29 J Z Young LT NO window Archaeology G6 LT NO window Bedford Way G03 NO window Bedford Way LG04 NO window Chadwick B05 LT NO window Christopher Ingold G21 Ramsay LT NO window Christopher Ingold XLG1 Chemistry LT NO window Cruciform B304 ‐ LT1 NO window Cruciform B404 ‐ LT2 NO window Darwin B40 LT NO window Gordon Street (25) E28 Harrie Massey LT NO window Malet Place Eng 1.02 NO window Malet Place Eng 1.03 NO window Medawar G01 Lankester LT NO window Medical Sciences 131 A V Hill LT NO window Medical Sciences G46 H O Schild Pharmacology LT NO window Roberts 106 NO window Roberts G06 Sir Ambrose Fleming LT NO window Roberts G08 Sir David Davies LT NO window Torrington (1‐19) 115 Galton LT NO window Torrington (1‐19) B17 Basement LT NO window

TABLE 1: Lecture theaters divided in two main categories: with and without windows. With color are noted the lecture theaters for which there are architectural drawings available and they will be used for further analysis.

3.2 STATISTICAL ANALYSIS After collecting the above data, an overall Excel spreadsheet was created, which was then used for statistical analysis with EXCEL and Analysis Toolkit. The analysis started by comparing the whole sample of Lecture theaters and gradually focused to more specific cases. 3.2.1 First categorization- Windows/no windows Lecture theaters were firstly divided in two main categories; LTs with windows and LTs without windows (Table 1). Having determined the variables influenced by the existence of windows -thermal comfort, air quality and movement, lighting quality and general design, there has been a comparison between the two categories in order to evaluate possible discrepancies. Additionally, these factors were correlated with the mean vote for general concentration for each lecture theater, using scatter diagrams. 3.2.2 Development of lecture theater archetypes The next step was to categorize Lecture theaters with windows based on their special char8

026 - 01 - 3

24 GORDON SQUARE

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DO NOT SCALE OFF THIS DRAWING. ALL DIMENSIONS MUST BE CHECKED ON SITE PRIOR TO ANY WORK BEING PUT IN HAND. ANY DISCREPANCIES ARE TO BE BROUGHT TO THE ATTENTION OF THE PROJECT MANAGER IMMEDIATELY UPON DISCOVERY.

rev

acteristics, i.e. the development of archetypes (Mavrogianni et al. 2012) (Steadman 2001). This process helped in making comparisons between different lecture theaters and examine what happens in the micro-scale of each classroom, in other words how votes are formed in relation to the distance from a window, how lighting affects specific areas in the theater etc. There were two main ways of categorizing; 1. by orientation -North, East-West or South windows 2. by windows position: in that case lecture theaters were divided by the relative position of the windows in regards to the seatings to: a) front and/or back windows b) side windows (Table 2)

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Moreover, naturally ventilated lecture theaters are noted in all diagrams throughout the process.

A30 OFFICE

A25 OFFICE

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PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT DO NOT SCALE OFF THIS DRAWING. ALL DIMENSIONS MUST BE CHECKED ON SITE PRIOR TO ANY WORK BEING PUT IN HAND. ANY DISCREPANCIES ARE TO BE BROUGHT TO THE ATTENTION OF THE PROJECT MANAGER IMMEDIATELY UPON A13 DISCOVERY.

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A9 OFFICE

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PLANT ROOM BELOW LECTURE THEATRE

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A27 LIBRARY A17 COMMON ROOM

COMMON ROOM

A19 PC CLUSTER ROOM

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A94D

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103 LECTURE THEATRE

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ENTRANCE G11A

G91 ENTRANCE LOBBY

G12 MICROSCOPE ROOM

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A22 OFFICE A23 FEMALE TOILET

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4 MEETING ROOM

10 COMMON ROOM

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181 486 Junction 420A South Stair WC

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485 DUCT 2 OFFICE 421 LECTURE THEATRE 91.62 m²

422 LECTURE THEATRE 99.56 m²

G91 IT

420 WC

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CORRIDOR

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G97

G10 LECTURE THEATRE

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6 OFFICE

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2A STORE 490 LIFT LOBBY

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499 STAIR B

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408 DATA ROOM

412 OPEN HUB SPACE

LINK BRIDGE

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402 OFFICE 9.28 m²

497

CORRIDOR

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G99

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419 OFFICE 23.91 m²

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411 OFFICE 15.13 m²

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CHANDLER G118

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In order to compare the performances of the archetypal LTs, t-test and one way analysis of variance (ANOVA) tests were run in order to determine if there are significant differences between different seating groups (front, middle, back or left, middle, right) or different orientation. In the next and final step different lecture theaters were analyzed, chosen from different archetypal categories: 1. Wilkins Gustave Tuck LT because of the relatively small windows compared to its size 2. Chanlder G10 because of the north orientation of the windows -and the available data of monitoring both from near the window and away from it 3. Medawar G02 Watson LT with side windows and also naturally ventilated 4. Drayton B03 Ricardo LT with 2-sided openings

4. RESULTS 4.1.THERMAL COMFORT In regards to thermal comfort the research hypothesis was that even if windows influence thermal comfort, their existence has a positive impact on students’ concentration. First step was to regress monitoring temperature and actual thermal vote for each lecture theater. It seems (Graph 1,2) that there are no significant differences between the overall temperatures and actual mean vote between lecture theaters with windows and no windows. More specifically, the range for both categories regarding thermal vote is from a mean of 3.5 to 5.3 (W) and 3.3 to 5.8 (NW), while the monitored temperatures are always within the acceptable range given

GRAPH 1 graph of the overall lecture theaters mean temperatures. there is a same pattern reported in both categories.

MEAN TEMPERATURE °C 50.0

no windows suggested Temperature

45.0 40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0

Chandler 118 Wilkins Gustave Tuck LT Drayton B20 Jevons LT Drayton B03 Ricardo LT Gordon Street (25) Maths 505 Gordon Square (24) 105 Gordon Street (25) D103 Gordon Street (25) Maths 500 Pearson (North East Entrance) G22 LT Chandler G10 Physics A1/3 Roberts 508 South Wing 9 Garwood LT Roberts 421 Medawar G02 Watson LT Roberts 309 Malet Place Eng 1.02 Medical Sciences 131 A V Hill LT Torrington (1‐19) 115 Galton LT Gordon Street (25) E28 Harrie Massey LT Darwin B40 LT Christopher Ingold XLG1 Chemistry LT Medawar G01 Lankester LT Cruciform B304 ‐ LT1 Anatomy G29 J Z Young LT Archaeology G6 LT Malet Place Eng 1.03 Roberts G06 Sir Ambrose Fleming LT Roberts G08 Sir David Davies LT Cruciform B404 ‐ LT2 Medical Sciences G46 H O Schild… Roberts 106 Christopher Ingold G21 Ramsay LT Bedford Way LG04 Bedford Way G03 Chadwick B05 LT Anatomy G04 Gavin de Beer LT Torrington (1‐19) B17 Basement LT

TEMPERATURE °C

windows nat. ventilated

by CIBSE Guide A (CIBSE, 1996)5. By the histograms (Graph 3,4) we can argue that generally, lecture theaters of UCL are thermally comfortable, as in both cases votes ranged between neutral and slightly cool or warm scales. It is worth mentioning, though, that in the case of lecture

CIBSE AM10 benchmarks for temperature in lecture THERMAL COMFORT theaters are 21-26°C

GRAPH 3-4 Histogram showing the percentage of thermal votes for all lecture theaters in relation to each category.

7.0

windows nat. ventilated no windows

6.0 5.0 4.0 3.0 2.0 1.0

Chandler 118 Medawar G02 Watson LT Gordon Street (25) Maths 505 Wilkins Gustave Tuck LT Physics A1/3 Pearson (North East Entrance) G22 LT Drayton B20 Jevons LT South Wing 9 Garwood LT Chandler G10 Drayton B03 Ricardo LT Gordon Street (25) Maths 500 Roberts 421 Gordon Square (24) 105 Roberts 309 Gordon Street (25) D103 Roberts 508 Medawar G01 Lankester LT Malet Place Eng 1.02 Anatomy G04 Gavin de Beer LT Christopher Ingold XLG1 Chemistry LT Bedford Way LG04 Roberts G06 Sir Ambrose Fleming LT Malet Place Eng 1.03 Cruciform B404 ‐ LT2 Torrington (1‐19) 115 Galton LT Gordon Street (25) E28 Harrie… Darwin B40 LT Anatomy G29 J Z Young LT Medical Sciences G46 H O Schild… Roberts G08 Sir David Davies LT Medical Sciences 131 A V Hill LT Cruciform B304 ‐ LT1 Roberts 106 Archaeology G6 LT Christopher Ingold G21 Ramsay LT Bedford Way G03 Chadwick B05 LT Torrington (1‐19) B17 Basement LT

GRAPH 2 Graph of MEAN VOTE for thermal comfort. As in the previous graph, there is a same pattern for both categories with voting from approximately 3.3 (slightly cool) to 5.7 (slightly warm). The lecture theaters with opened windows (natural ventilation) are noted.

MEAN VOTE

thermal comfort_NO WINDOWS 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% cold

cool

slightly cool

neutral

slightly warm

warm

hot

warm

hot

Thermal Comfort_WINDOWS 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% cold

cool

slightly cool

neutral

slightly warm

CHART 6 When voting for the ideal learning conditions, 22% of students voted for cooler environments, with 20% accounting for LT with openings.

THERMAL COMFORT FOR LEARNING_WINDOWS 100% 80% 60% 40% 20% 0% COOLER

NO CHANGE

WARMER

THERMAL COMFORT FOR LEARNING_NO WINDOWS 120% 100% 80% 60% 40% 20% 0% COOLER

WARMER

TEMPERATURE VS MEAN THERMAL VOTE 7.0

6.0 W: y = 0.1732x + 0.3313 R² = 0.1522

5.0

THERMAL VOTE

GRAPH 5 Correlation of monitoring temperature and thermal vote. Positive correlation r₁=0.38 (windows) r₂=0.63 (no windows) r₁<r₂

NO CHANGE

NW: y = 0.275x ‐ 2.198 R² = 0.4025

4.0

3.0

2.0

1.0

0.0 20.0

21.0

22.0

23.0

24.0

25.0

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TEMPERATURE °C WINDOWS

NO WINDOWS

Linear (NO WINDOWS)

Linear (WINDOWS)

theaters without openings the range is significantly higher, taking values from 3 to 6 (slightly cool to warm) while, unexpectedly, when openings do exist, the mean vote ranged from neutral to slightly warm, something that can probably support with the findings of Cai and Marmot (2013)6. Moreover, as far as the ideal conditions for learning are concerned (Graph 5,6), the majority of students seems satisfied with the learning conditions in terms of temperature, but in the case of lecture theaters with windows, 20% of participants would prefer the indoor temperature to be cooler -and not warmer as expected. That brings up the view mentioned in literature, suggesting that the ideal environments for learning are slightly cool(-0.5 in the PMV scale). Finally, the scatter diagram (Graph 7) shows that there is a weak correlation between temperature and thermal vote, with correlation coefficient 0.38 and 0.63 for LTs with windows and no windows respectively -in the case of LTs without windows there is a stronger correlation.

6 Cai and Marmot proved that thermal comfort increases with proximity to windows (see literature)

Chandler G10

1.0

13 Malet Place Eng 1.03

Bedford Way LG04

Chadwick B05 LT

Gordon Street (25) E28 Harrie Massey LT

Anatomy G04 Gavin de Beer LT

Christopher Ingold XLG1 Chemistry LT

Archaeology G6 LT

Torrington (1‐19) B17 Basement LT

Cruciform B404 ‐ LT2

Torrington (1‐19) 115 Galton LT

Roberts G08 Sir David Davies LT

Medical Sciences G46 H O Schild Pharmacology LT…

Bedford Way G03

Roberts G06 Sir Ambrose Fleming LT

Christopher Ingold G21 Ramsay LT

Roberts 106

Medawar G01 Lankester LT

Medical Sciences 131 A V Hill LT

Anatomy G29 J Z Young LT

Cruciform B304 ‐ LT1

Darwin B40 LT

Malet Place Eng 1.02

Roberts 309

Chandler 118

Pearson (North East Entrance) G22 LT

Physics A1/3

Gordon Square (24) 105

Roberts 508

Gordon Street (25) Maths 500

Drayton B20 Jevons LT

Gordon Street (25) D103

Drayton B03 Ricardo LT

MEAN VOTE

Gordon Square (24) 105 Roberts 309 Gordon Street (25) D103 Roberts 508 Gordon Street (25) Maths 500 Drayton B03 Ricardo Drayton B20 Jevons LT Chandler G10 Gordon Street (25) Maths 505 Roberts 421 Chandler 118 South Wing 9 Garwood LT Physics A1/3 Wilkins Gustave Tuck LT Pearson (North East Entrance) G22 LT Medawar G02 Watson LT Torrington (1‐19) B17 Basement LT Chadwick B05 LT Bedford Way G03 Archaeology G6 LT Christopher Ingold G21 Ramsay LT Cruciform B404 ‐ LT2 Anatomy G29 J Z Young LT Malet Place Eng 1.03 Roberts 106 Torrington (1‐19) 115 Galton LT Medical Sciences 131 A V Hill LT Bedford Way LG04 Roberts G06 Sir Ambrose Fleming LT Cruciform B304 ‐ LT1 Anatomy G04 Gavin de Beer LT Christopher Ingold XLG1 Chemistry LT Roberts G08 Sir David Davies LT Gordon Street (25) E28 Harrie Massey LT Malet Place Eng 1.02 Medical Sciences G46 H O Schild… Medawar G01 Lankester LT Darwin B40 LT

1.0

South Wing 9 Garwood LT

Medawar G02 Watson LT South Wing 9 Garwood LT Gordon Street (25) Maths 505 Gordon Street (25) Maths 500 Pearson (North East Entrance) G22 LT Roberts 508 Chandler G10 Drayton B20 Jevons LT Wilkins Gustave Tuck LT Drayton B03 Ricardo LT Physics A1/3 Roberts 309 Chandler 118 Gordon Street (25) D103 Gordon Square (24) 105 Roberts 421 Medawar G01 Lankester LT Anatomy G04 Gavin de Beer LT Malet Place Eng 1.02 Torrington (1‐19) 115 Galton LT Roberts G06 Sir Ambrose Fleming LT Archaeology G6 LT Medical Sciences G46 H O Schild… Christopher Ingold XLG1 Chemistry LT Gordon Street (25) E28 Harrie Massey LT Malet Place Eng 1.03 Cruciform B404 ‐ LT2 Bedford Way LG04 Roberts G08 Sir David Davies LT Bedford Way G03 Roberts 106 Darwin B40 LT Anatomy G29 J Z Young LT Christopher Ingold G21 Ramsay LT Medical Sciences 131 A V Hill LT Chadwick B05 LT Cruciform B304 ‐ LT1 Torrington (1‐19) B17 Basement LT

1.0

Gordon Street (25) Maths 505

Roberts 421

Wilkins Gustave Tuck LT

Medawar G02 Watson LT

MEAN VOTE 5.0

AIR QUALITY

4.0

GRAPH 7 Mean vote for air quality scale from 1 to 5 (very stuffy to very good)

3.0

2.0

neutral vote (3)

5.0

AIR MOVEMENT

GRAPH 8 Mean vote for air movement scale from 1 to 5 (draughty to still)

4.0

3.0

2.0

AIR AND CONCENTRATION

3.0

2.0

CHART 9 Mean vote for how air affects concentration scale from 1 to 3 (not at all- moderately- strongly)

4.2. VENTILATION

As far as ventilation is concerned, overall performances of LTs in terms of air quality, air movement and air affecting concentration were compared. The alternative hypothesis in that case was firstly that there is a difference in air quality rating between the two categories and secondly that there are differences between the way LTs with opened windows affect students’ performances.

A closer look at the diagrams reveals that there is a similar pattern in the way the values from max-

imum to minimum form. It is worth mentioning that Roberts 309, which is one of the natural ventilated theaters (open windows during the survey) accounts for the higher mean voting in terms of air quality receiving a average score of 4 (good).

4.3. LIGHTING GRAPH 10 Lighting: Distribution of lighting votes. Students are overall satisfied by the lighting in UCL lecture theaters

100% 90%

% OF RESPONCES

80% 70% 60% 50% 40% 30% 20% 10% 0% 1

VOTES FOR GENERAL LIGHTING WINDOWS

NO WINDOWS

GRAPH 11 Lighting: Distribution of lighting votes. Students are overall satisfied by the lighting in UCL lecture theaters

GENERAL LIGHTING 4.0

3.0

1.0

Drayton B20 Jevons LT Gordon Square (24) 105 Drayton B03 Ricardo LT Roberts 508 Gordon Street (25) Maths 505 Wilkins Gustave Tuck LT Roberts 421 Medawar G02 Watson LT Gordon Street (25) D103 Roberts 309 South Wing 9 Garwood LT Chandler G10 Gordon Street (25) Maths 500 Physics A1/3 Chandler 118 Pearson (North East Entrance)… Medical Sciences 131 A V Hill LT Medical Sciences G46 H O… Anatomy G04 Gavin de Beer LT Christopher Ingold XLG1… Cruciform B304 ‐ LT1 Medawar G01 Lankester LT Christopher Ingold G21… Roberts G08 Sir David Davies LT Archaeology G6 LT Bedford Way G03 Gordon Street (25) E28 Harrie… Chadwick B05 LT Malet Place Eng 1.03 Malet Place Eng 1.02 Anatomy G29 J Z Young LT Roberts G06 Sir Ambrose… Darwin B40 LT Cruciform B404 ‐ LT2 Torrington (1‐19) B17… Torrington (1‐19) 115 Galton LT Bedford Way LG04 Roberts 106

2.0

As far as lighting is concerned, the analysis was focused on whether natural lighting can affect performance by comparing the results for general lighting ratings again for all LTs. The questionnaire included questions concerning both general lighting in each lecture theater, as well as light quality where the participant was seating. Mean votes for general lighting show a normal distribution for both cases (Graph 10) -in the case of lecture theaters with openings, the distribution is slightly moved to the left, reflecting a small percentage (10%) of lecture the-

GRAPH 12: GENERAL DESIGN

GENERAL DESIGN VOTING 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% VERY POOR

POOR

NEUTRAL

GOOD

NO WINDOWS

VERY GOOD

WINDOWS

GRAPH 13: General design voting. There is a similar distribution for minimum to maximum mean votes, which in most cases are above the neutral vote (OK).

MEAN VOTE

GENERAL DESIGN 5.0

4.0

3.0

Darwin B40 LT

Cruciform B304 ‐ LT1

Roberts 106

Anatomy G29 J Z Young LT

Malet Place Eng 1.02

Roberts G08 Sir David Davies LT

Medical Sciences 131 A V Hill LT

Roberts G06 Sir Ambrose Fleming LT

Bedford Way LG04

Christopher Ingold G21 Ramsay LT

Cruciform B404 ‐ LT2

Torrington (1‐19) B17 Basement LT

Christopher Ingold XLG1 Chemistry LT

Gordon Street (25) E28 Harrie Massey LT

Malet Place Eng 1.03

Torrington (1‐19) 115 Galton LT

Bedford Way G03

Anatomy G04 Gavin de Beer LT

Chadwick B05 LT

Archaeology G6 LT

Medawar G01 Lankester LT

Roberts 421

Pearson (North East Entrance) G22 LT

Chandler 118

Roberts 309

Medawar G02 Watson LT

Roberts 508

Physics A1/3

Chandler G10

Gordon Street (25) Maths 505

Wilkins Gustave Tuck LT

South Wing 9 Garwood LT

Drayton B20 Jevons LT

Drayton B03 Ricardo LT

Gordon Street (25) Maths 500

Gordon Square (24) 105

Gordon Street (25) D103

1.0

Medical Sciences G46 H O Schild…

2.0

aters where the light was rated as dim. In the case of lecture theaters without windows all votes are accumulated in the center -100% of the mean of the votes was 3 (OK). Nonetheless, we must take into account that all surveys where being conducted under artificial and not natural lighting, which was a major limitation for the analysis.

4.4 GENERAL DESIGN

The last parameter to be examined is general design. If general design influences concentration, then in the case of lecture theaters with windows there may be a trend of increased concentration -as generally windows aesthetically improve indoor space. A closer look at the graphs, though, reveals that not only there is no difference in distributions (Graph 12); but also that it is a LT without windows that ranked first in terms of design.

4.5 SCATTER PLOTS

Scatter plots were made in order to test the correlation between the our variables and general concentration in each lecture theater. TABLE 3: CORRELATION COEFFICIENTS

correlation THERMAL COMFORT AIR/CONCENTRATION coefficient r1 -0.62 -0.22 WINDOWS r2 NO WINDOWS -0.22 -0.46

AIR QUALITY 0.65 0.63

AIR MOVEMENT -0.22 0.24

LIGHTING

GENERAL DESING

0.51 -0.02

0.68 0.78

GRAPH 14-17: SCATTER PLOTS

CONCENTRATION VS THERMAL COMFORT 7.0

THERMAL COMFORT

6.0

NW: y = ‐0.5229x + 5.9853 R² = 0.0491

5.0

W: y = ‐1.7425x + 10.527 R² = 0.3937

4.0 3.0 2.0 1.0 1.0

2.0

3.0

4.0

5.0

CONCENTRATION WINDOWS

NO WINDOWS

Linear (NO WINDOWS)

Linear (WINDOWS)

CONCENTRATION VS GENERAL DESIGN

MEAN VOTE DESIGN

5.0 W: y = 0.9643x ‐ 0.0261 R² = 0.4599

4.0

NW: y = 0.9208x + 0.1869 R² = 0.6021

3.0 2.0 1.0 1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

MEAN VOTE CONCENTRATION WINDOWS

NO WINDOWS

Linear (NO WINDOWS)

Linear (WINDOWS)

AIR AFFECTING CONCENTRATION AND GENERAL CONCENTRATION AIR AND CONCENTRATION

3.0

y = ‐0.1788x + 2.8922 R² = 0.2161

y = ‐0.1515x + 2.7699 R² = 0.0499

2.0

1.0 1.0

2.0

3.0

4.0

5.0

GENERAL CONCENTRATION windows

no windows

Linear (windows)

Linear (no windows)

CONCENTRATION VS GENERAL LIGHTING 4.0

GENERAL LIGHTING

3.5

W: y = 0.6292x + 1.0038 R² = 0.2561

3.0 2.5

NW: y= ‐0.0121x + 3.2054 R² = 0.0005

2.0 1.5 1.0 0.5 0.0 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

CONCENTRATION WINDOWS

NO WINDOWS

Linear (WINDOWS)

Linear (NO WINDOWS)

4.5

There is a weak correlation between concentration votes and thermal comfort especially in the case of windows with correlation coefficient r=-0.62 (negative correlation). The strongest correlations are reported in the cases of general design and air quality -general design and concentration in lecture theaters without windows have a correlation reaching 0.8.

4.6 USING CATEGORIZATION AND ARCHETYPES

Having separated lecture theaters with windows in different categories (Table 2, see also appendix), ANOVA method was used for comparing: 1. lecture theaters with back and side windows, as they comprise the largest categories and without windows. 2. Lecture theaters with northern, eastern, western or southern windows. The results are not statistically significant, so we have to accept the nul hypothesis, i.e. there is no difference between back, side or no windows and concentration etc. Moreover, in a bigger scale an attempt to compare typical LTs was made. The chosen LTs are: Watson LT: natural ventilated, north oriented, back windows Chanlder G10: mechanical ventilated, north oriented, back windows Ricardo LT: two-side openings Wilkins Gustave: windows outside the seating area and small compared to its size.

TABLE 4 ANOVA table comparing overall concentration and the position of windows. The critical value for F (Fcrit) is bigger that F value, therefore the null hypothesis is not rejected Also p-value > 0.05

null hypothesis: there is no difference between how different positions of windows affect concentration alternative hypothesis: there is a difference between different window positions and students' concentration SUMMARY Groups BACK WINDOWS SIDE WINDOWS NO WINDOWS

6 6 22

ANOVA Source of Variation Between Groups Within Groups Total

TABLE 5 ANOVA table comparing overall concentration in 3 different groups -different orientation. The critical value for F (Fcrit) is bigger that F value, therefore the null hypothesis is not rejected Also p-value > 0.05

Count

SUMMARY Groups North East‐West South

Sum 20.63 19.96 77.03

Average 3.44 3.33 3.50

Variance 0.04 0.12 0.06

0.15 2.08

2 31

2.23

F 0.07 0.07

1.09

P‐value 0.35

F crit 3.30

null hypothesis: there is no difference in concentration in LTs with different orientation Count 6.00 6.00 2.00

ANOVA Source of Variation Between Groups Within Groups

SS 0.20 3.23

Sum Average Variance 25.92 4.32 0.32 26.88 4.48 0.32 8.27 4.13 0.02

df 2.00 11.00

MS 0.10 0.29

F 0.34

P‐value 0.72

F crit 3.98

null hypothesis: there is no difference in how students rate general design with different winTABLE 6 LECTURE THEATER DESIGN dows positioning ANOVA table comparing SUMMARY Groups Count Sum Average Variance lecture theater design between BACK WINDOWS 6.00 20.01 3.33 0.07 6.00 19.96 3.33 0.12 3 different groups -different SIDE WINDOWS NO WINDOWS 22.00 77.03 3.50 0.06 position of windows. ANOVA Source of Variation Between Groups Within Groups Total

0.23 2.24

df 2.00 31.00

2.47

33.00

F 0.11 0.07

1.56

P‐value 0.23

F crit 3.30

Thermal Comfort ‐ seat position 7

GRAPH 18-21: Mean votes per seating group (front, middle, back or left, middle right). The line graphs show how votes are formed from one side of the lecture theater to the other. A simplification is made when considering the line connection two different points as linear.

DISTANCE FROM WINDOWS

BACK/LEFT

Wilkins Gustave

MIDDLE

Chandler G10

FRONT/RIGHT

Watson LT

Medawar Ricardo

AIR QUALITY_seat potition 5.00

4.00

3.00

2.00

1.00

BACK/LEFT

MIDDLE Chandler G10

Watson

FRONT/RIGHT

Wilkins Gustave

Ricardo

neutral vote

LIGHTING_seat position 5.00

4.00

3.00

2.00

1.00

BACK/LEFT

MIDDLE Wilkins Gustave

Chandler G10

FRONT/RIGHT Watson

Ricardo

neutral vote

CONCENTRATION ‐ Seat position 5.00

VOTES

4.00

3.00

• Chandler G10 and Watson LT show a discrepancy between back seating and front with lower votes -3 i.e. slightly cold- closer to windows, something that aggrees with monitored temperature as well (Graph 18) • Watson LT ranked first in air quality voting regardless of seating position. Ricardo voting improved towards the south window, with air quality characterized as stuffy towards the northern window1. (Graph 19) • There is not an obvious correlation between concentration and the distance from windows. •Watson LT has also a better performance in air quality regardless of seat position. •In Watson LT lighting is voted as dim near window, while it seems to ameliorate in the case of Chandler G10. If we take into account that there was

1 windows during survey were closed

2.00

1.00

BACK/LEFT

MIDDLE

FRONT/RIGHT

DISTANCE FROM WINDOW

Chandler G10

Watson

Wilkins Gustave

Ricardo

neutral vote

artificial lighting during the lectures we can conclude that probably results are influenced by the existence of artificial light.

5. DISCUSSION

1.1. INTERPRETATION OF RESULTS

5.1.1 Thermal Comfort Thermal comfort is a complicated subject as it is influenced by many different parameters. Within the frame of this report, we attempted to correlate thermal comfort and the existence of windows, as we assumed that thermal comfort can influence studentsâ&#x20AC;&#x2122; concentration. First of all, one can argue that lecture theaters of UCL have an overall good performance. Monitoring temperatures were within the proposed benchmarks (CIBSE,2009) and thermal vote on behalf of students is in most cases neutral. In case of LTs with windows, thermal vote was sometimes up to slightly cool and students asked for cooler learning environments. There are two assumption made by these results: 1. The fact that lecture theaters with windows have a more narrow range of thermal vote2 may support the view of Cui et al. suggesting that the existence of windows can increase not only performance, but also thermal comfort3. 2. the fact that people asked for cooler temperature indicates that users can accept slightly cooler temperatures in learning environments -that can be used for reducing the consumed energy for heating. Furthermore, the results indicate that there is a weak negative correlation between thermal comfort and concentration; the more the temperature rises the less concentrated the studentsâ&#x20AC;&#x2122; are. 3. Because of the fact that participants in lecture theaters with windows asked for cooler environments, a future suggestion should be to use the existing windows for ventilation more often -only four lecture theaters had opened windows during the survey. 5.1.2. Ventilation As far as ventilation is concerned, the analysis showed that there are no extreme differences in air quality and air movement between lecture theaters with and without windows, nor air affects concentration in a different way. That indicates that both natural and mechanical ventilated theaters perform fairly well. Nevertheless, it is worth mentioning that the LT with the highest rating in terms of air quality is Medawar Watson LT -with a significant difference compared to other lecture theaters. As mentioned before, it is a naturally ventilated theater with windows from the north side -which usually is best for fresh air intakes. Furthermore, air quality is the second most essential parameter influencing concentration (r=0.65 approximately for both cases, see Table 3). That can be used in future designs, that should take into account the use of openings for natural ventilation -that would help in reducing CO2 emissions and energy consumption, and at the same time improve concentration levels of students.

2 Neutral to slightly warm, in contrast to lecture theaters with windows which have a range from warm to cool 3 We should take into account that the external and internal temperatures were very close, i.e. we can assume that the differences do not occur because of differences in mean external or internal temperatures.

5.1.3. Lighting Lighting was the most demanding category in terms of analysis, as in all lecture theaters there was artificial lighting at the time of the surveys. This fact can alter the available data relative to lighting -and especially daylighting- and how it affects concentration. Generally, lighting in both examined categories is voted as OK -accounting for very high percentages reaching 100%. There is no correlation between lighting and concentration levels, probably because there were no classrooms in UCL facing relevant problems. In other words, there was a limitation in examining how light through windows affect students as the lighting level was always appropriate. Even when examining specific lecture theaters in section 4.6 , lighting votes remained steady throughout the lecture theater, and windows did not affect visibility levels neither positively nor negatively. Additionally, one can argue that due to the fact that surveys were carried out during winter months, the daylight is not as strong as it can be during summer in order to create relevant problems, such as glare. 5.1.4. General Design General design plays a major role in concentration levels, something that supports the findings of Yarbrough (2001) regarding students’ achievement and architectural design. Nonetheless, there is no correlation between the existence of windows and higher design rating, as presented in Graphs 9, 10 and also proved by ANOVA. There are other parameters influencing the way users perceive architectural space. There is a strong likelihood that the results would be far more accurate and comparable, if the questionnaire included questions more relevant to the existence of windows. Nevertheless, the fact that general design plays a significant role in concentration can be used in order to optimize learning environments at UCL Lecture theaters.

5.2. LIMITATIONS

Limitations that appeared during the process were: • Missing data -architectural plans, not completed questionnaires •Insufficient data relevant to windows -for example more specific answers in the questionnaire •construction materials of lecture theaters, that could help in making assumption regarding different performances •Different days and hours of surveys that made it difficult to compare because of the different external conditions. Future research could examine more specifically the different aspects that windows can affect in more detail taking into account the above limitations.

6. CONCLUSION This report constitutes an attempt to correlate the existence of windows to students’ concentration. Lecture theaters were divided in two main categories -with and without openingsand they were compared in regards to:

•thermal comfort vote •air quality, air movement and air affecting concentration votes •lighting quality voting •general design voting •monitored temperature

Lecture theaters of UCL of both categories showed generally high performances and similar distributions of votes. After statistical analysis, the different variables mentioned above were regressed with the ratings for general concentration. Results showed that the most significant impact on concentration has general design and air quality. In order to positively enhance this impact and, subsequently, improve the performance of lecture theaters and concentration levels, careful architectural design, renovation of lecture theaters and natural ventilation are suggested. Windows can play a significant role if incorporated in the architectural design; they can improve the space aesthetically without negatively affecting students in any other way and at the same time they can help in making lecture theaters more energy efficient.

7. BIBLIOGRAPHY

Aries, M.B.C., Veitch, J. a. & Newsham, G.R., 2010. Windows, view, and office characteristics predict physical and psychological discomfort. Journal of Environmental Psychology, 30(4), pp.533–541. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0272494409001078. Ashrae, 55 ‐ Thermal Environmental Conditions for Humanr Occupancy. , 0(4). Cai, J., Ap, L. & Associates, M.M., 2013. Let the sunshine in : Perception of windows by Chinese office workers. , 4(3), pp.1–13. Cibse, 2005. Natural ventilation in non‐domestic buildings, CIBSE Applications Manual AM10:2005. Clatworthy, P. & Kooymans, R., 2001. Academics ’ and Students ’ Perceptions of the Effect of the Physical Environment on Learning. Seventh Annual Pacific‐Rim Real Estate Society Conference, 61(January), pp.21–24. Clements‐Croome, D.J. et al., 2008. Ventilation rates in schools. Building and Environment, 43(3), pp.362–367. Available at: http://www.sciencedirect.com/science/article/pii/S0360132306003568\nhttp://www.scie ncedirect.com/science?_ob=MImg&_imagekey=B6V23‐4MK60WB‐2‐ 5&_cdi=5691&_user=7600538&_pii=S0360132306003568&_origin=&_coverDate=03/31/2 008&_sk=999569996&view=c&wchp=dGLzVlz‐z. Fleming, D. & Storr, J., 1999. The impact of lecture theatre design on learning experience. Facilities, 17(7/8), pp.231–236. Hancock, P. a et al., 2015. A Meta‐Analysis of Performance Response Under Thermal Stressors. , 49(5), pp.851–877. Harrigan, M. (1999). Plugging into energy savings. The American School Board Journal, 186(1), 12‐ 16. Mavrogianni, A. et al., 2012. Building characteristics as determinants of propensity to high indoor summer temperatures in London dwellings. Building and Environment, 55, pp.117–130. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0360132311004197. Mishra, A.K. & Ramgopal, M., 2015. A comparison of student performance between conditioned and naturally ventilated classrooms. Building and Environment, 84, pp.181–188. Available at: http://www.sciencedirect.com/science/article/pii/S0360132314003618.

Mumovic, D. et al., 2009. Winter indoor air quality, thermal comfort and acoustic performance of newly built secondary schools in England. Building and Environment, 44(7), pp.1466– 1477. Available at: http://dx.doi.org/10.1016/j.buildenv.2008.06.014. O'Connor, M.J. (1999). Study shows grades improve in daylit spaces. The AIA Journal, 88(8), 31. Romney, B.M. (1975). The effects of windowless classrooms on the cognitive and affective behavior of elementary school students. (ERIC Document Reproduction Service No. ED 008565) Rosén, K.G. & Richardson, G., 1999. Would removing indoor air particulates in children’s environments reduce rate of absenteeism ‐ A hypothesis. Science of the Total Environment, 234, pp.87–93. Schneider, M., 2002. Do School Facilities Affect Academic Outcomes? Steadman, P., 2001. Binary Encoding of a Class of Rectangular Built‐Forms. 3rd International Space Syntax Symposium, Atlanta, 2001, pp.09.1–09.16. Tomas, R., 1996. Environmental Design, Yarbrough, K., 2001. The relationship of school design to academic achievement of elementary school children. Available at: http://athenaeum.libs.uga.edu/handle/10724/5380.

199 191

117 NETWORK ROOM

G99

G91 IT

G97

G10 LECTURE THEATRE

152 CORRIDOR

8B STORE

10 COMMON ROOM 8A OFFICE 6 OFFICE

5 DEAN'S OFFICE MEETING ROOM

ROBERTS 421

AREA 151 CORRIDOR

6A OFFICE

4 MEETING ROOM

G26 COLD ROOM

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

103 LECTURE THEATRE

A5 OFFICE

A2 OFFICE

3A OFFICE

424 OFFICE 14.40 m²

426 OFFICE 16.95 m²

A4 OFFICE

1A OFFICE

3 WAITING 481 AREA

421 LECTURE THEATRE 91.62 m²

422 LECTURE THEATRE 99.56 m²

425 OFFICE 12.54 m²

427 OFFICE 14.50 m²

A6 OFFICE

1 OPEN PLAN OFFICE

181A LIFT 487

2 OFFICE 485 DUCT 484 DUCT

483 LOBBY

CHANDLER G118

423 OFFICE 10.56 m²

RODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

119 PLANT

118 LECTURE THEATRE

G98

504B OFFICE

CHANDLER G10

Door G08 & G10. G18 Staff Room. Small cupb'd G92. Dec. '14

July '15 C

SIZE

Ground Floor Drawn: S.S.

Scale: 1:100 @ A1

UCL ESTATES

GOWER STREET, LONDON WC1E 6BT

105 LECTURE ROOM

106 OFFICE

Lecturer Desk

Desk

106A

Blackboard

Flat Roof

Date

Jan. '14

Description

DRAWING UPDATED

DWG. NO.

1:100 @ A1

Scale:

002 - 01 - 3

FIRST FLOOR

25 GORDON STREET

March 1998

Date:

Drawn:

GOWER STREET, LONDON WC1E 6BT

UCL ESTATES

Rev.

rev

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

MEDAWAR BUILDING

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

PHYSICS

B19 CLASSROOM

198

STORE

G09 STAFF MEETING

505 LECTURE THEATRE

G18 STAFF ROOM G16 OFFICE G15 OFFICE G13 OFFICE 7 OPEN PLAN OFFICE G04 WORKROOM

A98 LIFTS

G03 OFFICE

G07A

Description Date

G94 FREEZER RROM G25 PREP ROOM G20B OFFICE

Partition G12 & G12A removed to make G12 Microscope Room.

DRAWING UPDATED MAY '13 A

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

GORDON STREET D103

G01 ESTER LECTURE THEATRE

BACK WINDOWS

G05 OFFICE

8C STORE G07B MALE WC

G19 LAB

G90A LIFT

G22 LAB

G92A G92 CORRIDOR G90 LIFT LOBBY G89

12A OFFICE 9 GARWOOD LECTURE THEATRE

G06 FEMALE WC

Desk

G07 DDA WC

EQUIPMENT

G21 G20A OFFICE G17A OFFICE

G24 LAB G23 OFFICE G20 LAB G17 OFFICE G14 LAB

24 14 OFFICE G93 CORRIDOR

MALET PLACE 505 G12 MICROSCOPE ROOM

16 OFFICE 11 OFFICE G11 HUB ROOM

18 OFFICE G17B OFFICE

21A 13 OFFICE

ROBERTS 309

G08 RECEPTION

15 OFFICE G91 ENTRANCE LOBBY

20 OFFICE 17 OFFICE

SOUTH WING G11A

22 OFFICE 19 OFFICE RESOURCES

21 MEETING ROOM

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

1. ONE-SIDE

GORDON SQUARE

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

Rev.

Aug. 1998 Date:

rev

037 - 01 - 1

DWG. NO.

BACK AND FRONT

G10 OFFICE

FRONT WINDOWS

G02 WATSON LECTURE THEATRE

Date

Description

GOWER STREET, LONDON WC1E 6BT

Sep, 1998

DWG. NO.

026 - 01 - 3

First Floor

24 GORDON SQUARE

Scale: 1:50 @ A1

Date:

Drawn: Wale

UCL ESTATES

Rev.

8. APPENDIX SIDE WINDOWS

PHYSICS A1/3 A7 OFFICE

A99 A97 A96

ENTRANCE

WATSON A8 OFFICE

488 DUCT

CORRIDOR

CLEANER

181 486 Junction 420A South Stair WC

420 WC

DUCT

2A STORE 489 LIFT

490 LIFT LOBBY

491 STAIR A

NDE CENTRE CORRIDOR

482 DUCT

430 OFFICE 10.31 m²

429 OFFICE 13.81 m²

428 OFFICE 21.06 m²

WILKINS GUSTAVE

rev

AIR MOVEMENT_ seat position

5.00 PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

1. THREE-SIDE

1. TWO-SIDE

4.00 PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

RICARDO B02 LOBBY B03 RICARDO LECTURE THEATRE

B01 PLANT ROOM

B04 CLASSROOM

A11 OFFICE

A25 OFFICE

A30 OFFICE

2.00

A28 OFFICE

A95 LIFT

A15 PRINT ROOM

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

PLANT ROOM BELOW LECTURE THEATRE

A9 OFFICE

3.00

A27 LIBRARY A17 COMMON ROOM

COMMON ROOM

1.00

BACK/LEFT

A19 PC CLUSTER ROOM

A94D

A94A

A27B

A21

G01B PLANT ROOM

A94B

A94

A17A

A93A

A94C

A93B

A14 OFFICE

Watson

Wilkins Gustave

Ricardo

neutral vote

EXPANSION JOINT

A93

EXPANSION JOINT

A88 ELECT. DISTRIB. A12 OFFICE

Chandler G10

A27A

HOBO SPECIFICATIONS A92

Physics Building Part 4th Floor

A10 OFFICE

FRONT/RIGHT

Axis Title

A24 OFFICE

A92A

A93C

MIDDLE

A26 OFFICE

A16 OFFICE

A18 OFFICE

A90 CLEANER

A89 DUCT

A91 A22 OFFICE

A23 FEMALE TOILET

A20 OFFICE A87

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

LAN

JEVONS

B20 JEVONS LECTURE THEATRE 406 MEETING ROOM 410 TEACHING ROOM

C Rev.

Nov.' 14

A94D Added

Date

Description

UCL ESTATES

GOWER STREET, LONDON WC1E 6BT

LINK BRIDGE

Drawn: S.S. Date:

Jan. 1996

Scale: 1:100 @ A1

PHYSICS BUILDING 405 DA OFFICE

http://www.onsetcomp.com/products/data-loggers/u12012 Fourth Floor

499 STAIR B

404A ADMIN OFFICE

408 DATA ROOM

412 OPEN HUB SPACE

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

500 LECTURE THEATRE

MALET PLACE 500

496 DUCT

404 RECEPTION

495 DUCT

402 OFFICE 9.28 m²

DWG. NO.

006 - 01 - 7

rev

497

CORRIDOR

498 LIFT LOBBY

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

409A

LIFT 2 493

419 OFFICE 23.91 m²

Rev.

Jun. '14 417 OFFICE Date 11.50 m²

DRAWING UPDATED 413 415 OFFICE OFFICE Description 15.14 m² 15.70 m²

409 OFFICE 14.84 m²

411 OFFICE 15.13 m²

407 OFFICE 15.20 m²

403B OFFICE 15.34 m²

UCL ESTATES 494 GOWER STREET, LONDON WC1E 6BT DUCT

403 OFFICE 14.05 m²

DUCT

LIFT 1 492 E DUCT

STANDARD DEV. AND SAMPLE SIZE 401 MALE WC

THERMAL COMROFT TEMPERATURE AIR QUALITY AIR‐CONCENTRATION AIR MOVEMENT LIGHTING OVERALL LIGHTING Drawn: S.S. THERMAL COMROFT TEMPERATURE AIR QUALITY AIR‐CONCENTRATION OVERALL LIGHTING LT01 1.50 0.70 AIR MOVEMENT LIGHTING 0.66 0.70 0.63 0.61 Date: Jan. 1997 1.50 LT02 0.70 0.66 0.70 0.63 0.61 0.88 0.74 0.63 0.74 0.63 0.59 Scale: 1:100 @ A1 0.88 LT03 0.74 0.63 0.74 0.63 0.59 1.02 0.75 0.61 0.75 0.73 0.66 1.02 LT04 0.75 0.61 0.75 0.73 0.66 1.17 0.73 0.66 0.73 0.71 0.75 SOUTH WING BUILDING 1.17 LT05 0.73 0.66 0.73 0.71 0.75 1.21 0.96 0.85 0.96 1.15 1.24 1.21 LT06 0.96 0.85 0.96 1.15 1.24 1.05 0.71 0.62 0.71 0.64 0.75 1.05 LT07 0.71 0.62 0.71 0.64 0.75 1.31 0.82 0.59 0.82 0.82 0.59 1.31 LT08 0.82 0.59 0.82 0.82 0.59 1.19 0.79 0.72 0.79 0.76 0.78 404,404A,405,406,408,410,and 412 updated B SEP. '14 1.19 LT09 0.79 0.72 0.79 0.76 0.78 1.01 0.73 0.58 0.73 Rooms 0.83 0.60 A OCT. '11 DRAWING UPDATED First Floor 1.01 0.73 0.58 0.73 0.83 0.60 LT10 1.07 0.73 0.66 0.73 Description 0.76 0.77 Rev. Date 1.07 LT11 0.73 0.66 0.73 0.76 0.77 0.89 0.73 0.68 0.73 0.81 0.85 DWG. NO. 012 - 01 - 4 1.21rev UCL ESTATES 0.89 LT12 0.73 0.68 0.73 0.81 0.85 0.73 0.69 0.73 0.72 0.69 1.21 LT13 0.73 0.69 0.73 0.72 0.69 1.10 0.86 0.66 0.86 0.63 0.63 1.10 LT14 0.86 0.66 0.86 0.63 0.63 1.20 0.73 0.72 0.73 0.75 0.72 1.20 LT15 0.73 0.72 0.73 0.75 0.72 1.08 0.66 0.68 0.66 0.73 0.66 Drawn: S.S. 1.08 LT16 0.66 0.68 0.66 0.73 0.66 1.26 0.89 0.65 0.891994 0.69 0.63 Date: October 1.26 LT17 0.89 0.65 0.89 0.69 1.15 0.77 0.63 0.77 0.84 1.07 Scale:0.63 1:100 @ A1 1.15 LT18 0.77 0.63 0.77 0.84 1.07 0.63 0.56 0.64 0.56 0.56 0.56 0.63 LT19 0.56 0.64 0.56 0.56 0.56 0.84 0.62 0.57 0.62 0.55 0.56 ROBERTS BUILDING 0.84 LT20 0.62 0.57 0.62 0.55 0.56 0.91 0.70 0.67 0.70 0.56 0.70 0.91 LT21 0.70 0.67 0.70 0.56 0.70 1.03 0.65 0.74 0.65 0.55 0.51 1.03 LT22 0.65 0.74 0.65 0.55 0.51 0.96 0.67 0.66 0.67 0.50 0.58 0.96 LT23 0.67 0.66 0.67 0.50 0.58 1.63 0.79 0.64 0.79 1.02 0.79 1.63 LT24 0.79 0.64 0.79 1.02 0.79 0.70 0.51 0.33 0.51 0.55 0.50 Fourth Floor 0.70 LT25 0.51 0.33 0.51 0.55 0.50 0.98 0.73 0.54 0.73 0.77 0.75 0.98 LT26 0.73 0.54 0.73 0.77 DWG.0.75 NO. 0.96 1.38 0.96 0.89 0.87- 7 0.92 045 - 01 rev 1.38 LT27 0.96 0.89 0.96 0.87 0.92 0.66 0.77 0.58 0.77 0.90 0.79 0.66 LT28 0.77 0.58 0.77 0.90 0.79 0.94 0.57 0.71 0.57 0.56 0.50 0.94 LT29 0.57 0.71 0.57 0.56 0.50 0.88 0.64 0.57 0.64 0.57 0.73 0.88 LT30 0.64 0.57 0.64 0.57 0.73 0.99 0.81 0.55 0.81 0.74 0.71 0.99 LT31 0.81 0.55 0.81 0.74 0.71 0.90 0.80 0.76 0.80 0.65 0.77 PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT 0.90 LT32 0.80 0.76 0.80 0.65 0.77 1.20 0.84 0.59 0.84 0.59 0.59 1.20 LT33 0.84 0.59 0.84 0.59 0.59 1.08 0.80 0.63 0.80 0.76 0.57 1.08 LT34 0.80 0.63 0.80 0.76 0.57 1.26 0.67 0.60 0.67 0.74 0.61 1.26 LT35 0.67 0.60 0.67 0.74 0.61 0.64 0.72 0.56 0.72 0.65 0.54 0.64 LT36 0.72 0.56 0.72 0.65 0.54 1.36 0.78 0.70 0.78 0.53 0.60 1.36 LT37 0.78 0.70 0.78 0.53 0.60 1.38 0.72 0.54 0.72 0.55 0.54 1.38 LT38 0.72 0.54 0.72 0.55 0.54 1.00 0.67 0.67 0.67 0.50 0.56 1.00 0.67 0.67 0.67 0.50 0.56

365 ENGINEERING FRONT BUILDING

GOWER STREET, LONDON WC1E 6BT

15m

PRODUCED BY AN AUTODESK EDUCATIONAL PRODUCT

SAMPLE SIZE 75.00 113.00 134.00 124.00 36.00 66.00 88.00 123.00 91.00 102.00 202.00 120.00 125.00 80.00 68.00 77.00 37.00 46.00 32.00 36.00 47.00 34.00 48.00 28.00 101.00 31.00 45.00 32.00 47.00 41.00 43.00 55.00 104.00 30.00 31.00 46.00 32.00 63.00