Indoor environment in a digital future - Master thesis - s154397 - s153767 (1)

INDOOR ENVIRONMENT IN A DIGITAL FUTURE

Data Collection, Analysis and Visualisation

Keywords: IEQ, productivity, IoT devices, data visualisation.

Masters Thesis in Architectural Engineering

July, 2020

By

Feodora Olivia Frisesdal - s153767

Rebekka Katrine Pallesen - s154397

Supervisor

Jørn Toftum, Professor - Department of Civil Engineering

Co-supervisor

Emilie Patricia Dam-Krogh, PhD student - Department of Civil Engineering

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Feodora Olivia Frisesdal

DTU, Department of Civil Engineering, Brovej, Building 118, 2800 Kgs. Lyngby Denmark

www.byg.dtu.dk

Preface

This Master thesis has been prepared over five months at the Section for Indoor Environment

Department of Civil Engineering, at the Technical University of Denmark, DTU, in partial fulfilment

for the degree Master of Science in Architectural Engineering. The project is credited 32.5 ECTS

points.

Despite some complications related to COVID-19, we are glad, grateful and proud of the final

outcome of this master thesis. The process of writing this thesis would not have been as interesting

and educative without valuable contribution from different people.

We would therefore like to thank our supervisor Professor Jørn Toftum for always making time to

provide us with feedback and advise us. We would also like to thank our co-supervisor PhD.

student Emilie Patricia Dam-Krogh for the investment in our project and understanding of our

creative aspects and visual ideas.

Furthermore, we would like to thank the two companies, who allowed us to perform IEQ investigations

in their offices and for filling in our questionnaires. In addition to this, thank you to Jesper

Dyhr and Ole Hansen from Expan, and Niels Peter Frisesdahl and Hans Jørgen Frisesdahl from

Frisesdahl A/S for sharing information about challenges related to renovation and participating

in our feedback sessions.

Kongens Lyngby, July 15, 2020

Feodora Olivia Frisesdal

Rebekka Katrine Pallesen

Abstract

Poor indoor environment quality (IEQ) can cause health issues, allergies, discomfort, lack of

concentration, fatigue, and many other issues. In office environments, poor IEQ and its related

symptoms can result in both reduced productivity and reduced ability to work. The costs caused

by and related to poor IEQ include, but are not limited to, medical treatments, loss of work, and

lowered productivity.

Buildings in Denmark, used for offices, businesses, stock and public administration, amount to ∼

7.2 million m 2 and work carried out in these office environments contributes to more than half of

the Danish gross domestic product. Notably, the cost of poor IEQ in Danish office buildings adds

an additional ∼ 30 billion DKK per aunnum. However, despite these facts, IEQ improvements

are often neglected in favour of other potential energy and cost savings.

The lack of current IEQ measurements and available data are two of the many reasons leading

to its neglect. As a result, poor IEQ is often referred to as an invisible danger. This master thesis

aims to make IEQ visible, measurable, and understandable to occupants and building owners.

The motivation behind this lies in the myriad possibilities to provide building owners with tools to

understand and improve IEQ in their office buildings. As such, the following work aims to use the

’Internet of Things’ (IoT) to investigate IEQ and its implications, as well as to explore means by

which decision-makers can come to view IEQ improvements more favourably.

In this thesis, the IEQ of three separate offices was investigated, using both measurements with

three IoT devices (out of five total examined devices) and occupant questionnaires. Of the

examined IoT devices, this study concluded that the uHoo and RoomAlyzer were superior for

IEQ office measurements because of their ease of use and range of measurable parameters.

Moreover, through the use of a benchmarking tool, developed alongside industry stakeholders,

the following work highlights the positive correlation between good IEQ and occupant productivity.

Throughout the development of this benchmarking tool, building owners and decisionmakers

were interviewed on multiple occasions, ensuring alignment between their needs and

the abilities of the benchmarking tool.

The project resulted in a completed benchmarking tool, consisting of weighted IEQ parameters,

a grading scheme, economic estimations, and a unique IEQ report. Given the common

neglect of IEQ in office buildings, the study concluded that the benchmarking tool’s greatest

value was its ability to allow building owners to grade the IEQ in their offices and predict economic

gains should the IEQ be improved. The project laid a foundation for future benchmarking

databases, allowing stakeholders to benchmark the IEQ in their offices while simultaneously

sharing their knowledge, experiences, and expertise.

Resumé

Dårligt indeklima kan forårsage helbredsproblemer, allergier, ubehag, lav koncentrationsevne,

træthed osv. I kontormiljøer kan dårligt indeklima og dets relaterede symptomer resultere i både

nedsat produktivitet og nedsat arbejdsevne. De økonomiske omkostninger i kontorer forårsaget

af dårligt indeklima er blandt andet medicinske behandlinger, sygefravær og nedsat produktivitet.

Bygninger der anvendes til kontorer, virksomheder, lager og offentlig administration i Danmark

udgør op mod ∼ 7.2 millioner m 2 . Arbejde udført i disse kontormiljøer bidrager til mere end

halvdelen af det danske bruttonationalprodukt, og omkostningerne ved dårligt indeklima i kontorbygninger

i Danmark nærmer sig årligt ∼ 30 milliarder DKK. Alligevel, nedprioriteres indeklimaet

ofte til fordel for potentielle energi- og omkostningsbesparelser.

En af grundene til, at indeklimaet nedprioriteres, er, at det sjældent måles, og at dets påvirkning

derfor er ukendt. Dårligt indeklima omtales derfor ofte som en usynlig fare. Dette speciale har

til formål at gøre indeklimaet synligt, målbart og forståeligt for både brugere og bygningsejere.

Motivationen bag dette ligger i mulighederne for at give bygningsejere værktøjer til at forstå og

forbedre indeklimaet i deres kontorbygninger. Derfor vil projektet undersøge brugen af ”Internet

of Things” (IoT) til at synliggøre indeklimaet og dets konsekvenser og endvidere, hvad der skal til

for at beslutningstagerne prioriterer indeklimaet i deres kontorer.

Indeklimaet blev derfor målt i tre separate kontorer ved hjælp af både spørgeskemaer og

målinger med tre forskellige IoT-sensorer (ud af fem undersøgt). Enhederne uHoo og RoomAlyzer

blev, på baggrund af en sammenligning af fem enheder, med henblik på brugervenlighed

og antal målbare parametre, anbefalet til indeklimamålinger i kontorer.

Med benchmarkingværktøjet, der blev udviklet med involvering af relevante aktører, fremhæver

projektet yderligere sammenhængen mellem godt indeklima og høj medarbejderproduktivitet.

I forbindelse med udviklingen af dette benchmarkingværktøj blev bygningsejere og beslutningstagere

fra kontorerne interviewet ved flere lejligheder for at sikre, at det udviklede benchmarkingværktøj

mødte deres behov og mangler.

Projektet resulterede i et værktøj bestående af en vægtning af indeklimaparametrene, en vurderingsordning,

økonomiske estimeringer og en indeklima-rapport. Med henblik på den observerede

nedprioritering af indeklimaet på kontorer, blev det i projektet vurderet, at det vigtigste

ved benchmarkingværktøjet var bygningsejernes mulighed for indeklimavurdering, samt

beregningerne af de økonomiske gevinster et forbedret indeklima kan medføre. Projektet udgør

et grundlag for en fremtidig benchmarkingdatabase, hvor aktører kan benchmarke deres kontors

indeklima og dele viden samt erfaringer.

Table of

Contents

Preface

Abstract

Resumé

iii

v

vii

1 Introduction 2

1.1 Project Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2 Project Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Indoor Environment 8

2.1 Legislative Authorities and Guidelines for IEQ in Offices . . . . . . . . . . . . . . . . . . . 10

2.2 Sick Building Syndrome (SBS) Symptoms and IEQ Parameters . . . . . . . . . . . . . . . 10

2.3 IAQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.4 Thermal Comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.5 Acoustic Comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.6 Visual Comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.7 Summary of Parameters and Symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.8 Smart Technologies, Digitalisation and IoT . . . . . . . . . . . . . . . . . . . . . . . . . 19

3 Market Research 24

3.1 Benchmarking and Certification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.2 IoT Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4 Method 36

4.1 IEQ Investigation and Analysis Process . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.2 Measurement Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.3 Offices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.4 Questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.5 Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

4.6 Benchmarking Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

4.7 Stakeholder Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

4.8 Interviews and Value Proposition Canvas . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.9 Economic Estimations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

5 Results 58

5.1 Preliminary Device Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.2 IEQ Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

5.3 Stakeholders and Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

5.4 Benchmarking Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

5.5 IEQ report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

6 Discussion 86

x


6.1 IEQ Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

6.2 Benchmarking tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

6.3 Future implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

7 Conclusion 94

7.1 Fulfilment of objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

7.2 Fulfilment of overall purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

Appendix A Desk Study Sensors 110

Appendix B Questionnaire 111

Appendix C Stakeholder matrix 117

Appendix D Interview guide 118

Appendix E Interview #1 119

Appendix F Interview #2 122

Appendix G IEQ Investigation 124

Appendix H Parameter Weighing 125

Appendix I Economic calculations 126

Appendix J IEQ Reports 129


xi

Abbreviations and

Nomenclature

BREEAM

CASBEE

DGNB

DTU

GB

GDPR

GDP

HQE

IAQ

IEQ

IoT

LBC

LEED

NAAQS

NABERS

PIR

PM

RH

SBi

SBS

SPL

TVOC

VOC

VPC

WELL

Building Research Establishment Environmental Assessment Method

Comprehensive Assessment System for Building Environmental Efficiency

German Sustainable Building Council

Technical University of Denmark

Green Building

General Data Protection Regulation

Gross Domestic Product

High Environmental Quality

Indoor Air Quality

Indoor Environmental Quality

Internet of Things

Living Building Challenge

Leadership in Energy and Environmental Design

American National Ambient Air Quality Standard

National Australian Built Environment Rating System

Passive InfraRed

Particulate Matter

Relative Humidity

Danish Building Research Institute

Sick Building Syndrome

Sound Pressure Level

Total Volatile Organic Compound

Volatile Organic Compound

Value Proposition Canvas

German Sustainable Building Council

List of Tables

2.1 CO2 criteria and guidelines [16][29] [31] . . . . . . . . . . . . . . . . . . . . . . 13

2.2 WHO guidelines for particulate matters [34] . . . . . . . . . . . . . . . . . . . . 13

2.3 TVOC guidelines from the German Federal Environmental Agency [37] . . . . . . 14

2.4 Limit values for air pollution and guidelines [38] [31] . . . . . . . . . . . . . . . . 14

2.5 Design criteria for temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.6 Design criteria for humidity in occupied spaces . . . . . . . . . . . . . . . . . . 15

2.7 Continuous sound levels from background noise [15] . . . . . . . . . . . . . . . 16

2.8 Lighting in offices [15][49] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.9 Overview of IEQ guidelines and related symptoms . . . . . . . . . . . . . . . . . 18

3.1 Certification and benchmarking tools . . . . . . . . . . . . . . . . . . . . . . . 29

3.2 Occurrence of parameters within the four IEQ categories . . . . . . . . . . . . . 32

3.3 Average accuracy for investigated devices with known accuracy . . . . . . . . 33

3.4 Market research on IoT devices . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.1 Results from checklist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.2 Temperature Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

4.3 CO2 Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

5.1 Key numbers from the 24h measurements . . . . . . . . . . . . . . . . . . . . . 61

5.2 Grading distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

5.3 Potential productivity increase . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

List of Figures

1.1 Building phases and examples of challenges within these [6] [7]. . . . . . . . . . . . . 4

1.2 Stakeholders in the building industry. . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1 SBS-symptoms [21]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2 IEQ categories and parameters [22] [15] . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.3 Average percentages of the weighting of IEQ categories [24] . . . . . . . . . . . . . . 12

2.4 Temperature and colour scale [52] . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.5 Elements of smart cities and intelligent buildings . . . . . . . . . . . . . . . . . . . . . 19

2.6 Architectural layers in IoT systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.7 Example of payload from IoT device . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.8 Limitations and possibilities for IoT devices . . . . . . . . . . . . . . . . . . . . . . . . 21

3.1 Process of the benchmarking desk study . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.2 Methods and Grading Schemes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

3.3 GB credit distribution and IEQ parameter occurrence in percentages [76] . . . . . . . 32

4.1 IEQ Investigation and analysis process . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.2 Devices and parameter coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.3 RoomAlyzer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

4.4 uHoo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4.5 Foobot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

4.6 Sens’it . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

4.7 IC-meter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

4.8 Office #1 Expan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.9 Office #2 Frisesdahl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45


4.11 Floor plan office #1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

4.12 Floor plan office #3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47


4.14 Structure and topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.15 Example of a question from the questionnaire in English . . . . . . . . . . . . . . . . . 49

4.16 Data processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

4.17 Benchmarking investigation and development. . . . . . . . . . . . . . . . . . . . . . 51

4.18 Stakeholder ’Power/Interest’-matrix [107]. . . . . . . . . . . . . . . . . . . . . . . . . 52

4.19 Value Proposition Canvas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

5.1 Evaluation of device and dashboard usability . . . . . . . . . . . . . . . . . . . . . . 60

5.2 24h CO2 measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

5.3 24h CO2 box plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

xvi


5.4 24h TVOC measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

5.5 24h TVOC box plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

5.6 24h temperature measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

5.7 24h temperature box plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

5.8 24h humidity measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

5.9 24h humidity box plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

5.10 24h noise measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

5.11 24h noise box plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

5.12 CO2 results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

5.13 TVOC results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

5.14 PM2.5 results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

5.15 Temperature results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

5.16 Humidity results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

5.17 Noise results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

5.18 Stakeholder ’Power/Interest’-matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

5.19 Value Proposition Canvas based on interviews . . . . . . . . . . . . . . . . . . . . . . 73

5.20 IEQ weighting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

5.21 Radar for office #2 and #3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

5.22 Radar office #1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

5.23 Potential cost saving savings for office #1 . . . . . . . . . . . . . . . . . . . . . . . . . 78

5.24 IEQ Report development process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

5.25 Feedback session #1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

5.26 Feedback session #2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

5.27 Grading scheme results for office #1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

5.28 Office #1’s grading scheme results for the four IEQ categories . . . . . . . . . . . . . . 81

5.29 Grading results for IEQ categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

5.30 CO2 measurements for office #1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

5.31 Symptoms related to CO2 for office #1 . . . . . . . . . . . . . . . . . . . . . . . . . . 82

5.32 Complaint related to CO2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83


xvii

CHAPTER 1

Introduction

Chapter 1 introduces the project background in a national

and international perspective. It provides an overview of the

project context including the challenges within different building

phases and the stakeholders in the industry. Furthermore, it

presents the digital aspects of the future building industry and

indoor environment on a national and institutional level. In the

light of the indoor environment quality challenges, stakeholders

and the digital possibilities, chapter 1 presents the project

description and approach.

Today many countries, including Denmark, rely on a large number of people working in offices. Currently,

an average of 36% of the European workforce, or 81.4 million people, work in an office environment

[1]. In Denmark, work carried out in office environments contributes to more than half of

the Danish gross domestic product (GPD) [2].

The large number of people working in offices is due to a significant economic shift, moving away

from the manufacturing sector and towards the knowledge-based and service sector. Consequently,

understanding the indoor environment quality (IEQ) in offices has never been more important [3].

Poor IEQ can lead to a wide range of health issues including allergies and asthma. Every year, the

economic costs of treatments, medical care, loss of work and low productivity related to dampness

and mould reach €82 billion across Europe [4]. Moreover, research conducted at the Technical

University of Denmark shows that poor IEQ in office buildings results in significant economic losses

due to lowered productivity. And the cost of poor IEQ in old office buildings in Denmark adds up to

∼30 billion DKK [2].

1.1 Project Context

Buildings used for offices, businesses, stock and public administration in Denmark amount to ∼7.2

million m 2 [5]. Most of these buildings face different challenges within the different building phases.

Challenges related to IEQ are mainly experienced in the operation and renovation phase as illustrated

in Figure 1.1.

Figure 1.1: Building phases and examples of challenges within these [6] [7].

Renovation has a great possibility of prolonging the operational phase of a building. However, in the

renovation phase of a building, the IEQ and occupants’ well-being is often neglected in favour of potential

energy savings and minimised costs [8]. As a result, a major challenge within the operational

4 INDOOR ENVIRONMENT IN A DIGITAL FUTURE

phase of an office building is poor IEQ, which affects occupants’ well-being and productivity. Improvements

hereof could potentially lead to great economic benefits. In the UK, studies have shown

that a good office environment could increase the productivity with up to 20%, which is equivalent

to £135 billion per year. In the US, research showed a national economic yield up to $12-125 billion

per year [3].

To help favour improved IEQ and occupants’ well-being in renovations, a greater understanding of

the various building industry stakeholders is necessary [9]. The stakeholders involved in, or affected

by, the IEQ in the operational phase of an office building and before renovation are presented in

Figure 1.2.

Figure 1.2: Stakeholders in the building industry.

In an office perspective, the main stakeholders are the tenant (a company e.g.), the occupants (the

employees of the company), and the administration which is the intermediary between the tenant(s)

and the owner of the building. To avoid neglecting IEQ and occupants’ well-being, stakeholders and

decision-makers should have easy access to knowledge and experiences from the building industry

regarding IEQ [9].

Digitalisation has great potential to create this needed transparency in the building industry. It could

encourage an increased focus on common goals and collaboration within the industry. Using data

from digital devices, the construction and operation phase of a building can become more efficient

and innovative ideas and new solutions could be prioritised [6].

Research on the use of IT shows that Denmark is one of the most digitalised countries in Europe.

Despite this, the level of digitalisation in the Danish building is below the European average [10]. On

the 30th of January 2019, the Danish Ministry of Transport and Housing took action towards changing

the low degree of digitalisation in the Danish building industry, by launching a digital strategy with

18 initiatives focusing on better use of digital tools, open formats, common standards, better use of

data, digital competencies for the entire value chain and more sustainable construction through

digitalisation [6].

On an institutional level, DTU Civil Engineering has, as a part of the university’s strategy for 2025,

designated exactly the digitalisation of construction as one of three strategic focus areas for the

INDOOR ENVIRONMENT IN A DIGITAL FUTURE 5

coming five years. The strategy encourages research on digitalisation of buildings, focus on future

digital aspects of the built environment, and an increased use of Internet of Things (IoT), sensors, big

data, data-driven modelling and building diagnostics [11].

1.2 Project Description

It is often said that poor IEQ is an invisible danger. Warm temperatures, high CO2-levels, noise, chemicals

in the indoor air etc. cannot be seen with the human eye. However, several of these IEQ parameters

can cause severe dissatisfaction and discomfort amongst occupants. This master thesis

project aims to make these parameters and IEQ issues visible, measurable and understandable to

occupants and building owners. The motivation in this work lies in the possibilities to provide buildings

owners with tools to understand and improve IEQ in their office buildings. With this project, we aspire

to get a deeper understanding of IEQ related issues in offices and to challenge status quo of IEQ

investigation by exploring new technologies. The intention hereof is to gain knowledge on indoor

environment in a digital future.

The master thesis is a part of the PhD study ’Benchmarking the indoor environment in office buildings

- characterization, synthesis, and practical application’. The purpose of the study is to characterise

IEQ, occupants’ well-being, health, and productivity in office buildings located in both Denmark

and Greenland. Furthermore, it aims to build up a comprehensive database containing occupant

and building information, which will be continuously expanded. In addition to this, the database will

provide the core of a new benchmarking tool offering building owners to evaluate the performance

of their building and workplace [12].

With this master thesis project we aim to contribute with an investigation and evaluation of state-ofthe-art

digital measurement devices to possibly be used in the PhD study. Furthermore, the intention

is to provide insights on relevant stakeholders and their motivation and concerns towards IEQ

databases and benchmarking tools. Lastly, we aim to present a benchmarking tool which could

potentially be used in the PhD study.

The methods used in this master thesis consist of two parts. One part focuses on the measurement

devices and IEQ analysis. Another part focuses on stakeholders and the development of a benchmarking

tool including an IEQ report. The two parts intertwine and both parts of the project are

based on a literature review and market research followed by analysis.

Objectives

1. Characterisation and comparison of existing benchmarking tools related to IEQ and available

technologies within IEQ measurement devices

2. Collection and analysis of IEQ data from office buildings

3. Identification of relevant stakeholders and the challenges related to IEQ they face

4. Development of a benchmarking tool and a detailed IEQ report

5. Evaluation and optimisation of the benchmarking tool and the IEQ report through feedback

sessions with the identified stakeholders


CHAPTER 2

Indoor

Environment

Chapter 2 presents an overview of the authorities, legislation,

requirements and guidelines relevant to indoor environment

quality (IEQ) in Danish office buildings. Furthermore, it presents

a review of existing literature and previous studies on indoor

environment, sick building syndrome (SBS) and the parameters

affecting it. In addition, chapter 2 describes smart technologies,

digitalisation and the concept ’Internet of Things’ (IoT)

which in this case refers to sensor devices connected to the

internet.

2.1 Legislative Authorities and Guidelines for IEQ in Offices

The Building Regulations specify the requirements of the Danish Building Act and contain the detailed

requirements that all construction work must comply with [13]. The building regulations ensure that a

building is designed and built to satisfy fire, safety, health and energy requirements. Violation of the

building regulations can result in fines.

The Danish Standards are common and repeated application documents providing guidelines. They

are developed and evaluated in collaboration with the Ministry of Industry [14]. One of the key

standards, used in this project, with regards to indoor environment is DS/EN 16798 [15].

DS/EN 16798 evaluates the quality of a building on a four scale stated to IEQ, where I is the highest

level and IIII is lowest. However, the most common levels are II and III, as level I is mainly used for

buildings with elderly or sick occupants. Level II represents a regular level, and is used for design

and operation and therefore as reference in this project. Level III and IIII are mainly used to describe

the IEQ in existing buildings and thus occupants in buildings within these categories may experience

dissatisfaction [15][16].

The Danish Working Environment Authority supervises companies and provides guidance on the

working environment. It is the Danish Authority who must ensure a safe, healthy and inspiring work environment,

as well as prevention of attrition, sickness absence and exclusion from the labour market.

The Danish Working Environment Authority distinguishes between documents of a legal and informative

nature and provide guidance and information towards both [17]. One of the key guidance

regarding indoor environment, used in this project, is A. 1.2-1 [18]

2.2 Sick Building Syndrome (SBS) Symptoms and IEQ Parameters

The term presenteeism describes occupants who are present at their workplace, but working with

a reduced performance [19]. Presenteeism can be caused by both psychological discomfort and

physical discomfort [20]. This project focuses on the physical discomfort related to poor IEQ and

SBS-symptoms which are presented in Figure 2.1. Symptoms related to SBS can be divided into four

categories: general symptoms, mucous membrane, skin, and respiratory symptoms [21].

Figure 2.1: SBS-symptoms [21].


SBS-symptoms are generally short-term effective which means that occupants will experience symptoms

shortly after being exposed to pollutants or a dissatisfying indoor environment. This can result in

long-term health issues. Anyhow, the focus of this project is the short-term effects leading to presenteeism

or sickness absence [20]. The presenteeism or sickness absence caused by SBS-symptoms are

primarily affected by parameters within the IEQ categories indoor air quality (IAQ), thermal comfort,

visual comfort and acoustic comfort [20]. The parameters within these categories are presented in

Figure 2.2.

Figure 2.2: IEQ categories and parameters [22] [15]

Several studies concerning IEQ satisfaction with the IEQ in conventional and green buildings 1 have

shown that it is highly unlikely for occupants to have full satisfaction with IAQ, visual, acoustic, and

thermal comfort parameters simultaneously [20]. In fact, multiple studies have found that there is a

gap in research on the relative impact of the IEQ categories in conventional office buildings. Therefore,

it is not clear which category has the largest effect on occupants’ (dis)satisfaction and health,

and, there is no existing ranking system of the categories or parameters within conventional buildings

[24]. However, research conducted looking at the ranking of the different IEQ categories’ effect on

occupancy (dis)satisfaction within green buildings.

The study presented in Figure 2.3 compared the ranking of IEQ categories relative to each other

from a number of different research papers. Figure 2.3 shows that IAQ caused the most dissatisfac-

1 Buildings that reduces/eliminates negative impacts on the climate and natural environment in the design, construction

and operational phase [23].


tion among occupants. Followed by thermal and acoustic comfort. The research suggested that

the dissatisfaction within these two categories could be due to the fact that thermal and acoustic

comfort is difficult for individuals to control in open-space offices. The category ranked as having the

lowest impact was visual comfort. Nonetheless, it should be emphasised that studies have demonstrated

that sufficient lighting conditions have a positive impact on productivity and, that insufficient

light moreover has the potential for major dissatisfaction [24].

Figure 2.3: Average percentages of the weighting of IEQ categories [24]

2.3 IAQ

Good IAQ refers to indoor air without harmful concentrations of contaminants and with a great majority

of occupants being satisfied [25]. Studies have shown that indoor air can be more than 5 times

as polluted as outdoor air. Poor IAQ is globally acknowledged as a significant health, environmental

and economic problem [26] [27]. It has been found that higher satisfaction with the IAQ in office

buildings leads to higher work productivity and lower stress levels [26]. Furthermore, previous studies

have discovered a decrease in productivity of 6-9 % in poor IAQ environments, compared to

environments with acceptable IAQ [25]. The most common contaminants are inorganic gases, particulate

matter (PM) and volatile organic compounds (VOC) [25]. IAQ recommendations are often

measured as limit values/concentrations, hourly/yearly means or a combination of both. It is often

measured in ppb, ppm, or μm/m 3 .

Carbon Dioxide

Occupants respiration is the primary source of CO2 in an office and, thus, it can be used to indicate

whether the ventilation rate supplied to an office is adequate. A high CO2-concentration can

cause SBS symptoms, such as headache, fatigue, eye irritation, nasal and respiratory symptoms [28].

The maximum CO2-level recommended from both the Danish Working Authority and the Danish

Standard Association are presented in Table 2.1. These recommendations are equal to a maximum

indoor CO2-level of 600-800 ppm above the outdoor air’s CO2-level which is approximately 400 ppm

[29]. Furthermore, the Danish Building Research Institute (SBi) has provided guidelines for CO2-levels

in indoor air [30]. The criteria and guidelines are presented in Table 2.1.


Maximum level

Danish Working Environment Authority

Danish Standard Association

SBi’s guidelines

Good IEQ

Less Good IEQ

Poor IEQ

1000 ppm

1200 ppm

<800 ppm

800-1000 ppm

>1000 ppm

Table 2.1: CO2 criteria and guidelines [16][29] [31]

Particulate Matter

PM is a mixture of solid and/or liquid particles suspended in air. They can vary in size, shape and

composition, and they can change because of temperature and humidity. Indoor sources of particles

include occupants, their activities, heating, chemical reactions, tobacco smoke, printers etc.

However, particles from the outside air can also contaminate the indoor air. PM10 is usually known

as dust and has a diameter of approximately 10 µm. PM2.5 is defined as fine particles and has a

diameter below 2.5 µm. Both particles can be inhaled. However PM2.5 is considered to be more

harmful than PM10, as the smaller particles can be inhaled deeper into the lungs and absorbed into

the bloodstream [32]. Studies have linked PM exposure to SBS-symptoms such as eye irritation, nose

and throat irritation, headache, skin irritation, fatigue and lack of concentration [33]. Denmark does

not yet have any limit values for particulate matters, but The Danish Working Authority recommends

compliance with WHO guidelines presented in Table 2.2.

Annual mean 24 hours mean

PM 2.5 10μg/m 3 25μg/m 3

PM 10 20μg/m 3 50μg/m 3

Table 2.2: WHO guidelines for particulate matters [34]

Volatile Organic Compounds

VOCs are organic compounds, common in indoor environments. The indoor level of VOCs is typically

significantly higher than the outdoor level. VOCs originate from building materials, cleaning supplies,

interior furnishing, occupants, food as well as processes, such as cleaning, printing and cooking [35].

High concentrations of VOCs have been associated with SBS-symptoms, such as throat and nose

irritation, eye irritation, headaches and fatigue [36].

When measuring and eliminating VOCs, TVOC is a common term. TVOC is the total concentration

of multiple VOCs simultaneously present in the air. It is cheaper to measure TVOC compared to individual

VOCs. As Denmark does not have guidelines for TVOC, the German guidelines are presented

in Table 2.3.


Exposure Limit TVOC [ppb]

1 Excellent no limit 0-65

2 Good no limit 65-220

3 Moderate < 12 months 220-660

4 Poor < 1 month 660-2200

5 Unhealthy hours 2200-5500

Table 2.3: TVOC guidelines from the German Federal Environmental Agency [37]

Other Inorganic Gases

Some of the most common nonindustrial indoor air pollutants amongst inorganic gasses are nitrogen

dioxide (NO2), ozone (O3) and carbon monoxide (CO). There are no specific danish regulations for

these pollutants in office environments, but the Danish Working Authority provides a list of limit values

for air pollution in general. These are presented in Table 2.4. Furthermore, SBi has provided guidelines

for a number of indoor air pollutants including NO2, O3 and CO. The guidelines indicate the effect

that the pollutant might have on the occupant under different levels of the pollutant. These are also

presented in Table 2.4. The American National Ambient Air Quality Standard (NAAQS) also provides

average daily (8 hours working day) limit values for the pollutants in indoor air. However, experts

recommend to maintain levels at 50% or less than the NAAQS [33].

Exposure to O3 can result in shortness of breath, throat and nose irritation for both healthy occupants

and even more so for individuals with preexisting airways diseases ie. asthma. The main sources of

O3 in offices are from outdoor air and air purifiers.

CO exposure can cause fatigue, headache and shortness of breath and even death in severe cases

with high exposures. The main sources of CO in offices are from gas appliances and environmental

tobacco smoke. However, the severity of CO poisoning is dependent on the concentration, time of

exposure, and the general health status of the exposed occupant.

Exposure to NO2 can lead to shortness of breath, coughing and wheezing. The main sources of NO2

in offices are from gas/heating appliances and roadside fumes from outdoor air.

Ozon Carbon Monoxide Nitrogen dioxide

Limit values for air pollution

Danish Working Authority 100 ppb 20 ppm 500 ppb

National Ambient Air Quality Standard 80 ppb 9 ppm 53 ppb

Sbi guidelines

Low/no effect <30 ppb <0.5 ppm <80 ppb

Medium effect 30-50 ppb 0.5-9 ppm 30-300 ppb

High effect >50 ppb >9 ppm >300 ppb

Table 2.4: Limit values for air pollution and guidelines [38] [31]


2.4 Thermal Comfort

Thermal comfort is mainly influenced by temperature and humidity, as well as personal factors such

as clothing and activity level [39]. Thermal discomfort can have a negative effect on mood, productivity,

and performance. Due to differences in personal preferences, it is usually difficult to achieve

thermal satisfaction for all occupants in a building at all times [25].

Temperature

Previous studies discovered a link between temperature and productivity in office buildings. While

there is no significant improvement or deterioration in productivity between 21-24 °C, increasing the

temperature up to 21 °C is associated with statistical improvement in productivity. In contrast, an

increase above 24 °C is associated with significant decrease in productivity [40][41]. In addition to

this, Seppänen (2003) showed productivity amongst occupants had a linear decrease of 2% per

increased °C in temperature above 25 °C [42]. Furthermore, high temperatures can cause nose irritation,

rashes, eye irritation, headaches, fatigue and lack of concentration [43] [44] [45]. The Danish

Standard Association guidelines from DS/EN 16798 for temperature ranges for both heating and cooling

seasons are presented in 2.5. These are the recommended temperature ranges in both single

and landscaped offices.

Heating season 20-24 °C

The Danish Standard Association

Cooling season 23-26 °C

The Danish Working Environment Authority Offices 20-22 °C

Table 2.5: Design criteria for temperature

As seen in Table 2.5, the Danish Working Environment Authority recommends a smaller temperature

range for office buildings, as temperatures above 23 °C cause an increased amount of complaints

from occupants. In addition to this, the Danish Working Environment Authority advises that the indoor

temperature does not exceed 25 °C in a room with sedentary work [18].

Relative Humidity

When the relative humidity is high, the natural evaporation from the body, which has a cooling effect,

is reduced. Relative humidity above 70% can therefore lead to discomfort. Relative humidity below

20% on the other hand, can cause eyes, nose, throat and skin irritation [43]. In addition, a high level

of humidity is less acceptable than a low level of humidity [46]. However, the humidity has minimal

impact on the thermal comfort at temperatures above 26 °C [47]. Table 2.6 presents the danish

standard (DS16798) recommendations for when to dehumidify and humidify in an office [15].

Dehumidification 60%

Humidification 25%

Table 2.6: Design criteria for humidity in occupied spaces


2.5 Acoustic Comfort

Acoustic comfort is often understood as an acceptable level of noise. However, the perception of

sound is more complex, and often it depends not only on the sound level, but also on factors such

as reverberation time, sound insulation and absorption. In an office building, acoustic comfort is the

capacity to protect occupants from indoor and outdoor noise and provide a good acoustic working

environment [39].

Noise

Noise is defined as unwanted sound [19]. An office can have two noise sources: external and internal.

External sources include noise from outside, such as traffic, machinery and the public. Internal

sources include noise from within the office, such as co-workers conversations, machine sounds, telephones

and office equipment.

Noise and poor acoustics can lead to a decrease in productivity, stress, fatigue, headache and

lack of concentration [43]. Studies have shown that occupants exposed to continuous external

noise, such as traffic noise, have higher levels of blood pressure and stress hormones. One study

showed a 66% decreased in performance within memory tasks when the occupants were exposed

to different types of background noises [19]. The Danish Standard Association’s recommendations

for continuous sounds levels from sounds generated by building service systems, also referred to as

background noise, are presented in Table 2.7. The Danish Working Environment Authority recommends

that sound-levels do not exceed 70 dB in a furnished office room.

Small office ≤ 35

Landscape office ≤ 40

Conference room ≤ 40

Table 2.7: Continuous sound levels from background noise [15]

2.6 Visual Comfort

Visual comfort in offices includes daylight, illuminance, glare and colour temperature. Studies have

shown daylight to have as a positive effect on health and glare as one of the most reported complaints

[39]. To enable occupants to perform visual tasks efficiently and accurately, appropriate

lighting at work spaces is essential. Appropriate light levels are achieved by both natural and/or

artificial light [25] [48].

The Danish Working Environment Authority states, that in addition with sufficient lighting from daylight

and artificial lighting, the outdoor surroundings should be visible [48]. Regarding the intensity

of artificial lighting, a study concerning the association of sick building syndrome with indoor air parameters

showed that the light intensity was significantly correlated to symptoms such as skin dryness,

eye irritation and fatigue [43].


Single office

Landscaped office

Meeting rooms

Surroundings

500 lux

500 lux

500 lux

300 lux

Table 2.8: Lighting in offices [15][49]

Table 2.8 presents the lighting criteria for work spaces in landscaped and single offices, as well as

meeting rooms according to DS12464 and DS16798. This should be obtained from a combination

of both daylight and artificial lighting [49]. The surrounding area, which is defined as more than 0.5

m from the area of the task, should meet the requirements of 300 lux [50]. Despite the fact that

there are no guidelines for maximum lightning in neither the Danish Standard nor the Danish Building

Regulations, excessive lighting may also result in discomfort. There is some evidence of increased

discomfort at illuminance above 1000 lux [51]. Furthermore, reflections and glare can cause fatigue

and headaches [48].

Correlated Colour Temperature

Artificial lighting can have either a red tint referred to as a warm colour temperature, a blue tint,

referred to as a cold colour temperature, or neutral indicating a white tint. Incandescent lamps

usually have warm colour temperatures, while fluorescent lamps and LEDs typically have cold colour

temperatures. The colour temperatures are indicated in Kelvin (K) as presented in Figure 2.4. In offices,

a neutral colour temperature of 3000-4000 K is often preferred [52].

Figure 2.4: Temperature and colour scale [52]


2.7 Summary of Parameters and Symptoms

Table 2.9 presents an overview of the IEQ categories, their parameters, guidelines and related symptoms.

The guidelines which are based on literature, research, standards and regulation previously

presented are divided into the categories good, acceptable and unacceptable. The other air pollutants

than the specified include Ozone, NO and CO which have different limits and the guidelines

are therefore not included in the Table. As seen on the Table several of the parameters can cause

the same symptoms, hence experienced symptoms related to one parameter could also be caused

by another parameter. Furthermore, some of the parameter might be related to other symptoms or

symptoms not listed simply because it has not been investigated or scientifically proven. This Table

however, gives a reasonable overview of guidelines and symptoms and has been used as a reference

through the rest of this project.

CO2

ppm

Indoor air quality

PM2.5

μm/m 3

VOC

ppb

Other

pollutants

Temperature

°C

Guidelines

Thermal comfort

RH

%

Acoustic

comfort

Noise

dB

Visual

comfort

Good 0-800 0-10 0-220 20-23 25-60 <40 >500

Acceptable 800-1200 10-25 220-660 18-20 and 23-25 20-25 and 60-70 40-70

Unacceptable >1200 >25 >660 <18 and >25 <20 and >70 >70 <500

Fatique

x

Lack of concentration

Headache

x

Shortness

of breath

Cough

x

Wheeze

x

Throat

irritation

Eye

irritation

Nose

irritation

Dryness

of skin

Skin

irritation

Rash

x

SBS symptoms

General symptoms Respiratory symptoms Mucous membrane symptoms Skin symptoms

Light

Lux

Table 2.9: Overview of IEQ guidelines and related symptoms


2.8 Smart Technologies, Digitalisation and IoT

Building audits and investigations of IEQ and related symptoms have been conducted using measurement

devices for several decades. Despite this, collected data, results and experiences have

not been shared to the detriment of fellow stakeholders. This is referred to as ’knowledge silos’. The

cross-sectoral silos which include producers, knowledge institutions, citizens, municipalities etc. are

often separated from each other and, thus, the knowledge of one does not benefit the others. However,

smart technologies, digitalisation and IoT have expanded the possibilities for data collection,

analysis and knowledge sharing [9].

Societies, cities or buildings which use IoT and/or undergo technological transformations are often

referred to ’smart cities’ or ’intelligent buildings’. Smart cities and intelligent buildings are composed

of a physical, digital and communicative elements as presented in Figure 2.5 [9].

Figure 2.5: Elements of smart cities and intelligent buildings

The digital element, which in this project is IoT devices, can be used to investigate and document

the physical context, (in this project office buildings). The strength of IoT devices, dashboards and

databases lie in their ability to collect, store, provide and share data about their surroundings. The

communicative element can be used to both communicate and visualise the results of investigations

and documentation in order to improve the physical context. The communicative element in this

project is focused on visualisations of technical data targeting relevant stakeholders [9].

All three elements are important when trying to breach the knowledge silos in order to enable stakeholders

to, not only share experiences, but also to recognise their shared interests and inspire one

another to find and develop smarter solutions [9].

Denmark has the potential of utilising the possibilities of all three elements because of its digital maturity

and high level of digitalisation. In fact, Danish citizens are some of the most frequent users of

the internet and smart phones in the entire EU. Furthermore, Denmark is ranked as the fourth most

developed country in the world when it comes to e-governance opportunities. Moreover, there is a

great potential towards open source and sharing of data in Denmark [9].


In order to fully comprehend the possibilities and limitations of IoT, it is crucial to understand the different

elements in IoT systems. The term ’Internet of Things’ was first introduced in 1999, and described

as a system where sensors acted like the eyes and ears of a computer: an entirely new way for computers

to see, hear and interpret their surroundings [53]. Figure 2.6 presents the architectural layers

of IoT systems. The context of the IoT system can be buildings, infrastructure and factories etc.

Figure 2.6: Architectural layers in IoT systems

The ’T’ in IoT are devices with one or more sensors, including thermometers measuring the temperature,

gas detectors measuring pollution, passive infrared sensors registering occupancy etc. The IoT

devices are in the”edge” of the network. There are more than 50 billion IoT devices worldwide [54].

The data from sensors, are called payloads and to make sense of the payload it must be stored and

analysed. An example of such is presented in Figure 2.7.

Figure 2.7: Example of payload from IoT device

The transportation and storage of payloads is the ’I’ in IoT. The data is transported through network

connections like the well-known Wi-Fi or Bluetooth or other protocols such as LoRa, NB-IoT or Sigfox

[54]. The payload of the device is most commonly sent to local servers called nodes. There are

millions of nodes categorised as ”Fog”. The nodes are transient storage for immediate data and

performs real-time analytics or analytics performed on data while it is being collected. The goal

of the ”Fog” is to improve the efficiency of local and cloud data storage, sorting and minimising

the amount of data required to be sent to the cloud to advance data analysis efficiency and the

security of IoT [54]. The ”Cloud” is a term used to describe data centres. It stores data summaries

from multiple fog nodes and performs deeper analysis on large data sets [54].


Figure 2.8 presents a number of limitations and possibilities of using commercial IoT devices to measure

IEQ in office buildings. Amongst the limitations is the fact that some of the commercial IoT devices

have a lower quality than the highly accurate measurement devices typically used in research

facilities. An example of this is a study conducted at DTU which investigated the dependency of air

temperature on the CO2-concentration accuracy for commercial low-cost CO2 sensors. The experiment

was conducted under different temperatures and CO2-concentrations where highly accurate

instruments were used for reference temperatures and CO2-concentrations. The study showed that

one of the two investigated devices was positively temperature dependent [55].

For longer periods of measuring the battery life time may also be a limitation. Often the frequency

of the payloads send to the dashboards determines the battery life. A battery for a device might

have a life time of months if the device sends a payload once every hour but will only last for days if it

sends a payload every minute [56]. Furthermore, the efficiency of the IoT devices is also dependent

on a reliable internet connection whether it is Wi-Fi, Bluetooth, LoRa, NB-IoT or Sigfox [54].

Additionally, it is important to keep in mind that even though IoT devices are often referred to as smart

objects, they are only as smart as the developers of the devices, their algorithms and dashboards.

This means that knowledge on IEQ parameters, symptoms related to poor IEQ and regulations on IEQ

must not be underestimated.

Likewise, the occupants and their perceptions should not be neglected in favour of solely using IoT

devices for investigation of IEQ. However, IoT devices could help visualise and document IEQ to back

up occupant perception or assist in finding the source of dissatisfaction. Some IEQ parameters which

cause symptoms might be impossible for occupants to detect but IoT data can help making these

invisible risks visible.

Some other great possibilities when using IoT devices to measure the IEQ is the connection to the

cloud which allows for storage of great amounts of data for analysis as well as data sharing between

stakeholders. Furthermore, the IoT architecture allows for real-time analysis and automation which

can help address IEQ issues as they occur [54].

Documentation of IEQ, investigation and visualisation of risks, cloud solutions for databases, IEQ analysis

and automation are important factors in a benchmarking perspective, which is one of the primary

elements in this project.

Figure 2.8: Limitations and possibilities for IoT devices


CHAPTER 3

Market Research

Chapter 3 presents a market research on benchmarking tools

and green building certifications. The motivation behind benchmarking

is described along with the findings from the market

research. This includes the application, stakeholders, methods,

grading schemes and parameters. Furthermore, chapter

3 presents the market research on IoT devices. It gives an

overview of the investigated devices along with price and accuracy

intervals.

3.1 Benchmarking and Certification

In order to improve and understand the IEQ in office buildings, building stakeholders need to be

aware of the building’s performance and potential improvements. Here, green building certifications

and benchmarking tools can be useful, but they are often quite extensive. The tools can be used to

rate and compare buildings, and thereby inform the stakeholders about the IEQ and advise about

potential improvements.

A wide range of benchmarking tools and green building certifications related to IEQ in buildings

already exist globally. In Denmark the most implemented green building certification is DGNB managed

by the Danish Green Building Council. DGNB is a complete evaluation of the building and

mostly addressing new buildings or buildings after an extensive renovation with a focus on their sustainability

level [57]. As DGNB mostly focuses on sustainability, the certification process can be too

complicated for existing buildings, when trying to improve their IEQ. Therefore, a comprehensive

database including a benchmarking tool can make it easier for existing buildings to evaluate their

indoor environment and estimate potential gains of improving the IEQ without undergoing an extensive

certification process.

To obtain more knowledge about existing benchmarking tools and certifications worldwide, a desk

study was performed. The desk study aimed to investigate their method, the parameters used to

evaluate and analyse buildings, especially the IEQ parameters, and in addition to this, how they

visualise their results. The investigated tools and certifications have different purposes, but with sustainability

and IEQ as recurring themes. Some of them mainly focus on rating the level of sustainability

for a building and some are aiming to improve living and working conditions in the buildings.

Figure 3.1: Process of the benchmarking desk study

The 21 investigated certification and benchmarking tools are presented in Table 3.1, which gives an

overview of methods, IEQ parameters, and grading schemes, before further explanation.


Origin Method IEQ Rating

Sustainbility

BBB Bæredygtig

Boværdi Barometer [58]

Denmark Questionnaire Radar

DGNB [59][60][61] Germany Third-party Medals

LEED [62] USA Third-party Medals

BREEAM [63][61] UK Third-party Stars

FRAME[64]

Denmark

Register and

planning tool

RET

Nordic Swan Ecolabel [65][61] Denmark

Third-party and

LCA

Label

Miljöbyggnad [61] Sweden Third-party Medals

Totalværdimodellen [66] Denmark Web-based Radar

HQE [67][61] France Third-party Stars

Green Star[61] Australia Third-party Stars

Green Globes [68] USA Third-party Globes

LBC [69][61] USA Measurements Label

CASBEE [61] Japan Third-party

Letters and

stars

Building performance

Minergie [61] Switzerland Third-party

Letters and

label

Berkeley benchmarking tool [70] USA Web-based Numbers

NABERS Indoor

Environment Tool [71]

Australia Third-party Stars

Rebus

IQ-Compass [72][73]

Denmark Calculation tool Letters

Mobistyle [74] Netherland Measurements Nudging

Active House [61]

Denmark

Calculation

Radar and

tool

label

TAIL [75] Denmark RET

Colour and

roman letters

WELL v2 [61] USA Third-party Medals

IAQ Thermal Visual Acoustic

Table 3.1: Certification and benchmarking tools


Application and Stakeholders

In the desk study, different purposes and target groups were discovered. Some of the investigated

tools are primarily used before applying for certification. They can be helpful when preparing for

the certification process, and during the design and planning process, which means they generally

involve developers, engineers, architects and consultants. FRAME and Berkeley are tools within this

category. FRAME helps to manage and document sustainability in projects, before applying for a

DGNB certification. Berkeley’s occupant survey and benchmarking tool can be useful in preparation

for a certification such as LEED, since it analyses the success of the design, and provides a database

for comparing similar buildings, so stakeholders can act on their results by applying modifications.

Some tools are simply labels or marks, raising awareness of the building type and met requirements.

The target group for these tools are mostly building owners, tenants and administration. Nordic Swan,

LBC and Active House are tools within this category. Most of the tools, however, provide the developer,

buildings owners or administration referred to as the applicants, with a level of certification.

These tools have a larger target group, as the level of certification can be attractive for everyone involved

from the designing to the operation phase. Other than the application process, the methods

for granting a certification is different for the investigated tools and certifications.

Methods

As seen in Table 3.1, the different benchmarking and certification tools use different methods to analyse

and rate a building. The most consistent methods are referred to as web-based, measurements,

questionnaire and third-party. The method distribution is illustrated in Figure 3.2. As the only one

BBB (Bæredygtig Boværdi Barometer), is entirely based on a questionnaire. A few are solely based

on measurements. For example, American LBC, which has a 12-months performance-recording period,

and Dutch Mobistyle, which aims to motivate behavioural change by installing small interactive

screens in offices. Others are web-based such as the American Berkeley and the Danish Totalværdimodellen,

where the results are outcomes of an online survey or web-tool. The greater part of the

tools uses an online registration and documentation platform, and they have verification by a thirdparty

assessor, who verifies the uploaded performance. Regardless of their methods, all the tools

illustrate their results with some kind of visualisation and the applicants can obtain different levels of

certification to indicate how well the building complied with the requirements.

Grading Schemes

All the investigated tools use different grading schemes, and often with 4-6 different levels. The highest

levels are often extremely hard to achieve. Three grading schemes recur: stars, medals and letters

as illustrated in Figure 3.2, the distribution of tools using a specific grading scheme is explored. The

most popular grading scheme is stars, which is used by tools such as Australian NABERS, French HQE

and British BREEAM. While American LEED, WELL and German DGNB use medals where the applicant

can achieve Gold, Silver, Bronze and Platinum. Furthermore, Swiss Minergie, Danish IQ-Compass and

Japanese CASBEE present their results with letters. In addition to this, some tools use numbers, colours,

globes and radars to visualise their results, and a few use a mix of two grading schemes. Moreover,

some of the investigated tools are entirely labels, achieved if a building complies with the tools or

certifications requirements. Certifications within this category are Nordic Swan, Active House and

LBC. These labels are well known in society since many everyday products and materials have different

labels, showing if they meet the requirements within a specific area such as allergy, chemicals,


testing and sustainability. Nordic Swan operates with labels for both products and buildings and is

well known in Scandinavia. LBC is a strict sustainability label with two versions of marks: living and

petal. Other than a label or grading scheme, most of the certifications and tools provide a detailed

report about the results, and the rating is based on a deeper analysis with a wide range of parameters.

Investigating the IEQ parameters is interesting for this project in order to obtain knowledge

about which to include in a benchmarking tool and database.

Figure 3.2: Methods and Grading Schemes

Parameters

A previous study has explored Green Building certificates’ distribution of credits assigned to each of

the four IEQ categories [76]. A focus in this desk study was on the occurrence of the parameters

within the four categories: IAQ, thermal, visual and acoustic comfort. This was done by counting the

tools and certifications different IEQ parameters related to each of the four categories.


IAQ Thermal comfort Acoustic comfort Visual comfort

Parameters 10 5 2 4

Occurrence 42 out of 107 25 out of 107 16 out of 107 24 out of 107

Table 3.2: Occurrence of parameters within the four IEQ categories

Table 3.2 illustrates the number of different parameters within each of the four IEQ categories. Furthermore,

it illustrates the occurrence of the parameters within the categories. Some of the tools,

do not identify which specific parameters they apply within a category, but only that it includes the

category. An example of parameters identified which were related to IAQ were ventilation, CO2,

pollution, particles, mould, VOC and CO. The distribution of credits in Green Building (GB) certification’s

schemes [76] and the occurrence of parameters within the four IEQ categories in the desk

study are presented in Figure 3.3.

Figure 3.3: GB credit distribution and IEQ parameter occurrence in percentages [76]

Figure 3.3 indicates a connection between GB credits assigned to different IEQ categories and occurrence

of parameters within different IEQ categories in the desk study. IAQ is the category with

most assigned GB credits and with the highest occurrence of parameters in the desk study. This

could indicate that IAQ is considered as having a major importance compared to the other categories

but also that the category is simply composed of more measurable or significant parameters.

The dedication of credits and occurrence of parameters in the IAQ category comply with findings

of the research previously described in this project, which found IAQ to be the category causing

the most dissatisfaction amongst occupants compared to other IEQ parameters. The category with

the second most GB credits and occurrence of parameters is thermal comfort category followed

by the visual and acoustic comfort category. It is important to mention that the investigated tools

and certification do not necessarily measure the applied parameters, but they incorporate them in

their analysis. Lastly, it must be acknowledged that some IEQ categories or parameters have low

representation or are simply not included in the GB schemes and benchmarking tools even though

they are relevant for characterising the IEQ of the building. The reasons hereof could be measuring

difficulties or lack of research and references defining the acceptable levels [76].


3.2 IoT Devices

A market research on available IoT devices with sensors played a major role in the investigation of

which devices to use for the measurement of IEQ in this project. The market research was conducted

as a desk study using primarily information from the respective producers of the devices and information

from the literature review. The aim of the desk study was to discover IoT devices which measured

multiple IEQ parameters within different price ranges. Furthermore, the purpose of the desk study was

to get an overview of the level of accuracy of the devices.

The desk study included 21 IoT devices. All of the investigated sensors measured temperature and

relative humidity and two thirds of the devices measured CO2 as well. The devices measured on

average 5 of the 9 relevant parameters which were described in section 2.2 ”Requirements for IEQ in

Danish office buildings”. The price range of the devices was 522-4306 DKK and the average cost of

the investigated devices was ∼1500 DKK. Furthermore, several of the IoT devices had a dashboard

service with a monthly or yearly subscription cost.

Table 3.3 shows an overview of the number of devices which measured the given parameters, along

with the number of devices where it was possible to obtain the accuracy for the parameter. Furthermore,

the table presents the average and median accuracy for the devices with known values.

Investigated

devices

Devices with

known accuracy

Average

accuracy

CO2 PM2.5 TVOC Gasses

Temperaturpancy

Occu-

RH Noise Light

14 11 11 1 21 21 5 4 2

8 4 4 1 14 14 0 0 0

± 55ppm ± 10 µg/m 3 ± 10 ppb ± 0.4 ◦ C ± 2%

Table 3.3: Average accuracy for investigated devices with known accuracy

Three intervals were defined in order to compare the accuracy of the various sensors in the devices.

The three intervals were defined as best, medium and worst third of the difference between the

lowest and highest accuracy for each parameter. The calculation of the three intervals for accuracy

of the temperature sensors in the devices is shown below as an example. This method has been used

to calculate the intervals for all devices with known values.

Lowest value = Min v = ± 0.1 ◦ C

Highest value = Max v = ± 1 ◦ C

Interval size = Int s = Max v - Min v = ± 1 ◦ C - ± 0.1 ◦ C = ± 0.9 ◦ C

Unknown value =

Interval 1 [ ± ◦ C ] = = [ Min v ; Min v + Int s ] = [ 0.1 ; 0.1 + 0.3 ] = [ 0.1 ; 0.4 ]

Interval 2 [ ± ◦ C ] = = ] Min v + Int s ; Min v + Int s·2 ] = ] 0.1 + 0.3 ; 0.1 + 0.3 ·2 ] = ] 0.4 ; 0.7 ]

Interval 3 [ ± ◦ C ] = = ] Min v + Int s ·2 ; Min v + Int s·3 ] = ] 0.1 + 0.3 ·2; 0.1 + 0.3 ·3 ] = ] 0.7 ; 1.0 ]

The same method was used to divide the devices into three intervals related to the purchase price

of the devices. Interval one defines cheaper devices, interval two defines medium priced devices

and interval three higher priced devices.


Unknown value =

Interval 1 [DKK] = = [ Min v ; Min v + Int s ] = [522 ; 522 +1261 ] = [522 ; 1783 ]

Interval 2 [DKK] = = ] Min v + Int s ; Min v + Int s·2 ] = ] 522 +1261 ; 522 +1261·2 ] = ]1783 ; 3045]

Interval 3 [DKK] = = ] Min v + Int s ·2 ; Min v + Int s·3 ] = ] 522 +1261·2; 522 +1261·3 ] = ]3045; 4306]

The complete list of investigated devices is presented in Figure 3.4 with intervals indicated by colours

and in appendix A with exact prices and accuracy. The overview indicates that higher prices devices

are rare and that accuracy for noise, light, TVOC and particles are difficult to obtain. Moreover it

indicates that high and medium priced devices guarantee a higher accuracy.

Total number

of paramters

Roomalyzer [40] 7

Price

CO2

RH Noise Light TVOC PM2.5

Other

pollutants

Temperature

Occupancy

TheO [77] 6

uHoo [78] 6

Awair [79] 5

Awair omn [80] 5

Huma-i [81] 5

Foobot [82] 5

Air mentor [83] 5

Sens’it [84] 4

Temptop [85] 4

Netatmo [86] 4

Laser Egg [87] 4

Wave Plus [88] 4

Air Visual [89] 4

IC-Meter [90] 4

RYSTA [91] 4

Iclever [92] 3

Eve room [93] 3

Hummbox [94] 3

INSAFE+ [95] 3

SIGLINK [96] 2

Table 3.4: Market research on IoT devices

Another aspect of the desk study investigated the source of power and the network connection.

The majority of devices in the desk study were powered by batteries. A few of the devices should be

plugged-in to a power source and some had both possibilities. Regarding the network connectivity

the majority of the devices needed an external Wi-Fi connection and one third of the devices could

use a sim card implemented in the device.

The overview and additional information obtained in the desk study were used later when deciding

which devices to investigate further, and which to use for measurements in the project.


CHAPTER 4

Method

Chapter 4 describes the methods used in this project. The chapter

consists of two parts. The first part presents the methods

used for the IEQ Investigation and analysis process. This includes

the description of measurement devices, the offices

used for measurements, the applied questionnaire and data

processing. The second part presents the methods used in

the benchmarking process. This part includes a description of

the stakeholder analysis, interview method, a value proposition

canvas and a presentation of the economic estimations

which were used as a part of the developed benchmarking

tool.

4.1 IEQ Investigation and Analysis Process

The IEQ investigation and analysis in this project consisted of four steps, as presented in Figure 4.1 The

first step, market research on IoT devices, was presented in the previous chapter and devised a list of

devices of which five were chosen. These selected devices spanned a broad range of prices and

accuracy levels, such that a wide variety of devices was investigated.

The second step consisted of a preliminary device evaluation aiming to investigate usability and

differences in test measurements. This allowed for an improved understanding of the five devices as

well as a comparison of device usability and performance.

Subsequently, in the third step, the devices were used to collect data in three separate offices. This

was done concurrently with questionnaires administered to office occupants in order to obtain both

objective and subjective data regarding IEQ.

The last step consisted of analysis of the measurements from the offices and the occupant questionnaires.

The results of these analysis were used later in the project for visualisation and benchmarking

purposes, with a focus on the possible economic gains of improving the IEQ in the offices. The final

step consisted of an analysis of the data from the measurements and questionnaires. These results

were later used for visualisation and benchmarking purposes, with a focus on possible economic

gains from office IEQ improvement.

Figure 4.1: IEQ Investigation and analysis process


4.2 Measurement Devices

When choosing devices for this project, the different IEQ categories were taken into consideration,

and, a selection of devices collectively covering parameters within each category was prioritised.

Furthermore, the selection represents a variety of devices produced for experimental, residential

and commercial use. As presented in Figure 4.2, most parameters were measured with multiple of

the devices, allowing for the possibility of comparing the devices.

Figure 4.2: Devices and parameter coverage


RoomAlyzer

The RoomAlyzer is produced by the Danish company, IoT Fabrikken. In comparison with other devices

from the market research, this device is medium-priced (1795 DKK + monthly subscription of 29-69

DKK) and has high accuracy within all parameters with known values (listed below). It is primarily for

commercial use and has operational conditions of 0-50 ◦ C and 0-95% RH and can cover rooms of

100m 2 or greater in cases with high air circulation. However, if the device is used for estimating the

occupancy based on detection of movement, it must be within 12 meters of its target(s), since the

range of the PIR-sensor is 12 m [97] [56].

List of parameters:

• CO2 (± 45 ppm)

• TVOC (± 15% of measured value)

• Temperature (± 0.2 ◦ C)

• Relative humidity (± 2%)

• Light and Light colour

• Movement

• Noise

Figure 4.3: RoomAlyzer

The RoomAlyzer uses two C batteries. It is placed vertically on the wall with an adhesive hook in

the height of occupants’ heads (1.2-1.5 m above the floor). The device should be placed out of

direct sunlight and preferably in the direction of the entrance to the room. The device is turned

on with a magnet and starts measuring when the blue LED on the device is blinking. The device is

calibrated from the production and has automatic calibration while in use. The device measures

every 15 minutes and transmits data through NB-IoT to the RoomAlyzer dashboard once every hour

when the room is occupied and once every fourth hour when the room is not occupied [56].

Data which is collected, stored and processed through the device and dashboard is owned solely by

the customer. RoomAlyzer may perform statistical analysis on anonymised aggregated data from

multiple customers [56], yet, data handling complies with the requirements of the General Data

Protection Regulation (GDPR) and can be deleted by the customer at all times.


uHoo

The uHoo is produced by a Hong Kong-based company specialising in indoor air quality. In comparison

with other devices from the market research, this device is medium-priced (2230 DKK + a

yearly subscription of 2040 DKK) and has a medium accuracy within all parameters with known values

(listed below). It is the largest device used within this project. It is primarily for residential use and

its operational conditions are 0-40 ◦ C and 5-95% RH (non-condensing). It is recommended to use

one device per 50-80 m 2 for high-precision measurements, however one device can cover up to

80-120 m 2 , although with lower precision [98] [78].

List of parameters:

• CO2 (± 50 ppm or 3%)

• PM2.5 (± 5 µg/m 3 and 15% reading)

• TVOC (± 10 ppb and 5% reading)

• Carbon monoxide (± 10 ppm)

• Ozone (± 10 ppb or 5% reading)

• Nitrogen dioxide (± 10 ppb or 5% reading)



Figure 4.4: uHoo

The uHoo should be placed on a desk or at occupant breathing height (usually 1-1.5 m above the

floor). The device should be placed out of direct sunlight and at minimum 1 m away from doors or

windows. Furthermore, the device should not be placed close to copy machines, microwaves etc.

The device must be plugged into a power source and connected to WiFi for setup. The calibration

time is 48 hours. The device transmits data through WiFi. The data can be obtained on a minute-basis

or hourly average from the uHoo dashboard.

The collection, storage and processing of data from the device, app and dashboard complies with

the requirements of the GDPR and personal information is thus not shared without the user’s consent.

However, the user can authorise uHoo to share current and historical air quality measurements and

data with third parties. Personal information is deleted when the service is no longer needed or

upon request. uHoo may share anonymised information on air quality measurements for industry

and market analysis, geographic profiling, marketing, advertising and other business purposes [78].


Foobot

The Foobot is produced by the Luxembourgish company Airboxlab. In comparison with other devices

from the market research, this device is low-priced (1300 DKK) and has a low accuracy within all

parameters with known values (listed below). It is the heaviest device used in this project. It is primarily

for residential use and its operational conditions are 15-45 ◦ C and 30-85% RH. The device can cover

70-140 m 2 [82][99] [100]. List of parameters:

• Temperature (± 1 ◦ C)


• PM2.5 (± 5 µg/m 3 and 15% reading)

• TVOC (± 15% of measured value)

Figure 4.5: Foobot

The Foobot should be placed on a desk or at occupant breathing height (usually 1-1.5 m above

the floor). The device must be plugged in a power source and connected to WiFi for setup. When

setting up the device, it must remain at maximum 2 m away from a WiFi router. The initial calibration

time is six days. If the device is turned off after the initial calibration, it requires a calibration of three

hours. The device transmits data through WiFi allowing data to be obtained on a minute-basis from

the Foobot dashboard [99].

Data from the device, app and dashboard is collected, processed, and stored through third-party

service providers and complies with the requirements of the GDPR. Personal information is deleted

after five years or upon request. Foobot however may share or sell anonymised data publicly and

to third parties without customer consent or compensation. The anonymised data will be retained

indefinitely for purposes of data analysis but cannot be directly linked to any specific user [82].


Sense’it

The Sense’it device is produced by the French global network operator company, Sigfox. In comparison

with other devices from the market research, this device is low-priced (522 DKK + yearly

subscription of 140 DKK) and has a medium accuracy within all parameters with known values (listed

below). It is the smallest and lightest device used in this project. The device is primarily produced for

experimentation and demonstration of the possibilities in the realm of IoT devices. There is therefore

no developed user guide or coverage specification. Its operational conditions are -10-50 ◦ C and

10-90% RH. It measures the below listed parameters [101] [102].

List of parameters:


• Relative humidity (± 3.5%)

• Light

• Door opening detection (± 0.244, 0.488, 0.976 mg and ± 0.1 μT/LSB)

• Vibration detection (± 0.244, 0.488, 0.976 mg and ± 0.1 μT/LSB)

• Magnet detection

Figure 4.6: Sens’it

The device can be plugged into a power source or can use the built-in battery with a lifetime of

3 weeks to 3 months depending on the measurement rate. The device can be placed on a table

or desk, or vertically on a wall with velcro. The device can measure using one sensor at a time. It

has an LED display with one button that can be used to turn the device on/off or select the desired

sensor for measurements. The device can measure every 10 minutes, every hour or on occurrence

and transmits the data through Sigfox to the Sens’it dashboard [102].

Collected data from the device and dashboard is processed and stored through third-party service

providers and complies with the requirements of the GDPR or corresponding requirements in non-

European countries. Personal information is only retained for as long as services are provided and is

deleted upon request [84].


IC-Meter

The IC-meter GSM 4.2 is produced by the Scandinavian company, IC-meter. In comparison with

other devices from the market research, this device is high-priced (4306 DKK) and has a high accuracy

within all parameters with known values (listed below). It is primarily for commercial use and its

operational conditions are -20-80 ◦ C and 0-95% RH. It is recommended to use one IC-meter for each

room, however, several devices can be used if the purpose of the measurements is to investigate

differences in the IEQ within a larger room such as an open space office. It measures the below listed

parameters [90] [103].

List of parameters:

• CO2 (± 30 ppm + 3% reading)


• Relative humidity (± 2)

• Noise

• Activity level

Figure 4.7: IC-meter

The IC-meter must be plugged in a power source when measuring. The IC-meter is placed vertically

on an inner wall or in an IC-meter stand close to the wall to ensure the most correct noise measurement,

since measurements in the middle of the room can result in readings up to 6 dB(A) lower than

the actual level. The correct placement is 1.2 m above the floor and out of direct sunlight. The distance

to heaters and seats must be at least 1.5 m. The device measures every 5 minutes and can

transmit the data through WiFi or LoRa to the IC-Meter Dashboard [103].

Data which is collected, stored and processed through the device and dashboard is owned solely

by the customer. The data handling complies with the requirements of the GDPR. IC-Meter provides

the customer with the possibility to share parts of the data with selected parties or to publish it. Data

collected with a device is encrypted before it is sent to the IC-Meter Cloud [90].


4.3 Offices

Using a checklist developed by DTU for the purpose of investigating IEQ in buildings, more knowledge

was obtained regarding each office. These results are presented in Table 4.1.

Office # 1 Office # 2 Office # 3

Construction Year 2015 2002 2008

Last Renovated - 2009/2010 -

Office Area 100 m2 70 m2 120 m2

Occupants 7 6 8

Occupancy 07:30-16:30 06:45-16:30 06:30-17:15

Floor Ground First First

Connecting Rooms

Hallway

Printer room, toilet

and kitchenette

Entrance, storage,

and meeting room

Tenancy/Owner Owner Owner Owner

Heating/Cooling

Radiator and

air condition

Radiator and

air condition

Floor heating and

air condition

Facade East/West South/East East/South/West

Shading Elements Internal Internal Interval

Windows Three layer Double Double

Cleaning Everyday Wednesday & Sunday Wednesday & Sunday

Table 4.1: Results from checklist

Figure 4.8: Office #1 Expan Figure 4.9: Office #2 Frisesdahl Figure 4.10: Office #3 Frisesdahl


Office #1

The first investigated office belongs to EXPAN, a producer of concrete components for buildings [104].

The office is located in one of EXPAN’s buildings in Brørup and is mainly used for producing technical

drawings. It was accommodating 7 out of 8 possible occupants at the time of the investigation.

Figure 4.11: Floor plan office #1

The office was divided into two zones as seen in Figure 4.11 with four workstations in each zone. The

devices were placed near each of the end walls at 1.2 m above the floor. IC-Meter and uHoo were

placed near the end wall facing north, and RoomAlyzer was placed near the end wall facing south

in the direction of the entrance.

Despite successful measurements in the preliminary evaluation of the devices, problems with the

device, uHoo, appeared in this office. While installing the sensors at EXPAN’s office, it became apparent

that the company has a captive portal network which requires log-in through a dedicated

web-page. As such, the IT department needed to add uHoo’s MAC address to their positive list.

However, the IT department was not successful and uHoo could therefore not be used for the investigation

in office #1 [98]. The zones were therefore represented solely by IC-Meter and RoomAlyzer.

Furthermore, Figure 4.11 illustrates the sun’s path around the building, which may have an impact on

the IEQ. The red crosses illustrate the position of the devices.


Floor plan office #2

The second and third offices both belong to the contracting company, Frisesdahl A/S [105]. Office

#2 is located in one of Frisesdahl’s buildings in Askov and accommodates 6 occupants. The office is

an older office, where mainly secretary work is done.

Figure 4.12: Floor plan office #3

The office was divided into three zones with two workstations in each zone, as shown in Figure 4.12.

The devices were placed on the dividing wall between the open-space office and the remaining

rooms at height of around 1.2 m. In this case, uHoo was placed in zone 1 close to the copy room as it

is the device measuring the most IAQ parameters. Conversely, IC-Meter was placed in zone 2, as it is

the device measuring the least number of parameters. RoomAlyzer was placed in zone 3, because

this zone is connected with the kitchen, and RoomAlyzer is the device measuring the second largest

amount of parameters.


the perceived IEQ. The red crosses illustrate the position of the devices.


Office #3

The third investigated office is also located in Frisesdahl A/S’s building in Askov. At the moment, it

accommodates 6 out of 8 possible occupants. Office #3 is a newer office building consisting of

project managers.

Figure 4.13: Office #3 Frisesdahl

The office was divided into three zones with three workstations in both zone 1 and 2, and two workstations

in the last zone, as demonstrated in Figure 4.13. The devices were placed on shelves on the

walls in the east and west directions, as well as on the wall in the north direction. All devices were

placed approximately 1.2 m above the floor. In this case, uHoo was placed in zone 3 close to the

printer/copier and coffee machine because it is the device measuring the most IAQ parameters.

IC-Meter and RoomAlyzer were placed in zones 1 and 2, respectively.


the perceived IEQ. The red crosses illustrate the position of the devices.


4.4 Questionnaires

The occupant questionnaire used for this project is a modification of a standardised questionnaire

developed at DTU for the purpose of investigating occupant perception of IEQ in office buildings.

Here, questionnaires were distributed via e-mail to all occupants in the three offices. The use of onlinedistributed

questionnaires poses the risks of a lack of process control and a decreased response rate.

However, the online survey method was chosen for this project because it allows for the use of visual

aids and eliminates the interview effect in which respondents are influenced by the interviewer’s

appearance, gesture, method of interviewing and other behaviours. Furthermore, the online survey

method minimises the effect of geographical distance and is both cost- and time-efficient [51] [106].

The questionnaire was provided in Danish in consideration of the respondents’ native language. A

time limit of ten minutes was set in order to minimise the burden of the survey and obtain as many

completed questionnaires as possible. Prior to answering questions, respondents were informed that

the survey is anonymous and that their answers will not be linked to their identity. Furthermore, respondent

answers were handled in accordance with the GDPR. The structure of the questionnaire

and the topics of the questions are presented in Figure 4.14. The initial part of the questionnaire

covers background information on the occupant’s office. This is followed by questions regarding

the occupant’s perception of, and satisfaction with, individual IEQ parameters. Finally, the respondent

is asked to rate various building functions and his/her overall perception of the IEQ in the office

building.

Figure 4.14: Structure and topics

The questionnaire consists primarily of factual and perceptual questions, both of which allowed for

questions to be answered within a scale or a closed category. The scale intentionally has six options,

leaving out a neutral answer option and thereby forcing the respondents to commit themselves to

either the lower or higher end of the rating scale. The categories for estimation of the regularity of

dissatisfaction or symptoms is presented in the example in Figure 4.15. The entire questionnaire is

presented in appendix B.

Figure 4.15: Example of a question from the questionnaire in English


4.5 Data Processing

In order to analyse the data from the measurements and the questionnaires, the data was processed

as presented in Figure 4.16. Here, the data from the measurement devices were downloaded from

the dashboards in xlsx or csv files and processed in Microsoft Excel. Similarly, the data from the questionnaires

were copied from a data presentation link and pasted in Excel where it was processed as

well. The data from the measurement devices were visually displayed in graphs and box plots for

comparison analysis. This was filtered such that only data from occupied hours were included. The

results hereof were analysed alongside an evaluation of questionnaire data for IEQ complaints and

symptoms in order to evaluate the IEQ in the three offices. The combined data presentation of questionnaire

and IEQ data were in the form of accumulated bar charts which included the percentage

of occupied hours within the IEQ categories good, acceptable and unacceptable along with the

percentage of occupant complaints and symptoms.

Figure 4.16: Data processing


4.6 Benchmarking Process

The benchmarking investigation and development performed in this project consisted of four steps,

which are presented in Figure 4.17. The first step was the market research on benchmarking tools

and Green Building certificates, which was presented in the previous chapter. The insights from the

market research were used as inspiration later in the project.

The second step in the benchmarking process consisted of a stakeholder matrix analysis. This method

was in order to get an overview of stakeholder roles in a renovation or IEQ improvement process.

Based on the stakeholder matrix, a number of building owners were interviewed in order to investigate

the possible value of a benchmarking tool for IEQ of their building, this was done through a

value proposition canvas.

The third step was the development of a grading scheme for IEQ. This step was based on the interviews

with the relevant stakeholders, the value proposition canvas and the market research of

benchmarking tools. Furthermore, this step included economic estimations on the possible gain

from improving the IEQ in the offices.

The last step in the benchmarking process concerned communication of the results of the IEQ analysis,

final grading and the economic estimations. In order to do so a number of visualisations were

prepared. The the value proposition canvas was used as framework for the visualisations. The visualisations

were presented for the previously interviewed stakeholders and feedback sessions were

conducted.

Figure 4.17: Benchmarking investigation and development.


4.7 Stakeholder Matrix

The stakeholder matrix analysis was used to investigate the interest and power of the stakeholders in

office buildings in different owner/tenant constellations. This was done in order to get an overview of

stakeholder roles in a renovation/IEQ improvement process. The four quadrants of the power-interest

grid, presented in Figure 4.18, can be seen as defining four categories of stakeholders with high and

low power and interest in a project, situation or job [107].

The most important and influential stakeholders who can support a job or process are the ’players’.

The ’subjects’, while interested, have less influence. However, coalition could increase their power

and convert them into ’players’. The ‘context setters’ can influence the future overall context for a job

or process. They are typically perceived as having the same values as the organisation who is driving

the job or process, but lacking awareness and motivation to support it. Ways of increasing their

interest and encouraging them to support the objectives of the organisation should be considered.

The ’crowd’ can be seen as potential rather than actual stakeholder. However, their interest and/or

power could be raised to convert them into ’subjects’ or ’context setters’ [107].

Figure 4.18: Stakeholder ’Power/Interest’-matrix [107].

This stakeholder matrix method was developed for cases in which a company owns and is the main

user of an office building as well as for cases in which a company rents an office building through

an administration firm. The matrix was, in part, formulated on the basis of a meeting with the administration

company Newsec [108].


4.8 Interviews and Value Proposition Canvas

A number of building owners were interviewed based on the stakeholder matrix for the case in which

a company is the owner and user of the building. This was done in order to investigate the owners’

motivation behind a possible or actual renovation of their building. Furthermore, the interviews investigated

the possible value of an IEQ-benchmarking tool for the building owners. The interviews were

conducted as semi-structured conversations with questions. Before the interviews, the structure and

questions were specified in an interview-guide which is presented in appendix D. After the interviews

were transcribed and coded, an analysis in the form of a value proposition canvas (VPC) was made.

The VPC is a structured method to examine the value of a product or service from the customer or

user’s perspective. As seen in Figure 4.19, the canvas consists of the customer profile (right) and

the value map (left). Each segment consists of three sections focusing on specific features of the

customer or user and product or service, respectively [109].

The customer profile on the right includes the customer or users’ job(s). In the context of this project,

the customer is the building owner and a plausible job could therefore be to ”improve the IEQ in

the office”. It also includes pains, which are the problems they might face in completing their tasks.

Furthermore, it includes gains, which are the positive outcomes that the customer expects from completing

the job. The value map to the left represents the product or service and how it can help the

customer complete their job. It includes pain relievers, which is how the product or service can minimise

or reduce the customers pains. Moreover, it includes the gain creators, which are meant to

improve the customer experience. While the customer or user may have many jobs to be completed,

the value proposition canvas can help to focus in on one job or situation. The more matches

between value map and customer profile, the higher chances that the product or service will be

useful [109].

Figure 4.19: Value Proposition Canvas


4.9 Economic Estimations

The estimations of the possible economic gain of improving the IEQ and hereby heightening the

occupant productivity are, in this project, based on a modified version of the methods used in the

previous project Totalværdi Indeklima. The project Totalværdi Indeklima (2017) [110] developed

a tool with the purpose of estimating possible productivity improvements in a IEQ context. The tool

includes the parameters temperature and CO2-level and is designed to be a simple and easy to

handle tool for different stakeholders. Despite light and noise also being considered important, current

knowledge about linking these parameters to productivity is insufficient, and they are thus not

included in the calculation tool [110].

The calculation for temperature impact on productivity is based on the study ’Effect of Temperature

on Task Performance in Office Environment’ by Seppänen et al. (2006) [111]. In light of this study, an

equation describing productivity linked with temperature, was formulated as presented in Equation

4.1. The equation was used to modify the calculation sheet from ”Totalværdi og Indeklima”, such that

the calculations were based on the temperature categories: good, acceptable and unacceptable

defined in this project [112][113].

P = 0.1647524 · T – 0.0058274 · T 2 + 0.0000623 · T 3 – 0.4685328 (4.1)

T = Temperature

[°C]

For the temperature categories, the equation is used to calculate the productivity percentage at

the lowest and highest temperature within a category. The average value of these are then defined

as the productivity percentage representing that category.

Category Intervals Min Max Average Productivity

Good 20-23 °C 0.99 1.00 1.00 100 %

Acceptable 18-20 °C 23-35 °C 0.97 0.98 98 %

Unacceptable <18 °C >25 °C 0.94 0.95 95 %

Table 4.2: Temperature Calculations

The equation linking CO2 and productivity is based on the study ’Ventilation and Performance in

Office Work’ by Seppänen et al. (2006)[114][112]. In order to apply this equation, the ventilation

rates were converted to corresponding CO2-level. This was completed by solving q v in Equation 4.2.

C = G q v

+ c o (4.2)

G = 17 · M

[L/h]

C = CO2 – level in the room

[ppm]

q v = Ventilation rate

[L/h]


c o = Outdoor CO2 – level

[ppm]

where M is the activity level, presumed to be 1.0 met for a person working in an office.

Next, the productivity equation, presented in Equation 4.3, was applied, and the productivity percentages

for the three categories were calculated [113].

P = 0.0188 · ln(x) + 0.9482 (4.3)

x = Average ventilation rate

[L/h]

Category Intervals Min Max x Productivity

Good 0-800 ppm - 11.8 1 1

Acceptable 800-1200 ppm 11.8 5.9 8.9 99

Unacceptable >1200 ppm 5.9 3.4 4.6 98

Table 4.3: CO2 Calculations

Finally, the calculation sheet was modified based on the calculations for the categories defined

in this project. The calculation sheet makes it possible to easily present a productivity percentage

change for the offices.


CHAPTER 5

Results

Chapter 5 presents the results of the preliminary device evaluation

followed by the IEQ investigation conducted in the three

offices. Furthermore, chapter 5 presents the stakeholder matrix

and the value proposition canvas followed by a presentation

of the developed benchmarking tool. This includes a description

of the IEQ parameters’ weighting, grading scheme, economic

estimations and database concept. Lastly, this chapter

presents the development process of the IEQ report including

the content of the report.

5.1 Preliminary Device Evaluation

Device and Dashboard Usability

The preliminary device evaluation investigated the ease of use, the means of support from the producer

of the device, the user-friendliness of the dashboards and the steps to access the raw data.

The result of this evaluation is an overview and comparison of the usability and performance of the

devices. The ease of use and the means of support from the producer is presented in Figure 5.1. First

the prerequisites and limitations, along with the ease of setup of the devices, were evaluated. The

ease of setup was evaluated as the number of steps in order for the device to be installed and measuring.

RoomAlyzer and IC-Meter have fewer steps, compared to the other devices, because these

devices and accounts were set up by the producers. The means of support from the producer of the

device was crucial when using and obtaining information on the devices. This was evaluated as the

response rate from the producers. Furthermore, the producers of uHoo, RoomAlyzer and IC-meters

were able to provide almost all of the desired information and assist in problems encountered. The

producers of Foobot, on the other hand, were not able to assist in connectivity issues, which resulted

in the device not being included in the study.

In relation to the dashboards presenting the data and providing a possibility to download data, the

preliminary study showed a difference in the latency of the dashboard updates and the number

of steps/clicks to download the raw data and prepare it for analysis. The reason that it takes 42

clicks to download data from the RoomAlyzer dashboard is because the data must be downloaded

individually for each measured parameter. Downloading data from the Sens’it dashboard is not

possible and must therefore be read or copied manually, which will be highly time consuming for

projects with long periods of measurements.

Figure 5.1: Evaluation of device and dashboard usability


Measurements

The preliminary study compared data from test measurements for the devices. The test measurements

were conducted in an unoccupied meeting room in May 2020 starting at 9am and with a

duration of 24 hours. The aim of the 24 hours test was to compare the measurements for temperature

and humidity for all four devices, CO2 measurements for three of the devices along with TVOC

and noise measurements for two of the devices. The intention of the study was not only to compare

the devices, but also to become aware of the potential differences and the reasons behind these

in collaboration with the producers if possible. Awareness of these were important, as the different

devices were used to represent different zones within the offices. The actual IEQ results were not analysed

or commented upon as the differences between the devices were the focus of this preliminary

study.

Initially, the averages over the 24h period were found for the different devices and parameters measured.

Furthermore, the maximum difference between lowest and highest measured values by two

devices at the same time was found. These key numbers are presented in Table 5.1.

CO2

ppm

TVOC

ppb

Temperature

°C

Humidity

%

Noise

RoomAlyzer 470 240.5 28.0 35.3 41.6

Difference between

lowest and highest average

Maximum difference between

lowest and highest measured

value at specific point of time

Uhoo 487 29.6 26.4 33.9

Sens’it 26.9 39.5

IC-meter 427 27.4 33.1 32.6

dB

60 207.9 1.6 4.6 9.0

128 279.9 2.4 7.5 13

Table 5.1: Key numbers from the 24h measurements

The data for each of the parameters measured by the devices was then plotted on chronological

graphs presented in the following pages. This compares tendencies for the measurements with the

different devices. Similar tendencies during the 24 hours could indicate that the devices use similar

or comparable sensors. Different tendencies could indicate different sensors or sampling methods

within the devices or different quality of the sensors.

Furthermore, box plots, also presented in the following pages, were used to visually display the data

and distribution. The box plots were used to display differences in standard deviation between the

devices. The size of the boxes were used to indicate if the measurements were characterised by high

fluctuation or by steady values.

The price and accuracy for the devices refer to the values and intervals from the market research. The

accuracy is referred to as ”claimed accuracy” as it is solely information from producers as opposed

to scientific tests.


The average CO2 measurements presented in Table 5.1 indicate lower measurements using the IC-

Meter compared to the uHoo and RoomAlyzer. Figure 5.2 and 5.3 show that the RoomAlyzer had

highly fluctuating measurements compared to the other devices. The fluctuation, according to producers,

is most likely due to the sampling method of the sensors and not the type of sensor. Since all

of the devices use a type called nondispersive infrared sensor for the CO2 measurements. Furthermore,

the use of a smoothing algorithms on CO2 measurements, which is common practise, could

explain the stability of the uHoo and IC-Meter curves. However, these methods are not used by any

of the producers [115] [103] [98]. The IC-meter is higher priced than the other devices and claims to

have a higher accuracy than the other devices within this parameter.

Figure 5.2: 24h CO2 measurements

Figure 5.3: 24h CO2 box plot


Table 5.1 shows that the average for TVOC measurements with the Roomalyzer was higher than

the uHoo. This can be seen on Figure 5.4 which also indicates different tendencies during the 24

hours. Furthermore, Figure 5.5 shows a greater difference between lowest and highest measured

value for the RoomAlyzer compared to the uHoo. The RoomAlyzer and uHoo have similar price

point and similar claimed accuracy. The difference in the measurements was investigated through

communication with the producers and is most likely due to the different sensors. The TVOC sensor in

the uHoo measures following nine specific VOC’s: a-Pinene, d-Limonene, acetaldehyde, acetone,

hexanal, n-Decane, toluene, formaldehyde and benzene [98]. Whereas the TVOC sensor in the

RoomAlyzer measures all reducing and oxidising gases and is not selective towards specific gases

[115]. This difference meant that special attention was paid to measurements of TVOC with these

devices during the subsequent measurements in the offices.

Figure 5.4: 24h TVOC measurements

Figure 5.5: 24h TVOC box plot


The average temperature measurements presented in Table 5.1 show a higher average for the Room-

Alyzer and IC-meter compared to the uHoo and Sens’it. Despite the relative differences in the averages,

Figure 5.6 shows similar tendencies for the four curves during the 24 hours. Figure 5.7 shows,

that on average, sens’it records higher temepratures when compared t the other three devices. The

RoomAlyzer and the IC-meter has the highest claimed accuracy for temperature measurements

while uHoo and Sens’it has medium claimed accuracy. The IC-Meter is the most expensive, while

the RoomAlyzer and uHoo is medium priced and the Sens’it is the least expensive.

Figure 5.6: 24h temperature measurements

Figure 5.7: 24h temperature box plot


Table 5.1 shows that Sens’it’s average relative humidity measurements are higher when compared to

the other devices. This can also be seen on Figure 5.8 which despite Sens’it shows similar tendencies

for the three other devices during the 24 hours. Figure 5.7 shows a higher relative similarity of the

measurements for the Sens’it compared to the three other devices. The RoomAlyzer and the ICmeter

has the highest claimed accuracy for temperature measurements while uHoo and Sens’it has

medium claimed accuracy.

Figure 5.8: 24h humidity measurements

Figure 5.9: 24h humidity box plot


Table 5.1 shows that the average noise measurements using the Roomalyzer was higher than the

IC-meter. This can be seen on Figure 5.10, which also indicates different data trends and levels of

fluctuation during the 24 hours. The difference was investigated through communication with the

producers and it was most likely due to different sensors. The noise sensor in the IC-meter has a sensitivity

of 32-110 dB [103]. The plot of the IC-Meter data should therefore be interpreted as indicating

that the noise level was 32dB or below in the majority of the 24 hours. The sensitivity for the noise

sensor in the RoomAlyzer was not obtained. The price level of the IC-Meter is high and the price level

for the RoomAlyzer is medium. None of the producers provided the accuracy for the noise sensors

in the devices. The difference meant that special attention was paid to measurements of noise with

these devices during the subsequent measurements in the offices.

Figure 5.10: 24h noise measurements

Figure 5.11: 24h noise box plot


5.2 IEQ Investigation

The following part will present the analysis of the objective data in the form of measurements and

subjective data in the form of occupant questionnaires, both obtained during the investigations of

the three offices. The investigations were conducted in May and June 2020 and with a duration of

five weekdays for each office.

Based on the usability evaluation and measurement comparison in the preliminary study it was decided

to use the RoomAlyzer, uHoo and IC-meter for measurements in the three offices. Since the

different zones in the offices were measured with different devices, special attention was paid to the

TVOC and noise measurements due to the differences seen in the 24 hour study.

The time percentage within the three previously presented categories: good, acceptable and unacceptable

were calculated for each office and presented in accumulated bar charts. The categories

are indicated with green, yellow and red. The percentage of time in the different categories

are presented along with the percentage of occupants experiencing symptoms, which might be

related to a specific parameter and the percentage of dissatisfied occupants based on complaints.

Data presentation

The results are presented for each zone within the offices and indicated by names where ’Office1_1’

for example is zone 1 in office #1. Figure 5.12, 5.13 and 5.14 presents the results of CO2, TVOC and

PM2.5 which are the parameters within the IAQ category.

Figure 5.12: CO2 results

Regarding the CO2 measurements, it was observed that none of the offices had any measurements

in the category ’unacceptable’, but as seen in Figure 5.12 most of the offices had zones with measurements

in the category ’acceptable’. Furthermore, it was discovered that the CO2-concentration


was highest for zone 1 in each office. The reasons could be, that the entrance to the offices is all

in zone 1. Consequently, these zones might be more occupied during the day. Zone 3 in office #2,

also has a higher percentage of CO2 measurements in the category ’acceptable’, which could

be due to the connecting meeting room occupied by several people at specific times during the

days. Furthermore, it is interesting how the CO2 measurements in zone 1 in office #3 has the highest

percentage of time in the category ’acceptable’, as it was observed that the workstations in this

zone were not occupied during the investigation. However, this zone contained the entrance, a

coffee machine, and a small meeting table, which might cause more occupants to be in this zone.

The amount of occupants who experience symptoms varies throughout the zones and no indication

of a correlation between the measurements and the symptoms was observed. Anyhow, it must be

acknowledged that the experienced symptoms could also be related to other parameters or factors

than the CO2-concentration. The only complaint related to IAQ is odour. Zone 2 in office #1, is the

only zone with odour complaints. As well as for the symptoms, complaints can be related to other

factors than IEQ.

Figure 5.13: TVOC results

Regarding the TVOC measurements, most of the zones in the offices were within the category ’good’.

Despite this, zone 2 in office #3, has the majority of time within the category ’acceptable’. The

preliminary study indicated that the RoomAlyzer measures higher values than the uHoo, because it

measures more compounds then the uHoo. Hence this could also explain the higher values in zone

2 in office #3 since the RoomAlyzer was used to measure this zone. Comparison of measurements

in the 24 hour study and measurements in the three offices however indicated that the difference

between these two devices were smaller during the measurements in the offices than during the 24

hour study. This comparison can be seen in appendix G.


Figure 5.14: PM2.5 results

The uHoo was not included in the investigation of office #1 because of the captive portal network in

the office. Therefore, are no PM2.5 measurements results for this office. Anyhow, the symptoms and

percentage of dissatisfied for this office have still been included in the presentation. The majority

of the PM2.5 measurements are within the category ’good’, which indicates that the experienced

symptoms might be caused by other parameters or factors.

Figure 5.15: Temperature results

Figure 5.15 presents the temperature measurements. High temperatures are seen in the offices. The


majority of the zones in the three offices only have a small percentage of measurements in the category

’good’. This indicates a problem with overheating in all of the investigated offices. Several

complaints related to temperature were observed. Especially in office #2, which is the office with

the highest percentages of dissatisfied occupants.

Furthermore, the results indicate that the temperatures are higher for the zones further away from

the entrance. For both office #1 and #2, the zones are placed in continuation of each other. Zone

1 is for both cases the zone with the entrance. Reasons for the higher temperature in zone 2 and

3 can be due to a higher air change closer to the entrance. Office #3 zones are not placed in

continuation of each other. Zone 1 is the zone including the entrance, while zone 2 and 3 are placed

in either east direction or west direction. Zone 1 with the entrance still contains lower temperature

but furthermore, it was discovered that the zone with the West direction (zone 2) have a higher

percentage of temperatures in the unacceptable category than the zone in the East direction. This

might be a result of the sun’s path. For the stakeholders, involved in the process, knowledge about

peaks during the day might be interesting.

Figure 5.16: Humidity results

The humidity measurements showed, that humidity was not a problem in the offices. However, a few

complaints related to humidity were obtained. Yet, it must be acknowledged that these complaints

can be linked to the temperatures as well. As with the temperature, the percentage of dissatisfied is

highest in office #2.


Figure 5.17: Noise results

The preliminary study indicated that the RoomAlyzer measures higher noise levels than the IC-Meter.

Hence this could also explain the higher values in zone 2 in office #3 as RoomAlyzer was used to

measure this zone. However, comparison between measurements in the 24 hour study and measurements

in the three offices indicated that the differences between measurements with these two

devices turned out to be smaller during the measurements in the offices than during the 24 hour

study. This comparison can be seen in appendix G.

Furthermore, it is important to underline that the good category for noise is hard to obtain, as it is

based on the limit for background noise from building services and not occupants. Therefore, a

higher percentage in the acceptable category is not as ”bad” in this case.

An important part of the following benchmarking tool is visualising the results for relevant stakeholders

providing information they can use. Thus, it is important to select the relevant stakeholders and to

understand their pains and requests.


5.3 Stakeholders and Value

Stakeholder Matrix

Figure 5.18 presents the stakeholder matrix for the situation where a company, who owns and is the

main user of a building, wishes to improve their IEQ or renovate their office. This is representative of

the office buildings used in this project. Additionally, a stakeholder matrix for the situation where a

company rents an office space was also constructed and can be seen in Appendix C.

Figure 5.18 shows how the stakeholders involved in a renovation process or IEQ improvement are from

various sectors. Facilitating collaboration between these stakeholders could therefore help break

down the cross-sectoral knowledge silos.

The crowd which can be seen as potential stakeholders include craftsmen, suppliers, researchers

and engineers. The context setters, which can influence the development, use and promotion of

a benchmarking tool, are consultants and authorities. The subjects are the occupants because of

their high interest in a improved IEQ leading to heightened personal well-being and health. However

they have less influence on the major decisions regarding renovation of the office. The players, who

are the stakeholders with the highest interest and power, are the building owners in this case. Building

owners could help improve the power of the occupants by including their opinions and perceptions

of the IEQ in the decision-making process.

Figure 5.18: Stakeholder ’Power/Interest’-matrix

Since the occupants and building owners are amongst the stakeholders with the highest interest they

have been investigated further in this project. Because of the building owners high power in decisionmaking

regarding their office buildings, they have been the focus area concerning stakeholders

and their point of views on a possible benchmarking tool for IEQ. Therefore, building owners were

interviewed in order to gain knowledge about pains and gains related to improving IEQ.


Interviews with Decision-Makers

Based on the interviews with the decision-makers, which can be found in appendix E and F, a Value

proposition canvas (VPC) was created. The VPC, which is presented in Figure 5.19, was created in order

to ensure an alignment with the building owners’ needs and the properties of the benchmarking

tool.

In the interviews, the building owners expressed interest in investigation of status quo in the form of

IEQ audits and in improvement of the IEQ. The benchmarking tool should therefore include guidance

on investigation methods and/or simply provide this as a service along with the benchmarking tool.

A challenge that the building owners described was the complexity of a renovation process, especially

the lack of knowledge and lack of access to valid information. The benchmarking tool should

therefore propose a simple and easily understandable tool, explanation of IEQ aspects and access

to information, possibly in the form of an open database. Furthermore, they mentioned that problems

were often solved long after they occurred and that they were solved by trial and error in most

cases. The benchmarking tool should therefore include proactive suggestions and justifications for

IEQ improvement decisions. The last but most frequently described challenge was the economic

compromises that the building owners faced and the lack of knowledge on the economic aspect

of IEQ. The benchmarking tool should therefor shed light on and include this aspect.

The positive outcomes that the building owners expected from a renovation or IEQ improvement

included a healthier and/or more sustainable profile and proof. The benchmarking could therefore

include a form of certification. Moreover, the building owners expected healthier and happier

employees, and hence, occupant inclusion is important for the benchmarking tool. The building

owners explained that by renovating or improving the IEQ, they would expect a higher productivity

and economic gains. The benchmarking tool should therefore include economic estimations, which

can show the economics gains of improving the IEQ and hereby productivity of the occupants.

Figure 5.19: Value Proposition Canvas based on interviews


5.4 Benchmarking Tool

Based on both the stakeholder matrix and interviews with decision-makers, a benchmarking tool has

been developed. In the following part, the benchmarking tool and the reasons for its creation will be

described. This includes the weighting of parameters and categories, the subjective and objective

calculations behind the rating, economic estimations, and the future database.

Weighting

The weighting of IEQ parameters is not predetermined. There is no overall weighting used by the

different studied certification and benchmarking tools. The composed weighting in this study is inspired

by NABERS, research papers including a Green Building study, IQ compass, and DGNB. The

two IEQ categories with the greatest weighting percentages are IAQ and thermal comfort. IAQ is

assigned the greatest percentage as it has the most parameters to measure. Additionally, it has

been discovered to lead to more complaints. The weighting can be seen in Figure 5.20.

Figure 5.20: IEQ weighting

The four categories are further divided into subcategories, consisting of both objective data and

subjective data. The objective data are measured with the IoT devices and include measurements

of IEQ parameters such as temperature, humidity, CO2-concentration, noise, Pm2.5, and other pollutants.

While the subjective data is obtained by questionnaires and present the occupants’ experienced

IEQ. The subjective data includes SBS symptoms, experienced conditions, and user control.

Each subcategory results in a score contributing to a final percentage describing the offices’ IEQ.

The weighting of the subcategories can be seen in Appendix H.

The objective data is divided into three categories: good, acceptable, and unacceptable. In order

to calculate the objective subcategories scores, the percentage of time within the three categories

is multiplied with a factor as seen in equation 5.1.

Timein ′ Good ′ · 1 + Timein ′ Acceptable ′ · 0.5 – Timein ′ Unacceptable ′ · 1 (5.1)

Likewise, the subjective data is divided into four categories: Not in the past four weeks, 1-3 days in

the past for weeks, 1-3 days per week in the past four weeks, every day during the past four weeks.


Later named: Never, monthly, weekly, and daily. To calculate the subjective subcategories scores,

the first and fourth category is multiplied with a factor 1, describing 20 out of 20 workdays, the second

category is multiplied with 0.1, describing 2 out of 20 workdays, and the third category with a factor

0.4 describing 8 out of 20 workdays. The equation used to estimate the score can be seen in equation

5.2.

Never · 1 – Monthly · 0.1 – Weekly · 0.4 – Daily · 1 (5.2)

Grading

The final percentage is calculated and the offices can be evaluated. The evaluation is based on a

grading scheme, a radar, and outlined in a detailed report. The grading scheme has been developed

in light of the market research. As stars were the most common grading scheme, they were

selected. The offices are evaluated on six levels inspired by NABERS. The distribution of stars and their

respective percentage levels can be seen in Table 5.2.

[0-40%] = Poor IEQ =

]40-50%] = Below Average IEQ =

]50-70%] = Average IEQ =

]70-80%] = Good IEQ =

]80-90%] = Excellent IEQ =

]90-100%] = Market leading IEQ =

Table 5.2: Grading distribution

In addition to the grading scheme, a radar has been developed to show the score distribution of

each of the categories and subcategories. The radar aims to create a quick and simple overview

and provide a more detailed justification of the reason behind the office’s grading score. The radars

were developed for each of the offices and are presented in Figure 5.21 and Figure 5.22.

(a) Office#2 (b) Office #3

Figure 5.21: Radar for office #2 and #3


Figure 5.22: Radar office #1

As seen in Figure 5.22, the radar illustrates the four categories’ weight distribution and furthermore

the weighting of their subcategories. In the middle of the radar, the office’s final score is illustrated.

As seen in the figures the office with the highest score is office #1, while office #2 and office #3 almost

scored similarly. Office 1’s grading is four stars, while office 2 and 3 only scores three stars. Furthermore,

the radars visualise the low scores in the category: thermal comfort, which is mostly due to the

observed overheating in each of the offices.


Economic Estimations

In addition to the rating, the economic benefit of improving productivity has been investigated. A

percentage predicting a potential productivity increase has been calculated for both offices and

their zones. The calculations are based on the project ’Totalværdi Indeklima (2017)’ [110][110].

Office #1 Office #2 Office #3

Total productivity increase

3,8 % 3,7 % 3,5 %

Zone 1 Zone 2 Zone 1 Zone 2 Zone 3 Zone 1 Zone 2 Zone 3

3,4 % 4,2 % 2,1 % 4 % 5 % 2,6 % 4,3 % 3,7 %

Table 5.3: Potential productivity increase

Table 5.3 presents the potential productivity increases. The results highlight the zones with the greatest

potential productivity improvements. Furthermore, the Table illustrates how office #1 is the office

with the greatest productivity increase percentage, although it is the office with the best grading.

However, it is important to acknowledge that the results are only based on objective measurements

of temperature and CO2-concentrations and they do not include subjective data from this office

study. Office #1 is the office with the least complaints and symptoms related to both temperature

and CO2, whereas office #2 is the office with the most complaints and symptoms.

Moreover, another important determinant is the measuring period. In this case, the period was a five

days period in either May or June where the weather was sunny. A five days period during summer

does not reflect the office during an entire year and the measuring period should for subsequent

testing be extended or repeated throughout the year.

In addition to calculated percentages, a graph was constructed illustrating the potential cost saving

due to improved productivity for each office. The graph is illustrated in Figure 5.23. The graph can

be described by Equation 5.3.

Employees · Currently yearly salaries · Potential productivity increase percentage (5.3)

The graphs provides decision-makers with an idea of potential saving due to increased productivity.

The cost saving depends on the average monthly salary for the occupants in the offices. If office #1

occupants’ salaries in average are 40.000 DKK monthly, the office could yearly save approximately

up to 110.000 DKK yearly by improving the temperature and CO2-concentration. The graph can

thereby be a help in decisions linked to improving IEQ.


Figure 5.23: Potential cost saving savings for office #1

Database

The benchmarking tool should include a database, where stakeholders can share knowledge and

retrieve guidance related to the problems occurring in their offices.

The purpose of the database is to avoid stakeholders’ trial and error, and instead, provide them

with knowledge about solutions which worked or did not work in other offices. Furthermore, the

database should provide opportunities to benchmark offices, and compare different trials in similar

offices to find the best solution. This could include everything from interior layout to window types.

The database should contain data from offices from all over Denmark in order to represent a great

variety of offices regarding size, year of construction, building materials, occupancy, means of use

etc.

The importance of a such database lies in its ability to provide stakeholders with knowledge, experiences,

innovative ideas, and solutions.

5.5 IEQ report

After the development of the benchmarking tool, a template for an IEQ report was developed. This

template was used to create a detailed IEQ report for each of the three offices. The purpose of the

report is to provide stakeholders with detailed information concerning their office and possible IEQ

issues. The report was constructed like a newspaper article, with the most important first to obtain


the undivided attention, and then slowly getting more detailed and ending with a summary. As presented

in Figure 5.24, drafts of the report were tested during two feedback session with stakeholders

related to the three offices, and then a final report was developed. The report includes visualisation

of both the objective and the subjective data, peaks and an encyclopedia.

Figure 5.24: IEQ Report development process

Feedback sessions

The feedback sessions were conducted as an informal presentation were the stakeholders were encouraged

to ask questions and comment upon the content. During the feedback sessions the stakeholders

comments and suggestions were noted or written on a printed version of the IEQ report as

seen on Figure 5.25 and 5.26.

Figure 5.25: Feedback session #1 Figure 5.26: Feedback session #2


Feedback from the first session included comments on the level of detail. The decision-makers were

interested in detailed graphs and information for each zone in the office and not just the whole

office as the first draft presented. However, they liked the introductory overview with graphs for the

whole office. Regarding the grading scheme consisting of 1-6 stars, they mentioned that they would

like to see the different percentages that would lead to different number of stars. For the plots of

IEQ measurements and understanding hereof, they would like the graphs to include the red area

which is the category ’unacceptable’, in order to see if they were close to reaching it. Furthermore,

they were interested in the peaks on the graphs and the exact day and time for these, since they

wanted to be able to understand if the peaks were related to the cleaning, weekly meetings or other

scheduled factors. The decision-makers mentioned that a simpler presentation of the percentage

of occupants with symptoms and complaints would be useful. Lastly, they mentioned that a form of

summary of the results would be helpful in order to understand their IEQ issues better.

Feedback from second session included minor improvements. The feedback was very positive, and

the decision-makers were positively surprised about their results. Furthermore, they easily understood

the flow of the report and its content. Received feedback included were to include peaks in each of

the zone graphs as well as the overall graphs. Furthermore, they were interested in knowing in which

zones the complaints occurred. In the first feedback session, summaries were requested. These were

made before this feedback session and the response was very positive. The decision-makers said the

summaries aided them en understanding of the results.

Content of the report

First, the decision-makers were presented with the results of their office. This includes both the grading

scheme and the appurtenant radar. Figure 5.27 illustrates an example of the presentation of the

grading scheme.

Figure 5.27: Grading scheme results for office #1

After presenting the granted rating for the office, the four IEQ categories’ scores are presented, as

seen in Figure 5.29. The purpose of this is to provide the stakeholders with a quick overview of the IEQ

categories with either a low or high score. Furthermore, it works as an introduction to the following

parts of the report, where each of the four IEQ categories data will be presented.


Figure 5.28: Office #1’s grading scheme results for the four IEQ categories

Each of the IEQ categories’ presentation starts with a short descriptive text to guide the reader and

then it presents the symptoms and complaints related to the category. Furthermore, it has a short

explanation of what the following part will include: peaks, symptoms, complaints, and a summary.

The summaries includes the considerations made during the IEQ investigation of the data. In addition

to this, the presentation contains smileys representing the three measurement categories: good,

acceptable, and unacceptable. An example hereof can be seen in Figure 5.29.

Figure 5.29: Grading results for IEQ categories


The more detailed part of the category is then illustrated with graphs for each of the measured

parameters related to the category. The graphs show the measurements within the five days measuring

period. First, the results for the whole office are presented in one graph. Thereafter, each zones

measurements are presented individually. An example of the graphs is illustrated in Figure 5.30.

Figure 5.30: CO2 measurements for office #1

The graph illustrates the CO2 measurements for office #1. As office #2 was divided into two zones,

both zones are illustrated in this graph. The graph illustrates the measurements during office hours.

To help the reader understand the measurements, the three measurement categories’ intervals are

highlighted in the background of the graph. Likewise, the peaks are highlighted and their times are

listed in the report. Furthermore, the graphs contain the smileys and percentages representing each

of the measurement categories.

The graphs are accompanied with the related symptoms. The visualisation presenting the symptoms

is presented in Figure 5.31. The visualisation shows how many percentages of the occupants, who

experience symptoms, which could be related to the measured parameter. The symptoms can be

experienced either daily, weekly, monthly, or never.

Figure 5.31: Symptoms related to CO2 for office #1


Moreover, the graphs and symptoms are accompanied by related complaints. The visualisation illustrating

the complaints is presented in Figure 5.32. Like symptoms, the complaints can be experienced

either daily, weekly, monthly or never.

Figure 5.32: Complaint related to CO2

The presentation of the parameter’s measurements and related symptoms and complaints ends with

a summary. The summary sums up what the previous pages showed, and what was discovered in the

IEQ investigation. Afterwards, another parameter or IEQ category is presented, and the productivity

increase percentage for the office. All of the reports are presented in Appendix J.


CHAPTER 6

Discussion

Chapter 6 presents an interpretation of the achieved results

along with a description of the significance of the findings of

this project. Furthermore, it sheds light on the uncertainties and

the limitations of the use of IoT devices and IEQ benchmarking.

Chapter 6 discusses the variances in results, measurement

period, GDPR, privacy and occupant questionnaires. Furthermore,

it comments upon the weighting of IEQ parameters, the

identified and involved stakeholders , and the economic estimates.

Lastly, it describes the future implication of the project

focusing on statistical modelling and sustainability.

6.1 IEQ Investigation

Preliminary device evaluation

The preliminary device evaluation concluded that the ease of setup was dependent on the power

source and connectivity. The devices with battery and a sim card like Sens’it and RoomAlyzer had

fewer setup steps and were easier to install. These devices could be installed faster and more discreetly

since they did not need WiFi or extension cords for a power supply. Moreover it was concluded

that the calibration time is essential if the devices are used in several different locations. Regarding

this, RoomAlyzer, Sens’it and IC-Meter are preferred as they are calibrated from the producer and

has auto-calibration when in use.

In order to minimise the number of devices to be used, it is also preferable to select as few devices

as possible which alone or collectively cover all parameters planned to be measured. Furthermore,

the communication and service provided by the producers turned out to be crucial for this project.

RoomAlyzer, uHoo and IC-Meter were the most reliable regarding response rate and helpfulness.

Based on the conclusions of the preliminary device evaluation it is recommended that, if a number of

IoT devices should be used in the PhD study, Foobot and Sens’it should not be used. IC-Meter could

be used, however it only measures four parameters. The recommended combination of devices is

uHoo and RoomAlyzer which collectively measure 12 relevant parameters. For uHoo, whose main

focus is IAQ, two devices would be ideal for an office of 100 m 2 . For RoomAlyzer, which has a broader

IEQ perspective, one device should be used on each workstation if the light, occupancy or noise is

measured. Otherwise, two devices for an office of 100 m 2 is sufficient.

Variances in Measurement Results

The use of IoT devices for IEQ measurements in the PhD study should not be seen as a substitute

for highly precise measurement instruments, but rather as an alternative providing less accurate but

more immediate and more easily accessible IEQ data.

In this project more attention was paid to usability and inclusion of various parameters rather than to

accuracy and precision. This will always be compromised when measuring in office environments,

where occupant behaviour can influence measurements and conditions are changing. However,

it is important to have knowledge about the validity of the measurements in order to determine if

variety in results could be derived from the instruments or incorrect use hereof. Tests of the devices’

actual accuracy and comparison between different devices in a closed and controlled environment,

and with highly precise instruments used as reference values, would provide an interesting

and important perspective of these IoT devices.

Some of the devices used in this project can cover areas of up to 100 m 2 and in some cases more.

Despite this, it was decided to divide the offices into 2-3 zones of approximately 20-50 m 2 for greater

precision, and to have the possibility to detect differences in the office’s IEQ. For projects where

even greater precision is desired, the offices could be divided into more zones or each workstation

could represent a zone. Defining each workstation as a zone is especially useful when measuring

occupancy, light, and noise since these can vary greatly from one workstation to another.


Measurement Period

The measurement period in the offices in this project was five weekdays per office. With a sampling

frequency of 1-15 minutes depending on the device, this resulted in between 180-2700 data points

per device per office. While this amount of data is enough to perform statistical analysis on the IEQ,

it is not enough to make general conclusions about the IEQ in the offices. For projects with a greater

time frame the measurement period could be expanded to one whole year as in LBC’s certification,

or to multiple individual measurements distributed evenly throughout the year.

GDPR and Privacy

The strategy for DTU 2020-2025 focuses on technology for people, which means that projects and

technologies should benefit and be used in favour of the people [116]. In an IEQ measurement

perspective, this means that focus on ethics and privacy are important aspects concerning the use

of IoT devices and storage of data.

For this project, the GDPR compliance and privacy policies for the devices and dashboards were

investigated. Even though all of the devices complied with the GDPR, it is still important to consider

the ethical aspects. There is often a fine line between measurements and surveillance, and the

objectives of the measurements and the way of conducting them are often the determining factor.

In this project, the objectives of the measurements are the possibilities to improve the IEQ which

would benefit the occupants’ health and well-being.

Occupant Questionnaires

Regarding the use of questionnaires to obtain data on the perceived IEQ, it was decided to use

anonymous surveys in this project. This was done in order to avoid that the respondents would elude

answering some questions because of concerns regarding the consequences of their answers. However,

it should still be taken into account that answers are solely based on the respondents’ perception

and memory, which means they might not be a true reflection of reality. For instance, it could

be difficult for occupants to remember the amount of days with symptoms in the past four weeks.

Another aspect of the use of questionnaires is the response rate. In this project a 100% response rate

was obtained. However, this might not be the case in similar or larger projects. This could lead to a

false positive or false negative average of perceived IEQ, and should be taken into consideration.

In a case where a low response rate is obtained, it could be that only occupants who were over

or under average satisfied responded. This would also lead to false positive or negative average of

perceived IEQ. To avoid these false positives or negatives a minimum response rate could be set as

an requirement. A rule of thumb in questionnaires for scientific use is that a response rate of 60% or

higher is acceptable [117].

6.2 Benchmarking tool

IEQ weighting

Since there is no existing definitive weighting of the four IEQ categories, the weighting often varies

within different benchmarking tools. The weighting for this benchmarking tool was developed based

on the market research and research papers. The weighting includes both objective and subjective


data in order to include as many aspects as possible. The objective and subjective data are subcategories

with the IEQ categories contributing to their associated IEQ category’s final score.

The weighting of some of the subcategories were not representative for the entire office. An example

hereof is light. Since light was only measured by one device in this project, it would not be

representative for the whole office. However, the light level as a subcategory is included in the rating

calculation sheet, so the benchmarking tool can be applied in other projects where light levels are

measured at more points. The offices in this study were granted top scores in this subcategory. Furthermore,

the visual comfort was defined by the distance from the workstations to a window, artificial

light at workstations and related symptoms and complaints.

In a future IEQ investigation, light levels should be measured at each workstation to make it representative

of the visual comfort. The developed calculation sheet for the rating has been created so

it can easily be modified in order to match updated guidelines or an adjusted weighting.

Stakeholder involvement

The stakeholders relevant to an IEQ improvement were identified through a stakeholder analysis. Occupants

and building owners are amongst the stakeholders with the highest interest, but as building

owners also have high power, they are the decision-makers in a renovation process or improvement

of IEQ. Thus, the building owners of the investigated offices were interviewed.

A great deal of this project has relied on stakeholder involvement. The stakeholders were involved

to get an understanding of the challenges they might face before renovating or improving IEQ,

but also to get feedback on the developed benchmarking tool and report. However, both of the

companies are related to or within the building industry. This might have led them to have more

interest in the project and more knowledge about renovation and IEQ compared to building owners

and occupants who do not work in this industry. While the concept of the benchmarking tool and

IEQ report might have been easier for them to understand, they could also be more critical in the

feedback sessions. Involving decision-makers from other industries to ensure that the benchmarking

tool and IEQ report features all relevant information would be interesting.

In addition to this, since all the decision-makers involved in the the project were building owners, the

tenants and administration companies are not represented. It would have been interesting to conduct

a feedback session with these stakeholders, and include them in the development process of

the benchmarking tool and report. This could ensure that the benchmarking tool would be relevant

for several types of decision-makers.

Regarding the stakeholders it would be interesting to also include researchers, consultants, authorities

etc. in the process of development. This could ensure that the database and benchmarking

tool could help breaking down the knowledge silos across sectors and benefit more stakeholders.

The ideal outcome of a database and benchmarking tool would be, that it could not only inform

but also inspire different stakeholders to collaborate in finding new solutions for better IEQ in offices.

Moreover, considering how to retain a positive view on data and knowledge sharing could be explored.

Transparency in the building industry could allow for better collaboration and it is therefore

important to keep the building owners willing to share data on their buildings.


Economic estimates

Regarding the economic aspect of the benchmarking tool, the estimates in this project are only

based on the measurements of CO2 and temperature. As more research about IEQ and IEQ parameters

are conducted, it would be interesting to explore, whether more parameters or data could

be included as well. This could be both objective data and subjective data. Occupants that complaint

about the IEQ might be less productive. Furthermore, it could be interesting to incorporate the

economic calculations more in the benchmarking tool and in statically models.

6.3 Future implications

Statistical modelling

As the data set in this project was relatively small, no statistical/predictive models were developed.

However, as the database expands actual benchmarking would be possible. As a part of the benhcmarking

it would be interesting to apply statistical models on collected and aggregated data.

Statistical models could be used to diagnose and forecast using IEQ data, symptoms, complaints

and implemented solutions. Thereby, decision-makers would be able to explore which solutions entails

better IEQ along with happier and healthier occupants. The next step in investigation and automation

through IoT devices would be to develop algorithms and rule-based actions based on the

IEQ data.

Sustainability

As the world moves towards a greener future, it would be relevant to include a sustainability perspective

in the benchmarking tool and database. Many companies wish to appear sustainable.

Whether this would require another benchmarking tool or not is uncertain. As the market research

on benchmarking tools already includes certification and benchmarking focusing on sustainability,

a tool or a cooperation with one of these, for instance DGNB, which is the most common certification

in Denmark, would be interesting. This would also be a part of breaking down the knowledge

silos across different sectors and would in the end benefit even more stakeholders.


CHAPTER 7

Conclusion

Chapter 7 describes the final conclusions of the project and

the contributions to the PhD study. It presents conclusions related

to IoT devices and the IEQ investigation through measurements

and questionnaires. Moreover, it describes the developed

benchmarking tool and IEQ report based on feedback

from identified stakeholders

7.1 Fulfilment of objectives

The fulfilment of the objectives in this project consisted of two parts. One part focused on measurement

devices and IEQ analysis. Another part focused on stakeholders and the development of a

benchmarking tool including an IEQ report. The outcome, of the two parts combined, was a greater

understanding of both measurements, visualisation, and benchmarking of IEQ in offices.

Benchmarking investigation

The characterisation and comparison of existing benchmarking tools resulted in an overview of 21

benchmarking tools and certifications. The majority of the investigated tools and certifications included

all IEQ categories and the majority used stars as grading scheme.

IoT device investigation

The characterisation and comparison of available technologies within IEQ measurement devices

consisted of a market research including 21 IoT devices and a preliminary study of five IoT devices.

The market research indicated that higher priced devices have higher accuracy. The preliminary

study concluded that number of measurable parameters, power source, connectivity, calibration

time, service provided by the producer, and data accessibility were important aspects. Furthermore,

the recommended devices for measurements in offices are the RoomAlyzer and uHoo.

IEQ investigation

The collection of IEQ data in office buildings in this project was conducted in three Danish offices

during May-June 2020. The duration of the measurements was five days per office. Furthermore,

questionnaires were distributed to the occupants in the offices. The results, which were later used

in the developed benchmarking tool, indicated no issues with PM2.5 and humidity in all offices, minor

issues with the CO2, TVOC and sound in most offices, and major issues with temperature in all

offices. Furthermore, several symptoms related to CO2, PM2.5 and TVOC were registered, however

few complaints on air quality were made in any of the offices. Several symptoms related to temperature

and humidity were registered, and complaints caused by thermal comfort were made in all

offices. Some symptoms related to noise were registered, however few complaints related to noise

were made in any of the offices.

Stakeholder analysis

Building owners were identified as the most relevant stakeholders in this context. Through interviews,

their challenges were found to be the complexity of a renovation process, lack of knowledge, limited

access to valid information, and economic compromises.

Benchmarking tool and IEQ report

The developed benchmarking tool were based on the four IEQ categories: IAQ (35%), thermal comfort

(30%), acoustic comfort (20%), and visual comfort (15%). The tool included a grading scheme

consisting of 1-6 stars. To provide the building owners with a more detailed review of their offices an

IEQ report were developed. The report includes a radar, which features the four IEQ categories as

well as the related subcategories. Additionally, it presents economic estimates related to occupants’

productivity.


Feedback sessions

The benchmarking tool and IEQ reports were evaluated in feedback sessions with decision-makers

and subsequently optimised. The IEQ report, which was designed to be simple and understandable,

starts with an introduction and then illustrates the symptoms and complaints related to the IEQ

category. It then illustrates the IEQ data in graphs and visualisations, and ends with a summary explaining

the results to the decision-makers. Furthermore, the report contains an encyclopedia, where

parameters are explained.

7.2 Fulfilment of overall purposes

Through the fulfilment of the objectives, this project has contributed with an investigation and evaluation

of IoT devices useful for the PhD study. Furthermore, it provided insights on relevant stakeholders

and their motivation and concerns towards IEQ databases and benchmarking tools. Moreover, it has

presented a benchmarking tool which could potentially be used in the PhD study or as framework

for development of a benchmarking tool and database.

The work related to this project has resulted in a greater understanding of IEQ related issues in offices.

It has provided the possibility to explore IoT measurement devices and given an understanding of

possibilities and limitation of these devices. The project has provided a solid background for working

with indoor environment in a digital future. Lastly, it has suggested means to make IEQ parameters

and related issues visible, measurable and understandable to occupants and building owners.


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Appendix

APPENDIX A

Desk Study Sensors

Device

type

Price

DKK

CO2

± ppm

Temperature

± ◦ C

RH

± ◦ C%

Noise

±dB

Light

± Lux

VOC

± ppb

PM2.5

± µg/m 3 Other

Polutants

Roomalyzer [97] Commercial 1795 45 0.2 2 B NB-IoT

Power

source

Occupancy

Connectivity

TheO [77] Residential 1026 B 1 M

uHoo [78] Residential 2230 50 0.5 3 10 5 P

Awair [79] Residential 1200 75 0.2 2 10 15

Awair omni [80] Commercial 950 75 0.2 2 10 15

Huma-i [81] Residential 1000 B

Foobot [82] Residential 1300 1.0 5 10 4 P

Air mentor [83] Residential 2170 0.1 1 B

P

Sens’it [84] Experimental 522 0.5 4

B

Temptop [85] Residential 900 B

Wi-Fi

Bluetooth

Wi-Fi

Bluetooth

Wi-Fi

WPA

Wi-Fi

Bluetooth

Wi-Fi

Bluetooth

Wi-Fi

Bluetooth

Sigfox

Netatmo [86] Residential 1279 50 0.3 3 Wi-Fi

Laser Egg [87] Residential 1330 1.0 1 B 8 H Wi-Fi

Wave Plus [88] Residential 1878 30 0.1 1 B 1.5 Y Bluetooth

Air Visual [89] Residential 2000 B 4 H Wi-Fi

B Wi-Fi

IC-Meter [118] Commercial 4306 0.3 2

P LoRa

RYSTA [91] Commercial B 1 Y NB-IoT

Iclever [92] Residential 819 0.3 3 B Wi-Fi

Eve room [93] Residential 670 B Bluetooth

Sigfox

Hummbox [94] Commercial 2232 50 0.2 2 B 5 Y

LoRa

INSAFE+ [95] Residential 65 0.2 1 B 10 Y Sigfox

SIGLINK [96] Commercial 0.2 2 B 5 Y Sigfox

Power source

Battery life

P = Plugged in B = Battery H = Hours W= weeks M = months Y= Years Unknown value =

Market research on IoT devices with known values and details


APPENDIX B

Questionnaire







APPENDIX C

Stakeholder matrix

Stakeholder matrix for tenants.


APPENDIX D

Interview guide

Navn:

Rolle:

Arbejdsområde:

Questions related to the VPC customer segment: job(s)

Har I lavet nogle renovering, tilbygninger og ændringer de seneste år/eller prøvet at forbedre indeklimaet?

Hvis ja: Hvilke overvejelser har I så haft før denne tilbygning eller renovering?

Hvis nej: Så forestil dig at i skulle renovere eller tilbygge eller forbedre indeklimaet, hvilke overvejelser

har I før denne tilbygning eller renovering?

Hvad er/har processen været – hvem gjorde hvad?:

Questions related to the VPC customer segment: pains

1. Hvilke udfordringer har i haft?

2. Var der nogen hindringer eller bekymringer? (Lovgivning, regler, økonomi)

3. Var der økonomiske overvejelser/begrænsninger? Hvilke – hvad måtte man prioritere/nedprioritere?

4. Hvad skal man bruge af oplysninger/viden - hvad manglede i?

Questions related to the VPC customer segment: gains

1. Hvad er formålet med en renovering eller med at forbedre indeklimaet: er det energi, bæredygtighed,

godt indeklima eller andet?

2. Havde i overblik over de økonomiske gevinster ved at renovere/forbedre indeklima?

Questions related to the VPC customer segment: general

1. Har i certificering eller har i overvejet det? (DGNB eller lign. – Hvorfor/hvorfor ikke)

(a) Hvis ja: udfordringer?

(b) Hvis nej: hvad skulle der til?

Questions related to the value proposition: product/service

1. Man regner med at lave en database for kontorbygninger i danmark, hvor man kan dele og

sammenligner erfaringer både med henblik på renovering og byggeri.

(a) Hvad tænker i umiddelbart ville være nødvendig i en sådan database?

(b) Er der nogle oplysninger, i kunne tænke jer at få adgang til før en renovering eller tilbygning?


Questions = italic

APPENDIX E

Interview #1

Respondent answer related to value proposition canvas: ‘Job(s)’, ‘Pains’, ‘Gains’ and ‘Product’.

Navn: Niels Peter Frisesdal

Rolle: Daglig leder

Arbejdsområde: Sagsansvarlig inden for opgaver i byggeriet og alt hvad der er i jorden

Har I lavet nogen renovering, tilbygninger og ændringer de seneste år/eller prøvet at forbedre indeklimaet?

Ja, vi har prøvet at lave nogle tiltag. Først med solgardiner og så aircondition eller varmepumpe.

Hvilke overvejelser har I så haft før denne tilbygning eller renovering?

Jamen, vores problematikker var jo, at når vi havde vinduerne åbne for at skylle luften igennem så kom der

støv ind. Det var ubehageligt at sidde i, så vi måtte lave et lukket forum, som vi kunne være i.

Hvad er/har processen været – hvem gjorde hvad?:

Det foregår ved at inddrage dem inde i huset, dem der sidder i den pågældende del af kontoret. Så har de

lov til at komme med forslag og idéer til det. Så starter vi med at få solgardinet for, at se om det gav effekt. Og

det viste sig det var meget lidt, så havde vi sidenhen fat i et firma som havde med indeklima, eller aircondition

anlæg og nedkøling at gøre. Så drøftede vi med dem hvordan vi skulle gøre, hvordan vi fik luftstrømmene til at

cirkulere i rummet. Her er rimelig højt til loftet, så de foreslog det skulle sidde fra midten og ud mod væggene

i stedet for modsat. Derfor blev der sat to anlæg op.

Hvilke udfordringer har I haft? F.eks. at det er for varmt, folk klager osv.?

Vi har ind imellem godt vidst at det var for varmt, det er en mørk bygning og der er store vinduer i. Vi synes også

det var varmt og hedt at sidde i, på givne tidspunkter. Det er altid en udfordring om vi synes konstruktionen

og bygningsdesign skal ændres eller man kan lave det ved at lave luftskifte.

Så man ikke behøver laver en stor ombygning, men klarer det indefra?

Ja. En anden ting der har noget at gøre, det er de flader man har udadtil, hvor stærk isolerede de er, og hvor

meget varme de driver ind, men også hvor meget kulde de kan drive ind, f.eks. i vinduessamlinger og arealer

kan give begge dele.

Når I laver sådan noget om, har I så hindringer eller bekymringer f.eks. mht. lovgivning? Det kunne også være

luftskiftet – med henblik på træk eller lyset, bliver det for mørkt med gardinerne.

Nej det havde vi ikke. Men det var ellers et godt emne at vurdere hvordan lyset er. Vi har jo oplejret i kontoret.

Vi er her hyppigst kun i dagligdagen, men derfor er der jo stadig morgen og aften og sidst på dagen. Så lyset

det kan godt være det bliver det næste vi skal spekulere i, altså hvordan vi skal inddrage lyset i rummene. Men

lige præcis træk var en af de ting der var snak om, for at få luften til at cirkulere i rummet fra de anlæg der

skulle sættes om, så fordeling kom jævnt og blev drysset ned over medarbejderne i stedet for den blev blæst.

Det skulle det givne anlæg også, og det har vist sig det virker rigtig godt.

Har I været indover lovgivning, eller anbefalinger f.eks. anbefalinger til luftskifte?


Nej, det har vi ikke haft myndighederne inddraget i, ej heller nogle af. . . hvad skal vi sige ingeniørfirmaerne. . .

vi har stolet blindt på aircondition firmaet.

Har økonomi spillet en rolle i disse beslutninger?

Som udgangspunkt har vi en holdning til, at det der som regel er bedst, er også lidt dyrere, men på længere

sigt er det altid det billigst. Det er i hvert fald vores erfaring. Køb noget godt og ordentligt, det holder længere,

og man bliver ikke ked af det og træt af det.

Var der økonomiske overvejelser/begrænsninger, som gjorde at noget måtte prioriteres fremfor noget andet,

eller noget blev nedprioriteret.

Altså nu har vi taget det over tid, det der med at prøve at få nogle mørklægningsgardiner ind, var jo det vi

prøvede det første år, og så fandt vi ud af det ikke var nok, og så var det først sæsonen efter. Det er sådan at

vores problematik er størst når det er sådan vi har virkelig sollys på, og det er jo i Danmark i princippet kun en

kortere periode, og derfor har vi lavet tiltagene over et par år.

Mht. støvet, fik vi ny belægning på ude foran, så vi samtidig med mørklægningsgardinerne kunne dæmpe

støvet, sådan vi bedre kunne have vinduerne åbne, men vi synes sikkert det var nok, og derfor valgte vi at få

køl på.

Hvad skal man bruge af oplysninger/viden - hvad manglede i?

Bygningen er jo fra 2008, og fra 2008 burde man måske have været klogere og inddraget det i bygningen på

det tidspunkt.

Kunne problemet have været løst nemmere, hvis I havde haft oplysninger eller erfaringer eller idéer til løsninger?

Vi har jo et tilstødende kontorlokale, som har en anden type aircondition, og derfra af erfaring kunne vi se, at

vi skulle passe meget meget på, hvordan man sidder med hensyn til træk.

Modsat er der en anden problematik, det er at vi byggede i 2008 og byggeriet gik ned og vi måske godt kunne

fornemme at problematikken var der med varme tidspunkter, og der var økonomien nok ikke med, og derfor

blev det nok tilsidesat i en periode, indtil man synes nu kunne vi ikke tilsidesætte det mere og økonomien blev

bedre.

Formålet med ændringen I lavet, var det hovedsagligt forbedring af indeklima, eller energimæssigt for bygningen,

eller bæredygtigt?

Formålet har hele tiden været det skulle være et rum som var rart at være i, men dermed ikke sagt at når

man sætter aircondition op som er en varmepumpe, så kunne man faktisk godt bruge den modsat, til at tage

varme om vinteren, og derved har vi tænkt energimæssigt over hvordan vi kan bruge den.

Havde I overblik over de økonomiske gevinster ved at renovere/forbedre indeklima?

Som udgangspunkt har vi ikke haft problemer med fravær og sygdomme og lignende hos medarbejdere,

men folks glæde ved at være i et sted der til at holde ud at være, kan man sagtens høre. Folk føler sig absolut

bedre tilpas i lokalet efter ændringerne.

Har I nogensinde overvejet at få certificeret jeres bygning? Det er jo blevet mere moderne at få certificeret

sin bygning især mhp bæredygtighed, fx svanemærket, DGNB

Nej, det har vi ikke.

Hvad skulle der til?

At nogen kan drage nytte af det. Man skal ikke gøre det bare for at gøre det. Det skal gerne være noget man

fælles kan få noget ud af.

Man regner med at lave en database for kontorbygninger i Danmark, hvor man kan dele og sammenligne

erfaringer både med henblik på renovering og byggeri, men også så man kan ” lære” af hinanden. Hvad

tænker i umiddelbart ville være nødvendig i en sådan database?


Nogen steder man kan søge viden, eller rådgiver kan søge viden om hvordan tilstanden er og hvad vej man

bedst kan. Vi står jo selv både med en ældre bygningsdel vi skal have renoveret og nok have lavet bedre

indeklima i, men vi står også foran et nyt kontorafsnit som vi skal bygge indenfor en overskuelig fremtid. Så alt

viden der kan søges, kan kun være med til at bidrage positiv til fremadrettet renovering og indretning.

Er der nogle oplysninger, i kunne tænke jer at få adgang til før en renovering eller tilbygning?

Hvordan man gør noget mest enkelt og simpelt, for ting der er for teknisk, hvis mange skal håndtere det, så får

man aldrig det rigtige ud af det.

Har du andet? Det kan være orientering, vinduer osv.

Nu har vi tilfældigvis vinduer mod syd, og det er fordi vi skal have oversigt over vores areal den vej ud. Det giver

selvfølgelig udfordringer med vinduer mod syd, og alt hvad man kan drage nytte af, med problematikken med

vinduer mod syd ville selvfølgelig være at foretrække. Vinduer mod vest har selvfølgelig samme effekt, men

vinduer mod syd står solen nok at bager mest og længst tid i løbet af dagen. Men også for den sags skyld lyset

for nord af, som man ikke er generet af, altså man får rummene rigtig placeret, og man drager nytte af det

nordlige lys og man drager nytte af solen for syd, og altså erfaringer fra hvordan man placerer rummene og

hvordan man sidder, som den almene opbygning af et kontor er jo også vigtig. Det er jo ikke kun spørgsmål om

man bare får suget og blæst og styret temperaturen, og får nogle filtre på så det ikke støver, og får skærme op

så det ikke larmer, men bare den helt lavpraktiske simple indretning, hvordan man kan gøre noget lettest, så

der ikke skal være en masse tilvalg bagefter for at redde bygningen. Hvis man har en database eller eferinger

indenfor det, så starter man jo ikke fra nul hver gang man skal til at indrette.


Questions = italic

APPENDIX F

Interview #2

Respondent answer related to value proposition canvas: ‘Job(s)’, ‘Pains’, ‘Gains’ and ‘Product’.

Navn: Jesper Dyhr

Rolle: Produktionschef

Arbejdsområde: Overordnet ansvarlig for produktion at betonelementer

Har I lavet nogle renovering, tilbygninger og ændringer de seneste år hvor i har forsøgt at forbedre

indeklimaet?

Ja altså derude hvor i foretog målingerne – og det er jo sjovt at man sætter en ” skurby” op og

pakker ind i plader når man nu selv laver betonelementer, men det var den nemmeste løsning på

det tidspunkt. Så ja det har vi, vi har også bygget ovre i Søndersø.

Okay lad os tage Pavillonen som eksempel (der hvor vi foretog målingerne), hvordan er processen

når i går i gang med sådan en udvidelse af jeres kontor – altså fra i finder ud af at der er noget i

gerne vil have løst – til i går i gang med at bygge bygningen?:

Det aller første skridt i vores verden, det er at CRH jo er en koncern der på verdensplan har et sted

mellem 85.000 og 100.000 medarbejdere fordelt på cirka 40 lande, så hver gang vi skal foretage os et

eller andet i den sammenhæng, så skal vi ansøge ud i det store udland om nogle penge og midler,

og det er i store koncerner. . . i store koncerner er ikke-afkastgivende investeringer ikke altid dem der

bliver prioriteret højest. Hvis vi nu ville bygge en ny hal hvor vi kunne producere og tjene 10 millioner

ekstra om året, så ville vi have fuld opmærksomhed – men når vi bare siger at vi skal have mere eller

bedre plads til vores medarbejdere, hvilket jo selvfølgelig også er en del af at tjene de 10 millioner,

så er det knapt så nemt. Og grunden til at den ikke er bygget i vores egne elementer, det er ren

og skær økonomi. Det var kun fordi at det her kunne gøres billigere, og når ikke behovet var der

længere, så piller vi skidtet ned igen. Så økonomi har en enorm betydning – det har det alle steder,

det er ikke kun i vores.

Hvilke udfordringer, hindringer eller bekymringer har I haft inden i begynder at bygge det her, som

du selv har nævnt, kan det være økonomi, men det kunne også være i forhold til andre ting?

Ja det er jo altid udgangspunktet, altså det må ikke koste noget, men det skal helst ligne og være

en million.

Har der været andre hindringer eller bekymringer, f.eks. lovgivning, regler eller andet end det økonomiske?

Ja, ikke måske bekymringer, men i hvert fald overvejelser, der er jo også, på trods af at det kun

er to niveauer, rampe og elevator og alverdens ting og sager – selvom jeg ikke tror elevatoren nogensinde

har kørt, ud over den ene gang om året hvor den bliver tjekket. De der ting der nu skal

være, handikapvenlighed mm. – der er mange ting der skal tænkes ind i et byggeri.

Hvad har der været af økonomiske overvejeler eller begrænsninger der betød at i måtte prioritere

eller nedprioritere i forhold til indeklima eller andet?

Der er klart nedprioriteret. Sådan starter man jo altid. Det er ligesom når man finder en bil, så finder

man altid den største og den bedste først, og så kigger man på hvad den koster, og så finder man

den man har råd til bagefter.


Har i haft nogle oplysninger eller viden, som i har manglet eller haft brug for som havde været fint at

få i starten, men man måske først har fundet ud af bagefter?

Nej, ikke mig bekendt, men vi er jo også relativt godt inde i byggereglementet eftersom vi selv er i

byggebranchen – så der er ikke som sådan så meget der overrasker os.

Hvad var formålet med jeres tilbygning?

Det var ren og skær pladsmangel.

Hvad har i noget overblik over de økonomiske gevinster i har fået ved at bygge til?

Nej, det har vi ikke lavet noget regnestykke over. I bund og grund har det jo givet os arbejdspladser

nok, og det gør jo at vi har kunnet huse de medarbejdere vi har skullet have for at sikre gennemførslen

af vores produktion – som jo i sidste ende er den vi lever af. Men der er selvfølgelig en masse andre

ting før som vi også skal have med, så hvis vi ikke havde haft det, så skulle vi have været ude i byen

og købe det hos tegnestuer og betale overpris for det, men der er ikke lavet et regnestykke på det.

Har i overvejet at få certificeret jeres bygninger eller planlagte bygninger? F.eks. DGNB. Er det noget

i har haft tænkt over?

Nej er det korte svar, men hvis vi skulle bygge en hel ny fabrik, så ville vi selvfølgelig tænke over det,

for det er jo det eneste rigtige lige i øjeblikket, og der er jo en masse krav i den sammenhæng som

vi skal leve op til over for vores kunder, så det vil jo også være det rigtige at gøre selv. Og vi har en

del tiltag her i koncernen med genbrug af vand og lignende net op for at få et bedre regnestykke

på den konto. Der er klart et grønt fokus, men altid med økonomi lige ved siden af.

Hvis man skulle lave en database for kontorbyggerier i Danmark hvor man kan dele erfaringer og

sammenligne, både med henblik på renovering, men også med henblik på byggeri. Hvad har du

så af tanker omkring det – hvis du skal tænke på hvad der især kunnet være vigtigt at dele? Det

kunne være alt fra orientering af bygning, vinduer, solafskærmning, materialer.

Jeg synes ikke at jeg har så meget at dele. Det vi har bygget herude, blev holdt på et minimum, så

jeg tror ikke at jeg har noget at dele med hele verden på den konto.

Er der nogle oplysninger i kunne tænke jer at have adgang til før man vælger at lave en renovering

eller en tilbygning?

Jeg er usikker på om det er der vi ville søge vores oplysning, men hvis databasen er god nok, og den

bliver synliggjort nok, så vil det selvfølgelig være et sted man kigger. Man skal vi vide at det er der for

at lede. Altså man tror jo at det nemmeste i hele verden det er jo at gå på google og så har man

svarret på alt, og det har jeg så konstateret et par gange, at det har man ikke. I hvert fald ikke på

den måde jeg evner at søge på, på det jeg skal bruge lige i øjeblikket. Så synlighed er jo ekstremt

vigtigt – oplysning: ” det er her i finder det rigtige” .


APPENDIX G

IEQ Investigation

TVOC box plot comparison of 24h and total measurements

Noise box plot comparison of 24h and total measurements


APPENDIX H

Parameter Weighing

Acoustics

Objective 50%

SPL 50%

Subjective 50%

Symptoms 25%

Noisy 25%

Acoustic comfort weighting

IAQ

Objective 60%

CO2 35%

Particulate Matter 10%

VOC 10%

OP 5%

Subjective 40%

Odurs 20%

Symptoms 20%

IAQ weighting

Visual

Objective 50%

Light 25%

Daylight 20%

Correlated Light Colour 5%

Subjective 50%

Symptoms 15%

Lighting to dim 7,5%

Lighting to bright 7,5%

Glare 5%

User control 15%

Visual comfort weighting

Thermal comfort

RH 30%

Measurements 15%

Dry air 5%

Humid 5%

Symptoms 5%

Temperature 60%

Measurements 40%

To cold 5,0%

To hot 5,0%

Symptoms 10%

Other 10%

To much air movement 5%

To little air movement 5%

Thermal comfort weighting


APPENDIX I

Economic calculations

Equations for finding productivity percentages


Economic calculations for Expan


Economic calculations for Expan


APPENDIX J

IEQ Reports


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