Final report for the design research project:

DPD41-Apps on Wheels

Coach: Jackues Terken

Student: Tijmen van Gurp, s081936

Block: M1.2Date: June 18th 2013

Faculty of Industrial design,

Eindhoven University of Technology

“”

Measure the air quality with an

integrated sensor in your car

A P P S O N W H E E L S

INTRODUCTION

A while ago I was on the bike towards the university, I had haste because I

was already too late, with the speed I had I followed a buss quite closely for

a while and I smelled the diesel fuels as I was biking right behind the exhaust

pipe. I had to think about the module I had a week ago were we discussed

the possibility of a car as measurement instrument that could sense what

the air quality is. As I was bicycling the idea that this data is still “unknown

made me wonder if I could realize such a device that would tell me what the

air quality means for my health.

In this report you can read about how we measure the air, and how I pro-

pose a new system of measurement that makes the data more accessible

for people like me and you.

2

ACKNOWLEDGEMENTS

I would like to express my deepest appreciation to all those who provided

me the possibility to complete this report. A special gratitude I give to my

coach, Jacques Terken, who supported me through this research project

and helped me making my decision by sharing his knowledge and expertise

and help reflecti ng my own decisions.

Furthermore I would like the thank Jean-Paul Close for his devotion and

guidance during the process of this project and showing me the importance

of my work. A special thanks goes to Tiziana Marciello who helped me during

most of my process as a discussion partner and a constant reflection mo-

ment. And not to forget all my family friends and peer students who helped

me getting new ideas, spreading the questionnaire, and giving feedback on

my work when needed.

3

INTRODUCTION 2

ACKNOWLEDGEMENTS 3

AIQU 6

OVERVIEW PROCESS 11

ITERATION 0 2

MODULE EXPLORING BUSINESS LANDSCAPES 12

ITERATION 1 3

INTRODUCTION 13

WHAT IS AIR QUALITY? 13

UNDERSTANDING AIR POLLUTANTS 14

RESEARCH QUESTIONS 15

RESEARCH QUESTIONS 16

FIRST THOUGHTS ABOUT AIR QUALITY 18

INTRODUCTION 18

SITUATION WORLD 18

HOW IS THIS POSSIBLE? 19

SITUATION NL 20

CALCULATION MODELS 20

WHAT DOES AIR QUALITY MEAN FOR YOUR HEALTH? 22

INTRODUCTION 22

PM10 AND PM2.5: MEASUREMENT METHODS 23

WHY MOBILE MEASUREMENT? 24

CONCLUSION 27

REFLECTION POINT 31

ITERATION 2 32

INTRODUCTION 32

CO CONSTRUCTING STORIES 32

WHAT IS CO CONSTRUCTING STORIES? 32

MY SETUP 32

ITERATION 3 36

INTRODUCTION 36

QUESTIONNAIRE 36

RESULTS 37

EXPERT MEETINGS 37

CONCLUSION 39

CONCLUSIE EXPERT MEETINGS 42

Bibl iografie 46

APENDIX A 49

APENDIX B 50

TABLE OF CONTENTS

4

5

On the next pages you can see the

final result, but to realy experience

the inteded interactions I would

like to ask you to watch the folow-

ing video: http://www.youtube.

com/watch?v=h3td6gPeEMM

AIQUW

e live in a world where everything is avail-

able everywhere. Radical transparency (Le-

berecht, 2008) is in my opinion becoming

more and more important. Air quality is now something

the government supplies through various measurement

points that are static and don’t give sufficient informa-

tion about the air quality, to really know what it means

for our personal health.

I propose a system that enables you to measure the air

quality where ever you are. You are able to see your own

hyper local data combined with the data of many oth-

ers and the government as a reference. This system ex-

ist out of a sensor in your car and maybe in the future

even in your mobile phone, that measures the ultrafine

particles (UFP) in the air so that you can see what the

air means for you and for others through an intelligent

application wherever you are.

Through the various literature I saw that there is defi-

nitely a future for mobile measurement, as it gives in-

sights in your own health life, but through all this litera-

ture, I saw very few translations of what this data could

mean, and how it should be brought to a broader public.

My goal of this research was to find the right way of

displaying air quality data to the user so that it becomes

understandable in different levels what the air means for

your health.

6

The application starts with the

place you are at that moment. You

see the an abstract representa-

tion of the place . You have than

the option to scroll through the

different places, open de menu

or ask for more information of tha

particular place

When you have selected the city,

or persone you will a more de-

tailed graph. With the options to

look further in the past or future.

Tapping the graph willl give a pop-

up with more detailed information

of the day and measured value.

Here the options are proviced to

look for the weather Influences, a

map view, history of a place and

sharing. In this way there are in

total 3 layers of information, ab-

stract, overview, and in depth.

An important function is the op-

tion to look what the weather in-

fluences are on the air quality. The

app gives the possibility to open

an extra layer over the graph. No-

table relations will be put on the

screen as an extra layer.

7

You will always have the op-

tion to open the menu with all

the functions in one overview.

One of these functions is to

see your last driven routs. you

get an overview of the last

routes with an indication of

the amount of pollution. You

will have the option to open

these routes and explore in

depth what your mesurements

are.

your own measurements

should be visaly available on

the map. You will have the

option to zoom in and see in

detailed what you have mea-

sured.

In this screen it might also be

possible to see routes of other

people to compare your mea-

surements, or see the com-

bined result. Certain hotspots

can be discoverd, and action

can be taken acordingly.

8

What exactly does it mean for

your health? The app should

provide an indication of what the

scales mean for your health. Also

here there is the possibility to get

some extra information.

Only a scale might not be enough at

a certain point. The app should pro-

vide in depth information about what

we know about air pollution and the

health risks. This should be has infor-

mative as possible.

Once you know more about the health

effects you might wonder what we

can do about it. I propose an open

platform where people can suggest

ideas about how to help for a cleaner

tomorrow.

9

Extra information about why

certain actions are good will

be provided.

For the people who like to

have an overview the map of

the netherlands will be pro-

vided.

The app also has options to

save measured data or share

it to friends and family.

10

SituationAir qualityWorld, EuNL, NL

How do wemeasure now?

Litarature ResearchExisting systems

Movie:Summary ResearchConcept

Research Sensor

Questionaire

GUI Developement

Co-Constructing StoriesExpert meetingDerya Özçelik

Expert meetings

Module: Exploring businessLandscapesClient: Toyota

Iteration 1

Iteration 2

Iteration 3

Jan TheunissenJean-Paul CloseRené OtjesAlicia Sanchez CrespoCharles Rodes, Juana Maria Frans SnikHans CrijnsGabriel Dulac-ArnoldAnnemarije Andriga

VITO: Aireas:

ECN: NXP:

MicroPem: ISPEX:

Air quality Egg: Labocitoyen:

Researcher Philips:

OVERVIEW PROCESS

This semester there were 8 full-time weeks to work on the future of the car.

In the future, cars become much more than a simple extension of our legs.

Cars become personal cocoons that provide us with comfortable living

space, give us protection and shelter, they become adaptable to our needs

and will do far more than only drive us around.

The first 2 weeks were spend on defining the scope and research direction

of this project. The basis was already made in the module that I had in the

beginning of this semester.

In the first iteration I focused on learning as much as possible about air

quality. What is the current situation in the world, how do we measure it

now? Next to this I did an exploration if it would be possible to measure

mobile. During this research I noticed that there is a lot going on in the

world around this topic. I decided, for myself and to show to others, to

summarize the results of what I had found in a short movie about air qual-

ity.

In the second iteration I used parts of the movie to connect to others in

co-constructing story sessions, interviews, and expert meetings. I also ex-

plored if it would be possible to measure mobile myself, I decided that it

was better to invest my knowledge in developing the final concept further,

as it is still quite difficult to set up a good mobile measurement device.

In the final iteration I took the results of the Co-constructing stories ses-

sions and build a questionnaire around the new found insights so that I

could make my final design decisions based upon what functions people

found most important. Of course I also used my own intuition to make

the final interaction in graphical user interface design. More iterations are

needed to see if people understand it and if it fits their needs.

11

ITERATION 0MODULE EXPLORING BUSINESS LANDSCAPES

The basis for this project, Apps

on wheels, was found in the module Ex-

ploring business landscapes with the client Toyota.

The basis for the concept was found in this module. We

saw the car as an organism in an ecosystem that provides

information about its surrounding.

I believe in a future were all cars are interlinked and connected to

each other, helping us to get from A to B, live healthy and helps us

to connect to other people. As air quality becomes more and more

evident to be an important factor in our health and the car is one

of the factors that causes pollution, I believe the car should

measure its surroundings and adapt to it. The car be-

comes a tool that helps us understand the air

quality better so that we can react and

act upon it efficiently.

12

ITERATION 1INTRODUCTION

In the first iteration I focused on learning as much as

possible about air quality. What is the current situa-

tion in the world, how do we measure it now? Next

to this, I explored if it would be possible to measure

mobile. During this research I noticed that there is a lot

going on in the world around this topic. I decided for

myself, and to show to others, to summarize the results

of what I had found in a short movie about air quality.

Keywords: what is air quality, how can we measure it, is

mobile measurement something that is needed?

WHAT IS AIR QUALITY?

According to BC Air quality (What is Air Quality?, sd),

the term “air quality” means: the state of the air around

us. Most places nowadays measure multiple particles in

the air, these are sulfur dioxide (SO2), nitrogen dioxide

(NO2), Particulate matter (PM2.5 and PM10), (particu-

late matter), Ozone and CO. They are all related to each

other in certain terms, but in terms of health effect the

fine particles (PM2.5) are the most discernible.

The US EPA-mandated PM2.5 pollution index shows us

the following scale (Milward, 2011). The values you see

are in micrograms per cubic meter (µg/m³). The Worlds

health organization sees a yearly average of PM2.5 un-

der the 25µg/m³ as a healthy level. (WHO, 2011)

13

UNDERSTANDING AIR POLLUTANTS

Fine particle matter is one of the pollutants in the air,

these have sources that are both natural and human-

based. Fine dust is also caused by salt, sand and vari-

ous other substances, but nowadays humans contrib-

ute substantially more to the air pollution problem by

burning fossil fuels in automobiles, homes, industries,

and agriculture (Yelda Aydin Türk, 2011). These particles

effect human health negatively, people that suffer these

effects mainly live in big cities (K. H. Kilburn, 1992). Epi-

demiological and toxicological research that focused

on the role of the ultrafine particles (PM2.5) have indi-

cated that there is a statistically significant relationship

between atmospheric particle matter and admissions to

hospitals for respiratory tract infections and mortalities

(Lipfert F.W., 1995).

There are 2 different sizes of particles that are measured

PM10, and PM2.5. The coarser particles (between 2,5

and 10 micrometer) mainly exist out of particles that have

their origin in mechanical processes and windblown soil

dust. The finer particles (<2,5 micrometer) mainly exist

out of particles that have their origin from burning fu-

els in combustion engines (E. Buijsman, januari 2013). A

study has indicated that the association with mortality

was higher with PM2.5 than with PM10 (Schwartz J,

1996). These fine particles are believed to pose the

greatest health risks, because of their small size (ap-

proximately 1/30th the average width of a human hair).

These particles can go deep into the lungs and even the

blood stream (Kaiser, 2005).

WEATHER AND GEOGRAPHICAL IN-

FLUENCES

The ultrafine particles are floating around in the air and

are greatly influenced by the weather. The wind some-

times puts a layer of Sahara sand on cars in northern

Europe, transporting it for more than 2000 kilometers.

The same thing happens with fine particles and ultra-

fine particles. On a bit smaller scale, the geographical

location of a city also influences the amount of air pol-

lution. The air can be trapped if the city is surrounded

by mountains or because of an effect that is called an

urban heat island.

Urban heat Island

14

On an even smaller scale, a busy road with buildings

at both sides or an open road with grassland will have

completely different values. Also the amount of traffic

on a certain place and the amount of accelerating has a

lot of influence on the measured values. On high pres-

sure weather systems, when the air is inactive for mul-

tiple days the amount of particles in the air can build

up(Marcelina Arkouli, 2010). A heavy rain can also clean

the air and wash everything away (Giri D., 2008).

Monthly mean PAH concentrations on PM2.5 and ambi-

ent temperature in 2005 and 2006/2007.

WHEN DID WE START MEASURING?

Air pollution is something that we really started taking

into account when we started burning coals to heat our

houses in big cities. In 1952 London had to camp with

a lot of smog due to cold weather and windless period

(Stegeman John J., 2002). This initiated the clean air act

of 1956 (1956: Thick fog causes death on roads, sd).

It was until the 1970’s that we started to monitor the air

quality more sub sequential.

RESEARCH QUESTIONS

These Research goals

A sketch of a normal weather pattern (left), and an abnormal weather pattern demonstrating inversion (Encyclo-

pedia of World Geography).

15

RESEARCH QUESTIONS

These Research goals were formulated for the

midterm presentation together with the gained

knowledge of my literature research. Shortly

afterwards I reflected upon these research opportuni-

ties, and picked one out.

Does real-time, local data about air pollution

make people more aware towards their environ-

ment?

This question was my main research question in the

beginning, but it was too vague to continue. Questions

came up like, what is awareness and how do you mea-

sure it? Initially my plan was to see if the video I made

could change people’s behavior or awareness on the

topic air quality. This was too much into the direction

of social psychology and understanding awareness in-

stead of gaining knowledge that had a designedly pur-

pose. I don’t want to be the person that is going to tell

everyone the air is bad, I want people to get curious to

learn more about the air quality if they change behavior

for the better that is their own decision, as a designer I

can support that, but not force it.

One objective is to find out what the current

knowledge is about air quality.

This question arose out of a personal interest. My hy-

pothesis is that most people in the Netherlands have

no clue about what the air quality is. They probably will

have an opinion about if it is good or bad, based upon

what they have experienced or seen in the news. One

research paper also indicated that higher educated

people are more aware of the state of air quality than

low educated people (SIGIT SUDARMADI, 2001). As

the question stays interesting I will try to intertwine this

through my research, but it will not be my main focus.

Another objective is to find out if people are will-

ing to change their behavior if they have more

awareness about air quality.

My hypothesis is that people that are more aware

about bad air quality, become more motivated to do

something about it. But they will see it as a too vague

problem and something the government should solve

for them. I believe the small steps that they can take

to make a change should be magnified so that the

positive results we become clearer. For example, the

amount of PM2.5 that I will not emit if I take the train for

a yearlong instead of the car.

A design question what than arises is: how

should the data about air quality be visualized

and communicated, in such a way that it is inter-

esting for everybody?

In the end this is the question that I decided to work

out further. Therefore I needed to know what the gen-

eral connection towards air quality is and if a system

would exist with data about the air quality: how should

this be visualized?

The more needed information was: how would

such an information providing system would

work, in terms of presentation of air quality in-

formation?

In my personal opinion I believe that most sources that

provide information about air quality are not substan-

tial enough. The information is too limited, or present-

ed in such a way that a broader public doesn’t know

what to do with it. Information should be into context,

multilayered and interlinked to generate new insights

about what the air quality actually means.

16

17

FIRST THOUGHTS ABOUT AIR QUALITY

INTRODUCTION

After I had gained a better understanding about what air

quality is, I wanted to know more about the situation in

the world, the EU and the Netherlands. I looked at what

the world health organization had to say about it, the

political games around it and, not unimportant, how bad

is the air quality actually?

SITUATION WORLD

Air pollution, particularly in cities, is certainly not

a new problem. Back in the middle Ages the

use of coal in cities such as London was begin-

ning to escalate. The problems of poor urban air qual-

ity, even as early as the end of the 16thcentury are well

documented. (History of Air Pollution, sd)

Sins 2000 the amount of deaths caused by air pollution

has increased with 300%. For the first time in history

air pollution is on the top 10 list of killers! Meaning that

there are more people dying because of bad air than

from traffic accidents. (Latest finding listing air pollution

as one of top 10 killers in the world shocking, says CSE,

2012)According to the medical journal Lancet (H. Wang,

2012) in 2010 there were 3.200.000 million people who

died prematurely, 65 % of these dead’s were in growing

economies in Asia. 1.2 million Deaths in China which is

nearly 40% of the total amount. 712.000 deaths in south

Asia (including India), Europe and Russia: 400.000.

Outdoor air pollution is ranked fourth in the mortality

and health burden in East Asia where it contributed to

1.2 million deaths in 2010 and sixth in South Asia where

it contributed to 712,000 deaths in 2010 (H. Wang, 2012).

(WONG, 2013)

When it is realized that the health of 1.6 billion people

may be at risk from poor urban air quality, it becomes

clear that the issue ranks alongside such international

problems as acid rain, stratospheric ozone depletion

and even global warming (Elsom, 1996).

The Organization for Economic Cooperation and Devel-

opment, based in Paris, warned that “urban air pollution

is set to become the top environmental cause of mor-

tality worldwide by 2050, ahead of dirty water and lack

of sanitation.” It estimated that up to 3.6 million people

could end up dying prematurely from air pollution each

year, mostly in China and India (Development, 2012).

18

HOW IS THIS POSSIBLE?

Looking at where the air quality is the worst, now it is

clear that mainly in Asia we currently have situations

that in Europe are already long gone. Due to the eco-

nomic growth in many nations in Asia there is big in-

crease of motorized vehicles and coal burning power

plants. Since 1950 the world population has more than

doubled and the global number of cars has increased

by a factor of 10 (Fenger, 1999). The byproduct are the

smoggy smelly skies above cities like Bejing, New Dehli

and Jakarta (Walsh, 2012).

Regulations for coal burning and diesel filters need to

be applied to be able to reduce this growing problem, as

the growth has not yet become to an end and even more

people will get a car.

SITUATION EU

Since the early 1970s, the EU has been working to im-

prove air quality by controlling emissions of harmful

substances into the atmosphere, improving fuel qual-

ity and by integrating environmental protection require-

ments into the transport and energy sectors.

In 2008 the directive was written on ambient air quality

and cleaner air for Europe, herein is stated that for the

year 2020 the 3 year average of PM2,5 should be be-

low 18 μg/m3, and for the 3 year average in 2015, this

should be 20 μg/m3 (Official Journal of the European

Union, 2008).

Compared to Asian countries the air quality in the EU is

already very good, but we should not forget that in year-

ly averages over multiple measurement stations, can be

lower than on street level measurements in big cities.

19

SITUATION NL

After having seen the comparison between the

world and the EU, I was already quite satisfied

about the air quality and I wanted to know: how

do we measure in the Netherlands? What is the trend of

the air quality over multiple years? How are we in com-

parison to the rest of EU? For how much are we, our-

selves, responsible for the air quality and what about

our neighbor countries?

In the Netherlands the most important sources for hu-

man created fine dust are: traffic (40%), industry (23%)

and agriculture (20%). At least 45% of the fine dust in

the Netherlands is inflicted by humans and only a third

of this has its origin in the Netherlands itself, the rest is

from abroad (E. Buijsman, januari 2013).

Since we started measuring we have also increased the

norms in the emission standards for patrol cars, power

plants and other industries.

Although new cars will have these norms, there are still

a lot of old diesel cars imported out of Germany where

cleaner cars also mean reduction on the toll roads (Maut

of tol in Europa, 2012), (ANP, 2012).

Overruns of the European norms still exist next to busy

roads an in big cities. On places where measuring is not

possible, calculation models are used. These models

are not as accurate as the measurement stations. This

can give a distorted picture of the reality (GROEN, 2013)

(Wat is fijnstof?, sd).

I started looking at the data from RIVM and saw that

we are only measuring pm10 levels and not yet pm2.5

although this is already quite long known as the most

important factor to measure (De meetdata van fijn stof

(PM10) vanaf 1992 tot en met 2012 , 2013). I decided to

combine all the data from all the 63 measurement sta-

tions and I plotted this data with a moving average and

a linear trend line to see what the Air quality is doing

over the last 10 years. This information has to be seen

with a bird’s eye view, than it means that in general the

air is getting better. But what about all the places where

we are not yet measuring?

CALCULATION MODELS

On most places it is unknown what the air quality is, but

the air quality is estimated by calculation models. There

have been a lot of discussions about the models and

for most it is not clear how the estimates of quality are

made. Calculation models not always take into account

that there can be a flat or school next to a busy road,

there are just too many variables. If 80 kilometers or 100

kilometers per hour is needed to improve the air quality

stays uncertain, because the direct effect of these mea-

sures is not visible (Redactie, 2013).

20

Running average with data from 62 measurement stations of PM10 in the Netherlands over 1992 - 2012

21

W H AT D O E S A I R Q U A L I T Y M E A N F O R Y O U R H E A LT H ?

INTRODUCTION

Now you know the ins and outs of how and why we measure

you might wonder what precisely the health effects are. Al-

though there is little known what precisely the health effects

are, epidemiological research has indicated that there is a direct link

between the amount of particles in the air and hospital emissions.

The particles with the greater than PM2.5 and smaller than PM10 can

reach the upper part of the human airways and lungs. The smaller par-

ticles penetrate more deeply into the lung and may reach the alveolar

region. These fine particles only contribute slightly to the PM10 mass,

but may be important from a health point of view. Although it has not

yet been said what type of particles have a toxic effect and on what

levels this toxicity exist, many studies in the 1990 have documented

that an increase in particulate-matter is associated with an increased

daily mortality and hospital admissions for respiratory and cardiovas-

cular disease (Thomas Kuhlbusch, 2004).

PM is mainly discussed here, because it is a pollutant that effects peo-

ple more than any other. Particulate Matter exists out of sulfates, ni-

trates, ammonia, sodium chloride, carbon, mineral dust and water. The

problem of these particles are the biggest in developing countries, but

even in the EU the average life expectancy is 8,6 months lower due to

exposure to PM2.5 produced by human activities (WHO, 2011).

22

PM10 AND PM2.5: MEASUREMENT

METHODS

The precise measurement methods for measuring fine

particles are still quite complex. They are based on the

increasing mass of a filter and optical monitors, which

can gauge the size of individual particles from signals

scattered from a light beam and integrate this into a

total volume of particles (NPL, 2010).

23

WHY MOBILE MEASUREMENT?

In the earlier sections of this report you could read

about why we measure the air quality. Nowadays

governments only measure on fixed places and take

sometimes a temporarily measurement. Mobile data

collection allows for air pollutant concentrations to be

obtained with a higher spatial distribution and density

than is possible with stationary or passive monitors.

Cut stationary monitors are inadequate in distribution

to quantify the change of air quality on city street level

(Matthew D. Adams, 2012).

Although we know on a larger scale that air quality has

health effects, with moving sensor a whole new level of

social science would open. For example tracking asth-

ma patients to see if they suffer more when the air qual-

ity is bad (CNN, 2010).

A study of Energy research Centre (ECN) has proven

that a moving measurement system to be a useful tool

to measure the spatial variability of particle concentra-

tions. It allows investigation in location specific charac-

teristics that cannot be performed with multiple station-

ary monitoring sites. Their measurements show that the

number of the concentration inside a city changes on

a scale of hundred meters, these fluctuations correlate

with the local traffic intensity and driving conditions.

Their studies also indicated that 100 meters downwind

from a busy road are exposed to 40% more particles

than people living in urban background areas (E.P. Wei-

jersa, 2004).

24

Particle number concentrations along the way from the

urban agglomeration of Amsterdam to the marine area

near Petten

(averages over 500 m; CPC-measurements).

A study done in Mol, Belgium indicated that the amount

particles that you breathe in on the bicycle is significant-

ly higher (more than 4 times higher), than the amount

of air breathed in by a passenger in a car (Luc Int Pa-

nis, 2010). A similar study in the same city indicates the

same results as ECN and shows that the air quality is

significantly worse when motorized vehicles accelerate

after for example a traffic light (P. Berghmansa, 2009).

The same thing was noticed with the device named Citi-

Sense, which was able to measure local concentrations

of ozone, nitrogen dioxide and carbon monoxide. In a

test 30 people carried this device with them which al-

lowed them to explore their neighborhoods and recog-

nize bad places and moments on the day. One of the

effects that it had was that people who had to wait long

for the bus, or normally would take the bicycle, now took

the car, because this was clearly better for their health.

The devices they used were around the 1000US$ to pro-

duce (Piero Zappi, 2012), (Celal Ziftci, 2012), (Demchak,

2010).

One way to measure is the method of Citisense, but

they are not yet measuring the fine particles in the air.

They correlate to each other, but not significant enough

to know what the health effects are of the fine particles.

Therefore an optical dust sensor needs to be integrated

as well. This sensor will make the price of the sensor a

lot steeper (Wat is fijnstof?, sd).

Sensor module CitiSenses

25

A study carried out by the National Institute for Health

research in the UK (NHS) seven members of the public

were given personal pollution monitors that measured

black carbon. The cumulative exposure of the black car-

bon was compared between these members. In these

measurements there are clear characteristics visible in

the time spend outside (Brannon, 2012).

26

CONCLUSION

Air quality is mainly measured by the

amount of pm2.5 in the air. The higher

the concentration the worse it is for your

health. A healthy level of this substance

should be below 25µg/m³ according to the

world health organization. In many places

these values are not yet met and even in

places where in yearly averages the value

might reach this level there will always be

moments and places that have higher val-

ues.

A system of multiple sensors connected

to moving vehicles is needed to generate

a higher resolution map. Only in this way

we can learn what the air quality means for

our health.

A wide variety of these sensors are already

available, further research is needed to

see which combination of sensors gives

the most reliable results. The translation of

this data into a multipurpose application

that is understandable for everyone is now

the challenge to develop further.

27

FIRST ITERATION IDEATION: CONCEPTS

Although the basis for the final concept was already there

shortly want to discuss some future visions/concepts on

the future of cars.

This car designed by Anne Fisher of Pforzheim University

was one of the ideas I had in terms of the future car show-

ing what the air quality is. The public that would see this

car would be able to see when the air is clean or dirty

through the form changing aspects of the car. Possibly

this car could also filter the air responsively by moving its

scales up and thereby also redirecting the airflow through

filters. Other ideas that I had were more app based, which

I developed into a scenario movie. Next to a scenario I

also summarized my research in a movie so that for the

future I had something visual to get into contact with ex-

perts.

28

29

One of the ideas was to make a visualization inside the

car, on the dashboard, steering wheel or display that

would subtly indicate what the weather is outside.

After you have driven a route you could see your own

measurements on the map, and zoom in on the data.

This data is than visualized with some extra info of the

place, giving you insights in the past days or weeks of

that specific place. So that you can see how your mea-

surements relate to the measurements of others.

Other information channels should be linked to the app

so that particular bad or good situations can be ex-

plained in terms of causes of the air quality. For exam-

ple, when there are a lot of diesel trucks in the rush hour,

this might have effect on the air quality for that place.

Also the weather influences the air quality greatly and

should be connected to the app.

30

When telling people that the air is bad, the app should

also give clear information about possibilities to reduce

the amount of pollution.

REFLECTION POINT

While discussing my ideas with

others, I received questions about

why measure with a car? Is it not

promoting something green while

you are actually polluting the

world? Why not in your smart-

phone or on the bike if you are ac-

tually outside?

I see the car as a logical carrier

for the sensor, as it has everything

already on board power the sen-

sor, collect and process the data

and also share the data. The extra

costs for the sensor could be paid

by the car manufacturer as it only

will be a fraction of the total as-

sembly costs and could give new

meaning to the car.

I don’t think we will solve the air

pollution problem by just imple-

menting some sensors in cars, but

I believe it can greatly influence

our awareness of our surrounding

and let us make conscious deci-

sions for our future.

I also received some feedback that

I actually was not so much further

in terms of concept in relation to

the results of the module. I decided

that I had enough information for

now and needed to start exploring

possibilities in terms of concept

and realization.

31

ITERATION 2INTRODUCTION

After this literature research I was a bit stuck in how to

continue. The question was what to do with this new

gained knowledge. I did not had to prove anymore that

mobile measurement is indeed needed to complement

the static measurement stations. And that mobile mea-

surements can give you more insights into your own

environment. At this stage I noticed that the research

questions I had stated in the beginning of this semester

were too vague and I had to redefine my goals and di-

rection. In this section of the report you can read about

this in particular.

CO CONSTRUCTING STORIES

To get more ideas from users about how such an appli-

cation should look like I decided to use the method co-

constructive stories. I had thought about other methods

like a diary study or concept mapping sessions, but my

ideas and questions were still too vague to be able to

set something up.

WHAT IS CO CONSTRUCTING STO-

RIES?

Co constructing stories is a participatory design tech-

nique for early, formative concept evaluations to elicit

in-depth user feedback and suggestions, revealing at-

titudes and motivations of users (Derya Ozcelik Busk-

ermolen, 2012). The process exists out of 2 phases: in

the first face the user gets introduced into the context

in the sensitizing phase, the stage is set for a dialogue

about the users past experiences. Then an envisioned

future is presented with new possibilities, perspectives

and insights are shared.

MY SETUP

The session was started with a short introduction into

my research. With a warm welcome and a word of grati-

tude they were asked if they had thought about the air

for the past six months and if this was the case about

what. If not, the subjects were asked if they recognized

some situations or stories from the news. I asked for

situations if they had experienced the air as particularly

good as well as bad. After 15 minutes I proposed them

the situation that you could see wherever you are what

the air quality would be and how this would look like in

terms of interface/ system. I let this completely open,

but if it was unclear I stepped in to give some sugges-

tions.

For full detail setup look in appendix A.

CONCLUSION:

The Co-constructing story sessions were very helpful to shed

new light on the ideas I had. New directions came up like com-

paring different places, different layers of information (abstract

to more concrete), weather influences and the possibility to

follow someone else.

32

‘ ’ I no t i ce tha t I a lways take the same rou te to my

work , I somet imes th ink i f ano ther rou te wou ld

be be t te r. ’’

“ I wou ld l i ke to be ab le to see the a i r qua l i t y in

con tex t w i th someth ing l i ke goog le g lass o r an

ind ica t ion on a lamppos t . ”

“My fa ther a lways c loses the w indows o f the car

in a tunne l , th i s i s someth ing my car shou ld do

au tomat ica l l y i f the a i r su r round ing me i s bad .”

“The most in te res t ing aspec t I th ink w i l l be tha t

you cou ld measure toge ther, I wou ld l i ke to know

who and where o ther peop le a re measur ing .”

“ I wou ld l i ke to have a v i sua l i za t ion l i ke a dead

b i rd i f the a i r i s bad , someth ing tha t v i sua l i zes

what your l i f e expec tancy i s , and what i t means

fo r your hea l th . ”

“““ “

“

“ In i t i a l l y I wou ld l i ke to see the da ta v i sua l i zed

in an abs t rac t way w i th co lo rs on a map. I can

dec ide myse l f how my rou te w i l l be . ” “

33

“ I no t i ce tha t the a i r i s bad when I come back

f rom a p lace where the a i r was rea l l y c lean l i ke

in the mounta ins . ”

“My nav iga t ion shou ld g i ve sugges t ion where to

d r i ve , i t w i l l g i ve an a le r t i f i t i s poss ib le to

avo id a d i r t y spo t . ”

“For me a map l i ke a weather map w i l l be enough,

I know where ever ybody l i ves , I can see how i t

i s the re . I f poss ib le I wou ld l i ke to see the a i r

qua l i t y w i th goog le s t ree t v iew.”

“A compar i son be tween d i f fe ren t c i t i es i s maybe

someth ing tha t I wou ld l i ke w i th in the app , than

you ge t a b i t o f compet i t i on , bu t tha t i t shou ld

be c lea r what the fac to rs a re tha t have an in f lu -

ence .”

“ I wou ld l i ke to be ab le to compare my da ta w i th

the da ta o f my fa ther in Ch ina . Jus t pure l y fo r

my own awareness , I don ’ t need any sc ien t i f i c

g ibber i sh . ”

“Peop le who l i ve in a c lean g reen v i l l age now

have a way to say someth ing good about the i r

p lace .”

“Most o f the t ime you w i l l have the same rou te ,

so f rom th is rou te I wou ld l i ke to know what the

a i r qua l i t y i s . ”““““

“ ““

“ I wou ld l i ke to be ab le to see a compar i son

be tween p laces where I have b ine in my own

count r y. Fo r example Ro t te rdam vs . E indhoven.”“ “““

34

“The on ly moment tha t I can imag ine tha t I rea l l y

want to know more about i t i s when I wou ld buy

a new house .”

“ I no t i ce when the a i r i s bad when there i s a

2 tac t moped in f ron t o f me, I can sme l l the fue ls

even i f i t i s 400 meters in f ron t o f me.”

‘ ’When I have been in Haar lem I no t i ce the a i r

here in Oos te rbeek i s much c leaner. ’’

“ I t shou ld show the connec t ion be tween the w ind

speeds and w ind d i rec t ions and the a i r qua l i t y. ”

“ In fo res ts i t i s a lways c leaner r igh t? Trees f i l t e r

the a i r? Anyway, I wou ld l i ke to know i f th i s i s

t rue o r no t . “

“ I wou ld l i ke to know how I can con t r ibu te to a

be t te r env i ronment , fo r example change the way

how I d r i ve . ”

I don ’ t rea l l y no t i ce tha t i f the a i r i s bad , some-

t imes shor t l y when I sme l l someth ing bu t mos t

o f the t ime th i s i s gone immed ia te l y.“““ “ “

““

35

ITERATION 3INTRODUCTION

This iteration I focused on validating the possibilities of

the air quality app that I wanted to develop. I did this

through a questionnaire that was spread under 27 peo-

ple. Not the highest number to say something signifi-

cantly, but enough to help me in my design process and

give new insights and directions for further validation

and exploration.

This iteration had as result the design for the app AIQU

and recommendations for future development of a mo-

bile air quality device.

QUESTIONNAIRE

The questionnaire had as goal for me to find out what

functions are important to integrate into the app.

First I have asked some general questions about their

Age, location of residence and highest finished edu-

cation. After this, I asked them questions about how

important clean air is for them and what they thought

about the air quality in the Netherlands.

After that there was asked to imagine an application

and think about how this should look like. Directly after

this, there was an open question with the question if an

image of an existing application corresponded to their

imagination.

After this, there were questions about functionality of

the application and there was the possibility to indicate

how important this function was.

To see the questionnaire go to:

h t t p s : / / d o c s . g o o g l e . c o m / f o r m s /

d/1GeTssmPCLD1SkUZqd62AY2s_lg5vqFaKf6d-

wHqQGmHs/viewform

36

RESULTS

In the limited time available, the number of people asked

is quite limited. The results must be seen as a source

of inspiration and guidance for future studies. The fo-

cus for me was to get guidance and inspiration in how

to make the app. How the app is designed, is a direct

translation of the findings of the questionnaire with, of

course, my own intuition and design rationale.

Here are the most notable results of 27 people. If you

want to see all the results look at appendix B

Quotes from the open question:

I wou ld a l so l i ke to be ab le to f i l l i n rou tes f rom A to B in

the app over a map w i th co lo rs . I wou ld l i ke to have the

op t ion to ind ica te " impor tan t" p laces so I can see how the

deve lopment i s in tha t p lace . P laces such as home, work ,

schoo l ch i ld ren .

I wou ld l i ke to be ab le to c l i ck on someth ing to ge t ex t ra

in fo rmat ion .

I imag ined d i f fe ren t l eve ls wh ich demonst ra te how my

GPS loca t ion i s po l lu ted and thereby how bad the po l lu-

t i on i s in compar i son w i th hea l thy s tandards .

I th ink i t i s impor tan t tha t you communica te when some-

th ing changes and what tha t change rea l l y means . In a

s imp le and c lear way. Communica te i t so tha t the in fo r-

mat ion rea l l y can mean someth ing fo r ever yone .

I wou ld l i ke the poss ib i l i t y to ca lcu la te your own “ foo t -

p r in t ” on a i r po l lu t i on in genera l . Fo r example on the

amounts on f l i gh ts per year, us ing o f wood s tove , mate r ia l

consumpt ion e tc .

See append ix B fo r a l l the resu l t s , o r con tac t me person-

a l y fo r the Exce l f i l e : t i jmenvangurp@gmai l . com

EXPERT MEETINGS

To learn more about it is possible to measure mobile I

had several meetings, mails, phone calls with experts

on the subject air quality measuring. Here you will find a

list of people, and their expertise.

Name: Alicia Sanchez Crespo

Company: Tu/e Faculty Electrical Engineering

Worked on: How to measure air quality with chip of NXP,

stopped this because commercial sensors had become

better, they claimed to be able to identification individ-

ual particles.

Explained me: The sensor I worked on is an optical

dust sensor. The operation principle of these sensors is

that they have a light source, infrared LED, and a photo

detector. In absence of particles, the light doesn't reach

the photo detector.

37

“ What did 27 People think about the proposed ideas? ”

Want to be able to “follow” the air quality data of other people

12

Agrees upon the fact that their measured data will be open source.

27

22 Would like to be inadvance if the air quality would get bad. Wants to know how the dif-

ferent levels of air quality has health.

21

Want to get tips about how to contribute to a cleaner air outside.

22

Want to be able to see the connection between the weather and the air quality

24

Want to be able to see history data of a place,as far back as possible.

26

38

CONCLUSION

Although there were not that many users who filled in the questionnaire,

I received some valuable new insights. Most functions I presented were

accepted as valuable or important. Most importantly is that I found out

people like the information presented in such a way that they can make

sense of it themselves, without any extra information. The information

should be presented in multiple layers, first an abstract vizualsation and

after that the more complex data. Functions for sharing are important but

most just want the data to be open, so that people are able to follow your

data when they want to. The system should have a certain intelligence,

and give warnings when the air quality is getting worse.

The app should also cover some extra functionality besides providing in-

formation about your measured air quality, the overall air quality, and the

air quality in driven routes. The app should also cover the health risks,

and information about what you could do about it.

39

Name: Gabriel Dulac-Arnold

Company: Labocitoyen

Current Job: PhD student at LIP6, part of Université

Pierre et Marie Curie

Website: http://gabe.squirrelsoup.net/

Worked on Gasser: an raspberry pi powered device

that could measure the air quality mobile. http://

wiki.labocitoyen.fr/index.php?n=Hardware.Gasser

Has experience with: Alphasense B4 serie sensors

Explained me: The sensors are from alphasense and

provide two voltages, in the range of 220-400mV

iirc. You need to be able to get a resolution of about

4-5mV to be able to get concentration resolutions in

the 10ppb range, which is the minimum necessary

to be able to do anything 'useful'.

Name: Jan Theunis

Function: Project Manager

Company: Environmental Risk and Health

Worked on: The Aeroflex: a bike for mobile air qual-

ity measurements

Explained me: Sensor technologies are still in de-

velopment, don’t expect too much of it. If you want

to sense gas like NO2 you need to measure nano-

voltages which is extremely hard to do. These sen-

sors are sensitive for temperature, humidity and

most of the time also for other gasses. If you want

to measure really precise you will need to pay a lot.

The cheap versions are all different and need to be

calibrated individually.

Name: Hester Volten

Company: RIVM - National Institute of Public Health

and the Environment,

Department: Environment and Safety Division, Cen-

tre for Environmental Monitoring

Currently working on: ISPEX initiative, a method to

measure the fine dust with a special device on the

Iphone.

Explained me: how air is measured in the Nether-

lands, and what the future of RIVM needs to be.

More and more they have to compete with people

who measure themselves, which is of course a good

thing but their measured values are not always cor-

rect. Before something is brought to the public via

RIVM it is first checked several times. Their sen-

sors are in the highest precision and controlled and

monitored in Bilthoven. For a future initiative like I

have a cooperation is needed to check the validity

of the measurements, and to combine and analyze

all the data.

40

Name: Jean-Paul close

Company: AiREAS, STIR academy

Working on: Sensor network of 35 sensor units in

Eindhoven, to get a higher resolution map of the

fine dust in Eindhoven.

Explained me: In Eindhoven you can achieve every-

thing if you know the right people. He is working

together with ECN, Philips, Gemeente Eindhoven,

Philips, NXP, ISPEX etc. He know most of the big

guys around and he addresses them on their re-

sponsibility. With his vision on sustainocracy he

wants to create a better and healthier tomorrow. He

was and is an inspiration for me who lets me think

about the things I am doing and can do in the future.

Name: Annemarije Andriga

Company: PHD Researcher Philips

Worked on: new way of measuring nitrogen diox-

ides

Explained me: that even though she had success

with her sensor Philips did not want to spend more

money on it because it only worked with NO2, and

NOX. Her sensor could possibly change the way

how we measure the air, because she used a semi-

conductor instead of an optical, or heating mech-

anism. This means that the sensor can be really

small, possibly even in your mobile phone. But this

was in lab conditions where humidity, temperature,

and airflow was controlled. Future development is

still needed make this kind of sensors possible.

41

Sensor Technology

Data analysesApp development

Branding and integration

Connecting ActorsDevelop interactions

Integration sensor

Sending andstoring data

Sensor Technology

Integrate in their existingtests

CONCLUSIE EXPERT MEETINGS

For the perfect sensor there is still a long road to go but in the region Eindhoven there is

a lot possible. For example NXP is currently testing with 150 taxies which send all their

data from the board computers towards a data center where it is analyzed. In this way

they can give feedback on driving behavior, monitor accidents and much more. Censor

technology from AiREAS and ECN could be combined with the NXP taxies to create the

first tests. RIVM should analyze the data and check the validity of it.

42

FINAL RESULT / FUTURE

Even though most people will not

see mobile air measurement as

a necessity or something where

they want to spend extra money

on most people find clean air im-

portant. When the information be-

comes more local and personal

it will have more value. The first

people who want to have such

a device in their car would prob-

ably people who are already in

this branch or would have person-

al interest in air quality, because

they live near a highway or have a

health condition that needs extra

attention. If it is worked out prop-

erly the image from the app and

the car should be green and posi-

tive and something you want to

have because you can feel good

about your contribution.

Development Sensor

HumidityMeasure: NOx NO2 O3 PM2,5

Mass productionDeployment carManufacturerData analysis

Test with multiple carsCompare with existing dataDevelopment applicationPromotion

43

CONCLUSION & RECOMMENDATIONS

There have been already many projects where people have shown

that mobile measurement is something that makes sense to do.

The sensor technology to measure mobile is not yet far enough

developed to be good enough. Sensors now are inaccurate and

too expensive for the commercial market for the average. The

government could start to equip buses and taxies with measuring

equipment to provide citizens, to create a better picture of the air

quality. This data should be brought as transparent and open as

possible. Data should be visualized in such a way that it makes

sense for everybody. Only than we can expect an average citizen

to understand what the air quality means for their lives.

In the sensor technology especially the placement, and control-

ling the conditions of the sensor will something that needs to be

developed and tested. Once the data has proven to be valuable

the applications around it should be build.

44

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Walsh, B. (2012, December 20). Unbreathable: Air Pollu-

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killer/

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human-healthy-the-case-of-the-city-of-trabzon

48

APENDIX AINTRODUCTION:

I am doing my research about outdoor air quality. In this

session I would like to explore with you your past expe-

riences in this topic, and together with you explore the

possibilities for a concept. There are no good or bad

answers, I just would like to know your thoughts about

this subject to give me new ideas.

SENSITIZATION:

Past experiences: fictional story: introduce context: non

directive questions: provoke relevant past experiences:

in the current context of use

My first question is:

Have you thought about the air quality the past 6

months?

• What did you experience?

• After the experience did you continue thinking

about this?

Do you recognize this situation?

What did you think about in this situation?

What other moments did you think about the air?

What is your opinion on how the news about air quality

is brought?

Can you explain the situation where the air was not that

good: home, holiday, traveling ( situations: concrete ex-

amples: what were they doing, time etc) how they real-

ize it was not that good, what they did, if they cared or

not etc. )

Feedback: Prepare small stories: about home, travel,

work. Scenario: he read in the news…, is wondering

about how it is in his neighborhood. Bring up different

situation.

A lot of pictures of situations: to let them ring a bell.

ELABORATION:

Envision future: fictional story: introducing the concept:

ask what they like and don’t like

What if you would be this person? What would you do?

Sketch the situation

Think out loud

Advice: John got a present: explain the device: what it

does etc. ( what does he measure, how does it look like,

what does it communicate? ) (Relate to the things they

said in the previous face.

What if you could see the amount of air pollution wher-

ever you are? How would this look like in your imagina-

tion?

Same situation: afterwards go into depth in different

situations?

Would this device give you something extra in these

situations?

If you have this device? How would this device be use-

ful for you?

What kind of data would you like to see?

What value would you give to this data?

Are there more people you know who would find this

data interesting?

What would you like to see? And how and where would

you like to see this data?

Are there specific places that come into your mind

where you would like to know the air quality?

When would you use such a system?

For who do you think this data would be important?

49

1

8

8

5

2

0 1 2 3 4 5 6 7 8 9

+ - 3 K M

+ - 5 K M

+ - 1 0 K M

+ - 1 5 K M

+ - 5 0 K M

I TRAVEL ON AVERAGE ........ PER DAY

18

14

5

0 5 10 15 20

G I V E A N O T I F I C A T I O N W H E R E C L E A N S P O T S A R E

A V O I D P O L L U T E D C I T I E S I F I T I S N O T T O O F A R O U T O F T H E

D I R E C T I O N

O T H E R W I S E

WITH THE PLANNING OF A LONG TRIP BY CAR, I WOULD LIKE MY NAVIGATION

TO

15

2

13

5

18

5

5

0 2 4 6 8 10 12 14 16 18 20

I N O T I C E T H A T T H E A I R I S B A D

W H E N I A R R I V E I N A N A R E A W H E R E T H E A I R I S C L E A N E R T H A N W H E R E I C A M E F R O M , ( M O U N T A I N A I R , S E A A I R , E T C )

W H E N M Y E Y E S T E A R

W H E N I T A K E P A R T I N T R A F F I C B Y B I K E

W H E N I A M I N A T R A F F I C J A M B Y C A R

W H E N I S M E L L S O M T H I N G

I D O N ' T N O T I C E T H I S

I NOTICE THAT THE AIR IS BAD

APENDIX B

18

14

5

0 5 10 15 20

G I V E A N O T I F I C A T I O N W H E R E C L E A N S P O T S A R E

A V O I D P O L L U T E D C I T I E S I F I T I S N O T T O O F A R O U T O F T H E

D I R E C T I O N

O T H E R W I S E

WITH THE PLANNING OF A LONG TRIP BY CAR, I WOULD LIKE MY NAVIGATION

TO

0

0

4

14

10

0 2 4 6 8 10 12 14 16

N O T S O I M P O R T A N T

V E R Y I M P O R T A N T

HOW IMPORTANT IS CLEAN AIR FOR YOU?

27

1

0 5 10 15 20 25 30

Y E S

N O

WOULD YOU LIKE TO SEE HOW THE AIR QUALITY WAS IN THE PAST?

12

1

10

4

1

0 2 4 6 8 10 12 14

Y E S

N O

M A Y B E

N O T S O I M P O R T A N T

O T H E R W I S E

WOULD YOU LIKE TO SEE LIVE DATA FROM OTHER PEOPLE?

2

3

1

12

10

0 2 4 6 8 10 12 14

D I S A G R E E

I A G R E E C O M P L E T L Y

I PREFER TO SEE A MORE ABSTRACT VISUALIZATION OF AIR QUALITY DATA

IN FIRST INSTANCE BEFORE I SEE MORE DETAILED INFORMATION

22

6

0 5 10 15 20 25

Y E S

N O

WOULD YOU LIKE TO KNOW THE HEALTH RISKS OF ANY SCALE WITH

RESPECT TO AIR QUALITY

50

18

14

5

0 5 10 15 20

G I V E A N O T I F I C A T I O N W H E R E C L E A N S P O T S A R E

A V O I D P O L L U T E D C I T I E S I F I T I S N O T T O O F A R O U T O F T H E

D I R E C T I O N

O T H E R W I S E

WITH THE PLANNING OF A LONG TRIP BY CAR, I WOULD LIKE MY NAVIGATION

TO

25

2

1

0 5 10 15 20 25 30

Y E S

N O

O T H E R W I S E

I WOULD LIKE TO SEE WHAT THE CONNECTION IS BETWEEN THE

WEATHER AND AIR QUALITY

2

1

4

5

1

5

9

0 1 2 3 4 5 6 7 8 9 10

1 M O N T H

3 Y E A R S

5 Y E A R S

2 0 Y E A R S

4 0 Y E A R S

5 0 Y E A R S

A S F A R B A C K A S P O S S I B L E

UNTIL HOW FAR BACK WOULD YOU LIKE TO BE ABLE TO SEE?

2

16

13

5

17

13

0 2 4 6 8 10 12 14 16 18

O T H E R W I S E

S H O U L D G I V E M E A W A R N I N G W H E N T H E V A L U E C O M E A B O V E A C E R T A I N T H R E S H O L D T H A T I H A V E S E T M Y S E L F .

S H O U L D A U T O M A T I C A L L Y C L O S E T H E W I N D O W S A N D A I R I N T A K E

S H O U L D S H O W T O O T H E R P E O P L E H O W G O O D / B A D T H E A I R I S O N T H E O U T S I D E O F T H E C A R

S H O U L D H E L P M E T O D R I V E C L E A N E R W H E N T H E A I R B A D

S H O U L D H E L P M E T O A V O I D D I R T Y P L A C E S

WHEN THERE WOULD BE A SENSOR FOR MEASURING THE AIR QUALITY IN MY CAR, THIS SENSOR MODULE

18

7

0

3

0 2 4 6 8 10 12 14 16 18 20

Y E S T H I S D A T A S H O U L D O P E N A N D A V A I L A B L E T O E V E R Y O N E

Y E S T H I S D A T A S H O U L D B E O P E N , I W O U L D L I K E T O B E A B L E T O S H A R E

T H I S E X P L I C I T L Y T O O T H E R S

N O , T H I S I S M Y D A T A N O T F O R O T H E R S .

O T H E R W I S E

WOULD YOU LIKE TO SHARE THE SELF MEASURED DATA TO OTHERS?

3

5

6

7

7

0 1 2 3 4 5 6 7 8

D I S A G R E E

A G R E E

I WOULD LIKE TO SEE THE DATA IN NUMBERS I MEADIATLY

22

4

2

0 5 10 15 20 25

Y E S

N O

O T H E R W I S E

WOULD YOU WANT TO BE ABLE TO SET AN ALERT AS THE PREDICTED AIR

QUALITY FOR THE NEXT DAY IS VERY BAD?

21

5

2

0 5 10 15 20 25

Y E S

N O

O T H E R W I S E

I WOULD LIKE THAT THE APPLICATION SHOWS WHAT THINGS I CAN DO TO

CONTRIBUTE TO CLEANER AIR

51

1

4

6

12

4

0 2 4 6 8 10 12 14

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE: INFORMATION HEALTH RISKS

0

1

9

15

2

0 2 4 6 8 10 12 14 16

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE: CONNECTION WEATHER AND AIR QUALITY

0

0

6

10

11

0 2 4 6 8 10 12

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE:NOTIFICATION BY BAD AIR QUAKITY

1

3

7

9

7

0 1 2 3 4 5 6 7 8 9 10

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE: TIPS TO CONTRIBUTE TO A CLEANER AIR

52

0

5

2

11

9

0 2 4 6 8 10 12

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE: ABSTRACT REPRESENTATATION OF DATA

0

6

6

12

3

0 2 4 6 8 10 12 14

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE: OPTION TO SHARE THE DATA

2

4

10

7

2

0 2 4 6 8 10 12

N O T I M P O R T A N T

N O T S O I M P O R T A N T

N E U T R A L

I M P O R T A N T

V E R Y I M P O R T A N T

IMPORTANCE: BEING ABLE TO FOLLOW DATA FROM SOMEONE ELSE

53