Classification of Air Quality Inside Car Cabin using Sensor System
Andrzej Szczurek and Monika Maciejewska
Faculty of Environmental Engineering, Wroclaw University of Technology,
Wyb. Wyspiańskiego 27, 50-370 Wroclaw, Poland
Keywords: Indoor Air Quality, Gas Sensor, Classification.
Abstract: Daily practice, but also research, show that poor indoor air quality (IAQ) is a serious problem in many
vehicles. In this work we present an approach to the evaluation of air quality in car cabin. It consists in IAQ
classification. We focussed on defining classes in a way which may be useful for improving air quality
during a trip. In order to assure the provision of objective information, IAQ classes are specified with
reference to measurable parameters of indoor air. The parameters: temperature, relative humidity, CO
2
concentration and VOC content indicator are considered jointly. Class assignment is realized on a software
level, based on the measurement data provided by the sensor module located inside car cabin. The final
announcement received by the driver refers to the class of indoor air. It informs about: thermal conditions,
air humidity and air freshness. These components correspond to the capabilities of air handling system in
the car and they were included in the message to provide hints for improving air quality. The information is
delivered in real time. We believe, the implementation of the presented approach will contribute to the
improvement of car microenvironment upon driving.
1 INTRODUCTION
It is estimated that over 1 billion passenger cars
travel the streets and roads of the world today. In
modern countries, people spend approximately 90
minutes in confined spaces of their cars, each day.
During this time, many factors affect comfort, safety
and health of drivers and passengers. Research has
shown that particulate matter and harmful
substances can be up to six times more concentrated
inside a vehicle than outside.
Human experiences car microenvironment
mainly via air quality, thermal conditions, noise
level and vibration. Air quality is a term which
describes the physical, chemical and biological state
of indoor air at some place and time. Usually it is
characterized by physical and chemical parameters
such as temperature (T), relative humidity (RH),
airflows and concentration of characteristic
pollutants. Research and practice show that poor
indoor air quality is a serious problem in many
vehicles (Müller et al., 2011). For example, inside
vehicle cabins concentrations of air pollutants such
as: carbon monoxide (CO), hydrocarbons (HC),
volatile organic compounds (VOC), and oxides of
nitrogen (NOx) are very often higher than safety
limits set by Occupational Safety and Health
Administration (OSHA) and World Health
Organization (WHO). Especially in new car’s
interiors the levels of airborne chemicals are
significantly higher than recommended for indoor
environments today (Fedoruk&Kerger, 2003).
Another problem is a discomfort experienced due to
offensive smells and inadequate temperature or
humidity.
Currently, conditions inside car cabins may be
improved by windows opening or the correct use of
heat, ventilation and air conditioning (HVAC)
system (manual or automated). There are also
available portable air purifiers. The effectiveness of
these methods is strongly dependent on the
evaluation of indoor air quality by the drivers or
passengers (Blashke et al., 2006). Traditionally it is
based on stimuli which come from the environment
and are perceived by human senses. This method is
simple and cheap. Unfortunately, human sensation
poses a number of problems when used as a source
of information. Perception of physical and chemical
conditions alters over time and varies among people.
It is prone to bias, fatigue as well as the attention
drift. For this reason, the most reliable evaluation of
cabin microenvironment is based on measurements
211
Szczurek A. and Maciejewska M..
Classification of Air Quality Inside Car Cabin using Sensor System.
DOI: 10.5220/0005225802110219
In Proceedings of the 4th International Conference on Sensor Networks (SENSORNETS-2015), pages 211-219
ISBN: 978-989-758-086-4
Copyright
c
 2015 SCITEPRESS (Science and Technology Publications, Lda.)

of parameters describing indoor air quality. It should
be noted that the concern for the vehicles interior air
quality is focused on (Galatsi&Wlodarski, 2006):
 indoor temperature and relative humidity;
 air pollutants entering the vehicle via the
ventilation system;
 lack of fresh airflow resulting in low O
2
and high
CO
2
concentrations due to occupants breathing
process;
 pollutant gases entering from the external
environment via window openings, imperfect
seals and other holes;
 toxic gases entering the vehicle cabin due to
redirected exhaust fumes.
Nowadays, there is no system or aftermarket product
designed to control thermal and chemical conditions
in vehicles in a comprehensive manner. There are
available sensors to measure temperature and
relative humidity. Regarding more advanced
proposals, currently there exist only two commercial
air quality monitoring (AQM) solutions for cars. The
most common are AQM systems controlling HVAC
ventilation flaps. The air quality sensors are
typically, located near the fresh air inlet, and not
inside car cabin. Their function is limited to
reducing the amount of pollution entering the
vehicle cabin through the HVAC system when the
vehicle enters a highly polluted area. Less common
are aftermarket toxic gas alarms for vehicle cabin
applications. Cars evolution as well as research and
development dedicated to comfort improvement are
responsible for the fact that around 10 % of the
produced cars are currently equipped with Air
Quality Sensors (AQS). Road test done by car
manufacturers, involving in/out car cabin analysers,
revealed more than 80 % reduction of pollution
peaks caused by the air entering the cabin (http,
2013).
The interior of a vehicle may be regarded as a
specific microenvironment. Many different factors,
either individually or in combination, influence car
interior. Hence, the quality of this gas should be
characterized by several parameters. Currently, it is
not a problem to measure/monitor physical and
chemical properties of air inside the vehicle cabin, in
real time. The problem is the simultaneous and quick
analysis of multivariate measurement data which
would extract a comprehensive information about
indoor air quality. This operation may be
complicated. It requires some knowledge and cannot
be performed by the drivers during a trip. Their
involvement might elevate the likelihood of collision
or other road fatalities. For that reason, we propose
an approach which is based on the idea of a
collective classification of air quality using a sensor
measurement system.
Generally speaking, classification is a systematic
arrangement in categories (classes) according to the
established criteria. In our work, we propose the
collective categorization of air quality inside car
cabin. In other words the properties of this gas are
recognized i.e. assigned to a class, which is
characterized descriptively. In this way, there is
provided a concise information and the driver can
make decisions how to improve air quality very
quickly and safely.
The aim of this work is to propose a method of
air quality classification. On this basis, we want to
show that classification of indoor air may be used to
improve car microenvironment. We assume that the
classification procedure should be an element of a
sensor measurement system. Due to fact that these
devices are relatively cheap the proposed method
may be widely applied.
2 ASSUMPTIONS
In this work we made several assumptions
concerning:
 target user of the sensor system for indoor air
quality classification ;
 subject of the evaluation;
 basis for IAQ classification;
 principle of IAQ classification;
 form of the final result.
The sensor system for air quality classification
inside car cabin is addressed to drivers as well as
passengers. Currently, they are most obvious target
users of this type of measurement equipment.
However, we assume that the idea of air quality
classification may be utilized in automatic systems
for heating, ventilation and air conditioning as well.
The subject of evaluation is the quality of air in a
selected location inside the cabin of a vehicle. More
specifically, it may be the surrounding of the driver
or the passenger. We chose the perspective of local
IAQ classification in order to be able to account for
the comfort of the driver and passengers
individually. People differently influence the quality
of air around them. It is due to: various level of
personal hygiene, health condition, metabolism rate,
sweating intensity, etc. On the other hand, the
sensitivity of various people to changes in air quality
is also different. It may depend on age and sex, but
not exclusively. As a consequence, satisfaction of
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Table 1: Ranges of measured parameters utilized for determining IAQ class in car interior.
Indoor air parameter Range 1 Range 2 Range 3
Temperature [C] t  24 24 < t  27 t > 27
Relative humidity [%] t  30 30 < RH  50 RH > 50
CO
2
concentration [ppm] [CO
2
]  600 600 < [CO
2
]  1000 [CO
2
] > 1000
IAQ sensor response
R
VOC
=(R-R
0
)/R
0
[-]
R
VOC
 0.33 0.33 < R
VOC
 1.22 R
VOC
> 1.22
Table 2: Terms used for describing three major aspects of IAQ in car interior.
IAQ coordinates Term 1 Term 2 Term 3
Thermal comfort too cold appropriate too warm
Air humidity dry appropriate too humid
Air freshness fresh air bad air very bad air
everybody in the car may be difficult to achieve.
Therefore in our concept, indoor air quality is
evaluated locally. But, one may choose various
locations to focus on them.
The classification of IAQ is based on
measurements of selected indoor air parameters. We
propose to monitor: temperature, relative humidity,
CO
2
concentration and an indicator of VOCs content
in air. These quantities contain complementary
information, which may be combined, leading to a
concise classification of indoor air quality. The first
two parameters allow to determine thermal comfort
in a given place inside car. Their usefulness is
undisputable. Additionally, we propose to take into
account the chemical aspect of air quality. For this
purpose there are considered CO
2
concentration and
the indication of VOCs content in air. In principle,
the first quantity is associated with human (also
animal) metabolism. Upon human presence, CO
2
is
always emitted to car cabin air. Although it is known
that carbon dioxide at high concentrations impairs
human performance, our bodies do not have an
efficient detection mechanism. Regarding VOCs,
their main sources inside car are: cabin materials
(ISO 12219-2, ISO 12219-3, ISO 12219-4), humans
(also animals and luggage) and the ambient air. It is
known that materials used in cars change their
characteristics when they are exposed to UV light
from the sun or due to high temperature. For this
reason, the concentration of potentially toxic
chemicals in car interior depends on its temperature
and the duration of exposure to sunlight. However,
based on our experiments, when the car is driven,
the dominant contribution of VOCs inside
automobile cabin comes from the road traffic
emission. Interestingly, the gradual elevation of
VOCs inside car usually remains unnoticed by
passengers. This may result from the olfactory
adaptation. On the other hand, a limited number of
VOCs delivered to car cabin are able to induce the
olfactory sensation.
The proposed principle of IAQ classification was
meant to assure the transformation of multivariate
measurement data into a comprehensive
information. The basis for establishing IAQ classes
in car are the predefined ranges of values of
individual indoor air parameters. They are shown in
Table 1. When choosing the limit values for
temperature and humidity we were guided by
thermal comfort requirements for space category A
(ASHRAE Standard 55-2013). In this case the
operative dry-bulb temperature is 25.5 C. The  1.5
C interval around this value is widely considered as
the summertime temperature comfort range. The
min-max humidity range for space category A was
defined as 30 % to 50 % (ASHRAE Standard 55-
2013). Based on (ACGIH. 1998; Bright et al., 1992)
we accepted that in case of CO
2
, comfort conditions
are maintained when its concentration is smaller
than 600 ppm. In general, higher concentrations are
unwelcomed and the exceedance of 1000 ppm is
disadvantageous. Respectively, we assumed that
IAQ sensor response smaller than 0.33 indicates
comfort conditions regarding VOCs content in air.
Higher values of the response, in particular those
exceeding 1.22, point at the increasingly
unfavourable surrounding. The quoted limit values
are associated with a particular sensor type and they
are based on our measurement experience.
In our approach, IAQ class is defined by
describing three aspects: thermal conditions, air
humidity and air freshness inside car cabin. The
terms used for characterization are given in Table 2.
An individual IAQ class is identified by the set
of three terms. The first accounts for the thermal
conditions – the evaluation is based on temperature,
the second term addresses air humidity – the
assignment is based on relative humidity and the
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third one characterizes air freshness – the rating is
based on CO
2
concentration and VOCs content in
car interior.
The choice of the particular set of terms to
determine air quality class is dependent on values of
air parameters measured inside the cabin of the
automobile (Table 2). Considering thermal
conditions, term 1 is used if air temperature belongs
to range 1, term 2 is applied when air temperature
belongs to range 2, and similar with term 3. The
same rule is applied to determine air humidity
component of IAQ class, based on the measurement
of relative humidity in car cabin. Regarding air
freshness, term 1 is used when both CO
2
concentration and IAQ sensor response belong to
range 1. Term 2 is applied when any of these
parameters is in range 2. Term 3 is employed if
either CO
2
concentration or IAQ sensor response
belongs to range 3. Altogether, in our approach there
were distinguished 27 air quality classes. They are
presented in detail in Table 3. Additionally, their
arrangement in the space of IAQ coordinates is
displayed in Fig. 1.
Figure 1: Arrangement of IAQ classes in the space of three
coordinates: thermal comfort, air humidity and air
freshness. Colours correspond to three levels of thermal
comfort: cold, appropriate, too warm. Abbreviations: AF –
air freshness, AH – air humidity, TC – thermal conditions.
IAQ class recognition is performed automatically
by the dedicated software, based on the
measurement data transmitted from the sensor
module. Neither driver nor passengers are involved
in the entire process. The user just receives the final
result.
We proposed to announce IAQ class using the
descriptive form. An example of information
delivered to the user of the sensor system equipped
with IAQ classification module is given in Fig. 2.
The form of descriptive communication of IAQ
classes was chosen on purpose. It serves to provide
the comprehensive information which is useful for
maintaining proper air quality while driving.
Table 3: Description used to announce the air quality
classes in car interior.
IAQ
class
Thermal
conditions
Air humidity Air freshness
1 Cold dry fresh air
2 cold dry bad air
3 cold dry very bad air
4 cold appropriate fresh air
5 cold appropriate bad air
6 cold appropriate very bad air
7 cold too humid fresh air
8 cold too humid bad air
9 cold too humid very bad air
10 appropriate dry fresh air
11 appropriate dry bad air
12 appropriate dry very bad air
13 appropriate appropriate fresh air
14 appropriate appropriate bad air
15 appropriate appropriate very bad air
16 appropriate too humid fresh air
17 appropriate too humid bad air
18 appropriate too humid very bad air
19 too warm dry fresh air
20 too warm dry bad air
21 too warm dry very bad air
22 too warm appropriate fresh air
23 too warm appropriate bad air
24 too warm appropriate very bad air
25 too warm too humid fresh air
26 too warm too humid bad air
27 too warm too humid very bad air
Class of air quality
Thermal conditions: too warm
Air humidity: appropriate
Air freshness: bad air
Figure 2: Example of IAQ class. The descriptive form
used to announce the final result of classification.
Thermal conditions of car interior may be
adjusted. The use of windows and the dedicated air
handling system allows for heating and cooling. Air
freshness is also under control. The regulation of
intensity of ambient air delivery to car cabin has
major contribution to this property of car interior.
Although HVAC systems modify humidity, in cars
they typically do not allow for its control.
Nevertheless, we incorporated the information about
humidity into IAQ class description. It may be very
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useful. For example, based on long-term
observations that the air inside the car cabin tends to
be permanently dry, one may decide to use a
humidifier.
The information on IAQ class is provided in real
time. The rate of update is limited exclusively by the
time resolution of sensor measurements.
3 EXPERIMENTAL
The objective of the experiment was to record air
parameters inside the cabin of a passenger car,
during a trip.
Table 4: Measuring characteristics of devices based on
various sensors, applied in measurements of air parameters
inside car cabin.
Measured
parameter
Measuring
range
Accuracy Resolution
Temperature -20  60 °C
±0.2 °C ± 0.15
%MV
0.1 °C
Relative
humidity
5  100
%RH
±2 % (10  90
%RH); ±2.5 %
outside
0.1 %
CO
2
concentration
0  5000
ppm
±50 ppm + 3
%MV
1 ppm
IAQ sensor
response
450  2000
ppm CO
2
equivalents
 
The following parameters were measured:
temperature, relative humidity, carbon dioxide
concentration and the indicator of total volatile
organic compounds content in the air.
There were applied instruments based on various
sensors: thermistor NTC 10 for temperature,
capacitive sensor for relative humidity, non-
dispersive infrared sensor for CO
2
and
semiconductor gas sensor as IAQ sensor. The
characteristics of these devices are presented in
Table 4.
Because of the fact that indoor air parameters
exhibit spatial dependence sensor devices were
located in different places inside car cabin. There
were examined spaces: in front of the driver’s seat,
ahead of the front seat passenger and ahead of the
back seat passengers. During a trip measurements
were carried out simultaneously in two selected
locations.
The tests were performed in the summer. The car
was driven in real traffic on the way from town A to
B and back. One way single trip lasted for about 1h
20 min. The car was occupied by the driver and
three passengers. They were asked to adjust air
quality in car cabin according to their needs.
4 MEASUREMENT RESULTS
In Fig. 3 and Fig. 4 we show the data collected
during air monitoring inside a traveling car. There
are displayed time series of temperature, relative
humidity, CO
2
concentration and IAQ sensor
response recorded in different locations inside car
cabin. In Fig. 3 we compare conditions in the
immediate vicinity of driver’s head and the back seat
passenger’s head. The surrounding of the front seat
passenger and back seat passenger are characterized
in Fig. 4. Data displayed in Fig. 3 and Fig. 4 were
collected during different trips, but on the same rout.
Based on Fig. 3 and Fig. 4 indoor air parameters
monitored in car cabin exhibited: temporal variation,
spatial variation and parameter-specific behaviour.
As shown in Fig. 3 and Fig. 4, all quantities
exhibited considerable changes in time. Their values
varied in a wide range, including extreme ones. The
changes in time domain could be described as rapid.
Spatial dependence of indoor air parameters in car
cabin was also well pronounced. Usually, the values
recorded in different locations were just shifted with
respect to each other (Fig. 3d, Fig. 4d), but in some
cases, distinct tendencies were observed. In
particular, we noted that thermal conditions close to
the driver’s seat were very different compared with
passenger’s seat, see Fig. 3a,b. The comparison of
simultaneously recorded distinct parameters of
indoor air revealed that they behaved differently.
There could be noticed some degree of correlation
between temperature and humidity as well as
between CO
2
concentration and VOC content
indicator. Nevertheless, each of these quantities
provided a great amount of distinct information on
the conditions in car cabin.
Upon driving the air quality in car interior is
under joint influence of many factors. The main ones
are: car itself (interior materials, HVAC operation),
human passengers, road traffic, passed land (its
character) and meteorological conditions. The
influence of individual factors is reflected in
particular parameters of indoor air. Hence, the
behaviour of individual parameters is distinct. The
individual factors themselves exhibit temporal and
spatial variations. Due to this property, they cause
temporal changes of indoor air parameters as well as
induce differences between distinct locations inside
the vehicle cabin.
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Figure 3: Results of indoor air parameters monitoring inside car cabin during a trip: a) temperature, b) relative humidity, c)
CO
2
concentration, d) IAQ sensor response. Comparison between conditions in the immediate vicinity of driver’s head and
back seat passenger’s head.
Figure 4: Results of indoor air parameters monitoring inside car cabin during a trip: a) temperature, b) relative humidity, c)
CO
2
concentration, d) IAQ sensor response. Comparison between conditions in the immediate vicinity of front and back
seat passengers’ heads.
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5 IAQ CLASSIFICATION
In our concept, sensor measurements of indoor air
parameters are the basis for determination of IAQ
classes. It is assumed that class assignment is
performed in distinct time steps of the monitoring
period. In Fig. 5 and Fig. 6 we present the results of
IAQ classification, which was based on the data
from monitoring car cabin air parameters displayed
in Fig. 3 and Fig. 4, respectively.
The classification allows for a synthesis of data
on various parameters of indoor air in order to
provide a comprehensive announcement on its
quality. At the same time there is preserved spatial
and temporal resolution of information about IAQ
corresponding to the instrumental monitoring
frequency. These features of class approach become
revealed when comparing indoor air monitoring data
(Fig. 3 and Fig. 4) with the respective IAQ class
recognition results (Fig. 5 and Fig. 6). As shown, the
multivariate measurement data was transformed into
a compact, univariate information, which has the
same temporal and spatial resolution as the data
itself.
Figure 5: IAQ classes determined using data from
monitoring car cabin air parameters in the space of a
driver and back seat passenger (compare with Fig. 3).
Obviously, the characterization of IAQ in terms
of classes is more coarse compared with using raw
multivariate measurement data. But, due to this
property class approach better serves the
generalization. For example, using classes it is easier
to group different locations inside car regarding IAQ
similarity. Our results clearly demonstrate that
conditions near the driver’s seat were typically
completely different than ahead of the back seat (see
Fig. 5). On the other hand, the IAQ near the front
seat and back seat belonged mostly to the same
category. The generalization effect is also visible in
time domain. As shown in Fig. 5 and Fig. 6, IAQ
classes did not change as fast as the values of
monitored indoor air parameters. Typically, in the
periods of several minutes, conditions in a particular
location inside car cabin were assigned to the same
IAQ class (see Fig. 5 and Fig. 6), whereas indoor air
parameters readily varied (see Fig. 3 and Fig. 4).
Figure 6: IAQ classes determined using data from car
cabin air parameters monitoring in the space of front and
back seat passenger (compare with Fig. 4).
The proposed classification approach gives rise
to easy examination of how frequently particular
IAQ conditions occur in various locations inside car
cabin. The corresponding summaries of IAQ classes
recognized during experiments considered in this
work are shown in Fig. 7 and in Fig. 8. The class
occurrence in the space of the driver and back seat
passenger are shown in Fig. 7. The corresponding
results for the spaces near the front and back seat
passengers are displayed in Fig. 8.
6 CONCLUSIONS
Comfort, safety and health of drivers as well as
passengers strongly depend on the quality of air
inside vehicle cabins. Common experience shows
that maintaining it at a high level may be a serious
problem. In this work we proposed an approach to
the evaluation of IAQ in car cabins. It consists in
classification of air quality using a sensor system.
In order to be objective, IAQ classification is
based on measurements of selected indoor air
parameters, in a chosen location inside car cabin.
The following parameters are considered:
temperature, relative humidity, CO
2
concentration
and VOCs content indicator. Together they form a
multivariate representation of the physical and
chemical conditions in a tested place of car interior.
Classification is meant to transform the
measurement data into a comprehensive information
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Figure 7: Comparison of the occurrence of distinct IAQ classes in two locations inside car cabin: (a) in the vicinity of
driver’s head, (b) in the vicinity of back seat passenger’s head. Abbreviations: AF – air freshness, AH – air humidity, TC –
thermal conditions.
Figure 8: Comparison of the occurrence of distinct IAQ classes in two locations inside car cabin: (a) in the vicinity of front
seat passenger’s head, (b) in the vicinity of back seat passenger’s head. Abbreviations: AF – air freshness, AH – air
humidity, TC – thermal conditions.
about IAQ. It basically consist in assigning
measured values to the predefined ranges and
combining the obtained results. This process is
performed by a software without human
contribution. The sensor system user is provided
with a final result in real-time.
The final announcement of IAQ class refers to:
thermal conditions, air humidity and air freshness.
This descriptive information provides hints for
improving air quality, because its components
correspond to the capabilities of air handling system
in the car.
ACKNOWLEDGEMENTS
This contribution was supported by the project: "The
variability of physical and chemical parameters in
time as the source of comprehensive information
about indoor air quality". The project is financially
supported by the National Science Center, Poland,
under the contract No. UMO-2012/07/B/ST8/03031.
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