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Differences in cyclists and car drivers exposure to air pollution from traffic in the city of Copenhagen


Abstract and Figures

It has frequently been claimed that cycling in heavy traffic is unhealthy, more so than driving a car. To test this hypothesis, teams of two cyclists and two car drivers in two cars were equipped with personal air samplers while driving for 4 h on 2 different days in the morning traffic of Copenhagen. The air sample charcoal tubes were analysed for their benzene, toluene, ethylbenzene and xylene (BTEX) content and the air filters for particles (total dust). The concentrations of particles and BTEX in the cabin of the cars were 2-4 times greater than in the cyclists' breathing zone, the greatest difference being for BTEX. Therefore, even after taking the increased respiration rate of cyclists into consideration, car drivers seem to be more exposed to airborne pollution than cyclists.
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Differences in Cyclists and Car Drivers Exposure to Air Pollution
from Traffic in the City of Copenhagen
Jette Rank (1), Jens Folke (2) and Per Homann Jespersen (1)
(1) University of Roskilde, Department of Environment, Technology and Social
Studies, P.O Box 260, DK-4000 Roskilde, Denmark.
(2) MFG-Environmental Research Group, Østergade 30, DK-3250 Gilleleje,
Corresponding author to whom the proofs should be sent:
Jette Rank, Department of Environment, Technology and Social Studies, 11.2,
Roskilde University, P.O Box 260, DK-4000 Roskilde, Denmark.
E-mail, Phone +45 4674 2071, Fax +45 4674 3041
It has frequently been claimed that cycling in heavy traffic was unhealthy, more so
than car driving. To test this hypothesis teams of two cyclists and two car drivers in
two cars were equipped with personal air samplers while driving for four hours on
two different days in the morning traffic of Copenhagen. The air sample charcoal
tubes were analysed for content of benzene, toluene, ethylbenzene and xylenes
(BTEX) and the air filters for particles (total dust). The concentrations of particles and
BTEX in the cabin of the cars were 2-4 times greater than in the breathing zone of
cyclists, the greatest difference being for BTEX. So, even taking an increased
respiration rate of cyclists into consideration, car drivers seem to be more exposed to
airborne pollution than cyclists.
Key words: traffic, air pollution, benzene exposure, car driver, cyclist.
In Denmark, as in most other countries, the number of cars is increasing and so is the
concern about the impact on human health caused by traffic related emissions.
Obviously, it is important to obtain knowledge of the amount of the most dangerous
air pollutants from the car exhaust, and already a lot of effort has gone into
monitoring the concentrations of these chemicals in urban air (Raaschou-Nielsen et
al., 1996; Jo & Choi 1996; Duffy & Nelson 1997; Fromme et al., 1997).
Exposure to the pollutants affects different kinds of road users, and
among these car drivers are of special interest, because many people spend several
hours every day inside an automobile. Volatile organic compounds have been
measured in car cabins and it was found that the inside-car concentrations were much
higher than the outdoor concentrations (Weisel et al., 1992) and concentrations in
buses (Jo & Choi, 1996) and also higher than what was found in a subway train
(Fromme et al., 1997/98).
Personal air sampling has been used in a Dutch study, where CO, NO2, benzene,
toluene, xylenes and PAH were sampled on persons either driving a car or a bicycle
(Wijnen et al., 1995). The study took place in Amsterdam, where cyclists and car
drivers drove the same routes through the city. The measurements showed that the
exposure levels were greater for the car drivers than for the cyclists. Moreover, a
Danish study using personal air sampling of children’s exposure to volatile organic
compounds, showed a highly significant correlation between exposure to benzene and
time spent in a car (Raaschou-Nielsen et al., 1997).
The main purpose of the present study was to compare the exposure levels of
four aromatic hydrocarbons, benzene, toluene, ethylbenzene and xylenes (BTEX) and
particulate matter for car drivers and cyclists, respectively, while driving the same
route in the traffic of Copenhagen.
Field study
A field pilot study was conducted using cyclists and car drivers equipped with two air
sampling pumps: one with a charcoal test tube and one with an air filter. Two teams of
two cyclists and two car drivers drove a slow 7.6 km. route (< 30 km/h average speed)
through the inner Copenhagen for four hours in the morning hours: 7.40 - 9.40 and
10.00 - 12.00, at two dates in the summer 1998, 18 June and 3 August. Both cars used
were typical B-class vehicles from the 90ies (VW Vento and Fiat Brava). None of
them used the air vent recirculation option during the experiment.
Meteorological data
Meteorological data (Table 1) were obtained from the measuring station situated at
Kastrup Airport in Copenhagen.
Air sampling
All sampling equipment came from the Danish Technological Institute. The air
sampling pumps were adjusted to a flow of 1.9 litres per minute immediately before
the start of the experiment. The tubes and the filters were placed close to the breathing
zone of the car drivers and the cyclists. For the cyclists the position was on the chest
and in the cars they were positioned at the top of the back on the drivers seat.
Chemical analysis
Vapours of benzene, toluene, ethylbenzene and xylenes (BTEX) were collected on a
gas sampling charcoal tube at a flow of 1.9 litre per minute. The detection limit of the
method was 0.05 – 0.1 µg/compound. BTEX were analysed in a gas
chromatographic/mass spectrometric method, using selected ion monitoring. Total
particulate matter was analysed gravimetrically after sampling on a membrane filter at
a flow rate of 1.9 litre per minute. The filter used was Millipore Celluloseacetate, 37
mm in diameter and 0.8µm pore size. The detection limit for total dust was 10
Statistical method
Data were analysed in a three-way ANOVA design without interaction terms. The
dependent variables were as follows: concentrations of benzene, concentrations of
toluene, concentrations of ethylbenzene and xylenes, concentrations of total
hydrocarbon and concentrations of particles (total dust). The independent variables
were: date of sampling (two levels), mode of transport (two levels) and car mark (two
levels nested in mode of transport).
Table 1 shows the meteorological data for the two sampling days. The temperature
and the air pressure were very similar for the two days. The most significant
difference was seen for the wind velocity being highest at the sampling day in June.
The samplings were carried out both in the morning rush hour and late morning. Data,
describing the sampling conditions, are shown in Table 2. The average speed for the
cars was low during the morning rush hours (17.8±2.3 km/h) and very similar to the
speed for the bicycles (14.6±0.3 km/h). However, in the late morning the cars are
driving faster, and the difference in speed between the cars (24.1±2.3 km/h) and the
bicycles (15.4±0.3 km/h) was more significant.
The results of BTEX and particle measurements can be seen in Table 3. The benzene
concentrations were in the range 11.0-17.5 µg/m3 in the cabins and 4.5-5.6 µg/m3 in
the breathing zone of the cyclists, giving about three times higher exposure for the car
drivers than the cyclists. The air concentrations of toluene and ethylbenzene/xylenes
are about four times higher than the benzene concentrations, and the exposure of the
car drivers for these chemicals are also about three times higher than the exposure of
the cyclists. The same pattern can be seen for the particulate matter, although the
ratio between the exposure of drivers and cyclists is only about a factor of two. The
results from 18 June showed a significant difference in the concentrations of all
pollutants between the two cars. The VW had the vent in a higher position on this day,
which may explain the lower concentrations measured inside this car due to more
efficient ventilation.
Table 4 shows the results from the analysis of variance (ANOVA). In all of the tests,
the concentrations were significantly dependent of the mode of transport, whereas no
significant differences could be observed between the two car marks. Another
significant result was that the level of particulate matter was higher on the first
sampling day (P = 0.009), while none of the hydrocarbons showed dependency on the
sampling date. The explanation for this phenomenon could be that on this day in June,
where the wind velocity was 8.5 m/s, the dust in the streets could have been whirled
around more than on the day in August, where the velocity of the wind was only 1-3
m/s (Table 1).
Road users are exposed to many hazardous chemicals, which are representatives for
traffic related air pollution. The most important parameters are BTEXs, PAHs, NOx,
CO, 1,3-butadiene and particles (Winjen et al., 1998), and among these we have
measured BTEX and particulate matter using personal air samplers.
Exposure to particulate air pollution can cause severe health problems. McConnell et
al. (McConnell et al., 1994) observed a positive association between PM10 and
bronchitis in children with a history of asthma in southern California, and recently
Pope III et al (Pope III et al., 1999) showed a dose-relationship between PM10
concentrations and daily mortality in Utah.
Among the BTEX compounds benzene is considered to be the most hazardous.
Benzene is a well-known carcinogen (WHO, 1993) and among all the volatile organic
compounds related to traffic, it is the chemical of most health concern (Guerra et al.,
1995; Fromme, 1995).
We consider BTEX a good indicator for exhaust gases from gasoline engines, while
particles originate from various combustion sources and therefore indicate a more
unspecific pollution. Further, the ratio of exposure between car drivers and cyclists
was found to be about two times higher for BTEX compared to particulate matter
(Table 4). Therefore, we consider the benzene results of the present study to be of the
greatest significance, and these are thus discussed in further detail in the following.
In a comprehensive review by Wijnen and Zee (1998) many studies of volatile
organic compounds are reported, which showed higher in-vehicle concentrations than
were found in the ambient air. In-car concentrations of benzene in three American
cities were in the range 10-17 µg/m3. This is very close to what was found in our
study, while in-vehicle concentrations in Amsterdam were much higher with a
variation of 43-74 µg/m3.
In another review of Gennart et al. (1994), results from studies of in-vehicle benzene
concentrations showed much higher concentrations than this study. Thus, driving in
dense traffic in Sweden showed 100-200 µg/m3, and when queuing, the
concentrations reached 200-400 µg/m3. Higher concentrations of benzene within a car
compared to the ambient air were found in a study by Weisel et al. (1992), who
estimated that the difference was allowed up to 50 times higher inside the cabin than
outside. The great variations of benzene concentrations in the above mentioned
studies could be due to many factors, the most important being the concentration of
benzene in gasoline. When this study was carried out the benzene concentration of
gasoline could be up to 5 mg/l, while the limit value shortly after the study was
lowered to 1mg/l to comply with new EU regulations. Other factors may also
influence the in-vehicle benzene concentrations. Duffy and Nelson (1997) showed in
study from Sydney that the age of the cars is of great importance. They found in-car
concentrations of old cars (pre 1986 without catalyst equipment) to be twice as high
as in newer cars. Rømmel et al. (1999) found that the BTEX concentrations in the
streets of Munich decreased significantly during the years 1993 to 1997, indicating
that replacement of old cars may influence the concentrations of the volatile
The study by Winjen et al. (1995) showed a respiratory average of 2.3 times higher
for the cyclists compared with the car drivers. By using this factor we have calculated
that car drivers still get twice as much benzene (0.2 µg/min) into the lungs than bikers
(0.1 µg/min). It could be argued that car drivers are exposed to a lesser degree due to
a higher speed. However, our results show that during the rush hours the speed of the
car drivers is very similar to the speed of the cyclists. Moreover, if we consider the
children transported on the back of a bicycle they will inhale lesser pollutants than
inside a car, because they as passive passengers exhale the same amount of air in the
two situations.
Concern for small children as road users is important, taking into consideration that
benzene can cause leukaemia, and that leukaemia can be correlated to car ownership
(Wolf, 1992). Further, a study by Savitz and Feingold (1989) has shown that
childhood cancer can be correlated to trafic density and later Nordlinder and Järvholm
(1997) found that car density could be correlated to acute myeloid leukemia in
children and young adults.
Among the pollutants analysed in the present study, benzene is the only
compound that may cause adverse effects in the measured concentrations. WHO
(1995) has established a life span risk of cancer during 70 years of one cancer
observation per million people at 0.13 – 0.23 µg/m3. The actual measurements are 5 –
14 µg/m3, i.e. at least 40 to 50 times above this concentration.
On the basis of this study we can conclude that cyclists in the City of Copenhagen are
exposed to lower concentrations of traffic related pollutants than car drivers. Further,
it can be concluded that car drivers experience 3-4 times higher BTEX concentrations
and around two times higher exposure of particles than bikers. The study also
indicates that children may experience a better atmosphere on the back of a bicycle
than inside a car.
The authors wish to thank Lykke Enøe and Anne-Grethe Winding, who assisted the
experimental planning and sampling, and Henrik Demant, Jesper K. Hansen, Dennis
Madsen and Jacob Turman, who participated in the field study. The Danish Ministry
of Transport funded the study.
Duffy BL, Nelson PF. Exposure to emissions of 1,3-butadiene and benzene in the
cabins of moving motor vehicles and buses in Sydney, Australia. Atmospheric
Environ 1997; 31(23):3877-3885.
Fromme H. Gesundheitliche Bedeutung der verkehrsbedingten Benzolbelastung der
allgemeinen Bevölkerung (in German with abstract in English: The significance for
the health of the general population of exposure to benzene in traffic). Zbl Hyg 1995;
196: 481-494.
Fromme H, Beyer A, Meusel K, Baudisch H, Laue W. Untersuchung zur Belastung
der Berliner Bevölkerung mit aromatischen Kohlenwasserstoffen und Schwermetallen
im Rahmen einer Studie zu den gesundheitlichen Auswirkungen des Kkz-Verkehrs (in
German with abstract in English: Exposure of the population of Berlin to aromatic
hydrocarbons and heavy metals – an aspect of investigated as part of a study of
traffic-related effects on health). Gesundheitswesen 1997; 59:512-518.
Fromme H, Oddoy A, Lahrz T, Piloty M, Gruhlke U. Exposition der Bevölkerung
gegenüber flüchtigen Luftschadstoffen im Autoinnenraum und in der U-Bahn (in
German with abstract in English: Exposure of the population against volatile organic
compounds inside a car and a subway-train). Zent bl Hyg Umweltmed 1997/98; 200:
Gennart JP, Sanderson JT, Simpson BJ. Exposure and health risks associated with
non-occupational sources of benzene. Report No. 1/94, Concawe, Brussels, 1994, 24
Guerra G, Iemma A, Lerda D, Martines C. Benzene emissions from motor vehicle
traffic in the urban area of Milan: hypothesis of health impact assessment. Atmos
Environ 1995; 29(23): 3559-3569.
McConnell R, Berhane K, Gilliland F, London SJ, Vora H, Avol E, Gauderman WJ,
Margolis HG, Lurman F, Thomas DC, Peters JM. Air pollution and bronchitis
symptoms in Southern California Children with asthma. Environ Health Perspect
1994; 107(9): 757-760.
Nordlinder R, Järvholm B. Environmental exposure to gasoline and leukemia in
children and young adults – an ecology study. Int Arch Occup Environ Health 1997;
Pope III CA, Hill RW, Villegas GM. Particulate air pollution and daily mortality on
Utah’s Wasatch Front. Environ Health Perspect 1999; 107(7): 567-573.
Raaschou-Nielsen O, Lohse C, Thomsen BL, Skov H, Olsen JH. Ambient air levels
and the exposure of children to benzene, toluene, and xylenes in Denmark. Environ
Res 1997; 75: 149-159.
Raaschou-Nielsen O, Olsen JH, Hertel O, Berkowicz R, Skov H, Hansen ÅM, Lohse
C. Exposure of Danish children to traffic exhaust fumes. Sci. Total Environ.1996;
189/190: 51-55.
Römmelt H, Pfaller A, Fruhmann G, Nowak D. Benzene exposures caused by traffic
in Munich public transportation systems between 1993 and 1997. Sci Total Environ
1999; 241:197-203.
Savitz DA, Feingold L. Association of childhood cancer with residential traffic
density. Scand J Work Environ Health 1989; 15:360-363.
Weisel CP, Lawryk NJ, Lioy PJ. Exposure to emissions from gasoline within
automobile cabins. J Exposure Anal Environ Epidemiol 1992; 2(1): 79-96.
WHO. Environmental Health Criteria 150. Benzene. Geneva, 1993, 156 pp.
WHO. Updating and revision of the air quality guidelines for Europe. Report on a
WHO working group on volatile organic compounds, Brussels, Belgium 2-6 October
1995. WHO regional office for Europe, Copenhagen, 1995.
Winjen JH van, Zee SC van der. Traffic-related air pollutants: exposure of road users
and populations living near busy roads. Rev Environ Health 1998; 13:1-2.
Wijnen JH van, Verhoeff AP, Jans HWA, Bruggen M. van. The Exposure of cyclists,
car drivers and pedestrians to traffic-related air pollutants. Int Arch Occup Environ
Health 1995; 67:187-193.
Wolff SP. Correlation between car ownership and leukaemia: Is non-occupational
exposure to benzene from petrol and motor vehicle exhaust a causative factor in
leukaemia and lymphoma? Experienta 1992; 48: 301-304.
Table 1. Meteorological data from the two sampling days.
18 June 3 August
Wind velocity (10 m’s height) m/s 8.5 1-3
Wind direction W NW – E
Temperature °C 13,3 14
Air pressure Pa 1017 1024
Humidity % 61 90 ® 70
Table 2.
Bicycling and driving data for the two sampling days
Date Period Time Rounds Speed
Time Rounds Speed
min (7.6 km) km/h
min (7.6 km) km/h
18 June Rush hour VW 120 4 15.2 Cyclist 1
120 4 15.2 Fiat
114 4 16.0 Cyclist 2 120
4 15.2
Late morning VW 120 6 22.8
Cyclist 1 113 4 16.1
Fiat 105 6 26.1
Cyclist 2 113 4 16.1
3 August Rush Hour VW 115 5 19.8 Cyclist 1
130 4 14.0 Fiat
113 5 20.2 Cyclist 2 130
4 14.0
Late morning VW 120 6 22.8
Cyclist 1 125 4 14.6
Fiat 110 6 24.9
Cyclist 2 125 4 14..6
Rush hour, average 17.8±2.3
14.6±0.3 Late morning, average
24.1±2.3 15.4±0.3
Table 3.
Concentrations of BTEX and particles (total dust) sampled on two
different days in the city of Copenhagen, 1998.
Pollutant Date Car µg/m3
Bicycle µg/m3
Benzene 18 June VW 11.0 Bicycle 1
Fiat 17.5
Bicycle 2 5.4
3 August VW 15.5 Bicycle 1
Fiat 13.7
Bicycle 2 4.5
Toluene 18 June VW 41.2 Bicycle 1
Fiat 82.9
Bicycle 2 19.4
3 August VW 77.0 Bicycle 1
Fiat 76.0
Bicycle 2 19.6
ethylbenzene 18 June VW 42.8 Bicycle 1
and xylenes Fiat 72.6
Bicycle 2 18.7
3 August VW 73.9 Bicycle 1
Fiat 77.6
Bicycle 2 20.4
Particles, 18 June VW 88 Bicycle 1
total dust Fiat 120
Bicycle 2 68
3 August VW 45 Bicycle 1
Fiat 47
Bicycle 2 21
Table 4.
Results from ANOVA analysis
Car Bicycle Standard error P
µg/m3 µg/m3 of estimates, µg/m3
Benzene 14.4 5.2 1.1
0.004 2.8
Toluene 69 21 6
0.004 3.4 Ethylbenzene 67
18 4 0.001 3.7 and xylenes
Hydrocarbons 215 58 9
0.0002 3.7 Particles (total dust) 75 44
4 0.007 1.7
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... L'automobiliste est en règle générale davantage exposé à la pollution de l'air qu'un cycliste (Rank et al., 2001). Malheureusement, ce type d'étude a uniquement mesuré la composition de l'air (black carbon, NOx, PM, UFP…) mais ne tient généralement pas compte du fait que l'automobiliste est assis dans sa voiture sans faire d'activité physique. ...
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Cahiers de l'Observatoire de la mobilité de la Région Bruxelles-Capitale, 2020 Ce septième Cahier vient compléter la collection des Cahiers de l’Observatoire de la mobilité de la Région de Bruxelles-Capitale (RBC). Après avoir traité de l’offre de transport, des pratiques de déplacement en général et de celles liées au travail et à l’école en particulier, de logistique et de transport de marchandises, ou encore de partage de l’espace public entre tous les modes, ce nouveau Cahier s’arrête pour la première fois sur un mode spécifique : le vélo. Cette publication comporte trois parties. La première offrira une brève histoire du vélo racontée depuis Bruxelles et évitera d’emblée toute naturalisation du phénomène : le lent déclin du vélo au cours de la seconde moitié du 20e siècle résulte d’évolutions structurelles et non d’explications selon lesquelles Bruxelles ne serait " pas faite pour le vélo ". Cette première partie comportera également une mise en contexte institutionnelle afin d’identifier qui sont les acteurs compétents en matière de politique cycliste et la place occupée par celle-ci dans les outils réglementaires et planologiques régionaux, ainsi que dans ses budgets. Elle se terminera par une définition et une typologie des vélos et autres engins de déplacement légers. La deuxième partie du Cahier abordera la pratique du vélo en RBC à travers une analyse approfondie du parc vélo et des déplacements à vélo. Enfin, la troisième partie analysera la cyclabilité de la Région : les aménagements pour le vélo en mouvement, la sécurité et l’insécurité des cyclistes, le stationnement des élos et les services liés au vélo. Une conclusion générale viendra clore ce vaste exercice de synthèse. À noter que les données mobilisées dans ce Cahier ont été arrêtées en juillet 2019. Il va de soi qu’une actualisation régulière de cette synthèse sera nécessaire pour suivre l’évolution de ce secteur en pleine ébullition.
... The level of exposure is driven by many factors, including, but not limited to, transport emissions, city and transportation infrastructure, time spent commuting, and climate and meteorology. In Europe, car-drivers are exposed to the largest amount of air pollution, followed by cyclists and public transportation users, with pedestrians typically exposed to the least amount [6][7][8]. A systematic review found that commuters using motorized transport had increased exposure to air pollution due to their proximity to traffic and high air interchange whereas the increased inhalation rates and commuting time of active commuters caused them to have a higher inhaled dose [9]. ...
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Cities in the 21st century are dynamically changing in response to environmental and societal pressures, not least among which are climate change and air pollution. In some of these metropoles, such as Berlin, a transformation of mobility systems has already begun. Along a mid-sized street in Berlin, a measurement campaign was conducted in 2020 to accompany the construction of a bike lane and the implementation of a community space along one of the side-streets. Using the new technology of low-cost sensors, higher resolution measurements of local air quality were enabled. Stationary and mobile measurements were taken using EarthSense Zephyr sensor systems before and after the construction of the bike lane and during the timeframe when the community space was in place. It was found that the implementation of the bike lane led to a reduction in NO2 exposure for cyclists. During periods when the community space was in place, a reduction in NO2 concentrations was also measured. This study highlights not only the utility of low-cost sensors for the measurement of urban air quality, but also their value in a science-policy context. Measuring local air quality changes in response to traffic interventions will enhance understanding of the associated health benefits, especially in connection with measures promoting more sustainable modes of active travel. More research of this nature is needed to gain a clear understanding of the impacts of traffic interventions on local air quality for better protection of human health.
... People inside vehicles inhale more emissions compared to people outside vehicle (Giles-Corti et al., 2010). Driver and passenger sitting inside the vehicle inhale 18 times more pollution compared to people outside the vehicle, even the cyclists (Rank et al., 2001;Roemer & van Wijnen, 2001). ...
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Non-motorized transport (NMT) is the use of a bicycle or walking to travel from one place to another. It is gaining popularity especially in the developed countries due to low transport externalities such as emissions and traffic congestion alongside its benefits to physical and mental health. In this paper, a comprehensive review of the existing literature related to NMT is presented focusing on the factors including built environment, geography, and weather, the health, and environmental benefits of NMT, and the motivational approach for increasing the use of NMT. The built environment, geography and weather, and socioeconomic factors significantly affect the use of NMT as a travel mode. This study reviewed some unique characteristics of NMT especially in developing countries to provide a clear understanding of the dynamics of NMT. Despite existence of vast research on NMT, a comprehensive literature review to evaluate different aspects of NMT seems essential to address the future challenges with significant automobile ownership increase in the developing nations and the associated externalities. The developing nations have to understand the factors of NMT with reference to their socio-economic conditions and perform quantitative analyses to estimate and project benefits of NMT including health benefits. The policy makers in the developing countries should consider the NMT as one element of the solution matrix to address the challenges of road transport. Graphic Abstract
... For the air pollution measurements, the health impacts of CO, PM 2.5 , particulate matter, SO 2 and NO exposure in different transport modes are all examined in the literature (Cepeda et al., 2017;Zhao et al., 2018). For health indicators, numerous studies utilize exposure indicators to investigate the levels of air pollution exposure in different transport modes (Huang et al., 2012;Rank et al., 2001), while some studies also utilize inhalation to investigate the health impacts (Briggs et al., 2008). In addition, the health impacts of air pollution exposure in different transport modes are various in different geographical contexts. ...
The effects of air pollution and commuting behavior on life satisfaction have received increasing research interests. However, the literature pays scant attention to haze pollution and its moder- ating effects on the relationship between commuting behavior and life satisfaction. Using two- round of cross-sectional survey data across 92 Chinese cities, this paper analyzes the impacts of haze pollution and commuting behavior on life satisfaction, and the moderating effects of haze pollution on the link between commuting behavior and life satisfaction. The findings suggest that haze pollution and its changes are important triggers of life satisfaction. Moreover, the effects of changes in haze pollution correlate with basic haze pollution levels. Active commuters report higher life satisfaction, while transit commuters report lower life satisfaction. Longer commutes cause losses in life satisfaction. Additionally, haze pollution mitigates the losses in life satisfaction for commuters using public transit, but strengthens the negative effect of commuting time. 1.
... During commuting, the proximity to traffic-related sources is one of the major determinants of exposure to PM and VOCs. For some pollutants, as PM and benzene, the exposure to traffic exhausts depends on mode of transport, time of the day, and source characteristics (Adams, Nieuwenhuijsen et al. 2001, Rank, Folke et al. 2001, Spinazze, Cattaneo et al. 2013, Spinazze, Cattaneo et al. 2015. Despite the relatively limited amount of time (6-8%) usually spent by individuals in these environments (Kaur, Nieuwenhuijsen et al. 2007), they can greatly contribute to the total daily exposure (Buonanno, Fuoco et al. 2013, Spinazzè, Cattaneo et al. 2014), J o u r n a l P r e -p r o o f ...
Background Human exposure to air pollutants, and specifically to particulate matter (PM) and volatile organic compounds (VOCs), may pose a relevant risk on human health. Aim To evaluate the personal exposure of adults living and working in Milan (Italy) by environmental and biological monitoring. Methods Personal exposure of 51 volunteer adults to PM2.5, PM2.5-10 and selected VOCs, including benzene, toluene, ethylbenzene, o-xylene, m+p-xylene, methyl tert-butyl ether, naphthalene, hexane, cyclohexane, heptane, and limonene was assessed along a 24-h period via personal cascade impactors and radial diffusive samplers. Urine spot samples were collected to investigate the corresponding urinary biomarkers. Time-activity patterns were filled in by participants to explore the performed activities. Multiple regression models were applied to investigate the association between personal exposure, biomarker levels, and tobacco smoke, traffic exposure, commuting mode, cooking activities, and personal characteristics. Results Median personal exposure to PM2.5, PM2.5-10, benzene, toluene, ethylbenzene o-xylene, m+p-xylene, methyl tert-butyl ether, naphthalene, hexane, cyclohexane, heptane, and limonene were 36.1, 7.8, 2.3, 7.8, 2.1, 1.8, 4.7, 0.8, 0.3, 1.4, 2.5, 1.6, and 59.9 μg/m³, respectively. Median levels of urinary benzene, toluene, ethylbenzene o-xylene, m+p-xylene, naphthalene, hexane, and heptane were 78.0, 88.1, 21.5, 15.2, 43.9, 21.0, 11.0, and 22.5 ng/L, respectively. For personal exposure, multiple regression models explained up to 67% (PM2.5) and 61% (benzene) of variability, with major contribution from commuting mode and environmental exposure. For biological monitoring, multiple regression analysis explained up to 74% of urinary benzene, with a major contribution given by creatinine, and secondary contributions by commuting mode, personal exposure to airborne benzene and smoking. Conclusions Personal exposure to air pollutants was lower than that measured in the past in Milan. Personal exposure was mainly driven by traffic variables, while internal dose was mainly driven by personal characteristics and smoking habit.
The aim of this study was to compare the concentrations of the benzene, toluene, ethylbenzene, and xylene (BTEX) compounds in the urine of smokers and the control group considering the role of age, weight, job, history of waterpipe and cigarette smoking, and driving time. The chemicals in the urine of 99 smokers and 31 nonsmokers were extracted by liquid-liquid extraction method and their concentrations were measured by liquid injection GC/MS. The mean concentration of benzene, toluene, ethylbenzene, m-xylene, o-xylene, p-xylene, and total BTEX in waterpipe smokers were found to be 471.40, 670.90, 127.91, 167.64, 90.62, 46.04, and 1574.50 ng/g. creatinine, respectively. For the waterpipe&cigarette smokers, the concentration of the compounds were 708.00, 959.00, 146.40, 192.50, 93.30, 53.07, and 2152.00 ng/g.creatinine, respectively. For nonsmokers the concentrations of these compounds were 88.12, 140.40, 36.68, 57.29, 31.53, 26.21, and 380.30 ng/g.creatinine, respectively. Driving time, waterpipe smoking and cigarette smoking were positively associated with BTEX concentration (p < 0.05). Fruity tobacco showed higher concentrations of BTEX compared to the regular tobacco, and athlete persons had les urinary BTEX than the non-athletes. There was not significant correlation between the BTEX and age, height, weight, and BMI. High concentrations of BTEX compounds in the urine of waterpipe and cigarette smokers compared to nonsmokers indicate that waterpipe and cigarette can be an important source of exposure to these compounds and the known adverse effects of these compounds, especially carcinogenicity, threaten the health of smokers.
This article proposes a dynamic assessment of the exposure to air pollution of the urban population of the Paris region (France). The original methodology takes into account the variability in space and time of pollutants and inhabitants. It is based on the cross-referencing of NO2 concentration data (Airparif) and daily mobility data of a representative sample of inhabitants (Île-de-France Mobilités–OMNIL–DRIEA). The results underline the determining role of daily mobility in the level of individual exposure to pollution. Compared to the reference exposure at home, daily mobility leads the inhabitants of Paris region to deteriorate their NO2 exposure level by 1.1 µg/m3 (+4%) on average, to 32.1 µg/m3. The differentiated mobility of inhabitants according to the use of individual motorized modes and the time spent in Paris leads to an unequal deterioration of the quality of the air they breathe. For working people, students and residents of the outer suburbs, their daily mobility tends to significantly increase their exposure to NO2, unlike that of inactive people and residents of Paris.
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Volunteers provided with personal air sampling (PAS) equipment covered concurrently, by car or bicycle, various selected routes. These comprised two inner city routes in Amsterdam (ICR 1 and 2) as well as a route including a tunnel on a busy highway (TR) and a rural route just south of Amsterdam (RR). A third inner city route, a busy narrow street, was subsequently also selected, and covered by bicycle or walking (ICR 3). Each run lasted about 1 h; the sampling time on the TR route was approximately 30 min. The sampling periods in January and May lasted 2 weeks with four sampling days per week. In August only ICR 3 was covered, this sampling period lasted 2 days. CO, NO2, benzene, toluene and xylenes were measured in the personal air samples. A monitoring vehicle covered the routes concurrently and measured CO, NO2 and pm10 (semi) continuously. Lead and PAH content in pm10 was determined. The ventilation of the volunteers was measured while they were using a car or a bicycle. The route and the type of transport influenced (P < 0.001) the concentrations of CO, benzene, toluene and xylenes. The daily average temperature was positively associated with the exposure of car drivers and cyclists to most compounds measured. A volunteer exhaled on average 2.3 times more air as a cyclist than as a car driver. Despite the much higher concentrations in the personal air samples of car drivers, the uptake of CO, benzene, toluene and xylenes of cyclists sometimes approached that of the car drivers. The uptake of NO2 of cyclists was clearly higher than that of car drivers.
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This study identified in-auto and in-bus exposures to six selected aromatic volatile organic compounds (VOCs) for commutes on an urban-suburban route in Korea. A bus-service route was selected to include three segments of Taegu and one suburban segment (Hayang) to satisfy the criteria specified for this study. This study indicates that motor vehicle exhaust and evaporative emissions are major sources of both auto and bus occupants' exposures to aromatic VOCs in both Taegu and Hayang. A nonparametric statistical test (Wilcoxon test) showed that in-auto benzene levels were significantly different from in-bus benzene levels for both urban-segment and suburban-segment commutes. The test also showed that the benzene-level difference between urban-segment and suburban-segment commutes was significant for both autos and buses. An F-test showed the same statistical results for the comparison of the summed in-vehicle concentration of the six target VOCs (benzene, toluene, ethylbenzene, and o,m,p-xylenes) as those for the comparison of the in-vehicle benzene concentration. On the other hand, the in-vehicle benzene level only and the sum were not significantly different among the three urban-segment commutes and between the morning and evening commutes. The in-auto VOC concentrations were intermediate between the results for the Los Angeles and Boston. The in-bus VOC concentrations were about one-tenth of the Taipei, Taiwan results.
Volatile aromatics (benzene, toluene, xylenes, the BTX-aromatics) were measured between 1993 and 1997 in buses and trams in Munich center and along main roads during regular rides. The sampling time was between 07.00 and 00.00 h. A total of 631 probes were sampled and centrally analyzed. In the mean of 5 years we found 15.0 μg benzene/m3, 50% above the limit of the 23. BImSchV and 107.5 μg BTX aromates/m3 along the strongly traffic loaded main streets. Splitting up these mean emissions into single years we observed a trend toward a decline of mean immission of all volatile aromatics (benzene from 23.8 μg/m3 to 7.4 μg/m3) and the sum of BTX aromatics (from 147.5 μg/m3 to 59.4 μg/m3). The measured hydrocarbon concentrations in Munich center were consistent with the long range theoretical calculations concerning the decrease of traffic-caused benzene immissions in cities. If the current trends continue, we can expect benzene concentrations to be below 5 μg/m3 by the year 2001 and below 2.5 μg/m3 by the year 2008. At these levels, the carcinogenic risk from benzene is probably less significant than the risks to public health from other car exhaust components.
This exposure study addresses the validity of the exposure assessment method of an epidemiological study of traffic-related air pollution and childhood cancer. In particular, this paper concerns the question of whether the concentration of nitrogen dioxide (NO2) outside the front door is a valid marker of the exposure of the child living at the address. The study includes 100 children living on streets with dense traffic in central parts of Copenhagen and 100 children living in rural areas. Preliminary results, based on 25% of the study subjects, suggest that both the outdoor NO2-concentration and the exposure of the children are two to three times higher in Copenhagen than in the rural districts. Moreover, the results suggest that the NO2-concentration outside the front door is a poor marker of the exposure of the children in Copenhagen, but a marker of some relevance for the exposure of the children in rural districts. The preliminary results must be treated with caution, as among other things, the analysis did not consider seasonal changes and indoor NO2-sources such as passive smoking, candles, and gas appliances.
Several problems concerning air quality in urban areas with special regard to benzene pollution from motor vehicle traffic are described. Some medical and regulatory aspects relative to the exposure of population and specific classes of workers are given particular stress. Benzene concentrations measured in the metropolitan area of Milan in an extensive monitoring campaign are presented together with historical carbon monoxide (CO) measurements realized by the Milan air pollution network. Starting from these two series of values a typical ratio between CO and benzene has been calculated and it has been found to be consistent with literature data. A risk assessment hypothesis has been performed using a simple model based on both kinds of data mentioned above.
Concentrations of 1,3-butadiene and benzene have been measured inside the cabins of both pre-1986 (non-catalyst-equipped) and post-1986 (catalyst-equipped) vehicles on freeway and urban driving routes around Sydney, Australia. Mean in-vehicle concentrations of 1,3-butadiene and benzene observed for the newer cars during the morning peak-hour were 5.5 ± 2.l and 22.1 ± 4.1 ppb respectively. Corresponding values for the older, poorly maintained vehicle were 11.5 ± 3.0 and 48.1 ± 6.9 ppb, respectively, about double those of newer vehicles. 1,3-Butadiene was only observed at significant concentrations inside the cabins of moving vehicles during peak-hour traffic. Concentrations of this species both in the ambient air, and in the vehicle cabins during freeway trips in non-peak periods, were near or below the detection limit of 0.1 ppb. Therefore, commuter trips are likely to be the major source of exposure to this compound. Both using the airconditioner and driving with the vents closed were the most effective ventilation conditions for minimising the exposure to fresh exhaust. For both conditions, trip average in-vehicle concentrations were about 70% of those in the air directly outside the vehicle. For vehicles left in a parking station during the day, exposures to 1,3-butadiene during evening commuter trips were observed to be about 1.2 times those in the morning peak-hour. Concentrations of volatile organic compounds measured inside buses were about 50% of those observed for newer cars.
Although there is widespread agreement that many cancers have environmental causes we are often unable to see associations between specific cancers and exposure to environmental chemicals. One might also speculate that the more widespread, common-place and 'normal' a chemical exposure is perceived to be then the less likely it will be that the exposure is recognised, let alone be considered to cause cancer. Widespread contamination of air by chemicals associated with internal combustion may be an example of one such 'invisible' carcinogenic exposure. Yet evidence is available which suggests that many leukaemia and lymphoma cases, as well as other cancers, may be caused by this mundane and ubiquitous environmental contamination. The hypothesis is developed that leukaemia 'clustering' as well as national leukaemia incidence may be related to non-occupational exposure to benzene formed by petrol combustion and resulting from petrol evaporation. The possible association between exposure to fuel vapours, internal combustion products and cancer merits much closer examination than it receives at present.
Gasoline is emitted from automobiles as uncombusted fuel and via evaporation. Volatile organic compounds (VOC) from gasoline are at higher levels in roadway air than in the surrounding ambient atmosphere and penetrate into automobile cabins, thereby exposing commuters to higher levels than they would experience in other microenvironments. Measurements of VOC concentrations and carbon monoxide were made within automobiles during idling, while driving on a suburban route in New Jersey, and on a commute to New York City. Concentrations of VOC from gasoline were determined to be elevated above the ambient background levels in all microenvironments while VOC without a gasoline source were not. The variability of VOC concentrations with location within the automobile was determined to be smaller than inter-day variability during idling studies. VOC and carbon monoxide levels within the automobile cabin differed among the different routes examined. The levels were related to traffic density and were inversely related to driving speed and wind speed. Overall, daily VOC exposure for gasoline-derived compounds during winter commuting in New Jersey was estimated to range between 5 and 20% and constituted between 15 and 40% of an individual's daily exposure based on comparison to urban and suburban settings, respectively. VOC exposure during commuting in Southern California was estimated to range between 15 and 60%.
Data from a recently completed case-referent study of childhood cancer were used to explore a possible role of environmental exposures from traffic exhaust. The street addresses of 328 cancer patients and 262 population-based referents were used to assign traffic density (vehicles per day) as a marker of potential exposure to motor vehicle exhaust. An odds ratio of 1.7 [95% confidence interval (95% CI) 1.0-2.8] was found for the total number of childhood cancers and 2.1 (95% CI 1.1-4.0) for leukemias in a contrast of high and low traffic density addresses (greater than or equal to 500 versus less than 500 vehicles per day). Stronger associations were found with a traffic density cutoff score of greater than or equal to 10,000 vehicles per day, with imprecise odds ratios of 3.1 (95% CI 1.2-8.0) and 4.7 (95% CI 1.6-13.5) for the total number of cancers and leukemias, respectively. Adjustment for suspected risk factors for childhood cancer did not substantially change these results. Though the results are inconclusive, the identified association warrants further evaluation.
Significant air pollution can be present in the interior of vehicles due to emissions from materials forming part of the interior fittings and to combustion and evaporation emissions, both when the motor is on and when the vehicle is stationary. In the case of new vehicles, escaping volatile organic compounds (VOC) in concentrations of 10-12 mg/m3 (partly up to 65 mg/m3) have been found. Benzene pollution of the interior of the vehicle is of particular significance to health. Benzene can be present in the interior of cars in average concentrations of about 50 micrograms/m3. Application of an overall risk assessment shows that, even under conditions of only a one-hour car ride per day, this pollution represents a risk of 30% of the total benzene risk (6 cases of cancer per 100.000 person exposed).