Traditionally, the exposure of the population to air pollutants has been assessed based on data from air quality monitoring stations located all across the country (in Catalonia we have the XPVCA, http://dtes.gencat.cat/icqa), which provide data for a variety of pollutants, but only in few points in a city or region.
However, according to the definition of Ott (1982), human exposure is ‘the event when a person comes into contact with a pollutant of a certain concentration during a certain period of time’. Therefore, for an accurate personal exposure assessment the different places in which time is spent should be considered (Ashmore and Dimitroulopoulou, 2009), and, in fact, is in indoor environments where people spend most of their time (approximately 90% of their day (Schweizer et al., 2006), depending on occupation, age, gender and status). Therefore, direct personal exposure measurements are the most representative of people’s exposure (Jantunen et al., 2002).
For personal exposure assessments, individuals should be carrying with them during the whole day one or more instruments or dosimeters which will allow to determine the actual exposure of this particular person to a specific air pollutant. These instruments should be small, light and battery operated (in case they need energy), since they need to be carried during all day. Nowadays, due to the miniaturisation of the instrumentation for air pollutant monitoring, there are many options available.
- Passive samplers/Dosimeters. Dosimeters are easy to use, very light and do not need energy to operate, since they are based on chemical reactions. They are suitable for gaseous pollutants, which react with the absorbent (specific for the target pollutant) in the dosimeter and can be quantified. They can be easily worn in the clothes without an important nuisance. Their main disadvantage is that they need to be exposed for long periods (generally more than 2 weeks). An example of a dosimeter for measuring the exposure to NO2 (a gaseous pollutant) is the Ogawa passive dosimeter (Figure 1).
Figure 1. Ogawa passive sampler for NO2. Source: http://ogawausa.com/passive-sampler/
- Filter samplers. Particulate matter (PM, particles suspended in the air) can be collected in filters using an impactor and a pump. The filters need to be weighted before and after the sampling, in order to determine the PM concentration. Besides, filters can be chemically analysed to obtain as well concentrations of the PM chemical components. Similarly to dosimeters, the time resolution of this methodology is low, with the filters needed to be exposed for at least 24h in order to get enough PM mass accumulated in the filter. An example would be the Sioutas Personal Cascade Impactor (PCIS), which should be attached to a pump (Figure 2). Figure 3 shows filters after being sampled with the PCIS.
Figure 2. A volunteer wearing a Sioutas Personal Cascade Impactor (PCIS) attached to a SKC Pump. Source: http://skcinc.com/catalog/pdf/instructions/1616.pdf
Figure 3. Filters after sampling with the PCIS. Source: Own archive.
- Miniaturised online monitors/sensors. The miniaturisation of air pollution monitors permits to obtain information of a specific air pollutant at a very high time resolution. These instruments are continuously monitoring the pollutant concentration and logging the information in an internal memory. Therefore, the main advantage is that the time resolution can be very high (the instrument may log information every few minutes or seconds). They are battery operated and should be light enough to not become a burden to the person who carries it. As an example, the MicroAeth AE51 monitors Black Carbon concentrations (black carbon, BC, is a particulate pollutant released to the atmosphere during combustion processes, such those that happen in diesel engines) and the DiSCmini measures ultrafine particle number concentration (in the cas of DiSCmini those particles with a diameter below 700 nm).
These monitors and dosimeters should be sampling air close to the breathing area, in order to get an accurate measurement of the air that the person is breathing.
As previously said, some instruments allow the collection of information about the pollutant concentration with a very high time resolution, while other methodologies need of longer periods of exposure. The former (high time resolution), permit the identification of the microenvironments which contribute more importantly to personal exposure.
In a study carried out in Barcelona (Rivas et al., 2015); within the BREATHE Project, www.creal.cat/projectebreathe), 45 children (7-10 years old) from 25 different schools were selected for personal monitoring. Those children were carrying a MicroAeth AE51, a GPS, an accelerometer and a mobile phone (the last acting as a GPS and accelerometer) packed inside a belt bag (Figure 5) during 48h during the weekday. Besides, they were asked to fill in a time-activity diary, in order to identify the main activities and the microenvironments in which these took place. From the information obtained in those diaries, the time that children spent during the day was classified as time spent inside the school building, in the school playground, at home, commuting and “others” (this include microenvironments such as library, swimming pool, football pitch, etc.).
Figure 5. Forty-eight children carried a MicroAeth AE51, a GPS, an accelerometer and a smartphone inside a belt bag during 48h. Source: own archive.
The results from this experiment showed that the highest concentrations of BC (which is mainly emitted from traffic in urban environments) were observed during commuting times (geometric mean (GM) = 2.0 µg/m3), which is when the children were closer to the emission source. On the other hand, the lowest concentrations were found at home (GM = 0.9 µg/m3). This could be explained by the fact that most of the time spend at home was during the night period, which is when the BC concentrations are lowest. BC concentrations found during the time when children were at schools were 1.2 µg/m3 when they were inside the school building and 1.0 µg/m3 when playing in the school playgrounds.
Figure 6. Average percentage of exposure and percentage of time that children receive/spent in a day.
According to the time spent in each microenvironment, we can determine the exposure to BC received in each microenvironment. In figure 6 we can observe how, although having the lowest mean concentration, children received the 50% of their daily exposure while being at home. This is due to the long period spent at home (58% of their time). Regarding the school environment, children spent 30% of their weekdays at schools, where they received 33% of their exposure to BC (26% in the classrooms and 7% at playgrounds). Globally, indoor environments (this is, classroom and home) accounted for the 82% of the time during weekdays and the 76% of the exposure. Hence, children received ¾ of their exposure in the indoor environment. However, the highest ratio of exposure with respect to the time spent was observed during commuting time. It was responsible for the 12% of the daily exposure while it only took 6% of the time. This is due to the very high concentrations that people is exposed to during transportation due to the physical proximity to traffic emission sources.
Policies to reduce BC concentrations should be enhanced throughout the urban area. However, although the time (and exposure) at home is higher, policies tackling the reduction of BC emission around schools (limiting traffic, for instance) should benefit a large number of children (which is actually one of the most vulnerable population) given the large amount of time that they spend in this shared location (school).
Ashmore, M.R., Dimitroulopoulou, C., 2009. Personal exposure of children to air pollution. Atmos. Environ. 43, 128–141. doi:10.1016/j.atmosenv.2008.09.024
Jantunen, M., Hänninen, O., Koistinen, K., Hashim, J.H., 2002. Fine PM measurements: personal and indoor air monitoring. Chemosphere 49, 993–1007.
Ott, W.R., 1982. Concepts of human exposure to air pollution. Environ. Int. 7, 179–196. doi:10.1016/0160-4120(82)90104-0
Rivas, I., Donaire-Gonzalez, D., Bouso, L., Esnaola, M., Pandolfi, M., de Castro, M., Viana, M., Àlvarez-Pedrerol, M., Nieuwenhuijsen, M., Alastuey, A., Sunyer, J., Querol, X. Spatio-temporally resolved Black Carbon concentration, schoolchildren’s exposure and dose in Barcelona. Indoor Air, in press, 2015. doi: 10.1111/ina.12214.
Schweizer, C., Edwards, R.D., Bayer-Oglesby, L., Gauderman, W.J., Ilacqua, V., Juhani Jantunen, M., Lai, H.K., Nieuwenhuijsen, M., Künzli, N., 2006. Indoor time–microenvironment-activity patterns in seven regions of Europe. J. Expo. Sci. Environ. Epidemiol. 17, 170–181. doi:10.1038/sj.jes.7500490