1. Personal exposure to PM2
Personal exposure to PM2.5 among high-school students in Milan: the EuroLifeNet study Alessandro Borgini 1, Andrea Tittarelli 1, Cristian Ricci 2, Martina Bertoldi 1, Emile De Saeger 3, Paolo Crosignani 1 1 Cancer Registry and Epidemiology Unit, National Cancer Institute, Milano, Italy 2 Biometry and Clinical Epidemiology Unit GSD Foundation Corso di Porta Vigentina, n Milano (MI) 3 European Commission, Joint Research Centre, Institute for Environment and Sustainability, Transport and Air Quality Unit, Ispra (Varese), Italy
1 – INTRODUCTION
Ninety students of three high schools in Milan city (Rinascita, Feltrinelli, Cremona) were monitored for personal PM2.5 exposure with portable nephelometers, during a period of three weeks in November and December The first aim of this study was to investigate personal exposure and the relationship between particulate matter PM2.5 assessed by the nephelometers (see figure 1) and background PM2.5 values by Environmental Regional Protection Agency (ARPA Lombardy). The student’s exposure were monitored continuously for 24-h for 10-second PM2.5 concentrations in different microenvironment (outdoor exposure and indoor exposure) from Monday to Friday.
2 – ENVIRONMENTAL DATA COLLECTION AND TIME – ACTIVITY DIARY
Students were also previously trained by the teachers to use the Time-Activity Diary (TAD) (see figure 2) to report their times, locations and activities (principally related to different mode of transport of the students); The 10-seconds measurements were averaged in 30-min intervals to match the TAD time. We calculated the average of the values of the concentration of fine particulate matter (PM2.5) every thirty minutes for every students and in the end we have calculated more than six hundred thousand concentration values of (PM2.5) personal exposure (see figure 3).
Fig. 1 TSI AM510 SIDEPAK
Personal Aerosol Monitor
Fig. 3 Example of one student’s exposure to PM2.5 in one day
Fig. 2 Exemple of Student’s Time Activity
Diary (TAD)
3 – RESULTS
During the study period, PM2.5 background daily concentrations varied from a minimum of 25 µg m-³ (on 22 November) to a maximum of 117 µg m-³ (on 16 November) see figure 4. The mean of this distribution was µg m-³, the median was µg m-³, the inter-quartile range was µg m-³. The correlation (Pearson’s R) between the mean nephelometer readings (six nephelometers each day) and daily background values varied from 0.64 to 0.75; the overall correlation was During the study period the mean of indoor measurements was µg m-³, while the mean of outdoor measurements was µg m-³. Application of the one-tail Mann-Whitney U-test showed that median indoor exposure was higher than median outdoor exposure, and that for 44 of 68 matched median comparisons by school and day. The binomial test showed that this difference was significant (P=0.005), and Fisher's combined p-value on the Mann-Witney U-test results value was < The differences between outdoor and indoor medians ranged from 0.84 µg m-³ to µg m-³ with a median of µg m-³ , a mean of µg m-³ and a standard deviation of µg m-³. Thus, the distribution of these differences was highly skewed. The concordance among schools was satisfactory as shown by Bland – Altman plots (see figure 5).
Fig. 4. Daily means of PM2.5 values for the three schools in relation to background levels. Solid line: background values (ref); circles: Cremona (CRE) school; triangles: Feltrinelli (FEL) school; squares: Rinascita (RIN) school.
Fig. 5. Bland – Altman plots: A - Cremona school vs. Feltrinelli school; B – Rinascita school vs. Feltrinelli school; C - Cremona school vs. Rinascita school
4 - CONCLUSIONS
Epidemiological studies on the health effects of air pollution usually make use of data from fixed monitoring stations as a proxy of individual exposure as it has often been impracticable to measure the personal exposure of each study participant. However it is important to measure pollutant concentrations in the microenvironments in which people spend their time (indoor and outdoor) because PM2.5 concentrations are higher in many microenvironments than those measured by fixed site monitors. Nevertheless our analysis revealed good overall concordance between personal PM2.5 exposure and exposure measured at the reference site. As shown by Pearson’s correlation coefficient, in the study period about 60% of the variability in personal exposure was due to the variability in background exposure, the other 40% due to differences in between-subject exposure. With regard to indoor vs. outdoor exposure, we found that exposure was generally higher in indoor environments than outdoors, as reported in other similar studies, such as the European EXPOLIS. Such a difference could be due to indoor sources of exposure like cooking at home or science laboratories at school, but mainly to tobacco smoke at home. Indoor PM2.5 is affected by ambient concentrations, air exchange rates, penetration factors, as well as deposition and resuspension. Cooking, cleaning and particularly smoking result in the formation of PM2.5 and others contaminants in indoor air.