The present study used a novel approach to measure air quality using a mobile platform
. We assessed PM10 levels in the street situation at a real time basis in order to analyse in-vehicle-PM10 exposure with roof-open versus roof-closed driving modes.
We first addressed the influence of the wind velocity and found out that there is a correlation of velocity and PM10 values both at our mobile measurements and at the stationary BLUME analyzers. Therefore, we were not able to accumulate all data (i.e. tours 1+4+7+10+13 vs. 2+5+8+11+14) but had to compare only those measuring intervals that are adjacent, i.e. intervals 1 vs. 2 were compared, 4 vs. 5 were compared, 7 vs. 8 were compared, 10 vs. 11 were compared and 13 vs. 14 were compared, respectively. We found out that there are partly significant differences between driving cars with the roof open or the roof closed. In this respect, driving in an environmental zone in the direction West to East with the roof open produces PM10 levels between 41.1 μg/m3 ± 6.2 μg/m3 in the time interval 1. This is significantly higher than the levels observed when driving with windows and roof closed (adjacent interval 2 with 32.5 μg/m3 ± 6.4 μg/m3, p < 0.0001), indicating a barrier effect by the closed roof in this period. So far, no other studies that measured PM levels with cars presented precise data on this effect on PM10 levels have been published in the literature
[1, 6]. Out of 5 compared intervals all open vs. all closed, 4 differed highly significant whereas the comparison of interval 4 (all open with 27.2 μg/m3 ± 7.2 μg/m3) vs. 5 (all closed with 23.7 μg/m3 ± 3.6 μg/m3) did not differ significantly (p = 0.062). Therefore, it needs to be stated that there are still biasing factors present in our experimental set up which prevent from extrapolation of the data to other driving situations.
Since there is much public debate on the question of environmental zones and congestion charging zones over Europe
[7–11], we also divided the data into non-environmental zone and environmental zone data. However, there were no large differences present and effects of environmental zones on PM10 levels can not be investigated using our MAQS approach. For this purpose, future studies should focus on data from stationary PM10 analysis prior and after the implementation of the environmental zone. Also bias factors such as weather conditions need to be taken into consideration as shown presently. In this respect, our present analysis which consisted only of data from one single day with no major weather changes apart from variations in the wind velocity between 1.5 and 3.5 m/s demonstrated that meteorological factors such as wind velocity need to be taken into account seriously.
A further aim was to investigate the effects of different vehicle speeds in closed and roof open driving modes. We compared the levels of PM10 within each driving interval. With regard to the hypothesis that a higher speed leads to a decrease in the PM10 levels measured in the vehicle, we found out that this only applies for the early intervals and only in the mode “roof open”, both in the environmental zone and the non-environmental zone. By contrast, when the roof is closed, there are no significant PM10 level differences related to the speed of the vehicle.
We can conclude that under certain circumstances, the vehicle operation mode (open/closed/speed) influences PM10 levels inside the vehicle. Concerning the biological meaning of these findings, it needs to be stated that although there are significant differences in PM10 levels, the duration of driving in open – convertible – vehicles is usually limited to summer months and non-crowded roads in a private situation. In this respect, it would be interesting to study occupational settings: i.e. the effects of opening windows on PM10 levels in trucks and lorries. So far, air quality analysis on the basis of mobile platforms did not reach large scale practical implementation
. Therefore, only little data is available in public databases such as the PubMed. As discussed earlier, a number of studies have used particulate matter analysis in closed vehicles
. In this respect, two studies assessed the exposure to fine airborne particulate matter (PM2.5) in closed vehicles
[1, 12, 13]. It was reported that this may be associated with cardiovascular events and increased mortality in older and cardiac patients. Another study assessed particulate matter concentrations whilst simultaneously walking and driving 48 routes in London, UK
[1, 6]. Car trips were performed with closed windows and the moderate ventilation system settings. It was shown that mean exposures while walking were greatly in excess of those while driving, by a factor 4.7 for the coarse particle mass (PM10-PM2.5), 2.2 for the fine particle mass (PM2.5-PM1), 1.9 for the very fine particle mass (<PM1) and 1.4 for ultrafine particle number density
. It is enticing to speculate how convertible vehicle measurements would have been. With the ability of the MAQS-platform, this analysis can be performed in future. The reduced in-car exposures can be attributed to the filtration system which helped to prevent ingress of particles, so that the vehicle acted as a more-or-less independent micro-environment, insulated against much of air pollution present in the street
[1, 6]. In contrast to results of these studies from closed vehicles
[1, 12, 13], exposure in open vehicles has not been investigated in great detail so far apart from the present study. In this respect, the present project may not only be used as mobile traffic pollution sensor platform but also to investigate the particulate matter exposure in open-convertible vehicles versus closed-convertible vehicles under a multitude of settings.
Concerning other mobile environmental sensing systems, a recent British project may be used as a benchmark. This project entitled Mobile Environmental Sensing System Across Grid Environments (MESSAGE) is a three-year research project that is funded jointly by the British Engineering and Physical Sciences Research Council and the British Department for Transport.