Assessment of Population Exposure to Particulate Matter for London and Helsinki

Abstract

Most epidemiological studies have been conducted based on relations between pollution concentrations measured at fixed ambient air quality monitoring sites, or modelled values using land-use regression models, and various health indicators. However, such simplistic modelling ignores several crucial factors, such as, (i) the activity patterns of individuals, i.e. people’s day-to-day movements, and (ii) the differences between indoor and outdoor air. We have developed a mathematical model for the determination of human exposure to ambient air pollution in an urban area, called EXPAND (EXposure model for Particulate matter And Nitrogen oxiDes). The model combines (i) predicted concentrations, and (ii) information on people’s activities and location of the population, to evaluate the spatial and temporal variation of average exposure of the urban population to ambient air pollution in different microenvironments. In particular, the model takes into account the movements of the population and the infiltration from outdoor to indoor air. We present fine-resolution numerical results on annual spatial concentration, time activity and population exposures to PM_2.5 in London and in the Helsinki Metropolitan Area, for 2008 and 2009. We have shown that the effect of neglecting the movements of the population, which is the currently commonly applied procedure, can result in an underprediction of exposure by several tens of per cent.

Questions and Answers

QUESTIONER: H. Schluenzen

QUESTION: How are indoor emissions considered? Are they included and what do we know?

ANSWER: This study addressed only the influence of outdoor air pollution on the population exposure. We took into account exposures caused by (i) pollution in outdoor air and (ii) outdoor air pollution that has been infiltrated to indoor air. A natural follow-up of this study would be to take into account also indoor air pollution sources.

In general, indoor air quality is determined by infiltration, ventilation and indoor pollution sources. Clearly, indoor air sources can in some cases have a substantial effect on the population exposure to air pollutants. A few examples of indoor pollution sources are smoking, heating and cooking. For instance, the influences of active or passive smoking in indoor environments is commonly larger than those caused by outdoor air pollution.

QUESTIONER: A. Hakami

QUESTION: If inaccuracies resulting from outdoor-indoor infiltration and population movements are already included in epidemiological estimates, then will this higher level of detail improve health impact assessments?

ANSWER: The problem is that the factors that you mentioned are commonly not included. Most of the epidemiological studies have been conducted based on pollution concentrations measured at fixed ambient air quality monitoring sites, or modelled values using land-use regression models. Such methods do not in any way allow for the infiltration of pollution indoors and population movements.

Since the urban population spends typically 80–95 % of their time indoors, the exposure to particles is commonly dominated by exposure in indoor environments. However, many previous approaches have ignored the differences between indoor and outdoor air.

In this study, we have allowed in a more realistic manner for the movements of people and outdoor-indoor infiltration. We have also shown that including these effects has a substantial effect on the evaluated health outcomes: these can change the predicted population exposure by tens of per cent or more.

QUESTIONER: D. Wong

QUESTION: How long is your study, i.e., how many years of data are included? Did you include data on man-made or natural barriers in your study? I have done CDF work that shows that obstacles have a significant effect on concentrations.

ANSWER: The computations that I presented were done for hourly averaged data within 1 year. It would of course be possible to repeat the computations for some other years. Clearly, the exposure of the whole urban population for different years can be totally different for specific hourly and daily values, but annually averaged values change slowly from year to year.

The dispersion modelling and the spatial averaging do not allow either for the dispersion in street canyons or the very fine-scale concentration distributions above the roads and streets. In some previous studies, we have also conducted both street canyon modelling, using the OSPM model, and CFD modelling for specific locations in Helsinki. You are correct of course that by using such methods the fine scale (meters or tens of meters) concentration distributions could be modelled more accurately. However, for practical reasons it was not possible in this study to use street canyon or CFD models for the tens or hundreds or street canyons in these cities.