Population exposure to fine particles and estimated excess mortality in Finland from an East European wildfire episode.

Long-range transported particulate matter (PM) air pollution episodes associated with wildfires in the Eastern Europe are relatively common in Southern and Southeastern Finland. In severe cases such as in August-September 2002, the reduced visibility and smell of the smoke, and symptoms such as irritation of eyes and airways experienced by the population raise the issue into the headlines. Because PM air pollution, in general, has been identified as a major health risk, and the exposures are of repeating nature, the issue warrants a risk assessment to estimate the magnitude of the problem. The current work uses the available air quality data in Finland to estimate population exposures caused by one of the worst episodes experienced in this decade. This episode originated from wildfires in Russia, Belarus, Ukraine, and the Baltic countries. The populations of 11 Southern Finnish provinces were exposed between 26 August and 8 September 2002, for 2 weeks to an additional population-weighted average PM(2.5) level of 15.7 microg/m(3). Assuming similar effect on mortality for these particles as observed in epidemiological time series studies on urban particles (0.5%-2% increase in mortality per 10 microg/m(3), central estimate 1%), this exposure level would be associated with 9-34 cases (17 cases central estimate) of additional mortality. Epidemiological evidence specific to particles from biomass combustion is scarce, affecting also the reliability of the current risk assessment. Do the wildfire aerosols exhibit the same level of toxicity as the urban particles? To shed light on this question, it is interesting to look at the exposure data in relationship to the observed daily mortality in Finland, even though the limited duration of the episode allows only for a weak statistical power. The percentage increases observed (0.8%-2.1% per 10 microg/m(3) of fine PM) are in line with the more general estimates for urban PM and those used in the current risk assessment.

Characterization of model error in a simulation of fine particulate matter exposure distributions of the working age population in Helsinki, Finland.

Exposure models are needed for comparison of scenarios resulting from alternative policy options. The reliability of models used for such purposes should be quantified by comparing model outputs in a real situation with the corresponding observed exposures. Measurement errors affect the observations, but if the distribution of these errors for single observations is known, the bias caused for the population statistics can be corrected. The current paper does this and calculates model errors for a probabilistic simulation of 48-hr fine particulate matter (PM2.5) exposures. Direct and nested microenvironment-based models are compared. The direct model requires knowledge on the distribution of the indoor concentrations, whereas the nested model calculates indoor concentrations from ambient levels, using infiltration factors and indoor sources. The model error in the mean exposure level was <0.5 microg m(-3) for both models. Relative errors in the estimated population mean were +1% and -5% for the direct and nested models, respectively. Relative errors in the estimated SD were -9% and -23%, respectively. The magnitude of these errors and the errors calculated for population percentiles indicate that the model errors would not drive general conclusions derived from these models, supporting the use of the models as a tool for evaluation of potential exposure reductions in alternative policy scenarios.

The EXPOLIS study: implications for exposure research and environmental policy in Europe.

Exposure analysis is a crucial part of effective management of public health risks caused by pollutants and chemicals in our environment. During the last decades, more data required for exposure analysis has become available, but the need for direct population based measurements of exposures is still clear. The current work (i) describes the European EXPOLIS study, designed to produce this kind of exposure data for major air pollutants in Europe, and the database created to make the collected data available for researchers (ii) reviews the exposure analysis conducted and results published so far using these data and (iii) discusses the implications of the results from the point of view of research and environmental policy in Europe. Fine particle (with 37 elements and black smoke), nitrogen dioxide, volatile organic compounds (30 compounds) and carbon monoxide inhalation exposures and exposure-related questionnaire data were measured in seven European cities during 1996-2000. The EXPOLIS database has been used for exposure analysis of these pollutants for 4 years now and results have been published in approximately 30 peer-reviewed journal papers, demonstrating the versatility, usability and scientific value of such a data set. The multipollutant exposure data from the same subjects in the random population samples allows for analyses of the determinants, microenvironments and sources of exposures to multipollutant mixtures and associations between the different air pollutants. This information is necessary and useful for developing effective policies and control strategies for healthier environment.

Quantitative analysis of environmental factors in differential weighing of blank Teflon filters.

Mass differences less than 100 microg must be correctly measured in gravimetric analysis of particles collected on filters. Even small variations in mass measurement may contribute significant errors to calculated concentrations. In addition to the collected particles, a number of other factors affect the observed mass difference between the measurements before and after sampling. The most often controlled of these factors are static charge, temperature, and humidity. Using 951 laboratory blank filter weights, we have statistically analyzed these and other factors that affect the observed filter weight. Some of these are controllable or correctable; others are not and enter into the final results as errors. The standard deviation of differential blank filter weighing after applying all corrections was 2.7 microg. The most important correctable factors are air buoyancy variation and filter storage time. When weighing blank Teflon filters at relative humidity < 50%, these are an order of magnitude more important than weighing-room humidity. Using field blank filters in each weighing batch could control these three factors but also doubles the errors caused by balance random variation and filter handling contamination, because four weighing measurements and the handling of two filters are needed to obtain one corrected differential mass result.