No abstract

There are currently no epidemiological studies on health effects of long-term exposure to ultrafine particles (UFP), largely because data on spatial exposure contrasts for UFP is lacking. The objective of this study was to develop a land use regression (LUR) model for UFP in the city of Amsterdam. Total particle number concentrations (PNC), PM10, PM2.5, and its soot content were measured directly outside 50 homes spread over the city of Amsterdam. Each home was measured during one week. Continuous measurements at a central urban background site were used to adjust the average concentration for temporal variation. Predictor variables (traffic, address density, land use) were obtained using geographic information systems. A model including the product of traffic intensity and the inverse distance to the nearest road squared, address density, and location near the port explained 67% of the variability in measured PNC. LUR models for PM2.5, soot, and coarse particles (PM10, PM2.5) explained 57%, 76%, and 37% of the variability in measured concentrations. Predictions from the PNC model correlated highly with predictions from LUR models for PM2.5, soot, and coarse particles. A LUR model for PNC has been developed, with similar validity as previous models for more commonly measured pollutants.

No abstract

In the early summer of 1995, the acute respiratory effects of ambient air pollution were studied in a panel of 61 children, ages 7 to 13 yr, of whom 77% were taking asthma medication. Peak flow was measured twice daily with MiniWright meters at home and the occurrence of acute respiratory symptoms and medication use was registered daily by the parents in a diary. Exposure to air pollution was characterized by the ambient concentrations of ozone, PM10, and black smoke. During the study period, maximal 1-h ozone concentrations never exceeded 130 microg/m3, and 24-h black smoke and PM10 concentrations were never higher than 41 and 60 microg/m3 respectively. Associations of air pollution and health outcomes were evaluated using time series analysis. After adjusting for pollen, time trend, and day of the week, black smoke in particular was associated with acute respiratory symptoms and with medication use. Less strong associations were found for PM10 and ozone. These results suggest that in this panel of children, most of whom had asthma, relatively low levels of particulate matter and ozone in ambient air are able to increase symptoms and medication use.