Authorities are faced with important challenges in evaluating the health relevance of air quality and its trends. First, advancements in exposure and modelling sciences result in the abundance of spatially and temporally resolved air quality models and the absence of a gold standard poses a challenge to the estimation of air pollution-related health effects. Second, researchers and policy makers from less polluted countries like Switzerland need to understand how health effects relate to low and very low levels of air pollution. It needs thus to be demonstrated whether further improvements of air quality also translate in further health benefits. Third, to take efficient air pollution control measures, a better understanding about the exposure-response relationship for different pollutants is needed.
In this project, we will apply several exposure models for PM10, PM2.5, NO2, BC, and O3 with high spatial and temporal resolution to health outcomes from the Swiss population-based cohorts SAPALDIA and Swiss National Cohort (SNC). We will investigate the acute and long-term associations of exposure estimated from different models with lung function and blood pressure in the SAPALDIA cohort and with overall and cause-specific mortality in the SNC cohort. We aim to quantify the influence of different exposure models and pollutants on the estimated exposure-morbidity/mortality associations and the uncertainty in these associations. In addition, there will be another measurement round to complete longitudinal lung function and blood pressure data in the SAPALDIA cohort to be able to assess the lung function effects at the current and low levels of air pollution.