Assessment of long-term exposure to airborne pollution in France (1990-2010)
Résumé
Background: Long-term exposure to air pollution has been consistently associated with adverse health effects and reduced life expectancy. Air pollution is a mixture of multiple pollutants originating from a large variety of sources and includes various substances classified as carcinogenic or probably carcinogenic to humans. Identifying the long-term effects of these airborne pollutants requires the computation of the spatio-temporal variability of concentration to estimate the exposure of the population. Aim : To provide an accurate assessment of long-term air pollution exposure (including airborne PM10, PM2.5, NO2, O3, BaP, PCB, PCDD/F and cadmium (cd) exposure in the whole France and in a case-control study nested in the French national prospective women’s cohort (E3N). Methods: Hourly airborne pollutant concentrations over the study period (1990-2010) were computed using a chemistry- transport model (CHIMERE) with a spatial resolution of 7x7km2. Cohort’s subjects were manually geocoded and annual concentrations were attributed to each subject’s address (n=19669). Results: Simulation scenarios of air pollutant concentrations show the variability of the pollutant sources over time with general decreasing levels of pollutant concentrations in air. At the E3N subject’s address, we observed a decline of concentration for all pollutants (PM10:-41%; PM2.5:-45%; NO2:-34%; PCB:-74%; PCDD/F:-87%, Cd:-68%; BaP:-45%) except for O3 (-0.04%). The percentage of subject exposed to an annual concentration exceeding WHO recommendation (PM10: 20 μg/m3; PM2.5: 10 μg/m3) decrease form 74% to 8% for PM10 and from 99% to 64% for PM2.5. We also observed strong territorial inequalities with differences in atmospheric concentrations that could be greater than a factor of five between regions. Conclusions: Findings from this study will be essential to increase the accuracy of the assessment of long-term airborne pollution exposure and will improve the results of epidemiological studies. The spatial resolution of concentrations will be improved by using complementary models such as land use regression.