Abstract
Current air pollution exposure assessments often underestimate exposure to air
pollutants by neglecting two key factors: population mobility and the infiltration of
outdoor pollutants into indoor environments. These oversights introduce bias,
leading to non-representative exposure estimates and subsequent estimation of
health effects.
In this seminar, an overview of an dynamic exposure estimation approach designed
to address these challenges is introduced. By integrating population activity and
pollutant infiltration, this approach offers a more accurate assessment of exposure
from urban to regional scales. Comparing this dynamic modeling approach to
traditional static methods reveals substantial differences, particularly for pollutants
like PM2.5, NO2, and O3. The findings demonstrate the potential underestimation of
exposure and health impacts in conventional assessments, highlighting the
importance of incorporating dynamic elements to better support public health
policies.
