%0 book part
%@ 
%A Ramacher, M.O.P.,Matthias, V.,Badeke, R.,Petrik, R.,Quante, M.,Arndt, J.,Fink, L.,Feldner, J.,Schwarzkopf, D.,Link, E.M.,Wedemann, R.

%D 2023
%J Air Pollution Modeling and its Application XXVIII. ITM 2021
%N 
%P 319-327 
%R doi:10.1007/978-3-031-12786-1_43
%T Urban Population Exposure to Air Pollution Under COVID-19 Lockdown Conditions - Combined Effects of Emissions and Population Activity
%U https://doi.org/10.1007/978-3-031-12786-1_43
 
%X The aim of this study is to quantify the BIAS in air pollution (PM2.5, NO2) exposure estimates that arise from neglecting population activity under COVID-19 lockdown conditions. We applied mobility data as derived from different sources (Google, Eurostat, Automatic Identification System, etc.) to model the impact of (1) changing emissions and (2) the change in population activity patterns in a European multi-city (Hamburg, Liège, Marseille) exposure study. Our results show significant underestimations of exposure estimates when activity profiles are either neglected or not adjusted for lockdown conditions.