A dynamic urban air pollution population exposure assessment study using model and population density data derived by mobile phone traffic. (April 2016) - Gariazzo, Claudio; Pelliccioni, Armando; Bolignano, Andrea
Abstract: A dynamic city-wide air pollution exposure assessment study has been carried out for the urban population of Rome, Italy, by using time resolved population distribution maps, derived by mobile phone traffic data, and modelled air pollutants (NO2, O3 and PM2.5 ) concentrations obtained by an integrated air dispersion modelling system. More than a million of persons were tracked during two months (March and April 2015) for their position within the city and its surroundings areas, with a time resolution of 15 min and mapped over an irregular grid system with a minimum resolution of 0.26 × 0.34 Km 2 . In addition, demographics information (as gender and age ranges) were available in a separated dataset not connected with the total population one. Such BigData were matched in time and space with air pollution model results and then used to produce hourly and daily resolved cumulative population exposures during the studied period. A significant mobility of population was identified with higher population densities in downtown areas during daytime increasing of up to 1000 people/Km 2 with respect to nigh-time one, likely produced by commuters, tourists and working age population. Strong variability (up to ±50% for NO2 ) of population exposures were detected as an effect of both mobility and time/spatial changing in pollutants concentrations. A comparison with the correspondent stationary approach based on National Census data, allows detecting the inability of latter in estimating the actual variability of population exposure. Significant underestimations of the amount of population exposed to daily PM2.5 WHO guideline was identified for the Census approach. Very small differences (up to a few μg/m 3 ) on exposure were detected for gender and age ranges population classes. Graphical abstract: Highlights: Mobile Phone traffic data can be used to track urban population. Dynamic urban population density maps indicate large mobility. Large variations of population exposure are detected. Small differences on exposure are estimated for different genders and age ranges. Assessment of population exposure based on residence is unable to estimate the actual variability of exposure.