Application of GIS in modelling real time population exposure to PM2.5

Abstract

Air pollution has caused many deaths globally across all age groups with most of the deaths attributed to PM2.5 which is an extremely small sized particulate matter that can travels deep in to the lungs, hit the blood stream and affect the respiratory track. This study has estimated Southampton spatiotemporal population exposure to air pollution using the Surface builder (SB) 24/7 model and a modelled air pollution data from DEFRA with a specific focus on the variation in the level of exposure to PM 2.5 by different population age groups, using GIS. After modeling the population exposure the resulted map was resampled to 200m by 200m to match the spatial resolution of the output population distribution model. The result shows that only few areas around the southern parts of the study areas (mostly residential areas with low commercial activities) have low concentration of PM2.5 pollutant. The results further identified a significant variation in the level of exposure by different population age groups with the population age group between the age of 18 to 64 (non-students) having the highest level of exposure at both 2am (55% of the exposed population) and 2pm (52%). On the other hand, the age group with the lowest level of exposure (2%), at both times of the day, is 16 to 17 years of age. 18 to 64 years old students in higher education (HE) and people of over 65 years of age are second subgroups highly exposed while the remaining age groups (0 to 4, 5 to 9, 10 to 15) show almost similar exposure (5 to 6%) in both times of the day. Overall, there is an incredible difference in exposure to PM2.5 by different age groups which reflects the level of spatial interaction by each age group.