Spatial modelling of population at risk and PM2.5 exposure index: A case study of Nigeria

Abstract

Particulate matter is a primary air pollutant, widely reported as important for public health especially for respiratory problems. However, monitoring, spatial representation and development of associated risk indicators have been major problems undermining formulation of relevant policy on air quality. This study used remotely sensed PM data complemented with population data to quantify population at risk and develop an Exposure Index (EI). Population at risk was computed from the population density data using the percentage contribution of two different ages groups (ages of 0-19 and 65+) and intersecting this with the PM concentration classes. EI is the sum product of the air quality measure and the population of vulnerable group per unit area. Almost the entire study area has PM2.5 concentration above the WHO guideline. Change in PM2.5 concentration showed that, around 54% of the study area remains the same, 43% improved and the remaining areas showed reduction. Between 77million and 81million of young vulnerable people were at risk over the period and about 4million elders were at risk. EI ranges between 1.5 x 10-4 and 8.3 x 10-2 per capita in 2001 and 1.9 x 10-4 and 1.5 x 10-1 per capita in 2010. This situation presents an environmental health burden in relation to potential risk of continuous exposure to dangerous levels of PM2.5. This information is necessary for rapid assessment of environmental health risk. However, research on the computation and exploration of other risk measures such as relative and attributable risks would further enhance policy making in relation to environmental health.

Key Words: Population at risk, PM2.5; Spatial modeling, GIS, Exposure index, environmental health