Space-time exposure modelling of troposheric O3 in Europe
Author(s)
Al-Aidarous, Fatima
Type
Thesis
Abstract
Exposure models need to be developed which can be applied at the continental scale, while still reflecting local variations in exposure conditions. Land use regression (LUR) has been widely adopted to describe the spatial variations in air pollutants over the longer term but not for short-term time-variable exposures. This study, therefore, aimed to develop and validate a space-time O3 model applicable to epidemiological studies investigating the health effects of short-term (e.g. daily) O3 exposures at the small-area scale.
A geographical information system (GIS) was developed, incorporating data from 1211 O3 monitoring sites across Western Europe and a range of predictors, stored as 100m grids, including land cover, roads, topography and meteorology. The spatial model consisted of a LUR model representing the long-term average for years 2001-2007. The monitoring sites were classified, using multivariate statistical techniques, into 13 site types based on a set of descriptive indicators, then 13 temporal models represented by time functions were produced – one for each site type. These were linked to the spatial model using probability of group membership as a weighting factor. Finally, local meteorological data were incorporated to produce the full space-time model to predict daily concentrations for point locations.
The spatial and temporal models were individually evaluated based on agreement with measurement data from a reserved subset of 20% of the monitoring sites. The performance of the spatial model was similar to other continental LUR models (R2=0.67; RMSE=7.64 μg/m3), while performance of the temporal models ranged from 0.3 to 0.5 (R2). Including local meteorological data into the full spatial-temporal model improved correlation with the concentrations measured at 30 monitoring sites in the Netherlands (R2= 0.42 without; R2=0.53 with meteorology).
Modelling daily O3 over large areas at a fine spatial scale is possible using this approach. Overall model performance was further improved as the temporal period was aggregated to weekly or monthly. The model was applied to mothers in two birth cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE) to provide daily O3 exposure estimates, which can be aggregated as needed to provide individualised exposures based on date of birth.
A geographical information system (GIS) was developed, incorporating data from 1211 O3 monitoring sites across Western Europe and a range of predictors, stored as 100m grids, including land cover, roads, topography and meteorology. The spatial model consisted of a LUR model representing the long-term average for years 2001-2007. The monitoring sites were classified, using multivariate statistical techniques, into 13 site types based on a set of descriptive indicators, then 13 temporal models represented by time functions were produced – one for each site type. These were linked to the spatial model using probability of group membership as a weighting factor. Finally, local meteorological data were incorporated to produce the full space-time model to predict daily concentrations for point locations.
The spatial and temporal models were individually evaluated based on agreement with measurement data from a reserved subset of 20% of the monitoring sites. The performance of the spatial model was similar to other continental LUR models (R2=0.67; RMSE=7.64 μg/m3), while performance of the temporal models ranged from 0.3 to 0.5 (R2). Including local meteorological data into the full spatial-temporal model improved correlation with the concentrations measured at 30 monitoring sites in the Netherlands (R2= 0.42 without; R2=0.53 with meteorology).
Modelling daily O3 over large areas at a fine spatial scale is possible using this approach. Overall model performance was further improved as the temporal period was aggregated to weekly or monthly. The model was applied to mothers in two birth cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE) to provide daily O3 exposure estimates, which can be aggregated as needed to provide individualised exposures based on date of birth.
Date Issued
2013
Date Awarded
2013-05
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Vienneau, Danielle
Briggs, David
Publisher Department
Public Health
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)