Abstract
ISEE-590 Objective: The UK has a long-running set of national air pollution data with over 3100 monitoring stations in existence at various points from 1955. This project aims to construct a detailed time series database of modeled concentrations of Black Smoke (BS) and SO2 for UK that can be applied to existing British cohort studies. This offers a unique opportunity to investigate health effects of lifecourse air pollution exposures. Materials and Methods: Different methods for modeling concentration surfaces are in development including Kriging, regression mapping, and dispersion modeling. The initial steps reported here are Ordinary Kriging of monitored annual BS concentrations for sample years (1962, 1971, 1981, and 1991), including data from stations with concentrations available for ≥75% of days in the year. Supplementary datasets for possible inclusion in regression and dispersion modeling have also been identified. Results: Kriging models were developed using 75% of the data with remaining data reserved for validation. Models worked well for 1962 and 1971 (r2=0.6 and 0.6, RMSE 49.3 and 18.8) but were less good for later years (r2=0.5 and 0.4, RMSE 7.8 and 6.6) when monitoring station numbers fell from around 1000 to less than 200. Highest concentrations were consistently observed in northern England (Liverpool, Manchester, and Tyneside), with lowest values in Scotland and the South-West. BS concentrations declined markedly over time with 90th percentile values falling from 270 μg/m3 in 1962 to 25 μg/m3 in 1991. Additional historical datasets identified for use in other modeling techniques included population density, land use, emissions inventories, gas networks, smoke control areas (relating to domestic fuel use), and the railway network. Conclusions: Kriging provides reasonable baseline maps against which more sophisticated modeling techniques can be compared. A range of datasets including air pollution concentrations are available to aid modeling of historical exposures to air pollution in UK.
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