Keywords
impact assessment, human health, ecosystem health, data integration
Start Date
1-7-2012 12:00 AM
Abstract
High ambient concentrations of air pollutants, such as particulate matter (PM10, PM2.5),nitrogen oxides (NOx) or ground-level ozone, occur in densely populated areas and thus have thepotential for serious adverse human health effects. While statutory requirements for air qualitymonitoring due to national or European legislation defines the need for the operation of monitoringstations in particular in the densely populated urban areas, the spatial distribution of those sites isoften not sufficient to adequately assess exposure to air pollutants for the whole population. Theassessment of exposure to one or several air pollutants in an integrated manner has been describedin Reis et al. (2005) for the European scale, however, the availability of high resolution data forScotland allows for a more detailed assessment, in particular with regard to the socio-economiccontext.Atmospheric chemistry transport models (in short ACTMs) are useful tools to determine air qualityacross a wide range of spatial scales, from regional to local, with the availability of highly resolved(spatially as well as temporally) datasets to drive these models being a prerequisite. In this paper wediscuss approaches for the integration of different datasets, such as stationary air quality monitoringdata with ACTM model results (using the EMEP4UK model, Vieno et al., 2010), to estimate exposureof the Scottish population to ambient air pollutant concentrations. In addition, contextual information(e.g. a spatial representation of the Scottish Index of Multiple Deprivation, SIMD) and the latest landuse data from the recently released CEH Land Cover Map 2007 allow us to derive enhanced,integrated data products for the quantitative assessment of human health effects. Finally, the paperdiscusses how the conceptual framework of a full-chain approach may be compromised by dataavailability and how impact assessments for human health and ecosystem health may be betterintegrated to improve the evidence base for policy action.
Methods for the assessment of human health impacts from air pollution based on monitoring data, atmospheric dispersion model results and contextual data in Scotland
High ambient concentrations of air pollutants, such as particulate matter (PM10, PM2.5),nitrogen oxides (NOx) or ground-level ozone, occur in densely populated areas and thus have thepotential for serious adverse human health effects. While statutory requirements for air qualitymonitoring due to national or European legislation defines the need for the operation of monitoringstations in particular in the densely populated urban areas, the spatial distribution of those sites isoften not sufficient to adequately assess exposure to air pollutants for the whole population. Theassessment of exposure to one or several air pollutants in an integrated manner has been describedin Reis et al. (2005) for the European scale, however, the availability of high resolution data forScotland allows for a more detailed assessment, in particular with regard to the socio-economiccontext.Atmospheric chemistry transport models (in short ACTMs) are useful tools to determine air qualityacross a wide range of spatial scales, from regional to local, with the availability of highly resolved(spatially as well as temporally) datasets to drive these models being a prerequisite. In this paper wediscuss approaches for the integration of different datasets, such as stationary air quality monitoringdata with ACTM model results (using the EMEP4UK model, Vieno et al., 2010), to estimate exposureof the Scottish population to ambient air pollutant concentrations. In addition, contextual information(e.g. a spatial representation of the Scottish Index of Multiple Deprivation, SIMD) and the latest landuse data from the recently released CEH Land Cover Map 2007 allow us to derive enhanced,integrated data products for the quantitative assessment of human health effects. Finally, the paperdiscusses how the conceptual framework of a full-chain approach may be compromised by dataavailability and how impact assessments for human health and ecosystem health may be betterintegrated to improve the evidence base for policy action.
