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Abstract: The aim of this study is to investigate the effects of specific emission control measures on the air quality of urban centres and local area hotspots. In order to achieve this, a sequence of regional, urban and local scale models was applied to assess the impact of European emission control strategies on urban and local scale air quality. First, vehicle fleet and activity data were estimated using appropriate models. The results of these models were used as input to the COPERT model in order to estimate vehicle emissions (NO2 and PM10) at country level up to the year 2030. Vehicle emissions were calculated according to two different scenarios: A baseline scenario, CLE (Current LEgislation) and an optimistic alternative, MFR (Maximum Feasible Reductions). Urban background and traffic hotspot concentrations of air pollutants were then calculated using the OFIS (Ozone FIne Structure) and OSPM (Operational Street Pollution Model) models respectively for 20 cities in Europe and for particular types of streets. Air quality was found to improve in 2030 compared to the reference year 2000, in line with the stricter NOx and PM vehicle emission limits imposed. The NO2 street increments for narrow canyons estimated for the reference year were found to be in the range of 16–53 μg m−3, depending on the city considered. These were reduced to 14–36 μg m−3 in the CLE scenario and 7–24 μg m−3 in the MFR scenario. The corresponding range for PM10 was estimated to be 5–15 μg m−3 for the reference year and was reduced to 2–8 μg m−3 and 0.2–2.4 μg m−3 for the CLE and the MFR scenarios respectively. [Copyright &y& Elsevier]

Abstract: Estimates of population exposure to air pollution on the European scale are required for policy development and health impact assessment. Long term exposure estimates of this type can be made using spatially distributed air quality and population density data. Gridded chemical transport models (CTMs) are often used for this purpose, however the grid resolution of CTMs that cover entire continents is usually limited to 25–100 km and there may be a significant level of unresolved variability within the grids that will impact on the exposure estimates. In this paper sub-grid variability and its impact on long term exposure estimates is assessed by investigating the covariance of concentration and population, which is shown to be the defining term in estimating the average sub-grid population exposure. A parameterisation of the sub-grid covariance is described, based on the sub-grid covariance of other proxy data, and this is applied using EMEP model results for all of Europe. The study shows that the error made in the exposure calculations for all of Europe is significant for the typical CTM resolution of 50 km. The error is largest for NO2, where the average European urban background exposure using CTMs is underestimated by 44 ± 4%. Particulate matter with a diameter less than 10 μm (PM10) is also underestimated, but only by 15 ± 4%. Calculation of the sub-grid covariance for the ozone health indicator SOMO35 (Sum of Ozone 8 h running Means Over 35 ppb) was not carried out for all of Europe as the sub-grid parameterisation was considered too uncertain for useful application. However, estimates based on observations alone show that population weighted SOMO35 concentrations are overestimated by around 13% when using model grid resolutions of 50 km. [Copyright &y& Elsevier]