Abstract: Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM2.5, while the AERMOD dispersion model has been used to account for missing sources of PM2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.
Abstract: The Greater Athens Area (GAA) faces photochemical
and particulate pollution episodes as a result of the combined effects
of local pollutant emissions, regional pollution transport, synoptic
circulation and topographic characteristics. The area has undergone
significant changes since the Athens 2004 Olympic Games because
of large scale infrastructure works that lead to the shift of population
to areas previously characterized as rural, the increase of the traffic
fleet and the operation of highways. However, few recent modelling
studies have been performed due to the lack of an accurate, updated
emission inventory. The photochemical modelling system
MM5/CAMx was applied in order to study the photochemical and
particulate pollution characteristics above the GAA for two distinct
ten-day periods in the summer of 2006 and 2010, where air pollution
episodes occurred. A new updated emission inventory was used
based on official data. Comparison of modeled results with
measurements revealed the importance and accuracy of the new
Athens emission inventory as compared to previous modeling
studies. The model managed to reproduce the local meteorological
conditions, the daily ozone and particulates fluctuations at different
locations across the GAA. Higher ozone levels were found at
suburban and rural areas as well as over the sea at the south of the
basin. Concerning PM10, high concentrations were computed at the
city centre and the southeastern suburbs in agreement with measured
data. Source apportionment analysis showed that different sources
contribute to the ozone levels, the local sources (traffic, port
activities) affecting its formation.