The Chemical Mass Balance (CMB) receptor model of the US-EPA was applied to PM10 data obtained during a field study performed in the Milan urban area, including daily average concentrations, element and ion concentrations. Two chemical fingerprints were estimated to characterise total traffic emissions and diesel engine exhaust emissions. Four main source groups were identified: road traffic, with a 56% contribution, secondary particulate with 26%, soil dust (15%), and industrial emissions (3%). A more detailed treatment of the traffic source showed the important contributions of diesel exhaust and tyre and brake wear to ambient PM10 concentrations. The influence of meteorology on source apportionment was also studied by analysing the effects of rainfall of different intensities, and those of wind speed.
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Mossetti et al. (2005) studied this question.
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