Volume 49, No. 3, August 2015

Volume 49, No. 3, August 2015

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 Technical Articles

Ancelet, T., Davy, P. K. and Trompetter, W. J.
Hourly variations in particulate matter source contributions in New Zealand’s southernmost city.

Size-resolved (PM2.5 and PM10–2.5) particulate matter samples were collected on an hourly time-scale during the 2014 winter in Invercargill, New Zealand. The hourly samples collected were analyzed for elemental concentrations using ion beam analysis techniques and for black carbon using light reflection. Positive matrix factorization (PMF) was used to identify PM10 sources and their contributions. PMF analysis identified five PM10 sources that accounted for 84 % of the measured PM10 mass. The sources identified were: biomass combustion (68 % of PM10), motor vehicles (10 % of PM10), crustal matter (1 % of PM10), and coarse and fine marine aerosol (21 % of PM10 combined). The biomass combustion source showed a similar diurnal profile to that of PM10 and indicated that residents were re-lighting their fires in the morning, as opposed to the morning peak in PM10 concentrations being related to rush hour traffic. The results of this study provide important information for the management of air quality in Invercargill and highlight the need for a longer-term monitoring campaign could provide useful information about source activity outside of winter. It is possible that with a longer-term study, new sources may be identified that could lead to a greater understanding  of the sources and factors that contribute to PM pollution in Invercargill.

 Brisbane tunnel study to assess the accuracy of Australian motor vehicle emission models and examine the main factors affecting prediction errors.

Smit, R., Kingston, P., Tooker, R., Neale, D., Torr, S., Harper, R., O’Brien,
E., Harvest, D. and Wainwright, D. A
Statistical analysis has been applied to vehicle emissions data collected in a recent Brisbane tunnel study with the aim being to validate newly developed Australian vehicle emission models and examine which factors are the main contributors to prediction errors. The results suggest that the COPERT Australia vehicle emission model is generally accurate at the fleet level, when compared with similar international studies, but underestimates emissions by 2 to 36%, depending on the pollutant. These findings apply only to the specific measurement conditions in the tunnel (high speed, free- flow). Regression analysis revealed that light and heavy diesel vehicles are consistently and strongly associated with prediction errors across all pollutants. Whereas fleet level prediction of PM emissions by COPERT is good, a substantial under-prediction of PM emissions from diesel trucks is suggested by the statistical analysis. For NOx, the analysis suggests that modern large petrol passenger vehicles (e.g. SUVs) play an important role in the under-estimation of emissions. This indicates that further targeted emissions testing for these vehicles using e.g. PEMS would benefit vehicle emission modelling practice and air quality assessments in Australia. Other tunnel datasets in other cities, preferably of longer duration than a week, could be analysed in a similar fashion to see if these results are confirmed.


  • Australia New Zealand Aerosol Assembly Workshop Report – Howard Bridgman
  • Conference report 9th Asian Aerosol Conference, Kanazawa, Japan – Howard Bridgman