Monday, 14 January 2002: 3:45 PM
Real-time Winter Dispersion Modelling Based on PM2.5 Mass for the Greater Montreal Area in Canada.
Montreal is the second largest city in Canada with 1.8 millions people located in St-Lawrence River valley. Since the 1998 winter major ice storm, when thousands of homes were deprived of electricity for two weeks or more, many people have installed woodburning appliances and other alternative sources of heating. Since then, during wintertime, woodburning is a growing source of air pollution and health risks on the island of Montreal. In order to assess these issues, Environment Canada, Montreal Public Health Department and Montreal Urban Community have conducted a field measurement study during the 98-99 and 99-00 winters in a residential area in the east-end of the Island of Montreal. Data clearly identified wood combustion as a major source of diverse pollutants and fine suspended particles with a diameter less than 2.5 mm. Under certain meteorological conditions, the lower layers of the atmosphere act like a lid that forces pollutants and fine suspended particles from various sources to remain close to the ground and contributes to the decline in air quality. In order to reduce the air pollution impacts caused by PM2.5 a dispersion forecast program has been put in place to predict these unfavorable atmospheric conditions ahead of time and thus encourage people to reduce or to avoid their emissions. The program encourages homeowners to refrain from using fireplaces or wood-stoves when "poor winter dispersion" advisories are in effect. To develop a mesoscale dispersion model, PM2.5 have been linked with meteorological parameters such as surface and upper level wind speed, vertical stability, mixing height, surface temperature, precipitation, heating degree-days, day of the week, and many others. All meteorological parameters come from the Canadian Global Environmental Multiscale model (GEM) and they are used as trial field to the dispersion model. A Multiple Discriminant Analysis has been used to classify air quality forecast into three categories : Good, Fair and Poor. The predicton performance are respectively : Good 89.4%, Fair 46.3% and Poor 88.5% (p < 0.05). The dispersion forecasts are done daily by meteorologists of the Montreal Weather Services Office. Meteorologists used their expertise to improve the accuracy of the model, especially surface wind speed when necessary. Program results from winter 2000 (n=108 days) show overall performance of 77%. Field study and the dispersion model will be presented in details with a complete evaluation of the dispersion program as well as the future. Such dispersion model will be eventually implemented throughout Canada in the near future.