| The forecast of PM10 pollution in Xi'an city had been studied according to the concentration value that monitored from 2001 to 2004 in heating season and the ground meteorological data from 2001 to 2004 in heating season of Xi'an city.When the air pollution index(API)>150, air quality belongs to low-grade and upwards, it will bring adverse impact to physical healthy. In the dissertation, statistical analysis had been done for the polluted days'(API>150) meteorological data in term of season, and compared with the distribution of none-polluted days'meteorological data. On the basis of contrast, confirm possible meteorological condition that can arise polluted day in different seasons.There is a close correlativity between PM10 concentration and meteorological condition, so one-member statistical method had been used to analyst the correlation between them according to season. From this, meteorological factors can been found which has distionct impact for the PM10 pollution, which become a gist to choice forecast gene in the study of forecast model.After contrasted many forecast method, the dissertation choose main element analysis methods in the excessive-member statistical method to build foreast model in the heating season, moreover compared the veracity and applicability of different model, and selected standard-stepwise regression analysis finally. In order to eliminate the total line, Matlap 6.5 the langrage of technical computing had been used. Through checkout in 485 days, veracity of model achieved 80.2%.
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