چکیده مقاله
Air pollution is known as a major cause of health and environment damages Various factors are involved in increasing air pollution, among which road trafficis one of the main sources of these issues Therefore, in this study, the effects oftraffic flow and metrological parameters on the PM10 and PM2 5 levels areinvestigated by a predictive model Time series analysis is used to predict futuredaily levels of PM10 and PM 2 5 in Mashhad, based on predicted daily traffic flowon the major highways of Mashhad, temperature, wind speed and humidity Themajor innovation of this paper is that the air pollution time series is modeledbased on another time series traffic volume In other words, the time seriesmodel for air pollution contains some time series variables as exogenousvariables These time series variables have some effects on each other, which areconsidered by Cross Correlation Function CCF For each variable,Autocorrelation Function ACF and Partial Autocorrelation Function PACF are calculated ACF defines the seasonal patterns of the observations, and PACFremoves dependence of internal lags for each variable A predictive SARIMAmodel, which estimates the future levels of PM10 and PM 2 5 is a result of thisstudy The R Square of the proposed model is 0 714 and 0 676; and RSME of itis 8 667 and 9 374 for PM10 and PM 2 5; respectively
کلیدواژهها
نویسندگان
Ramin Khavarzadeh
PhD Candidate, Department of Statistics, Mathematical Faculty, Tarbiat Modares University
Navid Kalantari
Avand e Tarh o Andisheh Consulting Engineers, Tehran, Iran
Neda Alirezaei
Shahid Beheshti University, Tehran, Iran
شیوه ارجاع
Khavarzadeh, Ramin and Kalantari, Navid and Alirezaei, Neda,1394,A Predictive SARIMA Model for PM10 and PM2.5 levels in Mashhad based on traffic flow and metrological data,The 14th International Conference on Traffic and Transportation Engineering,Tehran
ارائهشده در
مجموعه مقالات چهاردهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک5 اسفند 1393 · تهران