کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4444439 1311240 2006 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Statistical models for the prediction of respirable suspended particulate matter in urban cities
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
پیش نمایش صفحه اول مقاله
Statistical models for the prediction of respirable suspended particulate matter in urban cities
چکیده انگلیسی

Particulate matters (PM) constitute a major concern for air quality of metropolitan cities. In this paper, the problem of air quality forecasting of respirable suspended particulate matter (RSPM) based on some meteorological factors has been discussed. The present work deals with the application of three statistical models to forecast daily averaged concentration of RSPM in urban Delhi and Hong Kong. Model 1 is based on multiple linear regression of meteorological parameters, model 2 is based on Box-Jenkins time series auto regressive integrated moving average (ARIMA) model and model 3 is a combination of the two. A detailed analysis of results of above models shows that the combination of ARIMA and multiple regression (model 3) gives better results in comparison to the other two models with respect to observed data. Thus the model 3 has been used, in the present study, to forecast the air quality of Delhi and Hong Kong with respect to RSPM. It has been concluded that the same model may be used as a practical prognostic model for prediction of RSPM in urban cities.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Environment - Volume 40, Issue 11, April 2006, Pages 2068–2077
نویسندگان
, , ,