Open AccessFitting Statistical Distribution on Air Pollution: an Overview
Author(s) -
M. Jaffar,
Haslinda Abdul Hamid,
Riduan Yunus,
Ahmad Fauzi Raffee
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.23.17256
Subject(s) - weibull distribution , air pollution , air quality index , log normal distribution , environmental science , pollution , pollutant , air pollution index , event (particle physics) , air pollutant concentrations , statistical model , air pollutants , meteorology , computer science , econometrics , statistics , mathematics , geography , ecology , chemistry , physics , organic chemistry , quantum mechanics , biology
High event of air pollution would give adverse effect to human health and cause of instability towards environment. In order to overcome these issues, the statistical air pollution modelling is an important tool to predict the return period of high event on air pollution in future. This tool also will be useful to help the related government agencies for providing a better air quality management and it can provide significantly when air quality data been analyze appropriately. In fitting air pollutant data, statistical distribution of gamma, lognormal and Weibull distribution is widely used compared to others distributions model. In addition, the aims of this overview study are to identify which distributions is the most used for predicting the air pollution concentration thus, the accuracy for prediction future air quality is the important aspect to give the best prediction. The comprehensive study need to be conducted in statistical distribution of air pollution for fitting pollutant data. By using others statistical distributions model as main suggested in this paper.