air pollution is a challenging issue in some of the large cities in developing countries. air quality monitoring and interpretation of data are two important factors for air quality management in urban areas. several methods exist to analyze air quality. among them, we applied the dynamic neural network (tdnn) and radial basis function (rbf) methods to predict the concentrations of ground-level...

According to the Air Quality Framework Directive, air pollutant concentration levels have to be assessed and reported annually by each European Union member state, taking into consideration European air quality standards. Plans and programmes should be implemented in zones and agglomerations where pollutant concentrations exceed the limit and target values. The main objective of this study is t...

BACKGROUND Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollut...

the state of works of art exhibited inside museums can be strongly influenced by indoor air quality, due to chemical activity of gaseous pollutants and particulate matter. for that reason it is important to carry out periodic air quality controls to check if the concentration levels of air pollutants comply with the limits specified by the national laws. in this work we show results obtained i...

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selec...

Background: Air pollution and concerns about health impacts have been raised in metropolitan cities like Tehran. Trend and prediction of air pollutants can show the effectiveness of strategies for the management and control of air pollution. Artificial neural network (ANN) technique is widely used as a reliable method for modeling of air pollutants in urban areas. Therefore, the aim of current ...

In this paper we will show how Global Positioning Services (GPS) data obtained from smartphones can be used to model air quality in urban settings. The paper examines the uncertainty of smartphone location utilising GPS, and ties this location uncertainty to air quality models. The results presented in this paper indicates that the location error from using smartphones is within the accuracy ne...