Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.
Summary (1 min read)
Summary
- 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 selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10).
- The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries.
- The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time.
- The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities.
- The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA.
- This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.
Did you find this useful? Give us your feedback
Citations
146 citations
Cites background or methods or result from "Spatial and temporal air quality pa..."
...Previous studies done by Mutalib et al. (2013), Alkasassbeh et al. (2013), Brunelli et al. (2007), Tecer (2007), Perez and Reyes (2006), and Niska et al. (2004, 2005) prove that ANN is very well suited for solving environmental problems, especially in the analysis of air pollution....
[...]
...Once the lack of compliance is determined, the data can be used to advise or caution the decision makers or planners to avoid health effects (Kamal et al. 2006; Mutalib et al. 2013)....
[...]
...Two major air pollutants are PM10 and O3, particularly in the urban and suburban areas in Malaysia (Dominick et al. 2012; Latif et al. 2012; Mutalib et al. 2013), and have been recognized as two of the major concerns that have high potential for deleterious effects on health (Mahiyudin et al. 2013;…...
[...]
...…maintain air quality and protect public health, the Malaysian Department of Environment (DOE) has set up the API and established national air quality standards through the Recommended Malaysian Air Quality Guidelines (RMAQG) for each of these pollutants (Mutalib et al. 2013; Dominick et al. 2012)....
[...]
...The applications of different environmetric techniques such as cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), and discriminant analysis (DA) have been extensively applied in many scientific studies over the last few years (Mutalib et al. 2013; Singh et al. 2004, 2005), especially in air quality monitoring....
[...]
67 citations
54 citations
Cites background from "Spatial and temporal air quality pa..."
...However, the complex and non-linear behaviors of air quality variables are beyond the capabilities of a simple mathematical prediction formula [10]....
[...]
...Several air quality studies [10,22] have utilized ANN to simulate PM10 concentrations, air quality prediction, and other environmental issues....
[...]
48 citations
32 citations
Cites background from "Spatial and temporal air quality pa..."
...However, the highest values of R2 (which was near to 1) will be declared as the best linear model (Norusis 1990; Mutalib et al., 2013; Azid et al., 2013, 2014a)....
[...]
References
1,481 citations
1,429 citations
1,136 citations
839 citations
678 citations