Open Access
Spatial Assessment of Air Pollution Index Using EnvironmetricModeling Techniques
TLDR
In this article, the authors investigated the spatial variation in the source of air pollution; identify the most significant parameters contributing to the air pollution and to develop the best receptor model for predicting air pollution index (API).Abstract:
The quest for industrial and urban development over the years has changed the pattern and source of atmospheric air pollution in Malaysia. This study aims to investigate the spatial variation in the source of air pollution; identify the most significant parameterscontributing to the air pollution and to develop the best receptor model for predicting air pollution index (API). Data from five monitoring stations base on five year's observation (2007-2011) were used. Multivariate techniques such as cluster analysis (HACA), discriminate analysis (DA), principal component analysis (PCA), factor analysis (FA) and modeling techniques comprising of artificial neural network (ANN) and multiple linear regression (MLR) were used in this study. HACA was able to group the five monitoring stations into three clusters, indicating that one station in each cluster can provide a reasonable accurate spatial assessment of air quality within the study area. The result for standard mode, forward stepwise and backward stepwise DA gave a correct assignation of 82.37% (p˂ 0.05) which indicate that all the parameters significantly discriminate spatially. PCA and FA for the three clusters account for more than 62%, 56% and 58% of the total variance respectively indicating that the source of air pollution are from anthropogenic induced point source and nonpoint source. ANN gave a better prediction at Rread more
Citations
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Water quality modelling using artificial neural network and multivariate statistical techniques
TL;DR: In this article, the authors investigated and proposed a reduction in the number of water quality monitoring stations, parameters and developed the best input combination for water quality modelling using artificial neural network and multivariate statistical technique.
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Building-specific factors affecting indoor radon concentration variations in different regions in Bulgaria
TL;DR: In this paper, a survey of indoor radon concentration in 174 kindergartens of three Bulgarian cities was carried out in 777 ground floor rooms using alpha tract detectors, exposed for 3 months in cold period of 2014.
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Modeling the spatio-temporal dynamics of air pollution index based on spatial Markov chain model
TL;DR: This study aims to explore the potential impact of spatial dependence over time and space on the distribution of air pollution based on the spatial Markov chain (SMC) model using the longitudinal air pollution index (API) data.
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Application of chemometrics techniques to solve environmental issues in Malaysia.
Nur Zahidah Shafii,Ahmad Shakir Mohd Saudi,Jyh Chyang Pang,Izuddin Fahmy Abu,Norzahir Sapawe,Mohd Khairul Amri Kamarudin,Hammad Farhi Mohd Saudi +6 more
TL;DR: A comprehensive review of relevant scientific journals concerning on the major environmental issues in Malaysia, published between 2013 and 2017, suggested that chemometrics techniques have a greater accuracy, flexibility and efficiency to be applied in environmental modelling.
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Chemometric approach in environmental pollution analysis: A critical review.
Abel Inobeme,Vanya Nayak,T. J. Mathew,S. E Okonkwo,Lucky Ekwoba,A. I. Ajai,Esther Bernard,J Inobeme,M. Mariam Agbugui,Kshitij Rb Singh +9 more
TL;DR: In this paper , a review of the use of chemometrics in environmental pollution analysis is presented, highlighting its types, applications, advantages, and limitations in the environmental domain, as well as future trends in future applications.
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