Forecasting of Air Quality Index in Delhi Using Neural Network Based on Principal Component Analysis
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ure and Applied Geophysics
Forecasting of Air Quality Index in Delhi Using Neural Network Based on Principal Component Analysis ANIKENDER KUMAR1 and P. GOYAL1 Abstract—Forecasting of the air quality index (AQI) is one of the topics of air quality research today as it is useful to assess the effects of air pollutants on human health in urban areas. It has been learned in the last decade that airborne pollution has been a serious and will be a major problem in Delhi in the next few years. The air quality index is a number, based on the comprehensive effect of concentrations of major air pollutants, used by Government agencies to characterize the quality of the air at different locations, which is also used for local and regional air quality management in many metro cities of the world. Thus, the main objective of the present study is to forecast the daily AQI through a neural network based on principal component analysis (PCA). The AQI of criteria air pollutants has been forecasted using the previous day’s AQI and meteorological variables, which have been found to be nearly same for weekends and weekdays. The principal components of a neural network based on PCA (PCA-neural network) have been computed using a correlation matrix of input data. The evaluation of the PCAneural network model has been made by comparing its results with the results of the neural network and observed values during 2000–2006 in four different seasons through statistical parameters, which reveal that the PCA-neural network is performing better than the neural network in all of the four seasons. Key words: Air quality index (AQI), forecasting, neural network, principal component analysis (PCA).
1. Introduction Air pollution is a serious problem in many parts of the world. It is usually caused by energy production from power plants, industries, residential heating, fuel burning vehicles, natural disasters, etc. The human health concerns are one of the important short-term consequences of air pollution, especially in urban areas. The global warming and the
1 Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India. E-mail: [email protected]; [email protected]
greenhouse effect are among the long term consequences on the global climate. Air pollution related problems have resulted in an increased public awareness of the air quality in both developing and developed countries (KURT and OKTAY, 2010). National and international environmental agencies such as the European Environmental Agency (EEA), the Environmental Protection Agency (EPA) and the Ministry of Environment and Forests (MoEF) have been established to work out the necessary guidelines and the legal ground work on air pollution. There are many air pollutants adversely affecting human health in the polluted air such as carbon monoxide (CO), RSPM, SO2, NO2, SPM, ozone (O3), etc. The high concentration of these pollutants can be life threatening, causing breathing difficulty, headache and dizziness. They may even result in heart
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