24 Hour Advance Forecast of Surface Ozone Using Linear and Non-Linear Models at a Semi-Urban Site of Indo-Gangetic Plain

Nidhi Verma, Sonal Kumari, Anita Lakhani and K Maharaj Kumari
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K Maharaj Kumari: Social Sciences Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Belgium

International Journal of Environmental Sciences & Natural Resources, 2019, vol. 18, issue 2, 46-55

Abstract: The present study includes prediction of next day hourly ozone concentration using four models viz. multiple linear regression (MLR), principal component regression (PCR), artificial neural network (ANN) and principal component based artificial neural network (PCANN). The input variables used for models construction were hourly concentration of previous day ozone, nitrogen dioxide (NO2), carbon monoxide (CO), temperature (T), relative humidity (RH), wind speed (WS), solar radiation (SR) and solar radiation duration (SRD). The measurement of ozone and its precursors was carried out at a semi-urban site of Dayalbagh, Agra.

Keywords: earth and environment journals; environment journals; open access environment journals; peer reviewed environmental journals; open access; juniper publishers; ournal of Environmental Sciences; juniper publishers journals; juniper publishers reivew (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:adp:ijesnr:v:18:y:2019:i:2:p:46-55

DOI: 10.19080/IJESNR.2019.18.555982

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