Regression Model to Analyse Air Pollutants Over a Coastal Industrial Station Visakhapatnam ( India )

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N.V. Krishna Prasad
M.S.S.R.K.N. Sarma
P. Sasikala
Naga Raju M
N. Madhavi

Abstract

Particulate matter concentration and its study has gained tremendous significance in view of increase in air pollution. Since air pollution has many adverse effects on mankind, measures may be taken by observing the trends in PM2.5 (particulate matter) and concentrations of pollutants like NO2, SO2, NO2, NO, NOx, CO, NH3 and RH(Relative Humidity)  as well as temperature. Even though continuous monitoring of air pollution in urban locations has been increasing in view of its huge impact on the sustainable development and ecological balance a regression model is essential always to analyse large sets of data. These regression models also play vital role in some cases where data was not observed due to unavoidable circumstances and during times when the measuring instruments do not work. In this context an attempt was made to develop a regression model exclusively for Visakhapatnam(India) a coastal, urban and industrial station and to analyse the trends in particulate matter concentration at this staion. A regression model was developed with PM2.5 as dependent variable and SO2, NOx, NO2, CO, NH3, temperature(Temp) and relative humidity(RH) as independent variables. The efficiency of the model was tested with known independent variables and PM2.5 was estimated. It is found that observed and estimated PM2.5 values are highly correlated.

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[1]
N. K. Prasad, M. Sarma, P. Sasikala, N. Raju M, and N. Madhavi, “Regression Model to Analyse Air Pollutants Over a Coastal Industrial Station Visakhapatnam ( India )”, Int. J. Data. Science., vol. 1, no. 2, pp. 107-113, Jul. 2020.
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References

D.S. Satish Kumar, 2013. Air Pollution in Visakhapatnam – An Overview. International Journal of Civil Engineering (IJCE) Vol. 2, Issue 4, Pg. 11-14.

Sandeep Police, Sanjay Kumar Sahu, Gauri Girish Pandit ( 2016). Chemical characterization of atmospheric particulate matter and their source apportionment at an emerging industrial coastal city, Visakhapatnam, India. Atmopsheric Pollution Research. Vol( 7), Issue 4, Pg 725-733

Pradyumn Singh, Renuka Saini ,AjayTaneja(2014). , Physicochemical characteristics of PM2.5: Low, middle, and high–income group homes in Agra, India–a case study. Atmopsheric Pollution Research. Vol 5, Issue 3, Pg 352-360.

Reshmi Das , Bahareh Khezri, Bijayen Srivastava , Subhajit Datta , Pradip K.( 2015). Trace element composition of PM2.5 and PM10 from Kolkata – a heavily polluted Indian metropolis. Atmos. Pollut. Res., 6, pg. 742-750

Correia AW, Pope CA , Dockery DW, Wang Y, Ezzati M Dominici F.Correia( 2013). Effect of air pollution control on life expectancy in the United States an analysis of 545 US counties for the period from 2000 to 2007. Epidemiology, 24 (2013), pp. 23-31.

Padoan E, Malandrino M,Giacomino A,Grosa M M,Lollobrigida F( 2016). Spatial distribution and potential sources of trace elements in PM10 monitored in urban and rural sites of Piedmont Region. Chemosphere, vol.145 , pg. 495-507

Lim S.S, Vos T,Flaxman AD, Danaei G,Shibuya K et.al.,(2012)..A comparative risk assessment of burden of disease and injury attributable to67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010.Lancet, 380  pg. 2224-2260.

Danting Zhao , Hong Chen, Erze Yu and Ting Luo (2019). PM2.5/PM10 Ratios in Eight Economic Regions and their relationship with Meteorology in China. Advances in Meteorology,Volume 2019, Article ID 5295726, 15 pages

Cairong Lou, Hongyu Liu,Yufeng Li, Yan Peng, Juan Wang, and Lingjun Dai(,2017). Relatioships of relative humidity with PM2.5 and PM10 in the Yangtze River Delata, China. Environmental Monitoring and Assessment. Vol(189).Article No.582.

Wang Hua, Jiang Nan, Yang Naiwang (2014). The study of atmospheric environment quality and its change trend in Xi 'an during 1991-2012. Journal of environmental engineering, pg 526-529.

Central Pollution Control Board( http://cpcb.nic.in/)

Environmental Protection Agency(http://www.epa.gov.in/)