American Journal of Environmental Protection
ISSN (Print): 2328-7241 ISSN (Online): 2328-7233 Website: http://www.sciepub.com/journal/env Editor-in-chief: Mohsen Saeedi, Hyo Choi
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American Journal of Environmental Protection. 2016, 4(1), 1-6
DOI: 10.12691/env-4-1-1
Open AccessArticle

Influence of Some Meteorological Variables on PM10 and NOx in Gurgaon, Northern India

Ram Chhavi Sharma1, and Niharika Sharma2

1Department of Applied Sciences, Dronacharya College of Engineering Gurgaon Haryana, India

2Department of Chemistry, Government Senior Secondary School Kakoria, Rewari Haryana, India

Pub. Date: April 18, 2016

Cite this paper:
Ram Chhavi Sharma and Niharika Sharma. Influence of Some Meteorological Variables on PM10 and NOx in Gurgaon, Northern India. American Journal of Environmental Protection. 2016; 4(1):1-6. doi: 10.12691/env-4-1-1

Abstract

Urban air pollution is rapidly becoming an environmental problem of public concern worldwide. It can influence public health and local/regional weather and climate. In the present study, airborne particulate pollutants PM10 and NOx data were collected for a period of one year (January 2014 to December 2014) at Vikash Sadan location in Gurgaon, a rapidly developing city in Haryana State in Northern India. The pollutants data were collected by the Haryana Pollution Control Board. The observed concentrations of PM10 ranged between 50.77μg/m3 to 451.0μg/m3 and of NOx ranged between 9.83μg/m3 to 216.25μg/m3. The seasonal- and annual-average concentrations of the pollutant were mostly above Indian air quality standards. These pollutants concentration were correlated with meteorological variables such as temperature, humidity and rainfall. The regression correlation analysis has been performed between particulate pollutants and meteorological parameters to investigate the relationships between them. This statistic will give an idea about which meteorological parameter play a major role in modulating the pollutants concentrations over Gurgaon.

Keywords:
urban ambient air quality particulate pollutants meteorological variables regression analysis

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