Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 39, Pages: 1-7
A. Mishra1 , S. Tiwari2 and S. Tyagi1*
1 Department of Environmental Science, School of Vocational Studies and Applied Sciences, Gautam Buddha University, Greater Noida, UP, 201312, India; [email protected]
2 Indian Institute of Tropical Meteorology, New Delhi Branch, 110060, India
*Author for correspondence
Department of Environmental Science
Objectives: To improve the accuracy of atmospheric visibility forecast over New Delhi for Republic Day ceremony, a statistical model is developed for fog (visibility < 1000 m) forecasting based on meteorological elements and mass concentration of Particulate Matter (PM). Methods/ Statistical Analysis: Mass distribution (μg/m3 ) from 0.3 to 20 μm of PM were measured simultaneously along with the meteorological elements in New Delhi during the month of January 2014 and 2015 to get an appreciation of their role in the atmospheric obscurity. The best possible multiple regression model for predicting visibility dependent on depression temperature, wind speed, thermal inversion and mass concentration of PM2,5 is developed using statistical software package Origin and MS office Excel. Findings: The average visibility during 0700 h to 1300 h on Republic Day is found to be 2000 m ± 1400 m. The daily mean concentrations of PM10 and PM2.5 during 22 to 27 January in the year 2014 and 2015 were found to be 1.23 to 5.20 times and 1.22 to 4.80 times higher than the daily Indian national ambient air quality standards (NAAQS). The correlation coefficient (r) and coefficient of determination (r2 ) values of 0.88 and 0.77 respectively suggest that visibility < 1000 m can be predicted satisfactorily using multiple regression model based on various meteorological elements and pollutants. Application/Improvement: This study will provide a better knowledge and guidance to aviation meteorologists and aviators on visibility pattern during Republic Day ceremony. It will also enhance the accuracy of visibility forecast and contribute towards flight safety.
Keywords: Depression Temperature, Particulate Matter, Thermal Inversion, Visibility, Wind Speed
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