Asha B. Chelani

  • Air Pollution Control Division, National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, India

Received: December 29, 2014
Revised: April 10, 2015
Accepted: May 7, 2015
Download Citation: ||https://doi.org/10.4209/aaqr.2014.12.0337 

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Cite this article:
Chelani, A.B (2015). Exceedance Analysis of PM10 Concentration in Central Indian City: Predicting Gap between Two Exceedances. Aerosol Air Qual. Res. 15: 2158-2167. https://doi.org/10.4209/aaqr.2014.12.0337


HIGHLIGHTS

  • Gap between two exceedances of PM10 is analyzed with time series analysis.
  • Mining activity locations have higher PM10 than urban areas.
  • Exponential relation between annual average PM10 and gap between two exceedances.
  • PM10 concentration prediction model based on k-nearest neighbour approach.
  • Gap between two exceedances predicted with developed model and exponential relation.

 

ABSTRACT


In this study the gap between the two exceedances is analyzed using time series analysis. The time series of PM10 (particulate matter of size less than 10 micron) observed during 2005–2013 in two cities; Nagpur and Chandrapur in central India is considered. Higher PM10 concentration is observed in Chandrapur as compared to Nagpur. Exponential relationship is observed between the average time between the two exceedances and annual average PM10 concentration. This information along with the PM10 concentration prediction model is utilized to predict the average number of observations between the two exceedances for the following year. k-nearest neighbor approach is used for forecasting PM10 concentration which enabled estimating the average number of observations between two exceedances using exponential relationship. The approach can be used for estimating the average number of observations between the two exceedances over a year, which can further be utilized to make appropriate decision to control and manage high particulate matter pollution in an area.


Keywords: Exceedance time series; Gap or number of observations between two exceedances; k-nearest neighbor approach


Impact Factor: 2.735

5-Year Impact Factor: 2.827


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