Use of air dispersion modelling for the assessment of air quality of an industrial area

Abstract

For Gobindgarh town, out of total area of 9 sq. km. (2223acs.) 33.74% is occupied by industrial use. Air polluting industries in Mandi Gobindgarh are using coal /furnace oil as fuel in their furnaces emitting the aforesaid pollutants, besides the process/ fugitive emissions. In addition to this, burning of rice and wheat straw by the farmers in the agricultural fields surrounding Mandi Gobindgarh is also affecting the ambient air quality of the town. RSPM and SOx pollutants belong to Group-B pollutants (organics probable Carcinogens), whereas NOx is Group-A pollutant. The Exceedence Factor in regard to these pollutants has been observed to be more than 1.5 (critical pollution). The degradation in the quality of ambient air of Mandi Gobindgarh has taken place due to unplanned and improper development of the city. Therefore, a detailed study on emission sources and quantification of pollutant concentration by means of dispersion modelling is required to access the environmental impacts. On the basis of the predicted increments to air pollutant concentrations, an effective mitigation and environmental plan can be devised for sensitive areas. In this study 26 sampling sites were selected on the basis of major stacks in industrial area and types of industries. Stack monitoring campaign was carried out at periodic intervals, such as once every three months at the peak working hour of the industry through-out the study period of one year i.e. May 2012 to April 2013 to ensure proper representation of activities. The average emissions of SO2 and NO2 measured from representative stacks were taken to compile the emission inventory. The essential meteorological data like wind speed, wind direction, ambient air temperature, relative humidity, rainfall, atmospheric pressure, cloud cover, ceiling height and solar radiation were collected for daily mean hourly data through-out the study period with the help of Weather Monitoring Station and IMD, Patiala. Meteorological data then compiled in an excel file for further processing by AERMET and wind rose diagram and surface and profile file for the area has been generated. It was observed that the pre-dominant wind direction is from West with 59.87 % frequency of calm winds and the wind speed was 2.95 Knots. AERMOD was run for 1h, 24h and periodic average time to generate isopleths showing areas of minimal to high concentrations. In case of 1h average time for NO2 emissions, highest concentration of 11.87µg/m3 at receptor C (RIMT College) and lowest concentrations of 2.287µg/m3 at D (PPCB) and F (Floating restaurant, picnic spot) respectively were predicted. In case of 24h average time for NO2 emissions, highest concentration of 5.3µg/m3 at receptor A, B and C (RIMT College, Ambe Majra and Ajnali respectively) and lowest concentrations of 0.3µg/m3 and 0.1µg/m3 at D (PBCB) and F (Floating restaurant, picnic spot) were predicted. In case of periodic average time for NO2 emissions, highest concentration of 1.43µg/m3 at receptor C and B (RIMT College and Ambe Majra respectively) and lowest concentrations of 0.6µg/m3, 0.6µg/m3 and 0.02µg/m3 at D (PPCB), F (Floating restaurant, picnic spot) and E (Chattarpur Zoo) respectively were predicted. But in this study only 10 % of the industrial emissions were covered. In case of 1h average time for SO2 emissions, highest concentration of 0.451µg/m3 at receptor A and lowest concentrations of 0.025µg/m3 at D, B and F receptors were predicted. In case of 24h average time for SO2 emissions, highest concentration of 0.20µg/m3 at receptor A and lowest concentrations of 0.035µg/m3 at E and C receptors were predicted. In case of periodic average time for SO2 emissions, highest concentration of 0.0339µg/m3 at receptor C and lowest concentrations of 0.002µg/m3, 0.0017µg/m3 and 0.004µg/m3at E, D and F receptors were predicted. But in this study only 10 % of the industrial emissions were covered. Hence the actual emission scenario would be even worse than predicted from this simulation.