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Atmospheric pollution: A case study of degrading urban air quality over Punjab, India
Abstract
This paper presents the results of a case study of urban air quality over a densely populated city Ludhiana situated in Punjab, India, in the form of monthly and annual average concentrations of Suspended Particulate Matter (SPM), NO2 and SO2 for the periods 1988-1989, 1994-1999 and 2001-2005 which is generally found to be increasing with time and thus requires immediate corrective measures lest the situation becomes totally uncontrollable. The present situation is as bad as in other metropolitan Indian cities, although it seems to have somewhat improved as indicated by the latest 2001-2005 data in comparison with the past 1988-1989 and 1994-1999 data, but much more still needs to be done. In addition to the industrial and vehicular pollution, the agricultural pollution due to the burning of wheat and rice straws by the farmers should also be checked because it also creates tremendous pollution in the atmosphere.
... An equation for calculation of AQI in India based on four pollutants (Nitrogen di oxide, Sulphur di oxide, suspended particulate matter and respirable particulate matter) has been developed. Sehra (2007) was checked Air Quality in Punjab. This paper presents the summary results of a case study of hazardous air pollution problems over a densely populated city Ludhiana situated in Punjab in the form of annual average concentrations of suspended particulate matter (SPM). ...
... These factors lead to dispersion of pollutants near the source resulting into less concentration of pollutants during the winter or post-monsoon period. Low value of pollutants during the post-monsoon period is also in line with the findings of Tripathi and Panigrahi (2000) and Sehra (2007). ...
In the present study, ClimGen (weather generator) generated data was compared to the observed weather data of Ballowal, Ludhiana and Bathinda weather stations representing different type of climatic situations in Punjab. Several years of daily data of solar radiation, maximum and minimum temperature, morning and evening relative humidity, rainfall and wind speed were used as input and five years data were used for validation purpose. Evaluation was done on the basis of coefficient of determination (R2), Residual Mean Square Error (RMSE), General Standard Deviation (GSD) and Wilmott's index (d) of agreement between generated and observed data. The ClimGen generated data for maximum and minimum temperature showed good performance (GSD d" 0.10 and d e" 0.95) and the data generated for morning relative humidity was acceptable (GSD > 0.10 but d" 0.20 and d < 0.95 but e" 0.90) while evening relative humidity and wind speed were poor except for Ludhiana station. However, the generated rainfall data was poor for all the stations and hence, cannot be accepted. Overall, results indicated ClimGen a good performer as a weather generator for certain parameters.
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