A Long-Term Study of Oxides of Nitrogen, Sulphur Dioxide, and Ammonia for a Port and Harbor Region in India

Abstract

A long-term study of oxides of nitrogen (NO x ), sulphur dioxide (SO2), and ammonia (NH3) has been performed in a port and harbor region in India from 01 1997 to 12 2000. Meteorological data was also collected to establish the correlation with gaseous pollutants concentrations. Monthly mean concentrations of NO x were in the range of 19.5–59.0 µg/m3 and were observed to be highest during winter season. Monthly mean concentrations of SO2 were in the range of 8.6–51.3 µg/m3 and were observed to be highest during winter season. The concentrations of SO2 increased gradually from 18.8 µg/m3 in 1997 to 33.3 µg/m3 in 2000. This may be attributed to the increase in port activities and ship traffic, which had an annual growth of about 15%. Monthly mean concentrations of NH3 were in the range of 87.1–235.1 µg/m3 and the maximum concentration was observed during post-monsoon season. It may be concluded that NO x and SO2 have their maximum values during winter season while NH3 has a maximum value during post-monsoon season. Statistical analysis was carried out for air pollutant data for the period 1997–2000 and correlation between gaseous pollutants (NO x , SO2, NH3) and meteorological parameters (temperature and wind speed) was estimated. NH3 was found to be weakly correlated with NO x (0.46), strongly correlated with SO2 (0.75) and negatively correlated with wind speed (−0.60). The highest correlation (0.87) was observed between SO2 and NO x because of common sources. A strong negative correlation was found between wind speed and gaseous pollutants. The above finding is also supported by monitoring results that when the wind velocity doubled, the concentrations of pollutants decreased sharply to about a half. Regression analysis showed that relationship among NO x , SO2, wind speed, and temperature was moderate to strong while that among NH3, wind speed, and temperature was poor. Hence regression equations could be developed for predicting NO x and SO2 concentrations.