S. Abdulwahab et al., PREDICTING OZONE LEVELS - A STATISTICAL-MODEL FOR PREDICTING OZONE LEVELS IN THE SHUAIBA INDUSTRIAL-AREA, KUWAIT, Environmental science and pollution research international, 3(4), 1996, pp. 195-204
This paper presents a statistical model that is capable of predicting
ozone levels from precursor concentrations and meteorological conditio
ns during daylight hours in the Shuaiba Industrial Area (SIA) of Kuwai
t. The model has been developed from ambient air quality data that was
recorded for one year starting from December 1994 using an air pollut
ion mobile monitoring station. The functional relationship between ozo
ne level and the various independent variables has been determined by
using a stepwise multiple regression modelling procedure. The model co
ntains two terms that describe the dependence of ozone on nitrogen oxi
des (NOx) and non-methane hydrocarbon precursor concentrations, and ot
her terms that relate to wind direction, wind speed, sulphur dioxide (
SO2) and solar energy. In the model, the levels of the precursors are
inversely related to ozone concentration, whereas SO2 concentration, w
ind speed and solar radiation are positively correlated. Typically, 63
% of the variation in ozone levels can be explained by the levels of
NOx. The model is shown to be statistically significant and model pred
ictions and experimental observations are shown to be consistent. A de
tailed analysis of the ozone-temperature relationship is also presente
d; at temperatures less than 27 degrees C there is a positive correlat
ion between temperature and ozone concentration whereas at temperature
s greater than 27 degrees C a negative correlation is seen. This is th
e first time a non-monotonic relationship between ozone levels and tem
perature has been reported and discussed.