It is difficult to assess the effectiveness of regulatory programs in improving ozone air quality in the presence of meteorological fluctuations. In this paper, techniques are presented that improve upon previous methods for moderating the effects of meteorology on ozone concentrations. This approach entails the use of the relations between ozone and meteorological variables to construct meteorologically adjusted ozone time series. To this end, the effectiveness and usefulness of various methods for separating time series of ozone and meteorological data into long-term (climate- and policy-related), seasonal (solar-induced), and short-term (weather-related) components are examined. Correlations between baseline components (sum of long-term and seasonal variations) of ozone and meteorological variables are then investigated independently of correlations between short-term components (weather effects) of ozone and meteorological variables. This allows us to account for the effects of the dominant meteorological variables on each time scale embedded in time series of ozone data. Ozone time series that are devoid of seasonal and climatic variations as well as weather-related fluctuations can then be constructed to detect and track changes in ozone due to the emission control policies implemented. The results of this study reveal that the combination of solar radiation and specific humidity performs best in filtering the seasonal and climatic variations from the baseline component of the ozone data. The combination of temperature and dew point depression performs best in moderating the weather-related effects on the short-term component of ozone data. This method is able to explain about 65% of the variance in ozone data through meteorological variables at several locations examined here.
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