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On Regional Modeling to Support Air Quality Policies (book chapter)
Rao, S., H. Luo, M. Astitha, C. Hogrefe, R. Mathur, AND N. Kumar. On Regional Modeling to Support Air Quality Policies (book chapter). Chapter 4, Air Pollution Modeling and its Application XXV. Springer International Publishing AG, Cham (ZG), Switzerland, , 25-29, (2017).
Current developments in air pollution modelling are explored as a series of contributions from researchers at the forefront of their field. This newest contribution on air pollution modelling and its application is focused on local, urban, regional and intercontinental modelling; long term modelling and trend analysis; data assimilation and air quality forecasting; model assessment and evaluation; aerosol transformation. Additionally, this work also examines the relationship between air quality and human health and the effects of climate change on air quality. This Work is a collection of selected papers presented at the 35th International Technical Meeting on Air Pollution Modeling and its Application, held in Chania (Crete), Greece, Oct 3-7, 2016.
We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing meteorology and emissions loading over the contiguous United States. To this end, we spectrally decomposed the daily maximum 8-h (MDA8) ozone time-series for the period from 1990 to 2010 using the Kolmogorov-Zurbenk (KZ) filter to examine the variability in the relative strengths of the synoptic forcing (i.e., short-term variation induced by weather fluctuations) and the baseline forcing (i.e., long-term variation induced by emissions, policy, and trends) embedded in model output and observations. Using the information extracted from the synoptic and baseline forcings in ozone observations over the 21-year period, we present a new method for applying regional ozone air quality models in the regulatory setting. The new method provides the confidence limits for the 4th highest MDA8 ozone value and number of ozone exceedances for a given emission reduction scenario. This information is useful to policy-makers in deciding upon the emission control policy that can help meet and maintain the ozone National Ambient Air Quality Standard.