A new method for assessing the efficacy of emission control strategies
Luo, H., M. Astitha, C. Hogrefe, R. Mathur, AND S. Rao. A new method for assessing the efficacy of emission control strategies. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 199:233-243, (2019). https://doi.org/10.1016/j.atmosenv.2018.11.010
The novel concept in this work is the determination of confidence intervals for the ozone exceedances in the future year and probability of achieving ozone compliance for future emission scenarios. We utilize ozone observations over a 30-yr timeframe to demonstrate the proposed approach for examining expected changes in extreme ozone concentration levels for the future target year. A probabilistic assessment is used to investigate how the base year non-attainment situation would change with given emission control options in the future and obtain confidence limits associated with such projections. Results analyzed and presented in this probabilistic manner would enable more explicit consideration of the ever-present uncertainty in projected changes in air quality needed to comply with the ozone standard in the future.
Regional-scale air quality models and observations at routine air quality monitoring sites are used to determine attainment/non-attainment of the ozone air quality standard in the United States. In current regulatory applications, a regional-scale air quality model is applied for a base year and a future year with reduced emissions using the same meteorological conditions as those in the base year. Because of the stochastic nature of the atmosphere, the same meteorological conditions would not prevail in the future year. Therefore, we use multi-decadal observations to develop a new method for estimating the confidence bounds for the future ozone design value (based on the 4th highest value in the daily maximum 8-hr ozone concentration time series, DM8HR) for each emission loading scenario along with the probability of the design value exceeding a given ozone threshold concentration at all monitoring sites in the contiguous United States. To this end, we spectrally decompose the observed DM8HR ozone time series covering the period from 1981 to 2014 using the Kolmogorov-Zurbenko (KZ) filter and examine the variability in the relative strengths of the short-term variations (induced by synoptic-scale weather fluctuations; referred to as synoptic component, SY) and the long-term component (dictated by changes in emissions, seasonality and other slow-changing processes such as climate change; referred to as baseline component, BL). Results indicate that combining the projected change in the ozone baseline level with the adjusted synoptic forcing in historical ozone observations enables us to provide a probabilistic assessment of the efficacy of a selected emissions control strategy in complying with the ozone standard in future years. In addition, attainment demonstration is illustrated with a real-world application of the proposed methodology by using air quality model simulations, thereby helping build confidence in the use of regional-scale air quality models for supporting regulatory policies.