(729e) Photochemical Process Simulation and Control Strategy Development in Beijing Using Camx

Air quality models (AQM) are used to understand the complex relationships between different sources of air pollutants and ambient concentrations. Photochemical process that takes place in the atmosphere under the condition of specific meteorological statues and particular terrain layout. Among the pollutants that photochemical process generates, the ground level ozone threatens human health and becomes the main cause of lung cancer in large cities.

This paper introduces a multi-scale air quality model, Comprehensive Air quality Model with extensions (CAMx),^[1],[3] to simulate ozone concentration profiles over Beijing model domain for calendar year 2011^[2]. The simulation started at 00:00 on February 21 and ended at 24:00 on 22, lasting 48 hours. The model domain was divided into 105×56 grids with 1km cell lengths. The case utilized the meteorological and UV albedo data provided by the Beijing Weather Bureau, the emission and boundary conditions was self-defined. Sensitivity of model outputs to input data was investigated by using alternative input data and changing other important modeling assumptions, including the position of emissions and schemes to represent photochemistry. Impacts on model performance were evaluated by simulation results. The hourly concentration model evaluated indicates that the model is reliable compared with sample case released by Environ. Corporation. The ozone episodes occurred on the first day of the 48-hour simulation case, which coincide well with the daily air quality report released by Beijing Environment Protection Bureau. Due to the inactive atmospheric motion in model domain, the hot point of ozone was located in the city center, where the concentration was much higher than the surrounding areas.

The main goal of the paper is to find some pollution control strategies based on the performance of model simulation. The model was used to develop NOx and/or VOCs emission reduction strategies to attain ozone standard of air quality objectives. The ozone contribution of each source categories and source regions is examined by the model analysis utility named Ozone Source Apportionment Technology (OSAT). The results of OSAT suggest that the mobile source in the urban area and the Yanshan industrial Plants was the main source categories that contribute most to the ozone concentration. Sensitivities of ozone concentrations to precursor emissions such as NOx and VOCs are also quantified using the Decoupled Direct Method (DDM) integrated in CAMx^[2]. The results of sensitive analysis suggest that ozone generation over the urban area during the episodes days in winter is mostly NOx-dominated. To exam the effect of control strategies, the ozone precursor emission sources were mainly divided into 3 categories and the emission rate of NOx and/or VOCs was manually reduced by 10 to 30 percent. To obtain detailed performance of the control strategies, a list of different combination of emission reduction was made and applied into the model simulation. The model output indicates that the strategy of the combination of reducing mobile sources (mostly vehicles) in and around urban area and the hydrocarbon that industrial plants released on upwind and downwind directions is effective.

Unfortunately, the results could only show the theoretical performance of emission control strategies considering only scientific aspects. Well, the real problem is more than scientific, which means economic and social influence must be taken into account together when evolving the emission control strategies. New emission control strategies and an improved model should be developed in our future works.