389644 Uncertainties of Ozone Increments Caused By Industrial Startup Flaring

Tuesday, November 18, 2014: 1:50 PM
International A (Marriott Marquis Atlanta)
Jian Zhang, Ziyuan Wang, Qiang Xu and Thomas C. Ho, Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX

Ground-level ozone is one of six common pollutants defined by US EPA (Environmental Protection Agency).  It can cause health effects, including lung diseases.  HRVOC (Highly Reactive Volatile Organic Compounds) emissions from industries are highly responsible for ground-level ozone pollution, especially around industrial district.  Flare emissions from MSS (maintenance, startup and shutdown) & events are major sources of HRVOC emissions.

Most of air quality modeling treats industrial flares as constant emissions, which means the emissions keep constant for the whole scenario days, and the total amount of emissions equal to the total emissions reported to environmental authorities.  However, real flare emissions from MSS and events are time-various.  At certain time, flare emissions could be very huge, and at other time, flare emissions could be very small.  During emission peaks, the ozone formation could be much higher than a flat emission curve.

Our previous works showed that time-various flare emissions could increase the 8-hour average ozone concentration by 15 ppb, which is 20% of current ozone standard (75 ppb).  However, different locations may cause different results.

In this paper, different locations of time-various startup flare emissions are considered for air quality modeling.  Emission data are obtained from dynamic simulation of a typical ethylene plant.  The dynamic simulation results were validated with real plant data and emission data of startup events.  The time-various flare emission data were added into Houston-Galveston-Brazoria (HGB) 2006 episode base case modeling as a point emission source.  The flare emission point was placed at different locations which were obtained from center of industrial areas.

Simulation results gave a cluster of maximum ozone and ozone increment curves.  The mean value curve, standard deviation curve, 90% and 100% uncertainty regions were generated from ozone curves.  These curves showed the average and region of maximum ozone, ozone increment of the whole area and at monitoring stations.

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