(677e) Study on Ozone Formation Characterization during the Flaring of Chemical Plant Shutdown for Proactive Flare Minimization and Air-Quality Control
AIChE Annual Meeting
2019
2019 AIChE Annual Meeting
Process Development Division
Case Studies in Technology: Design, Risk Reduction and Implementation
Thursday, November 14, 2019 - 1:58pm to 2:20pm
Flaring is a necessary measure for chemical plant safety. However, the industrial flaring generates large amounts of VOCs and NOx, which could transiently aggravate regional ozone concentrations in the presence of sunlight that could affect on human health and negative societal impacts. Note that VOCs from the flaring of chemical plant shutdown mainly consist of ethylene, ethane, propylene, propane and other hydrocarbons, which have the different potential for ozone formation. So, it is important to know that the sensitivity and contribution of the regional ozone impact due to the different chemical species from the flaring of chemical plant shutdown. In this paper, plant-wide dynamic simulations for plant shutdown flare emissions with regional air-quality modeling were coupled together to quantify the air-quality impact (i.e., ozone concentration) due to the different chemical species. Also, deep insights of the ozone formation characterization are provided for proactive air-quality control and optimal flare minimization. Case studies indicate that ethylene and propylene are main species for ozone formation during the flaring of chemical plant shutdown, which accounts for 58.8 % and 23.1 % ozone formation potential, respectively. Thus, it becomes more important and attractive for the industry from the viewpoint of ozone pollution control to make flare minimization strategies by recycling the ethylene and propylene instead of all chemicals, which can save lots of resources and achieve the cost-effective strategies for air-quality control. This study could provide valuable and quantitative support for both the industry and environmental agencies on developing proactive and optimal ï¬are minimization strategies in the future.