Proactive and Cost-effective Regional Air-Quality and Industrial Emission Controls
Many industrial regions will continue facing ground-level ozone pollution issues. This leads to an urgent need to continue researches in improving scientific understanding of the mechanisms of ozone formation and transportation, as well as developing cost-effective air-quality control strategies. Our research group has developed multiple proactive and cost-effective air-quality control methodologies by coupling emission source reduction and air quality modeling studies. In this research area, the best air-quality control strategies are achieved at two different levels. In the chemical process level, in-plant optimization controls for emission source minimization will be explored to reduce total amount of emission, duration of intensive emission, as well as the number of instances potentially causing significant emissions. These could be accomplished with the help of plant-wide dynamic simulation and optimization. Based on the validated large-scale process models, various optimization activities can be virtually carried out and studied, such as optimal start-up and shutdown operations, smart process upset handling, and process design retrofit for flare gas recovery. These in-plant controls target on emission minimization within the plant; meanwhile, the associated dynamic simulations help to obtain hourly dynamic emission data, which can be used to update TCEQ emission inventories for air quality modeling. Based on the acquired VOCs and NOx emissions from the chemical process level, CAMx based air-quality modeling, simulation, and optimization will be conducted. The modeling activities will not only predict plant emission effects on regional air quality (e.g., ozone concentration increment due to a plant start-up), but also minimize regional air quality impacts of those planned emission events through optimization of available out-plant control factors, such as selections of date and starting time for plant start-up/shutdown operations, air-quality conscious scheduling for multi-plant turnaround operations, as well as new plant site determination.
Select References
- Ge, S. J., Wang, S. J., Xu, Q.*, T. C. Ho, “Air-quality Conscious Scheduling for Multiple Ethylene Plant Start-ups”, Industrial & Engineering Chemistry Research, 55 (36), 9698-9710, 2016.
- Wang, Z. Y., Wang S., Xu, Q.*, Ho, T. C., “Impacts of flare emissions from an ethylene plant shutdown to regional air quality”, Atmospheric Environment, 138, 22-41, 2016.
- Cai, T. X., Wang, S. J.*, Xu, Q.*, “Monte Carlo Optimization for Site Selection of New Chemical Plants”, Journal of Environmental Management, 163, 28-38, 2015.
- Chen, M., Wang, S. J.*, Xu, Q.*, “Multi-objective Optimization for Air-quality Monitoring Network Design”, Industrial & Engineering Chemistry Research, 54 (31), 7743-7750, 2015.
- Cai, T. X., Wang, S. J. Xu, Q*, “Scheduling of Multiple Chemical Plant Start-ups to Minimize Regional Air Quality Impacts”, Computers & Chemical Engineering, 54, 68-78, 2013. (2013 Best paper award of AIChE Environmental Division)
- Cai, T. X., Wang, S. J. Xu, Q.*, Ho, T.C., “Proactive Abnormal Emission Identification via Air-quality Monitoring Network”, Industrial & Engineering Chemistry Research, 52(26), 9189-9202, 2013.
- Ge, S. J., Wang, S. J., Xu, Q.*, T. C. Ho, “Air-quality Conscious Scheduling for Multi-Plant Turnaround Operations”, accepted, Proceedings of FOCAPO/CPC 2017, paper #47, Tucson, Arizona, USA, 2017.