Modeling the Dispersion and Scavenging of Air Pollutants from Industrial Sources

1. Modeling of Air Pollutants Dispersion from Industrial Sources in Environmental Impact Assessment B. Krasovitov1, T. Elperin1, A. Fominykh1, I. Katra2 1Department of Mechanical Engineering, The Pearlstone Center for Aeronautical Engineering Studies, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Israel 2Department of Geography and Environmental Development, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Israel

2. Industrial air pollution plumes Scavenging of air pollutions by cloud and rain droplets Scavenging of air pollutions by cloud and rain droplets Ne'ot Hovav chemical factory (Nothern Negev, Israel) Power plant (Ashquelon, Israel)

3. Industrial air pollution plumes Heating plant (Hanover, NH US) Scavenging of air pollutions by cloud and rain droplets

4. Industrial air pollution plumes • Substances emitted into the atmosphere • from industrial sources include: • Carbon dioxide (CO2) • Carbon monoxide (CO) • Sulfur oxides (SOx) • Nitrogen oxides (NOx) • Volatile organic compounds (VOC) • Carbon-based particulate matter (PM2.5-10)

5. Air quality model (AQM)

6. Air pollution monitoring Beer-Sheva, Northern Negev AQI

7. Air pollution monitoring Table of breakpoints (according to US Environmental Protection Agency standards)

8. Gaussian plume model Scavenging of air pollutions by cloud and rain droplets Gaussian Plume model

9. Gaussian plume model Pasquill-Gifford stability categories

10. Gaussian plume model Pasquill-Gifford horizontal dispersion parameters

11. Gaussian plume model Pasquill-Gifford vertical dispersion parameters

12. Gaussian plume model

13. Gaussian plume model Fig. 4. Concentration distributions in the XZ-plane, evaluated at Y=0.

14. Mean wind velocity profile

15. Measurements of mean wind velocity profile Fig. 6. A cup anemometer Katra et al., Aeolian Research 20 (2016) 147–156 Fig. 5. A 10-m wind mast

16. Measurements of mean wind velocity profile For each height the average wind velocity was calculated as follows

17. Adsorption of trace atmospheric gases by plume Scavenging of air pollutions by cloud and rain droplets Fig. 7. Concentration distributions in the XZ-plane, evaluated at Y=0 (Elperin et al., Process Saf. Environ. Prot., 111 (2017) 375–387).

18. Adsorption of trace atmospheric gases by plume Scavenging of air pollutions by cloud and rain droplets Fig. 8. Concentration profiles of HNO3 in the atmosphere calculated in the XZ-plane at Y = 0 (speed of wind at the height of release – 6.36 m/s; height of release – 20 m; rate of release – 10 g/s ). Fig. 9. Ground level concentration of HNO3 vs. distance from the point of release.

19. Wet deposition of PM emission Fig. 4. Concentration distribution in the XZ-plane, evaluated at Y=0 (Elperin et al., Process Saf. Environ. Prot., 102 (2016) 303-315). Scavenging of air pollutions by cloud and rain droplets

20. Conclusions Scavenging of air pollutions by cloud and rain droplets • The air quality modelling (AQM) is one of the principal approaches to air pollution exposure assessment. • Air quality study implies the estimation of some pollutants concentration in a region of interest, during a finite period of time. • The characteristics of each specific problem will define the physical and chemical processes involved, and consequently, the best model to use. • Mathematical models integrate our knowledge of the chemical and physical processes of pollutant dynamics into a structured framework that can be used to explain the relationship between sources of air pollution and the resulting impact on human health.

21. Acknowledgements Scavenging of air pollutions by cloud and rain droplets This work was partially supported by Israel Science Foundation governed by the Israeli Academy of Sciences (Grant No. 1210/15) and by Israel Ministry of National Infrastructures, Energy and Water Resources.