Gaussian Plume Dispersion Model

The Gaussian plume model is the most common air pollution model. It is based on a simple formula that describes the three-dimensional concentration field generated by a point source under stationary meteorological and emission conditions. 

1. AIR POLLUTION MODELLING KULVENDRA PATEL 2K19/ENE/05 Gaussian Plume Dispersion Model DELHI TECHNOLOGICAL UNIVERSITY

2. Dispersion Modelling The Gaussian plume model is the most common air pollution model. It is based on a simple formula that describes the three-dimensional concentration field generated by a point source under stationary meteorological and emission conditions.  Gaussian-based dispersion models are widely used to estimate local pollution levels. The dispersion of plume which is emitted from a chimney is governed by many factors: wind speed, wind direction, local terrain, turbulence intensity of atmosphere, temperature, etc.

3. A contaminant plume emitted from a continuous point source, with wind direction aligned with the x-axis. Profiles of concentration are given at two downwind locations (vertical in red, horizontal in blue) and the Gaussian shape of the plume cross-sections are shown relative to the plume centerline. From John M. Stockie : The Mathematics of Atmospheric Dispersion Modeling

4. C ( , , ) =   C = Pollution concentration (g/ ) Q = pollutant emission rate (g/s) y = lateral distance from the centerline of plume (m) z = height off the ground (m) H = effective stack height (m) u = wind speed (m/s)     and   are plume standard deviation in the y and z directions (m) Where atmospheric stability is chosen from A - very unstable, B - somewhat unstable, C -Neutral, D - somewhat stable, F - Very stable

5. Air quality modelling study to analyse the impact of the World Bank Emission Guidelines for thermal power plants in Delhi ( Arun Kansal et.al ) Delhi is one the most polluted cities in the world due to its unrestricted growth. Urban transport, manufacturing industries and thermal power plants are the major sources of anthropogenic pollution. The World Bank (WB) has propose some environmental Guidelines for the TPPs in 1998 as a part of its pollution prevention and abatement handbook. The present study analyses how the ambient air quality of Delhi would improve if the WBEG for the TPPs were to be implemented. Performance was evaluated by comparing monthly estimated and observed concentrations at seven receptor locations: - Ashok Vihar v. Shahadara ITO vi. Sirifort Shazadabagh vii. Nizamuddin Janakpuri

6. Emission from TPPs TPP Temperature (K) Exit Velocity (m/s) Stack Height (m) TSP (g/s) S (g/s) N (g/s) Rajgha 366.4 4.0 160 22.3 73.2 21.5 IG 384.0 1.6 30 0.36 0.1 12.6 I 402.1 8.2 61 14.5 45.1 28.8 Badarpu 401.7 25.2 150 237.9 1233 405.4 Pragat 372.0 2.3 70 0.7 0.08 23.8 TPP Temperature (K) Exit Velocity (m/s) Stack Height (m) TSP (g/s) 366.4 4.0 160 22.3 73.2 21.5 384.0 1.6 30 0.36 0.1 12.6 402.1 8.2 61 14.5 45.1 28.8 401.7 25.2 150 237.9 1233 405.4 372.0 2.3 70 0.7 0.08 23.8 Average emission rates and characteristics of TPPs a – average of 12 months of two stacks b – average of 12 months of three stacks

7. Emission from Industries Industrial Area Temp. (K) Exit Velocity (m/s) Stack Diameter (m) TSP (g/s) S (g/s) N (g/s) Okhla Ph I 356 7 1.2 0.21 0.08 0.04 Okhla Ph II 352 5 1.1 0.11 0.05 0.03 Okhla Ph III 357 4 1.4 0.16 0.05 0.03 Smaipur 346 7 0.9 0.11 0.03 0.02 Badli 345 6 1.4 0.32 0.10 0.06 Udyog Nagar 367 5 0.8 0.06 0.03 0.01 Zakhira 341 8 0.7 0.09 0.02 0.01 Shazadabagh 350 6 0.6 0.04 0.02 0.01 Jhilmil 353 8 1.0 0.19 0.08 0.05 Najafgarh 341 7 1.1 0.15 0.05 0.03 Nangloi 352 6 0.8 0.06 0.02 0.01 Naraina 343 5 1.3 0.20 0.07 0.02 Wazirpur 354 4 2.2 0.42 0.15 0.06 S.M.A. 340 8 0.7 0.06 0.03 0.02 Industrial Area Temp. (K) Exit Velocity (m/s) Stack Diameter (m) TSP (g/s) Okhla Ph I 356 7 1.2 0.21 0.08 0.04 Okhla Ph II 352 5 1.1 0.11 0.05 0.03 Okhla Ph III 357 4 1.4 0.16 0.05 0.03 Smaipur 346 7 0.9 0.11 0.03 0.02 Badli 345 6 1.4 0.32 0.10 0.06 Udyog Nagar 367 5 0.8 0.06 0.03 0.01 Zakhira 341 8 0.7 0.09 0.02 0.01 Shazadabagh 350 6 0.6 0.04 0.02 0.01 Jhilmil 353 8 1.0 0.19 0.08 0.05 Najafgarh 341 7 1.1 0.15 0.05 0.03 Nangloi 352 6 0.8 0.06 0.02 0.01 Naraina 343 5 1.3 0.20 0.07 0.02 Wazirpur 354 4 2.2 0.42 0.15 0.06 S.M.A. 340 8 0.7 0.06 0.03 0.02

8. Emission from Vehicles Receptor Station TSP S N ITO 33.4 0.42 8.60 Shazadabagh 8.80 0.04 2.60 Janakpuri 6.4 0.50 2.60 Ashok Vihar 2.5 0.10 2.10 Shahadara 24.4 1.15 7.60 Sirifort 21.9 0.12 7.70 Nizamuddin 14.1 0.04 6.70 Receptor Station TSP ITO 33.4 0.42 8.60 Shazadabagh 8.80 0.04 2.60 Janakpuri 6.4 0.50 2.60 Ashok Vihar 2.5 0.10 2.10 Shahadara 24.4 1.15 7.60 Sirifort 21.9 0.12 7.70 Nizamuddin 14.1 0.04 6.70 Pollutant emissions (g/s) from roads

9. Indian and the WBEG for TPPs

10. Results Average annual GLCs ( g/m3) of pollutants at CPCB air quality Monitoring stations in Delhi   Receptor Stations Indian Scenario WBEG Scenario Percent Reduction TSP S N TSP S N TSP S N ITO 63.8 6.3 10.8 20.6 6.1 7.6 67.8 2.1 8.1 Shazadabagh 120.6 7.6 3.4 14.0 6.7 3.1 88.4 11.4 10.3 Janakpuri 57.8 2.9 3.2 9.3 2.7 2.6 83.9 6.6 17.8 Ashok Vihar 125.7 9.3 4.2 14.5 7.8 3.5 88.4 16.7 15.7 Shahadara 22.8 1.6 0.7 4.6 1.6 0.7 79.8 2.4 6.9 Sirifort 110.5 6.3 2.8 14.5 5.6 2.5 86.9 11.0 11.0 Nizamuddin 168.1 19.2 11.0 27 17.2 9.2 83.9 10.0 16.6 Receptor Stations Indian Scenario WBEG Scenario Percent Reduction TSP TSP TSP ITO 63.8 6.3 10.8 20.6 6.1 7.6 67.8 2.1 8.1 Shazadabagh 120.6 7.6 3.4 14.0 6.7 3.1 88.4 11.4 10.3 Janakpuri 57.8 2.9 3.2 9.3 2.7 2.6 83.9 6.6 17.8 Ashok Vihar 125.7 9.3 4.2 14.5 7.8 3.5 88.4 16.7 15.7 Shahadara 22.8 1.6 0.7 4.6 1.6 0.7 79.8 2.4 6.9 Sirifort 110.5 6.3 2.8 14.5 5.6 2.5 86.9 11.0 11.0 Nizamuddin 168.1 19.2 11.0 27 17.2 9.2 83.9 10.0 16.6 Impact of WBEG on air quality of Delhi

11. Conclusion The implementation of WBEG shows a significant reduction in TSP concentrations. Impact of WBEG on SO2 levels is not significant, since the Indian coal has already lower sulphur content, and the current emissions are not affected significantly under the WBEG scenario. The significant reduction in TSP emissions under the WBEG Scenario from th e TPPs is noteworthy.

12. Air Dispersion Modeling: Using SCREEN3 to Determine the MAGLC of Air Toxics ( Mario G. Cora et.al ) The default hourly concentration estimate incorporated in the SCREEN3 program is based on one-hour averaging. 3-hour: Multiply by 0.90 8-hour: Multiply by 0.70 24-hour: Multiply by 0.40 Annual: Multiply by 0.08 MAGLC is the abbreviation for “maximum allowable ground level concentration. Determine if a TLV exists for the compound being modeled. Divide it by 10. Adjust the standard to account for the duration of the exposure MAGLC = 4(TLV)/XY Receptor means a particular location at which the pollutant’s concentration is measured or estimated

13. Maximum concentration at simple terrain = 130.3   TLV = 300 μ g/ (as per European Community 1992 (EU) )   MAGLC = 300 /42 = 7.14 μg/   MAGLC Calculation

14. References Kansal Arun, Khare Mukesh, Sharma Chandra Shekhar, 2011. Air quality modelling study to analyse the impact of the World Bank Emission Guidelines for thermal power plants in Delhi. Atmospheric Pollution Research, 99-105 Cora Mario G. ,Hung Yung-Tse, Pagan-Rodriguez Doritza , 2003. Air Dispersion Modeling: Using SCREEN3 to Determine the MAGLC of Air Toxics. Environmental Quality Management, 67-79

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