Introduction to SCREEN3 smokestacks image from Univ. of Waterloo Environmental Sciences Marti Blad NAU College of Engineering and Technology.

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Presentation transcript:

Introduction to SCREEN3 smokestacks image from Univ. of Waterloo Environmental Sciences Marti Blad NAU College of Engineering and Technology

2 Dispersion Models Repetitious solution of dispersion equations Computer solves over and over again Based on principles of transport, diffusion Complex mathematical equations Computer-aided simulation of atmosphere based on inputs Best models need good quality and site- specific data

3 Historically Image from collection of Pittsburgh Photographic Library, Carnegie Library of Pittsburgh

4 Types of Dispersion Models Gaussian Plume Analytical approximation of dispersion Numerical or CFDs Transport & diffusional flow fields Statistical & Empirical Based on experimental or field data Physical Flow visualization in wind tunnels, etc.

5 Computational Fluid Dynamics Modeling image from MAGNUM Technologies, Inc

6 CFD Building Effects

7 C(x,y,z) Downwind at (x,y,z) ? Gaussian Dispersion hh h H z x y   h = plume rise h = stack height H = effective stack height H = h +  h

8 Gaussian Plume

9 SCREEN3 Model Assumptions Continuous pollutant emissions Conservation of mass in atmosphere Steady-state meteorological conditions Concentration profiles are represented by Gaussian distribution—bell curve shape

10 SCREEN3 designed for… Single source, short-term calculations Estimate maximum ground level concentrations Distance to max. concentration from source Concentrations at user defined distances Simple downwash algorithm Max. concentrations in near & far wake Estimate concentrations in cavity recirculation zone Source types All options for point & flare

11 SCREEN3 designed for…(cont.) Full range of meteorological conditions accepted Stability classes Wind speeds Inversion break up Shoreline fumigation Determine plume rise for flare releases Includes effects of BID Buoyancy induced dispersion Simple area & volume sources

12 Source Options

13 Dispersion Model Structure INPUT DATA: Operator experience METEROLOGY EMISSIONS RECEPTORS Model Output: Estimates of Concentrations at Receptors Model does calculations

14 Model Input Considerations Source type Point, area, volume, flare Stack or source emission data Pollutant emission data Stack- or source-specific data Temperature in stack Velocity out of stack Receptor data

15 Input screen 1

16 Input Considerations Actual pattern of dispersion depends on atmospheric conditions prevailing during release Major meteorological factors that influence dispersion of pollutants Atmospheric stability (& temperature) Mixing height Wind speed & direction

17 Meteorological inputs Appropriate meteorological conditions Appropriate for location Appropriate for averaging time period Wind stability and speed Flat terrain or complex terrain Distances to points of interest Receptors

18 Input screen: met data

19 Discrete Distance input

20 Automated Distances input

21 Model Inputs not Covered Today Height of plume rise calculated Momentum and buoyancy Can significantly alter dispersion & location of downwind maximum ground-level concentration Effects of nearby buildings estimated Downwash wake effects Can significantly alter dispersion & location of downwind maximum ground-level concentration

22 Building downwash option

23 Run: screen update

24 Model results: graphs

25 View text results: editor

26 Editor information

27 Review Dispersion = expand & diffuse Picture Gaussian = even spreading directions Highest along axis Input data quality critical Screen3 limitation for reactive chemicals No reactions assumed to create or destroy

28 SCREEN3 DEMONSTRATION Software provided courtesy of a division of Lakes Environmental Consultants Inc.

29 Exercise 1 input 1

30 Exercise 1 input 2

31 Run: Exercise 1

32 Results exercise 1: graph

33 Editor view1

34 Editor: Model Summary

35 Exercise 2 input 1

36 Exercise 2 input 2

37 Run: Exercise 2

38 Exercise 2 results

39 Editor: Exercise 2

40 Editor: Model summary

41 Exercise 3 input 1

42 Exercise 3 results: graph

43 Exercise 3: Model summary

44 Model summary

45 Input screen

46 Editor: exercise 3