ADMS ADMS 3.3 Modelling Summary of Model Features.

Slides:



Advertisements
Similar presentations
AIR POLLUTION AND METEOROLOGY
Advertisements

Laboratory Modeling of Atmospheric Dispersion at the Fluid Modeling Facility of the U.S. Environmental Protection Agency by William H. Snyder MiniTech.
Commonly Used Weather Terminology Advisory - Issued when hazardous weather or hydrologic conditions exist, are imminent or are likely tc occur. Advisories.
1 Atmospheric models for damage costs TRADD, part 2 Ari Rabl, ARMINES/Ecole des Mines de Paris, November 2013 There are many different models for atmospheric.
Session 11: Modeling Dispersion of Chemical Hazards, using ALOHA 1 Modeling Dispersion of Chemical Hazards, using ALOHA Prepared by Dr. Erno Sajo, Associate.
Introduction to SCREEN3 smokestacks image from Univ. of Waterloo Environmental Sciences Marti Blad NAU College of Engineering and Technology.
Introduction to SCREEN3 smokestacks image from Univ. of Waterloo Environmental Sciences Marti Blad.
SCAQMD Modeling Parameters for Developing Localized Significance Thresholds March 5, 2003.
Setting Acceptable Odor Criteria Using Steady-state and Variable Weather Data Z. Yu 1, H. Guo 2, C. Lague 3 1.Division of Environmental Engineering, University.
Meteorological Data Issues for Class II Increment Analysis.
2. Dispersion We’re going to move on to the second major step in doing dose assessment.
Session 2, Unit 3 Atmospheric Thermodynamics
Transport of Air Pollutants
Module 9 Atmospheric Stability Photochemistry Dispersion Modeling.
1 AirWare : R elease R5.3 beta AERMOD/AERMET DDr. Kurt Fedra Environmental Software & Services GmbH A-2352 Gumpoldskirchen AUSTRIA
Weather & Climate By Sarah Waters & Therese Daly.
Toxic Release and Dispersion Models
Temperature Lapse rate- decrease of temperature with height:  = - dT/dz Environmental lapse rate (  ) order 6C/km in free atmosphere  d - dry adiabatic.
Introduction to the ISC Model Marti Blad NAU College of Engineering.
Calculation of wildfire Plume Rise Bo Yan School of Earth and Atmospheric Sciences Georgia Institute of Technology.
Air Quality Modeling.
CHAPTER 5 Concentration Models: Diffusion Model.
Stack Design Done by Eng. Mohamed AbdElRhaman. Content Definition of the stack Applications of stack Dispersion Model Selection of stack design Conclusion.
EFCOG Safety Analysis Working Group May 10, 2012 Jeremy Rishel Bruce Napier Atmospheric Dispersion Modeling in Safety Analyses: GENII.
Session 4, Unit 7 Plume Rise
AMBIENT AIR CONCENTRATION MODELING Types of Pollutant Sources Point Sources e.g., stacks or vents Area Sources e.g., landfills, ponds, storage piles Volume.
Earth System Sciences, LLC Suggested Analyses of WRAP Drilling Rig Databases Doug Blewitt, CCM 1.
Cases 1 through 10 above all depend on the specification of a value for the eddy diffusivity, K j. In general, K j changes with position, time, wind velocity,
Air Dispersion Primer Deposition begins when material reaches the ground Material from the lower stack reaches the ground before that of the taller stack.
Meteorology & Air Quality Lecture-1
Ashok Kumar Kanwar Siddharth Bhardwaj Abhilash Vijayan
Understanding the USEPA’s AERMOD Modeling System for Environmental Managers Ashok Kumar Abhilash Vijayan Kanwar Siddharth Bhardwaj University of Toledo.
1 The Wind. 2 3 The origin of wind The earth is unevenly heated by the sun resulting in the poles receiving less energy from the sun than the equator.
Understanding the USEPA’s AERMOD Modeling System for Environmental Managers Ashok Kumar University of Toledo Introduction.
ADMS 3.3 Modelling (Atmospheric Dispersion Model System)
08/20031 Volcanic Ash Detection and Prediction at the Met Office Helen Champion, Sarah Watkin Derrick Ryall Responsibilities Tools Etna 2002 Future.
Meteorology & Air Pollution Dr. Wesam Al Madhoun.
Session 3, Unit 5 Dispersion Modeling. The Box Model Description and assumption Box model For line source with line strength of Q L Example.
Stable Atmosphere.
Introduction to Modeling – Part II Marti Blad Northern Arizona University College of Engineering & Technology Dept. of Civil & Environmental Engineering.
Introduction to Modeling – Part II
Comparison of the AEOLUS3 Atmospheric Dispersion Computer Code with NRC Codes PAVAN and XOQDOQ 13th NUMUG Conference, October 2009, San Francisco, CA.
Air quality models DETERMINISTIC MODELS EULERIAN MODELS
Types of Models Marti Blad Northern Arizona University College of Engineering & Technology.
Example 2 Chlorine is used in a particular chemical process. A source model study indicates that for a particular accident scenario 1.0 kg of chlorine.
Observed Structure of the Atmospheric Boundary Layer
03/24/2011 Air Resources Laboratory Upgrade of NOAA's Dispersion Modeling for INL Applications Richard M. Eckman Field Research Division NOAA Air Resources.
Meteorology for modeling AP Marti Blad PhD PE. Meteorology Study of Earth’s atmosphere Weather science Climatology and study of weather patterns Study.
Air Pollution Meteorology Ñ Atmospheric thermodynamics Ñ Atmospheric stability Ñ Boundary layer development Ñ Effect of meteorology on plume dispersion.
Intro to Modeling – Terms & concepts Marti Blad, Ph.D., P.E. ITEP
Forecasting smoke and dust using HYSPLIT. Experimental testing phase began March 28, 2006 Run daily at NCEP using the 6Z cycle to produce a 24- hr analysis.
Climate Controls. What is the Difference Between Climate and Weather? Weather is the combination of temperature, precipitation, cloud cover, winds, relative.
Atmospheric Stability and Air Masses
Consequence Analysis Robert Wu South Coast Air Quality Management District.
Comparisons of CALPUFF and AERMOD for Vermont Applications Examining differing model performance for a 76 meter and 12 meter (stub) stack with emission.
CGS Ground School Meteorology Visibility
TERRAINS Terrain, or land relief, is the vertical and horizontal dimension of land surface. Terrain is used as a general term in physical geography, referring.
Consequence Analysis 2.1.
Volcanic Ash Detection and Prediction at the Met Office
Quantifying uncertainty in volcanic ash forecasts
Air Pollution and Control (Elective- I)
Chengcheng Chen, Tingting Jiang, Genyong Wu
Air Pollution Dispersion Lab
PURPOSE OF AIR QUALITY MODELING Policy Analysis
Climate Maps and Climate.
Introduction to Modeling – Part II
Fundamentals of air Pollution Engineering
Meteorology & Air Pollution Dr. Wesam Al Madhoun
Wind Velocity One of the effects of wind speed is to dilute continuously released pollutants at the point of emission. Whether a source is at the surface.
Air Masses and Fronts Earth Science Chapter 24.
Presentation transcript:

ADMS ADMS 3.3 Modelling Summary of Model Features

ADMS ADMS 3.3 CERC –“New Generation” Model –Detailed description of atmosphere based on boundary layer properties Features –Point, area, line, volume and jet sources –Multiple sources and pollutants –Buildings and Topography –Plume rise –Single condition or statistical meteorology –Odours, radioactivity, plume visibility –Deposition (Wet and Dry) –Statistics, long and short term, percentiles

ADMS Factors Influencing Dispersion –Meteorology Wind Speed and direction Atmospheric stability (Monin–Obukhov Length and Boundary Layer Height) –Release point and conditions Elevation Velocity Temperature Ground roughness –Buildings If > 1/3 stack height –Topography If steeper than 1:10 slope

ADMS Meteorology Older Models –Passive dispersion model Pasquill-Gifford Stability Classes (A – G) Wind speed, direction ADMS –Boundary Layer Model Boundary layer height Monin – Obukhov length Wind speed, direction

ADMS Meteorological Parameters Boundary Layer Height –Height at which surface effects influence dispersion –ADMS calculates boundary layer properties for different heights based on meteorology Monin-Obukhov Length –Measure of height at which mechanical turbulence is more significant than convection or stratification –ADMS calculates M-O length based on meteorology and ground roughness

ADMS Meteorology Options Specific Data Wind speed, wind direction, date, time, latitude, boundary layer height, cloud cover Met Office Data Statistical data (10 years) –2200 lines of data (medium run times) Hourly sequential data (1 – 5 years) –Can be used to identify specific conditions for known dates and times –8760 lines of data per year (long run times) –Use to compare releases against environmental standards (preferred option by EA)

ADMS Meteorology Effects Typical atmospheric conditions within the UK. Pasquill - Gifford Stability Classes as modelled in ADMS No exact correlation between boundary layer parameters Stability Class Wind Speed (m/s) Boundary Layer Height (m) Monin – Obukhov Length (m) Conditions A Convective - Hot Still Day B Convective C Convective D5800∞Neutral - Normal UK Day E Stable F210020Stable - Still Night G11005Stable

ADMS Example of A – G Conditions Stack Release –SO 2,150 g/s –50 m stack –5 m diameter, –20 m/s velocity –15°C

ADMS A – G conditions Centre Line Ground Level Concentrations

ADMS A1 Conditions Contour Plot Convective - Hot Still Day

ADMS D5 Conditions Contour Plot Neutral - Normal UK Day

ADMS F2 Conditions Contour Plot Stable - Still Night

ADMS Buildings Can have significant effects –Entrain pollutants into leeward cavity of building –Increased concentrations close to building –Decreased concentrations further away –Only relevant if >1/3 stack height –ADMS allows 10 buildings

ADMS Building Effects – Tall Stack Tall Stack –Release of NOx from a 50 m stack (3 m diameter, 5 m/s velocity, 30°C, 1 g/s NOx) –Unstable weather conditions –Stack is at the centre point of the building –Building is 30 m high, 30 m wide, 67 m long

ADMS Tall Stack – No Building

ADMS Tall Stack – With Building

ADMS Building Effects – Short Stack Short Stack –Release of NOx from a 35 m stack (3 m diameter, 5 m/s velocity, 30°C, 1 g/s NOx) –Unstable weather conditions –Stack is at the centre point of the building –Building is 30 m high, 30 m wide, 67 m long

ADMS Short Stack - Without Building

ADMS Short Stack - With Building

ADMS Topography Can effect dispersion –Changes plume trajectory –May increase or decrease concentrations –Include if terrain exceeds 1:10 (maximum 1:3) –Terrain data available from Ordnance Survey

ADMS Topography Example –Release of NOx from a 65 m stack –5 m diameter –5.25 m3/s flowrate –69°C, –1 kg/s NOx –Neutral weather conditions 10 m/s wind Boundary layer 1000 m –Simple hill 2.6 km to the East and 1 km South of the release

ADMS Without Hill

ADMS With Hill

ADMS 3D Hill

ADMS Statistical Meteorology 10 years statistical data 1 – 5 years hourly sequential data Can calculate –Annual averages –Percentiles (worst case conditions) –No of exceedences/year –Areas affected Direct comparison with UK Legislation (NAQS, PPC)

ADMS Statistical Results

ADMS Statistical + Topography Reproduced from Ordnance Survey® Panorama Digital Data, by permission of Ordnance Survey® on behalf of the Controller of Her Majesty’s Stationary Office. © Copyright All rights reserved. Licence No

ADMS Digital Maps Available from Ordnance Survey 1:50000 or 1:10000 Can overlay release contours onto maps

ADMS Digital Map Example Reproduced from Ordnance Survey® 1:10K Raster Data, by permission of Ordnance Survey® on behalf of the Controller of Her Majesty’s Stationary Office. © Copyright All rights reserved. Licence No

ADMS Digital Map + Topography + Concentrations Reproduced from Ordnance Survey® Panorama Digital Data and1:10K Raster Data, by permission of Ordnance Survey® on behalf of the Controller of Her Majesty’s Stationary Office. © Copyright All rights reserved. Licence No

ADMS Odours Model as Odour Units –ou: Number of times the mixture must be diluted at STP to reach detection limit of 1 ou. –ou E : The mass of pollutant that when evaporated into 1m 3 of gas at STP is 1 ou. –Information on detection limit is required. ADMS –Input and output in terms of ou or ou E.

ADMS Odour Example Release from landfill site –Odours in ou E –Two area sources, one line source Landfill 1: 100 m x 100 m, 10 ou E /m 2 /s Landfill 2: 100 m x 100 m, 5 ou E /m 2 /s Line 1: 200 m, 2 ou E /m/s –Flat terrain, no buildings –Neutral conditions 10 m/s wind Boundary layer 1000 m –Short term hourly average concentration

ADMS Odour Example - Sources

ADMS Odour Example - Results

ADMS Time Varying Releases Release rates often vary with production Time varying releases –Hourly sequential meteorological data –Details of release for each hour of met data flow, temperature, concentration, velocity Results can differ considerably when compared to average releases

ADMS Fluctuations Meteorology usually stable over 1 hour Turbulence causes short duration fluctuations Interest in lower times for exposure –Odours –NAQS (SO 2, 15 minute mean) ADMS turbulence calculations –Percentiles –Probability distribution function –Toxic response

ADMS Other Features Variable surface roughness Treatment of land sea internal boundary layer Puffs NOx Chemistry Radioactive decay Plume visibility (condensed plume)