ANALYSIS OF TRACER DATA FROM URBAN DISPERSION EXPERIMENTS Akula Venkatram and Vlad Isakov  Motivation for Field Experiments  Field Studies Conducted.

Slides:



Advertisements
Similar presentations
AIR POLLUTION AND METEOROLOGY
Advertisements

A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.
1 RLINE: A Line Source Dispersion Model for Near-Surface Releases Presented at the 12 th Annual CMAS Conference, Chapel Hill, NC October 28 – 30, 2013.
Field experiment on the effects of a nearby asphalt road on temperature measurement Mariko Kumamoto 1, Michiko Otsuka 2, Takeshi Sakai 1 and Toshinori.
 Provides natural ventilation and usually cools buildings/people because it accelerates the rate of heat transfer  Speed and direction change throughout.
OpenFOAM for Air Quality Ernst Meijer and Ivo Kalkman First Dutch OpenFOAM Seminar Delft, 4 november 2010.
Performance of Air Quality Models in Urban Areas  Objectives and Motivation  St. Louis study and ISC urban  Model Improvements  Performance of Improved.
Meteorological Data Issues for Class II Increment Analysis.
Will Pendergrass NOAA/ARL/ATDD OAR Senior Research Council Meeting Oak Ridge, TN August 18-19, 2010 Boundary–Layer Dispersion Urban Meteorology 5/20/2015Air.
ADMS ADMS 3.3 Modelling Summary of Model Features.
Module 9 Atmospheric Stability Photochemistry Dispersion Modeling.
The impact of boundary layer dynamics on mixing of pollutants Janet F.Barlow 1, Tyrone Dunbar 1, Eiko Nemitz 2, Curtis Wood 1, Martin Gallagher 3, Fay.
FIELD EXPERIMENT MUST Short Term Scientific Mission, COST 732 Efthimiou George 1, Silvia Trini Castelli 2, Tamir Reisin 3 31 March - 5 April 2008, Torino,
Influence functions for the WLEF tower (z=400m) for the June, July, August and September 2000 Simulation: RAMS v4.3 with two nested grids (Δx=100km and.
Modeling approach to regional flux inversions at WLEF Modeling approach to regional flux inversions at WLEF Marek Uliasz Department of Atmospheric Science.
NATO ADVANCED STUDY INSTITUTE, Kyiv, May 2004 Detailed numerical modeling of local atmospheric dispersion in an idealized urban area M. Milliez, S. Panzarella,
C. sampling strategy D. source configuration F. source-receptor matrix I. estimation of fluxes J. strategy evaluation uncertainty G. concentration pseudo-data.
A Basic Introduction to Boundary Layer Meteorology Luke Simmons.
Temperature, Buoyancy, and Vertical Motion Temperature, Pressure, and Density Buoyancy and Static Stability Temperature “Lapse Rates” Rising & Falling.
Power Generation from Renewable Energy Sources Fall 2013 Instructor: Xiaodong Chu : Office Tel.:
Air Quality Modeling.
Dispersion due to meandering Dean Vickers, Larry Mahrt COAS, Oregon State University Danijel Belušić AMGI, Department of Geophysics, University of Zagreb.
1 Air quality modeling – Neighborhood/urban scales Darko Koracin Desert Research Institute, Reno, Nevada, USA Vlad Isakov NOAA/EPA, Research Triangle Park,
Investigation of Meteorological Tower Siting Criteria Ken Sejkora Entergy Nuclear Northeast – Pilgrim Station Presented at the 15 th Annual RETS-REMP Workshop.
CHAPTER 5 Concentration Models: Diffusion Model.
Yamada Science & Art Corporation PROPRIETARY A Numerical Simulation of Building and Topographic Influence on Air Flows Ted Yamada ( YSA.
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.
Stephan F.J. De Wekker S. Aulenbach, B. Sacks, D. Schimel, B. Stephens, National Center for Atmospheric Research, Boulder CO; T. Vukicevic,
CONCEPTUAL MODELING PROTOCOL FOR THE NEIGHBORHOOD ASSESSMENT PROGRAM.
Modeling Overview For Barrio Logan Community Health Neighborhood Assessment Program Andrew Ranzieri Vlad Isakov Tony Servin Shuming Du October 10, 2001.
”On the sensitivity of Building Performance to the Urban Heat Island Effect” By Adil Rasheed, Darren Robinson, Alain Clappier.
The Pattern and Transport of Ozone in the Missouri Region Rudolf Husar and Bret Schichtel CAPITA Washington University April 9, 1997 Prepared for a briefing.
Combining HYSPLIT and CMAQ to resolve urban scale features: an example of application in Houston, TX Ariel F. Stein (1), Vlad Isakov (2), James Godowitch.
Estimating local versus regional contributions to tropospheric ozone: An example case study for Las Vegas Mark Green and Dave DuBois Desert Research Institute.
Observational and theoretical investigations of turbulent structures generated by low-Intensity prescribed fires in forested environments X. Bian, W. Heilman,
1/26 APPLICATION OF THE URBAN VERSION OF MM5 FOR HOUSTON University Corporation for Atmospheric Research Sylvain Dupont Collaborators: Steve Burian, Jason.
Meteorology & Air Pollution Dr. Wesam Al Madhoun.
Building Aware Flow and T&D Modeling Sensor Data Fusion NCAR/RAL March
A canopy model of mean winds through urban areas O. COCEAL and S. E. BELCHER University of Reading, UK.
Prof. Jiakuan Yang Huazhong University of Science and Technology Air Pollution Control Engineering.
Stable Atmosphere.
1 Microscale Air Dispersion Modeling Community Health Neighborhood Assessment Program Working Draft Do Not Cite or Quote Tony Servin, P.E. October 10,
Melanie Follette-Cook (MSU/GESTAR) Christopher Loughner (ESSIC, UMD) Kenneth Pickering (NASA GSFC) Rob Gilliam (EPA) Jim MacKay (TCEQ) CMAS Oct 5-7, 2015.
CITES 2005, Novosibirsk Modeling and Simulation of Global Structure of Urban Boundary Layer Kurbatskiy A. F. Institute of Theoretical and Applied Mechanics.
Urban Heat Island and Pollution
1 Tracer Experiments Barrio Logan Working Draft Do Not Cite or Quote Tony Servin, P.E. Shuming Du, Ph.D. Vlad Isakov, Ph.D. September 12, 2002 Air Resources.
Office of Research and Development Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory Simple urban parameterization for.
Types of Models Marti Blad Northern Arizona University College of Engineering & Technology.
Consequence Analysis 2.2.
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.
Validation of urbanSTREAM Using JU2003 CRTI RD Project Review Meeting Canadian Meteorological Centre August 22-23, 2006.
NUMUG - Oct Atmospheric Stability – Methods & Measurements Robert F. Yewdall PSEG Nuclear LLC.
The Arctic boundary layer: Characteristics and properties Steven Cavallo June 1, 2006 Boundary layer meteorology.
Challenges in PBL and Innovative Sensing Techniques Walter Bach Army Research Office
DAPPLE wind tunnel studies Hong Cheng Tom Lawton Paul Hayden Sandro Baldi Matteo Carpentieri Alan Robins.
Anemometry 4 The oldest known meteorological instrument about which there is any certain knowledge is the wind vane which was built in the first century.
Producing Meteorological Fields for Local Scale Pollutant Transport and Dispersion Estimates 1)Using the CALPUFF modeling system. 2)The model system produces.
Measuring meteorology in urban areas – some progress and many problems Ekaterina Batchvarova 1, Sven-Erik Gryning 2 National Institute of Meteorology and.
Comparisons of CALPUFF and AERMOD for Vermont Applications Examining differing model performance for a 76 meter and 12 meter (stub) stack with emission.
LA-UR The Effect of Boundary-Layer Scheme on WRF model simulations of the Joint Urban 2003 Field Campaign Matthew A. Nelson1, M. J. Brown1, S.
Performance of a new urban land-surface scheme in an operational mesoscale model for flow and dispersion Ashok Luhar, Marcus Thatcher, Peter Hurley Centre.
A New Method for Evaluating Regional Air Quality Forecasts
Consequence Analysis 2.1.
AERLINE: Air Exposure Research model for LINE sources
Air Pollution Dispersion Lab
Suggested Analyses of WRAP Drilling Rig Databases
Models of atmospheric chemistry
Meteorology & Air Pollution Dr. Wesam Al Madhoun
Presentation transcript:

ANALYSIS OF TRACER DATA FROM URBAN DISPERSION EXPERIMENTS Akula Venkatram and Vlad Isakov  Motivation for Field Experiments  Field Studies Conducted in Barrio Logan  Results from Current Models  New Modeling Approach  Results  Future Work

Motivation u Few experiments conducted for ground-level releases in urban areas. –St Louis Experiment in 1968 u Little data for near source dispersion u Data set is specific to Barrio Logan

Urban Effects on Dispersion Stable air from the rural area becomes unstable when it flows over warmer urban area Roughness increases turbulence and decreases wind speed

Field Experiments Tracer studies designed to study dispersion at scales of meters to kilometers in urban areas. –Near source experiment at Memorial High, April 2001 –CE-CERT parking lot study, April-May 2001 –Summer and winter Barrio Logan field studies –Dugway Proving Grounds Model Study

Near Field Dispersion-tens of meters SF 6 released at ground level in a school playground in an urban area u Source surrounded by two arcs at 10 and 20 meters u Flow measured with sonics, propeller anemometers, and mini-sodar u Real time analysis of data

Near source dispersion  v is comparable to effective wind speed transporting plume u Upwind dispersion becomes important u Plume model might not be applicable

Near Field Dispersion Experiment at BL Memorial School (April 7 – 14, 2001)

Concentration Pattern on 4/14/01

Concentration Pattern on 4/13/01

Concentration Pattern on 4/12/01

CE-CERT Parking Lot

CE-CERT Model Comparison

Low Wind Speed Model The horizontal distribution is written as:

Tracer Experiment at Barrio Logan l Tracer Experiment conducted in August and December of 2001 l Hourly SF6 concentrations sampled at 50 sites l Tracer released at NASSCO during daytime from 10 a.m. to 10 p.m. l Mobile van sampled continuously to measure crosswind SF6 concentrations l Mini-sodar to measure vertical winds up to 200m at 5m resolution l Six sonic anemometers to measure surface level winds and turbulence

Logan Memorial Wind Rose Nov 1, 1999 to Oct 31, 2000 Sea Breeze (predominately daytime) Land Breeze (predominately nighttime)

Map of Barrio Logan tracer experiment August 2001 yellow dotd - stationary samplers black lines - mobile van locations

Model Performance at 200m on 08/21/2001

Model Performance at 500m on 08/21/2001

Model Performance at 1000m on 08/21/2001

Model Performance at 2000m on 08/21/2001

Model Performance at 200m on 08/25/2001

Model Performance at 500m on 08/25/2001

Model Performance at 1000m on 08/25/2001

Model Performance at 2000m on 08/25/2001

Q-Q Plots for Model Results from 5 days

Model for Urban Areas u Micrometeorological variables used to describe flat terrain dispersion do not apply to urban areas u Formulate model that uses measured turbulence and velocity profiles

Model for Plume Spread

Comparison with Prairie Grass Data

Model Field Study u Understand dispersion in flat terrain at distances of less than 50 m u Examine the effect of increasingly complicated building structures on –Turbulence –Dispersion

Model Field Study u Conducted at Dugway Proving Ground, Utah July 17,18,19, u 13.5 hours under a variety of stability conditions u Velocity and turbulence measured with sonic anemometers u Buildings simulated with barrels

Model Urban Area u 5  9 array of 45 barrels u H=0.91 m and D=0.57 m at spacing of 1.8 m- frontal area/plan area=16% u Propylene released at z=0 and z=H u 6 different configurations to examine the effect of release height and source structure

Concentration Measurements u Tracer measured with 43 PIDs arranged in 3, 50 degree arcs u Arcs at 1.5S, 2.5S, and 4.5S u PIDs at 5 o spacing u PIDs located at z=0.23 m u Four 2 m towers were used to measure vertical profiles u Concentrations measured at 50 Hz

Meteorological Measurements u Turbulence measured with 6 sonics u Sonics mounted on 3 and 5 m towers u Mounted at 0.5, 1.5, 2.2 and 3.5H at various distances from the source u Measurements at 20 Hz

Figure 2. Observed versus Predicted concentration using model plume spreads without obstacle for ground level release

Figure 3. Observed versus Predicted concentration using linear plume spreads with one obstacle in array for ground level release

Figure 4. Observed versus Predicted concentration using model plume spreads with one obstacle in array for ground level release

Figure 6. Observed versus Predicted concentration using model plume spreads with two obstacles in array for ground level release

Future Work u Model might require modification to account for source effects u Need to account for plume meandering-upwind dispersion u Need to evaluate model with CE- CERT data and Barrio Logan winter data