Materials and Methods. Number of monitoring sites and area types overall Egypt TotalSinai Upper Egypt Delta and Canal Alex.CairoArea type 112333Industrial.

Slides:



Advertisements
Similar presentations
Bridging the Gap Between Statistics and Engineering Statistical calibration of CFD simulations in Urban street canyons with Experimental data Liora Malki-Epshtein.
Advertisements

Session 11: Modeling Dispersion of Chemical Hazards, using ALOHA 1 Modeling Dispersion of Chemical Hazards, using ALOHA Prepared by Dr. Erno Sajo, Associate.
A Study of Temporal Variability of Atmospheric Total Gaseous Mercury Concentrations in Windsor, Ontario, Canada Xiaohong (Iris) Xu, Umme Akhtar, Kyle Clark,
TCEQ Air Permits Division Justin Cherry, P.E. Ahmed Omar Stephen F. Austin State University February 28, 2013.
The Use of High Resolution Mesoscale Model Fields with the CALPUFF Dispersion Modelling System in Prince George BC Bryan McEwen Master’s project
EUROPEAN UNION INITIATIVES AND REQUIREMENTS : AIR QUALITY ASSESSMENT AS A POLICY MECHANISM Sonja Vidič Meteorological and Hydrological Service of Croatia.
Distribution of NO 2 concentrations over shooting (400 µg/m 3 per 1 hour) calculated with POLAIR dispersion model using (2004) NO 2 concentrations from.
University of Aveiro Final Meeting and Project Review 23/24 June 2003 Gdansk University of Aveiro Emissions and Air Quality Modelling Department of Environment.
Chapter 3 Space, Time, and Motion. (1) Wind Observations Vectors have both magnitude and direction. Wind is a vector quantity. The components of wind.
WORKING GROUP I MONITORING DATA ANALYSIS AND INTERPRETATION TFMM Workshop, Paris, 2006, Nov 29 –Dec 1.
1 AirWare : R elease R5.3 beta AERMOD/AERMET DDr. Kurt Fedra Environmental Software & Services GmbH A-2352 Gumpoldskirchen AUSTRIA
Distribution of annual mean SO 2 concentrations in µg/m 3 calculated with POLAIR dispersion model using (2004) SO 2 concentrations from the national monitoring.
Map of the Guadalupe Mountains Region NEW MEXICO TEXAS Guadalupe Mtns. Park Map To Carlsbad To El Paso To I-10 Visibility Degradation in Guadalupe Mountains.
Launch Meeting on Cambodia And Laos Initiative for Building Human Resources for the Environment (CALIBRE) Project May 08 – 09, 2008 Goldiana Hotel, Phnom.
1 Modelled Meteorology - Applicability to Well-test Flaring Assessments Environment and Energy Division Alex Schutte Science & Community Environmental.
1 Yu Tong BEIJING MUNICIPAL ENVIRONMENTAL MONITORING CENTER BAQ2002 HONGKONG Dec of 2002 AIR QUALITY MONITORING IN BEIJING.
Introduction to the ISC Model Marti Blad NAU College of Engineering.
fluidyn – PANAIR Fluidyn-PANAIR
1 THE ENVIRONMENT AND MOTOR VEHICLE EMISSIONS. 2 Motor vehicle emissions are major contributors to health risks and environmental damage at the local,
Jenny Stocker, Christina Hood, David Carruthers, Martin Seaton, Kate Johnson, Jimmy Fung The Development and Evaluation of an Automated System for Nesting.
DEVELOPMENT OF ESTONIAN AIR QUALITY MANAGEMENT SYSTEM Supply and Technical Assistance Contract for procurement of Air Quality Management System (AQMS)
Measurement of NO 2 Concentration in Ambient Air in Karachi using Diffusion Sampling By Zia-ul-Islam Director, Pak-EPA.
Air Quality Modeling.
Air Quality Management in Mumbai V.K.Phatak MMRDA.
Air Chemistry GISAT 112. Scientific and Technical Concepts Phases of airborne matter- gases, particles Inorganic and organic chemicals Balancing chemical.
Simulation of European emissions impacts on particulate matter concentrations in 2010 using Models-3 Rob Lennard, Steve Griffiths and Paul Sutton (RWE.
Air Pollution Control EENV 4313
CHAPTER 5 Concentration Models: Diffusion Model.
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.
TAG Progress Report: Landfill Odors Modeling Research C. D. Cooper, CECE Dept., Univ. of Central Fla. December 16, 2008.
Determining Alternative Futures - Urban Development Effects on Air Quality Julide Kahyaoglu-Koracin and Darko Koracin May 2007 Zagreb, Croatia.
The Use of Source Apportionment for Air Quality Management and Health Assessments Philip K. Hopke Clarkson University Center for Air Resources Engineering.
Fig.6a,b. Simulation of wind fields and toluene plumes on (a) May 12 and (b) May 13. Red dot is the beach site. Very low level of toluene was observed.
Online measurements of chemical composition and size distribution of submicron aerosol particles in east Baltic region Inga Rimšelytė Institute of Physics.
Air Dispersion Modeling City of Albuquerque Environmental Health Department Air Quality Program Director: Mary Lou Leonard.
P. Otorepec, M. Gregorič IVZ RS Use of rutinely collected air pollution and health data on local level for simple evaluation of health impact.
| Folie 1 Assessment of Representativeness of Air Quality Monitoring Stations Geneva, Wolfgang Spangl.
Transboundary Air Pollution Plan of Islamic Republic of Iran
Visual Correlation between Air Pollution and Population Density in Major Metropolitan Areas Texas A&M University, Department of Civil Engineering, Applications.
Air Quality Aneta Stefanovska Advisor in international and local eco-networks ETC –ACC visit and regional meeting of West Balkans countries Skopje,
New Techniques for Modeling Air Quality Impacts of DoD Activities Talat Odman and Ted Russell Environmental Engineering Department Georgia Institute of.
August 1999PM Data Analysis Workbook: Characterizing PM23 Spatial Patterns Urban spatial patterns: explore PM concentrations in urban settings. Urban/Rural.
Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division Office of Research and Development.
ENVIRONMENTAL HEALTH INDICATORS: EXPERIENCES IN HUNGARY Tibor Málnási, É. Vaskövi, G. Nádor, A. Páldy “József Fodor” National Center for Public Health,
Bret A. Schichtel Center for Air Pollution Impact and Trend Analysis (CAPITA) Washington University St. Louis, MO, Presented at EPA’s National Exposure.
Sampling and Measurement for Inorganic Gaseous Pollutants.
Types of Models Marti Blad Northern Arizona University College of Engineering & Technology.
Opening Remarks -- Ozone and Particles: Policy and Science Recent Developments & Controversial Issues GERMAN-US WORKSHOP October 9, 2002 G. Foley *US EPA.
Estimating PM 2.5 from MODIS and MISR AOD Aaron van Donkelaar and Randall Martin March 2009.
Using Measurements and Modeling to Understand Local and Regional Influences on PM 2.5 in Vicinity of the PRGS.
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.
NPS Source Attribution Modeling Deterministic Models Dispersion or deterministic models Receptor Models Analysis of Spatial & Temporal Patterns Back Trajectory.
Prof. Jiakuan Yang Huazhong University of Science and Technology Air Pollution Control Engineering.
Stephen F. Austin State University February 27, 2014 Justin Cherry, P.E. Reece Parker TCEQ Air Permits Division.
Ambient air sampling and monitoring Topic 5 Ms. Sherina Kamal.
State ecological monitoring system of Moscow-City.
7. Air Quality Modeling Laboratory: individual processes Field: system observations Numerical Models: Enable description of complex, interacting, often.
N Engl J Med Jun 29;376(26): doi: 10
Exposure to Air Pollution James Tate and Paul Seakins
Modeling of Air Pollutants Dispersion from
AERLINE: Air Exposure Research model for LINE sources
Suggested Analyses of WRAP Drilling Rig Databases
Representative Measurements – AQ-Workshop Bucharest, July 2008
Air Pollution Control EENV 4313
A Review of Time Integrated PM2.5 Monitoring Data in the United States
Dispersion Models Dispersion of pollutants in the atmosphere Models
Institute for Nature Management, Minsk, Belarus
JDS International seminar 2018
Air Quality Management in Mumbai
Presentation transcript:

Materials and Methods

Number of monitoring sites and area types overall Egypt TotalSinai Upper Egypt Delta and Canal Alex.CairoArea type Industrial 94311Urban Residential 33Street/road 3111 Regional/back r Mixed areas Total

Instruments and measurements techniques used in the air quality monitoring network O3O3 COPM 10 NO/NO 2 SO 2 Pollutants ( µ g/m 3 ) (mg/m 3 ) ( µ g/m 3 ) Concentration Units UV- Photometric Absorption Gas Filter correlation (Infrared Absorption) Tapered Filter element oscillating mocrobalance Chemiluminescence Pulsed UV- Flourescens Measurement technique TEI M49 CTEI M 48 C Beta gauge Ambient particulate monitor Thermo Environmental (TEI) M 42 C Thermo Environmental (TEI) M 43 C Instrument type

Air Quality Monitoring Network A full description of the selected monitoring sites (8 sites) used in the study Shoubra El Kheima Area description Highly industrial, very polluted, several small smelters and various industries. Local Sources Lead smelters to the west, north and east of the school, within a few hundred meters. Representativity Very polluted industrial area. Data show the impact of industries on the building. Paramters measuredSO 2, NO 2, TSP, PM10

Abbassyia site Description Regional residential area normally up-wind from Cairo city center, but down-wind from the Shoubra industrial area and Shoubra urban area. Local Sources: No immediate local sources, but regionally exposed. Representativity: Regional urban area. Paramters measuredSO 2, NO 2, O 3 and Meteorology Measurement

Qulaly site Area description: Urban center with dense traffic on the street coming from shoubra and crossing streets into Al Qulaly and to Ramses Station. Local Sources: The area is expected to be highly polluted from traffic in the main railway station area of Cairo. There are small industries north of the site and the whole Shoubra area is located upwind in prevailing wind direction. Representativity: urban central part of Cairo. Paramters measuredSO 2, NO 2, PM10, TSP, and VOC.Measurement

El Gomhoria site description Description: Street canyon in urban area with heavy traffic. Local Sources: Mainly traffic in the general area and around Ramses square (about 300m from the site). Heavy traffic on Gomhoryia street just under the sampler intake. Representativity: Representative for street canyons in central Cairo. Paramters measured SO 2, NO 2, CO, PM10

Fum El Khalig site description Description: Urban center roadside monitoring station with dense traffic on the streets on both sides of the site. Local Sources: The area is expected to be highly polluted from traffic Representativity: Representative for the urban central part of Cairo and specifically near two main roads. Paramters measured SO 2, NO 2, CO

Maadi Site description Description: Residential Local Sources: Mainly Traffic and general activities of people. Representativity: Typical for western Maadi area, near street surrounded by tall trees (slightly more traffic impacted than inside residential Maadi). Paramters measured SO 2, NO 2

Tabbin Site description Area description: Industrial, polluted from several cement factories and others north of the site, and smelters and chemical industries to the south. Local Sources Smelters, steel and iron factories, coke factory within 1 Km to the south, cement factories in the sector north-west to north-east. Representativity: Very polluted industrial area. Data is showing the impact of industries on the building. Paramters measuredSO 2, NO 2, TSP, PM10 dustfall and meteorology Measurement.

10th of Ramadan site description Area description: Some smaller industries 1-km to the north (upwind). Some industries to the west, but the major industries park is located to the south and south east; 2-3 km away. Not expected to be a polluted area. Representativity: Residential area. Paramters measured: SO2, NO2 and PM10 and dustfall. 10 Ramadan station

Dispersion Model Description POLAIR The POLAIR modeling has the fuctionality to simulate the atmospheric dispersion of gaseous polluting agents and fine particles from diverse sources. With the help of mathematical equations, POLAIR can help study the impact of emissions in zones subject to atmospheric pollution. The results are easily interpreted with graphical views depicitng color graded graphs.

Input, output and validation of dispersion model

Plume’s superelevation models Three models are availble to estimate the concentration by dispersion modeling The U.S. Environmental protection Agency (EPA)’s superelevation model; Holland’s superelevation model; Communauté Urbaine de Montréal’s (CUM) regulatory superelevation model. For the majority of study case scenarios, it is highly recommended to use the regulatory EPA model. It takes into account each of the varaibles for the plume’s superelevation and better represents reality.

Plume’s atmospheric dispersion model Gaussian model and associated parameters The Gaussian model is the most used in the world to study dispersion phenomena. This model estimates the pollutants’s concentration in spatial points while taking into account the following factors: the emission’s characteristics, the receiving environment and the meteorolgical conditions.

Interface and menus

Compound under study POLAIR model offers a database on physical, chemical and toxicological properties. The avaiable information is as follows: Name of chemical compound; Chemical formula; Molecular weight; Terminal velocity (can be used at 0m/s as the majority of gases have a density similar to air. This is not the case for particles and heavy metals); Thershold of smell preception; Inferior limits for explosion and flammability; Toxcity threshold; Concentrations profile.

Types of simulation Simulation results can be shown in results in several types of data presentations. The types of simulation can be seen in the results are as follows: With maxima –First hourly maximum; –Second hourly maximum; –Mean concentration on 2h, 4h, 8h and 24 hours. Perecentages of threstholds; Hourly arithmetic mean concentration.

Simulation with threshold overshoot The simulation with threshold overshoot indicate in percentage, the proportions of calculated values that have exceeded the set threshold of concentration. In accordance to the receiving point. The threshold was set according to the maximum permissible values in indicated in the Egyptain Environmental law no. 4/1994.

Passive and hand held samplers Passive samplers have been used for Model verfication along different distances (200m – 2000 m) for some of the monitoring sites (Tabbin- Maadi –Qualaly and Abassyia). Passive samplers is used for surveillance of time integrated SO 2 and NO2 concentration distributions. They have been analyzed in the laboratory after exposure in the field for typically one week.

Results and Discussion

POLAIR dispersion model performance results for SO 2 concentrations prediction using national monitoring stations network in Greater Cairo during 2004 Correlation coefficient, r 2 Fractional error % Normalized mean error % Mean error ( µ g/m 3 ) Ratio of means Calc/Obs Mean Observed ( µ g/m 3 ) Mean Calculated ( µ g/m 3 ) No. of OBS. Monitoring sites Shoubra Abassyia Qualaly Gomohria Maadi th of Ramadan

Distribution of annual mean SO 2 concentrations in µg/m 3 calculated with POLAIR dispersion model using (2004) SO 2 concentrations from the national monitoring network at Abassyia site

Distribution of SO 2 concentrations over shooting (150 µg/m 3 per 24 hours) calculated with POLAIR dispersion model using (2004) SO 2 concentrations from the national monitoring network at Abassyia site

Distribution of SO 2 concentrations over shooting (150 µg/m 3 per 24 hours) calculated with POLAIR dispersion model using (2004) SO 2 concentrations from the national monitoring network at Qualaly site

Annual mean SO 2 : observations versus predictions at some monitoring sites in Greater Cairo during 2004