Information-computational systems for city air quality monitoring - - PowerPoint PPT Presentation

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Information-computational systems for city air quality monitoring - - PowerPoint PPT Presentation

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Information-computational systems for city air quality monitoring and modeling Gordov E.P. Siberian center for Environmental Research and Training, Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, Russia,

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Information-computational systems for city air quality monitoring and modeling

Gordov E.P. Siberian center for Environmental Research and Training, Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, Russia, gordov@scert.ru

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Outlines

History – chemical, biological and nuclear weapon, radiation protection, МАГАТЭ, etc. Air quality monitoring/modeling systems (city – region level) Chemical weather out of scope! USA EPA Localization Europe EEA – monitoring network DERMA AirWare family Australia Asia/Japan – Lecture of Prof. H. Akimoto Russia MGO Moscow Tomsk

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Primary Sources

Nature (vulcano, dust storms, forests, bogs, etc.) Industry Transport Synergy of natural and man-made sources

Concequencies

Survival, security, health, quality of life

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Air Quality Models and Documentation TOXICS AND PERMITTING: California Air Toxics Emission Factors Database (CATEF) Health Risk Assessment Computer Program (HRA) Hot Spots Analysis Reporting Program (HARP) California Puff Model (CALPUFF)CALPUFF is maintained by Earth Tech, Inc. The CALPUFF system of files and documentation are located on Earth Tech's website.http://www.src.com/index.htm Industrial Source Complex Short Term (ISCST3) ModelISCST3 is maintained by U.S.

  • EPA. The ISCST3 system of files and documentation are located on U.S. EPA's

website.http://www.epa.gov/scram001/aqmindex.htm SCREEN3 ModelSCREEN3 is maintained by U.S. EPA. The SCREEN3 system of files and documentation are located on U.S. EPA's website.http://www.epa.gov/scram001/aqmindex.htm T-SCREEN Screening ModelTSCREEN is maintained by U.S. EPA. The TSCREEN system of files and documentaion are located on U.S. EPA's website.http://www.epa.gov/scram001/aqmindex.htm California Line Source Dispersion Model (CALINE-4)CALINE-4 is maintained by the California Department of Transportation (Caltrans). The CALINE-4 system of files and documentation are located on the Caltrans website.http://www.dot.ca.gov/hq/env/air/index.htm Wind Rose Plotting Program (WRPLOT)WRPLOT is maintained by U.S. EPA. The WRPLOT files and documentation are located on U.S. EPA's website.http://www.epa.gov/scram001/aqmindex.htm

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PHOTOCHEMICAL MODELS:California Photochemical Grid Model (CALGRID) Comprehensive Air Quality Model with Extensions (CAMx) SARMAP Air Quality Model (SAQM) METEOROLOGICAL MODELS:California Meteorological Model (CALMET)CALMET is maintained by Earth Tech, Inc. The CALMET is part of the CALPUFF system of files which, along with documentation, are located on Earth Tech's website.http://www.src.com/index.htm Mesoscale Model 5 (MM5) EMISSION INVENTORY MODELS:Motor Vehicle Emission Inventory Model (EMFAC / MVEI7G) Off-Road Emissions Model (OFF-ROAD) Transportation and Land Use Programs Model (URBEMIS 2002) Emissions Modeling System (EMS95) MODELING SYSTEMS:SARMAP Modeling System Environmental Decision Support System (EDSS) Models 3 OTHER MODELS:Census Data Gridding Program (CDGP) SIMPLEV Electric and Hybrid Vehicle Simulation Model OTHER MODELING SITES:U.S. EPA's Library of Air Quality Modeling Software

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DMI Activities

  • Nuclear emergency preparedness (accidental releases of

radioactivity from nuclear installations, terror acts, nuclear bombs, dirty bombs)

  • Nuclear risk assessment
  • Chemical emergency preparedness (accidental releases of

hazardous chemicals from industry or toxic fire, terror acts)

  • Preparedness for bio-terror
  • Veterinary emergency preparedness (airborne animal diseases)
  • Volcanic ash dispersion modelling
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A semi-

  • perational

version of DMI-HIRLAM with 1.4 km resolution and covering Denmark is run

  • n a test basis.

In the process of implementing urban features in the model.

Meteorological Models

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Danish Emergency Response Model of the Atmosphere (DERMA):

  • 3-D atmospheric long-range dispersion model (> 20 km)

developed at DMI

  • Developed mainly for nuclear emergency preparedness
  • Stochastic Lagrangian model using a puff diffusion

parameterization

  • Dry and wet deposition, particle size dependent
  • Radioactive decay
  • Simultaneous calculation for several isotopes
  • Simultaneous calculations for several release points
  • Source term estimation based on monitoring data
  • Uses data from the DMI-HIRLAM or ECMWF NWP models.

Thus able to describe releases from any location in the domains

Atmospheric Long-Range Dispersion Model

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DMI DMI-

  • HIRLAM

HIRLAM

  • T:

0.15°

  • S, G:

0.05° ECMWF global ECMWF global model model

DERMA DERMA

  • 3-D

atmospheric long-range dispersion model

  • Deposition
  • Decay

ARGOS ARGOS

  • Radiological

monitoring

  • Source term

estimation

  • Local-Scale

Model Chain

  • Health

effects

ARGOS Nuclear Decision Support

T S

Meteoro- logist

Q

Interactive use of ARGOS, automatic interface with DERMA using operational ftp-server

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Evaluation of DERMA

DERMA took part in the real-time evaluation of long-range dispersion models based on measurement data of the European Tracer Experiment (ETEX). The model evaluation involved 28 models from Europe, USA, Canada and Japan. DERMA was ranked in the group of models with “excellent performance”.

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http://gis.green.tsu.ru/Website/tomsk/viewer.htm

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Академгородок

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Автоматизированная система контроля радиационной обстановки Томской области (АСКРО). Оперативная информация с постов контроля радиационной обстановки.

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Integrated Integrated Information Information Systems Systems for for Air Air Quality Quality Monitoring Monitoring: : NIS NIS-

  • adapted

adapted ISIREMM ISIREMM System System and and City City of

  • f Tomsk

Tomsk Case Case Study Study

Fedra K., Gordov E.P.* Environmental Software & Services, Austria, *Institute of Atmospheric Optics SB RAS, Russia

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The ISIREMM system is developed under FP5 INCO COPERNICUS-2 Program

ISIREMM project consortium

AUSTRIA Environmental Software & Services GmbH RUSSIA Institute of Atmospheric Optics of the Siberian Branch of RAS Institute of Computational Mathematics and Mathematical Geophysics SB RAS Natural Resources and Oil and Gas Complex Department of Tomsk Regional Administration KAZAKHSTAN Space Research Institute of the Ministry of Education and Science BELARUS Institute of Physics of the National Academy of Sciences of Belarus FRANCE SILOGIC GREECE Aristotle University of Thessaloniki

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MODELS

The screening models The ISIREMM system has a number of embedded and fully interactive screening level regulatory models, primarily based on USEPA Gaussian guideline models such as ISC-3/ AERMOD, and PBM, a dynamic photochemical box model, as well as a dynamic multi-layer Eulerian code using the diagnostic wind model DWM as a pre-processor. These simple but efficient models are coupled to both the emission inventories, meteorological data bases, and monitoring data, and can be run interactively and with a fully graphical use interface with embedded GIS functionality in both short-term (episode) mode or as long-term models to generate seasonal or annual average results. The results of the long-term model, in the form of a source-receptor matrix, are the main input to the optimisation (emission control) module.

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The baseline air quality simulation models The air pollution model system used in ISIREMM was developed by Aristotle University of Thessaloniki. The model system takes into account interactions between the various scales influencing the pollution patterns in the airshed considered and comprises of the models MEMO and MUSE. MEMO is a prognostic mesoscale model, which allows describing the air motion

  • ver complex terrain. Within MEMO, the conservation equations for mass,

momentum, and scalar quantities as potential temperature, turbulent kinetic energy and specific humidity are solved in terrain-influenced co-ordinates. MUSE is a multilayer dispersion model for reactive species in the local-to- regional scale. The atmospheric boundary layer is divided into individual layers the thickness of which is allowed to vary in the course of the day. This variation reflects adequately the dynamics of the atmospheric boundary layer. The upper layer serves as a reservoir layer located just above the boundary layer. A shallow layer adjacent to the ground is used for simulating dry deposition (with the resistance model concept) and other sub grid phenomena. Thanks to the modular structure of MUSE, chemical transformations can be treated using any suitable chemical reaction mechanism.

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Data specifications

Aerosol lidars will provide with 3D aerosol distribution mapped at the city GIS boundary layer and its variation with time (a current polluting aerosol field) and 3-D mapped emissions from a chosen source. A Raman lidar will provide SO2 amount and concentration and their temporal behaviour in emissions from selected high stacks. An acoustic locator (Sodar) data (vertical distribution of temperature and the wind velocity) will be used to model the fate of pollutants in the atmosphere. The all-sky photometer data, which are digital images of the daytime behaviour

  • f industrial plumes and clouds, will be mapped and used for determination of

temperature distribution above the city. The mobile unit equipped with standard and specialised sensors to collect data on air quality and meteorological quantities (temperature, vertical gradient

  • f temperature, wind velocity vector, including its vertical component, etc) will

provide an additional data flow. Data from all above mentioned sensors will be pre-processed and provided in real time to the system server.

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  • 2.5
  • 2.0
  • 1.5
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  • 0.5

0.0 0.0 0.5 1.0 1.5 2.0 2.5

V=2m/s

mg/m**3

29.06.92 / RU-1

0.00 0.06 0.12 0.18 0.24 0.30 0.36 0.42 0.48

Measured (left) and calculated dust concentrations

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  • 100000
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20000 40000 60000 80000 100000 TOMSK

60 80 100 120 140 160 180 200 220 240 260 280 300 320 340

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Т о м с к Т о м с к Ю р г а Ю р г а К е м е р о в о К е м е р о в о А н ж е р о - С у д ж е н с к А н ж е р о - С у д ж е н с к Т о м с к Т о м с к Ю р г а Ю р г а К е м е р о в о К е м е р о в о А н ж е р о - С у д ж е н с к А н ж е р о - С у д ж е н с к Т о м с к Т о м с к Ю р г а Ю р г а К е м е р о в о К е м е р о в о А н ж е р о - С у д ж е н с к А н ж е р о - С у д ж е н с к Т о м с к Т о м с к Ю р г а Ю р г а К е м е р о в о К е м е р о в о А н ж е р о - С у д ж е н с к А н ж е р о - С у д ж е н с к

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12:00

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24:00

22 мая 2000

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  • 15000
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24:00 22 мая 2000

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  • 20
  • 10

10 20

время, ч

1 2 3 4 5

С к о р о с т ь в е т р а , м /с

  • 20
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10 20

время, ч

100 200 300 400

Н а п р а в л е н и е в е т р а , г р а д

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время, ч

4 8 12 16 20

П р и з е м н а я т е м п е р а т у р а , С

22-23 мая 2000 года

1D model

TOR data meteo data

3D model

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Возможности/потребности региона

Интегрированная система мониторинга и прогноза химической погоды в городе/регионе, как часть системы управления в условиях ЧС (природных, антропогенных). Для прогноза развития ситуации и определения ее возможных последствий необходимо постоянно поддерживать мезомасштабную метеомодель. Информационная система: отображение прогнозов, поддержка решений и подготовка и рассылка директив. Предварительная договоренность с Администрацией Томской области о подготовке соответствующей целевой Программы Первые результаты – в соответствующих докладах на конференции

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Спасибо за внимание!