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AirWare : urban and industrial air quality assessment and management Release R5.3 beta

AirWare : urban and industrial air quality assessment and management Release R5.3 beta. DDr. Kurt Fedra Environmental Software & Services GmbH A-2352 Gumpoldskirchen AUSTRIA info@ess.co.at http://www.ess.co.at/AIRWARE. Update Release R5.3. Emission data and modelling:

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AirWare : urban and industrial air quality assessment and management Release R5.3 beta

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  1. AirWare: urban and industrialair quality assessment and managementRelease R5.3 beta DDr. Kurt Fedra Environmental Software & Services GmbH A-2352 Gumpoldskirchen AUSTRIA info@ess.co.at http://www.ess.co.at/AIRWARE

  2. Update Release R5.3 Emission data and modelling: • Emission inventories • Editing, analysis, matrices, export • Emission scenarios • Editing, analysis, matrices, export • Emission modelling: • Estimation methods • Dynamic patterns

  3. Emission inventories Organised by: • Source type • Industrial plants • Boilers and stacks • Small point sources • Area sources • Line sources • Geographical domain

  4. Emission inventories Industrial plants: • Name, meta data, (owner, creation and modification dates, contact, documents) • Location (map) and description (HTML) • Attributes: • Start/end of operation, No.of stacks, power rating, volumetric flow, mass flux; • Emissions (total) • Boilers (emissions, TS, patterns)

  5. Contact and administrative data Optional for emission sources: • Contact address • Owner/operator profile/details • Contact person and data • Chronological log of contacts (e.g., permits, inspections, modifications, etc.) • Optional documents link (PDF, doc, PS, HTML)

  6. Boilers and stacks: Name and meta data, contact, documents, MS location tool; • Map and description • Attributes: • Stack parameters, technology, fuel/consumption, status • Emission data: • Totals by substance, NO/NO2 ratio • Emission time series (optional) • Emission pattern • Emission factors

  7. Emission inventories Small point sources (stacks) Selection from sorted lists by: • Name • Type (user defined) • Emissions (user selected substance) • From the map (under development, requires zooming  R5.4)

  8. Emission inventories Small point sources (stacks) • Name and meta data, description (optional) documents, monitoring station location • Attribute list (user defined, e.g., symbolic location, construction year. Classification, status, stack parameters); • Emission data • By substance, NO/NO2 ratio • Emission pattern • Emission factors

  9. Emission inventories Small point sources (stacks) Location: • Selection of background map from the map catalogue • Positioning (coordinates or on the map) • Definition of zooming (area around the source shown)

  10. Emission inventories Area sources • Name and meta data, contact, documents, geometry (polygon) import • Attributes: • Location, classification, • fuel/consumption, area, emission height • Emission data: • Substance specific rates, No/NO2 ratio • Emission pattern • Emission factors

  11. Emission inventories Line sources: • Name and meta data, geometry import (poly-line), near-field model (event) • Attributes: • Symbolic location, status, classification • Main vehicle categories (passenger cars, LDV, HDV, busses, and total frequency • Fleet composition (optional)

  12. Inventories by domain: • Compiles all sources with any user defined rectangular area, defined as a “domain object” in the data base; • Summary statistics can be recomputed after editing • Domain specific inventories can be displayed and exported as matrices (CSV format)

  13. Emission scenarios Part of model scenarios that define: • A model and substance • A geographical domain • A date or period Emission scenarios: • Include hypothetical sources • Multipliers for source classes • Toggle individual sources on/off

  14. Emission modelling Emission estimates: All estimated values are marked with * • NO/NO2/NOx and NO/NO2 ratio • Indirect estimates: • From fuel type and fuel consumption • From traffic frequency, fleet composition, vehicle type/speed dependent emission rates, cold start fraction and correction • All categories user defined !

  15. Emission modelling Emission estimates: • Emission factors for any user defined activity (default: fuel consumption) and substance combination (uses a linear function of activity level) • piecewise linear extension  R5.4

  16. Emission modelling Temporal patterns: Associated with classes/types or individual sources; Specify multipliers of the long-term annual average emission by • Month (12) • Day of the week (7) • Hour of the day (24) To generate a dynamic emission estimate for every hour of the year

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