1. 1 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Multiple dependencies and scenario management in emission inventories Wilfried Winiwarter, Rudi Orthofer ARC systems research Heinrich Humer, Gerald Schimak, Peter Kutschera ARC seibersdorf research (IT)

2. 2 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Overview Emission inventory in general Special IT problems in these tasks Scenario Management Multi dimensional analysis Application service providing (ASP) concept, multi organization platform 100 % Generation from Case-Tool as a general goal

3. 3 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Emission inventory in general From where? How much? What can be done?

4. 4 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Input Data Questionnaire Statistics Emission Factors Temporal Resolution Spatial Resolution Models emi CO = activity X * emifact CO Results Point / Line / Area Emission for SO 2, Nox, NMVOC, CO, CO 2 and PM 10 General tasks of calculation are very simple

5. 5 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Approaches for estimation Bottom up Summing up point sources and results of questionnaires, measurements and statistics to emission results for –counting units –local governmental units –districts –countries Top down Dividing global amounts (disaggregation) to the subunits using statistical information. No detail information is available Example: –Varnish by population

6. 6 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003

7. 7 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Special IT problems in these tasks I Data have to be collected from several primary data sources –periodic updates with different periods necessary –Syntax- and semantic problems –Management problem –Quality assurance (quality and completeness) Goal: –Wide range of simple import facilities of data –Support of basic data acquisition / preparation tools (Excel, flat files, …)

8. 8 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Special IT problems in these tasks II All is changing over time (data and algorithms) –The set of input data depends on state of the art and the focus of the analysis. –Also models can be changed depending on state of the art and the focus of the analysis. –Data and algorithms also depend on the user. Goal: –we need a tool for long term observation, high configurability –we need a minimum set of common conventions

9. 9 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Special IT problems in these tasks III Experts in modeling inventories are not always also experts in operating data management systems –Desktop data analysis tools are not suitable for long term data management –Mixing between data and User Interface –Professional support for database and basic algorithms Goal: –Outsourcing operation of database and basic support of application

10. 10 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 S S C C E E N N A A R R I I O O S S C C E E N N A A R R I I O O S S C C E E N N A A R R I I O O S S C C E E N N A A R R I I O O S S C C E E N N A A R R I I O O All is changing

11. 11 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Scenarios and Groups “Data groups”: –Logical associated set of input and model data (data domain) –A group can consist of table slices or of several database tables –A group has a name and description and can be modified in versions “Scenario”: –A scenario represents for a special question and includes a set of selected versions of data groups. –Scenarios have names and description. –All modifications are logged automatically

12. 12 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Scenario manager Allows comparison of data records of different situations –Different years –Different political strategies –Different models Quality assurance for scenario evaluation Project management tool Version management Not a dumb duplication of data !! No database administrator needed !!

13. 13 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Architecture of database tables Version managed OBJECT_ID SZM_VERSION_REF CREATED_DATE.... Scenario spezific results OBJECT_ID SZENARIO_REF CREATED_DATE.... Parameter lists, constants C_xxxxx Tabellen Historical tables......... VAILD_FROM VALID_TO Gültige Version wird vom Referenz- Datum des Szenarios abgeleitet Valid version is associated in scenario manager. Versions are organisation specific. Calculation algorithms (Simulator) Version managed Reports, dimensions Formulas

14. 14 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Reporting in different Dimensions

15. 15 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Software Architektur: „Three Tier Architecture“ Database-Tier: –Oracle RDBMS 9i –Data model: multi organisation support, Version management, Historical trend analyses without copying ALL data. Application-Server: –Access through Web-Services (SOAP) and WebAccess Client: –Java programs, activated by Java Webstart CASE-Tool –Oracle Designer 2000 + XML-Generators

16. 16 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 System Architecture Oracle Designer 2000 Repository Database Oracle 9i Tomcat Web-Server Navigator / Browser Web access for data Administration Questionnaires Upload of data Configuration is generated.xml multi organisation support Version management Web services, SOAP

17. 17 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Login at the application server Java Web Start for automatic software distribution Supporting of different clients with different characteristics (ASP concept) Platform independent Distributed computing

18. 18 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Scenario browser Switching scenarios Configuring scenarios Browsing input data Importing and exporting of data Filtering and editing 100% generic browser controlled by repository in the CASE tool (XML- Description of data model)

19. 19 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Configuring within a standard CASE tool CASE tool as a backbone repository of generic and specific structures End users see only configured GUIs Definition of presentations of data (Subsets, languages) Generating of XML-Description of user interface layout for each supported organization Automatic distribution of XML- definitions

20. 20 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Data access for Office Application through Web Access 1. Copying a prepared URL 2. Fix position in MS Excel 3. Authentication to the server 4. Receive the results …

21. 21 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 SNAP Code Selected Nomenclature for sources of Air Pollution

22. 22 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Point Sources

23. 23 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Linienquellen Line Sources

24. 24 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Flächenquellen Area Sources

25. 25 ARC SEIBERSDORF RESEARCH INFORMATION TECHNOLOGIES for Safety, Quality and Communications 24. 9. 2003 Special area of interest