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LEADS/EMS OVERVIEW

LEADS/EMS OVERVIEW. L eading E nvironmental A nalysis and D isplay S ystem Development Began At Lockheed In Late 1989 To Produce A New Commercial Weather Analysis Product LEADS Grew Out Of Two Military Weather Contracts

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LEADS/EMS OVERVIEW

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  1. LEADS/EMS OVERVIEW

  2. Leading Environmental Analysis and Display System Development Began At Lockheed In Late 1989 To Produce A New Commercial Weather Analysis Product LEADS Grew Out Of Two Military Weather Contracts TESS(3) -- A Navy Program Which Uses Surface Observations And Numerical Forecast Models To Provide Tactical Weather Forecasts For Carrier Fleets Mark IVB -- An Air Force Program Which Uses Satellite Imagery And Analysis Tools To Provide Long-Range Strategic Forecasts In 1994 Lockheed Was Brought Under Contract With TCEQ To Add Pollution In 1997 Information Processing Systems (IPS) Acquired The MeteoStar Product Line WHAT IS LEADS

  3. Near Real-time Data Acquisition Pollution Sensor Data Water Probe Data Conventional Meteorological Surface Data Weather Satellite Imagery (Geostationary) Automated Gas Chromatograph (AutoGC) Upper Air Data Radar Profiler And Acoustic Sounder Visualization Long-term Data Archival EPA Reporting Analysis Ozone Action Day Prediction Transport Studies Pollution Source Determination SYSTEM CAPABILITIES

  4. LEADS DATA PYRAMID EPA AQS Submittal Policy Makers Public Data Customers Review & Validate Data Data Presentation & Analysis Automatic QA/QC Data Collection EMS Configuration LEADS/EMS System Manual Validation Editor Data Report Web Pages AIRNow Web Pages

  5. The Entire Data Collection System Is Closely Integrated The Datalogger And Automatic Gas Calibrator Communicate With Each Other Via A Serial Interface The Interface Was Completely Defined By IPS This Interface Results In Preliminary Data Flagging At The Monitoring Site Based On What The Calibrator Is Doing The MeteoStar LEADS Software That Collects Data From The Datalogger Uses The Native Datalogger Computer-To-Computer Language (cc-sail) The Datalogger Keeps Track Of Which Data Records Have Been Retrieved Simplifies Retrieval Software Retrieval Software Queries Datalogger For Latest Unsent Data Records Data Collection Is Very Forgiving Of Missed Phone Calls, Busy Signals, Network Outages, Etc. SYSTEM INTEGRATION

  6. A Monitoring Site Is Associated With A Fixed Location LEADS/EMS Uses A Nine-Digit Number To Uniquely Identify Each Monitoring Site These Are Known As EPA Site Numbers Or AQS Numbers Or AIRS Numbers The First Two Digits Identify The State And The Next Three Identify The County Where The Site Is Located; The Last Four Are Assigned By The Monitoring Entity And Are Often Not Unique Across A Network The EPA Has Tables Of All States And Counties At Each Monitoring Site, There Can Be One Or More Data Loggers Each Data Logger Requires A Unique Identifier This Is The CAMS (Continuous Ambient Monitoring Station) Number This Is An informal Site Identifier There Can Be A Many-To-One Mapping Of CAMS To EPA Sites DEFINITION OF A SITE

  7. LEADS Uses A Multi-Tier Data Collection System Reduces Load On Any Single Computer Able To Rapidly Reconfigure the Communications Network In The Event Of A Hardware Failure Multi-Stage Archival Of Raw Measurements Possible To Retrieve Data From Any Of The Archive Locations And Reintroduce It Into The System The Datalogger Installed At Each Site Is Capable Of Storing One To Three Weeks Of Data Based On Number Of Instruments The Comms Front-End Processor Communicates With The Dataloggers And Retrieves Data From Them Preliminary Data Checks Are Performed The CFEP Forwards Collected Data To The Main Or Central Processor The CFEP Computers Store Three Months Of Data Once Data Arrives At The Central Processor, It Is Decoded, Checked For Errors, Processed And Stored In A Database POLLUTION DATA COLLECTION

  8. Monitoring Sites Are Serviced By The CFEP Communications Is A Balance Of Cost And Data Retrieval MeteoStar LEADS Nominally Collects Data From Every Site In The System Every 15 Minutes That Means 96 Connections To Every Site Each Day For IDEM, Most Sites Are Connected Via Aircards Data Is Generally Available Within 20 - 22 Minutes From The Time It Is Collected (Based On A 15-Minute Comms Cycle) Data Generally Made Available To The Public Within An Hour Public Data Has Gone Through Automatic QA/QC Checks, But May Change Later Based On Human Review GETTING DATA FROM THE SITES

  9. The LEADS/EMS Data Base Uses A Flat, Packed-Binary Structure There Are Tables For Site Definitions, Parameter Definitions, Etc. The Binary Data Files Are Physically Segregated By Date And Monitoring Site Each Binary Data File Contains All The Measurements From A Monitoring Site For A Specific Day There Are Five Elements That Are Used To Construct A Unique Key For Data Storage And Retrieval Date The Sample Was Collected (In UTC) Time The Sample Was Collected (In UTC) The AQS Number A Five-Digit Parameter Identifier The Parameter Occurrence Code (POC) DATA STORAGE

  10. Standardize Data Handling Insure Consistency Across The Entire Network Minimize Subjective Data Quality Judgements Automate As Much As Possible Instrument Calibrations Periodic Instrument Challenges Data Quality Flagging Rigorously Check The Instruments In Each Station And The Calibration System Perform Automatic Instrument Challenges On A Schedule Augment With Periodic Station Visits To Perform Independent Audits Provide A Set Of Tools For Operators, Validators, And Other Data Customers To View Not Only The Data But QA/QC Information And System Performance As Well LEADS QA/QC PHILOSOPHY

  11. TCEQ, IPS, Coastal (Datalogger), And Dasibi (Gas Calibrator) Developed Interfaces Between The Various Components And Software The Gas Calibrator Communicates Its Status To The Datalogger Which In Turn Sets The Initial Data Quality Flag IPS-Developed Software Examines The Flags Coming From The Datalogger And Determines Whether Or Not To Interpret The Data As Ambient Or Some Type Of Calibration Or Instrument Challenge MeteoStar LEADS Uses Established Methods For Challenging The Various Instruments Five-Point Calibration Three-Point Span Check Span-Zero Check Limit Checks Your Existing Quality Assurance Project Plan (QAPP) Will Most Likely Need To Be Updated To Incorporate LEADS LEADS QA/QC IMPLEMENTATION

  12. The Introduction Of LEADS Will Not Affect Some Things Documentation Of Procedures And Processes Traceability Of Measurements Back To A Basic Standard Independent Instrument Calibration And Certification Independent Station Audits Instrument Maintenance And Upkeep Procedures Major Impacts Of LEADS Ability To Expand Monitoring Network Without Increase In Manpower Higher Data Return High Confidence Level In Quality Of Data Ability To Rapidly Furnish Data To The General Public OTHER QA/QC CONSIDERATIONS

  13. There Are Several Types Of Automatic Quality Checks Calibration Sequences Are Run Periodically Or When Equipment Is Changed To Establish A New Slope And Intercept Span Check Sequences Are Run Weekly To Ascertain Whether Or Not A Particular Instrument Is Drifting Or Malfunctioning - May Also Set A New Intercept Span-Zero Check Sequences Are Run Nightly To Ascertain Whether Or Not A Particular Instrument Is Drifting Or Malfunctioning Any Of These Sequences Can Be Automatically Scheduled On Either The Calibrator Or The Datalogger Any Of These Sequences Can Be Manually Initiated As Necessary QUALITY CHECKS

  14. AUTOMATIC TESTS

  15. Automatic Met Data Checks Optional Upper And Lower Limits Optional NEG Test Optional MUL Test OTHER DATA CHECKS

  16. There Is An Electronic Operator Log On Each Datalogger Web Interface For Viewing Operator Logs Can Also Add Log Entries Via The Web Certain Web Pages Also Trigger Automatic Operator Log Entries Any Change Made By A Data Validator Results In An Automatic Validator Note Entry Web Interface For Viewing Validator Notes Certain Web Pages Also Trigger Automatic Validator Note Entries There Is A Web-Based Contact Manager That Can Be Used To Record Who Operates Sites And/Or Particular Instruments As Well As Who Validates The Data Web-Based Data Reports OPERATIONAL DOCUMENTATION

  17. Web Pages Are Dynamic And Written In Perl Web Pages Run Off A Combination Of Derived Files And The Master Pollution Database Derived Files Automatically Updated By Background Processes Derived Files Generally Contain Data Averages Or Information That Is Not Stored In The LEADS Pollution Database Some Derived Files May Literally Take Hours To Update - The Derived Files Speed Delivery Of Information To Web Users Many Of The Web Pages Display System Health And Status Information WEB INTERFACE

  18. Also Known As Manual Validation Or ManVal Lets You Examine 5-Minute Data As Well As Hourly Averages Data Graphically Displayed Up To One Month Of Data Can Be Displayed Data Validators Use This Interface To Edit Data Requires Specific Privileges In Order To Make Any Changes To Data Can Change Data Flags Can Change Slope And Intercept Wind And Pollution Roses Included In This Interface POLLUTION RETRIEVAL/DISPLAY

  19. MANUAL VALIDATION WINDOW

  20. STATUS INFORMATION • Information About Each Data Point Is Displayed At The Bottom Of The Window • The Information Displayed Is Dynamic And Is Based On The Data Point Located Under The Cursor • Available Information Includes: • Date And Time Sample Was Collected • Sample Value In Engineering Units • EPA Data Flag • The Slope And Intercept Applied To The Measured Voltages • Whether Or Not The Data Point Has Been Validated (Two Indicators) • Whether Or Not There Are Any Validator Notes Attached To The Data • There Are Also Data Entry Areas For Manually Entered Slopes And Intercepts

  21. WHAT’S IN THE DISPLAY

  22. ROSE TYPES • There Are Four Types Of Roses Available • Each Of The Roses Summarizes Data Over The Time Span You Select • Data Is Accumulated Into Each Of The Direction Bins • Wind Rose • This Is A Standard Wind Rose Plot Which Illustrates Wind Speed As A Function Of Direction • Average Concentration Rose • This Pollution Rose Will Display The Average Concentration Of A Particular Pollutant Or Other Parameter Measured At A Monitoring Site As A Function Of Wind Direction • Maximum Concentration Rose • This Pollution Rose Will Display The Maximum Concentration Of A Particular Pollutant Or Other Parameter Measured At A Monitoring Site As A Function Of Wind Direction • Percentile Rose • This Pollution Rose Allows You To Filter Pollution Concentrations In Order To Reject Abnormally High Or Low Readings - The Smaller The Percentile You Select, The Less Data Is Included In The Pollution Rose • Selecting A Percentile Of 100 Is The Same As Selecting A Maximum Concentration Rose

  23. WIND ROSE

  24. POLLUTION ROSE

  25. Sequences Are Composed Of Levels A Level Consists Of A Set Concentration From The Calibrator Introduced Into A Monitor For A Set Number Of 5-Minute Sample Periods Each Level Is Assigned A Letter Code (M, R, S, T, Or G) By The Datalogger -- These Correspond To Various Percentages Of The Instrument Full-Scale A Set Number Of 5-Minute Samples (Usually 1 - 3) In Each Level Are Allowed For Instrument Stabilization The Remaining Samples (Usually 3 - 4) Are Processed By LEADS. QC SEQUENCES

  26. FIVE-POINT CALIBRATION

  27. THREE-POINT SPAN CHECK

  28. TWO-POINT SPAN-ZERO CHECK

  29. Incomplete The Data Did Not Arrive In The Proper Sequence Or There Were Either Too Few Or Too Many Samples At Each Level Invalid The Calibrator Did Not Deliver The Challenge Gas At Correctly Spaced Intervals Failed One Or More Of The Automatic QC Checks Exceeded A Pre-Set Failure Limit -- Data Is Automatically Rejected Accordingly Warning One Or More Of The Automatic QC Checks Exceeded A Pre-Set Warning Limit -- The Calibration Or Span Check Is Still Valid And Is Still Used Passed All Automatic QC Checks Were Passed POSSIBLE QC CHECK FLAGS

  30. Completeness Test Tests To See That Data Arrives In Correct Order And The Correct Number Of Updates For Each Level Are Present Voltage Outlier Tests Are Based On The Measured Voltages From The Instrument Tests To See That No Single Voltage Measurement For A Level Is More Than An Allowed Deviation From The Average Voltage Concentration Outlier Tests To See That No Single Concentration Measurement For A Level Is More Than An Allowed Deviation From The Average Concentration This Test Was Specifically Designed To Catch Calibration System Problems AUTOMATIC TESTS

  31. NO2 Concentration Outlier Based Entirely On NO Channel Performance On Previous Non-Titration Level (M-Level) And Current Titration Level (M*-Level) -- NO2 Voltages Are Not Part Of This Test Tests To See That No Single Concentration Measurement For A Level Is More Than An Allowed Deviation From The Average Concentration Concentration Spacing Tests To See That The Calibrator Is Delivering Evenly Spaced Concentrations Throughout The Instrument’s Range No Concentration For A Level Can Be More Than An Allowed Deviation From The Ideal Concentration AUTOMATIC TESTS (Cont.)

  32. NO2 Concentration Spacing Based Entirely On NO Channel Performance On Previous Non-Titration Level (M-Level) And Current Titration Level (M*-Level) -- Differs From Normal Concentration Spacing Test No Concentration For A Level Can Be More Than An Allowed Deviation From The Ideal Concentration Slope Tests To See That The Instrument Is Responding Correctly. All Instrument Responses Should Be Linear And The Calculated Slope Should Be Near The Ideal Ideal Slopes: CO = 20 Other Pollutants = 1000 (0 - 1000 ppb Instrument Range) Other Pollutants = 2000 (0 - 500 ppb Instrument Range) AUTOMATIC TESTS (Cont.)

  33. Intercept Tests To See That The Instrument Is Responding Correctly And That The Calculated Intercept Is Near The Ideal Ideal Intercept = 0 Precision Tests To See That The Instrument Has A Stable, Linear Response The Voltage Average For Each Level Is Compared To The Calculated Regression Line And Must Be Within Limits Linearity Tests To See That The Instrument Is Holding A Stable, Linear Response The Voltage Average For The T-Level Is Compared To The Line Drawn Between The M-Level And The G-Level And Must Be Within Limits AUTOMATIC TESTS (Cont.)

  34. Zero Tests To See That The Instrument Calibration Is Holding Since The Last Good Calibration Or Span The Voltage Average For The G-Level Is Compared To The G-Level From The Last Good Calibration Or Span And Must Be Within Limits Span Tests To See That The Instrument Calibration Is Holding Since The Last Good Calibration Or Span The Voltage Average For The M-Level Is Compared To The M-Level From The Last Good Calibration Or Span And Must Be Within Limits AUTOMATIC TESTS (Cont.)

  35. NOx Balance Test Tests The Electronic And Flow Balance Between The NO and NOx Channels. Compares The Ratio Of The Average NO2 Span Response To The Average NO Span Response During Non-Titration Steps. Sensitive To NO2 Impurities In NO Cylinder. Impurities Give Positive Errors. Only Affects The Validity Of The NO2 Channel Calibration NO2 Converter Efficiency Test Tests The Efficiency Of the NO2  NO Converter Affects The Validity Of The NO2 And NOx Channel Calibrations AUTOMATIC TESTS (Cont.)

  36. H2S Converter Efficiency Test Tests The Efficiency Of the H2S  SO2 Converter Based On The T-Level And The T1-Level. Test Is Sensitive To Agreement Of The Calibrations Of The H2S Cylinder To The SO2 Cylinder. SO2 Scrubber Efficiency Test Tests The Efficiency Of the SO2 Scrubber AUTOMATIC TESTS (Cont.)

  37. All QC Tests Performed On Calibration,Span Check, Or Span-Zero Data Have Both Warning And Failure Limits Except The Outlier Tests Each Outlier Test Uses Only One Limit But The Test Is Repeated If An Outlier Is Detected. Each Warning Limit Is Chosen Statistically To Represent The 3rd Standard Deviation Value About The Mean Error Of A Test There Should Be Only A 0.27% Probability Of Exceeding A Warning Limit If The Monitoring System Is Working Properly Each Failure Limit Is Intended To Represent The Maximum Error That Will Be Tolerated Without Invalidation Of The Affected Data TEST LIMITS

  38. Automatic Invalidation Of Data Is Based Only On Whether A QC Test Passes Or Fails Warnings Are Not Considered In This Processing Failure Of A Concentration Outlier Test Or A Concentration Spacing Test Indicates A Problem With The Calibration System But Not With The Monitor (Except NO2) The Calibration Or Span Check Event Involved Is Considered Invalid And The Ambient Pollution Data Is Unaffected In The Event Of A Test Failure, Data Is Automatically Rejected (Flagged LIM) To Stop Rejecting Data Forward, A Successful Five-Point Calibration Must Be Run Data Is Rejected Back To The Last Successful Calibration, Span Check, Or Span-Zero Check DATA VALIDATION RULES

  39. Automatic Quality Control Should Be Augmented By Quarterly Manual Span Source Audits Span Source Audits Evaluate The Accuracy Of The Calibrator At Each Site Corrective Action Is Required If Audit Limits Are Exceeded If the Audit Passes, Then the Pollutant Monitor Should Be Adjusted to Agree With the M-level Concentration Produced by the Calibrator This Sets the Slope of the Monitor’s Response to the Ideal If a Slope Test Warning Is Reported Thereafter, Then Action Must Be Taken to Determine If the Error Was Caused by Monitor Drift or Span Source Drift A Span Source Audit May Be Needed If There Are No Obvious Instrument Problems SPAN SOURCE AUDITS

  40. Limits Can Be Defined For A Specific Instrument At A Site Any Parameter Can Have Limit Checks Defined Can Define Either An Upper Or Lower Limit Or Both System Automatically Flags Any Data That Falls Outside Specified Limits As LIM LIM Data Is Automatically Excluded From Averaging And Automatic Alerts UPPER AND LOWER LIMITS

  41. AUTOMATIC MET CHECKS

  42. Only Performed On Hourly Averages - Does Not Affect Five-Minute Averages NEG Test Can Be Defined For Any Parameter That Is Rolled Up Into An Hourly Average Test Will Automatically Set Slightly Negative Averages To 0.0 If Data Is “Too” Negative, It Will Be Flagged NEG Data Flagged NEG Is Automatically Excluded By Other Displays And Analysis Algorithms MUL Test Designed Specifically For NOx Family Tests To Make Sure That Sum Of NO And NO2 Measurements Are Consistent With NOx Measurement If Data Is Not Consistent, All Three Parameters Will Be Flagged MUL Data Flagged MUL Is Automatically Excluded By Other Displays And Analysis Algorithms NEG AND MUL TESTS

  43. There Are Five Basic User Roles System Administrator EMS General Administrator Data Validator Field Operator Weather Forecaster Everyone Has Access To The Same Basic Tools (Reviewing Data, System Operations, Etc.) Certain Roles Have Expanded Capabilities (Such As Changing System Configurations, Etc.) ROLES AND ACTIONS

  44. This Is Administration At The Operating System Level Responsible For System User Accounts Creation Maintenance File Ownership File Permissions Creates Scheduled Tasks Related To Operating System Responsible For Data Backups And Restores SYSTEM ADMINISTRATOR

  45. Administration At The EMS System Level Adding New Sites Monitoring Site Maintenance Log Maintenance General System Health Scheduled Tasks Related To EMS Setting Up And Maintaining Synchronization Communications Data Reloads User Accounts For Web Pages And Manual Validation EMS GENERAL ADMINISTRATOR

  46. Primary Job Is To Ensure Data Meets Quality Objectives Prior To Full Release Manual Validation Tool Designed Around Data Validation Review Of Data Data Flagging Data Recovery Creates Reports For Submission To AQS (Used To Be Called AIRS) Database This Is The Only Role With ManVal Write Permissions DATA VALIDATOR

  47. Responsible For Keeping The Monitoring Sites And Instruments Running Performs Physical Site Maintenance Filter Replacement Scheduled Instrument Maintenance Instrument Removal/Replacement/Repair Should Be Using Available Tools To Review Data And System Performance Use The Operator Log To Keep A Record Of Everything You Do At The Site FIELD OPERATOR

  48. Has Access To Full LEADS Weather Toolkit Can Create Products Overlaying Measured Data From The Sites With National Weather Service Data Can Use The LEADS Tools To Create Custom Pollution Forecast Products Ozone Potential Zones Pinpoint Weather Forecasts Should Be Involved With The Validation Of The Meteorological Data Measured At The Monitoring Sites WEATHER FORECASTER

  49. SYSTEM ARCHITECTURE

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