improving data quality in ceidars vijay bhargava emission inventory workshop air resources board...

Improving Data Quality in CEIDARS

Vijay BhargavaEmission Inventory Workshop

Air Resources BoardMarch 13, 2006

Air Resources Board

Emission Inventory Workshop Spring 2006

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Improving Data Quality in CEIDARS

What “quality data” means Why we need quality data Data quality issues QA/QC in CEIDARS QA reports in CEIDARS

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Accurate Complete Consistent Timely Fulfills end user needs

What “Quality Data” Means?

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Visibility of data Rule Development Air Quality Planning Photochemical Modeling Fee Programs NEI

Why We Need Quality Data?

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Incorrect SCC/SIC assignments Missing /incorrect Temporal Data Missing/incorrect UTM/stack data Missing /incorrect control equipment

data Missing speciation data

Data Quality Issues

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Example: Metal manufacturer

Facility sic 2514 With wood parts coating operation

Process SCC: 40201901 Wood furniture coating

Process SIC: 2514 Metal furniture manufacturing

This is an invalid combination

Incorrect SCC/SIC Assignments

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Create errors in: Categorization Reconciliation Chemical speciation Assignment of control and growth profiles

Which impacts Photochemical modeling Control strategy development Attainment plans


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Solution: Use valid combination

Process SCC: 40201901 wood furniture coating

Process SIC: 2511 wood furniture manufacturing

Facility SIC describes overall activity Facility SIC: metal furniture manufacturing


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Example: Hours/day, days/week, weeks/year, and

monthly activity fields Create errors in:

Temporal distribution of emissions

Missing/Incorrect Temporal Data

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Which Impacts Seasonal planning inventories Photochemical modeling Weekday/ weekend studies

Solution: provide temporal data for each process

Missing/Incorrect Temporal Data

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Example: Facility UTM and stack UTM fields Stack height, diameter fields Stack gas flow rate and temperature

fields Creates errors in:

Geographical location of emissions Calculation of “effective plume height”

Missing/IncorrectUTM/ stack/release point data

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Which impact: Photochemical modeling

Ozone studies Model validation

Health risk assessments Solution:

Provide UTM data for each facility and stack

Provide stack physical parameters

Missing/IncorrectUTM/ stack/release point data

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Example: Primary and secondary control device

fields Control efficiency field

Creates errors in: Controlled vs. uncontrolled emissions Identified control equipment used

Missing/ Incorrect Control Equipment data

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Which impact: Control strategy planning Rule development

Solution: Provide control device codes and/or

control efficiency for each controlled pollutants

Also provide uncontrolled and uncontrolled emission factors

Missing/ Incorrect Control Equipment data

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QA\QC Checks in CEIDARS

QA checks before the updates QA checks during the update

process QA checks after the updates

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FIGURE III - 3CEIDARS 2.5 UPDATE PROCESS

CURRENT YEAR DATABASE

MIX OF ROLLEDOVER ANDREVISED

POINT SOURCES

DistrictPoint Source

Updates

ARBOff-road Model

ARB On-road Model

ARBArea Source

Updates

DistrictArea Source

Updates

EXISTING DATABASE

Point SourcesRolled Over

Q1

Q1

Q2 Q2

Q3

Reconciliation

MIX OF GROWNAND

REVISEDAREA SOURCES

DRAFTPOINT SOURCES

LabelDRAFTAREA SOURCES

ALL REVISEDPOINT SOURCES

Total

Q1

PartialUpdates

Replacemrent

Is it a ful or

partial update?

Area Sources Grown to

Curent Year

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Pre-update QA checks

Replacement vs. selected updates Point and/or Area Sources Criteria and/or Toxics Data AB2588 or Annual updates Data Format Orphaned and widowed

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QA Checks during Update

On-line or Batch Updates Data Type Domain and Range Key and Required Fields Child without Parent

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Post-update QA Checks

QA Reports Summary Reports Reconciliation Reports

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QAFCC- Facility records with no emission data QAPRO - Process records with no emission data QASTACK - Stack records with no emissions data QADEV - Device records with no emissions data QAKEYS - KEY data QAKEMS - codes and emissions QATEMP - UTM, temporal and monthly activity QASTACK- stack parameters

Quality Assurance Reports

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QADP - device and process data QACNTL - control device and emission

factors Reconciliation - point and area source data Summary Reports

Quality Assurance Reports

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Fixing QA|QC Errors

Rejects Warnings Filling the Gaps

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Conclusion

“If you don’t have time to do the job right the first time, how will you have time to do it over again?”

Credibility of Data Tools are available to improve data

quality

improving data quality in ceidars vijay bhargava emission inventory workshop air resources board...

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