Introduction to PATS Data Quality

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Maximilian Cook
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1 /7/ Introduction to PATS Data Quality October 7, PATSAC Meeting DEQ PATSAC 9 5 & 7 Modeled Concentrations Review 7 Growth Factors Learn about EI, modeling and monitoring data PATSAC Formation Charter, Operating Principles PUBLIC INVOLVE MENT Compare to Benchmarks Identify Regional and Local Impacts Identify % reduction for each source category regionally and locally Review reduction targets for each pollutant regionally and locally Develop criteria to assess reduction strategies Identify /develop initial emission reduction strategies in conjunction with DEQ Point Area Mobile Attend PATSAC meetings, read web materials, provide feedback to PATSAC and DEQ With contractor and internally develop data on emission reductions, benefits and cost of emission reduction strategies for targeted pollutants /sectors Quantify emission reductions including GHGs and criteria pollutants Modify draft emission reduction strategies No Identify implementation tools Projected 7 EI and modeled concentrations Meet regional and local benchmarks? Yes Develop draft recommendations and metrics including 3 year milestones and contingency plan Assess health benefits and costs of recommendations Finalize recommendations Coordinate with local governments, partners EQC consideration and approval DEQ Plan Strategy adoption Comment period, workshops

targets for each pollutant regionally and locally Develop criteria to assess reduction strategies Identify /develop initial emission reduction strategies in conjunction with DEQ Point Area Mobile

2 /7/ Presentation Objectives Introduce aspects of data quality, show varying levels of robustness Show DEQ s qualitative system to describe 7 data Discuss model to monitor comparisons Hear PATSAC input on data quality tools and how best to consider data quality when developing emission reduction measures 3 Overview of how data quality will be used to develop strategies 7 Emission Inventory Run Model Data Quality Analysis 7 Concentrations Estimate percentage reductions needed for each pollutant regionally and locally Develop/identify initial emission reduction strategies for point, area and mobile sources Data Quality Consideration 4

how data quality will be used to develop strategies 7 Emission Inventory Run Model Data Quality Analysis 7 Concentrations Estimate percentage reductions needed

3 /7/ Overview of how data quality will be used to develop strategies 7 Emission Inventory Run Model Data Quality Analysis 7 Concentrations Estimate percentage reductions needed for each pollutant regionally and locally Develop/identify initial emission reduction strategies for point, area and mobile sources Data Quality Consideration 5 Emission Inventory Elements Emission Factors Activity Data Spatial Allocation Growth 5 EMISSION INVENTORY Regulatory Reductions 7 EMISSION INVENTORY 6 3

emission reduction strategies for point, area and mobile sources Data Quality Consideration 5 Emission Inventory Elements

4 /7/ Rating Data Quality What do we know about data quality? How data was produced EPA ratings DEQ ratings How will we use data quality information? Consideration in decision making and recommendations 7 Rating Data Quality A Excellent B Very Good C Good D Acceptable E Variable Emission Factor Direct source test; primarily permitted point source emissions estimates. EPA data, but also contractor and survey data. From EPA documents and/or models. EPA grades for surrogate data used. Source tests do not represent a random sample of the industry or source category. Activity Data Throughput reported directly to ODEQ by permitted facilities or another regulatory authority. Survey results. Activity based on models (for example EPA s nonroad model). Population or number of employees based activity. Limited information (e.g. National average) Spatial Allocation Exact latitude and longitude for a point or line where emissions occur is known (e.g. industrial facilities, highways). Exact latitude and longitude for a polygon where emissions occur is known (e.g. airports). Emission location is known and assigned to the area of a grid cell where the emissions occur (e.g. low traffic volume roadways). Emissions are allocated to a grid cell based on land use qualification (e.g. residential open burning). Emissions are allocated to a grid cell based on land use qualifications but emission location is variable (e.g. construction). 8 4

emissions estimates. EPA data, but also contractor and survey data. From EPA documents and/or models. EPA grades for surrogate data used.

5 /7/ Summary Data Quality Chart for Benzene B e n z e n e Emission Factors (5) Activity (5) Spatial Allocation (5) 5 EI Confidence Permitted Point sources A A A A Dry Cleaners Gas Stations C B A B Airports B B B B Residential Wood Combustion C B C C Construction C C E D Lawn and Garden C C E D Recreational C C B C Marine Commercial C B B B High volume C A A B Rail Low volume C C C C High volume C C A B Road Low volume C C C C Landfills C C A B POTW C C A B Other Non Road C C E D Residential Open Burning C B D C Solvents C C D C Area sources (general) C C E D = does not apply to this source category 9 Overview of how data quality information will be used to develop strategies 7 Emission Inventory Run Model 7 Concentrations Monitoring Data Estimate percentage reductions needed for each pollutant regionally and locally Develop/identify initial emission reduction strategies for point, area and mobile sources Data Quality Consideration Data Quality Analysis 5

volume C C A B Road Low volume C C C C Landfills C C A B POTW C C A B Other Non Road C C E D Residential Open Burning C B D C Solvents C C D C Area sources (general) C C E D = does not apply to this

6 /7/ Comparisons 9% of estimated concentrations are within a factor of two of monitored concentrations Acceptable model performance DEQ 5 Monitoring Locations 6

7 /7/ DEQ 5 Modeling Locations 3 Example Charts. Compare Values Modeled concentration in km radius of monitor. Ratio Values Monitored Concentration Modeled / Monitored Range of acceptable model performance within a factor of two = between.5 and

Ratio Values Monitored Concentration Modeled / Monitored Range

8 /7/ ABC =.5 ug/m3 Nickel.4.. Nickel, ug/m modeled monitored N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr Lead ABC =.5 ug/m3.4.. Lead, ug/m N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr 8

9 /7/ Manganese ABC =.9 ug/m3.5.4 Manganese, ug/m modeled monitored N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr Arsenic..5 Arsenic, ug/m N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr 9

10 /7/ Cadmium.4.3 Cadmium, ug/m N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr Benzene Benzene, ug/m modeled monitored 4 3 N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr

Vancvr Benzene 9 8 7 Benzene, ug/m3 6 5 4 3.

11 /7/ Formaldehyde Formaldehyde, ug/m modeled monitored.5.5 N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr Acetaldehyde.5 Acetaldehyde ug/m N Rosln Beavtn SE Laf Post Off Kell&Cur Vancvr

3.5.5.5. modeled monitored.5.5 N Rosln Beavtn SE Laf

12 /7/ Overview of how data quality information will be used to develop strategies 7 Emission Inventory Run Model Data Quality Analysis 7 Concentrations Estimate percentage reductions needed for each pollutant regionally and locally Develop/identify initial emission reduction strategies for point, area and mobile sources Data Quality Consideration 3 Discussion Items How is DEQ s data quality tool useful to PATSAC? Based on the presentation, are there any other ideas, concerns, or suggestions as we go forward? 4

initial emission reduction strategies for point, area and mobile sources Data Quality Consideration 3 Discussion Items How is

13 /7/ Appendix 5 Definitions: Emission Factor Rating A = Excellent. Direct source test; primarily permitted point source emissions estimates. B = Very Good. EPA data, but also contractor and survey data. DEQ unable to determine a rating factor from documentation, however a B rating assigned since much of the data was survey data or contractor/workgroup reviewed. C = Good. From EPA documents and/or models where DEQ staff unable to determine a rating factor either from EPA documentation or through contact with EPA. D = Acceptable. Rated EPA surrogate data used. E = Variable. EPA has rated the data E: Source tests do not represent a random sample of the industry or source category, and there may be variability within the source category population. 6 3

DEQ unable to determine a rating factor from documentation, however a B rating assigned since much of the data was survey data or contractor/workgroup reviewed. C = Good.

14 /7/ Definitions: Activity Data A = Excellent. Throughput reported directly to ODEQ by permitted facilities or another regulatory authority. B = Very Good. Survey results. C = Good. Activity based on models (for example EPA s nonroad transportation demand model). D = Acceptable. Population or number of employees based activity. E = Variable. Anecdotal information. 7 Definitions: Spatial Allocation Rating A = Excellent. Exact latitude and longitude for a point or line where emissions occur is known (e.g. industrial facilities, highways). B = Very good. Exact latitude and longitude for a polygon where emissions occur is known (e.g. airports). C = Good. Emission location is known and assigned to the area of a grid cell where the emissions occur (e.g. low traffic volume roadways). D = Acceptable. Emissions are allocated to a grid cell based on land use qualification (e.g. residential open burning). E= Variable. Emissions are allocated to a grid cell based on land use qualifications but emission location is variable (e.g. construction). 8 4

7 Definitions: Spatial Allocation Rating A = Excellent. Exact latitude and longitude for a point or line where emissions occur is known (e.g. industrial facilities, highways). B = Very good.

15 /7/ Data Quality Weighting Formula Rating scheme: A = Excellent (), B = Very Good (), C = Good (4), D=Acceptable (8), E=Variable (6). Lower grades are weighted heavier to illustrate that if one of the EI components is more qualitative, then predictive confidence in the emissions is lower. 9 Lead, Arsenic, Manganese and Cadmium Lead, ug/m Manganese, ug/m ABC =.9 ug/m3..4 Arsenic, ug/m Cadmium, ug/m

Lower grades are weighted heavier to illustrate that if one of the EI components is more qualitative, then

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