Estimating the Value of Data from Non-Governmental Agencies and Citizens to the AIRNow Program Timothy S. Dye 1, Patrick H. Zahn 1, Daniel M. Alrick 1,

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Presentation transcript:

Estimating the Value of Data from Non-Governmental Agencies and Citizens to the AIRNow Program Timothy S. Dye 1, Patrick H. Zahn 1, Daniel M. Alrick 1, John E. White 2, John Birks 3, and Jessa Ellenburg 4 1 Sonoma Technology, Inc. 2 U.S. Environmental Protection Agency 3 2B Technologies, Inc. 4 GO3 Project Presented at the National Air Quality Conferences March 7-10, 2011 San Diego, CA 4068

2 Outline Background Pilot project with GO3 Project –Instrument details –Data comparisons –Data merging and fusion –Results Challenges and benefits for AIRNow

3 Background – Everything Is (or Will Be) Monitored

4 Background – Monitoring by Citizens Citizen science Measurements made by –Citizens –Non-government organizations Data collected –At fixed locations or moving platforms –Indoors and/or outdoors Technology is key –Monitor cost and size –Internet telemetry and reporting

5 Background – Measurement Approaches 1.Miniaturize AQ instruments BAM  EBAM 2BTech ozone instrument 2.Use low-cost, less accurate sensors University efforts Intel Berkeley Do It Yourself (DIY) community Stacey Kuznetsov Carnegie Mellon University Allison Woodruff Intel 2B Technologies, Inc.

6 Background – AIRNow Data coverage –Increased coverage is costly –Many data gaps still exist New mapping systems –Better methods –NASA project data fusion AIRNow ozone monitoring network coverage

7 Pilot Project with GO3 The Global Ozone (GO3) Project –Middle and HS students get monitors –Strong focus on education –Student-run ozone monitoring stations Locations in –U.S. (mostly Colorado) (40) –International (32) GO3 Project

8 Pilot Project with GO3

9 20 Sites (CO Dept. of Public Health and Environment) 31 Sites (GO3 Project, by June 2011)

10 Pilot Project – Data Quality Location: Rifle, Colorado Monitors: AIRNow and GO3 (within 0.5 mi) Period: February through August 2010 GO3 ozone concentration (ppb)

11 Pilot Project – Mapping Data –1-hr ozone data –Focus on Colorado Methods to test 70% 100% 90% 85% Data Data QCMerged Grid Data QCWeighted GridsFused Grid Merged Fused-Weighed

12 Pilot Program – Mapping AIRNow and GO3 monitors in Colorado Locations of AIRNow SitesLocations of GO3 Sites Colorado New Mexico Wyoming

13 Pilot Program – Mapping Merged AIRNow-Tech Sites OnlyAIRNow-Tech and GO3 Sites Mean interpolation error: ppb RMS interpolation error: ppb Mean interpolation error: ppb RMS interpolation error: ppb Concentration (ppb) RMS = Root-Mean-Square 1-hour maximum daily ozone concentrations, 07/15/2010

14 Pilot Program – Mapping Merged Prediction Standard Error (PSE) Measure uncertainty of AQI estimations in regions without monitors PSE was also reduced across the domain GO3 data reduced PSE, especially near the added monitors Large error (PSE ≥ 13 ppb) reduced by roughly 18,000 km 2 The ppb PSE contour has been highlighted (in blue) to illustrate a larger area with low PSE resulting from the inclusion of GO3 data (right). Without GO3 sites Mean PSE = 14.3 ppb Including GO3 sites (shown in pink) Mean PSE = 13.8 ppb

15 Pilot Program – Fused-Weighted AIRNow-Tech Sites OnlyAIRNow-Tech and GO3 Sites Bias: ppb Mean Absolute Error: 0.45 ppb Concentration (ppb) Bias: 0.0 ppb* Mean Absolute Error: 0.02 ppb* *Compares interpolated value to monitor data point 1-hour maximum daily ozone concentrations, 07/15/2010

16 Pilot Program – What’s Next Deliver routine GO3 data for 31 sites to AIRNow Test data fusion as part of NASA project (satellite, model, observations) Post on AIRNow-Tech Evaluate improvement/effect on AIRNow Present results to AIRNow stakeholders and steering committee

17 Challenges and Benefits for AIRNow Data issues –Quality –Reliability –Ownership Representativeness “Gap filling” in data-sparse areas Citizen engagement and involvement

18 Tim Dye Sonoma Technology, Inc. (707) Contact