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Network Assessment Based on Estimation Uncertainty

Network Assessment Based on Estimation Uncertainty. Prepared for EPA OAQPS Richard Scheffe by Rudolf B. Husar and Stefan R. Falke Center for Air Pollution Impact and Trend Analysis, CAPITA Washington University, St. Louis December 2000. AQ Management Activity. Geographic Info. Need.

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Network Assessment Based on Estimation Uncertainty

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  1. Network Assessment Based onEstimation Uncertainty Prepared for EPA OAQPS Richard Scheffe by Rudolf B. Husar and Stefan R. Falke Center for Air Pollution Impact and Trend Analysis, CAPITA Washington University, St. Louis December 2000

  2. AQ Management Activity Geographic Info. Need Station Measure Risk assessment Pollutant concentration 4th highest O3 Risk Assessment Persons/Station Compliance evaluation Conc. vicinity to NAAQS Deviation from NAAQS Reg./local source attribution & tracking Spatial coverage Area of Sampling Zone All above Estimation uncertainty Meas. & est. difference Network Assessment Based on Estimation Uncertainty • There are at least five different measures that represent the information need for (1) risk assessment, (2) compliance monitoring and (3) tracking are listed below. • Estimation uncertainty measures the ability to estimate the concentration at a station location using data from all other stations. • The station with the highest deviation between the actual and the estimated values (i.e. estimation uncertainty) is ranked #1. In other words, the stations who’s values can be estimated accurately from other data are ranked (valued) low. Persons in sampling zone

  3. Concentration Error, E • The concentration error is determined by • selectively removing each site from the database • estimating the concentration at that site by spatial interpolation • setting the error as the difference between the estimated and measured values, E = Est.-Meas. The error estimates in both metric of ozone concentration over the Eastern US ranges between 0-15 %. High estimation error is generally observed over areas with low station density. Low estimation error generally occurs over areas with high station density

  4. Concentration Estimation Error (~ 5-6 ppb) • For the entire dataset, the measured and estimated data have the same avg. and a slope of 1. • The standard deviation of the meas.-est. difference is about 5 ppb, no bias. • The estimation error is also random in space. • The CastNet network characterizes the non-urban concentrations. • The estimation error for CastNet data is the same as for the entire network. • This implies that the errors are random.

  5. Ranking by Estimation Uncertainty • The uncertainty measures the ability to estimate the concentration from other data. • The highest uncertainty (red) is found urban stations where the concentrations are highly variable in space and time. • The lowest uncertainty (blue) is at remote sites where the concentrations are more homogeneous in space and time • From the perspective of estimation uncertainty, the blue stations have the lowest rank.

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