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SARP Presentation JEN

Date post: 30-May-2018
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    OverviewOverview

    IntroductionBackground

    Where/how the samples were

    collectedMethodology

    Comparing the three datasets

    Coefficient of VariationResults

    Conclusion

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    IntroductionIntroduction

    Airborne sample collection 1000 feet and below

    Ground grid study

    Comparison between data Confirmation

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    BackgroundBackgroundThere were three

    separate samplecollections

    A first flight on July 22nd

    A second flight on July

    24th

    Grid was predetermined by

    Melissa Yang, Ph.D.o Roughly 25 miles between

    centers of each boxo Designed to match up with

    previous grid studieso All samples taken away

    from possible sources(roads, tractors, etc.)

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    BackgroundBackground

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    MethodologyMethodology

    Samples wereanalyzed in theRowland/Blake Labusing gaschromotography

    Two systems wereutilized: the bigsystem and themethane system

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    MethodologyMethodology

    Data filtered 1500 feet

    Data was included where the three

    sampling campaigns overlappedIntroduction of error

    Data from the dairy and vineyardwere discarded

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    Actual Data

    Used

    All datacollectedduringSARP 2009

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    MethodologyMethodology

    Correlation Average concentrations

    Coefficient was too high

    Dominating concentrations

    Needed a different way to look at howthe data varied

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    MethodologyMethodology

    Made the decision to compare theconcentrations separately

    Calculated standard deviations from

    average concentrations Standard deviation inaccurate

    Used the coefficient of variationinstead

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    Results: Coefficients ofResults: Coefficients of

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    CCl4All Data

    Flight

    Flight

    Grid

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    PropeneAll Data Flight

    Flight Grid

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    ResultsResults

    Of all thegases, 9 havea coefficient

    of variationgreater than.4

    Shorterlifetimes

    Seinfeld, John. "Global Atmospheric Chemistry of ReactiveHydrocarbons." Reactive hydrocarbons in the atmosphere. Ed. C. N.

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    Further WorkFurther Work

    Attempt to compare datasets thatoverlay better (though this isdifficult when dealing with

    airplanes)Do a comparison between

    datasets that is more specificgeographically or temporally

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    Questions?Questions?

    Thank you!


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