Development of an optimal calibration strategy for trace gas measurements
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Development of an optimal calibration strategy for trace gas measurements. Mark Battle (Bowdoin College) Zane Davis, Ryan Hart, Jayme Woogerd, Jacob Scheckman, Eric Sofen, Becca Perry, John Carpenter. Special thanks: Britt Stephens (NCAR), Ralph Keeling (SIO), Bill Munger (Harvard)

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Development of an optimal calibration strategy for trace gas measurements

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Development of an optimal calibration strategy for trace gas measurements

Development of an optimal calibration strategy for trace gas measurements

Mark Battle

(Bowdoin College)

Zane Davis, Ryan Hart, Jayme Woogerd, Jacob Scheckman, Eric Sofen, Becca Perry, John Carpenter.

Special thanks: Britt Stephens (NCAR), Ralph Keeling (SIO), Bill Munger (Harvard)

Mary Lou Zeeman (Cornell/Bowdoin)

CompSust09 June 11, 2009

Funding from: DOE, Bowdoin College


Outline

Outline

  • Structure of a measurement program

  • What measurements might tell us

  • Example of one such program

  • Call for help


Measuring the composition of air

Measuring the composition of air

  • Precision vs. Accuracy


Precision vs accuracy

Precision vs. Accuracy


Measuring the composition of air1

Measuring the composition of air

  • Precision vs. Accuracy

  • Differential measurements


Benefits of differential measurements

Benefits of differential measurements

Initial Group

1001 Women

Final group

1002 Women


Benefits of differential measurements1

Benefits of differential measurements

Absolute changes

Initial # women: 1001

Final # women: 1002

Change in women: 0.1%

Initial Group

1001 Women

Final group

1002 Women


Benefits of differential measurements2

Benefits of differential measurements

Initial Group

999 Men

1001 Women

Final group

999 Men

1002 Women


Benefits of differential measurements3

Benefits of differential measurements

Initial Group

999 Men

1001 Women

Final group

999 Men

1002 Women

Differential changes

Initial gender diff: 2

Final gender diff: 3

Change in gender diff: 33%


Benefits of differential measurements4

Benefits of differential measurements

Absolute changes

Initial # women: 1001

Final # women: 1002

Change in women: 0.1%

Initial Group

999 Men

1001 Women

Final group

999 Men

1002 Women

Differential changes

Initial gender diff: 2

Final gender diff: 3

Change in gender diff: 33%


Measuring the composition of air2

Measuring the composition of air

  • Precision vs. Accuracy

  • Differential measurements

  • Measure samples relative to “standards”


Challenges of differential measurements

Challenges of differential measurements


Challenges of differential measurements1

Challenges of differential measurements


Challenges of differential measurements2

Challenges of differential measurements


Challenges of differential measurements3

Challenges of differential measurements


Challenges of differential measurements4

Challenges of differential measurements


Measuring the composition of air3

Measuring the composition of air

  • Precision vs. Accuracy

  • Differential measurements

  • Measure samples relative to “standards”

  • Instrumental response


Impact of instrumental non linearity

Impact of instrumental non-linearity


Metric

Metric

Precision & Accuracy

Constraints

Instrument time is precious

Standard air is precious


In summary

In summary:

Optimally combine many analyses of many standards to create a virtual standard against which all samples are measured.


Connecting to the real world measuring o 2 and co 2 to constrain the carbon cycle

Connecting to the real world:Measuring O2 and CO2to constrain the carbon cycle


Where does anthropogenic co 2 end up

Where does anthropogenic CO2 end up?

Values for 2000-2006 Canadell et al. PNAS 2007


How do we know these numbers

How do we know these numbers?


How do we know these numbers1

How do we know these numbers?

  • Record CO2 emissions

  • Measure CO2 in the atmosphere


How do we know these numbers2

How do we know these numbers?

  • Record CO2 emissions

  • Measure CO2 in the atmosphere

  • Measure CO2 in the oceans

  • Estimate from small-scale land measurements

  • Infer from spatial pattern and isotopes of atmospheric CO2


How do we know these numbers3

How do we know these numbers?

  • Record CO2 emissions

  • Measure CO2 in the atmosphere

  • Measure CO2 in the oceans

  • Estimate from small-scale land measurements

  • Infer from spatial pattern and isotopes of atmospheric CO2

  • Measure atmospheric O2


The link between o 2 and co 2

The link between O2 and CO2

CO2 = Land biota + Industry + Ocean

DO2 = Land biota + Industry


The link between o 2 and co 21

The link between O2 and CO2

CO2 = Land biota + Industry + Ocean

DO2 = Land biota + Industry


The link between o 2 and co 22

The link between O2 and CO2

CO2 = Land biota + Industry + Ocean

DO2 = Land biota + Industry


Development of an optimal calibration strategy for trace gas measurements

Google maps


The equipment

The equipment


The equipment1

The equipment


Real data

Real data


Real data1

Real data


Real data2

Real data


Summary

Summary

  • Important questions require excellent atmospheric measurements


Summary1

Summary

  • Important questions require excellent atmospheric measurements

  • Excellent measurements require intelligent weighting of experimental evidence


Summary2

Summary

  • Important questions require excellent atmospheric measurements

  • Excellent measurements require intelligent weighting of experimental evidence

  • I have abundant data. Intelligence, on the other hand…

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