Surrogate gas prediction model as a proxy for Delta C-14-based measurements of fossil fuel CO2
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Surrogate gas prediction model as a proxy for Delta C-14-based measurements of fossil fuel CO2

Filetype[PDF-1.76 MB]



Details:

  • Journal Title:
    Journal of Geophysical Research: Atmospheres
  • Description:
    The measured C-14:C-12 isotopic ratio of atmospheric CO2 (and its associated derived Delta C-14 value) is an ideal tracer for determination of the fossil fuel derived CO2 enhancement contributing to any atmospheric CO2 measurement (C-ff). Given enough such measurements, independent top-down estimation of U.S. fossil fuel CO2 emissions should be possible. However, the number of Delta C-14 measurements is presently constrained by cost, available sample volume, and availability of mass spectrometer measurement facilities. Delta C-14 is therefore measured in just a small fraction of samples obtained by flask air sampling networks around the world. Here we develop a projection pursuit regression (PPR) model to predict C-ff as a function of multiple surrogate gases acquired within the NOAA/Earth System Research Laboratory (ESRL) Global Greenhouse Gas Reference Network (GGGRN). The surrogates consist of measured enhancements of various anthropogenic trace gases, including CO, SF6, and halocarbon and hydrocarbon acquired in vertical airborne sampling profiles near Cape May, NJ and Portsmouth, NH from 2005 to 2010. Model performance for these sites is quantified based on predicted values corresponding to test data excluded from the model building process. Chi-square hypothesis test analysis indicates that these predictions and corresponding observations are consistent given our uncertainty budget which accounts for random effects and one particular systematic effect. However, quantification of the combined uncertainty of the prediction due to all relevant systematic effects is difficult because of the limited range of the observations and their relatively high fractional uncertainties at the sampling sites considered here. To account for the possibility of additional systematic effects, we incorporate another component of uncertainty into our budget. Expanding the number of Delta C-14 measurements in the NOAA GGGRN and building new PPR models at additional sites would improve our understanding of uncertainties and potentially increase the number of C-ff estimates by approximately a factor of 3. Provided that these estimates are of comparable quality to Delta C-14-based estimates, we expect an improved determination of fossil fuel CO2 emissions.
  • Source:
    Journal of Geophysical Research-Atmospheres, 121(12), 7489-7505.
  • Document Type:
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
  • File Type:

Supporting Files

  • No Additional Files

More +

Related Documents