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An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO2 concentration data
Verifying national greenhouse gas (GHG) emissions inventories is a critical step to ensure that reported emissions data to the United Nations Framework Convention on Climate Change (UNFCCC) are accurate and representative of a country’s contribution to GHG concentrations in the atmosphere. Furthermore, verifying biogenic fluxes provides a check on estimated emissions associated with managing lands for carbon sequestration and other activities, which often have large uncertainties. We report here on the challenges and results associated with a case study using atmospheric measurements of CO _2 concentrations and inverse modeling to verify nationally-reported biogenic CO _2 emissions. The biogenic CO _2 emissions inventory was compiled for the Mid-Continent region of United States based on methods and data used by the US government for reporting to the UNFCCC, along with additional sources and sinks to produce a full carbon balance. The biogenic emissions inventory produced an estimated flux of −408 ± 136 Tg CO _2 for the entire study region, which was not statistically different from the biogenic flux of −478 ± 146 Tg CO _2 that was estimated using the atmospheric CO _2 concentration data. At sub-regional scales, the spatial density of atmospheric observations did not appear sufficient to verify emissions in general. However, a difference between the inventory and inversion results was found in one isolated area of West-central Wisconsin. This part of the region is dominated by forestlands, suggesting that further investigation may be warranted into the forest C stock or harvested wood product data from this portion of the study area. The results suggest that observations of atmospheric CO _2 concentration data and inverse modeling could be used to verify biogenic emissions, and provide more confidence in biogenic GHG emissions reporting to the UNFCCC.
An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO2 concentration data
Verifying national greenhouse gas (GHG) emissions inventories is a critical step to ensure that reported emissions data to the United Nations Framework Convention on Climate Change (UNFCCC) are accurate and representative of a country’s contribution to GHG concentrations in the atmosphere. Furthermore, verifying biogenic fluxes provides a check on estimated emissions associated with managing lands for carbon sequestration and other activities, which often have large uncertainties. We report here on the challenges and results associated with a case study using atmospheric measurements of CO _2 concentrations and inverse modeling to verify nationally-reported biogenic CO _2 emissions. The biogenic CO _2 emissions inventory was compiled for the Mid-Continent region of United States based on methods and data used by the US government for reporting to the UNFCCC, along with additional sources and sinks to produce a full carbon balance. The biogenic emissions inventory produced an estimated flux of −408 ± 136 Tg CO _2 for the entire study region, which was not statistically different from the biogenic flux of −478 ± 146 Tg CO _2 that was estimated using the atmospheric CO _2 concentration data. At sub-regional scales, the spatial density of atmospheric observations did not appear sufficient to verify emissions in general. However, a difference between the inventory and inversion results was found in one isolated area of West-central Wisconsin. This part of the region is dominated by forestlands, suggesting that further investigation may be warranted into the forest C stock or harvested wood product data from this portion of the study area. The results suggest that observations of atmospheric CO _2 concentration data and inverse modeling could be used to verify biogenic emissions, and provide more confidence in biogenic GHG emissions reporting to the UNFCCC.
An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO2 concentration data
Stephen M Ogle (Autor:in) / Kenneth Davis (Autor:in) / Thomas Lauvaux (Autor:in) / Andrew Schuh (Autor:in) / Dan Cooley (Autor:in) / Tristram O West (Autor:in) / Linda S Heath (Autor:in) / Natasha L Miles (Autor:in) / Scott Richardson (Autor:in) / F Jay Breidt (Autor:in)
2015
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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