An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO2 concentration data

Abstract

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.

Keywords

• greenhouse gas emissions inventory
• atmospheric inversion modeling
• emissions verification
• carbon cycle