Anthropogenic carbon dioxide (CO2) emissions dominate the atmospheric greenhouse gas radiative forcing budget. However, these emissions are poorly constrained at the regional (102–106 km2) and seasonal scales. Here we use a combination of tall tower CO2 mixing ratio and carbon isotope ratio observations and inverse modeling techniques to constrain anthropogenic CO2 emissions within a highly heterogeneous agricultural landscape near Saint Paul, Minnesota, in the Upper Midwestern United States. The analyses indicate that anthropogenic emissions contributed 6.6, 6.8, and 7.4 μmol/mol annual CO2 enhancements (i.e., departures from the background values) in 2008, 2009, and 2010, respectively. Oil refinery, the energy industry (power and heat generation), and residential emissions (home heating and cooking) contributed 2.9 (42.5%), 1.4 (19.8%), and 1.1 μmol/mol (15.8%) of the total anthropogenic enhancement over the 3-year period according to a priori inventories. The total anthropogenic signal was further partitioned into CO2 emissions derived from fuel oil, natural gas, coal, gasoline, and diesel consumption using inverse modeling and carbon isotope ratio analyses. The results indicate that fuel oil and natural gas consumption accounted for 52.5% of the anthropogenic CO2 sources in winter. Here the a posteriori CO2 emission from natural gas was 79.0 ± 4.1% (a priori 20.0%) and accounted for 63% of the total CO2 enhancement including both biological and anthropogenic sources. The a posteriori CO2 emission from fuel oil was 8.4 ± 3.8% (a priori 32.5%)—suggesting a more important role of residential heating in winter. The modeled carbon isotope ratio of the CO2 source (δ13Cs, −29.3 ± 0.4‰) was relatively more enriched in 13C-CO2 compared to that derived from Miller-Tans plot analyses (−35.5‰ to −34.8‰), supporting that natural gas consumption was underestimated for this region.
Bibliographical noteFunding Information:
Financial support for this research has been provided by the National Science Foundation (grants 1640337 and ATM- 0546476). The first author acknowl edges a visiting scholarship from the China Scholarship Council. We would like to express our sincere thanks to R. Nassar for providing the hourly scaling factors for the different anthropogenic CO2 source categories. The tall tower data can be accessed at our group website (https://www.biometeorology. umn.edu/research/data-archives).
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- U.S. Corn Belt
- anthropogenic CO emissions
- carbon isotope ratios
- inverse modeling
- tall tower