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Top-Down Constraints on Anthropogenic CO2 Emissions Within an Agricultural-Urban Landscape

Xuhui Lee and 6 other contributors

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    Abstract

    Anthropogenic carbon dioxide (CO2) emissions dominate the atmospheric greenhouse gas radiative forcing budget. However, these emissions are poorly constrained at the regional (10(2)-10(6)km(2)) 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 7.4mol/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 1.1mol/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 79.04.1% (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 8.43.8% (a priori 32.5%)suggesting a more important role of residential heating in winter. The modeled carbon isotope ratio of the CO2 source (delta C-13(s), -29.3 +/- 0.4%) was relatively more enriched in C-13-CO2 compared to that derived from Miller-Tans plot analyses (-35.5 parts per thousand to -34.8 parts per thousand), supporting that natural gas consumption was underestimated for this region.