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Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes

  • Author(s): Zumkehr, Andrew Lee
  • Advisor(s): Campbell, John E
  • et al.
Abstract

Carbonyl sulfide (COS or OCS) is emerging as a potentially important tracer of terrestrial biological carbon fluxes. Anthropogenic sources of atmospheric COS are a first order uncertainty for utilizing COS as a tracer of the carbon cycle. As anthropogenic COS is a confounding source of atmospheric COS when interpreting COS observations, incorrect estimates of anthropogenic COS sources can introduce large interpretation bias when attempting to infer carbon cycle fluxes. However, the current gridded estimate of anthropogenic sources of atmospheric COS is largely derived from data over three decades old and therefore is not likely to be representative of current atmospheric conditions. Here I address this critical knowledge gap by providing a new gridded estimate of anthropogenic COS sources derived from the most current industry activity and emissions factor data available and employ a more sophisticated approach for the spatial distribution of sources than presented in previous work. This new data set results in a very different picture of the spatial distribution of anthropogenic sources of COS and in a large upward revision in total global sources than estimated in previous work. The large missing source of atmospheric COS needed to balance the global budget of atmospheric COS has largely been attributed to an unknown ocean source in previous work. However, considering the large upward revision of anthropogenic COS sources estimated here, I present the hypothesis that anthropogenic sources may be a key component of the missing source of atmospheric COS. I present subsequent modeling scenarios to test this hypothesis and show that anthropogenic COS sources can explain observations of atmospheric COS as well as or better than enhanced ocean sources. Therefore, the data set of anthropogenic sources of COS presented here emerges as a key component of reducing interpretation bias when inferring carbon cycle fluxes using COS and for explaining the missing source of atmospheric COS and balancing the global COS budget (which has previously not been considered).

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