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  1. Abstract

    Sulfuryl fluoride (SO2F2) is a synthetic pesticide and a potent greenhouse gas that is accumulating in the global atmosphere. Rising emissions are a concern since SO2F2has a relatively long atmospheric lifetime and a high global warming potential. The U.S. is thought to contribute substantially to global SO2F2emissions, but there is a paucity of information on how emissions of SO2F2are distributed across the U.S., and there is currently no inventory of SO2F2emissions for the U.S. or individual states. Here we provide an atmospheric measurement-based estimate of U.S. SO2F2emissions using high-precision SO2F2measurements from the NOAA Global Greenhouse Gas Reference Network (GGGRN) and a geostatistical inverse model. We find that California has the largest SO2F2emissions among all U.S. states, with the highest emissions from southern coastal California (Los Angeles, Orange, and San Diego counties). Outside of California, only very small and infrequent SO2F2emissions are detected by our analysis of GGGRN data. We find that California emits 60-85% of U.S. SO2F2emissions, at a rate of 0.26 ( ± 0.10) Gg yr−1. We estimate that emissions of SO2F2from California are equal to 5.5–12% of global SO2F2emissions.

     
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  2. null (Ed.)
    Abstract. We apply airborne measurements across three seasons(summer, winter and spring 2017–2018) in a multi-inversion framework toquantify methane emissions from the US Corn Belt and Upper Midwest, a keyagricultural and wetland source region. Combing our seasonal results withprior fall values we find that wetlands are the largest regional methanesource (32 %, 20 [16–23] Gg/d), while livestock (enteric/manure; 25 %,15 [14–17] Gg/d) are the largest anthropogenic source. Naturalgas/petroleum, waste/landfills, and coal mines collectively make up theremainder. Optimized fluxes improve model agreement with independentdatasets within and beyond the study timeframe. Inversions reveal coherentand seasonally dependent spatial errors in the WetCHARTs ensemble meanwetland emissions, with an underestimate for the Prairie Pothole region butan overestimate for Great Lakes coastal wetlands. Wetland extent andemission temperature dependence have the largest influence on predictionaccuracy; better representation of coupled soil temperature–hydrologyeffects is therefore needed. Our optimized regional livestock emissionsagree well with the Gridded EPA estimates during spring (to within 7 %) butare ∼ 25 % higher during summer and winter. Spatial analysisfurther shows good top-down and bottom-up agreement for beef facilities (withmainly enteric emissions) but larger (∼ 30 %) seasonaldiscrepancies for dairies and hog farms (with > 40 % manureemissions). Findings thus support bottom-up enteric emission estimates butsuggest errors for manure; we propose that the latter reflects inadequatetreatment of management factors including field application. Overall, ourresults confirm the importance of intensive animal agriculture for regionalmethane emissions, implying substantial mitigation opportunities throughimproved management. 
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  3. Abstract

    Carbon monoxide (CO) is an ozone precursor, oxidant sink, and widely used pollution tracer. The importance of anthropogenic versus other CO sources in the US is uncertain. Here, we interpret extensive airborne measurements with an atmospheric model to constrain US fossil and nonfossil CO sources. Measurements reveal a low bias in the simulated CO background and a 30% overestimate of US fossil CO emissions in the 2016 National Emissions Inventory. After optimization we apply the model for source partitioning. During summer, regional fossil sources account for just 9%–16% of the sampled boundary layer CO, and 32%–38% of the North American enhancement—complicating use of CO as a fossil fuel tracer. The remainder predominantly reflects biogenic hydrocarbon oxidation plus fires. Fossil sources account for less domain‐wide spatial variability at this time than nonfossil and background contributions. The regional fossil contribution rises in other seasons, and drives ambient variability downwind of urban areas.

     
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