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\begin{document}

\title{Assimilating Morning, Evening, and Nighttime Greenhouse Gas Observations
in Atmospheric Inversions}



\author[1]{Vanessa Monteiro}%
\author[1]{Jocelyn Christine Turnbull}%
\author[2]{Natasha L Miles}%
\author[2]{Kenneth J. Davis}%
\author[3]{Zachary Robert Barkley}%
\author[4]{Aijun Deng}%
\affil[1]{GNS Science}%
\affil[2]{Pennsylvania State University}%
\affil[3]{The Pennsylvania State University}%
\affil[4]{Vestas-American Wind Technology, Inc.}%


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  \date{May 18, 2024}


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\begin{abstract}
Improved urban greenhouse gas (GHG) flux estimates are crucial for
informing policy and mitigation efforts. Atmospheric inversion modelling
(AIM) is a widely used technique combining atmospheric measurements of
trace gas, meteorological modelling, and a prior emission map to infer
fluxes. Traditionally, AIM relies on mid-afternoon observations due to
the well-represented atmospheric boundary layer in meteorological
models. However, confining flux assessement to daytime observations is
problematic for the urban scale, where air masses typically move over a
city in a few hours and AIM therefore cannot provide improved
constraints on emissions over the full diurnal cycle. We hypothesized
that there are atmospheric conditions beyond the mid-afternoon under
which meteorological models also perform well. We tested this hypothesis
using tower-based measurements of CO2 and CH4, wind speed observations,
weather model outputs from INFLUX (Indianapolis Flux Experiment), and a
prior emissions map. By categorizing trace gas vertical gradients
according to wind speed classes and identifying when the meteorological
model satisfactorily simulates boundary layer depth (BLD), we found that
non-afternoon observations can be assimilated when wind speed is
\textgreater{}5 m/s. This condition resulted in small modeled BLD biases
(\textless{}40\%) when compared to calmer conditions
(\textgreater{}100\%). For Indianapolis, 37\% of the GHG measurements
meet this wind speed criterion, almost tripling the observations
retained for AIM. Similar results are expected for windy cities like
Auckland, Melbourne, and Boston, potentially allowing AIM to assimilate
up to 60\% the total (24-h) observations. Incorporating these
observations in AIMs should yield a more diurnally comprehensive
evaluation of urban GHG emissions.%
\end{abstract}%



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\textbf{Hosted file}

\verb`AdditionalDataAIM.docx`  available at \url{https://authorea.com/users/745460/articles/717483-assimilating-morning-evening-and-nighttime-greenhouse-gas-observations-in-atmospheric-inversions}

\textbf{Hosted file}

\verb`SuppInfo_AdditionalDataAIM.docx`  available at \url{https://authorea.com/users/745460/articles/717483-assimilating-morning-evening-and-nighttime-greenhouse-gas-observations-in-atmospheric-inversions}

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