Seasonally resolved excess urban methane emissions from the Baltimore/Washington, DC metropolitan region
Yaoxian Huang, Eric Kort, Anna Karion, John Ware, Kimberly Mueller, Sharon Gourdji
Methane (CH4) emissions from urban areas are increasingly recognized as a potentially important anthropogenic source, but we have limited observations of annual and seasonal emissions from these important regions. In this study, we quantify seasonal and annual urban CH4 emissions over the Baltimore, Maryland and Washington, DC metropolitan regions by combining in-situ CH4 atmospheric observations from four tall tower stations with a Lagrangian Particle Dispersion Model in both forward convolutions to simulate observations and backward inversions to estimate surface fluxes. We use observations spanning multiple seasons and employ an ensemble approach considering multiple meteorological representations, emission inventories, and upwind CH4 values at the boundary of our domain. Forward model simulations in winter, spring and fall underestimate observed atmospheric CH4, indicative of inventory underestimates. In summer, forward simulations overestimate observations, which is attributed to excess predicted wetland emissions. Inverse analyses produce an ensemble annual mean of urban CH4 emissions in DC/ Baltimore totaling 38.78.5 Gg/month (mean1 standard deviation), which is 1.990.44 times higher than the ensemble mean of bottom-up emission inventories, and 3.090.68 times larger than the gridded US EPA inventory in the region. We find a modest seasonal variability of urban CH4 emissions not captured in current inventories, with optimized summer emissions 41% lower than winter, broadly consistent with expectations if emissions correlate with natural gas usage. The estimated seasonal variability also implies that microbial activity is likely not a dominant source in the region.
, Kort, E.
, Karion, A.
, Ware, J.
, Mueller, K.
and Gourdji, S.
Seasonally resolved excess urban methane emissions from the Baltimore/Washington, DC metropolitan region, Environmental Science and Technology, [online], https://doi.org/10.1021/acs.est.9b02782, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927925
(Accessed December 4, 2023)