Matches in SemOpenAlex for { <https://semopenalex.org/work/W2899370903> ?p ?o ?g. }
- W2899370903 endingPage "2576" @default.
- W2899370903 startingPage "2561" @default.
- W2899370903 abstract "Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted down-wind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions." @default.
- W2899370903 created "2018-11-09" @default.
- W2899370903 creator A5000685091 @default.
- W2899370903 creator A5002362085 @default.
- W2899370903 creator A5013671936 @default.
- W2899370903 creator A5027270547 @default.
- W2899370903 creator A5038276464 @default.
- W2899370903 creator A5049782670 @default.
- W2899370903 creator A5055105677 @default.
- W2899370903 creator A5064244344 @default.
- W2899370903 creator A5071835263 @default.
- W2899370903 creator A5071960988 @default.
- W2899370903 creator A5081399756 @default.
- W2899370903 creator A5089120599 @default.
- W2899370903 date "2019-02-28" @default.
- W2899370903 modified "2023-10-16" @default.
- W2899370903 title "Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study" @default.
- W2899370903 cites W1485504984 @default.
- W2899370903 cites W1512208174 @default.
- W2899370903 cites W1543583936 @default.
- W2899370903 cites W1983075738 @default.
- W2899370903 cites W1985545401 @default.
- W2899370903 cites W2018546748 @default.
- W2899370903 cites W2038186817 @default.
- W2899370903 cites W2040812301 @default.
- W2899370903 cites W2055235188 @default.
- W2899370903 cites W2098007567 @default.
- W2899370903 cites W2104453141 @default.
- W2899370903 cites W2121476603 @default.
- W2899370903 cites W2128612888 @default.
- W2899370903 cites W2130035313 @default.
- W2899370903 cites W2142982385 @default.
- W2899370903 cites W2147578223 @default.
- W2899370903 cites W2151454278 @default.
- W2899370903 cites W2159214047 @default.
- W2899370903 cites W2195583399 @default.
- W2899370903 cites W2275714991 @default.
- W2899370903 cites W2290918481 @default.
- W2899370903 cites W2299576847 @default.
- W2899370903 cites W2323729925 @default.
- W2899370903 cites W2336999859 @default.
- W2899370903 cites W2410260501 @default.
- W2899370903 cites W2418013334 @default.
- W2899370903 cites W2427928079 @default.
- W2899370903 cites W2516739849 @default.
- W2899370903 cites W2528947667 @default.
- W2899370903 cites W2556131455 @default.
- W2899370903 cites W2574200814 @default.
- W2899370903 cites W2594512599 @default.
- W2899370903 cites W2610125855 @default.
- W2899370903 cites W2620297712 @default.
- W2899370903 cites W2733603021 @default.
- W2899370903 cites W2899370903 @default.
- W2899370903 cites W2915841000 @default.
- W2899370903 cites W851262579 @default.
- W2899370903 doi "https://doi.org/10.5194/acp-19-2561-2019" @default.
- W2899370903 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6605086" @default.
- W2899370903 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31275365" @default.
- W2899370903 hasPublicationYear "2019" @default.
- W2899370903 type Work @default.
- W2899370903 sameAs 2899370903 @default.
- W2899370903 citedByCount "18" @default.
- W2899370903 countsByYear W28993709032019 @default.
- W2899370903 countsByYear W28993709032020 @default.
- W2899370903 countsByYear W28993709032021 @default.
- W2899370903 countsByYear W28993709032022 @default.
- W2899370903 countsByYear W28993709032023 @default.
- W2899370903 crossrefType "journal-article" @default.
- W2899370903 hasAuthorship W2899370903A5000685091 @default.
- W2899370903 hasAuthorship W2899370903A5002362085 @default.
- W2899370903 hasAuthorship W2899370903A5013671936 @default.
- W2899370903 hasAuthorship W2899370903A5027270547 @default.
- W2899370903 hasAuthorship W2899370903A5038276464 @default.
- W2899370903 hasAuthorship W2899370903A5049782670 @default.
- W2899370903 hasAuthorship W2899370903A5055105677 @default.
- W2899370903 hasAuthorship W2899370903A5064244344 @default.
- W2899370903 hasAuthorship W2899370903A5071835263 @default.
- W2899370903 hasAuthorship W2899370903A5071960988 @default.
- W2899370903 hasAuthorship W2899370903A5081399756 @default.
- W2899370903 hasAuthorship W2899370903A5089120599 @default.
- W2899370903 hasBestOaLocation W28993709031 @default.
- W2899370903 hasConcept C105795698 @default.
- W2899370903 hasConcept C111368507 @default.
- W2899370903 hasConcept C120665830 @default.
- W2899370903 hasConcept C121332964 @default.
- W2899370903 hasConcept C126314574 @default.
- W2899370903 hasConcept C127313418 @default.
- W2899370903 hasConcept C130047971 @default.
- W2899370903 hasConcept C153294291 @default.
- W2899370903 hasConcept C177562468 @default.
- W2899370903 hasConcept C178790620 @default.
- W2899370903 hasConcept C185544564 @default.
- W2899370903 hasConcept C185592680 @default.
- W2899370903 hasConcept C189764856 @default.
- W2899370903 hasConcept C2776720842 @default.
- W2899370903 hasConcept C2778863792 @default.
- W2899370903 hasConcept C33923547 @default.
- W2899370903 hasConcept C39432304 @default.