English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

It is of crucial importance to be able to identify the location ofatmospheric pollution sources in our planet. Global models of atmospherictransport in combination with diverse Earth observing systems are a naturalchoice to achieve this goal. It is shown that the ability to successfullyreconstruct the location and magnitude of an instantaneous source in globalchemical transport models (CTMs) decreases rapidly as a function of the timeinterval between the pollution release and the observation time. A simple wayto quantitatively characterize this phenomenon is proposed based on theeffective -undesired- numerical diffusion present in current Eulerian CTMs andverified using idealized numerical experiments. The approach presented consistsof using the adjoint-based optimization method in a state-of-the-art CTM,GEOS-Chem, to reconstruct the location and magnitude of a realistic pollutionplume for multiple time scales. The findings obtained from these numericalexperiments suggest a time scale of 2 days after which the accuracy of theadjoint-based optimization methodology is compromised considerably in currentglobal CTMs. In conjunction with the mean atmospheric velocity, theaforementioned time scale leads to an estimate of a length scale of about1700km, downwind from the source, beyond which measurements, in conjunctionwith current global CTMs, may not be successfully utilized to reconstructcontinuous-in-time sources. The approach presented here can be utilized tocharacterize the capabilities and limitations of adjoint-based optimizationinversions in other regional and global Eulerian CTMs.

Quantifying the loss of information in source attribution problems using the adjoint method in global models of atmospheric chemical transport