Peroxy acetyl nitrate (PAN) measurements at northern midlatitude mountain sites in April: a constraint on continental source–receptor relationships
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Published:2018-10-25
Issue:20
Volume:18
Page:15345-15361
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Fiore Arlene M.ORCID, Fischer Emily V., Milly George P., Pandey Deolal Shubha, Wild OliverORCID, Jaffe Daniel A., Staehelin JohannesORCID, Clifton Olivia E.ORCID, Bergmann Dan, Collins WilliamORCID, Dentener Frank, Doherty Ruth M.ORCID, Duncan Bryan N., Fischer Bernd, Gilge Stefan, Hess Peter G., Horowitz Larry W., Lupu AlexandruORCID, MacKenzie Ian A., Park RokjinORCID, Ries LudwigORCID, Sanderson Michael G., Schultz Martin G.ORCID, Shindell Drew T.ORCID, Steinbacher MartinORCID, Stevenson David S.ORCID, Szopa SophieORCID, Zellweger Christoph, Zeng GuangORCID
Abstract
Abstract. Abundance-based model evaluations with observations
provide critical tests for the simulated mean state in models of
intercontinental pollution transport, and under certain conditions may also
offer constraints on model responses to emission changes. We compile
multiyear measurements of peroxy acetyl nitrate (PAN) available from five
mountaintop sites and apply them in a proof-of-concept approach that
exploits an ensemble of global chemical transport models (HTAP1) to identify
an observational “emergent constraint”. In April, when the signal from
anthropogenic emissions on PAN is strongest, simulated PAN at northern
midlatitude mountaintops correlates strongly with PAN source–receptor
relationships (the response to 20 % reductions in precursor emissions
within northern midlatitude continents; hereafter, SRRs). This finding
implies that PAN measurements can provide constraints on PAN SRRs by
limiting the SRR range to that spanned by the subset of models simulating
PAN within the observed range. In some cases, regional anthropogenic
volatile organic compound (AVOC) emissions, tracers of transport from
different source regions, and SRRs for ozone also correlate with PAN SRRs.
Given the large observed interannual variability in the limited available
datasets, establishing strong constraints will require matching meteorology
in the models to the PAN measurements. Application of this evaluation
approach to the chemistry–climate models used to project changes in
atmospheric composition will require routine, long-term mountaintop PAN
measurements to discern both the climatological SRR signal and its
interannual variability.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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