PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model

We present a spatially and temporally resolved global atmospheric polychlorinated biphenyl (PCB) model, driven by meteorological data, that is skilled at simulating mean atmospheric PCB concentrations and seasonal cycles in the Northern Hemisphere midlatitudes and mean Arctic concentrations. However...

Full description

Bibliographic Details
Main Author: Carey Friedman
Format: Dataset
Language:unknown
Published: Arctic Data Center 2016
Subjects:
Online Access:https://search.dataone.org/view/urn:uuid:3bc6ac85-8b67-4afc-8d42-5d8478099c63
_version_ 1828416990999478272
author Carey Friedman
author_facet Carey Friedman
author_sort Carey Friedman
collection Arctic Data Center (via DataONE)
description We present a spatially and temporally resolved global atmospheric polychlorinated biphenyl (PCB) model, driven by meteorological data, that is skilled at simulating mean atmospheric PCB concentrations and seasonal cycles in the Northern Hemisphere midlatitudes and mean Arctic concentrations. However, the model does not capture the ob- served Arctic summer maximum in atmospheric PCBs. We use the model to estimate global budgets for seven PCB con- geners, and we demonstrate that congeners that deposit more readily show lower potential for long-range transport, consistent with a recently described "differential removal hypothesis" regarding the hemispheric transport of PCBs. Using sensitivity simulations to assess processes within, outside, or transport to the Arctic, we examine the influence of climate- and emissions-driven processes on Arctic concentrations and their effect on improving the simulated Arctic seasonal cycle. We find evidence that processes occurring outside the Arctic have a greater influence on Arctic atmospheric PCB levels than processes that occur within the Arctic. Our simulations suggest that re-emissions from sea ice melting or from the Arctic Ocean during summer would have to be unrealistically high in order to capture observed temporal trends of PCBs in the Arctic atmosphere. We conclude that midlatitude pro- cesses are likely to have a greater effect on the Arctic under global change scenarios than re-emissions within the Arctic.
format Dataset
genre Arctic
Arctic Ocean
Sea ice
genre_facet Arctic
Arctic Ocean
Sea ice
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
id dataone:urn:uuid:3bc6ac85-8b67-4afc-8d42-5d8478099c63
institution Open Polar
language unknown
long_lat ENVELOPE(-180.0,0.0,90.0,66.0)
op_collection_id dataone:urn:node:ARCTIC
op_coverage Global simulation but focused on the Arctic (above 66 N)
ENVELOPE(-180.0,0.0,90.0,66.0)
BEGINDATE: 1979-01-01T00:00:00Z ENDDATE: 2010-01-01T00:00:00Z
publishDate 2016
publisher Arctic Data Center
record_format openpolar
spelling dataone:urn:uuid:3bc6ac85-8b67-4afc-8d42-5d8478099c63 2025-04-03T18:47:42+00:00 PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model Carey Friedman Global simulation but focused on the Arctic (above 66 N) ENVELOPE(-180.0,0.0,90.0,66.0) BEGINDATE: 1979-01-01T00:00:00Z ENDDATE: 2010-01-01T00:00:00Z 2016-12-28T00:00:00Z https://search.dataone.org/view/urn:uuid:3bc6ac85-8b67-4afc-8d42-5d8478099c63 unknown Arctic Data Center PCBs Arctic long range transport re-emissions volatilization Dataset 2016 dataone:urn:node:ARCTIC 2025-04-03T18:11:10Z We present a spatially and temporally resolved global atmospheric polychlorinated biphenyl (PCB) model, driven by meteorological data, that is skilled at simulating mean atmospheric PCB concentrations and seasonal cycles in the Northern Hemisphere midlatitudes and mean Arctic concentrations. However, the model does not capture the ob- served Arctic summer maximum in atmospheric PCBs. We use the model to estimate global budgets for seven PCB con- geners, and we demonstrate that congeners that deposit more readily show lower potential for long-range transport, consistent with a recently described "differential removal hypothesis" regarding the hemispheric transport of PCBs. Using sensitivity simulations to assess processes within, outside, or transport to the Arctic, we examine the influence of climate- and emissions-driven processes on Arctic concentrations and their effect on improving the simulated Arctic seasonal cycle. We find evidence that processes occurring outside the Arctic have a greater influence on Arctic atmospheric PCB levels than processes that occur within the Arctic. Our simulations suggest that re-emissions from sea ice melting or from the Arctic Ocean during summer would have to be unrealistically high in order to capture observed temporal trends of PCBs in the Arctic atmosphere. We conclude that midlatitude pro- cesses are likely to have a greater effect on the Arctic under global change scenarios than re-emissions within the Arctic. Dataset Arctic Arctic Ocean Sea ice Arctic Data Center (via DataONE) Arctic Arctic Ocean ENVELOPE(-180.0,0.0,90.0,66.0)
spellingShingle PCBs
Arctic
long range transport
re-emissions
volatilization
Carey Friedman
PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model
title PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model
title_full PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model
title_fullStr PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model
title_full_unstemmed PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model
title_short PCBs in the Arctic atmosphere: determining important driving forces using a global atmospheric transport model
title_sort pcbs in the arctic atmosphere: determining important driving forces using a global atmospheric transport model
topic PCBs
Arctic
long range transport
re-emissions
volatilization
topic_facet PCBs
Arctic
long range transport
re-emissions
volatilization
url https://search.dataone.org/view/urn:uuid:3bc6ac85-8b67-4afc-8d42-5d8478099c63