Cargando…

Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference

[Image: see text] Selenium (Se) is an essential dietary element for humans and animals, and the atmosphere is an important source of Se to soils. However, estimates of global atmospheric Se fluxes are highly uncertain. To constrain these uncertainties, we use a global model of atmospheric Se cycling...

Descripción completa

Detalles Bibliográficos
Autores principales: Feinberg, Aryeh, Stenke, Andrea, Peter, Thomas, Winkel, Lenny H. E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7301612/
https://www.ncbi.nlm.nih.gov/pubmed/32401017
http://dx.doi.org/10.1021/acs.est.0c01408
_version_ 1783547725897269248
author Feinberg, Aryeh
Stenke, Andrea
Peter, Thomas
Winkel, Lenny H. E.
author_facet Feinberg, Aryeh
Stenke, Andrea
Peter, Thomas
Winkel, Lenny H. E.
author_sort Feinberg, Aryeh
collection PubMed
description [Image: see text] Selenium (Se) is an essential dietary element for humans and animals, and the atmosphere is an important source of Se to soils. However, estimates of global atmospheric Se fluxes are highly uncertain. To constrain these uncertainties, we use a global model of atmospheric Se cycling and a database of more than 600 sites where Se in aerosol has been measured. Applying Bayesian inference techniques, we determine the probability distributions of global Se emissions from the four major sources: anthropogenic activities, volcanoes, marine biosphere, and terrestrial biosphere. Between 29 and 36 Gg of Se are emitted to the atmosphere every year, doubling previous estimates of emissions. Using emission parameters optimized by aerosol network measurements, our model shows good agreement with the aerosol Se observations (R(2) = 0.66), as well as with independent aerosol (0.59) and wet deposition measurements (0.57). Both model and measurements show a decline in Se over North America in the last two decades because of changes in technology and energy policy. Our results highlight the role of the ocean as a net atmospheric Se sink, with around 7 Gg yr(–1) of Se transferred from land through the atmosphere. The constrained Se emissions represent a substantial step forward in understanding the global Se cycle.
format Online
Article
Text
id pubmed-7301612
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher American Chemical Society
record_format MEDLINE/PubMed
spelling pubmed-73016122020-06-19 Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference Feinberg, Aryeh Stenke, Andrea Peter, Thomas Winkel, Lenny H. E. Environ Sci Technol [Image: see text] Selenium (Se) is an essential dietary element for humans and animals, and the atmosphere is an important source of Se to soils. However, estimates of global atmospheric Se fluxes are highly uncertain. To constrain these uncertainties, we use a global model of atmospheric Se cycling and a database of more than 600 sites where Se in aerosol has been measured. Applying Bayesian inference techniques, we determine the probability distributions of global Se emissions from the four major sources: anthropogenic activities, volcanoes, marine biosphere, and terrestrial biosphere. Between 29 and 36 Gg of Se are emitted to the atmosphere every year, doubling previous estimates of emissions. Using emission parameters optimized by aerosol network measurements, our model shows good agreement with the aerosol Se observations (R(2) = 0.66), as well as with independent aerosol (0.59) and wet deposition measurements (0.57). Both model and measurements show a decline in Se over North America in the last two decades because of changes in technology and energy policy. Our results highlight the role of the ocean as a net atmospheric Se sink, with around 7 Gg yr(–1) of Se transferred from land through the atmosphere. The constrained Se emissions represent a substantial step forward in understanding the global Se cycle. American Chemical Society 2020-05-13 2020-06-16 /pmc/articles/PMC7301612/ /pubmed/32401017 http://dx.doi.org/10.1021/acs.est.0c01408 Text en Copyright © 2020 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes.
spellingShingle Feinberg, Aryeh
Stenke, Andrea
Peter, Thomas
Winkel, Lenny H. E.
Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference
title Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference
title_full Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference
title_fullStr Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference
title_full_unstemmed Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference
title_short Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference
title_sort constraining atmospheric selenium emissions using observations, global modeling, and bayesian inference
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7301612/
https://www.ncbi.nlm.nih.gov/pubmed/32401017
http://dx.doi.org/10.1021/acs.est.0c01408
work_keys_str_mv AT feinbergaryeh constrainingatmosphericseleniumemissionsusingobservationsglobalmodelingandbayesianinference
AT stenkeandrea constrainingatmosphericseleniumemissionsusingobservationsglobalmodelingandbayesianinference
AT peterthomas constrainingatmosphericseleniumemissionsusingobservationsglobalmodelingandbayesianinference
AT winkellennyhe constrainingatmosphericseleniumemissionsusingobservationsglobalmodelingandbayesianinference