Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze

There are few multi-decadal observations of atmospheric aerosols worldwide. This study applies global hourly visibility (Vis) observations at more than 3000 stations to investigate historical trends in atmospheric haze over 1945–1996 for the US, and over 1973–2013 for Europe and eastern Asia. A...

Full description

Bibliographic Details
Main Authors: C. Li, R. V. Martin, B. L. Boys, A. van Donkelaar, S. Ruzzante
Format: Article
Language:English
Published: Copernicus Publications 2016-03-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/16/2435/2016/acp-16-2435-2016.pdf
id doaj-3346dbd43ad44e22b5e2b3d89c55f278
record_format Article
spelling doaj-3346dbd43ad44e22b5e2b3d89c55f2782020-11-24T21:33:37ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242016-03-01162435245710.5194/acp-16-2435-2016Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric hazeC. Li0R. V. Martin1R. V. Martin2B. L. Boys3A. van Donkelaar4S. Ruzzante5S. Ruzzante6Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, CanadaDepartment of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, CanadaHarvard-Smithsonian Center for Astrophysics, Cambridge, MA, USADepartment of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, CanadaDepartment of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, CanadaDepartment of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canadanow at: Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON, CanadaThere are few multi-decadal observations of atmospheric aerosols worldwide. This study applies global hourly visibility (Vis) observations at more than 3000 stations to investigate historical trends in atmospheric haze over 1945–1996 for the US, and over 1973–2013 for Europe and eastern Asia. A comprehensive data screening and processing framework is developed and applied to minimize uncertainties and construct monthly statistics of inverse visibility (1/Vis). This data processing includes removal of relatively clean cases with high uncertainty, and change point detection to identify and separate methodological discontinuities such as the introduction of instrumentation. Although the relation between 1/Vis and atmospheric extinction coefficient (<i>b</i><sub>ext</sub>) varies across different stations, spatially coherent trends of the screened 1/Vis data exhibit consistency with the temporal evolution of collocated aerosol measurements, including the <i>b</i><sub>ext</sub> trend of −2.4 % yr<sup>−1</sup> (95 % CI: −3.7, −1.1 % yr<sup>−1</sup>) vs. 1/Vis trend of −1.6 % yr<sup>−1</sup> (95 % CI: −2.4, −0.8 % yr<sup>−1</sup>) over the US for 1989–1996, and the fine aerosol mass (PM<sub>2.5</sub>) trend of −5.8 % yr<sup>−1</sup> (95 % CI: −7.8, −4.2 % yr<sup>−1</sup>) vs. 1/Vis trend of −3.4 % yr<sup>−1</sup> (95 % CI: −4.4, −2.4 % yr<sup>−1</sup>) over Europe for 2006–2013. Regional 1/Vis and Emissions Database for Global Atmospheric Research (EDGAR) sulfur dioxide (SO<sub>2</sub>) emissions are significantly correlated over the eastern US for 1970–1995 (<i>r</i> = 0.73), over Europe for 1973–2008 (<i>r</i> ∼ 0.9) and over China for 1973–2008 (<i>r</i> ∼ 0.9). Consistent "reversal points" from increasing to decreasing in SO<sub>2</sub> emission data are also captured by the regional 1/Vis time series (e.g., late 1970s for the eastern US, early 1980s for western Europe, late 1980s for eastern Europe, and mid 2000s for China). The consistency of 1/Vis trends with other in situ measurements and emission data demonstrates promise in applying these quality assured 1/Vis data for historical air quality studies.https://www.atmos-chem-phys.net/16/2435/2016/acp-16-2435-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author C. Li
R. V. Martin
R. V. Martin
B. L. Boys
A. van Donkelaar
S. Ruzzante
S. Ruzzante
spellingShingle C. Li
R. V. Martin
R. V. Martin
B. L. Boys
A. van Donkelaar
S. Ruzzante
S. Ruzzante
Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
Atmospheric Chemistry and Physics
author_facet C. Li
R. V. Martin
R. V. Martin
B. L. Boys
A. van Donkelaar
S. Ruzzante
S. Ruzzante
author_sort C. Li
title Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
title_short Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
title_full Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
title_fullStr Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
title_full_unstemmed Evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
title_sort evaluation and application of multi-decadal visibility data for trend analysis of atmospheric haze
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2016-03-01
description There are few multi-decadal observations of atmospheric aerosols worldwide. This study applies global hourly visibility (Vis) observations at more than 3000 stations to investigate historical trends in atmospheric haze over 1945–1996 for the US, and over 1973–2013 for Europe and eastern Asia. A comprehensive data screening and processing framework is developed and applied to minimize uncertainties and construct monthly statistics of inverse visibility (1/Vis). This data processing includes removal of relatively clean cases with high uncertainty, and change point detection to identify and separate methodological discontinuities such as the introduction of instrumentation. Although the relation between 1/Vis and atmospheric extinction coefficient (<i>b</i><sub>ext</sub>) varies across different stations, spatially coherent trends of the screened 1/Vis data exhibit consistency with the temporal evolution of collocated aerosol measurements, including the <i>b</i><sub>ext</sub> trend of −2.4 % yr<sup>−1</sup> (95 % CI: −3.7, −1.1 % yr<sup>−1</sup>) vs. 1/Vis trend of −1.6 % yr<sup>−1</sup> (95 % CI: −2.4, −0.8 % yr<sup>−1</sup>) over the US for 1989–1996, and the fine aerosol mass (PM<sub>2.5</sub>) trend of −5.8 % yr<sup>−1</sup> (95 % CI: −7.8, −4.2 % yr<sup>−1</sup>) vs. 1/Vis trend of −3.4 % yr<sup>−1</sup> (95 % CI: −4.4, −2.4 % yr<sup>−1</sup>) over Europe for 2006–2013. Regional 1/Vis and Emissions Database for Global Atmospheric Research (EDGAR) sulfur dioxide (SO<sub>2</sub>) emissions are significantly correlated over the eastern US for 1970–1995 (<i>r</i> = 0.73), over Europe for 1973–2008 (<i>r</i> ∼ 0.9) and over China for 1973–2008 (<i>r</i> ∼ 0.9). Consistent "reversal points" from increasing to decreasing in SO<sub>2</sub> emission data are also captured by the regional 1/Vis time series (e.g., late 1970s for the eastern US, early 1980s for western Europe, late 1980s for eastern Europe, and mid 2000s for China). The consistency of 1/Vis trends with other in situ measurements and emission data demonstrates promise in applying these quality assured 1/Vis data for historical air quality studies.
url https://www.atmos-chem-phys.net/16/2435/2016/acp-16-2435-2016.pdf
work_keys_str_mv AT cli evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
AT rvmartin evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
AT rvmartin evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
AT blboys evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
AT avandonkelaar evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
AT sruzzante evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
AT sruzzante evaluationandapplicationofmultidecadalvisibilitydatafortrendanalysisofatmospherichaze
_version_ 1725952919689232384