Tropospheric ozone assessment report: Global ozone metrics for climate change, human health, and crop/ecosystem research

Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Inv...

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Published in:Elementa (Washington, D.C.) Vol. 6; no. 1; p. 1
Main Authors: Lefohn, Allen S., Malley, Christopher S., Smith, Luther, Wells, Benjamin, Hazucha, Milan, Simon, Heather, Naik, Vaishali, Mills, Gina, Schultz, Martin G., Paoletti, Elena, De Marco, Alessandra, Xu, Xiaobin, Zhang, Li, Wang, Tao, Neufeld, Howard S., Musselman, Robert C., Tarasick, David, Brauer, Michael, Feng, Zhaozhong, Tang, Haoye, Kobayashi, Kazuhiko, Sicard, Pierre, Solberg, Sverre, Gerosa, Giacomo
Format: Journal Article
Language:English
Published: United States BioOne 2018
Subjects:
ground-level ozone
metrics
ozone distributions
shifting ozone concentrations
trends
tropospheric ozone
tropospheric ozone
ground-level ozone
metrics
ozone distributions
trends
shifting ozone concentrations
ISSN:2325-1026, 2325-1026
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Abstract Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
AbstractList Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the 'Tropospheric Ozone Assessment Report (TOAR)' is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
Author Xu, Xiaobin
Wells, Benjamin
Musselman, Robert C.
Solberg, Sverre
Zhang, Li
Feng, Zhaozhong
Lefohn, Allen S.
Simon, Heather
Wang, Tao
Paoletti, Elena
De Marco, Alessandra
Mills, Gina
Kobayashi, Kazuhiko
Gerosa, Giacomo
Brauer, Michael
Smith, Luther
Malley, Christopher S.
Schultz, Martin G.
Sicard, Pierre
Hazucha, Milan
Neufeld, Howard S.
Tang, Haoye
Naik, Vaishali
Tarasick, David
AuthorAffiliation Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, CN
NERC Centre for Ecology and Hydrology, Environment Centre Wales, Bangor, UK
Air Quality Research Division, Environment and Climate Change Canada, Downsview, ON, CA
School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, CA
ACRI-HE, 260 route du Pin Montard BP234, Sophia Antipolis, FR
Center for Environmental Medicine, Asthma, and Lung Biology, University of North Carolina, Chapel Hill, NC, US
Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, JP
Norwegian Institute for Air Research (NILU), Kjeller, NO
School of Chemistry, University of Edinburgh, Edinburgh, UK
A.S.L. & Associates, Helena. MT, US
Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Rome, IT
Stockholm Environment Institute, Environment Department, University of York, York, UK
Department
AuthorAffiliation_xml – name: Forschungszentrum Jülich GmbH, Jülich, DE
– name: Department of Biology, Appalachian State University, Boone,NC, US
– name: NERC Centre for Ecology and Hydrology, Environment Centre Wales, Bangor, UK
– name: Institute for Sustainable Plant Protection, National Research Council, Florence, IT
– name: Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, JP
– name: School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, CA
– name: Institute of Soil Sciences, Chinese Academy of Sciences, Nanjing, CN
– name: School of Chemistry, University of Edinburgh, Edinburgh, UK
– name: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, CN
– name: Norwegian Institute for Air Research (NILU), Kjeller, NO
– name: Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, CN
– name: Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Rome, IT
– name: A.S.L. & Associates, Helena. MT, US
– name: NERC Centre for Ecology and Hydrology, Penicuik, UK
– name: Center for Environmental Medicine, Asthma, and Lung Biology, University of North Carolina, Chapel Hill, NC, US
– name: Alion Science and Technology, Inc., Research Triangle Park, NC, US
– name: NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, US
– name: Air Quality Research Division, Environment and Climate Change Canada, Downsview, ON, CA
– name: Dipartimento di Matematica e Fisica, Università Cattolica del Sacro Cuore, Brescia, IT
– name: Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC, US
– name: Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, CN
– name: Stockholm Environment Institute, Environment Department, University of York, York, UK
– name: USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, US
– name: ACRI-HE, 260 route du Pin Montard BP234, Sophia Antipolis, FR
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  surname: Lefohn
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  organization: A.S.L. & Associates, Helena. MT, US
– sequence: 2
  givenname: Christopher S.
  surname: Malley
  fullname: Malley, Christopher S.
  organization: Stockholm Environment Institute, Environment Department, University of York, York, UK, NERC Centre for Ecology and Hydrology, Penicuik, UK, School of Chemistry, University of Edinburgh, Edinburgh, UK
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  surname: Smith
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  organization: Alion Science and Technology, Inc., Research Triangle Park, NC, US
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  surname: Wells
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  organization: Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC, US
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  givenname: Milan
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  organization: Center for Environmental Medicine, Asthma, and Lung Biology, University of North Carolina, Chapel Hill, NC, US
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  organization: Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC, US
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  givenname: Vaishali
  surname: Naik
  fullname: Naik, Vaishali
  organization: NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, US
– sequence: 8
  givenname: Gina
  surname: Mills
  fullname: Mills, Gina
  organization: NERC Centre for Ecology and Hydrology, Environment Centre Wales, Bangor, UK
– sequence: 9
  givenname: Martin G.
  surname: Schultz
  fullname: Schultz, Martin G.
  organization: Forschungszentrum Jülich GmbH, Jülich, DE
– sequence: 10
  givenname: Elena
  surname: Paoletti
  fullname: Paoletti, Elena
  organization: Institute for Sustainable Plant Protection, National Research Council, Florence, IT
– sequence: 11
  givenname: Alessandra
  surname: De Marco
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  organization: Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Rome, IT
– sequence: 12
  givenname: Xiaobin
  surname: Xu
  fullname: Xu, Xiaobin
  organization: Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, CN
– sequence: 13
  givenname: Li
  surname: Zhang
  fullname: Zhang, Li
  organization: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, CN
– sequence: 14
  givenname: Tao
  surname: Wang
  fullname: Wang, Tao
  organization: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, CN
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– sequence: 16
  givenname: Robert C.
  surname: Musselman
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  organization: USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, US
– sequence: 17
  givenname: David
  surname: Tarasick
  fullname: Tarasick, David
  organization: Air Quality Research Division, Environment and Climate Change Canada, Downsview, ON, CA
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  surname: Brauer
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  organization: School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, CA
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  organization: Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, CN
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  givenname: Haoye
  surname: Tang
  fullname: Tang, Haoye
  organization: Institute of Soil Sciences, Chinese Academy of Sciences, Nanjing, CN
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  organization: Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, JP
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  organization: ACRI-HE, 260 route du Pin Montard BP234, Sophia Antipolis, FR
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  givenname: Giacomo
  surname: Gerosa
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  organization: Dipartimento di Matematica e Fisica, Università Cattolica del Sacro Cuore, Brescia, IT
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30345319$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords tropospheric ozone
ground-level ozone
metrics
ozone distributions
trends
shifting ozone concentrations
Language English
License http://creativecommons.org/licenses/by/4.0
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
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Author contributions Contributed to conception and design: All co-authors.Contributed to acquisition of data: none.Contributed to analysis and interpretation of data: all co-authors.Drafted and/or revised the paper: all co-authors participated in the drafting of the original article, while a subset of the co-authors helped with revision of the various drafts of the manuscript.Approved the submitted and revised versions for publication: all co-authors.
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Snippet Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of...
Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of...
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SubjectTerms ground-level ozone
metrics
ozone distributions
shifting ozone concentrations
trends
tropospheric ozone
Title Tropospheric ozone assessment report: Global ozone metrics for climate change, human health, and crop/ecosystem research
URI https://www.ncbi.nlm.nih.gov/pubmed/30345319
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