% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Lefohn:845585,
      author       = {Lefohn, Allen S. and Malley, Christopher S. and Smith,
                      Luther and Wells, Benjamin and Hazucha, Milan and Simon,
                      Heather and Naik, Vaishali and Mills, Gina and Schultz,
                      Martin and Paoletti, Elena and De Marco, Alessandra and Xu,
                      Xiaobin and Zhang, Li and Wang, Tao and Neufeld, Howard S.
                      and Musselman, Robert C. and Tarasick, David and Brauer,
                      Michael and Feng, Zhaozhong and Tang, Haoye and Kobayashi,
                      Kazuhiko and Sicard, Pierre and Solberg, Sverre and Gerosa,
                      Giacomo},
      title        = {{T}ropospheric ozone assessment report: {G}lobal ozone
                      metrics for climate change, human health, and crop/ecosystem
                      research},
      journal      = {Elementa},
      volume       = {6},
      issn         = {2325-1026},
      address      = {Washington, DC},
      publisher    = {BioOne},
      reportid     = {FZJ-2018-02810},
      pages        = {28},
      year         = {2018},
      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.},
      cin          = {IEK-8 / JSC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IEK-8-20101013 / I:(DE-Juel1)JSC-20090406},
      pnm          = {243 - Tropospheric trace substances and their
                      transformation processes (POF3-243) / 512 - Data-Intensive
                      Science and Federated Computing (POF3-512) / Earth System
                      Data Exploration (ESDE)},
      pid          = {G:(DE-HGF)POF3-243 / G:(DE-HGF)POF3-512 /
                      G:(DE-Juel-1)ESDE},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000429374000001},
      pubmed       = {pmid:30345319},
      doi          = {10.1525/elementa.279},
      url          = {https://juser.fz-juelich.de/record/845585},
}