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@ARTICLE{Wang:1050288,
      author       = {Wang, Hantao and Miyazaki, Kazuyuki and Sun, Haitong Zhe
                      and Qu, Zhen and Liu, Xiang and Inness, Antje and Schultz,
                      Martin and Schröder, Sabine and Serre, Marc and West, J.
                      Jason},
      title        = {{I}ntercomparison of global ground-level ozone datasets for
                      health-relevant metrics},
      journal      = {Atmospheric chemistry and physics},
      volume       = {25},
      number       = {22},
      issn         = {1680-7316},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2026-00098},
      pages        = {15969 - 15990},
      year         = {2025},
      abstract     = {Ground-level ozone is a significant air pollutant that
                      detrimentally affects human health and agriculture. Global
                      ground-level ozone concentrations have been estimated using
                      chemical reanalyses, geostatistical methods, and machine
                      learning, but these datasets have not been compared
                      systematically. We compare six global ground-level ozone
                      datasets (three chemical reanalyses, two machine learning,
                      one geostatistics) relative to observations and against one
                      another, for the ozone season daily maximum 8 h average
                      mixing ratio, for 2006 to 2016. Comparing with global
                      ground-level observations, most datasets overestimate ozone,
                      particularly at lower observed concentrations. In 2016,
                      across all stations, grid-to-grid R2 ranges from 0.50 to
                      0.75 and RMSE 4.25 to 12.22 ppb. Agreement with observed
                      distributions is reduced at ozone concentrations above
                      50 ppb. Results show significant differences among
                      datasets in global average ozone, as large as 5–10 ppb,
                      multi-year trends, and regional distributions. For example,
                      in Europe, the two chemical reanalyses show an increasing
                      trend while other datasets show no increase. Among the six
                      datasets, the share of population exposed to over 50 ppb
                      varies from $61 \%$ $[28 \%,$ $94 \%]$ to $99 \%$
                      $[62 \%,$ $100 \%]$ in East Asia, $17 \%$ $[4 \%,$
                      $72 \%]$ to $88 \%$ $[53 \%,$ $99 \%]$ in North
                      America, and $9 \%$ $[0 \%,$ $58 \%]$ to $76 \%$
                      $[22 \%,$ $96 \%]$ in Europe (2006–2016 average).
                      Although sharing some of the same input data, we found
                      important differences, likely from variations in approaches,
                      resolution, and other input data, highlighting the
                      importance of continued research on global ozone
                      distributions. These discrepancies are large enough to
                      impact assessments of health impacts and other
                      applications.},
      cin          = {JSC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / Earth System Data
                      Exploration (ESDE)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-Juel-1)ESDE},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.5194/acp-25-15969-2025},
      url          = {https://juser.fz-juelich.de/record/1050288},
}