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This article proposes three spatial statistics approaches for estimating the distribution of \(\text {PM}_{10}\) concentrations in Lombardy, enabling the construction of exceedance probability maps to support regulatory risk assessment beyond mean-based summaries. By relying on daily \(\text {PM}_{10}\) concentration data, the analysis explores how different statistical paradigms and input resolutions influence spatial predictions. The obtained results show that the considered distributional approaches offer flexible tools for characterizing pollution variability, supporting robust assessments of environmental risk and guiding air quality management strategies.

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Three Spatial Methods for Assessing PM10 Concentration in the Lombardy Region

  • 会议论文

  • 发表日期：

    2025年

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  • Andrea Gilardi,
  • Marco F. De Sanctis,
  • Giacomo Milan,
  • Francesca Ieva,
  • Laura M. Sangalli,
  • Piercesare Secchi

摘要

This article proposes three spatial statistics approaches for estimating the distribution of \(\text {PM}_{10}\) concentrations in Lombardy, enabling the construction of exceedance probability maps to support regulatory risk assessment beyond mean-based summaries. By relying on daily \(\text {PM}_{10}\) concentration data, the analysis explores how different statistical paradigms and input resolutions influence spatial predictions. The obtained results show that the considered distributional approaches offer flexible tools for characterizing pollution variability, supporting robust assessments of environmental risk and guiding air quality management strategies.