{
  "abstract": "Statistical models that relate PM₂.₅ to meteorology are widely used to separate weather from emission effects, but they are rarely evaluated out of sample in clean, high-altitude cities, and the role of their trend term is seldom examined. This study fitted penalized additive spline models to hourly city-average PM₂.₅ in Lhasa, Tibetan Plateau (about 3,650 m a.s.l.), for 2019–2024 (51,955 valid hours), using ERA5 temperature, relative humidity, wind speed and precipitation as current-hour and 24-hour antecedent predictors with seasonal, diurnal and long-term controls, and benchmarked them against calendar, linear and random forest models. Three results emerge. First, the point-estimated wind and humidity responses are carried mainly by antecedent conditions: in perturbation decompositions, the 24-hour terms carry most of the fitted wind and humidity sensitivity. Second, the trend specification governs both the weather-normalized series and out-of-sample bias: a linear trend forces a near-monotonic normalized decline (10.98 to 9.66 µg/m³), although observed annual means fell from 12.16 to 8.55 µg/m³ by 2022 and rebounded to 10.36 µg/m³ in 2024. Third, a model frozen after 2019–2024 explained 42% of hourly and 60% of daily variance in 2025 (RMSE 5.35 and 2.80 µg/m³; calendar-only benchmark: 32% and 41%) and modestly outperformed the linear benchmark, but errors were concentrated in winter and in a few high-concentration hours; Gutor-evening residuals exceeded the same-year, same-hour winter background in five of the six years of the 2019–2024 record. Weather-normalized trends for Plateau cities should therefore be reported with alternative trend specifications and event-level diagnostics.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Zhongjie Ma"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9jmj7tee9qxm3.bib",
  "cited_by": 0,
  "doi": "10.31223/x5z817",
  "fulltext_url": null,
  "id": "9jmj7tee9qxm3",
  "issns": [],
  "landing_url": "https://eartharxiv.org/repository/view/15941/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/legalcode",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Lhasa"
    ],
    [
      "bepress",
      "Oceanography and Atmospheric Sciences and Meteorology"
    ],
    [
      "bepress",
      "PM₂.₅"
    ],
    [
      "bepress",
      "Tibetan Plateau"
    ],
    [
      "bepress",
      "generalized additive model"
    ],
    [
      "bepress",
      "out-of-sample evaluation"
    ],
    [
      "bepress",
      "weather normalization"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://eartharxiv.org/repository/object/15941/download/27577/",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9jmj7tee9qxm3.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:20:46Z",
      "native_id": "15941",
      "source": "eartharxiv",
      "url": "https://eartharxiv.org/repository/view/15941/"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "bepress:Oceanography and Atmospheric Sciences and Meteorology",
      "subfield": "atmospheric"
    },
    {
      "field": "earth",
      "origin": "bepress:Oceanography and Atmospheric Sciences and Meteorology",
      "subfield": "oceanography"
    }
  ],
  "title": "Meteorological associations of hourly PM₂.₅ in Lhasa, Tibetan Plateau: antecedent weather, trend specification and out-of-sample evaluation",
  "title_text": "Meteorological associations of hourly PM₂.₅ in Lhasa, Tibetan Plateau: antecedent weather, trend specification and out-of-sample evaluation",
  "type": "preprint",
  "updated_at": "2026-11-05T12:20:12Z",
  "url": "https://research.draconitic.com/paper/9jmj7tee9qxm3",
  "venue": "EarthArXiv",
  "versions": []
}