{
  "abstract": "Although fine particles (PM 2.5 ) concentrations in China have declined over the past decade, exposure disparities persist at hyperlocal scales. We conducted a six-month mobile monitoring campaign in Shenzhen, where four taxis with calibrated low-cost sensors gathered 24.6 million 1 Hz measurements (~3,700 hours) across 550 km² and 7.3 million residents. We developed a novel application of a multi-source XGBoost (MS-XGB) framework that integrates mobile and fixed-site station data to reconstruct a road-network PM 2.5 dataset at 30 m × 1 h resolution, filling 98% of missing observations. Validation demonstrates strong agreement with both mobile observations (R 2 = 0.97) and data from fixed regulatory monitoring stations (Pearson r = 0.82). We used the road-network dataset to generate a 100 m × 100 m population grid exposure map and benchmarked it against two conventional exposure assessment approaches that rely solely on fixed-site regulatory stations. Relative to MS-XGB, conventional methods systematically underestimated long-term PM 2.5 exposure, with grid-level differences of up to 15 μg/m³. Population-weighted mean exposure was higher in urban villages (16.51 µg/m³) than in other urban areas (14.41 µg/m³), with hotspots 52.5% more likely to occur in urban villages. In Longhua, high exposure was concentrated specifically in urban villages, indicating that district-level averages can mask substantial intra-district heterogeneity. In Nanshan, 40% of elderly residents live in high-exposure areas, compared with 34% of children aged 0–14 and 33% of adults aged 15–59, suggesting that older adults bear a disproportionate exposure burden and face elevated health risks. Our findings demonstrate that mobile-monitoring-based hyperlocal exposure assessment is essential for revealing true PM 2.5 exposure inequalities across population groups and spatial environments that are overlooked by conventional fixed-site approaches.",
  "abstract_shown": true,
  "affiliations": [
    "Sustainable Energy & Environment Thrust, Function Hub",
    "The Hong Kong University of Science and Technology (Guangzhou)",
    "Meta, 1 Meta Way, Menlo Park, CA, United States, 94025",
    "Soarability Technologies, Kexing Science Park, Building D, 24F, Nanshan District, Shenzhen, Guangdong, 518057",
    "Division of Natural and Applied Sciences, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, Jiangsu, China, 215316",
    "Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Ministry of Ecology and Environment",
    "Shanghai Academy of Environmental Sciences"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Zilin Guo",
      "orcid": "0009-0008-5678-3338"
    },
    {
      "affs": [
        2
      ],
      "name": "Ziyang Jiang"
    },
    {
      "affs": [
        3
      ],
      "name": "Shutong Jiang"
    },
    {
      "affs": [
        4
      ],
      "name": "Tongshu Zheng"
    },
    {
      "affs": [
        0,
        1,
        5,
        6
      ],
      "name": "Yutong Liang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/427prp0hb9t6p.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15009050/v1",
  "fulltext_url": null,
  "id": "427prp0hb9t6p",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009050/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2307|Air Quality and Health Impacts"
    ]
  ],
  "openalex": "W7213552552",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15009050/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/427prp0hb9t6p.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:19Z",
      "native_id": "10.26434/chemrxiv.15009050",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009050/v2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2307|Air Quality and Health Impacts",
      "subfield": "pharmacology-toxicology"
    }
  ],
  "title": "Hyperlocal PM2.5 Exposure and Health Burden Disparities Revealed by a Taxi-Based Mobile Monitoring Platform in Shenzhen",
  "title_text": "Hyperlocal PM2.5 Exposure and Health Burden Disparities Revealed by a Taxi-Based Mobile Monitoring Platform in Shenzhen",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:21Z",
  "url": "https://research.draconitic.com/paper/427prp0hb9t6p",
  "venue": "ChemRxiv",
  "versions": []
}