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Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
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A Multi-Source Sensor Dataset for Spain: Integrating Air Quality, Meteorological, Mobility and Calendar Records.

Juan Bonastre-Egea1, Andrés Bueno-Crespo1, Juan Morales-García2

  • 1Escuela Politécnica Superior, Universidad Católica de Murcia (UCAM), 30107 Murcia, Spain.

Sensors (Basel, Switzerland)
|June 26, 2026
PubMed
Summary

This study introduces an open, integrated dataset for Spain (2022-2024) combining air quality, weather, and mobility data. This comprehensive resource supports advanced environmental health and air quality forecasting research.

Keywords:
Spainair quality monitoringenvironmental monitoringmeteorological sensorsmobile network mobility datamulti-source sensor integrationnationwideopen dataset

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Area of Science:

  • Environmental Science
  • Data Science
  • Public Health

Background:

  • Air quality forecasting and environmental health research require integrated multi-source data, which is often not readily available.
  • Existing sensor networks are heterogeneous, posing challenges for data fusion and analysis.

Purpose of the Study:

  • To present a novel, open-access, integrated dataset combining diverse environmental and mobility data for Spain.
  • To provide a harmonized data resource for research in air quality forecasting, environmental epidemiology, and data fusion.

Main Methods:

  • Combined hourly air quality data (MITECO), daily meteorological data (AEMET), daily mobility indicators (MITMA), and public holidays.
  • Developed a processing pipeline to harmonize data with differing temporal resolutions, spatial codifications, and quality regimes.
  • Implemented spatial pairing of air quality and meteorological stations and temporal alignment schemes for data integration.

Main Results:

  • Created an integrated dataset with approximately 15 million hourly records and 56 variables per record for Spain (2022-2024).
  • Released both hourly and daily resolution variants of the dataset.
  • The dataset is publicly available on Zenodo under a CC BY 4.0 license (DOI 10.5281/zenodo.20196221).

Conclusions:

  • The presented open dataset provides a valuable substrate for nationwide research on air quality and environmental health.
  • Facilitates advanced studies in air quality forecasting, environmental epidemiology, and multi-source data fusion.
  • The harmonized and integrated nature of the dataset simplifies downstream analysis and promotes reproducible research.