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Familial Differences in Personal PM2.5 Exposure within a Rural African Community Explained with Spatiotemporal Exposure Apportionment

  • Ky Tanner
  • , Howard H. Chang
  • , Maggie L. Clark
  • , Vincent Cleveland
  • , Egide Kalisa
  • , Kayleigh P. Keller
  • , Christian L’Orange
  • , Theoneste Ntakirutimana
  • , Casey Quinn
  • , Rebecca Witinok-Huber
  • , Bonnie N. Young
  • , John Volckens

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Exposure to fine particulate matter (PM2.5) from solid-fuel combustion is a major determinant of global morbidity and mortality. However, variations in exposure remain uncertain across many high-risk populations. This work describes personal PM2.5 exposures among household members (adult men, adult women, and children) in rural sub-Saharan Africa, where biomass fuel is the primary household energy source. We assessed personal PM2.5 exposures using wearable monitors that combined real-time sensing, time-integrated (gravimetric filter) sampling, and continuous location-activity tracking over 48 h periods. A total of 1280 samples were collected from 579 Rwandan homes over a 15-month period comprising 304 men (aged 23–84 years), 495 women (aged 20–84 years), and 481 children (aged 8–17 years). Linear mixed models, controlling for household, suggested that children were exposed to 14% (CI: 6, 22%) more PM2.5 than their mothers and 100% (CI: 85, 117%) more than their fathers. Spatiotemporal analyses, aggregated into various microenvironments (e.g., home, school, transit, agricultural fieldwork), reveal that children bore a disproportionate exposure burden from in-home cooking activities compared with their parents. Results from this work indicate that interventions for household energy systems, in conjunction with familial lifestyle and behavior modifications, are necessary to reduce personal PM2.5 exposures in rural Rwanda, especially among children.

Original languageEnglish
Pages (from-to)15661-15669
Number of pages9
JournalEnvironmental Science and Technology
Volume59
Issue number30
Early online dateJul 24 2025
DOIs
StatePublished - Aug 5 2025

Keywords

  • Eastern Africa
  • UPAS
  • air pollution
  • fine particulate matter
  • machine learning
  • microenvironment
  • personal sampling
  • solid-fuel combustion

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