Source apportionment of fine particulate matter (PM2.5) personal exposures: findings from the Household Air Pollution Intervention Network (HAPIN) study in rural Guatemala

Abstract Background Source apportionment is a method that reconstructs sources of pollution from monitored values. The identification of these sources is important to develop interventions and other strategies to improve environmental quality. Objective This study aimed to identify and quantify potential sources that contribute to fine particulate matter (PM 2.5 ) personal exposures in a cohort of pregnant women participating in a fuel-cooking intervention trial in Guatemala. Methods We estimated the PM 2.5 and black carbon (BC) concentrations from 629 polytetrafluoroethylene (PTFE) filter samples using gravimetric and transmittance analyses, and we analyzed inorganic elements using energy dispersive X-ray fluorescence (ED-XRF). The filters correspond to personal exposure samples collected with the Enhanced Children’s MicroPEM™ (ECM) from pregnant women who cook using biomass or liquefied petroleum gas (LPG) fuels within the Household Air Pollution Intervention Network (HAPIN) randomized-controlled trial in rural Jalapa, Guatemala. We used the U.S. Environmental Protection Agency’s (EPA) Positive Matrix Factorization (PMF) model to identify the potential sources. Results A four-factor source apportionment model was derived from PMF. The potential sources and their relative contributions to PM 2.5 mass were identified as: biomass burning ( ~ 69.6%), fossil fuels (22%), crustal, and other soil ( ~ 4% each). When categorizing our samples by study group, baseline (155 µg/m 3 ; 95% CI: 129.7, 180.2) and post-intervention control (127.2 µg/m 3 ; 95% CI: 114.7, 139.7) samples had the highest amount of PM 2.5 mass (49.7% and 40.7%, respectively) compared to 9.6% (29.9 µg/m 3 ; 95% CI: 27.2, 32.7) from intervention samples. Significance We identified biomass burning, fossil fuel burning, crustal and other soil as sources of PM 2.5 pollution in rural Jalapa, Guatemala. These findings pave the road for future source apportionment studies in this region and highlight the importance of source characterization to implement interventions to reduce PM 2.5 emissions. Impact We identified four potential sources of PM 2.5 in rural Jalapa, Guatemala, based on personal exposure samples from pregnant women participating in the HAPIN trial. Biomass and fossil fuel burning are the sources with the highest contributions, followed by crustal and other soil. The findings of this study highlight the potential to prioritize emissions reduction efforts in rural Guatemala through the implementation of specific interventions based on the derived sources of pollution.

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Journal
Journal of Exposure Science & Environmental Epidemiology
Published
2026-06-26
DOI
https://doi.org/10.1038/s41370-026-00910-6
Primary Topic
Air Quality and Health Impacts
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article
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article

Source apportionment of fine particulate matter (PM2.5) personal exposures: findings from the Household Air Pollution Intervention Network (HAPIN) study in rural Guatemala

Howard H. Chang, Shakir Hossen, Joshua P. Rosenthal, Florien Ndagijimana et al.
Journal of Exposure Science & Environmental Epidemiology
Air Quality and Health Impacts
article

Source apportionment of fine particulate matter (PM2.5) personal exposures: findings from the Household Air Pollution Intervention Network (HAPIN) study in rural Guatemala

Howard H. Chang, Shakir Hossen, Joshua P. Rosenthal, Florien Ndagijimana, Maggie L. Clark, Lisa de las Fuentes, Kalpana Balakrishnan, Azhar Nizam, Ephrem Dusabimana, Katherine Kearns, Bernard Mutariyani, Carmen Lucía Contreras, Libny Monroy, Eduardo Canúz, Kirk R. Smith, Steven A. Harvey, Penelope P. Howards, Anaité Díaz-Artiga, Thomas Clasen, Priya Dsouza, Gurusamy Thangavel, Kyle Steenland, Adly Castañaza, J J Wang, Jane Mbabazi, Aris T. Papageorghiou, Rengaraj Ramasami, Vigneswari Aravindalochanan, Saritha Sendhil, Gloriose Bankundiye, John P. McCracken, Jacob Kremer, Jean de Dieu Ntivuguruzwa, Miles A. Kirby, Shirin Jabbarzadeh, Sarah Hamid, Sankar Sambandam, Y H Chen, Dina Goodman, Jeremy A. Sarnat, D. J. Barr, Alexie Mukeshimana, Rachel Craik, Jiawen Liao, Irma Sayury Pineda Fuentes, Viviane Valdes, Marilú Chiang, Margaret A. Laws, V. Davila-Roman, Mayarí Hengstermann, P. Barry Ryan, Luke P. Naeher, Julia N. McPeek, Lawrence Moulton, Alexander Ramirez, Ajay Pillarisetti, Juan Gabriel Espinoza, Oscar De Léon, J Jaime Miranda, Dr Amit Verma, Sheela S. Sinharoy, Krishnendu Mukhopadhyay, Michael Johnson, S Hartinger, L Nicolaou, E D Mccollum, J Peel, Lisa M. Thompson, Ghislaine Rosa, Lindsay J. Underhill, Armistead G. Russell, Ricardo Piedrahita, Rachel Meyers, Sudhakar Saidam, Parinya Panuwet, Grace Lee, Suzanne Simkovich, Savannah Gupton, Alejandra Bussalleu, Lisa Elon, Vanessa Burrowes, Sarah Rajkumar, Devan Campbell, Ian Hennessee, Erick Mollinedo, Christian L’Orange, Lance A. Waller, Elisa Puzzolo, Usha Ramakrishnan, Pattie Lenzen, Ahana Ghosh, Ashley Toenjes, Naveen Puttaswamy, Marjorie Howard, HAPIN Investigators, Durairaj Natesan, William Checkley, Sarada S. Garg, Amy E. Lovvorn, Phabiola Herrera
article en

Abstract

Abstract Background Source apportionment is a method that reconstructs sources of pollution from monitored values. The identification of these sources is important to develop interventions and other strategies to improve environmental quality. Objective This study aimed to identify and quantify potential sources that contribute to fine particulate matter (PM 2.5 ) personal exposures in a cohort of pregnant women participating in a fuel-cooking intervention trial in Guatemala. Methods We estimated the PM 2.5 and black carbon (BC) concentrations from 629 polytetrafluoroethylene (PTFE) filter samples using gravimetric and transmittance analyses, and we analyzed inorganic elements using energy dispersive X-ray fluorescence (ED-XRF). The filters correspond to personal exposure samples collected with the Enhanced Children’s MicroPEM™ (ECM) from pregnant women who cook using biomass or liquefied petroleum gas (LPG) fuels within the Household Air Pollution Intervention Network (HAPIN) randomized-controlled trial in rural Jalapa, Guatemala. We used the U.S. Environmental Protection Agency’s (EPA) Positive Matrix Factorization (PMF) model to identify the potential sources. Results A four-factor source apportionment model was derived from PMF. The potential sources and their relative contributions to PM 2.5 mass were identified as: biomass burning ( ~ 69.6%), fossil fuels (22%), crustal, and other soil ( ~ 4% each). When categorizing our samples by study group, baseline (155 µg/m 3 ; 95% CI: 129.7, 180.2) and post-intervention control (127.2 µg/m 3 ; 95% CI: 114.7, 139.7) samples had the highest amount of PM 2.5 mass (49.7% and 40.7%, respectively) compared to 9.6% (29.9 µg/m 3 ; 95% CI: 27.2, 32.7) from intervention samples. Significance We identified biomass burning, fossil fuel burning, crustal and other soil as sources of PM 2.5 pollution in rural Jalapa, Guatemala. These findings pave the road for future source apportionment studies in this region and highlight the importance of source characterization to implement interventions to reduce PM 2.5 emissions. Impact We identified four potential sources of PM 2.5 in rural Jalapa, Guatemala, based on personal exposure samples from pregnant women participating in the HAPIN trial. Biomass and fossil fuel burning are the sources with the highest contributions, followed by crustal and other soil. The findings of this study highlight the potential to prioritize emissions reduction efforts in rural Guatemala through the implementation of specific interventions based on the derived sources of pollution.

Journal of Exposure Science & Environmental Epidemiology
Boston Children's Hospital (US), National Institutes of Health (US), Georgia Institute of Technology (US), Harvard University (US), Johns Hopkins University (US), University of Liverpool (GB), Emory University (US), University of Georgia (US), Universidad Peruana Cayetano Heredia (PE), Sri Ramachandra Institute of Higher Education and Research (IN), Washington University in St. Louis (US), Johns Hopkins Medicine (US), University of Oxford (GB), Berkeley Air Monitoring Group (United States) (US), Prisma (PE), Global Water Partnership West Africa (BF), Harvard Global Health Institute (US), MedStar Health (US), Fogarty International Center (US), Universidad del Valle de Guatemala (GT), Colorado State University (US), University of California, Berkeley (US)
U.S. Department of Health and Human Services, Bill and Melinda Gates Foundation, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, Fogarty International Center, National Institute of Child Health and Human Development, Office of Strategic Coordination, Common Fund
Openalex Percentile: Top 8%
Air Quality and Health Impacts
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