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Tryner J, Quinn C, Molina Rueda E, Andales MJ, L'Orange C, Mehaffy J, Carter E, Volckens J. AirPen: A Wearable Monitor for Characterizing Exposures to Particulate Matter and Volatile Organic Compounds. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023. [PMID: 37450410 PMCID: PMC10373498 DOI: 10.1021/acs.est.3c02238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Exposure to air pollution is a leading risk factor for disease and premature death, but technologies for assessing personal exposure to particulate and gaseous air pollutants, including the timing and location of such exposures, are limited. We developed a small, quiet, wearable monitor, called the AirPen, to quantify personal exposures to fine particulate matter (PM2.5) and volatile organic compounds (VOCs). The AirPen combines physical sample collection (PM onto a filter and VOCs onto a sorbent tube) with a suite of low-cost sensors (for PM, VOCs, temperature, pressure, humidity, light intensity, location, and motion). We validated the AirPen against conventional personal sampling equipment in the laboratory and then conducted a field study to measure at-work and away-from-work exposures to PM2.5 and VOCs among employees at an agricultural facility in Colorado, USA. The resultant sampling and sensor data indicated that personal exposures to benzene, toluene, ethylbenzene, and xylenes were dominated by a specific workplace location. These results illustrate how the AirPen can be used to advance our understanding of personal exposure to air pollution as a function of time, location, source, and activity, even in the absence of detailed activity diary data.
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Affiliation(s)
- Jessica Tryner
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - Casey Quinn
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - Emilio Molina Rueda
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - Marie J Andales
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - Christian L'Orange
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - John Mehaffy
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - Ellison Carter
- Department of Civil and Environmental Engineering, Colorado State University, 1372 Campus Delivery, Fort Collins, Colorado 80523, United States
| | - John Volckens
- Department of Mechanical Engineering, Colorado State University, 1374 Campus Delivery, Fort Collins, Colorado 80523, United States
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Johnson M, Piedrahita R, Pillarisetti A, Shupler M, Menya D, Rossanese M, Delapeña S, Penumetcha N, Chartier R, Puzzolo E, Pope D. Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya. INDOOR AIR 2021; 31:1441-1457. [PMID: 33655590 DOI: 10.1111/ina.12790] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 12/24/2020] [Indexed: 06/12/2023]
Abstract
This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM2.5 , black carbon, CO); household air pollution (PM2.5 , CO); personal exposure (PM2.5 , CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single-zone model; indirect exposure models, which combine person-location and area-level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single-zone model was reasonably well-correlated with measured kitchen concentrations of PM2.5 (R2 = 0.45) and CO (R2 = 0.45), but lacked precision. The best performing regression model used a combination of survey-based data and physical measurements (R2 = 0.76) and a root mean-squared error of 85 µg/m3 , and the survey-only-based regression model was able to predict PM2.5 exposures with an R2 of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R2 of 0.57 and RMSE of 98 µg/m3 .
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Affiliation(s)
| | | | - Ajay Pillarisetti
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Matthew Shupler
- Department of Public Health and Policy, University of Liverpool, Liverpool, UK
| | - Diana Menya
- Department of Epidemiology and Medical Statistics, School of Public Health, College of Health Sciences, Moi University, Eldoret, Kenya
| | | | | | | | - Ryan Chartier
- RTI International, Research Triangle Park, North Carolina, USA
| | - Elisa Puzzolo
- Department of Public Health and Policy, University of Liverpool, Liverpool, UK
- Global LPG Partnership, London, UK
| | - Daniel Pope
- Department of Public Health and Policy, University of Liverpool, Liverpool, UK
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Gould CF, Schlesinger SB, Molina E, Lorena Bejarano M, Valarezo A, Jack DW. Long-standing LPG subsidies, cooking fuel stacking, and personal exposure to air pollution in rural and peri-urban Ecuador. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2020; 30:707-720. [PMID: 32415299 PMCID: PMC7316622 DOI: 10.1038/s41370-020-0231-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 03/06/2020] [Accepted: 04/23/2020] [Indexed: 05/05/2023]
Abstract
Ecuador presents a unique case study for evaluating personal air pollution exposure in a middle-income country where a clean cooking fuel has been available at low cost for several decades. We measured personal PM2.5 exposure, stove use, and participant location during a 48-h monitoring period for 157 rural and peri-urban households in coastal and Andean Ecuador. While nearly all households owned a liquefied petroleum gas (LPG) stove and used it as their primary cooking fuel, one-quarter of households utilized firewood as a secondary fuel and 10% used induction stoves secondary to LPG. Stove use monitoring demonstrated clear within- and across-meal fuel stacking patterns. Firewood-owning participants had higher distributions of 48-h and 10-min PM2.5 exposure as compared with primary LPG and induction stove users, and this effect became more pronounced with firewood use during monitoring.Accounting for within-subject clustering, contemporaneous firewood stove use was associated with 101 μg/m3 higher 10-min PM2.5 exposure (95% CI: 94-108 μg/m3). LPG and induction cooking events were largely not associated with contemporaneous PM2.5 exposure. Our results suggest that firewood use is associated with average and short-term personal air pollution exposure above the WHO interim-I guideline, even when LPG is the primary cooking fuel.
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Affiliation(s)
- Carlos F Gould
- Department of Environmental Health Science, Columbia University Mailman School of Public Health, New York, NY, USA
| | | | - Emilio Molina
- Department of Mechanical Engineering, Universidad San Francisco de Quito, Quito, Ecuador
| | - M Lorena Bejarano
- Department of Mechanical Engineering, Universidad San Francisco de Quito, Quito, Ecuador
| | - Alfredo Valarezo
- Department of Mechanical Engineering, Universidad San Francisco de Quito, Quito, Ecuador
| | - Darby W Jack
- Department of Environmental Health Science, Columbia University Mailman School of Public Health, New York, NY, USA.
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Johnson MA, Steenland K, Piedrahita R, Clark ML, Pillarisetti A, Balakrishnan K, Peel JL, Naeher LP, Liao J, Wilson D, Sarnat J, Underhill LJ, Burrowes V, McCracken JP, Rosa G, Rosenthal J, Sambandam S, de Leon O, Kirby MA, Kearns K, Checkley W, Clasen T. Air Pollutant Exposure and Stove Use Assessment Methods for the Household Air Pollution Intervention Network (HAPIN) Trial. ENVIRONMENTAL HEALTH PERSPECTIVES 2020; 128:47009. [PMID: 32347764 PMCID: PMC7228125 DOI: 10.1289/ehp6422] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 03/27/2020] [Accepted: 04/01/2020] [Indexed: 05/05/2023]
Abstract
BACKGROUND High quality personal exposure data is fundamental to understanding the health implications of household energy interventions, interpreting analyses across assigned study arms, and characterizing exposure-response relationships for household air pollution. This paper describes the exposure data collection for the Household Air Pollution Intervention Network (HAPIN), a multicountry randomized controlled trial of liquefied petroleum gas stoves and fuel among 3,200 households in India, Rwanda, Guatemala, and Peru. OBJECTIVES The primary objectives of the exposure assessment are to estimate the exposure contrast achieved following a clean fuel intervention and to provide data for analyses of exposure-response relationships across a range of personal exposures. METHODS Exposure measurements are being conducted over the 3-y time frame of the field study. We are measuring fine particulate matter [PM < 2.5 μ m in aerodynamic diameter (PM 2.5 )] with the Enhanced Children's MicroPEM™ (RTI International), carbon monoxide (CO) with the USB-EL-CO (Lascar Electronics), and black carbon with the OT21 transmissometer (Magee Scientific) in pregnant women, adult women, and children < 1 year of age, primarily via multiple 24-h personal assessments (three, six, and three measurements, respectively) over the course of the 18-month follow-up period using lightweight monitors. For children we are using an indirect measurement approach, combining data from area monitors and locator devices worn by the child. For a subsample (up to 10%) of the study population, we are doubling the frequency of measurements in order to estimate the accuracy of subject-specific typical exposure estimates. In addition, we are conducting ambient air monitoring to help characterize potential contributions of PM 2.5 exposure from background concentration. Stove use monitors (Geocene) are being used to assess compliance with the intervention, given that stove stacking (use of traditional stoves in addition to the intervention gas stove) may occur. CONCLUSIONS The tools and approaches being used for HAPIN to estimate personal exposures build on previous efforts and take advantage of new technologies. In addition to providing key personal exposure data for this study, we hope the application and learnings from our exposure assessment will help inform future efforts to characterize exposure to household air pollution and for other contexts. https://doi.org/10.1289/EHP6422.
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Affiliation(s)
| | - Kyle Steenland
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | | | - Maggie L Clark
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Ajay Pillarisetti
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Kalpana Balakrishnan
- Department of Environmental Health Engineering, ICMR Center for Advanced Research on Air Quality, Climate and Health, Sri Ramachandra Institute for Higher Education and Research (Deemed University), Chennai, India
| | - Jennifer L Peel
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado, USA
| | - Luke P Naeher
- Department of Environmental Health Science, College of Public Health, University of Georgia, Athens, Georgia, USA
| | - Jiawen Liao
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | | | - Jeremy Sarnat
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Lindsay J Underhill
- Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Vanessa Burrowes
- Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - John P McCracken
- Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Ghislaine Rosa
- Department of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Joshua Rosenthal
- Division of Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, USA
| | - Sankar Sambandam
- Department of Environmental Health Engineering, ICMR Center for Advanced Research on Air Quality, Climate and Health, Sri Ramachandra Institute for Higher Education and Research (Deemed University), Chennai, India
| | - Oscar de Leon
- Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Miles A Kirby
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Katherine Kearns
- Department of Environmental Health Engineering, ICMR Center for Advanced Research on Air Quality, Climate and Health, Sri Ramachandra Institute for Higher Education and Research (Deemed University), Chennai, India
| | - William Checkley
- Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Thomas Clasen
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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Kitchen Area Air Quality Measurements in Northern Ghana: Evaluating the Performance of a Low-Cost Particulate Sensor within a Household Energy Study. ATMOSPHERE 2019. [DOI: 10.3390/atmos10070400] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Household air pollution from the combustion of solid fuels is a leading global health and human rights concern, affecting billions every day. Instrumentation to assess potential solutions to this problem faces challenges—especially related to cost. A low-cost ($159) particulate matter tool called the Household Air Pollution Exposure (HAPEx) Nano was evaluated in the field as part of the Prices, Peers, and Perceptions cookstove study in northern Ghana. Measurements of temperature, relative humidity, absolute humidity, and carbon dioxide and carbon monoxide concentrations made at 1-min temporal resolution were integrated with 1-min particulate matter less than 2.5 microns in diameter (PM2.5) measurements from the HAPEx, within 62 kitchens, across urban and rural households and four seasons totaling 71 48-h deployments. Gravimetric filter sampling was undertaken to ground-truth and evaluate the low-cost measurements. HAPEx baseline drift and relative humidity corrections were investigated and evaluated using signals from paired HAPEx, finding significant improvements. Resulting particle coefficients and integrated gravimetric PM2.5 concentrations were modeled to explore drivers of variability; urban/rural, season, kitchen characteristics, and dust (a major PM2.5 mass constituent) were significant predictors. The high correlation (R2 = 0.79) between 48-h mean HAPEx readings and gravimetric PM2.5 mass (including other covariates) indicates that the HAPEx can be a useful tool in household energy studies.
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Abstract
Biomass burning for home energy use is a major environmental health concern. Improved cooking technologies could generate environmental health benefits, yet prior results regarding reduced personal exposure to air pollution are mixed. In this study, two improved stove types were distributed over four study groups in Northern Ghana. Participants wore real-time carbon monoxide (CO) monitors to measure the effect of the intervention on personal exposures. Relative to the control group (those using traditional stoves), there was a 30.3% reduction in CO exposures in the group given two Philips forced draft stoves (p = 0.08), 10.5% reduction in the group given two Gyapa stoves (locally made rocket stoves) (p = 0.62), and 10.2% reduction in the group given one of each (p = 0.61). Overall, CO exposure for participants was low given the prevalence of cooking over traditional three-stone fires, with 8.2% of daily samples exceeding WHO Tier-1 standards. We present quantification methods and performance of duplicate monitors. We analyzed the relationship between personal carbonaceous particulate matter less than 2.5 microns (PM2.5) and CO exposure for the dataset that included both measurements, finding a weak relationship likely due to the diversity of identified air pollution sources in the region and behavior variability.
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