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Turner MW, Prathibha P, Holder A, Rappold AG, Hassett-Sipple B, McCaughey B, Wei L, Davis A, Vinsonhaler K, Batchelder A, Carlstad J, Chelminski AN. Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community. Heliyon 2024; 10:e25225. [PMID: 38375293 PMCID: PMC10875335 DOI: 10.1016/j.heliyon.2024.e25225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 02/21/2024] Open
Abstract
Background Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Objective Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM2.5) from smoke. Methods We conducted studies in Fall 2021 ("wildfire study"; N = 10) and Winter 2022 ("wood stove study"; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants' symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. Results No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. Discussion This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.
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Affiliation(s)
- Mallory W. Turner
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
| | - Pradeep Prathibha
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
- Oak Ridge Institute for Science and Education Fellow, USA
| | - Amara Holder
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
| | - Ana G. Rappold
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
| | - Beth Hassett-Sipple
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
| | - Brian McCaughey
- Hoopa Valley Tribal Environmental Protection Agency, Hoopa, CA, USA
| | - Linda Wei
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
- Oak Ridge Associated Universities Contractor, USA
| | - Andrea Davis
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
| | - Kathryn Vinsonhaler
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
- Oak Ridge Institute for Science and Education Fellow, USA
| | - Amber Batchelder
- Region 9, U.S. Environmental Protection Agency, San Francisco, CA, USA
| | - Julia Carlstad
- Region 9, U.S. Environmental Protection Agency, San Francisco, CA, USA
| | - Ann N. Chelminski
- Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, USA
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Ostro B, Spada N, Kuiper H. The impact of coal trains on PM 2.5 in the San Francisco Bay area. AIR QUALITY, ATMOSPHERE, & HEALTH 2023; 16:1173-1183. [PMID: 37303962 PMCID: PMC10015136 DOI: 10.1007/s11869-023-01333-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/25/2023] [Indexed: 06/13/2023]
Abstract
Exposure to fine particulate matter (PM2.5) is associated with adverse health effects, including mortality, even at low concentrations. Rail conveyance of coal, accounting for one-third of American rail freight tonnage, is a source of PM2.5. However, there are limited studies of its contribution to PM2.5, especially in urban settings where residents experience higher exposure and vulnerability to air pollution. We developed a novel artificial intelligence-driven monitoring system to quantify average and maximum PM2.5 concentrations of full and empty (unloaded) coal trains compared to freight and passenger trains. The monitor was close to the train tracks in Richmond, California, a city with a racially diverse population of 115,000 and high rates of asthma and heart disease. We used multiple linear regression models controlling for diurnal patterns and meteorology. The results indicate coal trains add on average 8.32 µg/m3 (95% CI = 6.37, 10.28; p < 0.01) to ambient PM2.5, while sensitivity analysis produced midpoints ranging from 5 to 12 µg/m3. Coal trains contributed 2 to 3 µg/m3 more of PM2.5 than freight trains, and 7 µg/m3 more under calm wind conditions, suggesting our study underestimates emissions and subsequent concentrations of coal train dust. Empty coal cars tended to add 2 µg/m3. Regarding peak concentrations of PM2.5, our models suggest an increase of 17.4 µg/m3 (95% CI = 6.2, 28.5; p < 0.01) from coal trains, about 3 µg/m3 more than freight trains. Given rail shipment of coal occurs globally, including in populous areas, it is likely to have adverse effects on health and environmental justice.
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Affiliation(s)
- Bart Ostro
- Air Quality Research Center, University of California, Davis, CA USA
| | - Nicholas Spada
- Air Quality Research Center, University of California, Davis, CA USA
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deSouza P, Barkjohn K, Clements A, Lee J, Kahn R, Crawford B, Kinney P. An analysis of degradation in low-cost particulate matter sensors. ENVIRONMENTAL SCIENCE: ATMOSPHERES 2023; 3:521-536. [PMID: 37234229 PMCID: PMC10208317 DOI: 10.1039/d2ea00142j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Low-cost sensors (LCS) are increasingly being used to measure fine particulate matter (PM2.5) concentrations in cities around the world. One of the most commonly deployed LCS is the PurpleAir with ~ 15,000 sensors deployed in the United States, alone. PurpleAir measurements are widely used by the public to evaluate PM2.5 levels in their neighborhoods. PurpleAir measurements are also increasingly being integrated into models by researchers to develop large-scale estimates of PM2.5. However, the change in sensor performance over time has not been well studied. It is important to understand the lifespan of these sensors to determine when they should be serviced or replaced, and when measurements from these devices should or should not be used for various applications. This paper fills this gap by leveraging the fact that: (1) Each PurpleAir sensor is comprised of two identical sensors and the divergence between their measurements can be observed, and (2) There are numerous PurpleAir sensors within 50 meters of regulatory monitors allowing for the comparison of measurements between these instruments. We propose empirically derived degradation outcomes for the PurpleAir sensors and evaluate how these outcomes change over time. On average, we find that the number of 'flagged' measurements, where the two sensors within each PurpleAir sensor disagree, increases with time to ~ 4% after 4 years of operation. Approximately 2 percent of all PurpleAir sensors were permanently degraded. The largest fraction of permanently degraded PurpleAir sensors appeared to be in the hot and humid climate zone, suggesting that sensors in these locations may need to be replaced more frequently. We also find that the bias of PurpleAir sensors, or the difference between corrected PM2.5 levels and the corresponding reference measurements, changed over time by -0.12 μg/m3(95% CI: -0.13 μg/m3, -0.10 μg/m3) per year. The average bias increases dramatically after 3.5 years. Further, climate zone is a significant modifier of the association between degradation outcomes and time.
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Affiliation(s)
- Priyanka deSouza
- Department of Urban and Regional Planning, University of Colorado Denver, Denver CO, 80202, USA
- CU Population Center, University of Colorado Boulder, Boulder CO, 80302, USA
| | - Karoline Barkjohn
- Office of Research and Development, US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
| | - Andrea Clements
- Office of Research and Development, US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
| | - Jenny Lee
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Ralph Kahn
- NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
| | - Ben Crawford
- Department of Geography and Environmental Sciences, University of Colorado Denver, 80202, USA
| | - Patrick Kinney
- Boston University School of Public Health, Boston, MA, 02118 USA
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