Exposures and behavioural responses to wildfire smoke

Nature Human Behaviour, Journal Year: 2022, Volume and Issue: 6(10), P. 1351 - 1361

Published: July 7, 2022

Language: Английский

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Daily Local-Level Estimates of Ambient Wildfire Smoke PM_2.5 for the Contiguous US

Environmental Science & Technology, Journal Year: 2022, Volume and Issue: 56(19), P. 13607 - 13621

Published: Sept. 22, 2022

Smoke from wildfires is a growing health risk across the US. Understanding spatial and temporal patterns of such exposure its population impacts requires separating smoke-driven pollutants non-smoke long time series to quantify measure impacts. We develop parsimonious accurate machine learning model daily wildfire-driven PM2.5 concentrations using combination ground, satellite, reanalysis data sources that are easy update. apply our contiguous US 2006 2020, generating estimates smoke over 10 km-by-10 km grid use these characterize levels trends in PM2.5. contributions have increased by up 5 μg/m3 Western last decade, reversing decades policy-driven improvements overall air quality, with fastest for higher income populations predominantly Hispanic populations. The number people locations at least 1 day above 100 per year has 27-fold including nearly 25 million 2020 alone. Our set can bolster efforts comprehensively understand drivers societal extremes wildfire smoke.

Language: Английский

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Calibration of low-cost PurpleAir outdoor monitors using an improved method of calculating PM

Atmospheric Environment, Journal Year: 2021, Volume and Issue: 256, P. 118432 - 118432

Published: May 4, 2021

Language: Английский

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Long-term evaluation of a low-cost air sensor network for monitoring indoor and outdoor air quality at the community scale

The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 807, P. 150797 - 150797

Published: Oct. 7, 2021

Given the growing interest in community air quality monitoring using low-cost sensors, 30 PurpleAir II sensors (12 outdoor and 18 indoor) were deployed partnership with members living adjacent to a major interstate freeway from December 2017- June 2019. Established assurance/quality control techniques for data processing used sensor was evaluated by calculating completeness summarizing PM2.5 measurements. To evaluate performance, correlation coefficients (r) of divergence (CoD) assess temporal spatial variability between sensors. concentrations also compared traffic levels sensors' ability detect pollution. indoor indoor/outdoor (I/O) ratios during resident-reported activities calculated compared, linear mixed-effects regression model developed quantify impacts ambient quality, microclimatic factors, human on PM2.5. In general, performed more reliably than (completeness: 73% versus 54%). All highly temporally correlated (r > 0.98) spatially homogeneous (CoD<0.06). The observed I/O consistent existing literature, explains >85% variation levels, indicating that detected various sources. Overall, this study finds community-maintained can effectively monitor PM2.5, main concerns resulting incompleteness.

Language: Английский

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Publicly available low-cost sensor measurements for PM2.5 exposure modeling: Guidance for monitor deployment and data selection

Environment International, Journal Year: 2021, Volume and Issue: 158, P. 106897 - 106897

Published: Sept. 30, 2021

High-resolution, high-quality exposure modeling is critical for assessing the health effects of ambient PM2.5 in epidemiological studies. Using sparse regulatory measurements as principal model inputs may result two issues prediction: (1) they affect models' accuracy predicting spatial distribution; (2) internal validation based on these not reliably reflect performance at locations interest (e.g., a cohort's residential locations). In this study, we used from publicly available commercial low-cost network, PurpleAir, with an external dataset representative sample participants Adult Changes Thought - Air Pollution (ACT-AP) to improve prediction cohort participant locations. We also proposed metric component analysis (PCA) PCA distance assess similarity between monitor and guide deployment data selection. The was spatiotemporal framework 51 "gold-standard" monitors 58 PurpleAir development, well 105 home validation, Puget Sound region Washington State June 2017 March 2019. After including calibrated part dependent variable, R2 root-mean-square error, RMSE, two-week concentration averages improved 0.84 2.22 μg/m3 0.92 1.63 μg/m3, respectively. RMSE long-term over period 0.72 1.01 0.79 0.88 predictions incorporating demonstrated sharper urban-suburban gradients. shorter distances model's more substantially than longer distances, supporting use metric.

Language: Английский

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Outside in: the relationship between indoor and outdoor particulate air quality during wildfire smoke events in western US cities

Environmental Research Health, Journal Year: 2022, Volume and Issue: 1(1), P. 015003 - 015003

Published: June 30, 2022

Previous research on the health and air quality impacts of wildfire smoke has largely focused impact outdoor quality; however, many people spend a majority their time indoors. The indoor smoke-impacted days is unknown. In this analysis, we use publicly available data from an existing large network low-cost fine particulate matter (PM2.5) monitors to quantify relationship between in 2020 across western United States (US). We also investigate possible regional socioeconomic trends for regions surrounding six major cities US. find PM2.5 concentrations are 82% or 4.2 µg m−3 (median all US year 2020; interquartile range, IQR: 2.0–7.2 m−3) higher compared smoke-free days. Indoor/outdoor ratios show variability by region, particularly However, ratio indoor/outdoor less than 1 (i.e. lower outdoor) at nearly indoor-outdoor monitor pairs Although typically days, that heavily (outdoor > 55 m−3), can exceed 35 24 h standard set Environmental Protection Agency. Further, total daily-mean increase 2.1 with every 10 PM2.5. statistically significant linear regression slopes pairs; 1.0–4.3 These results environments included our remaining indoors during events currently effective, but limited, strategy reduce exposure.

Language: Английский

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Calibration of PurpleAir PA-I and PA-II Monitors Using Daily Mean PM2.5 Concentrations Measured in California, Washington, and Oregon from 2017 to 2021

Sensors, Journal Year: 2022, Volume and Issue: 22(13), P. 4741 - 4741

Published: June 23, 2022

Large quantities of real-time particle data are becoming available from low-cost monitors. However, it is crucial to determine the quality these measurements. The largest network monitors in United States maintained by PurpleAir company, which offers two monitors: PA-I and PA-II. have a single sensor (PMS1003) PA-II employ independent PMS5003 sensors. We new calibration factor for monitor revise previously published algorithm (ALT-CF3). From API site, we downloaded 83 million hourly average PM2.5 values database Washington, Oregon, California between 1 January 2017 8 September 2021. Daily outdoor means 194 were compared daily 47 nearby Federal regulatory sites using gravimetric Reference Methods (FRM). find revised 3.4 For monitors, determined (also 3.4) comparing 26 117 sites. These results show that measurements can agree well with when an optimum found.

Language: Английский

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Assessing residential PM _2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(50)

Published: Dec. 4, 2023

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM2.5). To study PM2.5 spatiotemporal variability in residences, we acquired paired indoor measurements at 3,977 residences across the United States totaling >10,000 monitor-years time-resolved data (10-min resolution) from PurpleAir network. Time-series analysis statistical modeling apportioned to sources (median contribution = 52% total, coefficient variation 69%), episodic emission events such as cooking (28%, CV 210%) persistent (20%, 112%). Residences temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time open windows milder climates. Likewise, all zones, factors were highest summer lowest winter, decreasing by approximately half most zones. Large outdoor-indoor temperature differences associated lower suggesting particle losses active filtration occurred during heating cooling. Absolute contributions both increased wildfire events. Infiltration decreased periods high PM2.5, wildfires, reducing potential exposures outdoor-origin particles but increasing indoor-origin particles. Time-of-day reveals that are frequent mealtimes well on holidays (Thanksgiving Christmas), indicating cooking-related activities a strong source monitored residences.

Language: Английский

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Fine Particulate Air Pollution, Early Life Stress, and Their Interactive Effects on Adolescent Structural Brain Development: A Longitudinal Tensor-Based Morphometry Study

Cerebral Cortex, Journal Year: 2021, Volume and Issue: 32(10), P. 2156 - 2169

Published: Sept. 8, 2021

Air pollution is a major environmental threat to public health; we know little, however, about its effects on adolescent brain development. Exposure air co-occurs, and may interact, with social factors that also affect development, such as early life stress (ELS). Here, show severity of ELS fine particulate (PM2.5) are associated volumetric changes in distinct regions, but uncover regions which moderates the PM2.5. We interviewed adolescents events, used satellite-derived estimates ambient PM2.5 concentrations, conducted longitudinal tensor-based morphometry assess regional volume over an approximately 2-year period (N = 115, ages 9-13 years at Time 1). For who had experienced less severe ELS, was across several gray white matter regions. Fewer were observed for more although occasionally they opposite direction. This pattern results suggests many moderate largely constrains structural Further theory research needed joint brain.

Language: Английский

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Intercomparison of PurpleAir Sensor Performance over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5

Sensors, Journal Year: 2022, Volume and Issue: 22(7), P. 2755 - 2755

Published: April 2, 2022

Low-cost particle sensors are now used worldwide to monitor outdoor air quality. However, they have only been in wide use for a few years. Are reliable? Does their performance deteriorate over time? the algorithms calculating PM2.5 concentrations provided by sensor manufacturers accurate? We investigate these questions using continuous measurements of four PurpleAir monitors (8 sensors) under normal conditions inside and outside home 1.5-3 A recently developed algorithm (called ALT-CF3) is compared two existing (CF1 CF_ATM) Plantower manufacturer PMS 5003 PA-II monitors. Results. The CF1 lost 25-50% all indoor data due part practice assigning zero below threshold. None were ALT-CF3 algorithm. Approximately 92% showed precision better than 20% algorithm, but approximately 45-75% achieved that level limits detection (LODs) mostly 1 µg/m3, 3-10 µg/m3 percentage observations exceeding LOD was 53-92% 16-44% At low found many homes, appear poorly suited.

Language: Английский

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