Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke

Sensors, Journal Year: 2022, Volume and Issue: 22(24), P. 9669 - 9669

Published: Dec. 10, 2022

PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries for real-time air quality information, particularly during wildfire smoke episodes. Uncorrected data can be biased may exhibit a nonlinear response at extreme concentrations (>300 µg/m3). This bias nonlinearity result disagreement with traditional ambient monitoring network, leading to public’s confusion These must evaluated smoke-impacted times then corrected bias, ensure that accurate reported. The nearby public sensor monitor pairs were identified summer of 2020 supplement from collocated develop an extended U.S.-wide correction high concentrations. We several schemes identify optimal correction, using previously developed up 300 µg/m3, transitioning quadradic fit above 400 µg/m3. reduces each index (AQI) breakpoint; most collocations studied met Environmental Protection Agency’s (EPA) performance targets (twelve thirteen EPA’s targets) some sites (5 out 15 terms 1-h averages). also improve comparability regulatory-grade monitors when they collectively analyzed or shown together on information websites; methods this paper correct future air-sensor types. network is already filling spatial temporal gaps regulatory providing valuable air-quality

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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An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations

Atmospheric measurement techniques, Journal Year: 2024, Volume and Issue: 17(21), P. 6425 - 6457

Published: Nov. 8, 2024

Abstract. We reviewed 60 sensor networks and 17 related efforts (sensor review papers data accessibility projects) to better understand the landscape of stationary low-cost gas-phase deployed in outdoor environments worldwide. This study is not exhaustive every network on globe but rather exists categorize types by their key characteristics explore general trends. also exposes gaps monitoring date, especially regarding availability measurements compared particulate matter (PM) geographic coverage (the Global South, rural areas). ground-based that measure air pollutants into two main subsets based deployment type – quasi-permanent (long term) campaign (short medium commonplace practices, strengths, weaknesses networks. conclude with a summary cross-network unification quality control efforts. work aims help scientists looking build best practices common pathways aid end users finding datasets meet needs.

Language: Английский

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Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data

ACS ES&T Air, Journal Year: 2024, Volume and Issue: 1(10), P. 1203 - 1214

Published: Sept. 17, 2024

Air sensors can provide valuable non-regulatory and supplemental data as they be affordably deployed in large numbers stationed remote areas far away from regulatory air monitoring stations. have inherent limitations that are critical to understand before collecting interpreting the data. Many of these mechanistic nature, which will require technological advances. However, there documented quality assurance (QA) methods promote quality. These include laboratory field evaluation quantitatively assess performance, application corrections improve precision accuracy, active management condition or state health sensors. This paper summarizes perspectives presented at U.S. Environmental Protection Agency's 2023 Sensors Quality Assurance Workshop (https://www.epa.gov/air-sensor-toolbox/quality-assurance-air-sensors#QAworkshop) by stakeholders (e.g., manufacturers, researchers, agencies) identifies most pressing needs. QA protocols, streamlined processing, improved total volatile organic compound (TVOC) interpretation, development speciated VOC sensors, increased documentation hardware handling. Community members using need training resources, timely data, accessible approaches, shared responsibility with other stakeholders. In addition identifying vital next steps, this work provides a set common QC actions aimed improving homogenizing sensor allow varying fields levels expertise effectively leverage protect human health.

Language: Английский

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Indoor contribution to PM _{2 .5} exposure using all PurpleAir sites in Washington, Oregon, and California

Indoor Air, Journal Year: 2022, Volume and Issue: 32(9)

Published: Sept. 1, 2022

Low-cost monitors have made it possible for the first time to measure indoor PM2.5 concentrations over extended periods of (months years). Coupled with concurrent outdoor measurements, these measurements can be divided into particles entering building from outdoors and generated activities. Indoor-generated are not normally considered in epidemiological studies, but they health effects (e.g., passive smoking high-temperature cooking). We employed The Random Component Superposition (RCS) regression model estimate infiltration factors up 790 000 matched sites. median subgroups 3-state region ranged between 0.22 0.24, an interquartile range (IQR) 0.13–0.40. These allowed calculation both indoor-generated outdoor-infiltrated PM2.5. contributed, on average, 46%–52% total concentrations. However, site-specific fractional contribution sources near-zero nearly 100%. influence potential exposures varied widely relative greatest occurred at low-to-moderate daily mean levels around 6 μg/m3 was negligible >20 μg/m3. Epidemiological studies incorporating only estimated due ambient origin may benefit newly available knowledge long-term particle

Language: Английский

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Cracking the code—Matching a proprietary algorithm for a low-cost sensor measuring PM1 and PM2.5

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 893, P. 164874 - 164874

Published: June 17, 2023

Language: Английский

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Spatial Variation of PM2.5 Indoors and Outdoors: Results from 261 Regulatory Monitors Compared to 14,000 Low-Cost Monitors in Three Western States over 4.7 Years

Sensors, Journal Year: 2023, Volume and Issue: 23(9), P. 4387 - 4387

Published: April 29, 2023

Spatial variation of indoor and outdoor PM2.5 within three states for a five-year period is studied using regulatory low-cost PurpleAir monitors. Most these data were collected in an earlier study (Wallace et al., 2022 Indoor Air 32:13105) investigating the relative contribution indoor-generated outdoor-infiltrated particles to exposures. About 260 monitors ~10,000 ~4000 are included. Daily mean concentrations, correlations, coefficients divergence (COD) calculated pairs at distances ranging from 0 (collocated) 200 km. We use transparent reproducible open algorithm that avoids proprietary algorithms provided by manufacturer sensors PA-I PA-II The available on API website under name "PM2.5_alt". This validated several hundred separated up 0.5 spatial outdoors homogeneous with high correlations least 10 km, as shown COD index 0.2. There also steady improvement concentrations increasing distance not even < 100 m. good agreement between located <100 m apart collocated Federal Equivalent Methods (FEM).

Language: Английский

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Moving from monitoring to real-time interventions for air quality: are low-cost sensor networks ready to support urban digital twins?

Frontiers in Sustainable Cities, Journal Year: 2025, Volume and Issue: 6

Published: Jan. 15, 2025

Modern cities now have an increasing multitude of Internet-of-Things data streams on urban phenomena, including transport, mobility, and meteorology. One area development has been the use low-cost sensors to complement (or in some cases, substitute for) regulatory monitoring ambient air pollution. As part a bigger integrated approach cities, such as Urban Observatories, disparate live can readily be collated disseminated via platform facilitate hyperlocal for real-time decision making whilst supporting longer term sustainable goals. digital twins are next logical step this journey these becoming increasingly popular tool, at least conceptually, better interpret well understand consequences management interventions. To date, there few examples true environmental challenges with many limited ‘digital shadow’ stage development, characterized by lack bi-directional feedback between model physical world. Observatories present opportunity change providing often overlooked, but crucial, underpinning foundations twins. This paper focuses utilization stream demonstrates that quality applications provide realistic target given density observations available, which routinely combined other datasets added value insights needed pollution management. However, availability standardization big is major challenge issues interoperability, metadata management, communicating uncertainty, network longevity, ownership transparency. contributes concerning how overcome calls common practice generating managing data.

Language: Английский

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Deep Learning Calibration Model for PurpleAir PM2.5 Measurements: Comprehensive Investigation of the PurpleAir Network

Atmospheric Environment, Journal Year: 2025, Volume and Issue: unknown, P. 121118 - 121118

Published: Feb. 1, 2025

Language: Английский

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Understanding the effect of outdoor pollution episodes and HVAC type on indoor air quality

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112978 - 112978

Published: April 1, 2025

Language: Английский

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