Indoor Household Particulate Matter Measurements Using a Network of Low-cost Sensors

Hegde, Shruti; Min, Kyungha; Moore, James E.; Lundrigan, Philip; Patwari, Neal; Collingwood, Scott C.; Balch, Alfred H.; Kelly, Kerry E.

doi:10.4209/aaqr.2019.01.0046

Cited by 62 publications

(41 citation statements)

References 57 publications

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“…There is clear evidence that movement or floor vacuuming, due to air agitation, contributes to dust resuspension from various surfaces [ 17 , 18 , 19 ]. Multiple sensor comparative studies performed parallelly in various residences comprehensively described the main particle sources and people’s exposure to air pollutants [ 20 ]. However, pandemic mobility restrictions forced people to stay in their homes.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Kaliszewski

Włodarski

Młyńczak

et al. 2020

Sensors

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This study shows the results of air monitoring in high- and low-occupancy rooms using two combinations of sensors, AeroTrak8220(TSI)/OPC-N3 (AlphaSense, Great Notley, UK) and OPC-N3/PMS5003 (Plantower, Beijing, China), respectively. The tests were conducted in a flat in Warsaw during the restrictions imposed due to the COVID-19 lockdown. The results showed that OPC-N3 underestimates the PN (particle number concentration) by about 2–3 times compared to the AeroTrak8220. Subsequently, the OPC-N3 was compared with another low-cost sensor, the PMS5003. Both devices showed similar efficiency in PN estimation, whereas PM (particulate matter) concentration estimation differed significantly. Moreover, the relationship among the PM1–PM2.5–PM10 readings obtained with the PMS5003 appeared improbably linear regarding the natural indoor conditions. The correlation of PM concentrations obtained with the PMS5003 suggests an oversimplified calculation method of PM. The studies also demonstrated that PM1, PM2.5, and PM10 concentrations in the high- to low-occupancy rooms were about 3, 2, and 1.5 times, respectively. On the other hand, the use of an air purifier considerably reduced the PM concentrations to similar levels in both rooms. All the sensors showed that frying and toast-making were the major sources of particulate matter, about 10 times higher compared to average levels. Considerably lower particle levels were measured in the low-occupancy room.

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Section: Introductionmentioning

confidence: 99%

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Kaliszewski

Włodarski

Młyńczak

et al. 2020

Sensors

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“…We validated this finding with a week-long pilot study involving 10 Dylos monitors colocated with several calibrated, laboratory-grade air quality monitors 4,5,6 in the first author's home. All monitors were subjected to a host of domestic activities: lighting and extinguishing candles, vacuuming, changing bed sheets, and doing laundry, the results of which verify the monitors' measurement accuracy against calibrated air quality monitoring hardware [22]. During the study, a trained research assistant periodically cleaned participants' 1 Dylos DC1100 Pro -http://www.dylosproducts.com/dcproairqumo.html 2 https://beagleboard.org/black 3 http://hass.io 4 GRIMM 11-B: http://wiki.grimm-aerosol.de/index.php?title=IAQ-11-B 5 Dustrack: http://www.tsi.com/DUSTTRAK-DRX-Aerosol-Monitor-8533/ 6 minivol: http://www.airmetrics.com/products/minivol/index.html air quality monitors following the manufacturer's guidelines for maintaining the board-level air quality sensor but did not recalibrate.…”

Section: Low-cost Monitors and Gateway Computermentioning

confidence: 86%

“…Back end services further monitor, analyze, and alert participants based on their indoor air quality. More information on data aggregation and processing can be found in Lundrigan et al [38], and our Dylos testing procedures are outlined in Hegde et al [22].…”

Section: Low-cost Monitors and Gateway Computermentioning

confidence: 99%

Managing In-home Environments through Sensing, Annotating, and Visualizing Air Quality Data

Moore

Goffin

Meyer

et al. 2018

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Air quality is important, varies across time and space, and is largely invisible. Pioneering past work deploying air quality monitors in residential environments found that study participants improved their awareness of and engagement with air quality. However, these systems fielded a single monitor and did not support user-specified annotations, inhibiting their utility. We developed MAAV-a system to Measure Air quality, Annotate data streams, and Visualize real-time PM 2.5 levelsto explore how participants engage with an air quality system addressing these challenges. MAAV supports collecting data from multiple air quality monitors, annotating that data through multiple modalities, and sending text message prompts when it detects a PM 2.5 spike. MAAV also features an interactive tablet interface for displaying measurement data and annotations. Through six long-term field deployments (20-47 weeks, mean 37.7 weeks), participants found these system features important for understanding the air quality in and around their homes. Participants gained new insights from between-monitor comparisons, reflected on past PM 2.5 spikes with the help of their annotations, and adapted their system usage as they familiarized themselves with their air quality data and MAAV. These results yield important insights for designing residential sensing systems that integrate into users' everyday lives.

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“…Potential applications of LCS devices in IAQ research have been elaborated for unattended large‐scale monitoring and for immediate warning for high pollutant levels 19 . Some researchers have used LCS devices to assess IAQ, such as Dylos, iKair, and Yun PM sensors used in the United States and China 31‐33 . On the other hand, LCS devices were used for PM exposure assessment.…”

Section: Discussionmentioning

confidence: 99%

“…The availability of these newly developed LCS devices for PM 2.5 would facilitate the implementation of PM 2.5 exposure campaigns in Asia with much lower costs and evaluate more Asia-specific exposure sources in indoor and outdoor microenvironments.Potential applications of LCS devices in IAQ research have been elaborated for unattended large-scale monitoring and for immediate warning for high pollutant levels 19. Some researchers have used LCS devices to assess IAQ, such as Dylos, iKair, and Yun PM sensors used in the United States and China [31][32][33]. On the other hand, LCS devices TA B L E 4 For at-home periods, contributions (A) of indoor and outdoor levels to personal PM 2.5 exposures (Model 1), of outdoor levels with indoor sources and ventilation terms to personal PM 2.5 exposures (Model 2), and (B) of outdoor levels with indoor sources and ventilation terms to indoor PM 2.5 (Model 3); PM 2.5 are all at a 5-min resolution (μg/m 3 , n = 26 321)…”

mentioning

confidence: 99%

Concurrent assessment of personal, indoor, and outdoor PM _2.5 and PM ₁ levels and source contributions using novel low‐cost sensing devices

Lung

Tsou

et al. 2020

Indoor Air

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Household air pollution is one of the leading environmental risk factors for death with particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM 2.5 ), a classified human carcinogen, 1 as a major concern. [2][3][4] In particular, Asia accounted for two-thirds of global premature deaths, with 1.64 million in 2017 due to household air pollution, 3,4 while the intensities, frequencies, durations, and contribution of distinct PM 2.5 sources in Asian households have seldom been evaluated. In addition, indoor infiltration of high ambient PM 2.5 levels in Asia 5 affecting Indoor Air Quality (IAQ) exacerbates exposure levels indoors. Characterizing PM 2.5 exposures due to these sources in Asian households is critical for both environmental health research and health advisories to reduce the associated health risks. 6,7 PM 2.5 exposures are usually higher than the ambient levels measured by regulatory monitoring stations. [7][8][9] Distinct sources in Asian households such as cooking and incense burning generate

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Indoor Household Particulate Matter Measurements Using a Network of Low-cost Sensors

Cited by 62 publications

References 57 publications

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Managing In-home Environments through Sensing, Annotating, and Visualizing Air Quality Data

Concurrent assessment of personal, indoor, and outdoor PM _2.5 and PM ₁ levels and source contributions using novel low‐cost sensing devices

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Indoor Household Particulate Matter Measurements Using a Network of Low-cost Sensors

Cited by 62 publications

References 57 publications

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Managing In-home Environments through Sensing, Annotating, and Visualizing Air Quality Data

Concurrent assessment of personal, indoor, and outdoor PM 2.5 and PM 1 levels and source contributions using novel low‐cost sensing devices

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Product

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About

Concurrent assessment of personal, indoor, and outdoor PM _2.5 and PM ₁ levels and source contributions using novel low‐cost sensing devices