Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study

Zusman, Marina; Schumacher, Cooper S.; Gassett, Amanda; Spalt, Elizabeth W; Austin, Elena; Larson, Timothy V.; Carvlin, Graeme; Seto, Edmund; Kaufman, Joel D.; Sheppard, Lianne

doi:10.1016/j.envint.2019.105329

Cited by 123 publications

(87 citation statements)

References 28 publications

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“…Meanwhile, the calibration limitations and the risk of overfitting exist in small calibration datasets 23 . In practice, an appropriate and simple choice is to convert the low-cost sensor data to the reference system.…”

Section: Discussionmentioning

confidence: 99%

Spatial calibration and PM2.5 mapping of low-cost air quality sensors

Chu

Ali

2020

Sci Rep

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The data quality of low-cost sensors has received considerable attention and has also led to PM2.5 warnings. However, the calibration of low-cost sensor measurements in an environment with high relative humidity is critical. This study proposes an efficient calibration and mapping approach based on real-time spatial model. The study carried out spatial calibration, which automatically collected measurements of low-cost sensors and the regulatory stations, and investigated the spatial varying pattern of the calibrated low-cost sensor data. The low-cost PM2.5 sensors are spatially calibrated based on reference-grade measurements at regulatory stations. Results showed that the proposed spatial regression approach can explain the variability of the biases from the low-cost sensors with an R-square value of 0.94. The spatial calibration and mapping algorithm can improve the bias and decrease to 39% of the RMSE when compared to the nonspatial calibration model. This spatial calibration and real-time mapping approach provide a useful way for local communities and governmental agencies to adjust the consistency of the sensor network for improved air quality monitoring and assessment.

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Section: Discussionmentioning

confidence: 99%

Spatial calibration and PM2.5 mapping of low-cost air quality sensors

Chu

Ali

2020

Sci Rep

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“…The increase in the availability of low-cost air pollution sensors has increased the number of community residents collecting and using air quality data to better characterize and understand their local environment [28]. Portable, low-cost sensors offer the potential to expand the temporal and spatial coverage of air quality information [29][30][31] and increasingly are being used in exposure and health studies [32][33][34]. These sensor technologies offer new opportunities in urban environmental justice communities to gather neighborhood-level data that illustrate the impact of emissions sources and/or the magnitude of air quality issues affecting their communities To date, there is limited research on how or why sensors and sensor data are used by communities [35].…”

Section: Introductionmentioning

confidence: 99%

Youth Engaged Participatory Air Monitoring: A ‘Day in the Life’ in Urban Environmental Justice Communities

Johnston

Juarez

Navarro³

et al. 2019

IJERPH

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Air pollution in Southern California does not impact all communities equally; communities of color are disproportionately burdened by poor air quality and more likely to live near industrial facilities and freeways. Government regulatory monitors do not have the spatial resolution to provide air quality information at the neighborhood or personal scale. We describe the A Day in the Life program, an approach to participatory air monitoring that engages youth in collecting data that they can then analyze and use to take action. Academics partnered with Los Angeles-based youth environmental justice organizations to combine personal air monitoring, participatory science, and digital storytelling to build capacity to address local air quality issues. Eighteen youth participants from four different neighborhoods wore portable personal PM2.5 (fine particles <2.5 µm in diameter) monitors for a day in each of their respective communities, documenting and mapping their exposure to PM2.5 during their daily routine. Air monitoring was coupled with photography and videos to document what they experienced over the course of their day. The PM2.5 exposure during the day for participants averaged 10.7 µg/m3, although the range stretched from <1 to 180 µg/m3. One-third of all measurements were taken <300 m from a freeway. Overall, we demonstrate a method to increase local youth-centered understanding of personal exposures, pollution sources, and vulnerability to air quality.

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“…It consists of multiple stackable M5Stack products (Figure 1), including a basic core (microcontroller) with an LED display; a particulate-matter (PM) sensor base integrated with PMSA003 (a PM sensor developed by Plantower, Beijing, China) and SHT20 (a humidity and temperature sensor); a GPS module; and a 700 mAh lithium-ion polymer battery. Sensor performance was tested by previous studies, and the results demonstrated its high precision and acceptable accuracy (Badura et al, 2020;Levy Zamora et al, 2019;Zusman et al, 2020).…”

Section: Geoair: a Low-cost Air-pollution Monitor For Health/medical mentioning

confidence: 99%

“…Finally, hands-on experience of sensor calibration, performance evaluation, and data validation could be embedded in an advanced course that focuses mainly on environmental chemistry, environmental engineering, or exposure assessments. Low-cost sensors should be calibrated in a controlled laboratory before deployment in the field to obtain more reliable data (Sousan et al, 2018;Zusman et al, 2020), and require constant recalibration and maintenance to ensure data quality (Tsujita et al, 2004). However, these processes require unique specialties, a significant amount of time, and expensive equipment, which may not be available to all instructors.…”

Section: Limitations and Recommendations For Future Workmentioning

confidence: 99%

A GPS-enabled portable air pollution sensor and web-mapping technologies for field-based learning in health geography

Park

2021

Journal of Geography in Higher Education

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Geographic technologies and perspectives are important for understanding health issues because places and locations influence human health and diseases. Despite the increasing use of a geographic information system (GIS) in health research, and the explosion of new and emerging technologies, little is known about their potential as educational tools for health geography and the effectiveness for student learning. Focusing on air-sensing and web GIS technologies, this article presents an innovative pedagogical strategy to integrate these technologies as tools for field-based learning in health geography and discusses the effectiveness and challenges of this teaching method. A class project, undertaken in a university health geography course, was developed to offer students hands-on training and real-world experience with state-ofthe-art technologies. It consisted of (1) a lecture and pre-fieldwork training; (2) field data collection using a low-cost, GPS-enabled portable air-pollution sensor; (3) data visualization using web GIS; and (4) sharing the findings through a web-based story map application. The successful implementation of the teaching method, as indicated by students' positive comments, demonstrated that such class projects can reinforce students' knowledge of air pollution and health risks; improve their technical, critical thinking, and research skills; and prepare students for entering a technology-driven society.

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Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study

Cited by 123 publications

References 28 publications

Spatial calibration and PM2.5 mapping of low-cost air quality sensors

Spatial calibration and PM2.5 mapping of low-cost air quality sensors

Youth Engaged Participatory Air Monitoring: A ‘Day in the Life’ in Urban Environmental Justice Communities

A GPS-enabled portable air pollution sensor and web-mapping technologies for field-based learning in health geography

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