Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

Bulot, Florentin M. J.; Johnston, Steven J.; Basford, Philip J.; Easton, Natasha H. C.; Apetroaie-Cristea, Mihaela; Foster, Gavin L.; Morris, Andrew K. R.; Cox, Simon J.; Loxham, Matthew

doi:10.1038/s41598-019-43716-3

Cited by 197 publications

(183 citation statements)

References 42 publications

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“…The sensors' response, at a 10 s sampling period, to spikes of pollution lasting ≈1 min was monitored, with a PM 2.5 median peak concentrations <40 µg/m 3 , from two different sources of pollution. Such peaks are similar to measurements undertaken under outdoor conditions by these sensors [35,40] and may inform regarding the potential and limitations of these sensors for outdoor deployments. This is especially pertinent for their use as personal exposure monitors or for mobile applications and especially to assess their capacity to track sources of pollution.…”

Section: Introductionsupporting

confidence: 68%

“…In Nyarku et al [34] a mobile phone equipped with PM and Volatile Organic Compounds (VOC) sensors was tested against reference instruments with a range of pollutants, the PM sensor was found to have a linear response at elevated PM concentrations but not at the lower concentrations pertinent to ambient monitoring. The lower accuracy of the sensors at lower concentration has been observed by other studies [35,36]. Particle density and refractive index are assumed in the conversion of sensor signal to a mass of PM so the calibration of a sensor will only be accurate for PM of a specific density, as determined by composition and therefore the sensors must be re-calibrated for different environments [27].…”

Section: Introductionmentioning

confidence: 91%

“…These models have been selected due to their frequency of use in air quality monitoring studies and for their compact size and price which makes them suitable for large scale deployments. The Plantower PMS5003 has been widely studied [32,35,40,43,45,50,51]. The Alphasense OPC-R1 is a lower cost and lower size version of the OPC-N2 which is widely used and studied [33,35,40,52,53].…”

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

“…The Plantower PMS5003 has been widely studied [32,35,40,43,45,50,51]. The Alphasense OPC-R1 is a lower cost and lower size version of the OPC-N2 which is widely used and studied [33,35,40,52,53]. To the best of the authors knowledge, the Honeywell HPMA115S0 has only been characterised by a limited number of studies [35] and the Novafitness SDS018 and the Sensirion SPS030 have not been characterised in the literature.…”

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

“…A number of recent studies of low-cost sensors for both static and mobile applications have employed manufacturer-supplied performance data without performing an independent calibration [28,38]. However, there is evidence that the deployment conditions will impact sensor response and that sensors exhibit inter-model variability [33,35]. Sayahi et al [38] developed a calibration chamber for low-cost PM sensors that could identify malfunctioning sensors and expose inter-model inconsistencies as well as differing response to different aerosol types between sensors.…”

Section: Introductionmentioning

confidence: 99%

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Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Bulot

Russell

Rezaei

et al. 2020

Sensors

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Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min, and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response.

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Section: Introductionsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 91%

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Bulot

Russell

Rezaei

et al. 2020

Sensors

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Low‐cost air quality monitoring networks for long‐term field campaigns: A review

Carotenuto,

Bisignano,

Brilli

et al. 2023

Meteorological Applications

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The application of low‐cost air quality monitoring networks has substantially grown over the last few years, following the technological advances in the production of cheap and portable air pollution sensors, thus potentially greatly increasing the limited spatial information on air quality conditions provided by traditional stations. However, the use of low‐cost air quality sensors still presents many limitations, mostly related to the reliability of their measurements. Despite the increasing number of papers focusing on these issues, some of the challenges connected to the use of low‐cost air quality sensors are still poorly investigated and understood, considering in particular those related to long‐term applications of low‐cost air quality networks and their integration within the reference air quality monitoring system. The present review aims at filling this gap, by analysing the characteristics of low‐cost air quality monitoring networks that were run across long‐term field campaigns, including their geographical location, the pollutants monitored, the type and number of stations employed, and the length of the field campaign, with a particular attention on assessing the aims for their deployment and on the evaluation of their integration within official air quality monitoring networks. Moreover, a critical analysis of the most insightful suggestions and recommendations delivered in the literature, as well as of the relevant critical issues, is presented, highlighting still open research areas and outlining future challenges.

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What can we learn from nested IoT low‐cost sensor networks for air quality? A case study of PM₂_.5 in Birmingham, UK

Cowell,

Baldo,

Chapman

et al. 2024

Meteorological Applications

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Low‐cost sensing and the Internet of Things (IoT), present new possibilities for unconventional monitoring of environmental parameters. This paper describes a series of intersecting networks of particulate matter sensors that were deployed across the Birmingham conurbation for a 12‐month period. The networks consisted of a combination of commercially available sensors and University developed sensors. Data from these networks were assimilated with data from a third‐party Zephyr deployment, along with the DEFRA AURN network, which was hosted on an open‐source online platform. This nesting of sensor networks allowed for new insights into sensor performance, including the accuracy of a large network to detect regional concentrations and the number of sensors needed for effective monitoring beyond indicative measurements. After comprehensive data validation steps, the sensors were shown to perform well during co‐location with reference instrumentation (exhibiting slopes of 0.74–1.3). The sensors demonstrated good capability of detecting temporal patterns of regional PM2.5 with the mean of the entire sensor network recording an annual mean PM2.5 concentration within 0.2 μgm−3 of the regulatory network annual mean observation. Network‐derived statistics for estimating urban background concentrations compared to a reference site increase in‐line with the number of sensors available, however when assessing this for near‐source concentrations the importance of sensor location rather than the number of sensors is highlighted. Overall, the network provided novel insights into local concentrations, detecting similar hotspots to those identified by a high‐resolution model. The increased spatial coverage afforded by the sensor network has the potential to support higher resolution evaluation of models and provide unprecedented spatial evidence for air pollution management interventions.

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Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

Cited by 197 publications

References 42 publications

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Low‐cost air quality monitoring networks for long‐term field campaigns: A review

What can we learn from nested IoT low‐cost sensor networks for air quality? A case study of PM₂_.5 in Birmingham, UK

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Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

Cited by 197 publications

References 42 publications

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Low‐cost air quality monitoring networks for long‐term field campaigns: A review

What can we learn from nested IoT low‐cost sensor networks for air quality? A case study of PM2.5 in Birmingham, UK

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What can we learn from nested IoT low‐cost sensor networks for air quality? A case study of PM₂_.5 in Birmingham, UK