City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT Devices

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

doi:10.3390/s19010209

Cited by 110 publications

(63 citation statements)

References 35 publications

(34 reference statements)

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“…A combination of two sensors may also prove interesting for the post-processing of the data to detect faults or erroneous data by comparing the two models of sensors. Johnston et al [49] present the evolution the versions of an Air Quality Internet of Things device from hosting four sensors to ten sensors going from $900 to $1000. Camprodon et al [83] present another air quality monitoring device which can host one or two Plantower PMS5003 for respectively $120 or $170.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, five different models of low-cost PM sensors from different manufacturers have been tested [49]: Honeywell HPMA115S0, Alphasense OPC-R1, Novafitness SDS018, Sensirion SPS030 and Plantower PMS5003 (see Figure 1a). 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.…”

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

“…The sensors are placed within four different air quality monitors as described in Johnston et al [49], placed in the middle of the chamber to avoid particle loss around the edges of the chamber. The air quality monitors were named lab-1, lab-2, lab-3 and lab-4.…”

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

See 2 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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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: Discussionmentioning

confidence: 99%

Section: Low-cost Pm Sensorsmentioning

confidence: 99%

See 1 more Smart Citation

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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“…Application of low-cost air quality (AQ) sensors is on the rise and is being used to determine air pollution in cities [1][2][3][4], monitoring of indoor AQ [5][6][7], and for exposure assessment [8][9][10]. Traditionally exposure studies use data from monitoring stations, questionnaires, or biomarkers [11], and more recently land-use regression models [12,13] and other modelling techniques [14], while the most sought-after method is measuring intake dose on a personal level [15].…”

Section: Introductionmentioning

confidence: 99%

Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data

Novak

Kocman

Robinson

et al. 2020

Sensors

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Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6–22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.

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“…Deploying an LPWAN network to give city wide coverage poses significantly more challenges than setting up a simple test network. This LoRaWAN network has not been setup in isolation, it is used as communication means for the air quality monitors which are currently being deployed in and around Southampton [4], [5]. A comparison between different LPWAN technologies is presented in Section II, further details of the use case for air quality are given in Section III.…”

Section: Introductionmentioning

confidence: 99%

LoRaWAN for city scale IoT deployments

Basford

Johnston

Apetroaie-Cristea

et al. 2019

2019 Global IoT Summit (GIoTS)

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LoRaWAN is a Low-Power Wide Area Network (LPWAN) technology designed for Internet of Things (IoT) deployments, this paper presents experiences gained from deploying a citywide LoRaWAN network across Southampton, UK. This network has been deployed to support an installation of air quality sensors and to explore the LoRaWAN technology. This deployment uses a mixture of commercial off-the-shelf gateways and custom gateways. The custom gateways have required the development of a new printed circuit board interface which is available open-source. The gateway locations have been chosen based on combination of availability and predicted coverage. This paper shows that this approach has provided a reasonable coverage of the city.

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City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT Devices

Cited by 110 publications

References 35 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

Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data

LoRaWAN for city scale IoT deployments

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