From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors

Journal of Aerosol Science, Journal Year: 2021, Volume and Issue: 158, P. 105833 - 105833

Published: July 2, 2021

Low-cost sensors for particulate matter mass (PM) enable spatially dense, high temporal resolution measurements of air quality that traditional reference monitoring cannot. PM are especially beneficial in low and middle-income countries where few, if any, grade exist areas the concentration fields pollutants have significant spatial gradients. Unfortunately, low-cost also come with a number challenges must be addressed their data products to used anything more than qualitative characterization quality. The various monitors all subject biases calibration dependencies, corrections which range from relatively straightforward (e.g. meteorology, age sensor) complex aerosol source, composition, refractive index). methods correcting calibrating these dependencies been literature likewise simple linear quadratic models machine learning algorithms. Here we review needs when trying get high-quality sensors. We present set best practices follow obtain

Language: Английский

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Calibrating low-cost sensors for ambient air monitoring: Techniques, trends, and challenges

Environmental Research, Journal Year: 2021, Volume and Issue: 197, P. 111163 - 111163

Published: April 19, 2021

Language: Английский

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Air quality assessment in three East African cities using calibrated low-cost sensors with a focus on road-based hotspots

Environmental Research Communications, Journal Year: 2021, Volume and Issue: 3(7), P. 075007 - 075007

Published: June 23, 2021

Abstract Poor air quality is a development challenge. Urbanization and industrial along with increased populations have brought clear socio-economic benefits to Low-and Middle-Income Countries (LMICs) but can also bring disadvantages such as decreasing quality. A lack of reliable data in East African cities makes it difficult understand pollution exposure predict future trends. This work documents urban the capital Kampala (Uganda), Addis Ababa (Ethiopia) Nairobi (Kenya). We build situational awareness through repeated static dynamic mobile monitoring range locations, including background, roadside (pavement building), rural bus station sites, alongside vehicle-based measurements buses motorcycle t axis. Data suggest that measured particulate matter mass concentrations (PM 2.5 , PM 10 ) all studied was at high concentrations, often hazardous human health, defined by WHO guidelines. Overall, poorest observed Kampala, where mean daily were significantly above limits background locations 122% 69% 193% 215%, respectively. Traffic clearly major contributor pollution; Ababa, on axis, stations indicated drivers commuters exposed poor throughout their commute. Road-related impact indoor near roads. Using one exemplar building located within Nairobi’s Central Business District, shown outdoor correlate (r = 0.84). link between emissions buildings close road should be explored more fully. study, series case studies, provides evidence roads traffic need focus for mitigation strategies reduce cities.

Language: Английский

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Calibration Method for Particulate Matter Low-Cost Sensors Used in Ambient Air Quality Monitoring and Research

Sensors, Journal Year: 2021, Volume and Issue: 21(12), P. 3960 - 3960

Published: June 8, 2021

Over the last decade, manufacturers have come forth with cost-effective sensors for measuring ambient and indoor particulate matter concentration. What these make up in cost efficiency, they lack reliability of measured data due to their sensitivities temperature relative humidity. These weaknesses are especially evident when it comes portable or mobile measurement setups. In recent years many studies been conducted assess possibilities limitations sensors, however mostly restricted stationary measurements. This study reviews published literature until 2020 on summarizes recommendations experts field based experiences, outlines quantile-mapping methodology calibrate low-cost applications. Compared commonly used linear regression method, quantile mapping retains spatial characteristics measurements, although a common correction factor cannot be determined. We conclude that can useful calibration measurements given well-elaborated plan assures providing necessary data.

Language: Английский

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Leveraging machine learning algorithms to advance low-cost air sensor calibration in stationary and mobile settings

Atmospheric Environment, Journal Year: 2023, Volume and Issue: 301, P. 119692 - 119692

Published: March 1, 2023

Language: Английский

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Monitoring and apportioning sources of indoor air quality using low-cost particulate matter sensors

Environment International, Journal Year: 2023, Volume and Issue: 174, P. 107907 - 107907

Published: March 31, 2023

Air quality is one of the most important factors in public health. While outdoor air widely studied, indoor environment has been less scrutinised, even though time spent indoors typically much greater than outdoors. The emergence low-cost sensors can help assess quality. This study provides a new methodology, utilizing and source apportionment techniques, to understand relative importance pollution sources upon methodology tested with three placed different rooms inside an exemplar house (bedroom, kitchen office) When family was present, bedroom had highest average concentrations for PM2.5 PM10 (3.9 ± 6.8 ug/m3 9.6 12.7 μg/m3 respectively), due activities undertaken there presence softer furniture carpeting. kitchen, while presenting lowest PM both size ranges (2.8 5.9 4.2 6.9 presented spikes, especially during cooking times. Increased ventilation office resulted PM1 concentration (1.6 1.9 μg/m3), highlighting strong effect infiltration smallest particles. Source apportionment, via positive matrix factorisation (PMF), showed that up 95 % found be all rooms. reduced as particle increased, contributing >65 PM2.5, 50 PM10, depending on room studied. approach elucidate contributions total exposure, described this paper, easily scalable translatable locations.

Language: Английский

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Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 889, P. 164063 - 164063

Published: May 17, 2023

Language: Английский

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Constructing a pollen proxy from low-cost Optical Particle Counter (OPC) data processed with Neural Networks and Random Forests

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 871, P. 161969 - 161969

Published: Feb. 6, 2023

Pollen allergies affect a significant proportion of the global population, and this is expected to worsen in years come. There demand for development automated pollen monitoring systems. Low-cost Optical Particle Counters (OPCs) measure particulate matter have attractive advantages real-time high time resolution data affordable costs. This study asks whether low-cost OPC sensors can be used meaningful airborne pollen. We employ variety methods, including supervised machine learning techniques, construct proxies from hourly-average evaluate their performance, holding out 40 % observations test proxies. The most successful methods are Neural Network (NN) Random Forest (RF) trained concentrations collected Hirst-type sampler. These perform significantly better than using simple particle size-filtered proxy or Positive Matrix Factorisation (PMF) source apportionment proxy. Twelve NN RF models were developed proxy, each varying by model type, input features target variable. results show that such useful information on data. best metrics achieved (Spearman correlation coefficient = 0.85, determination 0.67) constructing Poaceae (grass) based size information, temperature, relative humidity. Ability distinguish events was evaluated F1 Scores, score reflecting fraction true positives with respect false negatives, promising (F1 ≤ 0.83). Model-constructed demonstrated ability follow monthly diurnal trends discuss suitability OPCs offer advice future progress. demonstrate an alternative could provide valuable timely benefit allergy sufferers.

Language: Английский

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Improving PM10 sensor accuracy in urban areas through calibration in Timișoara

npj Climate and Atmospheric Science, Journal Year: 2024, Volume and Issue: 7(1)

Published: Nov. 1, 2024

Low-cost particulate matter sensors (LCS) are vital for improving the spatial and temporal resolution of air quality data, supplementing sparsely placed official monitoring stations. Despite their benefits, LCS readings can be biased due to physical properties aerosol particles device limitations. An optimization model is essential enhance data accuracy. This paper presents a calibration study network Timișoara, Romania. The began by selecting devices near National Air Quality Monitoring Network (NAQMN) stations developing parametric models, choosing best broader application. Plantower, Sensirion, Honeywell showed comparable Calibration involved clusters within 750 m radius around NAQMN Models incorporating RH corrections multiple linear regression (MLR) were fitted. was validated against from unseen sensors, leading mean bias errors (MBE) 9-17% RMSEs 33-35%, sensor uncertainty margins. Applied city-wide network, identified several regularly exceeding EU daily PM10 threshold, unnoticed limited coverage. highlights necessity granular accurately capture urban variations.

Language: Английский

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Evaluation of optical particulate matter sensors under realistic conditions of strong and mild urban pollution

Atmospheric measurement techniques, Journal Year: 2020, Volume and Issue: 13(12), P. 6427 - 6443

Published: Nov. 30, 2020

Abstract. In this paper we evaluate characteristics of three optical particulate matter sensors/sizers (OPS): high-end spectrometer 11-D (Grimm, Germany), low-cost sensor OPC-N2 (Alphasense, United Kingdom) and in-house developed MAQS (Mobile Air Quality System), which is based on another – PMS5003 (Plantower, China), under realistic conditions strong mild urban pollution. Results were compared against a reference gravimetric system, Gemini (Dadolab, Italy), 2.3 m3 h−1 air sampler, with two channels (simultaneously measuring PM2.5 PM10 concentrations). The measurements performed in Sarajevo, the capital Bosnia-Herzegovina, from December 2019 until May 2020. This interval divided into period 1 pollution 2 city Sarajevo one most polluted cities Europe terms matter: average concentration during was 83 µg m−3, daily values exceeding 500 m−3. During 2, 20 These represent good opportunity to test devices instrument wide range ambient (PM) concentrations. effect an diffusion dryer for discussed as well. order analyse mass distribution particles, scanning mobility particle sizer (SMPS), together gives full spectrum nanoparticles diameter 10 nm coarse particles 35 µm, used. All tested showed excellent correlation 1, R2 between 0.90 0.99 PM However, where concentrations much narrower, decreased significantly, 0.28 0.92. We have also included results 13.5-month long-term comparison our nearby beta attenuation monitor (BAM) 1020 (Met One Instruments, USA) operated by States Environmental Protection Agency (US EPA), similar no observable change performance over time.

Language: Английский

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