Articles | Volume 13, issue 11
https://doi.org/10.5194/amt-13-6343-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-6343-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessing the accuracy of low-cost optical particle sensors using a physics-based approach
David H. Hagan
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA 02139, USA
QuantAQ, Inc., Somerville, MA 02143, USA
Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA 02139, USA
Department of Chemical Engineering, Massachusetts Institute of
Technology, Cambridge, MA 02139, USA
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- Indoor–Outdoor Oxidative Potential of PM2.5 in Wintertime Fairbanks, Alaska: Impact of Air Infiltration and Indoor Activities Y. Yang et al. 10.1021/acsestair.3c00067
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62 citations as recorded by crossref.
- Evaluating the PurpleAir monitor as an aerosol light scattering instrument J. Ouimette et al. 10.5194/amt-15-655-2022
- Evaluation of aerosol-spectrometer based PM2.5 and PM10 mass concentration measurement using ambient-like model aerosols in the laboratory T. Wu et al. 10.1016/j.measurement.2022.111761
- Significance of sources and size distribution on calibration of low-cost particle sensors: Evidence from a field sampling campaign V. Malyan et al. 10.1016/j.jaerosci.2022.106114
- Development of ASTM International D8405—Standard Test Method for Evaluating PM 2.5 Sensors or Sensor Systems Used in Indoor Applications W. Mui et al. 10.1080/15459624.2023.2212739
- SENSORES DE MATERIAL PARTICULADO EN SUSPENSIÓN DE BAJO COSTO: INTEGRACIÓN AL MONITOREO DE LA CALIDAD DEL AIRE D. Gomez & J. Vassallo 10.22201/iingen.0718378xe.2023.16.3.86568
- Particulate matter in a lockdown home: evaluation, calibration, results and health risk from an IoT enabled low-cost sensor network for residential air quality monitoring N. Cowell et al. 10.1039/D2EA00124A
- Assessment of aerosol persistence in ICUs via low-cost sensor network and zonal models K. Glenn et al. 10.1038/s41598-023-30778-7
- Introducing Project-Based Climate Education in Moroccan Universities via a New Air Quality Monitoring Network in Rabat M. Lbadaoui-Darvas et al. 10.1051/e3sconf/202341805003
- Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning models B. Prajapati et al. 10.1016/j.jaerosci.2023.106284
- Air Pollution Measurements and Land-Use Regression in Urban Sub-Saharan Africa Using Low-Cost Sensors—Possibilities and Pitfalls A. Abera et al. 10.3390/atmos11121357
- Low‐cost air quality monitoring networks for long‐term field campaigns: A review F. Carotenuto et al. 10.1002/met.2161
- Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure S. Lim et al. 10.1016/j.scitotenv.2022.155207
- Determination of Hygroscopic Aerosol Growth Based on the OPC-N3 Counter K. Nurowska & K. Markowicz 10.3390/atmos15010061
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- Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. 10.3390/s22249669
- Can 10× cheaper, lower-efficiency particulate air filters and box fans complement High-Efficiency Particulate Air (HEPA) purifiers to help control the COVID-19 pandemic? D. Srikrishna 10.1016/j.scitotenv.2022.155884
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- A systematic investigation on the effects of temperature and relative humidity on the performance of eight low-cost particle sensors and devices Y. Zou et al. 10.1016/j.jaerosci.2020.105715
- Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India M. Campmier et al. 10.5194/amt-16-4357-2023
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- A study on the performance of low-cost sensors for source apportionment at an urban background site D. Bousiotis et al. 10.5194/amt-15-4047-2022
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- Low-Cost Investigation into Sources of PM2.5 in Kinshasa, Democratic Republic of the Congo D. Westervelt et al. 10.1021/acsestair.3c00024
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- Assessment of PM2.5 concentrations, transport, and mitigation in indoor environments using low-cost air quality monitors and a portable air cleaner S. Sankhyan et al. 10.1039/D2EA00025C
- Development and evaluation of correction models for a low-cost fine particulate matter monitor B. Nilson et al. 10.5194/amt-15-3315-2022
- The impact of COVID-19 public health restrictions on particulate matter pollution measured by a validated low-cost sensor network in Oxford, UK T. Bush et al. 10.1016/j.buildenv.2023.110330
- Inter- versus Intracity Variations in the Performance and Calibration of Low-Cost PM2.5 Sensors: A Multicity Assessment in India S. V et al. 10.1021/acsearthspacechem.2c00257
- Application of Gaussian Mixture Regression for the Correction of Low Cost PM2.5 Monitoring Data in Accra, Ghana C. McFarlane et al. 10.1021/acsearthspacechem.1c00217
- Diagnosing domestic and transboundary sources of fine particulate matter (PM2.5) in UK cities using GEOS-Chem J. Kelly et al. 10.1016/j.cacint.2023.100100
- Fundamentals of low-cost aerosol sensor design and operation J. Ouimette et al. 10.1080/02786826.2023.2285935
- Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana G. Raheja et al. 10.1021/acs.est.2c09264
- Tutorial: Guidelines for implementing low-cost sensor networks for aerosol monitoring N. Zimmerman 10.1016/j.jaerosci.2021.105872
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- Investigation of indoor air quality in university residences using low-cost sensors R. Afroz et al. 10.1039/D2EA00149G
- Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution E. Molina Rueda et al. 10.1021/acs.estlett.3c00030
- Can data reliability of low-cost sensor devices for indoor air particulate matter monitoring be improved? – An approach using machine learning H. Chojer et al. 10.1016/j.atmosenv.2022.119251
- Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. 10.5194/amt-17-1051-2024
- Characterisation and calibration of low-cost PM sensors at high temporal resolution to reference-grade performance F. Bulot et al. 10.1016/j.heliyon.2023.e15943
- A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists J. Gómez-Suárez et al. 10.3390/s22031272
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- Evaluation of a low-cost multi-channel monitor for indoor air quality through a novel, low-cost, and reproducible platform A. Baldelli 10.1016/j.measen.2021.100059
- Aerial monitoring of atmospheric particulate matter produced by open-pit mining using low-cost airborne sensors A. Zafra-Pérez et al. 10.1016/j.scitotenv.2023.166743
- Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number Concentrations F. Bulot et al. 10.3390/s23177657
- Measuring Particulate Matter: An Investigation on Sensor Technology, Particle Size, Monitoring Site F. Gandino et al. 10.1109/ACCESS.2023.3319092
- Bias in PM2.5 measurements using collocated reference-grade and optical instruments M. Kushwaha et al. 10.1007/s10661-022-10293-4
- Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation A. Mynard et al. 10.5194/amt-16-4229-2023
- Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study D. Bousiotis et al. 10.5194/amt-14-4139-2021
- Development of Particle Size Resolution Evaluation Method of OPC-type Low-cost and Mid-to-low cost Dust Sensors H. Kim et al. 10.5572/KOSAE.2022.38.1.159
- A MISR-Based Method for the Estimation of Particle Size Distribution: Comparison with AERONET over China Y. Shao et al. 10.34133/remotesensing.0032
5 citations as recorded by crossref.
- High time‐resolution measurements of ultrafine and fine woodsmoke aerosol number and surface area concentrations in biomass burning kitchens: A case study in Western Kenya D. Wagner et al. 10.1111/ina.13132
- Combining low-cost, surface-based aerosol monitors with size-resolved satellite data for air quality applications P. deSouza et al. 10.5194/amt-13-5319-2020
- Towards comprehensive air quality management using low-cost sensors for pollution source apportionment D. Bousiotis et al. 10.1038/s41612-023-00424-0
- Features and Practicability of the Next-Generation Sensors and Monitors for Exposure Assessment to Airborne Pollutants: A Systematic Review G. Fanti et al. 10.3390/s21134513
- Effects of Optical Configuration on the Accuracy and Response of Low-Cost Optical Particle Counters B. Hales et al. 10.1007/s10765-022-03001-4
Latest update: 27 Mar 2024
Short summary
Assessing the error of low-cost particulate matter (PM) sensors has been difficult as each empirical study presents unique limitations. Here, we present a new, open-sourced, physics-based model (opcsim) and use it to understand how the properties of different particle sensors alter their accuracy. We offer a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer recommendations for the choice of optimal calibrant.
Assessing the error of low-cost particulate matter (PM) sensors has been difficult as each...