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Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
 

Article 

  1. Articles
  2. Volume 11, issue 8
  3. AMT, 11, 4883–4890, 2018

Multiple terms: term1 term2
red apples
returns results with all terms like:
Fructose levels inred andgreen apples

Precise match in quotes: "term1 term2"
"red apples"
returns results matching exactly like:
Anthocyanin biosynthesis inred apples

Exclude a term with -: term1 -term2
apples -red
returns results containingapples but notred:
Malic acid in greenapples

Articles |Volume 11, issue 8
https://doi.org/10.5194/amt-11-4883-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-4883-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
 | 
27 Aug 2018
Research article | | 27 Aug 2018

The influence of humidity on the performance of a low-cost air particle mass sensor and the effect of atmospheric fog

Rohan Jayaratne,Xiaoting Liu,Phong Thai,Matthew Dunbabin,andLidia Morawska

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Cited

226 citations as recorded by crossref.

  1. Evaluation of two low-cost PM monitors under different laboratory and indoor conditionsR. He et al.10.1080/02786826.2020.1851649
  2. Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality MonitoringR. Kureshi et al.10.3390/s22031093
  3. Coincidence effect of a low-cost particulate matter sensor: Observations from environmental chamber tests at diverse particle concentrationsK. Kim et al.10.1016/j.apr.2025.102581
  4. Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in DelhiT. Zheng et al.10.5194/amt-12-5161-2019
  5. Examining the functional range of commercially available low‐cost airborne particle sensors and consequences for monitoring of indoor air quality in residencesY. Zou et al.10.1111/ina.12621
  6. An application of low-cost sensors to monitor children's exposure to air pollution at five schools in Queensland, AustraliaB. Pradhan et al.10.1016/j.atmosenv.2024.120424
  7. Ambient air quality measurements in a large city: existing solutions, new opportunities and challengesE. Lezina & M. Misyurev10.1088/1742-6596/2192/1/012031
  8. Assessment of Low-Cost Particulate Matter Sensor Systems against Optical and Gravimetric Methods in a Field Co-Location in NorwayM. Vogt et al.10.3390/atmos12080961
  9. Low-Cost Sensors for Air Quality Monitoring - the Current State of the Technology and a Use OverviewP. Buček et al.10.2478/cdem-2021-0003
  10. Unilateral boundary time series forecastingC. Chang et al.10.3389/fdata.2024.1376023
  11. Common model to approximate the time-variant behaviour of air humidity-change influence on some fundamental standards of precision electromagnetic measurementL. Liu et al.10.1016/j.measurement.2020.108647
  12. Can data reliability of low-cost sensor devices for indoor air particulate matter monitoring be improved? – An approach using machine learningH. Chojer et al.10.1016/j.atmosenv.2022.119251
  13. Bias in PM2.5 measurements using collocated reference-grade and optical instrumentsM. Kushwaha et al.10.1007/s10661-022-10293-4
  14. PM2.5 reduction capacities and their relation to morphological and physiological traits in 13 landscaping tree speciesK. Kim et al.10.1016/j.ufug.2022.127526
  15. Low-Cost Indoor Sensor Deployment for Predicting PM2.5 ExposureS. Tsameret et al.10.1021/acsestair.3c00105
  16. Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, ChileM. Tagle et al.10.1007/s10661-020-8118-4
  17. Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid EnvironmentsZ. Kunić et al.10.3390/s24175477
  18. Efficient calibration of cost-efficient particulate matter sensors using machine learning and time-series alignmentS. Koziel et al.10.1016/j.knosys.2024.111879
  19. Calibration of low-cost particulate matter sensors for coal dust monitoringN. Amoah et al.10.1016/j.scitotenv.2022.160336
  20. Low-cost sensors for measuring airborne particulate matter: Field evaluation and calibration at a South-Eastern European siteG. Kosmopoulos et al.10.1016/j.scitotenv.2020.141396
  21. Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost SensorsA. Samad et al.10.3390/s24030945
  22. Feasibility of low-cost particulate matter sensors for long-term environmental monitoring: Field evaluation and calibrationZ. Feng et al.10.1016/j.scitotenv.2024.174089
  23. Effects of aerosol type and simulated aging on performance of low-cost PM sensorsJ. Tryner et al.10.1016/j.jaerosci.2020.105654
  24. MitH: A framework for Mitigating Hygroscopicity in low-cost PM sensorsM. Casari & L. Po10.1016/j.envsoft.2024.105955
  25. Indoor Air Pollution from Residential Stoves: Examining the Flooding of Particulate Matter into Homes during Real-World UseR. Chakraborty et al.10.3390/atmos11121326
  26. Development and evaluation of correction models for a low-cost fine particulate matter monitorB. Nilson et al.10.5194/amt-15-3315-2022
  27. Effects of Gas and Steam Humidity on Particulate Matter Measurements Obtained Using Light-Scattering SensorsH. Kim et al.10.3390/s23136199
  28. Development and performance evaluation of a mixed-sensor system for fine particles and road traffic noiseC. Wu et al.10.1016/j.eti.2022.102902
  29. In-kitchen aerosol exposure in twelve cities across the globeP. Kumar et al.10.1016/j.envint.2022.107155
  30. Response of low-cost sensors to high PM 2.5 concentrations during bushfire and haze eventsX. Liu et al.10.1080/02786826.2024.2368733
  31. Household air pollution and its impact on human health: the case of Vihiga County, KenyaC. Ang’u et al.10.1007/s11869-022-01249-1
  32. Characterising temporal variability of PM2.5/PM10 ratio and its correlation with meteorological variables at a sub-urban site in the Taj CityS. Bamola et al.10.1016/j.uclim.2023.101763
  33. Fine particle mass monitoring with low-cost sensors: Corrections and long-term performance evaluationC. Malings et al.10.1080/02786826.2019.1623863
  34. Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experimentA. Caseiro et al.10.1039/D4EA00086B
  35. From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensorsM. Giordano et al.10.1016/j.jaerosci.2021.105833
  36. Exploration of a practical approach to providing RH corrections to low cost sensor networksS. Lekamge & H. Oswin10.1038/s41612-025-01115-8
  37. Urban meteorology and air quality in a rapidly growing city: Inter-parameter associations and intra-urban heterogeneityG. Ulpiani et al.10.1016/j.scs.2021.103553
  38. Assessing the value of complex refractive index and particle density for calibration of low-cost particle matter sensor for size-resolved particle count and PM2.5 measurementsC. Huang et al.10.1371/journal.pone.0259745
  39. Low-Cost Sensor Node for Air Quality Monitoring: Field Tests and Validation of Particulate Matter MeasurementsU. Schilt et al.10.3390/s23020794
  40. IoT-Enabled Particulate Matter Monitoring and Forecasting Method Based on Cluster AnalysisJ. Yun & J. Woo10.1109/JIOT.2020.3038862
  41. Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in GreeceI. Stavroulas et al.10.3390/atmos11090926
  42. Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring DeviceE. Bagkis et al.10.3390/atmos12020251
  43. The relationship between greenspace and personal exposure to PM2.5 during walking trips in Delhi, IndiaW. Mueller et al.10.1016/j.envpol.2022.119294
  44. The nexus between in-car aerosol concentrations, ventilation and the risk of respiratory infectionP. Kumar et al.10.1016/j.envint.2021.106814
  45. Evaluation of a low-cost dryer for a low-cost optical particle counterM. Chacón-Mateos et al.10.5194/amt-15-7395-2022
  46. Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensorsJ. Kuula et al.10.5194/amt-13-2413-2020
  47. The application of a multi-channel sensor network to decompose the local and background sources and quantify their contributionsX. Qin et al.10.1016/j.buildenv.2023.110005
  48. Performance assessment of NOVA SDS011 low-cost PM sensor in various microenvironmentsA. Božilov et al.10.1007/s10661-022-10290-7
  49. The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methodsX. Qin et al.10.1016/j.scitotenv.2020.136791
  50. Improved Fine Particles Monitoring in Smart Cities by Means of Advanced Data ConcentratorP. Castello et al.10.1109/TIM.2020.3031987
  51. Development of ASTM International D8405—Standard Test Method for Evaluating PM 2.5 Sensors or Sensor Systems Used in Indoor ApplicationsW. Mui et al.10.1080/15459624.2023.2212739
  52. Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure ResearchJ. Huang et al.10.3390/s22062381
  53. Air Quality Sensors Systems as Tools to Support Guidance in Athletics Stadia for Elite and Recreational AthletesM. Viana et al.10.3390/ijerph19063561
  54. Sensor network for PM2.5 measurements on an academic campus areaM. Badura et al.10.1051/e3sconf/201911600004
  55. Gas sensing properties of AACVD-derived ZnO/Co3O4 bilayer thin film nanocompositesA. Mokrushin et al.10.1016/j.ceramint.2023.12.194
  56. Field calibration of low-cost particulate matter sensors using artificial neural networks and affine response correctionS. Koziel et al.10.1016/j.measurement.2024.114529
  57. Evaluation of Temperature and Humidity Pretreatment Technology and Sensor Performance for Monitoring Gaseous Compounds Emitted from Small-Scale Air Emission StacksI. Choi et al.10.5572/KOSAE.2025.41.1.039
  58. On-field test and data calibration of a low-cost sensor for fine particles exposure assessmentY. Jiang et al.10.1016/j.ecoenv.2021.111958
  59. ‘Envilution™’ chamber for performance evaluation of low-cost sensorsH. Omidvarborna et al.10.1016/j.atmosenv.2020.117264
  60. A systematic investigation on the effects of temperature and relative humidity on the performance of eight low-cost particle sensors and devicesY. Zou et al.10.1016/j.jaerosci.2020.105715
  61. Improved PM2.5 concentration estimates from low-cost sensors using calibration models categorized by relative humidityJ. Hua et al.10.1080/02786826.2021.1873911
  62. Laboratory and field evaluation of a low-cost optical particle sizerM. Tang et al.10.1016/j.jes.2023.06.031
  63. Environmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic TechniqueM. Khan et al.10.3390/su13147797
  64. A novel low-cost sensors system for real-time multipollutant indoor air quality monitoring – Development and performanceH. Chojer et al.10.1016/j.buildenv.2024.112055
  65. Investigating the effect of trees on urban quality in Dublin by combining air monitoring with i-Tree Eco modelE. Riondato et al.10.1016/j.scs.2020.102356
  66. Dynamic and stationary monitoring of air pollutant exposures and dose during marathonsC. Ribalta et al.10.1016/j.scitotenv.2024.171997
  67. Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditionsM. Mathieu-Campbell et al.10.5194/amt-17-6735-2024
  68. Field evaluation of low-cost particulate matter (PM) sensor instruments in indoor and outdoor environments: A university lecture hall and urban southeastern United StatesS. Westgate et al.10.1080/02786826.2025.2484244
  69. Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performanceS. Jain & N. Zimmerman10.1016/j.jaerosci.2024.106335
  70. In-situ validation of embedded physics-based calibration in low-cost particulate matter sensor for urban air quality monitoringZ. Feng et al.10.1016/j.uclim.2025.102289
  71. Low-cost electronic sensors for environmental research: Pitfalls and opportunitiesK. Chan et al.10.1177/0309133320956567
  72. Real‐time measurements of PM2.5and ozone to assess the effectiveness of residential indoor air filtration in Shanghai homesK. Barkjohn et al.10.1111/ina.12716
  73. Particulate Matter Profiles along the Rack Railway Route Using Low-Cost SensorA. Samad et al.10.3390/atmos12020126
  74. Dual-purpose smoke alarms: Integrating low-cost PM 2.5 sensors for combined fire detection and indoor air quality monitoringS. Lekamge et al.10.1080/02786826.2025.2457327
  75. Design and testing of a low-cost sensor and sampling platform for indoor air qualityJ. Tryner et al.10.1016/j.buildenv.2021.108398
  76. Progress on polymer-based materials and composites for humidity sensor applications: from materials aspects to sensor performancesK. Pasalwad et al.10.1039/D5TA00028A
  77. Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicativeA. Caseiro et al.10.1039/D2EA00085G
  78. Performance characteristics of the low-cost Plantower PMS optical sensorM. He et al.10.1080/02786826.2019.1696015
  79. Performance Assessment of Low- and Medium-Cost PM2.5 Sensors in Real-World Conditions in Central EuropeB. Atfeh et al.10.3390/atmos16070796
  80. Application of low-cost particulate matter sensors for air quality monitoring and exposure assessment in underground mines: A reviewN. Amoah et al.10.1007/s12613-021-2378-z
  81. Evaluation and calibration of low-cost particulate matter sensors for respirable coal mine dust monitoringZ. Feng et al.10.1080/02786826.2023.2288609
  82. Features and Practicability of the Next-Generation Sensors and Monitors for Exposure Assessment to Airborne Pollutants: A Systematic ReviewG. Fanti et al.10.3390/s21134513
  83. A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban CyclistsJ. Gómez-Suárez et al.10.3390/s22031272
  84. Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, NorwayH. Liu et al.10.3390/atmos10020041
  85. Band-Sensitive Calibration of Low-Cost PM2.5 Sensors by LSTM Model with Dynamically Weighted Loss FunctionJ. Ryu & H. Park10.3390/su14106120
  86. Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air QualityA. Samad et al.10.3390/s21030804
  87. City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT DevicesS. Johnston et al.10.3390/s19010209
  88. Impact of COVID-19 lockdown on air quality of Sri Lankan citiesM. Senarathna et al.10.11159/ijepr.2021.002
  89. Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensorK. Barkjohn et al.10.5194/amt-14-4617-2021
  90. Impact of Wildfire Smoke PM2.5 on Indoor Air Quality of Public Buildings on a University CampusR. Afroz et al.10.1021/acsestair.4c00342
  91. Assessing Inequitable Urban Heat Islands and Air Pollution Disparities with Low-Cost Sensors in Richmond, VirginiaA. Eanes et al.10.3390/su122310089
  92. Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental JusticeR. Tanzer et al.10.3390/ijerph16142523
  93. Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural IndiaM. Campmier et al.10.5194/amt-16-4357-2023
  94. Calibrating low-cost sensors using MERRA-2 reconstructed PM2.5 mass concentration as a proxyV. Malyan et al.10.1016/j.apr.2023.102027
  95. A Smoke Chamber Study on Some Low-Cost Sensors for Monitoring Size-Segregated Aerosol and Microclimatic ParametersL. Bencs & A. Nagy10.3390/atmos15030304
  96. In-Vehicle Air Pollutant Exposures from Daily Commute in the San Francisco Bay Area, CaliforniaR. Deevi & M. Lu10.3390/atmos15091130
  97. A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor MeasurementsM. Ahmed et al.10.3390/atmos15121535
  98. An efficient spatiotemporal data calibration approach for the low-cost PM2.5 sensing network: A case study in TaiwanC. Lee et al.10.1016/j.envint.2019.05.032
  99. AirMLP: A Multilayer Perceptron Neural Network for Temporal Correction of PM2.5 Values in TurinM. Casari et al.10.3390/s23239446
  100. Comparative Study on the Use of Some Low-Cost Optical Particulate Sensors for Rapid Assessment of Local Air Quality ChangesL. Bencs et al.10.3390/atmos13081218
  101. Uncertainty-Based Calibration Method for Environmental Sensors—Application to Chlorine and pH Monitoring With Carbon Nanotube Sensor ArrayG. Perrin & B. Lebental10.1109/JSEN.2023.3238900
  102. Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2K. Ko et al.10.5194/amt-17-3303-2024
  103. Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor NetworksW. Wang et al.10.3390/s20133661
  104. Catastrophic impact of extreme 2019 Indonesian peatland fires on urban air quality and healthM. Grosvenor et al.10.1038/s43247-024-01813-w
  105. Effect of relative humidity on the performance of five cost-effective PM sensorsP. Wang et al.10.1080/02786826.2021.1910136
  106. Opportunistic mobile air quality mapping using sensors on postal service vehicles: from point clouds to actionable insightsJ. Hofman et al.10.3389/fenvh.2023.1232867
  107. Comparison of PM10 emission flux of two fugitive area sources based on the real-time flux monitoring resultsS. Kim et al.10.1016/j.scitotenv.2023.168666
  108. A novel application of mobile low-cost sensors for atmospheric particulate matter monitoring in open-pit minesA. Zafra-Pérez et al.10.1016/j.eti.2022.102974
  109. Twenty Years of High Spatiotemporal Resolution Estimates of Daily PM2.5 in West Africa Using Satellite Data, Surface Monitors, and Machine LearningD. Westervelt et al.10.1021/acsestair.4c00366
  110. Effect of air quality improvement by urban parks on mitigating PM2.5 and its associated heavy metals: A mobile-monitoring field studyT. Su et al.10.1016/j.jenvman.2022.116283
  111. A Case Study on the Long-Term Field Performance of a Frost-based Moisture Pretreatment Device for Sensor-Based Telemonitoring SystemsS. Lee et al.10.5572/KOSAE.2024.40.6.733
  112. Unveiling the Limits of Existing Correction Factors for a Low-Cost PM2.5 Sensor in Cold Environments and Development of a Tailored SolutionJ. Leenose et al.10.1021/acsestair.5c00018
  113. Theoretical Design of the Scattering-Based Sensor for Analysis of the Vehicle Tailpipe EmissionS. Molaie & P. Lino10.3390/mi11121085
  114. Measurement of Air Pollution Parameters in Montenegro Using the Ecomar SystemN. Zaric et al.10.3390/ijerph18126565
  115. The Metrological Qualification of Commercial VOC Multisensor Systems: A Mandatory Step Prior to Indoor Air Quality MonitoringM. Verriele et al.10.1109/JSEN.2024.3368285
  116. Calibration Methods for Low-Cost Particulate Matter Sensors Considering Seasonal VariabilityJ. Kang & K. Choi10.3390/s24103023
  117. First in-Lab Testing of a Cost-Effective Prototype for PM2.5 Monitoring: The P.ALP AssessmentG. Fanti et al.10.3390/s24185915
  118. Civil air quality monitoring as an alternative and supplement to the National Air Quality Monitoring NetworkA. Bozilov et al.10.2298/TSCI220303103B
  119. PM sensors as an indicator of overall air quality: Pre-COVID and COVID periodsJ. Prakash et al.10.1016/j.apr.2022.101594
  120. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire SmokeK. Barkjohn et al.10.3390/s22249669
  121. Air quality during and after the Commonwealth Games 2018 in Australia: Multiple benefits of monitoringT. Kuhn et al.10.1016/j.jaerosci.2020.105707
  122. Long-term evaluation and calibration of three types of low-cost PM2.5 sensors at different air quality monitoring stationsG. Hong et al.10.1016/j.jaerosci.2021.105829
  123. Spatiotemporal distribution prediction for PM2.5 based on STXGBoost model and high-density monitoring sensors in Zhengzhou High Tech Zone, ChinaS. Zhao et al.10.1016/j.jenvman.2024.123682
  124. Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine LearningI. Vajs et al.10.3390/s21103338
  125. Evaluation of Low-Cost Sensors for Ambient PM2.5 MonitoringM. Badura et al.10.1155/2018/5096540
  126. Field Evaluation of Low-Cost Particulate Matter Sensors in BeijingH. Mei et al.10.3390/s20164381
  127. Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor SystemsP. Schneider et al.10.3390/atmos14030540
  128. Improving PM10 sensor accuracy in urban areas through calibration in TimișoaraR. Blaga & S. Gautam10.1038/s41612-024-00812-0
  129. Application of PM 2.5 low-cost sensors for indoor air quality compliance monitoringL. Morawska et al.10.1080/02786826.2025.2457326
  130. Ambient PM2.5 and PM10 Exposure and Respiratory Disease Hospitalization in Kandy, Sri LankaS. Priyankara et al.10.3390/ijerph18189617
  131. Environmental storage conditions influencing the filtration behavior of electret filters with repeated useJ. Lee et al.10.1177/15280837221119411
  132. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of PollutionF. Bulot et al.10.3390/s20082219
  133. Air Pollution Measurements and Land-Use Regression in Urban Sub-Saharan Africa Using Low-Cost Sensors—Possibilities and PitfallsA. Abera et al.10.3390/atmos11121357
  134. Development and Performance Evaluation of a Mixed-Sensor System for Fine Particles and Road Traffic NoiseC. Wu et al.10.2139/ssrn.4020749
  135. Investigation of indoor air quality in university residences using low-cost sensorsR. Afroz et al.10.1039/D2EA00149G
  136. PM2.5 exposure of various microenvironments in a community: Characteristics and applicationsW. Hsu et al.10.1016/j.envpol.2020.114522
  137. Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methodsM. Si et al.10.5194/amt-13-1693-2020
  138. Estimation of aerosol liquid water from optical scattering instruments using ambient and dried sample streamsJ. Zhang et al.10.1016/j.atmosenv.2020.117787
  139. Use of low-cost PM monitors and a multi-wavelength aethalometer to characterize PM2.5 in the Yakama Nation reservationO. Stampfer et al.10.1016/j.atmosenv.2020.117292
  140. A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in CitiesC. Correia et al.10.3390/ijerph20054073
  141. Deep Learning in Airborne Particulate Matter Sensing and Surface Plasmon Resonance for Environmental MonitoringB. Chauhan et al.10.3390/atmos16040359
  142. From air quality sensors to sensor networks: Things we need to learnY. Li et al.10.1016/j.snb.2021.130958
  143. Calibration of Low-Cost LoRaWAN-Based IoT Air Quality Monitors Using the Super Learner Ensemble: A Case Study for Accurate Particulate Matter MeasurementG. Balagopal et al.10.3390/s25051614
  144. Laboratory evaluation of low-cost PurpleAir PM monitors and in-field correction using co-located portable filter samplersJ. Tryner et al.10.1016/j.atmosenv.2019.117067
  145. How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical RecommendationsE. Brattich et al.10.3390/s20113073
  146. Efficacy of Air Filtration and Education Interventions on Indoor Fine Particulate Matter and Child Lower Respiratory Tract Infections among Rural U.S. Homes Heated with Wood Stoves: Results from the KidsAIR Randomized TrialE. Walker et al.10.1289/EHP9932
  147. Evaluation of Two Low-Cost Optical Particle Counters for the Measurement of Ambient Aerosol Scattering Coefficient and Ångström ExponentK. Markowicz & M. Chiliński10.3390/s20092617
  148. Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-ArtM. Narayana et al.10.3390/s22010394
  149. New Water and Air Pollution Sensors Added to the Sonic Kayak Citizen Science System for Low Cost Environmental MappingA. Griffiths et al.10.5334/joh.35
  150. Performance and Deployment of Low-Cost Particle Sensor Units to Monitor Biomass Burning Events and Their Application in an Educational InitiativeF. Reisen et al.10.3390/s21217206
  151. The approach to adjusting commercial PM2.5 sensors with a filter-based gravimetric methodW. Wang et al.10.1051/e3sconf/202339601119
  152. Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical propertiesX. Qin et al.10.1016/j.envpol.2024.124354
  153. Laboratory and field evaluation of real-time and near real-time PM 2.5 smoke monitorsA. Mehadi et al.10.1080/10962247.2019.1654036
  154. Investigation of Low-Cost and Optical Particulate Matter Sensors for Ambient MonitoringM. Rogulski & A. Badyda10.3390/atmos11101040
  155. Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environmentF. Bulot et al.10.1038/s41598-019-43716-3
  156. Use of a Distributed Micro-sensor System for Monitoring the Indoor Particulate Matter Concentration in the Atmosphere of Ferroalloy Production PlantsH. Myklebust et al.10.1007/s11837-022-05487-7
  157. Spatial and Temporal Variations in SO2 and PM2.5 Levels Around Kīlauea Volcano, Hawai'i During 2007–2018R. Whitty et al.10.3389/feart.2020.00036
  158. Gas source localization and mapping with mobile robots: A reviewA. Francis et al.10.1002/rob.22109
  159. Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological studyM. Zusman et al.10.1016/j.envint.2019.105329
  160. Advancing air quality monitoring: A low-cost sensor network in motion – Part IC. Correia et al.10.1016/j.jenvman.2024.121179
  161. Precision and Accuracy of a Direct-Reading Miniaturized Monitor in PM2.5 Exposure AssessmentF. Borghi et al.10.3390/s18093089
  162. Low-Cost Investigation into Sources of PM2.5 in Kinshasa, Democratic Republic of the CongoD. Westervelt et al.10.1021/acsestair.3c00024
  163. Added Value of Vaisala AQT530 Sensors as a Part of a Sensor Network for Comprehensive Air Quality MonitoringT. Petäjä et al.10.3389/fenvs.2021.719567
  164. Tutorial: Guidelines for implementing low-cost sensor networks for aerosol monitoringN. Zimmerman10.1016/j.jaerosci.2021.105872
  165. Relationship Between the Concentrations Of PM2.5 Indoors Obtained by Using the Optical and Gravimetric Methods: Preliminary AnalysisJ. PASTUSZKA10.21307/acee-2020-035
  166. Deployment of networked low-cost sensors and comparison to real-time stationary monitors in New DelhiJ. Prakash et al.10.1080/10962247.2021.1890276
  167. Effect of aerosol composition on the performance of low-cost optical particle counter correction factorsL. Crilley et al.10.5194/amt-13-1181-2020
  168. Fundamental study of horizontal wind velocity effect on PM2.5 and PM10 sampling accuracy of low-Cost sensorsY. Lee et al.10.1016/j.jaerosci.2025.106645
  169. Evaluation of optical particulate matter sensors under realistic conditions of strong and mild urban pollutionA. Masic et al.10.5194/amt-13-6427-2020
  170. Evaluating the Performance of Low-Cost Air Quality Monitors in Dallas, TexasH. Khreis et al.10.3390/ijerph19031647
  171. Moisture Removal Techniques for a Continuous Emission Monitoring System: A ReviewT. Dinh & J. Kim10.3390/atmos12010061
  172. Performance of Aether Low-Cost Sensor Device for Air Pollution Measurements in Urban Environments. Accuracy Evaluation Applying the Air Quality Index (AQI)G. Spyropoulos et al.10.3390/atmos12101246
  173. Hygroscopic properties of particulate matter and effects of their interactions with weather on visibilityW. Won et al.10.1038/s41598-021-95834-6
  174. A Network of Field-Calibrated Low-Cost Sensor Measurements of PM2.5 in Lomé, Togo, Over One to Two YearsG. Raheja et al.10.1021/acsearthspacechem.1c00391
  175. Estimating Mass Concentration Using a Low-cost Portable Particle Counter Based on Full-year Observations: Issues to Obtain Reliable Atmospheric PM2.5 DataS. Ueda et al.10.5572/ajae.2020.14.2.155
  176. Design and Evaluation of a Dryer System for IoT Hyperlocal Particulate Matter Monitoring DeviceE. Illueca Fernández et al.10.1109/JSEN.2024.3364537
  177. Miniature Optical Particle Counter and Analyzer Involving a Fluidic-Optronic CMOS Chip Coupled with a Millimeter-Sized Glass Optical SystemG. Jobert et al.10.3390/s21093181
  178. Enhancing accuracy of air quality sensors with machine learning to augment large-scale monitoring networksK. Ravindra et al.10.1038/s41612-024-00833-9
  179. Performance and data acquisition from low-cost air quality sensors: a comprehensive reviewM. Siddiqui et al.10.1007/s11869-024-01683-3
  180. Analysis of indoor and outdoor particulate (PM2.5) at a women and children’s hospital in West JakartaH. Yulinawati et al.10.1088/1755-1315/737/1/012067
  181. Measurements of PM2.5 with PurpleAir under atmospheric conditionsK. Ardon-Dryer et al.10.5194/amt-13-5441-2020
  182. Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the ScienceJ. Hofman et al.10.3390/s24175653
  183. Utilization of scattering and absorption-based particulate matter sensors in the environment impacted by residential wood combustionJ. Kuula et al.10.1016/j.jaerosci.2020.105671
  184. Enhancing the reliability of particulate matter sensing by multivariate Tobit model using weather and air quality dataW. Won et al.10.1038/s41598-023-40468-z
  185. Characterizing outdoor infiltration and indoor contribution of PM2.5 with citizen-based low-cost monitoring dataJ. Bi et al.10.1016/j.envpol.2021.116763
  186. A quadcopter unmanned aerial system (UAS)-based methodology for measuring biomass burning emission factorsR. Vernooij et al.10.5194/amt-15-4271-2022
  187. Low-cost sensors and Machine Learning aid in identifying environmental factors affecting particulate matter emitted by household heatingA. Hassani et al.10.1016/j.atmosenv.2023.120108
  188. Applicability of the low-cost OPC-N3 optical particle counter for microphysical measurements of fogK. Nurowska et al.10.5194/amt-16-2415-2023
  189. Qualification of the Alphasense optical particle counter for inline air quality monitoringS. Bezantakos et al.10.1080/02786826.2020.1864276
  190. Network of low-cost air quality sensors for monitoring indoor, outdoor, and personal PM2.5 exposure in Seattle during the 2020 wildfire seasonJ. He et al.10.1016/j.atmosenv.2022.119244
  191. Community-based participatory research for low-cost air pollution monitoring in the wake of unconventional oil and gas development in the Ohio River Valley: Empowering impacted residents through community scienceG. Raheja et al.10.1088/1748-9326/ac6ad6
  192. Humidity, density, and inlet aspiration efficiency correction improve accuracy of a low-cost sensor during field calibration at a suburban site in the North-Western Indo-Gangetic plain (NW-IGP)H. Pawar & B. Sinha10.1080/02786826.2020.1719971
  193. An integrated strategy for air quality monitoring and management in industrial port areasM. López et al.10.1016/j.clet.2024.100729
  194. Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust StormsA. Khader & R. Martin10.3390/atmos10090539
  195. Smart Citizen Kit and Station: An open environmental monitoring system for citizen participation and scientific experimentationG. Camprodon et al.10.1016/j.ohx.2019.e00070
  196. Performance evaluation of twelve low-cost PM2.5 sensors at an ambient air monitoring siteB. Feenstra et al.10.1016/j.atmosenv.2019.116946
  197. Ubiquity of hazardous airborne substances on passenger ferriesA. Targino et al.10.1016/j.jhazmat.2021.127133
  198. Proposal for concentration calibration method for field evaluation of particulate matters monitors based on light scattering using decision tree techniquesS. Park et al.10.15250/joie.2023.22.4.314
  199. Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputsS. Koziel et al.10.1038/s41598-025-02069-w
  200. Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning modelsB. Prajapati et al.10.1016/j.jaerosci.2023.106284
  201. A new evaluation method of three different low-cost dust sensors using exponentially decaying particle concentrationsK. Kang et al.10.4491/eer.2020.501
  202. Design Considerations for a Distributed Low-Cost Air Quality Sensing System for Urban Environments in Low-Resource SettingsE. Bainomugisha et al.10.3390/atmos14020354
  203. Cross-concentration calibration of low-cost sensors for effective dust monitoring at construction sitesL. Zheng et al.10.1016/j.jaerosci.2024.106456
  204. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number ConcentrationsF. Bulot et al.10.3390/s23177657
  205. Characteristic of real-time airborne bacteria measurement and the response of low-cost particulate matter sensor: a pilot studyH. Zhang & A. Lai10.1016/j.jobe.2025.113021
  206. Impact of Weather, Lockdown, and Fire on Air Quality: An Analysis of Particulate Matter in Kochi, IndiaA. Thomas et al.10.1007/s41810-025-00294-4
  207. Diurnal and seasonal source‐proximal dust concentrations in complex terrain, West GreenlandJ. Bullard et al.10.1002/esp.5661
  208. Citizen-operated mobile low-cost sensors for urban PM2.5 monitoring: field calibration, uncertainty estimation, and applicationA. Hassani et al.10.1016/j.scs.2023.104607
  209. Assessing the usefulness of dense sensor network for PM2.5 monitoring on an academic campus areaM. Badura et al.10.1016/j.scitotenv.2020.137867
  210. Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire SmokeA. Holder et al.10.3390/s20174796
  211. Deep learning calibration model for PurpleAir PM2.5 measurements: Comprehensive Investigation of the PurpleAir networkM. Ghahremanloo et al.10.1016/j.atmosenv.2025.121118
  212. Calibration of Portable Particulate Matter–Monitoring Device using Web Query and Machine LearningB. Loh & G. Choi10.1016/j.shaw.2019.08.002
  213. Effect of environmental conditions on the performance of a low-cost atmospheric particulate matter sensorB. Macías-Hernández et al.10.1016/j.uclim.2023.101753
  214. Reducing Construction Dust Pollution by Planning Construction Site LayoutG. Tao et al.10.3390/buildings12050531
  215. A parent-school initiative to assess and predict air quality around a heavily trafficked schoolP. Kumar et al.10.1016/j.scitotenv.2022.160587
  216. Development and Implementation of a Platform for Public Information on Air Quality, Sensor Measurements, and Citizen ScienceJ. Wesseling et al.10.3390/atmos10080445
  217. In Situ Calibration Algorithms for Environmental Sensor Networks: A ReviewF. Delaine et al.10.1109/JSEN.2019.2910317
  218. Spatial calibration and PM2.5 mapping of low-cost air quality sensorsH. Chu et al.10.1038/s41598-020-79064-w
  219. An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitationsK. Okorn & L. Iraci10.5194/amt-17-6425-2024
  220. Methodology for Addressing Infectious Aerosol Persistence in Real-Time Using Sensor NetworkS. Makhsous et al.10.3390/s21113928
  221. Application of Gaussian Mixture Regression for the Correction of Low Cost PM2.5 Monitoring Data in Accra, GhanaC. McFarlane et al.10.1021/acsearthspacechem.1c00217
  222. Preliminary research for low-cost particulate matter sensor networkC. Báthory et al.10.1051/e3sconf/201910000004
  223. Influence of particle properties and environmental factors on the performance of typical particle monitors and low-cost particle sensors in the market of ChinaD. Wu et al.10.1016/j.atmosenv.2021.118825
  224. An experimental application of laser-scattering sensor to estimate the traffic-induced PM2.5 in BeijingX. Liu et al.10.1007/s10661-020-08398-9
  225. Design and evaluation of a portable PM2.5 monitor featuring a low-cost sensor in line with an active filter samplerJ. Tryner et al.10.1039/C9EM00234K
  226. Impact of California Fires on Local and Regional Air Quality: The Role of a Low‐Cost Sensor Network and Satellite ObservationsP. Gupta et al.10.1029/2018GH000136

223 citations as recorded by crossref.

  1. Evaluation of two low-cost PM monitors under different laboratory and indoor conditionsR. He et al.10.1080/02786826.2020.1851649
  2. Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality MonitoringR. Kureshi et al.10.3390/s22031093
  3. Coincidence effect of a low-cost particulate matter sensor: Observations from environmental chamber tests at diverse particle concentrationsK. Kim et al.10.1016/j.apr.2025.102581
  4. Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in DelhiT. Zheng et al.10.5194/amt-12-5161-2019
  5. Examining the functional range of commercially available low‐cost airborne particle sensors and consequences for monitoring of indoor air quality in residencesY. Zou et al.10.1111/ina.12621
  6. An application of low-cost sensors to monitor children's exposure to air pollution at five schools in Queensland, AustraliaB. Pradhan et al.10.1016/j.atmosenv.2024.120424
  7. Ambient air quality measurements in a large city: existing solutions, new opportunities and challengesE. Lezina & M. Misyurev10.1088/1742-6596/2192/1/012031
  8. Assessment of Low-Cost Particulate Matter Sensor Systems against Optical and Gravimetric Methods in a Field Co-Location in NorwayM. Vogt et al.10.3390/atmos12080961
  9. Low-Cost Sensors for Air Quality Monitoring - the Current State of the Technology and a Use OverviewP. Buček et al.10.2478/cdem-2021-0003
  10. Unilateral boundary time series forecastingC. Chang et al.10.3389/fdata.2024.1376023
  11. Common model to approximate the time-variant behaviour of air humidity-change influence on some fundamental standards of precision electromagnetic measurementL. Liu et al.10.1016/j.measurement.2020.108647
  12. Can data reliability of low-cost sensor devices for indoor air particulate matter monitoring be improved? – An approach using machine learningH. Chojer et al.10.1016/j.atmosenv.2022.119251
  13. Bias in PM2.5 measurements using collocated reference-grade and optical instrumentsM. Kushwaha et al.10.1007/s10661-022-10293-4
  14. PM2.5 reduction capacities and their relation to morphological and physiological traits in 13 landscaping tree speciesK. Kim et al.10.1016/j.ufug.2022.127526
  15. Low-Cost Indoor Sensor Deployment for Predicting PM2.5 ExposureS. Tsameret et al.10.1021/acsestair.3c00105
  16. Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, ChileM. Tagle et al.10.1007/s10661-020-8118-4
  17. Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid EnvironmentsZ. Kunić et al.10.3390/s24175477
  18. Efficient calibration of cost-efficient particulate matter sensors using machine learning and time-series alignmentS. Koziel et al.10.1016/j.knosys.2024.111879
  19. Calibration of low-cost particulate matter sensors for coal dust monitoringN. Amoah et al.10.1016/j.scitotenv.2022.160336
  20. Low-cost sensors for measuring airborne particulate matter: Field evaluation and calibration at a South-Eastern European siteG. Kosmopoulos et al.10.1016/j.scitotenv.2020.141396
  21. Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost SensorsA. Samad et al.10.3390/s24030945
  22. Feasibility of low-cost particulate matter sensors for long-term environmental monitoring: Field evaluation and calibrationZ. Feng et al.10.1016/j.scitotenv.2024.174089
  23. Effects of aerosol type and simulated aging on performance of low-cost PM sensorsJ. Tryner et al.10.1016/j.jaerosci.2020.105654
  24. MitH: A framework for Mitigating Hygroscopicity in low-cost PM sensorsM. Casari & L. Po10.1016/j.envsoft.2024.105955
  25. Indoor Air Pollution from Residential Stoves: Examining the Flooding of Particulate Matter into Homes during Real-World UseR. Chakraborty et al.10.3390/atmos11121326
  26. Development and evaluation of correction models for a low-cost fine particulate matter monitorB. Nilson et al.10.5194/amt-15-3315-2022
  27. Effects of Gas and Steam Humidity on Particulate Matter Measurements Obtained Using Light-Scattering SensorsH. Kim et al.10.3390/s23136199
  28. Development and performance evaluation of a mixed-sensor system for fine particles and road traffic noiseC. Wu et al.10.1016/j.eti.2022.102902
  29. In-kitchen aerosol exposure in twelve cities across the globeP. Kumar et al.10.1016/j.envint.2022.107155
  30. Response of low-cost sensors to high PM 2.5 concentrations during bushfire and haze eventsX. Liu et al.10.1080/02786826.2024.2368733
  31. Household air pollution and its impact on human health: the case of Vihiga County, KenyaC. Ang’u et al.10.1007/s11869-022-01249-1
  32. Characterising temporal variability of PM2.5/PM10 ratio and its correlation with meteorological variables at a sub-urban site in the Taj CityS. Bamola et al.10.1016/j.uclim.2023.101763
  33. Fine particle mass monitoring with low-cost sensors: Corrections and long-term performance evaluationC. Malings et al.10.1080/02786826.2019.1623863
  34. Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experimentA. Caseiro et al.10.1039/D4EA00086B
  35. From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensorsM. Giordano et al.10.1016/j.jaerosci.2021.105833
  36. Exploration of a practical approach to providing RH corrections to low cost sensor networksS. Lekamge & H. Oswin10.1038/s41612-025-01115-8
  37. Urban meteorology and air quality in a rapidly growing city: Inter-parameter associations and intra-urban heterogeneityG. Ulpiani et al.10.1016/j.scs.2021.103553
  38. Assessing the value of complex refractive index and particle density for calibration of low-cost particle matter sensor for size-resolved particle count and PM2.5 measurementsC. Huang et al.10.1371/journal.pone.0259745
  39. Low-Cost Sensor Node for Air Quality Monitoring: Field Tests and Validation of Particulate Matter MeasurementsU. Schilt et al.10.3390/s23020794
  40. IoT-Enabled Particulate Matter Monitoring and Forecasting Method Based on Cluster AnalysisJ. Yun & J. Woo10.1109/JIOT.2020.3038862
  41. Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in GreeceI. Stavroulas et al.10.3390/atmos11090926
  42. Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring DeviceE. Bagkis et al.10.3390/atmos12020251
  43. The relationship between greenspace and personal exposure to PM2.5 during walking trips in Delhi, IndiaW. Mueller et al.10.1016/j.envpol.2022.119294
  44. The nexus between in-car aerosol concentrations, ventilation and the risk of respiratory infectionP. Kumar et al.10.1016/j.envint.2021.106814
  45. Evaluation of a low-cost dryer for a low-cost optical particle counterM. Chacón-Mateos et al.10.5194/amt-15-7395-2022
  46. Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensorsJ. Kuula et al.10.5194/amt-13-2413-2020
  47. The application of a multi-channel sensor network to decompose the local and background sources and quantify their contributionsX. Qin et al.10.1016/j.buildenv.2023.110005
  48. Performance assessment of NOVA SDS011 low-cost PM sensor in various microenvironmentsA. Božilov et al.10.1007/s10661-022-10290-7
  49. The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methodsX. Qin et al.10.1016/j.scitotenv.2020.136791
  50. Improved Fine Particles Monitoring in Smart Cities by Means of Advanced Data ConcentratorP. Castello et al.10.1109/TIM.2020.3031987
  51. Development of ASTM International D8405—Standard Test Method for Evaluating PM 2.5 Sensors or Sensor Systems Used in Indoor ApplicationsW. Mui et al.10.1080/15459624.2023.2212739
  52. Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure ResearchJ. Huang et al.10.3390/s22062381
  53. Air Quality Sensors Systems as Tools to Support Guidance in Athletics Stadia for Elite and Recreational AthletesM. Viana et al.10.3390/ijerph19063561
  54. Sensor network for PM2.5 measurements on an academic campus areaM. Badura et al.10.1051/e3sconf/201911600004
  55. Gas sensing properties of AACVD-derived ZnO/Co3O4 bilayer thin film nanocompositesA. Mokrushin et al.10.1016/j.ceramint.2023.12.194
  56. Field calibration of low-cost particulate matter sensors using artificial neural networks and affine response correctionS. Koziel et al.10.1016/j.measurement.2024.114529
  57. Evaluation of Temperature and Humidity Pretreatment Technology and Sensor Performance for Monitoring Gaseous Compounds Emitted from Small-Scale Air Emission StacksI. Choi et al.10.5572/KOSAE.2025.41.1.039
  58. On-field test and data calibration of a low-cost sensor for fine particles exposure assessmentY. Jiang et al.10.1016/j.ecoenv.2021.111958
  59. ‘Envilution™’ chamber for performance evaluation of low-cost sensorsH. Omidvarborna et al.10.1016/j.atmosenv.2020.117264
  60. A systematic investigation on the effects of temperature and relative humidity on the performance of eight low-cost particle sensors and devicesY. Zou et al.10.1016/j.jaerosci.2020.105715
  61. Improved PM2.5 concentration estimates from low-cost sensors using calibration models categorized by relative humidityJ. Hua et al.10.1080/02786826.2021.1873911
  62. Laboratory and field evaluation of a low-cost optical particle sizerM. Tang et al.10.1016/j.jes.2023.06.031
  63. Environmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic TechniqueM. Khan et al.10.3390/su13147797
  64. A novel low-cost sensors system for real-time multipollutant indoor air quality monitoring – Development and performanceH. Chojer et al.10.1016/j.buildenv.2024.112055
  65. Investigating the effect of trees on urban quality in Dublin by combining air monitoring with i-Tree Eco modelE. Riondato et al.10.1016/j.scs.2020.102356
  66. Dynamic and stationary monitoring of air pollutant exposures and dose during marathonsC. Ribalta et al.10.1016/j.scitotenv.2024.171997
  67. Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditionsM. Mathieu-Campbell et al.10.5194/amt-17-6735-2024
  68. Field evaluation of low-cost particulate matter (PM) sensor instruments in indoor and outdoor environments: A university lecture hall and urban southeastern United StatesS. Westgate et al.10.1080/02786826.2025.2484244
  69. Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performanceS. Jain & N. Zimmerman10.1016/j.jaerosci.2024.106335
  70. In-situ validation of embedded physics-based calibration in low-cost particulate matter sensor for urban air quality monitoringZ. Feng et al.10.1016/j.uclim.2025.102289
  71. Low-cost electronic sensors for environmental research: Pitfalls and opportunitiesK. Chan et al.10.1177/0309133320956567
  72. Real‐time measurements of PM2.5and ozone to assess the effectiveness of residential indoor air filtration in Shanghai homesK. Barkjohn et al.10.1111/ina.12716
  73. Particulate Matter Profiles along the Rack Railway Route Using Low-Cost SensorA. Samad et al.10.3390/atmos12020126
  74. Dual-purpose smoke alarms: Integrating low-cost PM 2.5 sensors for combined fire detection and indoor air quality monitoringS. Lekamge et al.10.1080/02786826.2025.2457327
  75. Design and testing of a low-cost sensor and sampling platform for indoor air qualityJ. Tryner et al.10.1016/j.buildenv.2021.108398
  76. Progress on polymer-based materials and composites for humidity sensor applications: from materials aspects to sensor performancesK. Pasalwad et al.10.1039/D5TA00028A
  77. Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicativeA. Caseiro et al.10.1039/D2EA00085G
  78. Performance characteristics of the low-cost Plantower PMS optical sensorM. He et al.10.1080/02786826.2019.1696015
  79. Performance Assessment of Low- and Medium-Cost PM2.5 Sensors in Real-World Conditions in Central EuropeB. Atfeh et al.10.3390/atmos16070796
  80. Application of low-cost particulate matter sensors for air quality monitoring and exposure assessment in underground mines: A reviewN. Amoah et al.10.1007/s12613-021-2378-z
  81. Evaluation and calibration of low-cost particulate matter sensors for respirable coal mine dust monitoringZ. Feng et al.10.1080/02786826.2023.2288609
  82. Features and Practicability of the Next-Generation Sensors and Monitors for Exposure Assessment to Airborne Pollutants: A Systematic ReviewG. Fanti et al.10.3390/s21134513
  83. A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban CyclistsJ. Gómez-Suárez et al.10.3390/s22031272
  84. Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, NorwayH. Liu et al.10.3390/atmos10020041
  85. Band-Sensitive Calibration of Low-Cost PM2.5 Sensors by LSTM Model with Dynamically Weighted Loss FunctionJ. Ryu & H. Park10.3390/su14106120
  86. Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air QualityA. Samad et al.10.3390/s21030804
  87. City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT DevicesS. Johnston et al.10.3390/s19010209
  88. Impact of COVID-19 lockdown on air quality of Sri Lankan citiesM. Senarathna et al.10.11159/ijepr.2021.002
  89. Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensorK. Barkjohn et al.10.5194/amt-14-4617-2021
  90. Impact of Wildfire Smoke PM2.5 on Indoor Air Quality of Public Buildings on a University CampusR. Afroz et al.10.1021/acsestair.4c00342
  91. Assessing Inequitable Urban Heat Islands and Air Pollution Disparities with Low-Cost Sensors in Richmond, VirginiaA. Eanes et al.10.3390/su122310089
  92. Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental JusticeR. Tanzer et al.10.3390/ijerph16142523
  93. Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural IndiaM. Campmier et al.10.5194/amt-16-4357-2023
  94. Calibrating low-cost sensors using MERRA-2 reconstructed PM2.5 mass concentration as a proxyV. Malyan et al.10.1016/j.apr.2023.102027
  95. A Smoke Chamber Study on Some Low-Cost Sensors for Monitoring Size-Segregated Aerosol and Microclimatic ParametersL. Bencs & A. Nagy10.3390/atmos15030304
  96. In-Vehicle Air Pollutant Exposures from Daily Commute in the San Francisco Bay Area, CaliforniaR. Deevi & M. Lu10.3390/atmos15091130
  97. A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor MeasurementsM. Ahmed et al.10.3390/atmos15121535
  98. An efficient spatiotemporal data calibration approach for the low-cost PM2.5 sensing network: A case study in TaiwanC. Lee et al.10.1016/j.envint.2019.05.032
  99. AirMLP: A Multilayer Perceptron Neural Network for Temporal Correction of PM2.5 Values in TurinM. Casari et al.10.3390/s23239446
  100. Comparative Study on the Use of Some Low-Cost Optical Particulate Sensors for Rapid Assessment of Local Air Quality ChangesL. Bencs et al.10.3390/atmos13081218
  101. Uncertainty-Based Calibration Method for Environmental Sensors—Application to Chlorine and pH Monitoring With Carbon Nanotube Sensor ArrayG. Perrin & B. Lebental10.1109/JSEN.2023.3238900
  102. Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2K. Ko et al.10.5194/amt-17-3303-2024
  103. Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor NetworksW. Wang et al.10.3390/s20133661
  104. Catastrophic impact of extreme 2019 Indonesian peatland fires on urban air quality and healthM. Grosvenor et al.10.1038/s43247-024-01813-w
  105. Effect of relative humidity on the performance of five cost-effective PM sensorsP. Wang et al.10.1080/02786826.2021.1910136
  106. Opportunistic mobile air quality mapping using sensors on postal service vehicles: from point clouds to actionable insightsJ. Hofman et al.10.3389/fenvh.2023.1232867
  107. Comparison of PM10 emission flux of two fugitive area sources based on the real-time flux monitoring resultsS. Kim et al.10.1016/j.scitotenv.2023.168666
  108. A novel application of mobile low-cost sensors for atmospheric particulate matter monitoring in open-pit minesA. Zafra-Pérez et al.10.1016/j.eti.2022.102974
  109. Twenty Years of High Spatiotemporal Resolution Estimates of Daily PM2.5 in West Africa Using Satellite Data, Surface Monitors, and Machine LearningD. Westervelt et al.10.1021/acsestair.4c00366
  110. Effect of air quality improvement by urban parks on mitigating PM2.5 and its associated heavy metals: A mobile-monitoring field studyT. Su et al.10.1016/j.jenvman.2022.116283
  111. A Case Study on the Long-Term Field Performance of a Frost-based Moisture Pretreatment Device for Sensor-Based Telemonitoring SystemsS. Lee et al.10.5572/KOSAE.2024.40.6.733
  112. Unveiling the Limits of Existing Correction Factors for a Low-Cost PM2.5 Sensor in Cold Environments and Development of a Tailored SolutionJ. Leenose et al.10.1021/acsestair.5c00018
  113. Theoretical Design of the Scattering-Based Sensor for Analysis of the Vehicle Tailpipe EmissionS. Molaie & P. Lino10.3390/mi11121085
  114. Measurement of Air Pollution Parameters in Montenegro Using the Ecomar SystemN. Zaric et al.10.3390/ijerph18126565
  115. The Metrological Qualification of Commercial VOC Multisensor Systems: A Mandatory Step Prior to Indoor Air Quality MonitoringM. Verriele et al.10.1109/JSEN.2024.3368285
  116. Calibration Methods for Low-Cost Particulate Matter Sensors Considering Seasonal VariabilityJ. Kang & K. Choi10.3390/s24103023
  117. First in-Lab Testing of a Cost-Effective Prototype for PM2.5 Monitoring: The P.ALP AssessmentG. Fanti et al.10.3390/s24185915
  118. Civil air quality monitoring as an alternative and supplement to the National Air Quality Monitoring NetworkA. Bozilov et al.10.2298/TSCI220303103B
  119. PM sensors as an indicator of overall air quality: Pre-COVID and COVID periodsJ. Prakash et al.10.1016/j.apr.2022.101594
  120. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire SmokeK. Barkjohn et al.10.3390/s22249669
  121. Air quality during and after the Commonwealth Games 2018 in Australia: Multiple benefits of monitoringT. Kuhn et al.10.1016/j.jaerosci.2020.105707
  122. Long-term evaluation and calibration of three types of low-cost PM2.5 sensors at different air quality monitoring stationsG. Hong et al.10.1016/j.jaerosci.2021.105829
  123. Spatiotemporal distribution prediction for PM2.5 based on STXGBoost model and high-density monitoring sensors in Zhengzhou High Tech Zone, ChinaS. Zhao et al.10.1016/j.jenvman.2024.123682
  124. Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine LearningI. Vajs et al.10.3390/s21103338
  125. Evaluation of Low-Cost Sensors for Ambient PM2.5 MonitoringM. Badura et al.10.1155/2018/5096540
  126. Field Evaluation of Low-Cost Particulate Matter Sensors in BeijingH. Mei et al.10.3390/s20164381
  127. Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor SystemsP. Schneider et al.10.3390/atmos14030540
  128. Improving PM10 sensor accuracy in urban areas through calibration in TimișoaraR. Blaga & S. Gautam10.1038/s41612-024-00812-0
  129. Application of PM 2.5 low-cost sensors for indoor air quality compliance monitoringL. Morawska et al.10.1080/02786826.2025.2457326
  130. Ambient PM2.5 and PM10 Exposure and Respiratory Disease Hospitalization in Kandy, Sri LankaS. Priyankara et al.10.3390/ijerph18189617
  131. Environmental storage conditions influencing the filtration behavior of electret filters with repeated useJ. Lee et al.10.1177/15280837221119411
  132. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of PollutionF. Bulot et al.10.3390/s20082219
  133. Air Pollution Measurements and Land-Use Regression in Urban Sub-Saharan Africa Using Low-Cost Sensors—Possibilities and PitfallsA. Abera et al.10.3390/atmos11121357
  134. Development and Performance Evaluation of a Mixed-Sensor System for Fine Particles and Road Traffic NoiseC. Wu et al.10.2139/ssrn.4020749
  135. Investigation of indoor air quality in university residences using low-cost sensorsR. Afroz et al.10.1039/D2EA00149G
  136. PM2.5 exposure of various microenvironments in a community: Characteristics and applicationsW. Hsu et al.10.1016/j.envpol.2020.114522
  137. Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methodsM. Si et al.10.5194/amt-13-1693-2020
  138. Estimation of aerosol liquid water from optical scattering instruments using ambient and dried sample streamsJ. Zhang et al.10.1016/j.atmosenv.2020.117787
  139. Use of low-cost PM monitors and a multi-wavelength aethalometer to characterize PM2.5 in the Yakama Nation reservationO. Stampfer et al.10.1016/j.atmosenv.2020.117292
  140. A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in CitiesC. Correia et al.10.3390/ijerph20054073
  141. Deep Learning in Airborne Particulate Matter Sensing and Surface Plasmon Resonance for Environmental MonitoringB. Chauhan et al.10.3390/atmos16040359
  142. From air quality sensors to sensor networks: Things we need to learnY. Li et al.10.1016/j.snb.2021.130958
  143. Calibration of Low-Cost LoRaWAN-Based IoT Air Quality Monitors Using the Super Learner Ensemble: A Case Study for Accurate Particulate Matter MeasurementG. Balagopal et al.10.3390/s25051614
  144. Laboratory evaluation of low-cost PurpleAir PM monitors and in-field correction using co-located portable filter samplersJ. Tryner et al.10.1016/j.atmosenv.2019.117067
  145. How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical RecommendationsE. Brattich et al.10.3390/s20113073
  146. Efficacy of Air Filtration and Education Interventions on Indoor Fine Particulate Matter and Child Lower Respiratory Tract Infections among Rural U.S. Homes Heated with Wood Stoves: Results from the KidsAIR Randomized TrialE. Walker et al.10.1289/EHP9932
  147. Evaluation of Two Low-Cost Optical Particle Counters for the Measurement of Ambient Aerosol Scattering Coefficient and Ångström ExponentK. Markowicz & M. Chiliński10.3390/s20092617
  148. Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-ArtM. Narayana et al.10.3390/s22010394
  149. New Water and Air Pollution Sensors Added to the Sonic Kayak Citizen Science System for Low Cost Environmental MappingA. Griffiths et al.10.5334/joh.35
  150. Performance and Deployment of Low-Cost Particle Sensor Units to Monitor Biomass Burning Events and Their Application in an Educational InitiativeF. Reisen et al.10.3390/s21217206
  151. The approach to adjusting commercial PM2.5 sensors with a filter-based gravimetric methodW. Wang et al.10.1051/e3sconf/202339601119
  152. Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical propertiesX. Qin et al.10.1016/j.envpol.2024.124354
  153. Laboratory and field evaluation of real-time and near real-time PM 2.5 smoke monitorsA. Mehadi et al.10.1080/10962247.2019.1654036
  154. Investigation of Low-Cost and Optical Particulate Matter Sensors for Ambient MonitoringM. Rogulski & A. Badyda10.3390/atmos11101040
  155. Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environmentF. Bulot et al.10.1038/s41598-019-43716-3
  156. Use of a Distributed Micro-sensor System for Monitoring the Indoor Particulate Matter Concentration in the Atmosphere of Ferroalloy Production PlantsH. Myklebust et al.10.1007/s11837-022-05487-7
  157. Spatial and Temporal Variations in SO2 and PM2.5 Levels Around Kīlauea Volcano, Hawai'i During 2007–2018R. Whitty et al.10.3389/feart.2020.00036
  158. Gas source localization and mapping with mobile robots: A reviewA. Francis et al.10.1002/rob.22109
  159. Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological studyM. Zusman et al.10.1016/j.envint.2019.105329
  160. Advancing air quality monitoring: A low-cost sensor network in motion – Part IC. Correia et al.10.1016/j.jenvman.2024.121179
  161. Precision and Accuracy of a Direct-Reading Miniaturized Monitor in PM2.5 Exposure AssessmentF. Borghi et al.10.3390/s18093089
  162. Low-Cost Investigation into Sources of PM2.5 in Kinshasa, Democratic Republic of the CongoD. Westervelt et al.10.1021/acsestair.3c00024
  163. Added Value of Vaisala AQT530 Sensors as a Part of a Sensor Network for Comprehensive Air Quality MonitoringT. Petäjä et al.10.3389/fenvs.2021.719567
  164. Tutorial: Guidelines for implementing low-cost sensor networks for aerosol monitoringN. Zimmerman10.1016/j.jaerosci.2021.105872
  165. Relationship Between the Concentrations Of PM2.5 Indoors Obtained by Using the Optical and Gravimetric Methods: Preliminary AnalysisJ. PASTUSZKA10.21307/acee-2020-035
  166. Deployment of networked low-cost sensors and comparison to real-time stationary monitors in New DelhiJ. Prakash et al.10.1080/10962247.2021.1890276
  167. Effect of aerosol composition on the performance of low-cost optical particle counter correction factorsL. Crilley et al.10.5194/amt-13-1181-2020
  168. Fundamental study of horizontal wind velocity effect on PM2.5 and PM10 sampling accuracy of low-Cost sensorsY. Lee et al.10.1016/j.jaerosci.2025.106645
  169. Evaluation of optical particulate matter sensors under realistic conditions of strong and mild urban pollutionA. Masic et al.10.5194/amt-13-6427-2020
  170. Evaluating the Performance of Low-Cost Air Quality Monitors in Dallas, TexasH. Khreis et al.10.3390/ijerph19031647
  171. Moisture Removal Techniques for a Continuous Emission Monitoring System: A ReviewT. Dinh & J. Kim10.3390/atmos12010061
  172. Performance of Aether Low-Cost Sensor Device for Air Pollution Measurements in Urban Environments. Accuracy Evaluation Applying the Air Quality Index (AQI)G. Spyropoulos et al.10.3390/atmos12101246
  173. Hygroscopic properties of particulate matter and effects of their interactions with weather on visibilityW. Won et al.10.1038/s41598-021-95834-6
  174. A Network of Field-Calibrated Low-Cost Sensor Measurements of PM2.5 in Lomé, Togo, Over One to Two YearsG. Raheja et al.10.1021/acsearthspacechem.1c00391
  175. Estimating Mass Concentration Using a Low-cost Portable Particle Counter Based on Full-year Observations: Issues to Obtain Reliable Atmospheric PM2.5 DataS. Ueda et al.10.5572/ajae.2020.14.2.155
  176. Design and Evaluation of a Dryer System for IoT Hyperlocal Particulate Matter Monitoring DeviceE. Illueca Fernández et al.10.1109/JSEN.2024.3364537
  177. Miniature Optical Particle Counter and Analyzer Involving a Fluidic-Optronic CMOS Chip Coupled with a Millimeter-Sized Glass Optical SystemG. Jobert et al.10.3390/s21093181
  178. Enhancing accuracy of air quality sensors with machine learning to augment large-scale monitoring networksK. Ravindra et al.10.1038/s41612-024-00833-9
  179. Performance and data acquisition from low-cost air quality sensors: a comprehensive reviewM. Siddiqui et al.10.1007/s11869-024-01683-3
  180. Analysis of indoor and outdoor particulate (PM2.5) at a women and children’s hospital in West JakartaH. Yulinawati et al.10.1088/1755-1315/737/1/012067
  181. Measurements of PM2.5 with PurpleAir under atmospheric conditionsK. Ardon-Dryer et al.10.5194/amt-13-5441-2020
  182. Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the ScienceJ. Hofman et al.10.3390/s24175653
  183. Utilization of scattering and absorption-based particulate matter sensors in the environment impacted by residential wood combustionJ. Kuula et al.10.1016/j.jaerosci.2020.105671
  184. Enhancing the reliability of particulate matter sensing by multivariate Tobit model using weather and air quality dataW. Won et al.10.1038/s41598-023-40468-z
  185. Characterizing outdoor infiltration and indoor contribution of PM2.5 with citizen-based low-cost monitoring dataJ. Bi et al.10.1016/j.envpol.2021.116763
  186. A quadcopter unmanned aerial system (UAS)-based methodology for measuring biomass burning emission factorsR. Vernooij et al.10.5194/amt-15-4271-2022
  187. Low-cost sensors and Machine Learning aid in identifying environmental factors affecting particulate matter emitted by household heatingA. Hassani et al.10.1016/j.atmosenv.2023.120108
  188. Applicability of the low-cost OPC-N3 optical particle counter for microphysical measurements of fogK. Nurowska et al.10.5194/amt-16-2415-2023
  189. Qualification of the Alphasense optical particle counter for inline air quality monitoringS. Bezantakos et al.10.1080/02786826.2020.1864276
  190. Network of low-cost air quality sensors for monitoring indoor, outdoor, and personal PM2.5 exposure in Seattle during the 2020 wildfire seasonJ. He et al.10.1016/j.atmosenv.2022.119244
  191. Community-based participatory research for low-cost air pollution monitoring in the wake of unconventional oil and gas development in the Ohio River Valley: Empowering impacted residents through community scienceG. Raheja et al.10.1088/1748-9326/ac6ad6
  192. Humidity, density, and inlet aspiration efficiency correction improve accuracy of a low-cost sensor during field calibration at a suburban site in the North-Western Indo-Gangetic plain (NW-IGP)H. Pawar & B. Sinha10.1080/02786826.2020.1719971
  193. An integrated strategy for air quality monitoring and management in industrial port areasM. López et al.10.1016/j.clet.2024.100729
  194. Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust StormsA. Khader & R. Martin10.3390/atmos10090539
  195. Smart Citizen Kit and Station: An open environmental monitoring system for citizen participation and scientific experimentationG. Camprodon et al.10.1016/j.ohx.2019.e00070
  196. Performance evaluation of twelve low-cost PM2.5 sensors at an ambient air monitoring siteB. Feenstra et al.10.1016/j.atmosenv.2019.116946
  197. Ubiquity of hazardous airborne substances on passenger ferriesA. Targino et al.10.1016/j.jhazmat.2021.127133
  198. Proposal for concentration calibration method for field evaluation of particulate matters monitors based on light scattering using decision tree techniquesS. Park et al.10.15250/joie.2023.22.4.314
  199. Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputsS. Koziel et al.10.1038/s41598-025-02069-w
  200. Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning modelsB. Prajapati et al.10.1016/j.jaerosci.2023.106284
  201. A new evaluation method of three different low-cost dust sensors using exponentially decaying particle concentrationsK. Kang et al.10.4491/eer.2020.501
  202. Design Considerations for a Distributed Low-Cost Air Quality Sensing System for Urban Environments in Low-Resource SettingsE. Bainomugisha et al.10.3390/atmos14020354
  203. Cross-concentration calibration of low-cost sensors for effective dust monitoring at construction sitesL. Zheng et al.10.1016/j.jaerosci.2024.106456
  204. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number ConcentrationsF. Bulot et al.10.3390/s23177657
  205. Characteristic of real-time airborne bacteria measurement and the response of low-cost particulate matter sensor: a pilot studyH. Zhang & A. Lai10.1016/j.jobe.2025.113021
  206. Impact of Weather, Lockdown, and Fire on Air Quality: An Analysis of Particulate Matter in Kochi, IndiaA. Thomas et al.10.1007/s41810-025-00294-4
  207. Diurnal and seasonal source‐proximal dust concentrations in complex terrain, West GreenlandJ. Bullard et al.10.1002/esp.5661
  208. Citizen-operated mobile low-cost sensors for urban PM2.5 monitoring: field calibration, uncertainty estimation, and applicationA. Hassani et al.10.1016/j.scs.2023.104607
  209. Assessing the usefulness of dense sensor network for PM2.5 monitoring on an academic campus areaM. Badura et al.10.1016/j.scitotenv.2020.137867
  210. Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire SmokeA. Holder et al.10.3390/s20174796
  211. Deep learning calibration model for PurpleAir PM2.5 measurements: Comprehensive Investigation of the PurpleAir networkM. Ghahremanloo et al.10.1016/j.atmosenv.2025.121118
  212. Calibration of Portable Particulate Matter–Monitoring Device using Web Query and Machine LearningB. Loh & G. Choi10.1016/j.shaw.2019.08.002
  213. Effect of environmental conditions on the performance of a low-cost atmospheric particulate matter sensorB. Macías-Hernández et al.10.1016/j.uclim.2023.101753
  214. Reducing Construction Dust Pollution by Planning Construction Site LayoutG. Tao et al.10.3390/buildings12050531
  215. A parent-school initiative to assess and predict air quality around a heavily trafficked schoolP. Kumar et al.10.1016/j.scitotenv.2022.160587
  216. Development and Implementation of a Platform for Public Information on Air Quality, Sensor Measurements, and Citizen ScienceJ. Wesseling et al.10.3390/atmos10080445
  217. In Situ Calibration Algorithms for Environmental Sensor Networks: A ReviewF. Delaine et al.10.1109/JSEN.2019.2910317
  218. Spatial calibration and PM2.5 mapping of low-cost air quality sensorsH. Chu et al.10.1038/s41598-020-79064-w
  219. An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitationsK. Okorn & L. Iraci10.5194/amt-17-6425-2024
  220. Methodology for Addressing Infectious Aerosol Persistence in Real-Time Using Sensor NetworkS. Makhsous et al.10.3390/s21113928
  221. Application of Gaussian Mixture Regression for the Correction of Low Cost PM2.5 Monitoring Data in Accra, GhanaC. McFarlane et al.10.1021/acsearthspacechem.1c00217
  222. Preliminary research for low-cost particulate matter sensor networkC. Báthory et al.10.1051/e3sconf/201910000004
  223. Influence of particle properties and environmental factors on the performance of typical particle monitors and low-cost particle sensors in the market of ChinaD. Wu et al.10.1016/j.atmosenv.2021.118825

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Latest update: 07 Jul 2025
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Short summary
It is important to correctly interpret the readings reported by low cost airborne particle sensors at high humidity. We demonstrate that deliquescent growth of particles and the formation of fog droplets in the atmosphere can lead to significant increases in particle number and mass concentrations reported by such sensors, unless they are fitted with dryers at the inlet. This is important as air quality standards for particles are specifically limited to solid particles.
It is important to correctly interpret the readings reported by low cost airborne particle...
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