97 citations as recorded by crossref.

1. Evaluating the PurpleAir monitor as an aerosol light scattering instrument J. Ouimette et al. 10.5194/amt-15-655-2022
2. 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
3. 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
4. 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
5. 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
6. 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
7. Improving PM10 sensor accuracy in urban areas through calibration in Timișoara R. Blaga & S. Gautam 10.1038/s41612-024-00812-0
8. Deriving the hygroscopicity of ambient particles using low-cost optical particle counters W. Huang et al. 10.5194/amt-17-6073-2024
9. Assessment of aerosol persistence in ICUs via low-cost sensor network and zonal models K. Glenn et al. 10.1038/s41598-023-30778-7
10. 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
11. 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
12. 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
13. Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical properties X. Qin et al. 10.1016/j.envpol.2024.124354
14. Multi-Sensor Instrument for Aerosol In Situ Measurements I. Bruchkouski et al. 10.3390/atmos16010042
15. Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data K. Barkjohn et al. 10.1021/acsestair.4c00125
16. Low‐cost air quality monitoring networks for long‐term field campaigns: A review F. Carotenuto et al. 10.1002/met.2161
17. In-situ observations of charged Saharan dust from an uncrewed aircraft system V. Savvakis et al. 10.1080/02786826.2024.2372399
18. 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
19. Determination of Hygroscopic Aerosol Growth Based on the OPC-N3 Counter K. Nurowska & K. Markowicz 10.3390/atmos15010061
20. Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experiment A. Caseiro et al. 10.1039/D4EA00086B
21. MitH: A framework for Mitigating Hygroscopicity in low-cost PM sensors M. Casari & L. Po 10.1016/j.envsoft.2024.105955
22. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. 10.3390/s22249669
23. Portable Air Cleaner Usage and Particulate Matter Exposure Reduction in an Environmental Justice Community: A Pilot Study A. McIntyre et al. 10.1177/11786302241258587
24. 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
25. Calibrating low-cost sensors using MERRA-2 reconstructed PM2.5 mass concentration as a proxy V. Malyan et al. 10.1016/j.apr.2023.102027
26. AirMLP: A Multilayer Perceptron Neural Network for Temporal Correction of PM2.5 Values in Turin M. Casari et al. 10.3390/s23239446
27. Laboratory evaluation of the effects of particle size and composition on the performance of integrated devices containing Plantower particle sensors Y. Zou et al. 10.1080/02786826.2021.1905148
28. From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors M. Giordano et al. 10.1016/j.jaerosci.2021.105833
29. Investigating the Sources of Urban Air Pollution Using Low-Cost Air Quality Sensors at an Urban Atlanta Site L. Yang et al. 10.1021/acs.est.1c07005
30. 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
31. 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
32. Improving Data Quality of Low-Cost Light-Scattering PM Sensors: Toward Automatic Air Quality Monitoring in Urban Environments G. Ramirez-Espinosa et al. 10.1109/JIOT.2024.3405623
33. Wintertime spatial patterns of particulate matter in Fairbanks, AK during ALPACA 2022 E. Robinson et al. 10.1039/D2EA00140C
34. Applicability of the low-cost OPC-N3 optical particle counter for microphysical measurements of fog K. Nurowska et al. 10.5194/amt-16-2415-2023
35. 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
36. 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
37. An approach enabling Accuracy-as-a-Service for resistance-based sensors using intelligent Digital Twins V. Stegmaier et al. 10.1016/j.procir.2022.05.071
38. Calibration method of particulate matter sensor based on density peaks clustering combined with stacking algorithm J. Lu et al. 10.1016/j.atmosenv.2024.120460
39. Evaluation of Measurement Reliability of Light-scattering PM2.5 Monitor Applied with Referenced-channel Calibration Technology J. Ryu et al. 10.5572/KOSAE.2022.38.3.341
40. Unveiling the potential of a novel portable air quality platform for assessment of fine and coarse particulate matter: in-field testing, calibration, and machine learning insights D. Topalović et al. 10.1007/s10661-024-13069-0
41. Using Indoor and Outdoor Measurements to Understand Building Protectiveness against Wildfire, Atmospheric Inversion, and Firework PM2.5 Pollution Events D. Mendoza et al. 10.3390/environments11090186
42. Low-Cost Investigation into Sources of PM2.5 in Kinshasa, Democratic Republic of the Congo D. Westervelt et al. 10.1021/acsestair.3c00024
43. Significance of Meteorological Feature Selection and Seasonal Variation on Performance and Calibration of a Low-Cost Particle Sensor V. Kumar et al. 10.3390/atmos13040587
44. 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
45. Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment D. Bousiotis et al. 10.1016/j.envint.2024.109069
46. Development and evaluation of correction models for a low-cost fine particulate matter monitor B. Nilson et al. 10.5194/amt-15-3315-2022
47. 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
48. Insights into low-cost pm sensors using size-resolved scattering intensity of cooking aerosols in a test house A. Thakur et al. 10.1080/02786826.2024.2342722
49. 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
50. 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
51. Field calibration and performance evaluation of low-cost sensors for monitoring airborne PM in the occupational mining environment A. Penchala et al. 10.1016/j.jaerosci.2024.106519
52. Monitoring wind and particle concentrations near freshwater and marine harmful algal blooms (HABs) L. Bilyeu et al. 10.1039/D4VA00172A
53. 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
54. High-resolution urban air pollution mapping J. Apte & C. Manchanda 10.1126/science.adq3678
55. Fundamentals of low-cost aerosol sensor design and operation J. Ouimette et al. 10.1080/02786826.2023.2285935
56. Monitoring of PM2.5 Using Well-Calibrated Low-Cost Sensors over One Year in Burkina Faso B. Nana et al. 10.1021/acsestair.4c00126
57. Optimisation of supercritical fluid extraction of orange (Citrus sinenis L.) peel essential oil and its physicochemical properties W. Ling Felicia et al. 10.1016/j.crgsc.2024.100410
58. A novel low-cost sensors system for real-time multipollutant indoor air quality monitoring – Development and performance H. Chojer et al. 10.1016/j.buildenv.2024.112055
59. What can we learn from nested IoT low‐cost sensor networks for air quality? A case study of PM2.5 in Birmingham, UK N. Cowell et al. 10.1002/met.2220
60. 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
61. Tutorial: Guidelines for implementing low-cost sensor networks for aerosol monitoring N. Zimmerman 10.1016/j.jaerosci.2021.105872
62. Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns E. Gramsch et al. 10.3389/fenvs.2021.751267
63. Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi A. Bittner et al. 10.5194/amt-15-3353-2022
64. Effects of aerosol type and simulated aging on performance of low-cost PM sensors J. Tryner et al. 10.1016/j.jaerosci.2020.105654
65. Laboratory evaluation of the Alphasense OPC-N3, and the Plantower PMS5003 and PMS6003 sensors K. Kaur & K. Kelly 10.1016/j.jaerosci.2023.106181
66. Innovative Wearable Technology for Visually Impaired N. Azizan et al. 10.1051/e3sconf/202457001007
67. Investigation of indoor air quality in university residences using low-cost sensors R. Afroz et al. 10.1039/D2EA00149G
68. Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution E. Molina Rueda et al. 10.1021/acs.estlett.3c00030
69. Assessments and application of low-cost sensors to study indoor air quality in layer facilities R. Afroz et al. 10.1016/j.eti.2024.103773
70. 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
71. Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. 10.5194/amt-17-1051-2024
72. Response of low-cost sensors to high PM 2.5 concentrations during bushfire and haze events X. Liu et al. 10.1080/02786826.2024.2368733
73. 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
74. Longevity of size-dependent particle removal performance of do-it-yourself box fan air filters T. Pistochini et al. 10.1039/D4EM00406J
75. 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
76. Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions M. Mathieu-Campbell et al. 10.5194/amt-17-6735-2024
77. Application and validation of a wearable monitor for assessing time- and location-resolved exposures to particulate matter in California’s Central Valley X. Li et al. 10.1080/02786826.2024.2415481
78. Spatio-temporal analysis of bicyclists’ PM2.5 exposure levels in a medium sized urban agglomeration M. Tames et al. 10.1007/s10661-024-13356-w
79. High spatio-temporal resolution predictions of PM2.5 using low-cost sensor data A. Kar et al. 10.1016/j.atmosenv.2024.120486
80. Using in-situ CO2, PM1, PM2.5, and PM10 measurements to assess air change rates and indoor aerosol dynamics S. Westgate & N. Ng 10.1016/j.buildenv.2022.109559
81. Design and testing of a low-cost sensor and sampling platform for indoor air quality J. Tryner et al. 10.1016/j.buildenv.2021.108398
82. Calibration Methods for Low-Cost Particulate Matter Sensors Considering Seasonal Variability J. Kang & K. Choi 10.3390/s24103023
83. Can commercial Doppler lidars serve air quality applications? Results from a field comparison with PM 10 , PM 2.5 , and granulometric observations in a multi-influenced harbor city E. Dieudonné et al. 10.1080/02786826.2024.2427868
84. 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
85. 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
86. 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
87. Measuring Particulate Matter: An Investigation on Sensor Technology, Particle Size, Monitoring Site F. Gandino et al. 10.1109/ACCESS.2023.3319092
88. Bias in PM2.5 measurements using collocated reference-grade and optical instruments M. Kushwaha et al. 10.1007/s10661-022-10293-4
89. 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
90. 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
91. 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
92. A MISR-Based Method for the Estimation of Particle Size Distribution: Comparison with AERONET over China Y. Shao et al. 10.34133/remotesensing.0032
93. 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
94. 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
95. Towards comprehensive air quality management using low-cost sensors for pollution source apportionment D. Bousiotis et al. 10.1038/s41612-023-00424-0
96. 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
97. 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