138 citations as recorded by crossref.

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2. Air Quality Impacts at an E‐Waste Site in Ghana Using Flexible, Moderate‐Cost and Quality‐Assured Measurements L. Kwarteng et al. 10.1029/2020GH000247
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5. Incorporating Low-Cost Sensor Measurements into High-Resolution PM2.5 Modeling at a Large Spatial Scale J. Bi et al. 10.1021/acs.est.9b06046
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12. Garbage in, gospel out? – Air quality assessment in the UK planning system A. Mills & S. Peckham 10.1016/j.envsci.2019.06.010
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17. Evaluation and environmental correction of ambient CO<sub>2</sub> measurements from a low-cost NDIR sensor C. Martin et al. 10.5194/amt-10-2383-2017
18. Calibration of Portable Particulate Matter–Monitoring Device using Web Query and Machine Learning B. Loh & G. Choi 10.1016/j.shaw.2019.08.002
19. Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown M. Kaliszewski et al. 10.3390/s20247290
20. A Survey on Real-Time Communications in Wireless Sensor Networks B. Kim et al. 10.1155/2017/1864847
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22. Mathematical Modelling and Parameter Optimization of Fine Particle Sensors based on Laser Light Scattering W. Shao et al. 10.1109/JSEN.2017.2747083
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26. Low Cost Sensor With IoT LoRaWAN Connectivity and Machine Learning-Based Calibration for Air Pollution Monitoring S. Ali et al. 10.1109/TIM.2020.3034109
27. What does the Shinyei PPD42NS Low-Cost Dust Sensor Really Measure? M. Canu et al. 10.18178/ijesd.2021.12.1.1310
28. Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality A. Samad et al. 10.3390/s21030804
29. Assessing the accuracy of low-cost optical particle sensors using a physics-based approach D. Hagan & J. Kroll 10.5194/amt-13-6343-2020
30. The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methods X. Qin et al. 10.1016/j.scitotenv.2020.136791
31. Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements E. Cross et al. 10.5194/amt-10-3575-2017
32. A tunable high-pass filter for simple and inexpensive size-segregation of sub-10-nm nanoparticles N. Surawski et al. 10.1038/srep45678
33. A Survey on Sensor Calibration in Air Pollution Monitoring Deployments B. Maag et al. 10.1109/JIOT.2018.2853660
34. Development of Low-Cost Air Quality Stations for Next Generation Monitoring Networks: Calibration and Validation of PM2.5 and PM10 Sensors A. Cavaliere et al. 10.3390/s18092843
35. In-car particulate matter exposure across ten global cities P. Kumar et al. 10.1016/j.scitotenv.2020.141395
36. Evaluation of the Performance of Low-Cost Air Quality Sensors at a High Mountain Station with Complex Meteorological Conditions H. Li et al. 10.3390/atmos11020212
37. Comparison of methods for converting Dylos particle number concentrations to PM2.5 mass concentrations R. Franken et al. 10.1111/ina.12546
38. Data Verification Tools for Minimizing Management Costs of Dense Air-Quality Monitoring Networks G. Miskell et al. 10.1021/acs.est.5b04421
39. New Methods for Personal Exposure Monitoring for Airborne Particles K. Koehler & T. Peters 10.1007/s40572-015-0070-z
40. Evaluation of two low-cost PM monitors under different laboratory and indoor conditions R. He et al. 10.1080/02786826.2020.1851649
41. Ambient and laboratory evaluation of a low-cost particulate matter sensor K. Kelly et al. 10.1016/j.envpol.2016.12.039
42. A Statistical Calibration Framework for Improving Non-Reference Method Particulate Matter Reporting: A Focus on Community Air Monitoring Settings S. Commodore et al. 10.3390/atmos11080807
43. Evaluation of a Low-Cost Aerosol Sensor to Assess Dust Concentrations in a Swine Building S. Jones et al. 10.1093/annhyg/mew009
44. Re-calibrating DIY: Testing digital participation across dust sensors, fry pans and environmental pollution H. Pritchard et al. 10.1177/1461444818777473
45. Estimating Hourly Concentrations of PM2.5 across a Metropolitan Area Using Low-Cost Particle Monitors N. Zikova et al. 10.3390/s17081922
46. Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments L. Chatzidiakou et al. 10.5194/amt-12-4643-2019
47. Extensive evaluation and classification of low‐cost dust sensors in laboratory using a newly developed test method K. Ahn et al. 10.1111/ina.12615
48. Observation and modeling of vertical carbon dioxide distribution in a heavily polluted suburban environment Z. BAO et al. 10.1080/16742834.2020.1746627
49. Evaluation of PM2.5 measured in an urban setting using a low-cost optical particle counter and a Federal Equivalent Method Beta Attenuation Monitor B. Magi et al. 10.1080/02786826.2019.1619915
50. The use of low-cost measuring devices for testing air quality in hard-to-reach locations M. Rogulski et al. 10.1051/e3sconf/20184400151
51. Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensors J. Kuula et al. 10.5194/amt-13-2413-2020
52. Response Characterization of an Inexpensive Aerosol Sensor 10.3390/s17122915
53. RELATIONSHIP BETWEEN THE CONCENTRATIONS OF PM2.5 INDOORS OBTAINED BY USING THE OPTICAL AND GRAVIMETRIC METHODS: PRELIMINARY ANALYSIS J. PASTUSZKA 10.21307/ACEE-2020-035
54. An Integrated Sensor Data Logging, Survey, and Analytics Platform for Field Research and Its Application in HAPIN, a Multi-Center Household Energy Intervention Trial D. Wilson et al. 10.3390/su12051805
55. Fine-Scale Spatiotemporal Air Pollution Analysis Using Mobile Monitors on Google Street View Vehicles Y. Guan et al. 10.1080/01621459.2019.1665526
56. Performance of low-cost indoor air quality monitors for PM2.5 and PM10 from residential sources Z. Wang et al. 10.1016/j.buildenv.2020.106654
57. Evaluation of optical particulate matter sensors under realistic conditions of strong and mild urban pollution A. Masic et al. 10.5194/amt-13-6427-2020
58. Experimental and modeling assessment of a novel automotive cabin PM2.5 removal system J. Vande Hey et al. 10.1080/02786826.2018.1490694
59. Compositional Analysis of Adsorbed Organic Aerosol on a Microresonator Mass Sensor A. Zielinski et al. 10.1007/s41810-018-0029-1
60. Usability of a Personal Air Pollution Monitor: Design-Feedback Iterative Cycle Study G. Duncan et al. 10.2196/12023
61. Field testing a low-cost passive aerosol sampler for long-term measurement of ambient PM2.5 concentrations and particle composition M. Castillo et al. 10.1016/j.atmosenv.2019.116905
62. Real-time particle monitoring of pesticide drift from an axial fan airblast orchard sprayer M. Blanco et al. 10.1038/s41370-018-0090-5
63. Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study M. Zusman et al. 10.1016/j.envint.2019.105329
64. Investigation of Low-Cost and Optical Particulate Matter Sensors for Ambient Monitoring M. Rogulski & A. Badyda 10.3390/atmos11101040
65. Application of Machine Learning for the in-Field Correction of a PM2.5 Low-Cost Sensor Network W. Wang et al. 10.3390/s20175002
66. Validation of a light-scattering PM2.5 sensor monitor based on the long-term gravimetric measurements in field tests J. Shi et al. 10.1371/journal.pone.0185700
67. Laboratory evaluation of low-cost PurpleAir PM monitors and in-field correction using co-located portable filter samplers J. Tryner et al. 10.1016/j.atmosenv.2019.117067
68. Fusion of Environmental Sensing on PM2.5 and Deep Learning on Vehicle Detecting for Acquiring Roadside PM2.5 Concentration Increments W. Wang et al. 10.3390/s20174679
69. Particulate matter pollution in an informal settlement in Nairobi: Using citizen science to make the invisible visible S. West et al. 10.1016/j.apgeog.2019.102133
70. Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring L. Crilley et al. 10.5194/amt-11-709-2018
71. Health Benefit Assessment of Running in Urban Areas against the Background of Particulate Matter 2.5 Concentration: The Munich Olympic Park L. Zeindl & J. Koenigstorfer 10.3390/urbansci4040062
72. Evaluation and Application of a Novel Low-Cost Wearable Sensing Device in Assessing Real-Time PM2.5 Exposure in Major Asian Transportation Modes W. Wang et al. 10.3390/atmos12020270
73. Measuring Micrometers of Matter and Inventing Indices: Entangling Social Perception within Discrete and Continuous Measurements of Air Quality E. Schmitt 10.3390/socsci8020048
74. Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado S. Feinberg et al. 10.5194/amt-11-4605-2018
75. Real-time sensors for indoor air monitoring and challenges ahead in deploying them to urban buildings P. Kumar et al. 10.1016/j.scitotenv.2016.04.032
76. Low-cost PM monitors as an opportunity to increase the spatiotemporal resolution of measurements of air quality M. Rogulski 10.1016/j.egypro.2017.09.026
77. Potential of a low-cost gas sensor for atmospheric methane monitoring M. van den Bossche et al. 10.1016/j.snb.2016.07.092
78. Field and Laboratory Evaluations of the Low-Cost Plantower Particulate Matter Sensor M. Levy Zamora et al. 10.1021/acs.est.8b05174
79. Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile M. Tagle et al. 10.1007/s10661-020-8118-4
80. Small, Smart, Fast, and Cheap: Microchip-Based Sensors to Estimate Air Pollution Exposures in Rural Households A. Pillarisetti et al. 10.3390/s17081879
81. Effects of fireworks on particulate matter concentration in a narrow valley: the case of the Medellín metropolitan area C. Hoyos et al. 10.1007/s10661-019-7838-9
82. Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods M. Si et al. 10.5194/amt-13-1693-2020
83. Particulate Matter Sensors Mounted on a Robot for Environmental Aerosol Measurements A. Cashikar et al. 10.1061/(ASCE)EE.1943-7870.0001569
84. 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. Sinha 10.1080/02786826.2020.1719971
85. Review of the Performance of Low-Cost Sensors for Air Quality Monitoring F. Karagulian et al. 10.3390/atmos10090506
86. Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates? N. Castell et al. 10.1016/j.envint.2016.12.007
87. Contribution of low-cost sensor measurements to the prediction of PM2.5 levels: A case study in Imperial County, California, USA J. Bi et al. 10.1016/j.envres.2019.108810
88. A feasible experimental framework for field calibration of portable light-scattering aerosol monitors: Case of TSI DustTrak Z. Li et al. 10.1016/j.envpol.2019.113136
89. Review of smoke taint in wine: smoke-derived volatile phenols and their glycosidic metabolites in grapes and vines as biomarkers for smoke exposure and their role in the sensory perception of smoke taint M. Krstic et al. 10.1111/ajgw.12183
90. Smart homes and the control of indoor air quality A. Schieweck et al. 10.1016/j.rser.2018.05.057
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93. Response of eight low-cost particle sensors and consumer devices to typical indoor emission events in a real home (ASHRAE 1756-RP) Y. Zou et al. 10.1080/23744731.2019.1676094
94. Enhanced performance of pocket-sized nanoparticle exposure monitor for healthy indoor environment H. Wasisto et al. 10.1016/j.buildenv.2015.09.013
95. FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor M. Budde et al. 10.3390/s19030749
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97. The BErkeley Atmospheric CO<sub>2</sub> Observation Network: field calibration and evaluation of low-cost air quality sensors J. Kim et al. 10.5194/amt-11-1937-2018
98. Assessment of PM2.5 monitoring using MicroPEM: A validation study in a city with elevated PM2.5 levels Y. Du et al. 10.1016/j.ecoenv.2019.01.002
99. Identification of technical problems affecting performance of DustTrak DRX aerosol monitors I. Rivas et al. 10.1016/j.scitotenv.2017.01.129
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101. Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi T. Zheng et al. 10.5194/amt-12-5161-2019
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105. Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise C. Borrego et al. 10.1016/j.atmosenv.2016.09.050
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107. Development and evaluation of a palm-sized optical PM2.5 sensor T. Nakayama et al. 10.1080/02786826.2017.1375078
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114. Real-Time Monitoring of Spray Drift from Three Different Orchard Sprayers M. Blanco et al. 10.1016/j.chemosphere.2019.01.092
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119. Field evaluation of low-cost particulate matter sensors in high- and low-concentration environments T. Zheng et al. 10.5194/amt-11-4823-2018
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122. Outlier detection and gap filling methodologies for low-cost air quality measurements T. Ottosen & P. Kumar 10.1039/C8EM00593A
123. Effect of micropillars with varying geometry and density on the efficiency of impaction-based quartz crystal microbalance aerosol sensors M. Hajizadehmotlagh & I. Paprotny 10.1063/1.5125895
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128. Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network S. Sousan et al. 10.3390/s18093008
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131. How Sensors Might Help Define the External Exposome M. Loh et al. 10.3390/ijerph14040434
132. Air pollution and child obesity: Assessing the feasibility of measuring personal PM2.5 exposures and behaviours related to BMI in preschool-aged children in China H. Ong et al. 10.1016/j.obmed.2019.100149
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134. Crowd-sourced air quality studies: A review of the literature & portable sensors J. Thompson 10.1016/j.teac.2016.06.001
135. Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust Storms A. Khader & R. Martin 10.3390/atmos10090539
136. Laboratory Evaluation and Calibration of Three Low-Cost Particle Sensors for Particulate Matter Measurement Y. Wang et al. 10.1080/02786826.2015.1100710
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