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20. Pilot study of the vertical variations in outdoor pollutant concentrations and environmental conditions along the height of a tall building P. Azimi et al. 10.1016/j.buildenv.2018.04.031
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26. Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensors J. Kuula et al. 10.5194/amt-13-2413-2020
27. 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
28. Evaluation of low-cost gas sensors to quantify intra-urban variability of atmospheric pollutants A. Baruah et al. 10.1039/D2EA00165A
29. Low-Cost Air Quality Sensors: One-Year Field Comparative Measurement of Different Gas Sensors and Particle Counters with Reference Monitors at Tušimice Observatory P. Bauerová et al. 10.3390/atmos11050492
30. Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece I. Stavroulas et al. 10.3390/atmos11090926
31. Advances in Application of Air Quality Sensors in Environmental Monitoring 英. 宋 10.12677/AEP.2019.93037
32. Spatial modelling of particulate matter air pollution sensor measurements collected by community scientists while cycling, land use regression with spatial cross-validation, and applications of machine learning for data correction M. Adams et al. 10.1016/j.atmosenv.2020.117479
33. 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
34. Spatial and temporal variability of urban cyclists’ exposure to PM2.5 in Medellín, Colombia J. Martínez et al. 10.1016/j.apr.2023.101946
35. Insights about the Sources of PM2.5 in an Urban Area from Measurements of a Low-Cost Sensor Network G. Kosmopoulos et al. 10.3390/atmos13030440
36. The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action P. English et al. 10.1289/EHP1772
37. Using a network of lower-cost monitors to identify the influence of modifiable factors driving spatial patterns in fine particulate matter concentrations in an urban environment S. Rose Eilenberg et al. 10.1038/s41370-020-0255-x
38. In Situ Calibration Algorithms for Environmental Sensor Networks: A Review F. Delaine et al. 10.1109/JSEN.2019.2910317
39. Tropical Air Chemistry in Lagos, Nigeria A. Odu-Onikosi et al. 10.3390/atmos13071059
40. 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
41. Evaluation of low-cost sensors for quantitative personal exposure monitoring S. Mahajan & P. Kumar 10.1016/j.scs.2020.102076
42. City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT Devices S. Johnston et al. 10.3390/s19010209
43. 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
44. Long-term sensor measurements of lung deposited surface area of particulate matter emitted from local vehicular and residential wood combustion sources J. Kuula et al. 10.1080/02786826.2019.1668909
45. Community-based participatory research for the study of air pollution: a review of motivations, approaches, and outcomes A. Commodore et al. 10.1007/s10661-017-6063-7
46. Using Low-Cost Air Quality Sensor Networks to Improve the Spatial and Temporal Resolution of Concentration Maps F. Ahangar et al. 10.3390/ijerph16071252
47. 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
48. Environment-Adaptive Calibration System for Outdoor Low-Cost Electrochemical Gas Sensors B. Tian et al. 10.1109/ACCESS.2019.2916826
49. 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
50. On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction S. Koziel et al. 10.1016/j.knosys.2024.111564
51. Challenges and Opportunities in Calibrating Low-Cost Environmental Sensors N. Nalakurthi et al. 10.3390/s24113650
52. In-car and Near-road Exposure to PM2.5 and BC C. Ma & G. Kang 10.5572/ajae.2020.14.2.146
53. Design and Evaluation of a Reliable Low-Cost Atmospheric Pollution Station in Urban Environment G. Astudillo et al. 10.1109/ACCESS.2020.2980736
54. Using a distributed air sensor network to investigate the spatiotemporal patterns of PM2.5 concentrations R. Cao et al. 10.1016/j.envpol.2020.114549
55. Understanding social and behavioral drivers and impacts of air quality sensor use B. Hubbell et al. 10.1016/j.scitotenv.2017.11.275
56. Field calibration of electrochemical NO<sub>2</sub> sensors in a citizen science context B. Mijling et al. 10.5194/amt-11-1297-2018
57. Integrating Fixed Monitoring Systems with Low-Cost Sensors to Create High-Resolution Air Quality Maps for the Northern China Plain Region C. Chao et al. 10.1021/acsearthspacechem.1c00174
58. 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
59. 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
60. Machine learning calibration of low-cost NO<sub>2</sub> and PM<sub>10</sub> sensors: non-linear algorithms and their impact on site transferability P. Nowack et al. 10.5194/amt-14-5637-2021
61. Assessment of aerosol persistence in ICUs via low-cost sensor network and zonal models K. Glenn et al. 10.1038/s41598-023-30778-7
62. 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
63. Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA P. English et al. 10.3390/s20113031
64. Leveraging low-cost sensors to predict nitrogen dioxide for epidemiologic exposure assessment C. Zuidema et al. 10.1038/s41370-024-00667-w
65. A citizen science approach for enhancing public understanding of air pollution S. Mahajan et al. 10.1016/j.scs.2019.101800
66. Response of consumer and research grade indoor air quality monitors to residential sources of fine particles B. Singer & W. Delp 10.1111/ina.12463
67. Electrochemical Gas Sensors as Microphones D. Williams et al. 10.2139/ssrn.4094644
68. End-User Feedback on a Low-Cost Portable Air Quality Sensor System—Are We There Yet? J. Robinson et al. 10.3390/s18113768
69. Concentration-Temporal Multilevel Calibration of Low-Cost PM2.5 Sensors R. Day et al. 10.3390/su141610015
70. Evaluation of a new low-cost particle sensor as an internet-of-things device for outdoor air quality monitoring F. Roberts et al. 10.1080/10962247.2022.2093293
71. Examining the functional range of commercially available low‐cost airborne particle sensors and consequences for monitoring of indoor air quality in residences Y. Zou et al. 10.1111/ina.12621
72. Investigating measurement variation of modified low-cost particle sensors S. Collingwood et al. 10.1016/j.jaerosci.2019.04.017
73. 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
74. Air Quality Sensors and Data Adjustment Algorithms: When Is It No Longer a Measurement? G. Hagler et al. 10.1021/acs.est.8b01826
75. A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado B. Ford et al. 10.5194/amt-12-6385-2019
76. Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing S. Koziel et al. 10.1016/j.jestch.2024.101729
77. Air Quality in Puerto Rico in the Aftermath of Hurricane Maria: A Case Study on the Use of Lower Cost Air Quality Monitors R. Subramanian et al. 10.1021/acsearthspacechem.8b00079
78. Air pollution monitoring network using low-cost sensors, a case study in Hanoi, Vietnam T. Nguyen et al. 10.1088/1755-1315/266/1/012017
79. UNI-CAL: A Universal AI-Driven Model for Air Pollutant Sensor Calibration With Domain-Specific Knowledge Inputs Y. Han et al. 10.1109/ACCESS.2024.3410171
80. Node-to-node field calibration of wireless distributed air pollution sensor network F. Kizel et al. 10.1016/j.envpol.2017.09.042
81. Particulate matters: student-led air quality research in the third-year environmental chemistry classroom and the field S. Gao et al. 10.1007/s00216-018-0972-3
82. The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS): Integration of Low-Cost Sensors and Reference Grade Monitoring in a Complex Metropolitan Area. Part 1: Overview of the Project S. Kimbrough et al. 10.3390/chemosensors7020026
83. Schoolchildren’s exposure to PM2.5: a student club–based air quality monitoring campaign using low-cost sensors L. Chen et al. 10.1007/s11869-020-00815-9
84. Estimating concentrations for particle and gases in a mechanically ventilated building in Hong Kong: multivariate method and machine learning W. Che et al. 10.1007/s11869-021-01093-9
85. Amperometric Gas Sensors as a Low Cost Emerging Technology Platform for Air Quality Monitoring Applications: A Review R. Baron & J. Saffell 10.1021/acssensors.7b00620
86. Using crowd-sourced low-cost sensors in a land use regression of PM2.5 in 6 US cities T. Lu et al. 10.1007/s11869-022-01162-7
87. Errors in Ambient Gas Concentration Measurement Caused by Acoustic Response of Electrochemical Gas Sensors D. Williams et al. 10.2139/ssrn.4159819
88. Response Characterization of an Inexpensive Aerosol Sensor J. Kuula et al. 10.3390/s17122915
89. Field evaluation of low-cost particulate matter sensors in high- and low-concentration environments T. Zheng et al. 10.5194/amt-11-4823-2018
90. On the Security and Data Integrity of Low-Cost Sensor Networks for Air Quality Monitoring L. Luo et al. 10.3390/s18124451
91. Effects of personal air pollution exposure on asthma symptoms, lung function and airway inflammation L. Chambers et al. 10.1111/cea.13130
92. Low-Power Wide-Area technologies as building block for smart sensors in air quality measurements M. Knoll et al. 10.1007/s00502-018-0639-y
93. The performance assessment of low-cost air pollution sensor in city and the prospect of the autonomous vehicle for air pollution reduction L. Phuong Linh et al. 10.1088/1757-899X/819/1/012018
94. Evaluation of Cairpol and Aeroqual Air Sensors in Biomass Burning Plumes A. Whitehill et al. 10.3390/atmos13060877
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96. Nitrogen Dioxide, Greenhouse Gas Emissions and Transportation in Urban Areas: Lessons From the Covid-19 Pandemic C. Restrepo 10.3389/fenvs.2021.689985
97. A Low-Cost Optoacoustic Sensor for Environmental Monitoring A. Stylogiannis et al. 10.3390/s21041379
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99. High-performance machine-learning-based calibration of low-cost nitrogen dioxide sensor using environmental parameter differentials and global data scaling S. Koziel et al. 10.1038/s41598-024-77214-y
100. A protocol for measuring the impact of a smoke-free housing policy on indoor tobacco smoke exposure R. Cardozo et al. 10.1186/s12889-019-7043-3
101. Investigation of LASSO Regression Method as a Correction Measurements’ Factor for Low-Cost Air Quality Sensors I. Christakis et al. 10.3390/signals5010004
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103. Testing the performance of field calibration techniques for low-cost gas sensors in new deployment locations: across a county line and across Colorado J. Casey & M. Hannigan 10.5194/amt-11-6351-2018
104. Towards collaborative smart cities: a participatory framework to co-develop an environmental monitoring dashboard along the Texas Coast O. Jenewein et al. 10.1080/12265934.2024.2438201
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110. Field comparison of electrochemical gas sensor data correction algorithms for ambient air measurements Y. Liang et al. 10.1016/j.snb.2020.128897
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