278 citations as recorded by crossref.

1. Application of Machine Learning for the in-Field Correction of a PM2.5 Low-Cost Sensor Network W. Wang et al. 10.3390/s20175002
2. Errors in ambient gas concentration measurement caused by acoustic response of electrochemical gas sensors A. Farquhar et al. 10.1016/j.sna.2023.114254
3. On-field test and data calibration of a low-cost sensor for fine particles exposure assessment Y. Jiang et al. 10.1016/j.ecoenv.2021.111958
4. Performance evaluation of light weight gas sensor system suitable for airborne applications against co-location gas analysers over Delhi A. Ahlawat et al. 10.1016/j.scitotenv.2019.134016
5. Domain Adaptation-Based Deep Calibration of Low-Cost PM₂.₅ Sensors S. Jha et al. 10.1109/JSEN.2021.3118454
6. Optimising Citizen-Driven Air Quality Monitoring Networks for Cities S. Gupta et al. 10.3390/ijgi7120468
7. Evaluating uncertainty in sensor networks for urban air pollution insights D. Peters et al. 10.5194/amt-15-321-2022
8. Automated data scanning for dense networks of low-cost air quality instruments: Detection and differentiation of instrumental error and local to regional scale environmental abnormalities M. Alavi-Shoshtari et al. 10.1016/j.envsoft.2017.12.002
9. Assessing the accuracy of commercially available gas sensors for the measurement of ambient ozone and nitrogen dioxide K. Isiugo et al. 10.1080/15459624.2018.1513135
10. Anomaly Detection and Repairing for Improving Air Quality Monitoring F. Rollo et al. 10.3390/s23020640
11. Spatially dense air pollutant sampling: Implications of spatial variability on the representativeness of stationary air pollutant monitors H. Li et al. 10.1016/j.aeaoa.2019.100012
12. Temporal changes in field calibration relationships for Aeroqual S500 O3 and NO2 sensor-based monitors N. Masey et al. 10.1016/j.snb.2018.07.087
13. Modeling fine-grained spatio-temporal pollution maps with low-cost sensors S. Iyer et al. 10.1038/s41612-022-00293-z
14. Secondhand smoke exposure in public and private high-rise multiunit housing serving low-income residents in New York City prior to federal smoking ban in public housing, 2018 E. Anastasiou et al. 10.1016/j.scitotenv.2019.135322
15. Interpreting Mobile and Handheld Air Sensor Readings in Relation to Air Quality Standards and Health Effect Reference Values: Tackling the Challenges G. Woodall et al. 10.3390/atmos8100182
16. Added Value of Vaisala AQT530 Sensors as a Part of a Sensor Network for Comprehensive Air Quality Monitoring T. Petäjä et al. 10.3389/fenvs.2021.719567
17. Low- and Medium-Cost Sensors for Tropospheric Ozone Monitoring—Results of an Evaluation Study in Wrocław, Poland M. Badura et al. 10.3390/atmos13040542
18. Developing a Modular Unmanned Aerial Vehicle (UAV) Platform for Air Pollution Profiling Q. Gu et al. 10.3390/s18124363
19. Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO<sub><i>x</i></sub> simulations over the city of Zürich, Switzerland A. Berchet et al. 10.5194/gmd-10-3441-2017
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
21. Outlier detection and gap filling methodologies for low-cost air quality measurements T. Ottosen & P. Kumar 10.1039/C8EM00593A
22. Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data W. Che et al. 10.1016/j.jes.2022.02.041
23. Reversible Electrochemical Gelation of Metal Chalcogenide Quantum Dots C. Hewa-Rahinduwage et al. 10.1021/jacs.0c03156
24. Development and evaluation of a palm-sized optical PM2.5sensor T. Nakayama et al. 10.1080/02786826.2017.1375078
25. End-user perspective of low-cost sensors for outdoor air pollution monitoring A. Rai et al. 10.1016/j.scitotenv.2017.06.266
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
95. CLEAN - Collaborative low-cost environmental and air-quality network F. Campo et al. 10.1016/j.envsoft.2023.105664
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
98. Air Quality Sensor Networks for Evidence-Based Policy Making: Best Practices for Actionable Insights J. Hofman et al. 10.3390/atmos13060944
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
102. Performance evaluation of MeteoTracker mobile sensor for outdoor applications F. Barbano et al. 10.5194/amt-17-3255-2024
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. Self-Portraits of Personal Exposure to Air Pollution: on where and when People Are Exposed, and on why it Is Difficult to Avoid N. da Schio 10.1007/s10745-020-00176-y
105. Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary) A. Clements et al. 10.3390/s17112478
106. Design Considerations for a Distributed Low-Cost Air Quality Sensing System for Urban Environments in Low-Resource Settings E. Bainomugisha et al. 10.3390/atmos14020354
107. Understanding the effect of temperature and relative humidity on sensor sensitivities in field environments and improving the calibration models of multiple electrochemical carbon monoxide (CO) sensors in a tropical environment R. Ariyaratne et al. 10.1016/j.snb.2023.133935
108. 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
109. Field comparison of electrochemical gas sensor data correction algorithms for ambient air measurements Y. Liang et al. 10.1016/j.snb.2020.128897
110. Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network M. Levy Zamora et al. 10.1021/acsestengg.1c00367
111. Precision and Accuracy of a Direct-Reading Miniaturized Monitor in PM2.5 Exposure Assessment F. Borghi et al. 10.3390/s18093089
112. Ambient Air Quality Measurement with Low-Cost Optical and Electrochemical Sensors: An Evaluation of Continuous Year-Long Operation J. Bílek et al. 10.3390/environments8110114
113. Association between microenvironment air quality and cardiovascular health outcomes Y. Tan et al. 10.1016/j.scitotenv.2020.137027
114. Evaluation methods for low-cost particulate matter sensors J. Bean 10.5194/amt-14-7369-2021
115. Characterising a mobile reference station (MoRS) to quantify personal exposure to air quality M. Hedges et al. 10.1016/j.atmosenv.2023.120160
116. Atomically dispersed Pb ionic sites in PbCdSe quantum dot gels enhance room-temperature NO2 sensing X. Geng et al. 10.1038/s41467-021-25192-4
117. Association between particulate matter and respiratory symptoms in students in the municipality of Guachetá, Colombia B. Saavedra Bayona et al. 10.17533/udea.redin.20210954
118. Evaluation of two collocated federal equivalent method PM2.5 instruments over a wide range of concentrations in Sarajevo, Bosnia and Herzegovina G. Hagler et al. 10.1016/j.apr.2022.101374
119. Fine particle mass monitoring with low-cost sensors: Corrections and long-term performance evaluation C. Malings et al. 10.1080/02786826.2019.1623863
120. Network of low-cost air quality sensors for monitoring indoor, outdoor, and personal PM2.5 exposure in Seattle during the 2020 wildfire season J. He et al. 10.1016/j.atmosenv.2022.119244
121. Identification of indoor air quality events using a K-means clustering analysis of gas sensors data A. Caron et al. 10.1016/j.snb.2019.126709
122. Air Quality Enhancement Districts: democratizing data to improve respiratory health K. Stevens et al. 10.1007/s13412-021-00670-9
123. Effects of Road Traffic on the Accuracy and Bias of Low-Cost Particulate Matter Sensor Measurements in Houston, Texas T. Oluwadairo et al. 10.3390/ijerph19031086
124. A Survey on Sensor Calibration in Air Pollution Monitoring Deployments B. Maag et al. 10.1109/JIOT.2018.2853660
125. Field evaluation of low-cost electrochemical air quality gas sensors under extreme temperature and relative humidity conditions R. Papaconstantinou et al. 10.5194/amt-16-3313-2023
126. Effects of aerosol particle size on the measurement of airborne PM2.5 with a low-cost particulate matter sensor (LCPMS) in a laboratory chamber T. Oluwadairo et al. 10.1007/s10661-021-09715-6
127. Minimized Training of Machine Learning-Based Calibration Methods for Low-Cost O3 Sensors S. Tondini et al. 10.1109/JSEN.2023.3339202
128. Monitoring of greenhouse gases and pollutants across an urban area using a light-rail public transit platform L. Mitchell et al. 10.1016/j.atmosenv.2018.05.044
129. A Variational Bayesian Blind Calibration Approach for Air Quality Sensor Deployments G. Li et al. 10.1109/JSEN.2022.3212009
130. Development of Air Quality Boxes Based on Low-Cost Sensor Technology for Ambient Air Quality Monitoring P. Gäbel et al. 10.3390/s22103830
131. Review of low-cost sensors for indoor air quality: Features and applications M. Ródenas García et al. 10.1080/05704928.2022.2085734
132. Probability-guaranteed distributed set-membership filtering over sensor networks: A stochastic communication protocol case H. Yu et al. 10.1016/j.sysconle.2024.105800
133. Performance evaluation of twelve low-cost PM2.5 sensors at an ambient air monitoring site B. Feenstra et al. 10.1016/j.atmosenv.2019.116946
134. Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration F. Concas et al. 10.1145/3446005
135. Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California T. Lu et al. 10.3390/ijerph19148777
136. Youth Engaged Participatory Air Monitoring: A ‘Day in the Life’ in Urban Environmental Justice Communities J. Johnston et al. 10.3390/ijerph17010093
137. A compact, modular and low-cost Internet of Things (IoT) platform for air quality monitoring in urban areas C. Spandonidis et al. 10.1088/1742-6596/1710/1/012004
138. Low-cost sensors as an alternative for long-term air quality monitoring X. Liu et al. 10.1016/j.envres.2020.109438
139. Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performance S. Jain & N. Zimmerman 10.1016/j.jaerosci.2024.106335
140. An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations K. Okorn & L. Iraci 10.5194/amt-17-6425-2024
141. Calibrating low-cost sensors for ambient air monitoring: Techniques, trends, and challenges L. Liang 10.1016/j.envres.2021.111163
142. Gaps and future directions in research on health effects of air pollution R. Vilcassim & G. Thurston 10.1016/j.ebiom.2023.104668
143. SCAN B. Maag et al. 10.1145/3090084
144. Estimating hourly PM2.5 concentrations at the neighborhood scale using a low-cost air sensor network: A Los Angeles case study Y. Lu et al. 10.1016/j.envres.2020.110653
145. A Community-Based Sensor Network for Monitoring the Air Quality in Urban Romania L. Velea et al. 10.3390/atmos14050840
146. Mobile phones as monitors of personal exposure to air pollution: Is this the future? M. Nyarku et al. 10.1371/journal.pone.0193150
147. Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors A. Mukherjee et al. 10.3390/s19214701
148. Estimating Mass Concentration Using a Low-cost Portable Particle Counter Based on Full-year Observations: Issues to Obtain Reliable Atmospheric PM2.5 Data S. Ueda et al. 10.5572/ajae.2020.14.2.155
149. Enhancing the reliability of particulate matter sensing by multivariate Tobit model using weather and air quality data W. Won et al. 10.1038/s41598-023-40468-z
150. Design and integration of air pollutants monitoring system for emergency management in construction site based on BIM and edge computing Z. Xu et al. 10.1016/j.buildenv.2021.108725
151. 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
152. A New Black Carbon Sensor for Dense Air Quality Monitoring Networks J. Caubel et al. 10.3390/s18030738
153. Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA G. Carvlin et al. 10.1080/10962247.2017.1369471
154. Low-Cost CO Sensor Calibration Using One Dimensional Convolutional Neural Network S. Ali et al. 10.3390/s23020854
155. Identification of the Safe Variation Limits for the Optimization of the Measurements in Low-Cost Electrochemical Air Quality Sensors I. Christakis et al. 10.3390/electrochem5010001
156. Low‐cost air quality monitoring networks for long‐term field campaigns: A review F. Carotenuto et al. 10.1002/met.2161
157. Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment F. Bulot et al. 10.1038/s41598-019-43716-3
158. Deployment of networked low-cost sensors and comparison to real-time stationary monitors in New Delhi J. Prakash et al. 10.1080/10962247.2021.1890276
159. A citizen science approach for air quality monitoring in a Kenyan informal development T. Manshur et al. 10.1016/j.cacint.2023.100105
160. Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring P. Wei et al. 10.3390/s18020059
161. Influence of particle properties and environmental factors on the performance of typical particle monitors and low-cost particle sensors in the market of China D. Wu et al. 10.1016/j.atmosenv.2021.118825
162. MAIC: Metalearning-Based Adaptive In-Field Calibration for IoT Air Quality Monitoring System N. Liu et al. 10.1109/JIOT.2022.3150849
163. Quantifying Neighborhood-Scale Spatial Variations of Ozone at Open Space and Urban Sites in Boulder, Colorado Using Low-Cost Sensor Technology L. Cheadle et al. 10.3390/s17092072
164. Citizen as Sensors' Commitment in Urban Public Action G. l'Her et al. 10.4018/IJEPR.2019100103
165. Wildfire Smoke Adjustment Factors for Low-Cost and Professional PM2.5 Monitors with Optical Sensors W. Delp & B. Singer 10.3390/s20133683
166. Air pollution measurement errors: is your data fit for purpose? S. Diez et al. 10.5194/amt-15-4091-2022
167. 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
168. Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks W. Wang et al. 10.3390/s20133661
169. Field and laboratory performance evaluations of 28 gas-phase air quality sensors by the AQ-SPEC program A. Collier-Oxandale et al. 10.1016/j.atmosenv.2019.117092
170. Technical note: Understanding the effect of COVID-19 on particle pollution using a low-cost sensor network E. Chadwick et al. 10.1016/j.jaerosci.2021.105766
171. Data Quality in IoT-Based Air Quality Monitoring Systems: a Systematic Mapping Study J. Buelvas et al. 10.1007/s11270-023-06127-9
172. Intra-urban spatial variability of surface ozone in Riverside, CA: viability and validation of low-cost sensors K. Sadighi et al. 10.5194/amt-11-1777-2018
173. Robust statistical calibration and characterization of portable low-cost air quality monitoring sensors to quantify real-time O<sub>3</sub> and NO<sub>2</sub> concentrations in diverse environments R. Sahu et al. 10.5194/amt-14-37-2021
174. Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2 K. Ko et al. 10.5194/amt-17-3303-2024
175. Review of the Performance of Low-Cost Sensors for Air Quality Monitoring F. Karagulian et al. 10.3390/atmos10090506
176. Methodology for Addressing Infectious Aerosol Persistence in Real-Time Using Sensor Network S. Makhsous et al. 10.3390/s21113928
177. Low-cost urban carbon monitoring network and implications for china: a comprehensive review H. Jiang et al. 10.1007/s11356-023-29836-4
178. 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
179. Estimating personal exposures from a multi-hazard sensor network C. Zuidema et al. 10.1038/s41370-019-0146-1
180. Examining spatiotemporal variability of urban particulate matter and application of high-time resolution data from a network of low-cost air pollution sensors S. Feinberg et al. 10.1016/j.atmosenv.2019.06.026
181. Challenges and opportunities of low-cost sensors in capturing the impacts of construction activities on neighborhood air quality W. Jaafar et al. 10.1016/j.buildenv.2024.111363
182. Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia D. Stojanović et al. 10.3390/s24134052
183. Development and application of a United States-wide correction for PM<sub>2.5</sub> data collected with the PurpleAir sensor K. Barkjohn et al. 10.5194/amt-14-4617-2021
184. Bio(sensors) based on molecularly imprinted polymers and silica materials used for food safety and biomedical analysis: Recent trends and future prospects X. Yan et al. 10.1016/j.talanta.2024.126292
185. Performance evaluation of ozone and particulate matter sensors H. DeWitt et al. 10.1080/10962247.2020.1713921
186. Effect of Three-Dimensional-Printed Thermoplastics Used in Sensor Housings on Common Atmospheric Trace Gasses T. Mangin et al. 10.3390/s24082610
187. Distant calibration of low-cost PM and NO2 sensors; evidence from multiple sensor testbeds J. Hofman et al. 10.1016/j.apr.2021.101246
188. Emulation of a Chemical Transport Model to Assess Air Quality under Future Emission Scenarios for the Southwest of Western Australia S. Vander Hoorn et al. 10.3390/atmos13122009
189. Effect of environmental conditions on the performance of a low-cost atmospheric particulate matter sensor B. Macías-Hernández et al. 10.1016/j.uclim.2023.101753
190. Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning I. Apostolopoulos et al. 10.3390/s24134110
191. A methodology for the characterization of portable sensors for air quality measure with the goal of deployment in citizen science B. Languille et al. 10.1016/j.scitotenv.2019.134698
192. Community-Based Measurements Reveal Unseen Differences during Air Pollution Episodes K. Kelly et al. 10.1021/acs.est.0c02341
193. Particulate Matter Emissions at Different Microenvironments Using Low-Cost Sensors in Megacity Dhaka, Bangladesh M. Nayeem et al. 10.3390/atmos15080897
194. 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
195. Cost-Efficient measurement platform and machine-learning-based sensor calibration for precise NO2 pollution monitoring A. Pietrenko-Dabrowska et al. 10.1016/j.measurement.2024.115168
196. Predicting airborne pollutant concentrations and events in a commercial building using low-cost pollutant sensors and machine learning: A case study A. Mohammadshirazi et al. 10.1016/j.buildenv.2022.108833
197. A Review of Literature on the Usage of Low-Cost Sensors to Measure Particulate Matter A. Raysoni et al. 10.3390/earth4010009
198. Spatial-Temporal Analysis of PM2.5 and NO2 Concentrations Collected Using Low-Cost Sensors in Peñuelas, Puerto Rico S. Reece et al. 10.3390/s18124314
199. 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
200. A User-Centric Design Thinking Approach for Advancement in Off-Line PM Air Samplers: Current Status and Future Directions K. Biswas et al. 10.1007/s41810-020-00071-5
201. 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
202. The Spatial and Temporal Variability of the Indoor Environmental Quality during Three Simulated Office Studies at a Living Lab N. Clements et al. 10.3390/buildings9030062
203. Improvement of community monitoring network data for urban heat island investigation in Hong Kong Y. Lam et al. 10.1016/j.uclim.2021.100852
204. Air Pollution Effects on Mental Health Relationships: Scoping Review on Historically Used Methodologies to Analyze Adult Populations K. Leontjevaite et al. 10.3390/air2030016
205. Estimating the spatial variability of fine particles at the neighborhood scale using a distributed network of particle sensors R. Shafran-Nathan et al. 10.1016/j.atmosenv.2019.117011
206. In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches D. Topalović et al. 10.1016/j.atmosenv.2019.06.028
207. Long-term behavior and stability of calibration models for NO and NO<sub>2</sub> low-cost sensors H. Kim et al. 10.5194/amt-15-2979-2022
208. Statistical data pre-processing and time series incorporation for high-efficacy calibration of low-cost NO2 sensor using machine learning S. Koziel et al. 10.1038/s41598-024-59993-6
209. Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone? L. Morawska et al. 10.1016/j.envint.2018.04.018
210. A Smart Rig for Calibration of Gas Sensor Nodes M. Benammar et al. 10.3390/s20082341
211. Key factors in epidemiological exposure and insights for environmental management: Evidence from meta-analysis Y. Wang et al. 10.1016/j.envpol.2024.124991
212. A Novel Method for Removing Baseline Drifts in Multivariate Chemical Sensor A. Grover & B. Lall 10.1109/TIM.2020.2976224
213. Personal exposure to fine particulate air pollutants impacts blood pressure and heart rate variability D. Lee et al. 10.1038/s41598-020-73205-x
214. First-Principles Algorithm for Air Quality Electrochemical Gas Sensors B. Ouyang 10.1021/acssensors.0c01129
215. Low cost air pollution monitoring systems: A review of protocols and enabling technologies Z. Idrees & L. Zheng 10.1016/j.jii.2019.100123
216. Missing Data Imputation on IoT Sensor Networks: Implications for on-Site Sensor Calibration N. Okafor & D. Delaney 10.1109/JSEN.2021.3105442
217. Seasonal Influence on the Performance of Low-Cost NO2 Sensor Calibrations S. Ratingen et al. 10.3390/s21237919
218. Analysis of fine particle pollution data measured at 29 US diplomatic posts worldwide R. Dhammapala 10.1016/j.atmosenv.2019.05.070
219. Fleet-based vehicle emission factors using low-cost sensors: Case study in parking garages B. Liu & N. Zimmerman 10.1016/j.trd.2020.102635
220. Low-Cost Sensors for Air Quality Monitoring - the Current State of the Technology and a Use Overview P. Buček et al. 10.2478/cdem-2021-0003
221. Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States D. Zhang et al. 10.1021/acs.est.3c05143
222. Feasibility and acceptability of monitoring personal air pollution exposure with sensors for asthma self-management S. Xie et al. 10.1186/s40733-021-00079-9
223. Nonlinear Regression Approach as a Correction Factor of Measurements of Low-Cost Electrochemical Air Quality Sensors I. Christakis et al. 10.3390/app14083282
224. Mindful Application of Digitalization for Sustainable Development: The Digitainability Assessment Framework S. Gupta & J. Rhyner 10.3390/su14053114
225. Continuous in-home PM2.5 concentrations of smokers with and without a history of respiratory exacerbations in Iowa, during and after an air purifier intervention E. Stapleton et al. 10.1038/s41370-020-0235-1
226. Air quality assessment system based on self-driven drone and LoRaWAN network A. Simo et al. 10.1016/j.comcom.2021.04.032
227. 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
228. Agent-based modeling to estimate exposures to urban air pollution from transportation: Exposure disparities and impacts of high-resolution data S. Gurram et al. 10.1016/j.compenvurbsys.2019.01.002
229. ICT Y. Cheng et al. 10.1145/3314393
230. Research of low-cost air quality monitoring models with different machine learning algorithms G. Wang et al. 10.5194/amt-17-181-2024
231. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. 10.3390/s22249669
232. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring N. Zimmerman et al. 10.5194/amt-11-291-2018
233. Evaluation of low-cost optical particle counters for monitoring individual indoor aerosol sources P. Salimifard et al. 10.1080/02786826.2019.1697423
234. Low-cost sensors for measuring airborne particulate matter: Field evaluation and calibration at a South-Eastern European site G. Kosmopoulos et al. 10.1016/j.scitotenv.2020.141396
235. Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study C. Zuidema et al. 10.3390/s21124214
236. Characterization of Ambient Air Quality in Selected Urban Areas in Uganda Using Low-Cost Sensing and Measurement Technologies D. Okure et al. 10.1021/acs.est.1c01443
237. The U.S. EPA wildland fire sensor challenge: Performance and evaluation of solver submitted multi-pollutant sensor systems M. Landis et al. 10.1016/j.atmosenv.2020.118165
238. QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation S. Diez et al. 10.1038/s41597-024-03767-2
239. A novel application of mobile low-cost sensors for atmospheric particulate matter monitoring in open-pit mines A. Zafra-Pérez et al. 10.1016/j.eti.2022.102974
240. Estimating daily PM2.5 concentrations in New York City at the neighborhood-scale: Implications for integrating non-regulatory measurements K. Huang et al. 10.1016/j.scitotenv.2019.134094
241. Low-processing data enrichment and calibration for PM2.5 low-cost sensors D. Stojanovic et al. 10.2298/TSCI221109221S
242. Leveraging Temporal Information to Improve Machine Learning-Based Calibration Techniques for Low-Cost Air Quality Sensors S. Ali et al. 10.3390/s24092930
243. Design of an ozone and nitrogen dioxide sensor unit and its long-term operation within a sensor network in the city of Zurich M. Mueller et al. 10.5194/amt-10-3783-2017
244. No one knows which city has the highest concentration of fine particulate matter R. Martin et al. 10.1016/j.aeaoa.2019.100040
245. Evaluating the Impact of Airborne Fine Particulate Matter and Heavy Metals on Oxidative Stress via Vitamin Supplementation E. Lee et al. 10.3390/toxics12070465
246. Use of Low-Cost Air Quality Monitoring Devices for Assessment of Road Transport Related Emissions N. Celikkaya et al. 10.1016/j.trpro.2019.09.125
247. An improved low-power measurement of ambient NO<sub>2</sub> and O<sub>3</sub> combining electrochemical sensor clusters and machine learning K. Smith et al. 10.5194/amt-12-1325-2019
248. Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments A. Heintzelman et al. 10.3390/ijerph20031934
249. Assessment of air quality microsensors versus reference methods: The EuNetAir Joint Exercise – Part II C. Borrego et al. 10.1016/j.atmosenv.2018.08.028
250. IoT-Enabled Particulate Matter Monitoring and Forecasting Method Based on Cluster Analysis J. Yun & J. Woo 10.1109/JIOT.2020.3038862
251. 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
252. Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art M. Narayana et al. 10.3390/s22010394
253. Global Ozone (GO3) Project and AQTreks: Use of evolving technologies by students and citizen scientists to monitor air pollutants J. Ellenburg et al. 10.1016/j.aeaoa.2019.100048
254. 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
255. Impact of California Fires on Local and Regional Air Quality: The Role of a Low‐Cost Sensor Network and Satellite Observations P. Gupta et al. 10.1029/2018GH000136
256. An efficient spatiotemporal data calibration approach for the low-cost PM2.5 sensing network: A case study in Taiwan C. Lee et al. 10.1016/j.envint.2019.05.032
257. Dynamic Measurement and Data Calibration for Aerial Mobile IoT J. Gu et al. 10.1109/JIOT.2020.2977910
258. Practical Field Calibration of Portable Monitors for Mobile Measurements of Multiple Air Pollutants C. Lin et al. 10.3390/atmos8120231
259. Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado S. Feinberg et al. 10.5194/amt-11-4605-2018
260. 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 measurements C. Huang et al. 10.1371/journal.pone.0259745
261. Particulate Matter in the Korea Train eXpress (KTX) Cabin and its Exposure C. Ma & G. Kang 10.5572/ajae.2022.041
262. Improving Data Quality of Low-cost IoT Sensors in Environmental Monitoring Networks Using Data Fusion and Machine Learning Approach N. Okafor et al. 10.1016/j.icte.2020.06.004
263. 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
264. Assessing the effects of mobility on air quality: The Liverpool Smart Pedestrian project N. Verstaevel et al. 10.1016/j.trpro.2020.08.276
265. In-car particulate matter exposure across ten global cities P. Kumar et al. 10.1016/j.scitotenv.2020.141395
266. The Development of a Low-Cost Particulate Matter 2.5 Sensor Calibration Model in Daycare Centers Using Long Short-Term Memory Algorithms H. Jeon et al. 10.3390/atmos14081228
267. Application of Low-Cost Electrochemical Sensors to Aqueous Systems to Allow Automated Determination of NH3 and H2S in Water M. Cämmerer et al. 10.3390/s20102814
268. Testing the performance of sensors for ozone pollution monitoring in a citizen science approach A. Ripoll et al. 10.1016/j.scitotenv.2018.09.257
269. Mapping Occupational Hazards with a Multi-sensor Network in a Heavy-Vehicle Manufacturing Facility C. Zuidema et al. 10.1093/annweh/wxy111
270. 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
271. Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments D. Hagan et al. 10.5194/amt-11-315-2018
272. Urban Air Quality Management at Low Cost Using Micro Air Sensors: A Case Study from Accra, Ghana C. Hodoli et al. 10.1021/acsestair.4c00172
273. Calibration Assessment of Low-Cost Carbon Dioxide Sensors Using the Extremely Randomized Trees Algorithm T. Araújo et al. 10.3390/s23136153
274. Assessing the Utility of Low-Cost Particulate Matter Sensors over a 12-Week Period in the Cuyama Valley of California A. Mukherjee et al. 10.3390/s17081805
275. How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations E. Brattich et al. 10.3390/s20113073
276. Performance Evaluation and Community Application of Low-Cost Sensors for Ozone and Nitrogen Dioxide R. Duvall et al. 10.3390/s16101698
277. Development and evaluation of an open-source, low-cost distributed sensor network for environmental monitoring applications N. Gunawardena et al. 10.1088/1361-6501/aa97fb
278. Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things F. M. Bublitz et al. 10.3390/ijerph16203847