197 citations as recorded by crossref.

1. Multi-unit calibration rejects inherent device variability of chemical sensor arrays A. Solórzano et al. https://doi.org/10.1016/j.snb.2018.02.188
2. Real-Time Environmental Monitoring Platform for Wellness and Preventive Care in a Smart and Sustainable City with an Urban Landscape Perspective: The Case of Developing Countries V. Gonzalez et al. https://doi.org/10.3390/land11101635
3. The impacts of water vapour and co-pollutants on the performance of electrochemical gas sensors used for air quality monitoring X. Pang et al. https://doi.org/10.1016/j.snb.2018.03.144
4. IoT-based filter management system using reinforced ANFIS for VOCs reduction in urban industrial facilities K. Kim et al. https://doi.org/10.1038/s41598-025-02435-8
5. Field and laboratory performance evaluations of 28 gas-phase air quality sensors by the AQ-SPEC program A. Collier-Oxandale et al. https://doi.org/10.1016/j.atmosenv.2019.117092
6. Confined space rescue: A proposed procedure to reduce the risks J. Selman et al. https://doi.org/10.1016/j.ssci.2018.11.017
7. Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer P. Monks et al. https://doi.org/10.5194/acp-15-8889-2015
8. Clustering approaches to improve the performance of low cost air pollution sensors K. Smith et al. https://doi.org/10.1039/C7FD00020K
9. Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System K. Alhasa et al. https://doi.org/10.3390/s18124380
10. Miniature Low-Cost Carbon Dioxide Sensor for Mobile Devices L. Scholz et al. https://doi.org/10.1109/JSEN.2017.2682638
11. An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations K. Okorn & L. Iraci https://doi.org/10.5194/amt-17-6425-2024
12. Intelligent Wireless Sensor Network for Gas Classification Using Machine Learning N. Zaeri & R. Qasim https://doi.org/10.1109/JSYST.2023.3238357
13. Informed Nonnegative Matrix Factorization Methods for Mobile Sensor Network Calibration C. Dorffer et al. https://doi.org/10.1109/TSIPN.2018.2811962
14. Enrichment of Air Quality Monitoring with mobile Sensors for Spatial Modelling of Pollutants (case study: CO in Tehran) M. Kheradmandi & R. Abbaspour https://doi.org/10.29252/jgit.4.2.29
15. Field calibration of a low-cost sensors network to assess traffic-related air pollution along the Brenner highway A. Bisignano et al. https://doi.org/10.1016/j.atmosenv.2022.119008
16. A portable, low-cost, smartphone assisted methodology for on-site measurement of NO2 levels in ambient air by selective chemical reactivity and digital image analysis M. Cerrato-Alvarez et al. https://doi.org/10.1016/j.snb.2021.129867
17. Two step calibration method for ozone low-cost sensor: Field experiences with the UrbanSense DCUs J. Sá et al. https://doi.org/10.1016/j.jenvman.2022.116910
18. Reducing the Influence of Environmental Factors on Performance of a Diffusion-Based Personal Exposure Kit H. Zong et al. https://doi.org/10.3390/s21144637
19. Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performance S. Jain & N. Zimmerman https://doi.org/10.1016/j.jaerosci.2024.106335
20. Use of Uncertainty Calculation Software as a Didactic Tool to Improve the Knowledge of Chemistry Students in Analytical Method Validation M. Cerrato-Alvarez et al. https://doi.org/10.1021/acs.jchemed.3c00102
21. Monitoring Environmental Tobacco Smoke (ETS) by Smart E-Nose: A Review Y. Wu et al. https://doi.org/10.1109/JSEN.2025.3598571
22. Low-Cost Air Quality Sensors: Biases, Corrections and Challenges in Their Comparability I. Hayward et al. https://doi.org/10.3390/atmos15121523
23. Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors A. Mukherjee et al. https://doi.org/10.3390/s19214701
24. Solution to the Problem of Calibration of Low-Cost Air Quality Measurement Sensors in Networks G. Miskell et al. https://doi.org/10.1021/acssensors.8b00074
25. Handling non-stationarity in E-nose design: a review V. Pareek et al. https://doi.org/10.1108/SR-02-2021-0038
26. On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter M. Jovašević-Stojanović et al. https://doi.org/10.1016/j.envpol.2015.08.035
27. High-Sensitivity NO2 Gas Sensor: Exploiting UV-Enhanced Recovery in a Hexadecafluorinated Iron Phthalocyanine-Reduced Graphene Oxide J. Cruz Lozada et al. https://doi.org/10.1021/acsomega.4c08662
28. Metrology for low-cost CO2 sensors applications: the case of a steady-state through-flow (SS-TF) chamber for CO2 fluxes observations R. Curcoll et al. https://doi.org/10.5194/amt-15-2807-2022
29. Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art M. Narayana et al. https://doi.org/10.3390/s22010394
30. Low-Cost Air Quality Sensing towards Smart Homes H. Omidvarborna et al. https://doi.org/10.3390/atmos12040453
31. A Statistical Calibration Framework for Improving Non-Reference Method Particulate Matter Reporting: A Focus on Community Air Monitoring Settings S. Commodore et al. https://doi.org/10.3390/atmos11080807
32. AirQuality Lab-on-a-Drone: A Low-Cost 3D-Printed Analytical IoT Platform for Vertical Monitoring of Gaseous H2S V. Leal et al. https://doi.org/10.1021/acs.analchem.3c02719
33. How Sensors Might Help Define the External Exposome M. Loh et al. https://doi.org/10.3390/ijerph14040434
34. Data Verification Tools for Minimizing Management Costs of Dense Air-Quality Monitoring Networks G. Miskell et al. https://doi.org/10.1021/acs.est.5b04421
35. Developing a Low-Cost Wearable Personal Exposure Monitor for Studying Respiratory Diseases Using Metal–Oxide Sensors K. Mallires et al. https://doi.org/10.1109/JSEN.2019.2917435
36. Calibrating Low-Cost Sensors by a Two-Phase Learning Approach for Urban Air Quality Measurement Y. Lin et al. https://doi.org/10.1145/3191750
37. Developing the scientific framework for urban geochemistry L. Chambers et al. https://doi.org/10.1016/j.apgeochem.2016.01.005
38. A CO2optical sensor based on self-assembled metal–organic framework nanoparticles B. Chocarro-Ruiz et al. https://doi.org/10.1039/C8TA02767F
39. 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. https://doi.org/10.1016/j.buildenv.2022.108833
40. Intra-urban spatial variability of surface ozone in Riverside, CA: viability and validation of low-cost sensors K. Sadighi et al. https://doi.org/10.5194/amt-11-1777-2018
41. Characterizing the Aging of Alphasense NO2 Sensors in Long-Term Field Deployments J. Li et al. https://doi.org/10.1021/acssensors.1c00729
42. A reproducible R workflow for harmonizing indoor air quality sensor data and cleaning activity logs in school-based field campaigns C. Falzone et al. https://doi.org/10.1016/j.mex.2026.103995
43. Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment F. Bulot et al. https://doi.org/10.1038/s41598-019-43716-3
44. Reputation-Based Reverse Combination Auction Incentive Method to Encourage Vehicles to Participate in the VCS System H. Yu et al. https://doi.org/10.1109/TNSE.2021.3095679
45. Spatial temporal distribution of particulate matter emission in Purwokerto, Banyumas, Central Java I. Sani et al. https://doi.org/10.1088/1755-1315/1556/1/012013
46. Seasonal Influence on the Performance of Low-Cost NO2 Sensor Calibrations S. Ratingen et al. https://doi.org/10.3390/s21237919
47. Transformational IoT sensing for air pollution and thermal exposures J. Pantelic et al. https://doi.org/10.3389/fbuil.2022.971523
48. Non-linear probabilistic calibration of low-cost environmental air pollution sensor networks for neighborhood level spatiotemporal exposure assessment A. Patton et al. https://doi.org/10.1038/s41370-022-00493-y
49. Calibration strategies and measurement frameworks for low-cost particulate matter sensors: a comprehensive review Z. Feng et al. https://doi.org/10.1088/1361-6501/ae6298
50. A Systematic Review of Air Quality Sensors, Guidelines, and Measurement Studies for Indoor Air Quality Management H. Zhang & R. Srinivasan https://doi.org/10.3390/su12219045
51. End-User Feedback on a Low-Cost Portable Air Quality Sensor System—Are We There Yet? J. Robinson et al. https://doi.org/10.3390/s18113768
52. Efficacy of Paired Electrochemical Sensors for Measuring Ozone Concentrations C. Zuidema et al. https://doi.org/10.1080/15459624.2018.1540872
53. Validation of Low-Cost Sensors in Measuring Real-Time PM10 Concentrations at Two Sites in Delhi National Capital Region R. Sahu et al. https://doi.org/10.3390/s20051347
54. Investigating transport of particulate matter from cooking emissions in a multi-story house using low-cost sensor measurements and different modeling approaches A. Martin et al. https://doi.org/10.1016/j.indenv.2025.100126
55. Towards Improving Air Quality Monitoring Using Fixed and Mobile Stations: Case of Mohammedia City A. El Arfaoui et al. https://doi.org/10.3390/su18062944
56. The influence of humidity on the performance of a low-cost air particle mass sensor and the effect of atmospheric fog R. Jayaratne et al. https://doi.org/10.5194/amt-11-4883-2018
57. A fast calibration algorithm for Non-Dispersive Infrared single channel carbon dioxide sensor based on deep learning K. Mao et al. https://doi.org/10.1016/j.comcom.2021.08.003
58. A hardware–software co-design calibration framework for two-electrode gas sensors under low-temperature conditions: accuracy, latency, and energy trade-offs Y. Chen et al. https://doi.org/10.1016/j.measurement.2026.120656
59. Characterization of PM 2.5 exposure concentration in transport microenvironments using portable monitors Z. Li et al. https://doi.org/10.1016/j.envpol.2017.05.039
60. Ambient and laboratory evaluation of a low-cost particulate matter sensor K. Kelly et al. https://doi.org/10.1016/j.envpol.2016.12.039
61. The effect of ego-motion on environmental monitoring U. Lerner et al. https://doi.org/10.1016/j.scitotenv.2015.06.066
62. 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. https://doi.org/10.5194/amt-10-3783-2017
63. Spatial variability and pollutant-specific mitigation effects of an urban vegetated park observed with a high-density air quality sensor network J. Ryu et al. https://doi.org/10.1016/j.envpol.2026.128696
64. Rational Design of Semiconductor‐Based Chemiresistors and their Libraries for Next‐Generation Artificial Olfaction S. Jeong et al. https://doi.org/10.1002/adma.202002075
65. Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring R. Kureshi et al. https://doi.org/10.3390/s22031093
66. Mapping Occupational Hazards with a Multi-sensor Network in a Heavy-Vehicle Manufacturing Facility C. Zuidema et al. https://doi.org/10.1093/annweh/wxy111
67. SmartAirQ: A Big Data Governance Framework for Urban Air Quality Management in Smart Cities A. Kaginalkar et al. https://doi.org/10.3389/fenvs.2022.785129
68. Prototype design of urban monitoring on several gaseous pollutants using low-cost electrochemical sensors K. Alhasa et al. https://doi.org/10.1088/1755-1315/1201/1/012024
69. Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments D. Hagan et al. https://doi.org/10.5194/amt-11-315-2018
70. Assessing the Utility of Low-Cost Particulate Matter Sensors over a 12-Week Period in the Cuyama Valley of California A. Mukherjee et al. https://doi.org/10.3390/s17081805
71. Kitchen Area Air Quality Measurements in Northern Ghana: Evaluating the Performance of a Low-Cost Particulate Sensor within a Household Energy Study E. Coffey et al. https://doi.org/10.3390/atmos10070400
72. Poly(3,4-ethylenedioxythiophene)/carbon-based nanocomposite for gas sensing I. Olenych et al. https://doi.org/10.1080/15421406.2020.1732567
73. Low-complexity methods to mitigate the impact of environmental variables on low-cost UAS-based atmospheric carbon dioxide measurements G. Britto Hupsel de Azevedo et al. https://doi.org/10.5194/amt-15-5599-2022
74. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring N. Zimmerman et al. https://doi.org/10.5194/amt-11-291-2018
75. Low Cost Sensor With IoT LoRaWAN Connectivity and Machine Learning-Based Calibration for Air Pollution Monitoring S. Ali et al. https://doi.org/10.1109/TIM.2020.3034109
76. Validate personal air-pollution sensors A. Lewis & P. Edwards https://doi.org/10.1038/535029a
77. Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis A. Gaiardo et al. https://doi.org/10.3390/s21030783
78. Practical Use of Metal Oxide Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban Environments P. Peterson et al. https://doi.org/10.3390/s17071653
79. Design, fabrication, and calibration of the Building EnVironment and Occupancy (BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor H. Fritz et al. https://doi.org/10.1016/j.buildenv.2022.109432
80. Low-cost, multimodal environmental monitoring based on the Internet of Things G. Coulby et al. https://doi.org/10.1016/j.buildenv.2021.108014
81. Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning I. Apostolopoulos et al. https://doi.org/10.3390/s24134110
82. Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring L. Sun et al. https://doi.org/10.3390/s16020211
83. Mapping urban air quality in near real-time using observations from low-cost sensors and model information P. Schneider et al. https://doi.org/10.1016/j.envint.2017.05.005
84. Air pollution and pregnancy J. Aguilera et al. https://doi.org/10.1016/j.semperi.2023.151838
85. Review of the Performance of Low-Cost Sensors for Air Quality Monitoring F. Karagulian et al. https://doi.org/10.3390/atmos10090506
86. CO2 gas sensing with an electrolyte-gated transistor using impedance spectroscopy B. Ersöz et al. https://doi.org/10.1016/j.snb.2021.129598
87. Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors T. Sayahi et al. https://doi.org/10.1016/j.envpol.2018.11.065
88. Understanding the ability of low-cost MOx sensors to quantify ambient VOCs A. Collier-Oxandale et al. https://doi.org/10.5194/amt-12-1441-2019
89. Smartphone App for Residential Testing of Formaldehyde (SmART-Form) S. Zhang et al. https://doi.org/10.1016/j.buildenv.2018.11.029
90. Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring S. Vikram et al. https://doi.org/10.5194/amt-12-4211-2019
91. Calibration and performance evaluation of PM2.5 and NO2 air quality sensors for environmental epidemiology M. Chacón-Mateos et al. https://doi.org/10.5194/amt-18-4061-2025
92. Evaluating the performance of low cost chemical sensors for air pollution research A. Lewis et al. https://doi.org/10.1039/C5FD00201J
93. The Smart Ring Experience in l’Aquila (Italy): Integrating Smart Mobility Public Services with Air Quality Indexes M. Villani et al. https://doi.org/10.3390/chemosensors4040024
94. Rapid and Selective Detection of Linalool Using Solidly Mounted Resonators for Plant Health Monitoring U. Yaqoob et al. https://doi.org/10.1109/JSEN.2025.3626138
95. Air Pollution Monitoring via Wireless Sensor Networks: The Investigation and Correction of the Aging Behavior of Electrochemical Gaseous Pollutant Sensors I. Christakis et al. https://doi.org/10.3390/electronics12081842
96. Using A Low-Cost Sensor Array and Machine Learning Techniques to Detect Complex Pollutant Mixtures and Identify Likely Sources J. Thorson et al. https://doi.org/10.3390/s19173723
97. 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. https://doi.org/10.3390/s21124214
98. A Novel Network‐Based Approach to Determining Measurement Representation Error for Model Evaluation of Aerosol Microphysical Properties E. Asher et al. https://doi.org/10.1029/2021JD035485
99. Multivariate estimation of the limit of detection by orthogonal partial least squares in temperature-modulated MOX sensors J. Burgués & S. Marco https://doi.org/10.1016/j.aca.2018.03.005
100. Conducting Human-Centered Building Science at the Well Living Lab S. Aristizabal et al. https://doi.org/10.1080/24751448.2019.1640535
101. Assessing Mobility-Based Real-Time Air Pollution Exposure in Space and Time Using Smart Sensors and GPS Trajectories in Beijing J. Ma et al. https://doi.org/10.1080/24694452.2019.1653752
102. Using low-cost particle sensors in HVAC ducts V. Gentile et al. https://doi.org/10.1080/02786826.2025.2475085
103. Wearable system for outdoor air quality monitoring in a WSN with cloud computing: Design, validation and deployment S. Palomeque-Mangut et al. https://doi.org/10.1016/j.chemosphere.2022.135948
104. Observational Inferences of NOx and CO Emission Factors for Vehicles and Homes in the San Francisco Bay Area Y. Zhu et al. https://doi.org/10.1021/acsestair.5c00004
105. Investigating the intra-urban thermal and air quality environment: New transect sensing methodology and measurements I. Kousis et al. https://doi.org/10.1016/j.measurement.2023.113210
106. Field calibration of electrochemical NO2 sensors in a citizen science context B. Mijling et al. https://doi.org/10.5194/amt-11-1297-2018
107. Domain Adaptation-Based Deep Calibration of Low-Cost PM₂.₅ Sensors S. Jha et al. https://doi.org/10.1109/JSEN.2021.3118454
108. Electronic Noses: From Advanced Materials to Sensors Aided with Data Processing W. Hu et al. https://doi.org/10.1002/admt.201800488
109. Long-term reliability of the Figaro TGS 2600 solid-state methane sensor under low-Arctic conditions at Toolik Lake, Alaska W. Eugster et al. https://doi.org/10.5194/amt-13-2681-2020
110. Application of Low-Cost Sensors for Accurate Ambient Temperature Monitoring B. Mobaraki et al. https://doi.org/10.3390/buildings12091411
111. Application of low-cost particulate matter sensors for air quality monitoring and exposure assessment in underground mines: A review N. Amoah et al. https://doi.org/10.1007/s12613-021-2378-z
112. An evaluation tool kit of air quality micro-sensing units B. Fishbain et al. https://doi.org/10.1016/j.scitotenv.2016.09.061
113. Spatial Modeling of Daily PM2.5, NO2, and CO Concentrations Measured by a Low-Cost Sensor Network: Comparison of Linear, Machine Learning, and Hybrid Land Use Models S. Jain et al. https://doi.org/10.1021/acs.est.1c02653
114. Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO2 Sensor Drift Correction L. Sun et al. https://doi.org/10.3390/s17081916
115. Development of end-to-end low-cost IoT system for densely deployed PM monitoring network: an Indian case study A. Parmar et al. https://doi.org/10.3389/friot.2024.1332322
116. Calibration of low-cost NO2 sensors in an urban air quality network V. van Zoest et al. https://doi.org/10.1016/j.atmosenv.2019.04.048
117. Performance of artificial neural networks and linear models to quantify 4 trace gas species in an oil and gas production region with low-cost sensors J. Casey et al. https://doi.org/10.1016/j.snb.2018.12.049
118. Machine Learning for Improving Accuracy and Utility of Low-Cost Environmental Air Pollution Sensor Networks for Probabilistic Spatial Exposure Assessment A. Patton et al. https://doi.org/10.2139/ssrn.4001163
119. Effect of Relative Humidity and Air Temperature on the Results Obtained from Low-Cost Gas Sensors for Ambient Air Quality Measurements A. Samad et al. https://doi.org/10.3390/s20185175
120. Mapping trends and analyzing key themes in low-cost sensors for air quality monitoring K. Alhasa et al. https://doi.org/10.1007/s12145-025-01927-5
121. Transit pollution exposure monitoring using low-cost wearable sensors N. Motlagh et al. https://doi.org/10.1016/j.trd.2021.102981
122. Online decorrelation of humidity and temperature in chemical sensors for continuous monitoring R. Huerta et al. https://doi.org/10.1016/j.chemolab.2016.07.004
123. COCAP: a carbon dioxide analyser for small unmanned aircraft systems M. Kunz et al. https://doi.org/10.5194/amt-11-1833-2018
124. Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication J. Wang et al. https://doi.org/10.1016/j.envint.2023.107934
125. A review of international experience in air quality assessment M. Pozdnyakov et al. https://doi.org/10.17816/humeco456406
126. Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary) A. Clements et al. https://doi.org/10.3390/s17112478
127. 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 https://doi.org/10.5194/amt-11-6351-2018
128. Evaluation of a low-cost multi-channel monitor for indoor air quality through a novel, low-cost, and reproducible platform A. Baldelli https://doi.org/10.1016/j.measen.2021.100059
129. Academically Produced Air Pollution Sensors for Personal Exposure Assessment: The Canarin Project B. Dessimond et al. https://doi.org/10.3390/s21051876
130. 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. https://doi.org/10.3390/s18092843
131. Improving Air Pollutant Metal Oxide Sensor Quantification Practices through: An Exploration of Sensor Signal Normalization, Multi-Sensor and Universal Calibration Model Generation, and Physical Factors Such as Co-Location Duration and Sensor Age K. Okorn & M. Hannigan https://doi.org/10.3390/atmos12050645
132. 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. https://doi.org/10.1038/s41370-020-0255-x
133. People-Centric Cognitive Internet of Things for the Quantitative Analysis of Environmental Exposure L. Yang et al. https://doi.org/10.1109/JIOT.2017.2751307
134. Understanding the origins of urban particulate matter pollution based on high-density vehicle-based sensor monitoring and big data analysis Y. Liang et al. https://doi.org/10.1016/j.uclim.2024.102241
135. Solar-powered air quality monitor applied under subtropical conditions in Hong Kong: Performance evaluation and application for pollution source tracking P. Wei et al. https://doi.org/10.1016/j.atmosenv.2019.116825
136. Review of urban computing in air quality management as smart city service: An integrated IoT, AI, and cloud technology perspective A. Kaginalkar et al. https://doi.org/10.1016/j.uclim.2021.100972
137. Wireless Sensor Network Combined with Cloud Computing for Air Quality Monitoring P. Arroyo et al. https://doi.org/10.3390/s19030691
138. Evaluation of low-cost formaldehyde sensors calibration M. Justo Alonso et al. https://doi.org/10.1016/j.buildenv.2022.109380
139. W-Air B. Maag et al. https://doi.org/10.1145/3191756
140. Applicability of compact and useful PM2.5 instrument with gas sensors in Japan and Thailand H. Aung et al. https://doi.org/10.1016/j.aeaoa.2025.100350
141. Low-cost electronic sensors for environmental research: Pitfalls and opportunities K. Chan et al. https://doi.org/10.1177/0309133320956567
142. A small, lightweight multipollutant sensor system for ground-mobile and aerial emission sampling from open area sources X. Zhou et al. https://doi.org/10.1016/j.atmosenv.2017.01.029
143. Personalised and Sustainable IEQ Monitoring: Use of Multi-Modal and Pervasive Technologies G. Coulby et al. https://doi.org/10.3390/ijerph20064897
144. Hyperlocal air pollution in an urban environment - measured with low-cost sensors L. Frederickson et al. https://doi.org/10.1016/j.uclim.2023.101684
145. From Crowdsourcing to Extreme Citizen Science: Participatory Research for Environmental Health P. English et al. https://doi.org/10.1146/annurev-publhealth-040617-013702
146. New understanding of miniaturized VOCs monitoring device: PID-type sensors performance evaluations in ambient air W. Xu et al. https://doi.org/10.1016/j.snb.2020.129285
147. Characterizing methane and total non-methane hydrocarbon levels in Los Angeles communities with oil and gas facilities using air quality monitors K. Okorn et al. https://doi.org/10.1016/j.scitotenv.2021.146194
148. Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring R. Laref et al. https://doi.org/10.3390/s21113581
149. An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis D. Sales-Lérida et al. https://doi.org/10.3390/s21144781
150. Stationary and portable multipollutant monitors for high-spatiotemporal-resolution air quality studies including online calibration C. Buehler et al. https://doi.org/10.5194/amt-14-995-2021
151. Low-Cost Sensors Accuracy Study and Enhancement Strategy S. Komarizadehasl et al. https://doi.org/10.3390/app12063186
152. Orthorhombic MoO3 nanobelts based NO2 gas sensor A. Mane & A. Moholkar https://doi.org/10.1016/j.apsusc.2017.02.055
153. Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone? L. Morawska et al. https://doi.org/10.1016/j.envint.2018.04.018
154. Characterization of inexpensive metal oxide sensor performance for trace methane detection D. Furuta et al. https://doi.org/10.5194/amt-15-5117-2022
155. iLOCuS: Incentivizing Vehicle Mobility to Optimize Sensing Distribution in Crowd Sensing S. Xu et al. https://doi.org/10.1109/TMC.2019.2915838
156. Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments A. Collier-Oxandale et al. https://doi.org/10.5194/amt-11-3569-2018
157. Assessing personal travel exposure to on-road PM2.5 using cellphone positioning data and mobile sensors Q. Li et al. https://doi.org/10.1016/j.healthplace.2022.102803
158. Review of low-cost sensors for indoor air quality: Features and applications M. Ródenas García et al. https://doi.org/10.1080/05704928.2022.2085734
159. A Deep Calibration Method for Low-Cost Air Monitoring Sensors With Multilevel Sequence Modeling H. Yu et al. https://doi.org/10.1109/TIM.2020.2978596
160. Mobile sensor network noise reduction and recalibration using a Bayesian network Y. Xiang et al. https://doi.org/10.5194/amt-9-347-2016
161. Low-cost measurement techniques to characterize the influence of home heating fuel on carbon monoxide in Navajo homes J. Casey et al. https://doi.org/10.1016/j.scitotenv.2017.12.312
162. Applications and Limitations of Quantifying Speciated and Source-Apportioned VOCs with Metal Oxide Sensors K. Okorn & M. Hannigan https://doi.org/10.3390/atmos12111383
163. Informing decisions in agent-based models — A mobile update A. Bell https://doi.org/10.1016/j.envsoft.2017.03.028
164. Fine particle mass monitoring with low-cost sensors: Corrections and long-term performance evaluation C. Malings et al. https://doi.org/10.1080/02786826.2019.1623863
165. Wearable sensors for respiratory protection in occupational settings J. Devkota & H. Sharma https://doi.org/10.1016/j.jsr.2026.02.006
166. Accuracy and practicality of a portable ozone monitor for personal exposure estimates J. Sagona et al. https://doi.org/10.1016/j.atmosenv.2017.11.036
167. One-year spatiotemporal variations of air pollutants in a major chemical-industry park in the Yangtze River Delta, China by 30 miniature air quality monitoring stations X. Pang et al. https://doi.org/10.3389/fenvs.2022.1026842
168. Evaluation and environmental correction of ambient CO2 measurements from a low-cost NDIR sensor C. Martin et al. https://doi.org/10.5194/amt-10-2383-2017
169. Environmental chemical sensing using small drones: A review J. Burgués & S. Marco https://doi.org/10.1016/j.scitotenv.2020.141172
170. Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration F. Concas et al. https://doi.org/10.1145/3446005
171. Using spatiotemporal prediction models to quantify PM2.5 exposure due to daily movement S. Jain et al. https://doi.org/10.1039/D3EA00051F
172. Field comparison of electrochemical gas sensor data correction algorithms for ambient air measurements Y. Liang et al. https://doi.org/10.1016/j.snb.2020.128897
173. The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors J. Kim et al. https://doi.org/10.5194/amt-11-1937-2018
174. Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science A. Collier-Oxandale et al. https://doi.org/10.3390/s22072543
175. Do new bike lanes impact air pollution exposure for cyclists?—a case study from Berlin S. Schmitz et al. https://doi.org/10.1088/1748-9326/ac1379
176. Impact of Outdoor Air Pollution on Indoor Air Quality in Low-Income Homes during Wildfire Seasons P. Shrestha et al. https://doi.org/10.3390/ijerph16193535
177. Development of an Integrated Micro-Environmental Monitoring System for Construction Sites M. Wong et al. https://doi.org/10.1016/j.proenv.2016.09.034
178. A Perspective on Indoor Air Quality Monitoring, Guidelines, and the Use of Various Sensors F. Amin Beigh et al. https://doi.org/10.1080/15275922.2024.2431330
179. A Survey on Sensor Calibration in Air Pollution Monitoring Deployments B. Maag et al. https://doi.org/10.1109/JIOT.2018.2853660
180. An Improved Sensor Calibration with Anomaly Detection and Removal X. Fang & I. Bate https://doi.org/10.1016/j.snb.2019.127428
181. End-user perspective of low-cost sensors for outdoor air pollution monitoring A. Rai et al. https://doi.org/10.1016/j.scitotenv.2017.06.266
182. Gas sensing properties of (MoO3)0.4(V2O5)0.6 microsheets: Effect of Pd sensitization A. Mane et al. https://doi.org/10.1016/j.vacuum.2017.07.034
183. A Variational Bayesian Blind Calibration Approach for Air Quality Sensor Deployments G. Li et al. https://doi.org/10.1109/JSEN.2022.3212009
184. Estimating personal exposures from a multi-hazard sensor network C. Zuidema et al. https://doi.org/10.1038/s41370-019-0146-1
185. Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors A. Cavaliere et al. https://doi.org/10.5194/amt-16-4723-2023
186. Development of Air Quality Boxes Based on Low-Cost Sensor Technology for Ambient Air Quality Monitoring P. Gäbel et al. https://doi.org/10.3390/s22103830
187. Data Quality in IoT-Based Air Quality Monitoring Systems: a Systematic Mapping Study J. Buelvas et al. https://doi.org/10.1007/s11270-023-06127-9
188. 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. https://doi.org/10.3390/s17092072
189. Reducing the destructive effect of ambient humidity variations on gas detection capability of a temperature modulated gas sensor by calcium chloride H. Mahdavi et al. https://doi.org/10.1016/j.snb.2020.129091
190. Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO2 monitoring in urban areas E. Arzoumanian et al. https://doi.org/10.5194/amt-12-2665-2019
191. A Decentralized Bayesian Algorithm For Distributed Compressive Sensing in Networked Sensing Systems W. Chen & I. Wassell https://doi.org/10.1109/TWC.2015.2487989
192. Community-Based Health and Exposure Study around Urban Oil Developments in South Los Angeles B. Shamasunder et al. https://doi.org/10.3390/ijerph15010138
193. Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study M. Shupler et al. https://doi.org/10.1016/j.envint.2021.107021
194. Comparing Building and Neighborhood-Scale Variability of CO2 and O3 to Inform Deployment Considerations for Low-Cost Sensor System Use A. Collier-Oxandale et al. https://doi.org/10.3390/s18051349
195. Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates? N. Castell et al. https://doi.org/10.1016/j.envint.2016.12.007
196. A Kalman Filter Scheme for the Optimization of Low-Cost Gas Sensor Measurements I. Christakis et al. https://doi.org/10.3390/electronics13010025
197. Statistical field calibration of a low-cost PM2.5 monitoring network in Baltimore A. Datta et al. https://doi.org/10.1016/j.atmosenv.2020.117761