206 citations as recorded by crossref.

1. Highly resolved spatiotemporal variability of fine particle number concentrations in an urban neighborhood Y. Etzion & D. Broday 10.1016/j.jaerosci.2018.01.004
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
3. Field Evaluation of Low-Cost Particulate Matter Sensors in Beijing H. Mei et al. 10.3390/s20164381
4. Spatial calibration and PM2.5 mapping of low-cost air quality sensors H. Chu et al. 10.1038/s41598-020-79064-w
5. Laboratory assessment of low-cost PM monitors A. Manikonda et al. 10.1016/j.jaerosci.2016.08.010
6. Evaluation methods for low-cost particulate matter sensors J. Bean 10.5194/amt-14-7369-2021
7. Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors T. Sayahi et al. 10.1016/j.envpol.2019.113131
8. Effects of spatial sensitivity on mass sensing with bulk acoustic mode resonators A. Zielinski et al. 10.1016/j.sna.2015.11.003
9. 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
10. Observation of PM2.5 using a combination of satellite remote sensing and low-cost sensor network in Siberian urban areas with limited reference monitoring C. Lin et al. 10.1016/j.atmosenv.2020.117410
11. Development and testing a low-cost device for airborne PM monitoring in highly anthropized areas: The international maritime hub of Civitavecchia (Rome, Italy) F. Lucci et al. 10.1016/j.geogeo.2022.100120
12. Application of PM 2.5 low-cost sensors for indoor air quality compliance monitoring L. Morawska et al. 10.1080/02786826.2025.2457326
13. A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors S. Smith et al. 10.3390/s25041028
14. Evaluation and environmental correction of ambient CO2 measurements from a low-cost NDIR sensor C. Martin et al. 10.5194/amt-10-2383-2017
15. Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown M. Kaliszewski et al. 10.3390/s20247290
16. Assessment and Improvement of Two Low-Cost Particulate Matter Sensor Systems by Using Spatial Interpolation Data from Air Quality Monitoring Stations C. Liang & P. Yu 10.3390/atmos12030300
17. Indoor Air Pollution and Health: Bridging Perspectives from Developing and Developed Countries A. Pillarisetti et al. 10.1146/annurev-environ-012220-010602
18. A Survey on Real-Time Communications in Wireless Sensor Networks B. Kim et al. 10.1155/2017/1864847
19. Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors T. Sayahi et al. 10.1016/j.envpol.2018.11.065
20. Field Assessment of the Village Green Project: An Autonomous Community Air Quality Monitoring System W. Jiao et al. 10.1021/acs.est.5b01245
21. What does the Shinyei PPD42NS Low-Cost Dust Sensor Really Measure? M. Canu et al. 10.18178/ijesd.2021.12.1.1310
22. Review of low-cost sensors for indoor air quality: Features and applications M. Ródenas García et al. 10.1080/05704928.2022.2085734
23. How Sensors Might Help Define the External Exposome M. Loh et al. 10.3390/ijerph14040434
24. 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
25. The Aerosol Research Observation Station (AEROS) K. Ardon-Dryer et al. 10.5194/amt-15-2345-2022
26. A tunable high-pass filter for simple and inexpensive size-segregation of sub-10-nm nanoparticles N. Surawski et al. 10.1038/srep45678
27. 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
28. Comparison of methods for converting Dylos particle number concentrations to PM2.5 mass concentrations R. Franken et al. 10.1111/ina.12546
29. Assessing the spatial transferability of calibration models across a low-cost sensors network V. Malyan et al. 10.1016/j.jaerosci.2024.106437
30. Calibration and validation-based assessment of low-cost air quality sensors J. Dong et al. 10.1016/j.scitotenv.2025.179364
31. Hygroscopic properties of particulate matter and effects of their interactions with weather on visibility W. Won et al. 10.1038/s41598-021-95834-6
32. Publicly available low-cost sensor measurements for PM2.5 exposure modeling: Guidance for monitor deployment and data selection J. Bi et al. 10.1016/j.envint.2021.106897
33. Evaluation of a Low-Cost Aerosol Sensor to Assess Dust Concentrations in a Swine Building S. Jones et al. 10.1093/annhyg/mew009
34. Re-calibrating DIY: Testing digital participation across dust sensors, fry pans and environmental pollution H. Pritchard et al. 10.1177/1461444818777473
35. Estimating Hourly Concentrations of PM2.5 across a Metropolitan Area Using Low-Cost Particle Monitors N. Zikova et al. 10.3390/s17081922
36. 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
37. Building and optimising an automatic monitoring system network for outdoor PM2.5: a case study of Ho Chi Minh City L. Bui et al. 10.1007/s10661-023-11319-1
38. Observation and modeling of vertical carbon dioxide distribution in a heavily polluted suburban environment Z. BAO et al. 10.1080/16742834.2020.1746627
39. Evaluating the Performance of Low-Cost Air Quality Monitors in Dallas, Texas H. Khreis et al. 10.3390/ijerph19031647
40. The use of low-cost measuring devices for testing air quality in hard-to-reach locations M. Rogulski et al. 10.1051/e3sconf/20184400151
41. Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensors J. Kuula et al. 10.5194/amt-13-2413-2020
42. Response Characterization of an Inexpensive Aerosol Sensor J. Kuula et al. 10.3390/s17122915
43. 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
44. 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
45. Fine-Scale Spatiotemporal Air Pollution Analysis Using Mobile Monitors on Google Street View Vehicles Y. Guan et al. 10.1080/01621459.2019.1665526
46. 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
47. Low-Cost CO Sensor Calibration Using One Dimensional Convolutional Neural Network S. Ali et al. 10.3390/s23020854
48. Visualization of Dust Generation in Outdoor Workplaces Using A Wearable Particle Monitor and Global Navigation Satellite System S. SEKOGUCHI et al. 10.7888/juoeh.44.1
49. Experimental and modeling assessment of a novel automotive cabin PM2.5 removal system J. Vande Hey et al. 10.1080/02786826.2018.1490694
50. Domain Adaptation-Based Deep Calibration of Low-Cost PM₂.₅ Sensors S. Jha et al. 10.1109/JSEN.2021.3118454
51. 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
52. Usability of a Personal Air Pollution Monitor: Design-Feedback Iterative Cycle Study G. Duncan et al. 10.2196/12023
53. Application of Machine Learning for the in-Field Correction of a PM2.5 Low-Cost Sensor Network W. Wang et al. 10.3390/s20175002
54. 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
55. 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
56. 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
57. 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
58. Spatial and temporal variability of urban cyclists’ exposure to PM2.5 in Medellín, Colombia J. Martínez et al. 10.1016/j.apr.2023.101946
59. 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
60. 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
61. Potential of a low-cost gas sensor for atmospheric methane monitoring M. van den Bossche et al. 10.1016/j.snb.2016.07.092
62. A machine learning field calibration method for improving the performance of low-cost particle sensors S. Patra et al. 10.1016/j.buildenv.2020.107457
63. Inadequacy of air purifier for indoor air quality improvement in classrooms without external ventilation Y. Choe et al. 10.1016/j.buildenv.2021.108450
64. Solar-powered air quality monitor applied under subtropical conditions in Hong Kong: Performance evaluation and application for pollution source tracking P. Wei et al. 10.1016/j.atmosenv.2019.116825
65. Field and Laboratory Evaluations of the Low-Cost Plantower Particulate Matter Sensor M. Levy Zamora et al. 10.1021/acs.est.8b05174
66. 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
67. Small, Smart, Fast, and Cheap: Microchip-Based Sensors to Estimate Air Pollution Exposures in Rural Households A. Pillarisetti et al. 10.3390/s17081879
68. 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
69. 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
70. Development and performance evaluation of a mixed-sensor system for fine particles and road traffic noise C. Wu et al. 10.1016/j.eti.2022.102902
71. 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
72. 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
73. Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study D. Bousiotis et al. 10.5194/amt-14-4139-2021
74. 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
75. Air Pollution Effects on Mental Health Relationships: Scoping Review on Historically Used Methodologies to Analyze Adult Populations K. Leontjevaite et al. 10.3390/air2030016
76. Performance validation and calibration conditions for novel dynamic baseline tracking air sensors in long-term field monitoring H. Mei et al. 10.5194/amt-18-1771-2025
77. Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO2 monitoring in urban areas E. Arzoumanian et al. 10.5194/amt-12-2665-2019
78. The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors J. Kim et al. 10.5194/amt-11-1937-2018
79. Bias in PM2.5 measurements using collocated reference-grade and optical instruments M. Kushwaha et al. 10.1007/s10661-022-10293-4
80. Identification of technical problems affecting performance of DustTrak DRX aerosol monitors I. Rivas et al. 10.1016/j.scitotenv.2017.01.129
81. Performance of low-cost monitors to assess household air pollution A. Curto et al. 10.1016/j.envres.2018.01.024
82. 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
83. End-user perspective of low-cost sensors for outdoor air pollution monitoring A. Rai et al. 10.1016/j.scitotenv.2017.06.266
84. Response of consumer and research grade indoor air quality monitors to residential sources of fine particles B. Singer & W. Delp 10.1111/ina.12463
85. Improving accuracy of air pollution exposure measurements: Statistical correction of a municipal low-cost airborne particulate matter sensor network E. Considine et al. 10.1016/j.envpol.2020.115833
86. Measurements of PM2.5 with PurpleAir under atmospheric conditions K. Ardon-Dryer et al. 10.5194/amt-13-5441-2020
87. Identifying optimal co-location calibration periods for low-cost sensors M. Levy Zamora et al. 10.5194/amt-16-169-2023
88. Evaluation of low-cost sensors for quantitative personal exposure monitoring S. Mahajan & P. Kumar 10.1016/j.scs.2020.102076
89. Mobile phones as monitors of personal exposure to air pollution: Is this the future? M. Nyarku et al. 10.1371/journal.pone.0193150
90. A new evaluation method of three different low-cost dust sensors using exponentially decaying particle concentrations K. Kang et al. 10.4491/eer.2020.501
91. Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors A. Cavaliere et al. 10.5194/amt-16-4723-2023
92. In Situ Calibration Algorithms for Environmental Sensor Networks: A Review F. Delaine et al. 10.1109/JSEN.2019.2910317
93. Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States W. Jiao et al. 10.5194/amt-9-5281-2016
94. Field evaluation of low-cost particulate matter sensors in high- and low-concentration environments T. Zheng et al. 10.5194/amt-11-4823-2018
95. Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment N. Johnson et al. 10.1016/j.atmosenv.2018.04.019
96. Assessment of seasonal variation in PM2.5 concentration using low-cost sensors: A case study of Jaipur city, India S. Chaudhry et al. 10.1016/j.atmosenv.2025.121067
97. Portable, Ambient PM2.5 Sensor for Human and/or Animal Exposure Studies T. Cao & J. Thompson 10.1080/00032719.2016.1190736
98. Outlier detection and gap filling methodologies for low-cost air quality measurements T. Ottosen & P. Kumar 10.1039/C8EM00593A
99. 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
100. 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
101. Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research J. Huang et al. 10.3390/s22062381
102. Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors A. Samad et al. 10.3390/s24030945
103. Exploring the applicability and limitations of selected optical scattering instruments for PM mass measurement J. Zhang et al. 10.5194/amt-11-2995-2018
104. 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. 10.5194/amt-11-4883-2018
105. 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
106. Evaluating the feasibility of a personal particle exposure monitor in outdoor and indoor microenvironments in Shanghai, China K. Wang et al. 10.1080/09603123.2018.1533531
107. Assessment of health impact of the surface ozone on a population residing at Agadir city (Morocco) using the AirQ+ model Y. Bouchriti et al. 10.1051/e3sconf/202336402003
108. Node-to-node field calibration of wireless distributed air pollution sensor network F. Kizel et al. 10.1016/j.envpol.2017.09.042
109. Garbage in, gospel out? – Air quality assessment in the UK planning system A. Mills & S. Peckham 10.1016/j.envsci.2019.06.010
110. Evaluation of low-cost optical particle counters for monitoring individual indoor aerosol sources P. Salimifard et al. 10.1080/02786826.2019.1697423
111. A versatile low-cost sensing device for assessing PM2.5 spatiotemporal variation and quantifying source contribution S. Lung et al. 10.1016/j.scitotenv.2020.137145
112. Calibration of Portable Particulate Matter–Monitoring Device using Web Query and Machine Learning B. Loh & G. Choi 10.1016/j.shaw.2019.08.002
113. Low-Cost Indoor Sensor Deployment for Predicting PM2.5 Exposure S. Tsameret et al. 10.1021/acsestair.3c00105
114. Mathematical Modelling and Parameter Optimization of Fine Particle Sensors based on Laser Light Scattering W. Shao et al. 10.1109/JSEN.2017.2747083
115. Representativeness of the particulate matter pollution assessed by an official monitoring station of air quality in Santiago, Chile: projection to human health M. Préndez et al. 10.1007/s10653-022-01390-x
116. Performance evaluation of ozone and particulate matter sensors H. DeWitt et al. 10.1080/10962247.2020.1713921
117. 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
118. 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
119. Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality A. Samad et al. 10.3390/s21030804
120. 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
121. Assessment of particulate matter (PM10, PM5, PM2.5, and PM1) concentrations at significant intersections in Douala-Cameroon city using low-cost sensors Y. Ngangmo & C. Adiang 10.1007/s12517-025-12239-9
122. Assessing the accuracy of low-cost optical particle sensors using a physics-based approach D. Hagan & J. Kroll 10.5194/amt-13-6343-2020
123. 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
124. 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
125. 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
126. A Survey on Sensor Calibration in Air Pollution Monitoring Deployments B. Maag et al. 10.1109/JIOT.2018.2853660
127. 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
128. 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
129. In-car particulate matter exposure across ten global cities P. Kumar et al. 10.1016/j.scitotenv.2020.141395
130. Data Verification Tools for Minimizing Management Costs of Dense Air-Quality Monitoring Networks G. Miskell et al. 10.1021/acs.est.5b04421
131. Factors influencing particle resuspension and dispersion: An experimental study using test-track measurements B. Obeid et al. 10.1016/j.trd.2024.104321
132. New Methods for Personal Exposure Monitoring for Airborne Particles K. Koehler & T. Peters 10.1007/s40572-015-0070-z
133. Evaluation of two low-cost PM monitors under different laboratory and indoor conditions R. He et al. 10.1080/02786826.2020.1851649
134. 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
135. Ambient and laboratory evaluation of a low-cost particulate matter sensor K. Kelly et al. 10.1016/j.envpol.2016.12.039
136. Anti-perspirant deodorant particulate matter temporal concentrations during home usage V. Seller et al. 10.1016/j.buildenv.2021.107738
137. Low-Cost Particulate Matter Mass Sensors: Review of the Status, Challenges, and Opportunities for Single-Instrument and Network Calibration J. Zhang et al. 10.1021/acssensors.4c03293
138. The Effects of Climate Therapy on Cardiorespiratory Fitness and Exercise-Induced Bronchoconstriction in Children with Asthma C. De Pieri et al. 10.3390/atmos12111486
139. 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
140. Annual NO2 as a Predictor of Hourly NO2 Variability: Do Defra UK’s Heuristics Make Sense? A. Mills & S. Peckham 10.3390/atmos12030385
141. 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
142. A fast calibration algorithm for Non-Dispersive Infrared single channel carbon dioxide sensor based on deep learning K. Mao et al. 10.1016/j.comcom.2021.08.003
143. 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
144. Calibrating low-cost sensors for ambient air monitoring: Techniques, trends, and challenges L. Liang 10.1016/j.envres.2021.111163
145. Monitoring of Indoor Air Quality in a Classroom Combining a Low-Cost Sensor System and Machine Learning I. Apostolopoulos et al. 10.3390/chemosensors13040148
146. 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
147. Evaluation of a low-cost dryer for a low-cost optical particle counter M. Chacón-Mateos et al. 10.5194/amt-15-7395-2022
148. Compositional Analysis of Adsorbed Organic Aerosol on a Microresonator Mass Sensor A. Zielinski et al. 10.1007/s41810-018-0029-1
149. Understanding and revealing the intrinsic impacts of the COVID-19 lockdown on air quality and public health in North China using machine learning Y. Lv et al. 10.1016/j.scitotenv.2022.159339
150. Calibrating networks of low-cost air quality sensors P. deSouza et al. 10.5194/amt-15-6309-2022
151. 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
152. Improving data reliability: A quality control practice for low-cost PM2.5 sensor network X. Qiao et al. 10.1016/j.scitotenv.2021.146381
153. 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
154. Real-time particle monitoring of pesticide drift from an axial fan airblast orchard sprayer M. Blanco et al. 10.1038/s41370-018-0090-5
155. 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
156. Investigation of Low-Cost and Optical Particulate Matter Sensors for Ambient Monitoring M. Rogulski & A. Badyda 10.3390/atmos11101040
157. Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. 10.1039/D2EA00085G
158. Quantifying the impacts of PM2.5 constituents and relative humidity on visibility impairment in a suburban area of eastern Asia using long-term in-situ measurements Y. Ting et al. 10.1016/j.scitotenv.2021.151759
159. 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
160. 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
161. 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
162. 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
163. Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication J. Wang et al. 10.1016/j.envint.2023.107934
164. Evaluating Indoor Air Quality in Residential Environments: A Study of PM2.5 and CO2 Dynamics Using Low-Cost Sensors K. Shah et al. 10.3390/environments11110237
165. Measuring Micrometers of Matter and Inventing Indices: Entangling Social Perception within Discrete and Continuous Measurements of Air Quality E. Schmitt 10.3390/socsci8020048
166. Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado S. Feinberg et al. 10.5194/amt-11-4605-2018
167. 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
168. Evaluation of Low-cost Air Quality Sensor Calibration Models K. Aula et al. 10.1145/3512889
169. Efficient calibration of cost-efficient particulate matter sensors using machine learning and time-series alignment S. Koziel et al. 10.1016/j.knosys.2024.111879
170. Development and Performance Evaluation of a Mixed-Sensor System for Fine Particles and Road Traffic Noise C. Wu et al. 10.2139/ssrn.4020749
171. Particulate Matter Sensors Mounted on a Robot for Environmental Aerosol Measurements A. Cashikar et al. 10.1061/(ASCE)EE.1943-7870.0001569
172. Low-Cost Air Quality Sensing towards Smart Homes H. Omidvarborna et al. 10.3390/atmos12040453
173. Review of the Performance of Low-Cost Sensors for Air Quality Monitoring F. Karagulian et al. 10.3390/atmos10090506
174. 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
175. 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
176. 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
177. 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
178. Smart homes and the control of indoor air quality A. Schieweck et al. 10.1016/j.rser.2018.05.057
179. Flow rate-independent electrical aerosol sensor A. Rostedt & J. Keskinen 10.1080/02786826.2018.1498586
180. 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
181. Enhanced performance of pocket-sized nanoparticle exposure monitor for healthy indoor environment H. Wasisto et al. 10.1016/j.buildenv.2015.09.013
182. FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor M. Budde et al. 10.3390/s19030749
183. Evaluation of new low-cost particle monitors for PM2.5 concentrations measurements N. Zikova et al. 10.1016/j.jaerosci.2016.11.010
184. 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
185. Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise C. Borrego et al. 10.1016/j.atmosenv.2016.09.050
186. Development and evaluation of a palm-sized optical PM2.5sensor T. Nakayama et al. 10.1080/02786826.2017.1375078
187. 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
188. 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
189. Performance calibration of low-cost and portable particular matter (PM) sensors D. Liu et al. 10.1016/j.jaerosci.2017.05.011
190. Integrating low-cost air quality sensor networks with fixed and satellite monitoring systems to study ground-level PM2.5 J. Li et al. 10.1016/j.atmosenv.2020.117293
191. Real-Time Monitoring of Spray Drift from Three Different Orchard Sprayers M. Blanco et al. 10.1016/j.chemosphere.2019.01.092
192. Hourly land-use regression models based on low-cost PM monitor data M. Masiol et al. 10.1016/j.envres.2018.06.052
193. Measurement of PM10 concentration using hybrid cyclone separator and particle counter R. Purbakawaca et al. 10.1088/1755-1315/622/1/012025
194. The Exposome in the Era of the Quantified Self X. Zhang et al. 10.1146/annurev-biodatasci-012721-122807
195. Effect of relative humidity on the performance of five cost-effective PM sensors P. Wang et al. 10.1080/02786826.2021.1910136
196. Improving Urban Air Quality Monitoring in Delhi, India: Reflections on Low-Cost Air Quality Sensors (LCAQS) and Participatory Engagement A. Kumar & S. Chaudhuri 10.1177/09754253221122752
197. Aerosol Health Effects from Molecular to Global Scales M. Shiraiwa et al. 10.1021/acs.est.7b04417
198. Laboratory Evaluation of the Shinyei PPD42NS Low-Cost Particulate Matter Sensor E. Austin et al. 10.1371/journal.pone.0137789
199. 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
200. Personal exposure monitoring of PM 2.5 in indoor and outdoor microenvironments S. Steinle et al. 10.1016/j.scitotenv.2014.12.003
201. Inter-comparison of low-cost sensors for measuring the mass concentration of occupational aerosols S. Sousan et al. 10.1080/02786826.2016.1162901
202. Crowd-sourced air quality studies: A review of the literature & portable sensors J. Thompson 10.1016/j.teac.2016.06.001
203. Biomass-fuelled improved cookstove intervention to prevent household air pollution in Northwest Ethiopia: a cluster randomized controlled trial M. Adane et al. 10.1186/s12199-020-00923-z
204. Laboratory Evaluation and Calibration of Three Low-Cost Particle Sensors for Particulate Matter Measurement Y. Wang et al. 10.1080/02786826.2015.1100710
205. The Silver Lining of COVID‐19: Estimation of Short‐Term Health Impacts Due to Lockdown in the Yangtze River Delta Region, China L. Huang et al. 10.1029/2020GH000272
206. A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China M. Gao et al. 10.1016/j.envpol.2015.01.013