103 citations as recorded by crossref.

1. Digital Healthcare for Airway Diseases from Personal Environmental Exposure Y. Park et al. 10.3349/ymj.2022.63.S1
2. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. 10.3390/s22249669
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4. Project FRESH Air: A Community Engagement Project About Health and Climate S. Holler et al. 10.1119/5.0136945
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7. Environmental Influences on Academic Proficiency S. Grineski et al. 10.1007/s40471-023-00324-0
8. Combining Regulatory Instruments and Low-Cost Sensors to Quantify the Effects of 2020 California Wildfires on PM2.5 in San Joaquin Valley F. Enayati Ahangar et al. 10.3390/fire5030064
9. Mobile Observations of Ozone and Aerosols in Alabama: Southeastern US Summer Pollution and Coastal Variability S. Kuang et al. 10.1029/2023JD039514
10. Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. 10.5194/amt-17-1051-2024
11. Evaluation of Cairpol and Aeroqual Air Sensors in Biomass Burning Plumes A. Whitehill et al. 10.3390/atmos13060877
12. Air quality and health impacts of the 2020 wildfires in California M. Carreras-Sospedra et al. 10.1186/s42408-023-00234-y
13. Evaluating the PurpleAir monitor as an aerosol light scattering instrument J. Ouimette et al. 10.5194/amt-15-655-2022
14. An analysis of degradation in low-cost particulate matter sensors P. deSouza et al. 10.1039/D2EA00142J
15. Impacts of distinct travel behaviors on potential air pollution exposure measurement error Y. Lu & R. Habre 10.1016/j.atmosenv.2023.119820
16. A new approach for determining optimal placement of PM2.5air quality sensors: case study for the contiguous United States M. Kelp et al. 10.1088/1748-9326/ac548f
17. Data-Driven Machine Learning Calibration Propagation in A Hybrid Sensor Network for Air Quality Monitoring I. Vajs et al. 10.3390/s23052815
18. Technical note: Identifying a performance change in the Plantower PMS 5003 particulate matter sensor N. Searle et al. 10.1016/j.jaerosci.2023.106256
19. Leveraging crowd-sourced environmental data to assess air pollution exposure disparity: A case of Los Angeles County T. Lu et al. 10.1016/j.jag.2023.103599
20. Spatialized PM2.5 during COVID-19 pandemic in Brazil’s most populous southern city: implications for post-pandemic era G. da Costa et al. 10.1007/s10653-023-01809-z
21. Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information E. Considine et al. 10.1021/acs.est.2c06626
22. Improvement of Surface PM2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission C. Li et al. 10.1021/acsestair.3c00008
23. Air Pollution and Home Blood Pressure: The 2021 Athens Wildfires E. Andreadis et al. 10.1007/s40292-022-00547-0
24. A Novel AI Framework for PM Pollution Prediction Applied to a Greek Port City F. Anagnostopoulos et al. 10.3390/atmos14091413
25. Long-term evaluation of a low-cost air sensor network for monitoring indoor and outdoor air quality at the community scale R. Connolly et al. 10.1016/j.scitotenv.2021.150797
26. Seasonal Field Calibration of Low-Cost PM2.5 Sensors in Different Locations with Different Sources in Thailand R. Dejchanchaiwong et al. 10.3390/atmos14030496
27. 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
28. Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States D. Zhang et al. 10.1021/acs.est.3c05143
29. A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3 S. Raffuse et al. 10.5194/gmd-17-381-2024
30. Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution E. Molina Rueda et al. 10.1021/acs.estlett.3c00030
31. Evaluation methods for low-cost particulate matter sensors J. Bean 10.5194/amt-14-7369-2021
32. Developing high-resolution PM2.5 exposure models by integrating low-cost sensors, automated machine learning, and big human mobility data M. Yu et al. 10.3389/fenvs.2023.1223160
33. Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India M. Campmier et al. 10.5194/amt-16-4357-2023
34. Association between PM2.5 and respiratory hospitalization in Rio Branco, Brazil: Demonstrating the potential of low-cost air quality sensor for epidemiologic research. E. Coker et al. 10.1016/j.envres.2022.113738
35. Sens-BERT: A BERT-Based Approach for Enabling Transferability and Re-Calibration of Calibration Models for Low-Cost Sensors Under Reference Measurements Scarcity M. Narayana et al. 10.1109/JSEN.2024.3362962
36. 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
37. Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil P. Connerton et al. 10.3390/atmos14121796
38. Investigating the Sensitivity of Low-Cost Sensors in Measuring Particle Number Concentrations across Diverse Atmospheric Conditions in Greece and Spain G. Kosmopoulos et al. 10.3390/s23146541
39. 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
40. Development and evaluation of correction models for a low-cost fine particulate matter monitor B. Nilson et al. 10.5194/amt-15-3315-2022
41. Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science A. Collier-Oxandale et al. 10.3390/s22072543
42. The impact of coal trains on PM2.5 in the San Francisco Bay area B. Ostro et al. 10.1007/s11869-023-01333-0
43. Performance of Vehicle Add-on Mobile Monitoring System PM2.5 measurements during wildland fire episodes A. Bittner et al. 10.1039/D3EA00170A
44. Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter M. Aix et al. 10.1016/j.scitotenv.2023.164063
45. Evaluation of calibration approaches for indoor deployments of PurpleAir monitors K. Koehler et al. 10.1016/j.atmosenv.2023.119944
46. 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
47. The value of adding black carbon to community monitoring of particulate matter R. Sugrue et al. 10.1016/j.atmosenv.2024.120434
48. Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. 10.1039/D2EA00085G
49. Field and laboratory evaluation of PurpleAir low-cost aerosol sensors in monitoring indoor airborne particles S. Park et al. 10.1016/j.buildenv.2023.110127
50. A national crowdsourced network of low-cost fine particulate matter and aerosol optical depth monitors: results from the 2021 wildfire season in the United States E. Wendt et al. 10.1039/D3EA00086A
51. Forecasting Air Quality in Kiev During 2022 Military Conflict Using Sentinel 5P and Optimized Machine Learning M. Mehrabi et al. 10.1109/TGRS.2023.3292006
52. Characterizing the effects of structural fires on fine particulate matter with a dense sensing network A. Anyachebelu et al. 10.1038/s41598-023-38392-3
53. Comparison of outlier detection approaches in a Smart Cities sensor data context S. Zafeirelli & D. Kavroudakis 10.2478/ijssis-2024-0004
54. Intra- and inter-city variability of PM2.5 concentrations in Greece as determined with a low-cost sensor network K. Dimitriou et al. 10.1016/j.atmosenv.2023.119713
55. Five Years of Accurate PM2.5 Measurements Demonstrate the Value of Low-Cost PurpleAir Monitors in Areas Affected by Woodsmoke D. Robinson et al. 10.3390/ijerph20237127
56. Laboratory evaluation of the Alphasense OPC-N3, and the Plantower PMS5003 and PMS6003 sensors K. Kaur & K. Kelly 10.1016/j.jaerosci.2023.106181
57. Spectral analysis approach for assessing the accuracy of low-cost air quality sensor network data V. Kumar et al. 10.5194/amt-16-5415-2023
58. Urban fraction influence on local nocturnal cooling rates from low-cost sensors in Dallas-Fort Worth B. McBroom et al. 10.1016/j.uclim.2024.101823
59. High spatio-temporal resolution predictions of PM2.5 using low-cost sensor data A. Kar et al. 10.1016/j.atmosenv.2024.120486
60. Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions L. Liang et al. 10.1016/j.envpol.2023.121832
61. Evaluating data quality for blended data using a data quality framework J. Parker et al. 10.3233/SJI-230125
62. HazeL: A Low-Cost Learning Platform for Aerosol Measurements G. de Vera et al. 10.1021/acs.jchemed.2c00535
63. An evaluation of the U.S. EPA's correction equation for PurpleAir sensor data in smoke, dust, and wintertime urban pollution events D. Jaffe et al. 10.5194/amt-16-1311-2023
64. Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California Y. Liang et al. 10.1073/pnas.2106478118
65. Effects of Air Pollutants from Wildfires on Downwind Ecosystems: Observations, Knowledge Gaps, and Questions for Assessing Risk M. Paul et al. 10.1021/acs.est.2c09061
66. Spatial Variation of PM2.5 Indoors and Outdoors: Results from 261 Regulatory Monitors Compared to 14,000 Low-Cost Monitors in Three Western States over 4.7 Years L. Wallace & T. Zhao 10.3390/s23094387
67. Temporal trends in ambient fine particulate matter and the impacts of COVID-19 on this pollutant in Grenada, West Indies N. Dirienzo et al. 10.1080/10962247.2022.2126555
68. Outside in: the relationship between indoor and outdoor particulate air quality during wildfire smoke events in western US cities K. O’Dell et al. 10.1088/2752-5309/ac7d69
69. 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
70. Short-Term Exposure to Wildfire Smoke and PM2.5 and Cognitive Performance in a Brain-Training Game: A Longitudinal Study of U.S. Adults S. Cleland et al. 10.1289/EHP10498
71. Design and testing of a low-cost sensor and sampling platform for indoor air quality J. Tryner et al. 10.1016/j.buildenv.2021.108398
72. Calibrating networks of low-cost air quality sensors P. deSouza et al. 10.5194/amt-15-6309-2022
73. A dynamic spatial filtering approach to mitigate underestimation bias in field calibrated low-cost sensor air pollution data C. Heffernan et al. 10.1214/23-AOAS1751
74. Disparate air pollution reductions during California’s COVID-19 economic shutdown R. Bluhm et al. 10.1038/s41893-022-00856-1
75. Long-Term Characterization of Indoor Air Quality at a Research Area Building: Comparing Reference Instruments and Low-Cost Sensors M. Calvello et al. 10.1155/2024/8799498
76. Fine particulate matter infiltration at Western Montana residences during wildfire season E. Walker et al. 10.1016/j.scitotenv.2023.165238
77. Evaluation of a low-cost dryer for a low-cost optical particle counter M. Chacón-Mateos et al. 10.5194/amt-15-7395-2022
78. Fundamentals of low-cost aerosol sensor design and operation J. Ouimette et al. 10.1080/02786826.2023.2285935
79. 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
80. Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast J. Bi et al. 10.1021/acs.est.1c05578
81. Performance evaluation of MOMA (MOment MAtching) – a remote network calibration technique for PM2.5 and PM10 sensors L. Weissert et al. 10.5194/amt-16-4709-2023
82. Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US M. Childs et al. 10.1021/acs.est.2c02934
83. Measurements of traffic-related air pollution at a U.S.–Mexico port of entry and its impacts on nearby community W. Li et al. 10.1007/s44274-023-00010-4
84. Temporal Characteristics and Sources of PM2.5 in Porto Velho of Amazon Region in Brazil from 2020 to 2022 Y. Jang & G. Jung 10.3390/su151814012
85. Education for Environmental Justice: The Fordham Regional Environmental Sensor for Healthy Air S. Holler et al. 10.3390/socsci12120681
86. 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
87. Performance and Deployment of Low-Cost Particle Sensor Units to Monitor Biomass Burning Events and Their Application in an Educational Initiative F. Reisen et al. 10.3390/s21217206
88. Outdoor and indoor fine particulate matter at skilled nursing facilities in the western United States during wildfire and non‐wildfire seasons L. Montrose et al. 10.1111/ina.13060
89. AirSensor v1.0: Enhancements to the open-source R package to enable deep understanding of the long-term performance and reliability of PurpleAir sensors A. Collier-Oxandale et al. 10.1016/j.envsoft.2021.105256
90. Indoor Air Quality Considerations for Laboratory Animals in Wildfire-Impacted Regions—A Pilot Study A. Schuller et al. 10.3390/toxics10070387
91. MitH: A framework for Mitigating Hygroscopicity in low-cost PM sensors M. Casari & L. Po 10.1016/j.envsoft.2024.105955
92. Data‐Driven Placement of PM2.5 Air Quality Sensors in the United States: An Approach to Target Urban Environmental Injustice M. Kelp et al. 10.1029/2023GH000834
93. EEATC: A Novel Calibration Approach for Low-Cost Sensors M. Narayana et al. 10.1109/JSEN.2023.3304366
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95. Applying machine learning for large scale field calibration of low‐cost PM2.5 and PM10 air pollution sensors P. Adong et al. 10.1002/ail2.76
96. Assessing residential PM 2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors D. Lunderberg et al. 10.1073/pnas.2308832120
97. Wildfire Smoke and Private Provision of Public Air-Quality Monitoring M. Coury et al. 10.2139/ssrn.4783702
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99. Indoor-Generated PM2.5 During COVID-19 Shutdowns Across California: Application of the PurpleAir Indoor–Outdoor Low-Cost Sensor Network A. Mousavi & J. Wu 10.1021/acs.est.0c06937
100. 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
101. Indoor contribution to PM 2 .5 exposure using all PurpleAir sites in Washington, Oregon, and California L. Wallace et al. 10.1111/ina.13105
102. High-Resolution Assessment of Air Quality in Urban Areas—A Business Model Perspective K. Schäfer et al. 10.3390/atmos12050595
103. Calibration of PurpleAir PA-I and PA-II Monitors Using Daily Mean PM2.5 Concentrations Measured in California, Washington, and Oregon from 2017 to 2021 L. Wallace et al. 10.3390/s22134741