144 citations as recorded by crossref.

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2. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. 10.3390/s22249669
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8. Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas A. Jordan et al. 10.3389/fpubh.2024.1394678
9. Environmental Influences on Academic Proficiency S. Grineski et al. 10.1007/s40471-023-00324-0
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11. Mobile Observations of Ozone and Aerosols in Alabama: Southeastern US Summer Pollution and Coastal Variability S. Kuang et al. 10.1029/2023JD039514
12. Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. 10.5194/amt-17-1051-2024
13. Evaluation of Cairpol and Aeroqual Air Sensors in Biomass Burning Plumes A. Whitehill et al. 10.3390/atmos13060877
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15. Evaluating the PurpleAir monitor as an aerosol light scattering instrument J. Ouimette et al. 10.5194/amt-15-655-2022
16. Enhanced urban PM2.5 prediction: Applying quadtree division and time-series transformer with WRF-chem S. Zhang & M. Yu 10.1016/j.atmosenv.2024.120758
17. An analysis of degradation in low-cost particulate matter sensors P. deSouza et al. 10.1039/D2EA00142J
18. Impacts of distinct travel behaviors on potential air pollution exposure measurement error Y. Lu & R. Habre 10.1016/j.atmosenv.2023.119820
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20. Data-Driven Machine Learning Calibration Propagation in A Hybrid Sensor Network for Air Quality Monitoring I. Vajs et al. 10.3390/s23052815
21. Low-Cost Indoor Sensor Deployment for Predicting PM2.5 Exposure S. Tsameret et al. 10.1021/acsestair.3c00105
22. Technical note: Identifying a performance change in the Plantower PMS 5003 particulate matter sensor N. Searle et al. 10.1016/j.jaerosci.2023.106256
23. 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
24. 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
25. 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
26. Improvement of Surface PM2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission C. Li et al. 10.1021/acsestair.3c00008
27. Air Pollution and Home Blood Pressure: The 2021 Athens Wildfires E. Andreadis et al. 10.1007/s40292-022-00547-0
28. A Novel AI Framework for PM Pollution Prediction Applied to a Greek Port City F. Anagnostopoulos et al. 10.3390/atmos14091413
29. The dependence of PurpleAir sensors on particle size distribution and meteorology and their relationship to integrating nephelometers W. Malm et al. 10.1016/j.atmosenv.2024.120757
30. 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
31. Seasonal Field Calibration of Low-Cost PM2.5 Sensors in Different Locations with Different Sources in Thailand R. Dejchanchaiwong et al. 10.3390/atmos14030496
32. 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
33. Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States D. Zhang et al. 10.1021/acs.est.3c05143
34. 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
35. Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution E. Molina Rueda et al. 10.1021/acs.estlett.3c00030
36. Evaluation methods for low-cost particulate matter sensors J. Bean 10.5194/amt-14-7369-2021
37. 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
38. 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
39. 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
40. 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
41. Air Quality Monitoring with Low-Cost Sensors: A Record of the Increase of PM2.5 during Christmas and New Year’s Eve Celebrations in the City of Queretaro, Mexico A. Rodríguez-Trejo et al. 10.3390/atmos15080879
42. 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
43. Environmental Impact by Particulate Material and Meteorological Parameters on the Incidence of Positive Cases of COVID-19 During the First Year of the Pandemic in a High Andean City I. Miranda Hankgo et al. 10.1007/s41748-024-00477-y
44. Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil P. Connerton et al. 10.3390/atmos14121796
45. 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
46. Patterns and drivers of maternal personal exposure to PM2.5 in informal settlements in Nairobi, Kenya M. Johnson et al. 10.1039/D3EA00074E
47. 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
48. Disparities of compound exposure of particulate matter (PM2.5) and heat index using citywide monitoring networks Y. Ahn 10.1016/j.scs.2024.105626
49. Development and evaluation of correction models for a low-cost fine particulate matter monitor B. Nilson et al. 10.5194/amt-15-3315-2022
50. The Relationship between Indoor and Outdoor Fine Particulate Matter in a High-Rise Building in Chicago Monitored by PurpleAir Sensors M. Wenner et al. 10.3390/s24082493
51. Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science A. Collier-Oxandale et al. 10.3390/s22072543
52. The impact of coal trains on PM2.5 in the San Francisco Bay area B. Ostro et al. 10.1007/s11869-023-01333-0
53. Performance of Vehicle Add-on Mobile Monitoring System PM2.5 measurements during wildland fire episodes A. Bittner et al. 10.1039/D3EA00170A
54. Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter M. Aix et al. 10.1016/j.scitotenv.2023.164063
55. Evaluation of calibration approaches for indoor deployments of PurpleAir monitors K. Koehler et al. 10.1016/j.atmosenv.2023.119944
56. 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
57. Rapid response of stream dissolved phosphorus concentrations to wildfire smoke N. Fernandez et al. 10.1038/s43247-024-01732-w
58. 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
59. The value of adding black carbon to community monitoring of particulate matter R. Sugrue et al. 10.1016/j.atmosenv.2024.120434
60. Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. 10.1039/D2EA00085G
61. 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
62. 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
63. 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
64. 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
65. Characterizing indoor-outdoor PM2.5 concentrations using low-cost sensor measurements in residential homes in Dhaka, Bangladesh P. Saha et al. 10.1016/j.atmosenv.2024.120945
66. Comparison of outlier detection approaches in a Smart Cities sensor data context S. Zafeirelli & D. Kavroudakis 10.2478/ijssis-2024-0004
67. Wildfire smoke and private provision of public air-quality monitoring M. Coury et al. 10.1016/j.jeem.2024.103036
68. 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
69. 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
70. Laboratory evaluation of the Alphasense OPC-N3, and the Plantower PMS5003 and PMS6003 sensors K. Kaur & K. Kelly 10.1016/j.jaerosci.2023.106181
71. 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
72. Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions M. Mathieu-Campbell et al. 10.5194/amt-17-6735-2024
73. 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
74. 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
75. High spatio-temporal resolution predictions of PM2.5 using low-cost sensor data A. Kar et al. 10.1016/j.atmosenv.2024.120486
76. Application of quasi-empirical orthogonal functions to estimate wildfire impacts in northwestern Spain J. Gili et al. 10.1016/j.scitotenv.2024.172747
77. 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
78. Bag of DAGs: Inferring Directional Dependence in Spatiotemporal Processes B. Jin et al. 10.1214/24-BA1473
79. Evaluating data quality for blended data using a data quality framework J. Parker et al. 10.3233/SJI-230125
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81. HazeL: A Low-Cost Learning Platform for Aerosol Measurements G. de Vera et al. 10.1021/acs.jchemed.2c00535
82. Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy) G. Gualtieri et al. 10.3390/s24123946
83. Impacts of PM2.5 exposure near cement facilities on human health and years of life lost: A case study in Brazil P. Souza Zorzenão et al. 10.1016/j.jenvman.2024.122975
84. 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
85. Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California Y. Liang et al. 10.1073/pnas.2106478118
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87. Wildfire smoke reduces lake ecosystem metabolic rates unequally across a trophic gradient A. Smits et al. 10.1038/s43247-024-01404-9
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89. Data-driven analysis of heating and cooling base temperatures for buildings: Case studies in South Korea H. Kim et al. 10.1016/j.enbuild.2024.114709
90. 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
91. Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons T. Zhao et al. 10.1021/acsestair.4c00120
92. 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
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