95 citations as recorded by crossref.

1. Mobile Observations of Ozone and Aerosols in Alabama: Southeastern US Summer Pollution and Coastal Variability S. Kuang et al. https://doi.org/10.1029/2023JD039514
2. Assessing capability of Copernicus Atmosphere Monitoring Service to forecast PM2.5 and PM10 hourly concentrations in a European air quality hotspot G. Gualtieri et al. https://doi.org/10.1016/j.apr.2025.102567
3. Relationship between forest fires and air quality: a study of particulate matter in localities distant from the main emission source B. Warthon et al. https://doi.org/10.1590/1519-6984.290857
4. Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. https://doi.org/10.3390/s22249669
5. The Aerosol Research Observation Station (AEROS) K. Ardon-Dryer et al. https://doi.org/10.5194/amt-15-2345-2022
6. A Novel AI Framework for PM Pollution Prediction Applied to a Greek Port City F. Anagnostopoulos et al. https://doi.org/10.3390/atmos14091413
7. Design and Evaluation of a Calibration Chamber for Low-Cost PM Sensors–Part 2: Mass Concentration-Based Assessment V. Malyan et al. https://doi.org/10.1021/acsestair.6c00161
8. A framework for integrated energy and exposure to ambient pollution (iEnEx) assessment toward low-carbon, healthy, and equitable cities M. Ashayeri & N. Abbasabadi https://doi.org/10.1016/j.scs.2021.103647
9. Response of low-cost sensors to high PM 2.5 concentrations during bushfire and haze events X. Liu et al. https://doi.org/10.1080/02786826.2024.2368733
10. Performance Evaluation and Calibration of Low-Cost PurpleAir PM2.5 Sensors in South Asian Conditions: Dhaka, Bangladesh C. Hossain et al. https://doi.org/10.1021/acsestair.5c00105
11. Improvement of Surface PM2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission C. Li et al. https://doi.org/10.1021/acsestair.3c00008
12. Application of an Ultra-Low-Cost Passive Sampler for Light-Absorbing Carbon in Mongolia B. Bekbulat et al. https://doi.org/10.3390/s23218977
13. Breathe Providence: an integrated approach to siting a low-cost air monitoring network G. Berg et al. https://doi.org/10.1088/1748-9326/ae2ca4
14. Retrieval of bulk hygroscopicity from PurpleAir PM2.5 sensor measurements J. Psotka et al. https://doi.org/10.5194/amt-18-3135-2025
15. Reliability Assessment of Low-Cost PM Sensors Under High Humidity and High PM Level Outdoor Conditions G. Kumar et al. https://doi.org/10.1109/JSEN.2025.3592796
16. Community-Based Measurements Reveal Unseen Differences during Air Pollution Episodes K. Kelly et al. https://doi.org/10.1021/acs.est.0c02341
17. COVID‐19 New Cases and Environmental Factors During Wet and Dry Seasons in West and Southern Africa G. Jenkins et al. https://doi.org/10.1029/2022GH000765
18. Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor K. Barkjohn et al. https://doi.org/10.5194/amt-14-4617-2021
19. Calibration Methods for Low-Cost Particulate Matter Sensors Considering Seasonal Variability J. Kang & K. Choi https://doi.org/10.3390/s24103023
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. https://doi.org/10.1007/s10653-023-01809-z
21. High-resolution urban air quality monitoring from citizen science data with echo-state transformer networks M. Bonas & S. Castruccio https://doi.org/10.1093/jrsssc/qlaf007
22. Evaluating PurpleAir Sensors: Do They Accurately Reflect Ambient Air Temperature? J. Tse & L. Liang https://doi.org/10.3390/s25103044
23. 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. https://doi.org/10.3390/fire5030064
24. Concentration, source identification and risk assessment of atmospheric polycyclic aromatic hydrocarbons at a kindergarten school in Kigali, Rwanda A. Omodieke & E. Kalisa https://doi.org/10.1016/j.cacint.2025.100260
25. Temporal variations of air pollutants and meteorological variables over a tropical station in Osogbo, Nigeria O. Omokungbe et al. https://doi.org/10.1007/s42452-025-08149-w
26. Developing high-resolution PM2.5 exposure models by integrating low-cost sensors, automated machine learning, and big human mobility data M. Yu et al. https://doi.org/10.3389/fenvs.2023.1223160
27. Assessing low-cost sensor for characterizing temporal variation of PM2.5 in Bandung, Indonesia S. Kurniawati et al. https://doi.org/10.1016/j.kjs.2024.100297
28. Practical Guidance for Using PurpleAir Particle Monitors for Indoor and Outdoor Measurements in Community Field Studies M. Wang et al. https://doi.org/10.1007/s44408-025-00048-4
29. Correction of PM2.5 underestimation in low-cost sensors under elevated dust loading using only sensor measurements K. Kaur et al. https://doi.org/10.5194/amt-19-1077-2026
30. Highly local sources and large spatial variations in PM2.5 across a city: evidence from a city-wide sensor network in Cork, Ireland R. Byrne et al. https://doi.org/10.1039/D2EA00177B
31. Indoor-Generated PM2.5 During COVID-19 Shutdowns Across California: Application of the PurpleAir Indoor–Outdoor Low-Cost Sensor Network A. Mousavi & J. Wu https://doi.org/10.1021/acs.est.0c06937
32. Development and evaluation of correction models for a low-cost fine particulate matter monitor B. Nilson et al. https://doi.org/10.5194/amt-15-3315-2022
33. Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018–2020: Implications for Environmental Justice in the Context of Climate Change S. Masri et al. https://doi.org/10.3390/cli10100145
34. Assessing urban mortality from wildfires with a citizen science network P. Shen et al. https://doi.org/10.1007/s11869-021-01072-0
35. Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning models B. Prajapati et al. https://doi.org/10.1016/j.jaerosci.2023.106284
36. The Role of Meteorological Variables and Aerosols in the Transmission of COVID‐19 During Harmattan Season S. Ogunjo et al. https://doi.org/10.1029/2021GH000521
37. Polluting under the Radar: Emissions, Inequality, and Concrete Batch Plants in Houston N. Zirogiannis et al. https://doi.org/10.1021/acs.est.3c04412
38. Evaluation of calibration approaches for indoor deployments of PurpleAir monitors K. Koehler et al. https://doi.org/10.1016/j.atmosenv.2023.119944
39. Four-year community-wide PM2.5 exposure characterization using a low-cost sensor network in a rural valley influenced by residential wood smoke N. Traviss et al. https://doi.org/10.1016/j.atmosenv.2025.121398
40. Modeling and Characterization of Fine Particulate Matter Dynamics in Bujumbura Using Low-Cost Sensors E. Ndamuzi et al. https://doi.org/10.4236/jamp.2024.121020
41. Poorly quantified trends in ammonium nitrate remain critical to understand future urban aerosol control strategies R. Ward et al. https://doi.org/10.1126/sciadv.adt8957
42. Analysis of sources and sinks of indoor particulate matter reveals insights into the real-world efficacy of portable air cleaners in a randomized intervention trial S. Farhoodi et al. https://doi.org/10.1016/j.scitotenv.2025.180136
43. Calibration of SpatioTemporal forecasts from citizen science urban air pollution data with sparse recurrent neural networks M. Bonas & S. Castruccio https://doi.org/10.1214/22-AOAS1683
44. Field and laboratory evaluation of PurpleAir low-cost aerosol sensors in monitoring indoor airborne particles S. Park et al. https://doi.org/10.1016/j.buildenv.2023.110127
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. https://doi.org/10.3390/s23146541
46. 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. https://doi.org/10.3390/atmos15080879
47. Indoor air quality assessment using low-cost sensors, and impact of outdoors Y. Dahima & A. Vaishya https://doi.org/10.1007/s11869-025-01843-z
48. Evaluation and Correction of PurpleAir Temperature and Relative Humidity Measurements E. Couzo et al. https://doi.org/10.3390/atmos15040415
49. A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements M. Ahmed et al. https://doi.org/10.3390/atmos15121535
50. Dust Under the Radar: Rethinking How to Evaluate the Impacts of Dust Events on Air Quality in the United States K. Ardon‐Dryer et al. https://doi.org/10.1029/2023GH000953
51. Spectral analysis approach for assessing the accuracy of low-cost air quality sensor network data V. Kumar et al. https://doi.org/10.5194/amt-16-5415-2023
52. A Network of Field-Calibrated Low-Cost Sensor Measurements of PM2.5 in Lomé, Togo, Over One to Two Years G. Raheja et al. https://doi.org/10.1021/acsearthspacechem.1c00391
53. Assessing the contributions of outdoor and indoor sources to air quality in London homes of the SCAMP cohort T. Vu et al. https://doi.org/10.1016/j.buildenv.2022.109359
54. Health impacts of smoke exposure in South America: increased risk for populations in the Amazonian Indigenous territories E. Bonilla et al. https://doi.org/10.1088/2752-5309/acb22b
55. Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions M. Mathieu-Campbell et al. https://doi.org/10.5194/amt-17-6735-2024
56. A Review of Literature on the Usage of Low-Cost Sensors to Measure Particulate Matter A. Raysoni et al. https://doi.org/10.3390/earth4010009
57. Exposure to PM2.5 on Public Transport: Guidance for Field Measurements with Low-Cost Sensors K. Fameli et al. https://doi.org/10.3390/atmos15030330
58. Observationally constrained mass balance box model analysis of aerosol mitigation potential using fan powered filters S. Wang et al. https://doi.org/10.1088/2515-7620/ad1422
59. Unveiling the Limits of Existing Correction Factors for a Low-Cost PM2.5 Sensor in Cold Environments and Development of a Tailored Solution J. Leenose et al. https://doi.org/10.1021/acsestair.5c00018
60. Significance of sources and size distribution on calibration of low-cost particle sensors: Evidence from a field sampling campaign V. Malyan et al. https://doi.org/10.1016/j.jaerosci.2022.106114
61. A dynamic spatial filtering approach to mitigate underestimation bias in field calibrated low-cost sensor air pollution data C. Heffernan et al. https://doi.org/10.1214/23-AOAS1751
62. Effects of distance and number of $$\hbox {PM}_{2.5}$$ low-cost sensors on correction models V. Kumar et al. https://doi.org/10.1007/s41060-025-00852-6
63. Socioeconomic Disparities of Low-Cost Air Quality Sensors in California, 2017–2020 Y. Sun et al. https://doi.org/10.2105/AJPH.2021.306603
64. Site-Specific Calibration of Low-Cost Particulate Matter (PM) 2.5 Monitors in the United States: A Comparison of Industrial and Non-Industrial Communities J. Lee et al. https://doi.org/10.1007/s44408-026-00112-7
65. Information entropy tradeoffs for efficient uncertainty reduction in estimates of air pollution mortality M. Alifa et al. https://doi.org/10.1016/j.envres.2022.113587
66. Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy) G. Gualtieri et al. https://doi.org/10.3390/s24123946
67. Impact of 4th of July Fireworks on Spatiotemporal PM2.5 Concentrations in California Based on the PurpleAir Sensor Network: Implications for Policy and Environmental Justice A. Mousavi et al. https://doi.org/10.3390/ijerph18115735
68. Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California Y. Liang et al. https://doi.org/10.1073/pnas.2106478118
69. Temporal Characteristics and Sources of PM2.5 in Porto Velho of Amazon Region in Brazil from 2020 to 2022 Y. Jang & G. Jung https://doi.org/10.3390/su151814012
70. Vertical distribution analysis of PM2.5 concentration at urban highway intersections using low-cost sensors and unmanned aerial vehicles M. Zarei & B. Yeganeh https://doi.org/10.1016/j.uclim.2024.102243
71. Assessment of particulate matter and particle path trajectory analysis using a HYSPLIT model over Dire Dawa, Ethiopia T. Endale et al. https://doi.org/10.1007/s42452-024-05741-4
72. Seasonal effects in the application of the MOment MAtching (MOMA) remote calibration tool to outdoor PM2.5 air sensors L. Weissert et al. https://doi.org/10.5194/amt-18-3635-2025
73. 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. https://doi.org/10.3390/s21217206
74. Differences in Ozone and Particulate Matter Between Ground Level and 20 m Aloft are Frequent During Wintertime Surface‐Based Temperature Inversions in Fairbanks, Alaska M. Cesler‐Maloney et al. https://doi.org/10.1029/2021JD036215
75. Effectiveness of Air Filtration in Reducing PM2.5 Exposures at a School in a Community Heavily Impacted by Air Pollution M. Thompson et al. https://doi.org/10.3390/atmos15080901
76. Application of PM 2.5 low-cost sensors for indoor air quality compliance monitoring L. Morawska et al. https://doi.org/10.1080/02786826.2025.2457326
77. Race and Street-Level Firework Legalization as Primary Determinants of July 4th Air Pollution across Southern California S. Masri et al. https://doi.org/10.3390/atmos14020401
78. Correction of humidity and sensor aging effects in low-cost PM 2.5 light scattering sensors for improved measurement accuracy T. Kumpika et al. https://doi.org/10.1080/26395940.2026.2616098
79. Air quality monitoring and measurement in an urban airshed: Contextualizing datasets from the Detroit Michigan area from 1952 to 2020 B. O'Leary et al. https://doi.org/10.1016/j.scitotenv.2021.152120
80. Long-Term Assessment of PurpleAir Low-Cost Sensor for PM2.5 in California, USA Z. Farooqui et al. https://doi.org/10.3390/pollutants3040033
81. Spatio-temporal modeling of PM2.5 exposure in California's San Joaquin Valley using a community sensor network K. DeMarsh et al. https://doi.org/10.1016/j.jenvman.2026.129540
82. Measurements of traffic-related air pollution at a U.S.–Mexico port of entry and its impacts on nearby community W. Li et al. https://doi.org/10.1007/s44274-023-00010-4
83. Nano to micron-size combustion particles in smokers’ homes: Magnetic properties of tobacco and cigarette ashes M. Chaparro et al. https://doi.org/10.1016/j.envpol.2024.125276
84. A Comparative Analysis on Indoor and Outdoor PM2.5 and Their Hourly Associations with Acute Respiratory Inflammation Among College Students in Lhasa R. Qiao et al. https://doi.org/10.1021/acs.est.4c04304
85. Air Pollution Exposures of Bangladeshi Women from Rural and Peri-Urban Areas: Baseline Assessment for Behavior Change Communication Intervention as a Sustainable Approach E. Akhtar et al. https://doi.org/10.3390/su18073507
86. Polluting Under the Radar: Emissions, Inequality, and Concrete Batch Plants in Houston N. Zirogiannis et al. https://doi.org/10.2139/ssrn.4470152
87. Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experiment A. Caseiro et al. https://doi.org/10.1039/D4EA00086B
88. Quantifying impact of correlated predictors on low-cost sensor PM2.5 data using KZ filter V. Kumar et al. https://doi.org/10.3389/fams.2024.1368147
89. Concentration of black carbon and particulate matter air pollution and source apportionment in Rwanda, East Africa F. Ramiza & E. Kalisa https://doi.org/10.1088/2515-7620/ae5765
90. Temporal and spatial variation of PM2.5 in Antananarivo, the capital city of Madagascar M. Andriamamonjy et al. https://doi.org/10.1007/s44408-025-00039-5
91. Increasing co-occurrence of fine particulate matter and ground-level ozone extremes in the western United States D. Kalashnikov et al. https://doi.org/10.1126/sciadv.abi9386
92. 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. https://doi.org/10.1016/j.jaerosci.2021.105833
93. The present state of low-cost air quality sensors in Japan and their accuracy M. Lassalle https://doi.org/10.1080/00207233.2024.2358716
94. 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. https://doi.org/10.5194/amt-16-1311-2023
95. Significance of Meteorological Feature Selection and Seasonal Variation on Performance and Calibration of a Low-Cost Particle Sensor V. Kumar et al. https://doi.org/10.3390/atmos13040587