155 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
3. The Aerosol Research Observation Station (AEROS) K. Ardon-Dryer et al. 10.5194/amt-15-2345-2022
4. Project FRESH Air: A Community Engagement Project About Health and Climate S. Holler et al. 10.1119/5.0136945
5. Can data reliability of low-cost sensor devices for indoor air particulate matter monitoring be improved? – An approach using machine learning H. Chojer et al. 10.1016/j.atmosenv.2022.119251
6. Field calibration of low-cost particulate matter sensors using artificial neural networks and affine response correction S. Koziel et al. 10.1016/j.measurement.2024.114529
7. Emissions and exposure to NOx, CO, CO2 and PM2.5 from a gas stove using reference and low-cost sensors D. Jaffe & A. Creekmore 10.1016/j.atmosenv.2024.120564
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. Performance evaluation of Atmotube PRO sensors for air quality measurements in an urban location A. Shittu et al. 10.5194/amt-18-817-2025
10. Environmental Influences on Academic Proficiency S. Grineski et al. 10.1007/s40471-023-00324-0
11. 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
12. Mobile Observations of Ozone and Aerosols in Alabama: Southeastern US Summer Pollution and Coastal Variability S. Kuang et al. 10.1029/2023JD039514
13. Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. 10.5194/amt-17-1051-2024
14. Evaluation of Cairpol and Aeroqual Air Sensors in Biomass Burning Plumes A. Whitehill et al. 10.3390/atmos13060877
15. Air quality and health impacts of the 2020 wildfires in California M. Carreras-Sospedra et al. 10.1186/s42408-023-00234-y
16. Evaluating the PurpleAir monitor as an aerosol light scattering instrument J. Ouimette et al. 10.5194/amt-15-655-2022
17. Improved daily PM 2.5 estimates in India reveal inequalities in recent enhancement of air quality A. Kawano et al. 10.1126/sciadv.adq1071
18. 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
19. An analysis of degradation in low-cost particulate matter sensors P. deSouza et al. 10.1039/D2EA00142J
20. Impacts of distinct travel behaviors on potential air pollution exposure measurement error Y. Lu & R. Habre 10.1016/j.atmosenv.2023.119820
21. 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
22. Data-Driven Machine Learning Calibration Propagation in A Hybrid Sensor Network for Air Quality Monitoring I. Vajs et al. 10.3390/s23052815
23. Low-Cost Indoor Sensor Deployment for Predicting PM2.5 Exposure S. Tsameret et al. 10.1021/acsestair.3c00105
24. Technical note: Identifying a performance change in the Plantower PMS 5003 particulate matter sensor N. Searle et al. 10.1016/j.jaerosci.2023.106256
25. 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
26. 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
27. 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
28. Improvement of Surface PM2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission C. Li et al. 10.1021/acsestair.3c00008
29. Air Pollution and Home Blood Pressure: The 2021 Athens Wildfires E. Andreadis et al. 10.1007/s40292-022-00547-0
30. A Novel AI Framework for PM Pollution Prediction Applied to a Greek Port City F. Anagnostopoulos et al. 10.3390/atmos14091413
31. 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
32. 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
33. Spatiotemporal modeling of long-term PM2.5 concentrations and population exposure in Greece, using machine learning and statistical methods A. Kakouri et al. 10.1016/j.scitotenv.2024.178113
34. Seasonal Field Calibration of Low-Cost PM2.5 Sensors in Different Locations with Different Sources in Thailand R. Dejchanchaiwong et al. 10.3390/atmos14030496
35. 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
36. Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States D. Zhang et al. 10.1021/acs.est.3c05143
37. 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
38. Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution E. Molina Rueda et al. 10.1021/acs.estlett.3c00030
39. Evaluation methods for low-cost particulate matter sensors J. Bean 10.5194/amt-14-7369-2021
40. 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
41. 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
42. 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
43. 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
44. 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
45. 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
46. 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
47. A low-cost IoT-based real-time pollution monitoring system using ESP8266 NodeMCU A. Gueye et al. 10.1177/00202940241306690
48. Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil P. Connerton et al. 10.3390/atmos14121796
49. 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
50. Patterns and drivers of maternal personal exposure to PM2.5 in informal settlements in Nairobi, Kenya M. Johnson et al. 10.1039/D3EA00074E
51. 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
52. Disparities of compound exposure of particulate matter (PM2.5) and heat index using citywide monitoring networks Y. Ahn 10.1016/j.scs.2024.105626
53. Development and evaluation of correction models for a low-cost fine particulate matter monitor B. Nilson et al. 10.5194/amt-15-3315-2022
54. 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
55. Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science A. Collier-Oxandale et al. 10.3390/s22072543
56. The impact of coal trains on PM2.5 in the San Francisco Bay area B. Ostro et al. 10.1007/s11869-023-01333-0
57. Performance of Vehicle Add-on Mobile Monitoring System PM2.5 measurements during wildland fire episodes A. Bittner et al. 10.1039/D3EA00170A
58. A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements M. Ahmed et al. 10.3390/atmos15121535
59. Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter M. Aix et al. 10.1016/j.scitotenv.2023.164063
60. Evaluation of calibration approaches for indoor deployments of PurpleAir monitors K. Koehler et al. 10.1016/j.atmosenv.2023.119944
61. 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
62. Rapid response of stream dissolved phosphorus concentrations to wildfire smoke N. Fernandez et al. 10.1038/s43247-024-01732-w
63. Rural Roads to cognitive Resilience (RRR): A prospective cohort study protocol L. Besser et al. 10.1371/journal.pone.0312660
64. 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
65. The value of adding black carbon to community monitoring of particulate matter R. Sugrue et al. 10.1016/j.atmosenv.2024.120434
66. Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. 10.1039/D2EA00085G
67. 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
68. 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
69. 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
70. 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
71. 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
72. Comparison of outlier detection approaches in a Smart Cities sensor data context S. Zafeirelli & D. Kavroudakis 10.2478/ijssis-2024-0004
73. Wildfire smoke and private provision of public air-quality monitoring M. Coury et al. 10.1016/j.jeem.2024.103036
74. 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
75. 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
76. Laboratory evaluation of the Alphasense OPC-N3, and the Plantower PMS5003 and PMS6003 sensors K. Kaur & K. Kelly 10.1016/j.jaerosci.2023.106181
77. 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
78. 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
79. 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
80. 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
81. High spatio-temporal resolution predictions of PM2.5 using low-cost sensor data A. Kar et al. 10.1016/j.atmosenv.2024.120486
82. Application of quasi-empirical orthogonal functions to estimate wildfire impacts in northwestern Spain J. Gili et al. 10.1016/j.scitotenv.2024.172747
83. 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
84. Bag of DAGs: Inferring Directional Dependence in Spatiotemporal Processes B. Jin et al. 10.1214/24-BA1473
85. Evaluating data quality for blended data using a data quality framework J. Parker et al. 10.3233/SJI-230125
86. Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data K. Barkjohn et al. 10.1021/acsestair.4c00125
87. TracMyAir smartphone application for modeling exposures to PM2.5 and ozone – Integration with air quality networks and location-activity sensors M. Breen et al. 10.1016/j.scitotenv.2024.178200
88. HazeL: A Low-Cost Learning Platform for Aerosol Measurements G. de Vera et al. 10.1021/acs.jchemed.2c00535
89. Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy) G. Gualtieri et al. 10.3390/s24123946
90. 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
91. 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
92. Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California Y. Liang et al. 10.1073/pnas.2106478118
93. 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
94. Wildfire smoke reduces lake ecosystem metabolic rates unequally across a trophic gradient A. Smits et al. 10.1038/s43247-024-01404-9
95. U.S. Ambient Air Monitoring Network Has Inadequate Coverage under New PM2.5 Standard Y. Wang et al. 10.1021/acs.estlett.4c00605
96. 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
97. 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
98. Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons T. Zhao et al. 10.1021/acsestair.4c00120
99. Enhancing accuracy of air quality sensors with machine learning to augment large-scale monitoring networks K. Ravindra et al. 10.1038/s41612-024-00833-9
100. 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
101. 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
102. 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
103. 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
104. 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
105. Calibrating networks of low-cost air quality sensors P. deSouza et al. 10.5194/amt-15-6309-2022
106. Dynamics of PM2.5 and network activity during extreme pollution events N. Bashan et al. 10.1038/s41612-024-00716-z
107. An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations K. Okorn & L. Iraci 10.5194/amt-17-6425-2024
108. 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
109. A novel low-cost sensors system for real-time multipollutant indoor air quality monitoring – Development and performance H. Chojer et al. 10.1016/j.buildenv.2024.112055
110. Disparate air pollution reductions during California’s COVID-19 economic shutdown R. Bluhm et al. 10.1038/s41893-022-00856-1
111. 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
112. Application and validation of a wearable monitor for assessing time- and location-resolved exposures to particulate matter in California’s Central Valley X. Li et al. 10.1080/02786826.2024.2415481
113. Fine particulate matter infiltration at Western Montana residences during wildfire season E. Walker et al. 10.1016/j.scitotenv.2023.165238
114. Evaluation of a low-cost dryer for a low-cost optical particle counter M. Chacón-Mateos et al. 10.5194/amt-15-7395-2022
115. Fundamentals of low-cost aerosol sensor design and operation J. Ouimette et al. 10.1080/02786826.2023.2285935
116. 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
117. Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast J. Bi et al. 10.1021/acs.est.1c05578
118. 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
119. Forecasting the Exceedances of PM2.5 in an Urban Area S. Logothetis et al. 10.3390/atmos15050594
120. Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experiment A. Caseiro et al. 10.1039/D4EA00086B
121. Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US M. Childs et al. 10.1021/acs.est.2c02934
122. 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
123. Indoor and ambient influences on PM2.5 exposure and well-being for a rail impacted community and implications for personal protections I. Torres et al. 10.1088/1748-9326/ad90f5
124. 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
125. Education for Environmental Justice: The Fordham Regional Environmental Sensor for Healthy Air S. Holler et al. 10.3390/socsci12120681
126. Assessing low-cost sensor for characterizing temporal variation of PM2.5 in Bandung, Indonesia S. Kurniawati et al. 10.1016/j.kjs.2024.100297
127. Seasonal Inter-comparison of Fine Particulate Matter (PM<sub>2.5</sub>) Over Addis Ababa, Ethiopia T. Redi 10.11648/j.ijema.20241206.11
128. 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
129. 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
130. Behavioral Responses to Wildfire Smoke: A Case Study in Western Montana T. Stewart et al. 10.1007/s10900-024-01390-1
131. 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
132. 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
133. High-resolution urban air pollution mapping J. Apte & C. Manchanda 10.1126/science.adq3678
134. Indoor Air Quality Considerations for Laboratory Animals in Wildfire-Impacted Regions—A Pilot Study A. Schuller et al. 10.3390/toxics10070387
135. Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor K. Barkjohn et al. 10.5194/amt-14-4617-2021
136. Ambient smoke exposure and indoor air quality in eastern Massachusetts during the 2023 wildfire season B. Sun et al. 10.1080/10962247.2024.2409790
137. MitH: A framework for Mitigating Hygroscopicity in low-cost PM sensors M. Casari & L. Po 10.1016/j.envsoft.2024.105955
138. Racial and Ethnic Disparities in Regulatory Air Quality Monitor Locations in the US B. Kelly et al. 10.1001/jamanetworkopen.2024.49005
139. 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
140. EEATC: A Novel Calibration Approach for Low-Cost Sensors M. Narayana et al. 10.1109/JSEN.2023.3304366
141. Application of PM 2.5 low-cost sensors for indoor air quality compliance monitoring L. Morawska et al. 10.1080/02786826.2025.2457326
142. Low-cost PM2.5 sensors can help identify driving factors of poor air quality and benefit communities T. Keyes et al. 10.1016/j.heliyon.2023.e19876
143. 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. 10.1021/acs.est.4c04304
144. Source-resolved black carbon and PM2.5 exposures during wildfires and prescribed burns J. Gili et al. 10.1016/j.envpol.2025.125660
145. 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
146. Applying machine learning for large scale field calibration of low‐cost PM2.5and PM10air pollution sensors P. Adong et al. 10.1002/ail2.76
147. Spatial variability of dust concentration and deposition around an industrial port in South Africa emphasises the complexity of sources and transport H. Vos et al. 10.1007/s11869-024-01581-8
148. Assessing residential PM 2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors D. Lunderberg et al. 10.1073/pnas.2308832120
149. Wildfire Smoke and Private Provision of Public Air-Quality Monitoring M. Coury et al. 10.2139/ssrn.4783702
150. Quantifying impact of correlated predictors on low-cost sensor PM2.5 data using KZ filter V. Kumar et al. 10.3389/fams.2024.1368147
151. City-Scale Air Quality Network of Low-Cost Sensors A. Masic 10.3390/atmos15070798
152. Evaluating the Performance of Low-Cost PM2.5Sensors in Mobile Settings P. deSouza et al. 10.1021/acs.est.3c04843
153. 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
154. Indoor contribution to PM 2 .5 exposure using all PurpleAir sites in Washington, Oregon, and California L. Wallace et al. 10.1111/ina.13105
155. High-Resolution Assessment of Air Quality in Urban Areas—A Business Model Perspective K. Schäfer et al. 10.3390/atmos12050595