Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-4617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jun 2021
Research article |
| 22 Jun 2021
| 22 Jun 2021
Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor
Karoline K. Barkjohn
CORRESPONDING AUTHOR
Office of Research and Development, US Environmental Protection
Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Brett Gantt
Office of Air Quality Planning and Standards, US Environmental
Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Andrea L. Clements
Office of Research and Development, US Environmental Protection
Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Related authors
Tongshu Zheng, Michael H. Bergin, Karoline K. Johnson, Sachchida N. Tripathi, Shilpa Shirodkar, Matthew S. Landis, Ronak Sutaria, and David E. Carlson
Atmos. Meas. Tech., 11, 4823–4846, https://doi.org/10.5194/amt-11-4823-2018, https://doi.org/10.5194/amt-11-4823-2018, 2018
Short summary
Short summary
Low-cost particulate matter sensors are promising tools for supplementing existing air quality monitoring networks but their performance under field conditions is not well understood. We characterized how well Plantower PMS3003 sensors measure PM2.5 in a wide range of ambient conditions against different reference sensors. When a more precise reference method is used for calibration and proper RH corrections are made, our work suggests PMS3003's can measure PM2.5 within ~ 10 % of ambient values.
Karoline K. Johnson, Michael H. Bergin, Armistead G. Russell, and Gayle S. W. Hagler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2015-331, https://doi.org/10.5194/amt-2015-331, 2016
Revised manuscript not accepted
Short summary
Short summary
Low-cost air quality sensors were evaluated in Atlanta, GA, in Hyderabad, India and also in lab experiments. Freeway emissions were also quantified in Atlanta. The performance of these sensors were evaluated against current measurement instruments. Results show potential usefulness for these sensors in polluted areas. The ability to inexpensively measure air pollution will enable researches, citizens, and policy makers to make informed decisions to reduce health impacts from air pollution.
Lena F. Weissert, Geoff S. Henshaw, Andrea L. Clements, Rachelle M. Duvall, and Carry Croghan
EGUsphere, https://doi.org/10.5194/egusphere-2024-3454, https://doi.org/10.5194/egusphere-2024-3454, 2024
Short summary
Short summary
This study evaluates a remote calibration tool, referred to as MOMA for calibrating PurpleAir PM2.5 sensors, especially for varying PM sources, and compares it with the EPA correction. MOMA improved the accuracy of PurpleAir sensor data comparable to the EPA correction. Although reliant on nearby reference sites, MOMA offers valuable insights into potential PM sources, thereby increasing the overall value of PurpleAir sensor networks.
Qinyi Li, Rafael Borge, Golam Sarwar, David de la Paz, Brett Gantt, Jessica Domingo, Carlos A. Cuevas, and Alfonso Saiz-Lopez
Atmos. Chem. Phys., 19, 15321–15337, https://doi.org/10.5194/acp-19-15321-2019, https://doi.org/10.5194/acp-19-15321-2019, 2019
Short summary
Short summary
The abundance and distribution of reactive halogen species and their impact on air quality in Europe are poorly understood. We adopt a state-of-the-art regional model (CMAQ) to evaluate such effects, and the results demonstrate the significant influence of halogen chemistry on the capacity of atmospheric oxidation and the formation of air pollutants in Europe. Our study highlights the necessity of including halogen chemistry in the formulation of air pollution control policy.
Tongshu Zheng, Michael H. Bergin, Karoline K. Johnson, Sachchida N. Tripathi, Shilpa Shirodkar, Matthew S. Landis, Ronak Sutaria, and David E. Carlson
Atmos. Meas. Tech., 11, 4823–4846, https://doi.org/10.5194/amt-11-4823-2018, https://doi.org/10.5194/amt-11-4823-2018, 2018
Short summary
Short summary
Low-cost particulate matter sensors are promising tools for supplementing existing air quality monitoring networks but their performance under field conditions is not well understood. We characterized how well Plantower PMS3003 sensors measure PM2.5 in a wide range of ambient conditions against different reference sensors. When a more precise reference method is used for calibration and proper RH corrections are made, our work suggests PMS3003's can measure PM2.5 within ~ 10 % of ambient values.
K. Wyat Appel, Sergey L. Napelenok, Kristen M. Foley, Havala O. T. Pye, Christian Hogrefe, Deborah J. Luecken, Jesse O. Bash, Shawn J. Roselle, Jonathan E. Pleim, Hosein Foroutan, William T. Hutzell, George A. Pouliot, Golam Sarwar, Kathleen M. Fahey, Brett Gantt, Robert C. Gilliam, Nicholas K. Heath, Daiwen Kang, Rohit Mathur, Donna B. Schwede, Tanya L. Spero, David C. Wong, and Jeffrey O. Young
Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, https://doi.org/10.5194/gmd-10-1703-2017, 2017
Short summary
Short summary
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system. The CMAQ model is used extensively throughout the world to simulate air pollutants for many purposes, including regulatory and air quality forecasting applications. This work describes the scientific updates made to the latest version of the CMAQ modeling system (CMAQv5.1) and presents an evaluation of the new model against observations and results from the previous model version.
Karoline K. Johnson, Michael H. Bergin, Armistead G. Russell, and Gayle S. W. Hagler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2015-331, https://doi.org/10.5194/amt-2015-331, 2016
Revised manuscript not accepted
Short summary
Short summary
Low-cost air quality sensors were evaluated in Atlanta, GA, in Hyderabad, India and also in lab experiments. Freeway emissions were also quantified in Atlanta. The performance of these sensors were evaluated against current measurement instruments. Results show potential usefulness for these sensors in polluted areas. The ability to inexpensively measure air pollution will enable researches, citizens, and policy makers to make informed decisions to reduce health impacts from air pollution.
B. Gantt, J. T. Kelly, and J. O. Bash
Geosci. Model Dev., 8, 3733–3746, https://doi.org/10.5194/gmd-8-3733-2015, https://doi.org/10.5194/gmd-8-3733-2015, 2015
B. Gantt, M. S. Johnson, M. Crippa, A. S. H. Prévôt, and N. Meskhidze
Geosci. Model Dev., 8, 619–629, https://doi.org/10.5194/gmd-8-619-2015, https://doi.org/10.5194/gmd-8-619-2015, 2015
B. Gantt, J. He, X. Zhang, Y. Zhang, and A. Nenes
Atmos. Chem. Phys., 14, 7485–7497, https://doi.org/10.5194/acp-14-7485-2014, https://doi.org/10.5194/acp-14-7485-2014, 2014
B. Gantt and N. Meskhidze
Atmos. Chem. Phys., 13, 3979–3996, https://doi.org/10.5194/acp-13-3979-2013, https://doi.org/10.5194/acp-13-3979-2013, 2013
Related subject area
Subject: Aerosols | Technique: In Situ Measurement | Topic: Validation and Intercomparisons
Field intercomparison of ice nucleation measurements: the Fifth International Workshop on Ice Nucleation Phase 3 (FIN-03)
A view on recent ice-nucleating particle intercomparison studies: Why the uncertainty of the activation conditions matters
Performance of a low-cost optical particle counter (Alphasense OPC-N3) for estimating size-resolved dust emission flux using eddy covariance
Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions
Testing ion exchange resin for quantifying bulk and throughfall deposition of macro- and micro-elements in forests
Classification accuracy and compatibility across devices of a new Rapid-E+ flow cytometer
A 2-year intercomparison of three methods for measuring black carbon concentration at a high-altitude research station in Europe
Comparison of the LEO and CPMA-SP2 techniques for black-carbon mixing-state measurements
Aerosol trace element solubility determined using ultrapure water batch leaching: an intercomparison study of four different leaching protocols
Field comparison of dual- and single-spot Aethalometers: equivalent black carbon, light absorption, Ångström exponent and secondary brown carbon estimations
Comparison of the imaginary parts of the atmospheric refractive index structure parameter and aerosol flux based on different measurement methods
Spectral analysis approach for assessing the accuracy of low-cost air quality sensor network data
Challenges and solutions in determining dilution ratios and emission factors from chase measurements of passenger vehicles
Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India
Performance evaluation of portable dual-spot micro-aethalometers for source identification of black carbon aerosols: application to wildfire smoke and traffic emissions in the Pacific Northwest
Further validation of the estimates of the downwelling solar radiation at ground level in cloud-free conditions provided by the McClear service: the case of Sub-Saharan Africa and the Maldives Archipelago
Identifying optimal co-location calibration periods for low-cost sensors
Intercomparison of airborne and surface-based measurements during the CLARIFY, ORACLES and LASIC field experiments
Balloon-borne aerosol–cloud interaction studies (BACIS): field campaigns to understand and quantify aerosol effects on clouds
Correcting for filter-based aerosol light absorption biases at the Atmospheric Radiation Measurement program's Southern Great Plains site using photoacoustic measurements and machine learning
Development and evaluation of correction models for a low-cost fine particulate matter monitor
Relative errors in derived multi-wavelength intensive aerosol optical properties using cavity attenuated phase shift single-scattering albedo monitors, a nephelometer, and tricolour absorption photometer measurements
Aircraft-engine particulate matter emissions from conventional and sustainable aviation fuel combustion: comparison of measurement techniques for mass, number, and size
Inter-comparison of online and offline methods for measuring ambient heavy and trace elements and water-soluble inorganic ions (NO3−, SO42−, NH4+, and Cl−) in PM2.5 over a heavily polluted megacity, Delhi
Measurement of black carbon emissions from multiple engine and source types using laser-induced incandescence: sensitivity to laser fluence
Compositional data analysis (CoDA) as a tool to evaluate a new low-cost settling-based PM10 sampling head in a desert dust source region
On the use of reference mass spectra for reducing uncertainty in source apportionment of solid-fuel burning in ambient organic aerosol
Estimates of mass absorption cross sections of black carbon for filter-based absorption photometers in the Arctic
Effects of different correction algorithms on absorption coefficient – a comparison of three optical absorption photometers at a boreal forest site
Determination of the multiple-scattering correction factor and its cross-sensitivity to scattering and wavelength dependence for different AE33 Aethalometer filter tapes: a multi-instrumental approach
Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data
Absorption instruments inter-comparison campaign at the Arctic Pallas station
Sizing response of the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) and Laser Aerosol Spectrometer (LAS) to changes in submicron aerosol composition and refractive index
Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 2: Spatiotemporal trends
The importance of size ranges in aerosol instrument intercomparisons: a case study for the Atmospheric Tomography Mission
Intercomparison of thermal–optical carbon measurements by Sunset and Desert Research Institute (DRI) analyzers using the IMPROVE_A protocol
Ångström exponent errors prevent accurate visibility measurement
Comparison of co-located refractory black carbon (rBC) and elemental carbon (EC) mass concentration measurements during field campaigns at several European sites
Real-time measurement of radionuclide concentrations and its impact on inverse modeling of 106Ru release in the fall of 2017
Effects of the prewhitening method, the time granularity, and the time segmentation on the Mann–Kendall trend detection and the associated Sen's slope
Best practices for precipitation sample storage for offline studies of ice nucleation in marine and coastal environments
Interferences with aerosol acidity quantification due to gas-phase ammonia uptake onto acidic sulfate filter samples
Multi-year ACSM measurements at the central European research station Melpitz (Germany) – Part 1: Instrument robustness, quality assurance, and impact of upper size cutoff diameter
The new instrument using a TC–BC (total carbon–black carbon) method for the online measurement of carbonaceous aerosols
Aerosol retrievals from the EKO MS-711 spectral direct irradiance measurements and corrections of the circumsolar radiation
Characterization of anthropogenic organic aerosols by TOF-ACSM with the new capture vaporizer
Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods
Intercomparison between the aerosol optical properties retrieved by different inversion methods from SKYNET sky radiometer observations over Qionghai and Yucheng in China
A comparison of lognormal and gamma size distributions for characterizing the stratospheric aerosol phase function from optical particle counter measurements
Comparison of aircraft measurements during GoAmazon2014/5 and ACRIDICON-CHUVA
Paul J. DeMott, Jessica A. Mirrielees, Sarah Suda Petters, Daniel J. Cziczo, Markus D. Petters, Heinz G. Bingemer, Thomas C. J. Hill, Karl Froyd, Sarvesh Garimella, A. Gannet Hallar, Ezra J. T. Levin, Ian B. McCubbin, Anne E. Perring, Christopher N. Rapp, Thea Schiebel, Jann Schrod, Kaitlyn J. Suski, Daniel Weber, Martin J. Wolf, Maria Zawadowicz, Jake Zenker, Ottmar Möhler, and Sarah D. Brooks
Atmos. Meas. Tech., 18, 639–672, https://doi.org/10.5194/amt-18-639-2025, https://doi.org/10.5194/amt-18-639-2025, 2025
Short summary
Short summary
The Fifth International Ice Nucleation Workshop Phase 3 (FIN-03) compared the ambient atmospheric performance of ice-nucleating particle (INP) measuring systems and explored general methods for discerning atmospheric INP compositions. Mirroring laboratory results, INP concentrations agreed within 5–10 factors. Measurements of total aerosol properties and investigations of INP compositions supported a dominant role of soil and plant organic aerosol elements as INPs during the study.
Jann Schrod and Heinz G. Bingemer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3778, https://doi.org/10.5194/egusphere-2024-3778, 2025
Short summary
Short summary
Ice-nucleating particle (INP) observations often differ by 1 order of magnitude, when multiple instruments measure in parallel. As INP measurements are sensitive to the activation conditions, inaccuracies in the temperature measurement may induce significant deviations in the INP concentration. It was found that typical temperature uncertainties reported in intercomparison studies may explain divergences of a factor of 2 (± 0.5 °C) or 5 to 10 (± 1 °C) between two INP counters with opposite bias.
Sylvain Dupont, Eric Lamaud, Mark R. Irvine, Jean-Marc Bonnefond, Adolfo Gonzalez-Romero, Andrés Alastuey, Cristina González-Flórez, Xavier Querol, Konrad Kandler, Martina Klose, and Carlos Pérez García-Pando
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-187, https://doi.org/10.5194/amt-2024-187, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Low-cost optical particle counters (OPCs) offer new opportunities to monitor dust particles from wind soil erosion. They are more affordable, compact, and use less power than traditional OPCs. We tested the ability of the low-cost OPC-N3 from Alfasense to estimate the dust emission flux during erosion events in Jordan. The N3 estimated well the dust flux, with differences of less than 30% compared to a traditional OPC. Our results confirm the potential of low-cost OPCs for dust-erosion research.
Martine E. Mathieu-Campbell, Chuqi Guo, Andrew P. Grieshop, and Jennifer Richmond-Bryant
Atmos. Meas. Tech., 17, 6735–6749, https://doi.org/10.5194/amt-17-6735-2024, https://doi.org/10.5194/amt-17-6735-2024, 2024
Short summary
Short summary
The main source of measurement error from particulate matter PurpleAir sensors is relative humidity. Recent bias correction methods have not focused on the humid southeastern United States (US). To provide high-quality spatial and temporal data to inform community exposure in this area, our study developed and evaluated PurpleAir correction models for use in the warm–humid climate zones of the US. We found improved performance metrics, with error metrics decreasing by 16–23 % for our models.
Marleen A. E. Vos, Wim de Vries, G. F. (Ciska) Veen, Marcel R. Hoosbeek, and Frank J. Sterck
Atmos. Meas. Tech., 17, 6579–6594, https://doi.org/10.5194/amt-17-6579-2024, https://doi.org/10.5194/amt-17-6579-2024, 2024
Short summary
Short summary
Atmospheric deposition poses risks with high anthropogenic inputs. Current deposition measurement methods are labor-intensive. Ion exchange resin (IER) offers a promising, cost-effective alternative. We assessed IER for bulk deposition and throughfall, testing adsorption capacity, recovery efficiency and field performance. IER showed good adsorption and recovery and was unaffected by environmental conditions, showing potential for robust and efficient measurements of atmospheric deposition.
Branko Sikoparija, Predrag Matavulj, Isidora Simovic, Predrag Radisic, Sanja Brdar, Vladan Minic, Danijela Tesendic, Evgeny Kadantsev, Julia Palamarchuk, and Mikhail Sofiev
Atmos. Meas. Tech., 17, 5051–5070, https://doi.org/10.5194/amt-17-5051-2024, https://doi.org/10.5194/amt-17-5051-2024, 2024
Short summary
Short summary
We assess the suitability of a Rapid-E+ particle counter for use in pollen monitoring networks. The criterion was the ability of different devices to provide the same signal for the same pollen type, which would allow for unified reference libraries and recognition algorithms for Rapid-E+. We tested three devices and found notable differences between their fluorescence measurements. Each one showed potential for pollen identification, but the large variability between them needs to be addressed.
Sarah Tinorua, Cyrielle Denjean, Pierre Nabat, Véronique Pont, Mathilde Arnaud, Thierry Bourrianne, Maria Dias Alves, and Eric Gardrat
Atmos. Meas. Tech., 17, 3897–3915, https://doi.org/10.5194/amt-17-3897-2024, https://doi.org/10.5194/amt-17-3897-2024, 2024
Short summary
Short summary
The three most widely used techniques for measuring black carbon (BC) have been deployed continuously for 2 years at a French high-altitude research station. Despite a similar temporal variation in the BC load, we found significant biases by up to a factor of 8 between the three instruments. This study raises questions about the relevance of using these instruments for specific background sites, as well as the processing of their data, which can vary according to the atmospheric conditions.
Arash Naseri, Joel C. Corbin, and Jason S. Olfert
Atmos. Meas. Tech., 17, 3719–3738, https://doi.org/10.5194/amt-17-3719-2024, https://doi.org/10.5194/amt-17-3719-2024, 2024
Short summary
Short summary
It is crucial to accurately measure the mixing states of light-absorbing carbon particles from emission sources like wildfires and biomass combustion to decrease climate forcing uncertainties. This study compares methods that measure light-absorbing carbon in the atmosphere. The CPMA-SP2 method offers more accurate results than traditional light-scattering methods, such as the leading-edge-only (LEO) method, thereby enhancing the accuracy of measuring the mixing states of light-absorbing carbon.
Rui Li, Prema Piyusha Panda, Yizhu Chen, Zhenming Zhu, Fu Wang, Yujiao Zhu, He Meng, Yan Ren, Ashwini Kumar, and Mingjin Tang
Atmos. Meas. Tech., 17, 3147–3156, https://doi.org/10.5194/amt-17-3147-2024, https://doi.org/10.5194/amt-17-3147-2024, 2024
Short summary
Short summary
We found that for ultrapure water batch leaching, the difference in specific experimental parameters, including agitation methods, filter pore size, and contact time, only led to a small and sometimes insignificant difference in determined aerosol trace element solubility. Furthermore, aerosol trace element solubility determined using four common ultrapure water leaching protocols showed good agreement.
Liangbin Wu, Cheng Wu, Tao Deng, Dui Wu, Mei Li, Yong Jie Li, and Zhen Zhou
Atmos. Meas. Tech., 17, 2917–2936, https://doi.org/10.5194/amt-17-2917-2024, https://doi.org/10.5194/amt-17-2917-2024, 2024
Short summary
Short summary
Field comparison of dual-spot (AE33) and single-spot (AE31) Aethalometers by full-year collocated measurements suggests that site-specific correction factors are needed to ensure the long-term data continuity for AE31-to-AE33 transition in black carbon monitoring networks; babs agrees well between AE33 and AE31, with slight variations by wavelength (slope: 0.87–1.04; R2: 0.95–0.97). A ~ 20 % difference in secondary brown carbon light absorption was found between AE33 and AE31.
Renmin Yuan, Hongsheng Zhang, Jiajia Hua, Hao Liu, Peizhe Wu, Xingyu Zhu, and Jianning Sun
Atmos. Meas. Tech., 17, 2089–2102, https://doi.org/10.5194/amt-17-2089-2024, https://doi.org/10.5194/amt-17-2089-2024, 2024
Short summary
Short summary
Previously, a new method for atmospheric aerosol flux was proposed, and a large-aperture scintillometer was developed for experimental measurements, but the method was consistently not validated. In this paper, eddy correlation experiments for aerosol vertical transport fluxes were conducted to verify the reliability of the previous large-aperture scintillometer method. The experimental results also show that urban green land is a sink area for aerosol particles.
Vijay Kumar, Dinushani Senarathna, Supraja Gurajala, William Olsen, Shantanu Sur, Sumona Mondal, and Suresh Dhaniyala
Atmos. Meas. Tech., 16, 5415–5427, https://doi.org/10.5194/amt-16-5415-2023, https://doi.org/10.5194/amt-16-5415-2023, 2023
Short summary
Short summary
Low-cost sensors are becoming increasingly important in air quality monitoring due to their affordability and ease of deployment. While low-cost sensors have the potential to democratize air quality monitoring, their use must be accompanied by careful interpretation and validation of the data. Analysis of their long-term data record clearly shows that the reported data from low-cost sensors may not be equally sensitive to all emission sources, which can complicate policy-making.
Ville Leinonen, Miska Olin, Sampsa Martikainen, Panu Karjalainen, and Santtu Mikkonen
Atmos. Meas. Tech., 16, 5075–5089, https://doi.org/10.5194/amt-16-5075-2023, https://doi.org/10.5194/amt-16-5075-2023, 2023
Short summary
Short summary
Emission factor calculation was studied to provide models that do not use traditional CO2-based calculation in exhaust plume analysis. Two types of models, one based on the physical dependency of dilution of the exhaust flow rate and speed and two based on the statistical, measured dependency of dilution of the exhaust flow rate, acceleration, speed, altitude change, and/or wind, were developed. These methods could possibly be extended to also calculate non-exhaust emissions in the future.
Mark Joseph Campmier, Jonathan Gingrich, Saumya Singh, Nisar Baig, Shahzad Gani, Adithi Upadhya, Pratyush Agrawal, Meenakshi Kushwaha, Harsh Raj Mishra, Ajay Pillarisetti, Sreekanth Vakacherla, Ravi Kant Pathak, and Joshua S. Apte
Atmos. Meas. Tech., 16, 4357–4374, https://doi.org/10.5194/amt-16-4357-2023, https://doi.org/10.5194/amt-16-4357-2023, 2023
Short summary
Short summary
We studied a low-cost air pollution sensor called PurpleAir PA-II in three different locations in India (Delhi, Hamirpur, and Bangalore) to characterize its performance. We compared its signal to more expensive reference sensors and found that the PurpleAir sensor was precise but inaccurate without calibration. We created a custom calibration equation for each location, which improved the accuracy of the PurpleAir sensor, and found that calibrations should be adjusted for different seasons.
Mrinmoy Chakraborty, Amanda Giang, and Naomi Zimmerman
Atmos. Meas. Tech., 16, 2333–2352, https://doi.org/10.5194/amt-16-2333-2023, https://doi.org/10.5194/amt-16-2333-2023, 2023
Short summary
Short summary
Black carbon (BC) has important climate and human health impacts. Aethalometers are used to measure BC, but they are hard to deploy in many environments (remote, mobile). We evaluate how well a portable micro-aethalometer (MA300) performs compared to a reference aethalometer at a road-side site in Vancouver, BC, Canada, during regular and wildfire conditions. We find that the MA300 can reproduce overall patterns in concentrations and source characterization but with some underestimation.
William Wandji Nyamsi, Yves-Marie Saint-Drenan, Antti Arola, and Lucien Wald
Atmos. Meas. Tech., 16, 2001–2036, https://doi.org/10.5194/amt-16-2001-2023, https://doi.org/10.5194/amt-16-2001-2023, 2023
Short summary
Short summary
The McClear service provides estimates of surface solar irradiances in cloud-free conditions. By comparing McClear estimates to 1 min measurements performed in Sub-Saharan Africa and the Maldives Archipelago in the Indian Ocean, McClear accurately estimates global irradiance and tends to overestimate direct irrradiance. This work establishes a general overview of the performance of the McClear service.
Misti Levy Zamora, Colby Buehler, Abhirup Datta, Drew R. Gentner, and Kirsten Koehler
Atmos. Meas. Tech., 16, 169–179, https://doi.org/10.5194/amt-16-169-2023, https://doi.org/10.5194/amt-16-169-2023, 2023
Short summary
Short summary
We assessed five pairs of co-located reference and low-cost sensor data sets (PM2.5, O3, NO2, NO, and CO) to make recommendations for best practices regarding the field calibration of low-cost air quality sensors. We found diminishing improvements for calibration periods longer than about 6 weeks for all sensors and that co-location can be minimized if the period is strategically selected and monitored so that the calibration period is representative of the desired measurement setting.
Paul A. Barrett, Steven J. Abel, Hugh Coe, Ian Crawford, Amie Dobracki, James Haywood, Steve Howell, Anthony Jones, Justin Langridge, Greg M. McFarquhar, Graeme J. Nott, Hannah Price, Jens Redemann, Yohei Shinozuka, Kate Szpek, Jonathan W. Taylor, Robert Wood, Huihui Wu, Paquita Zuidema, Stéphane Bauguitte, Ryan Bennett, Keith Bower, Hong Chen, Sabrina Cochrane, Michael Cotterell, Nicholas Davies, David Delene, Connor Flynn, Andrew Freedman, Steffen Freitag, Siddhant Gupta, David Noone, Timothy B. Onasch, James Podolske, Michael R. Poellot, Sebastian Schmidt, Stephen Springston, Arthur J. Sedlacek III, Jamie Trembath, Alan Vance, Maria A. Zawadowicz, and Jianhao Zhang
Atmos. Meas. Tech., 15, 6329–6371, https://doi.org/10.5194/amt-15-6329-2022, https://doi.org/10.5194/amt-15-6329-2022, 2022
Short summary
Short summary
To better understand weather and climate, it is vital to go into the field and collect observations. Often measurements take place in isolation, but here we compared data from two aircraft and one ground-based site. This was done in order to understand how well measurements made on one platform compared to those made on another. Whilst this is easy to do in a controlled laboratory setting, it is more challenging in the real world, and so these comparisons are as valuable as they are rare.
Varaha Ravi Kiran, Madineni Venkat Ratnam, Masatomo Fujiwara, Herman Russchenberg, Frank G. Wienhold, Bomidi Lakshmi Madhavan, Mekalathur Roja Raman, Renju Nandan, Sivan Thankamani Akhil Raj, Alladi Hemanth Kumar, and Saginela Ravindra Babu
Atmos. Meas. Tech., 15, 4709–4734, https://doi.org/10.5194/amt-15-4709-2022, https://doi.org/10.5194/amt-15-4709-2022, 2022
Short summary
Short summary
We proposed and conducted the multi-instrumental BACIS (Balloon-borne Aerosol–Cloud Interaction Studies) field campaigns using balloon-borne in situ measurements and ground-based and space-borne remote sensing instruments. Aerosol-cloud interaction is quantified for liquid clouds by segregating aerosol and cloud information in a balloon profile. Overall, the observational approach proposed here demonstrated its capability for understanding the aerosol–cloud interaction process.
Joshin Kumar, Theo Paik, Nishit J. Shetty, Patrick Sheridan, Allison C. Aiken, Manvendra K. Dubey, and Rajan K. Chakrabarty
Atmos. Meas. Tech., 15, 4569–4583, https://doi.org/10.5194/amt-15-4569-2022, https://doi.org/10.5194/amt-15-4569-2022, 2022
Short summary
Short summary
Accurate long-term measurement of aerosol light absorption is vital for assessing direct aerosol radiative forcing. Light absorption by aerosols at the US Department of Energy long-term climate monitoring SGP site is measured using the Particle Soot Absorption Photometer (PSAP), which suffers from artifacts and biases difficult to quantify. Machine learning offers a promising path forward to correct for biases in the long-term absorption dataset at the SGP site and similar Class-I areas.
Brayden Nilson, Peter L. Jackson, Corinne L. Schiller, and Matthew T. Parsons
Atmos. Meas. Tech., 15, 3315–3328, https://doi.org/10.5194/amt-15-3315-2022, https://doi.org/10.5194/amt-15-3315-2022, 2022
Short summary
Short summary
Correction models were developed using PurpleAir–Federal Equivalent Method (FEM) hourly fine particulate matter (PM2.5) observation colocation sites across North America (NA). These were evaluated in comparison with four existing models at an additional 15 NA colocation sites. This study provides a robust framework for the evaluation of low-cost PM2.5 sensor correction models using the Canadian AQHI+ system and presents an optimized general correction model for North American PA sensors.
Patrick Weber, Andreas Petzold, Oliver F. Bischof, Benedikt Fischer, Marcel Berg, Andrew Freedman, Timothy B. Onasch, and Ulrich Bundke
Atmos. Meas. Tech., 15, 3279–3296, https://doi.org/10.5194/amt-15-3279-2022, https://doi.org/10.5194/amt-15-3279-2022, 2022
Short summary
Short summary
In our laboratory closure study, we measured the full set of aerosol optical properties for different light-absorbing aerosols using a set of instruments.
Our key finding is that the extensive and intensive aerosol optical properties obtained agree with data from reference instruments, except the absorption Ångström exponent of externally mixed aerosols. The reported uncertainty in the single-scattering albedo fulfils the defined goals for Global Climate Observing System applications of 10 %.
Joel C. Corbin, Tobias Schripp, Bruce E. Anderson, Greg J. Smallwood, Patrick LeClercq, Ewan C. Crosbie, Steven Achterberg, Philip D. Whitefield, Richard C. Miake-Lye, Zhenhong Yu, Andrew Freedman, Max Trueblood, David Satterfield, Wenyan Liu, Patrick Oßwald, Claire Robinson, Michael A. Shook, Richard H. Moore, and Prem Lobo
Atmos. Meas. Tech., 15, 3223–3242, https://doi.org/10.5194/amt-15-3223-2022, https://doi.org/10.5194/amt-15-3223-2022, 2022
Short summary
Short summary
The combustion of sustainable aviation fuels in aircraft engines produces particulate matter (PM) emissions with different properties than conventional fuels due to changes in fuel composition. Consequently, the response of various diagnostic instruments to PM emissions may be impacted. We found no significant instrument biases in terms of particle mass, number, and size measurements for conventional and sustainable aviation fuel blends despite large differences in the magnitude of emissions.
Himadri Sekhar Bhowmik, Ashutosh Shukla, Vipul Lalchandani, Jay Dave, Neeraj Rastogi, Mayank Kumar, Vikram Singh, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 15, 2667–2684, https://doi.org/10.5194/amt-15-2667-2022, https://doi.org/10.5194/amt-15-2667-2022, 2022
Short summary
Short summary
This study presents comparisons between online and offline measurements of both refractory and non-refractory aerosol. This study shows differences between the measurements, related to either the limitations of the instrument (e.g., aerosol mass spectrometer only observing non-refractory aerosol) or known interferences with the technique (e.g., volatilization or reactions). The findings highlight the measurement methods' accuracy and imply the particular type of measurements needed.
Ruoyang Yuan, Prem Lobo, Greg J. Smallwood, Mark P. Johnson, Matthew C. Parker, Daniel Butcher, and Adrian Spencer
Atmos. Meas. Tech., 15, 241–259, https://doi.org/10.5194/amt-15-241-2022, https://doi.org/10.5194/amt-15-241-2022, 2022
Short summary
Short summary
The relationship between the non-volatile particulate matter (nvPM) mass emissions produced by different engine sources and the response of the LII 300 instrument, used for regulatory measurements of nvPM mass emissions in aircraft engine certification tests, was investigated for different sources and operating conditions. Laser fluence optimisation was required for real-time nvPM mass concentration measurements. These results will inform the development of updated calibration protocols.
Yangjunjie Xu-Yang, Rémi Losno, Fabrice Monna, Jean-Louis Rajot, Mohamed Labiadh, Gilles Bergametti, and Béatrice Marticorena
Atmos. Meas. Tech., 14, 7657–7680, https://doi.org/10.5194/amt-14-7657-2021, https://doi.org/10.5194/amt-14-7657-2021, 2021
Short summary
Short summary
Suspended particles in air (aerosols) are sampled with a pump drawing ambient air through a filter. The air inlet must be carefully designed to control the size of sampled particles and to reject the largest ones (> 10 µm). A low-cost sampling head for determination of the finest fraction of aerosol (> 10 µm in diameter) is presented. Compositional data analysis (CoDA) tools are extensively used here to demonstrate similarity between the low-cost sampling head and other existing systems.
Chunshui Lin, Darius Ceburnis, Anna Trubetskaya, Wei Xu, William Smith, Stig Hellebust, John Wenger, Colin O'Dowd, and Jurgita Ovadnevaite
Atmos. Meas. Tech., 14, 6905–6916, https://doi.org/10.5194/amt-14-6905-2021, https://doi.org/10.5194/amt-14-6905-2021, 2021
Short summary
Short summary
Source apportionment of solid-fuel-burning emissions can be complicated by the use of different fuels, stoves, and burning conditions. Here, the organic aerosol mass spectra produced from burning a range of solid fuels in several stoves were compared. This study accounts for the source variability and provides better constraints on the primary factor contributions to the ambient organic aerosol estimations, holding significant implications for public health and policymakers.
Sho Ohata, Tatsuhiro Mori, Yutaka Kondo, Sangeeta Sharma, Antti Hyvärinen, Elisabeth Andrews, Peter Tunved, Eija Asmi, John Backman, Henri Servomaa, Daniel Veber, Konstantinos Eleftheriadis, Stergios Vratolis, Radovan Krejci, Paul Zieger, Makoto Koike, Yugo Kanaya, Atsushi Yoshida, Nobuhiro Moteki, Yongjing Zhao, Yutaka Tobo, Junji Matsushita, and Naga Oshima
Atmos. Meas. Tech., 14, 6723–6748, https://doi.org/10.5194/amt-14-6723-2021, https://doi.org/10.5194/amt-14-6723-2021, 2021
Short summary
Short summary
Reliable values of mass absorption cross sections (MACs) of black carbon (BC) are required to determine mass concentrations of BC at Arctic sites using different types of filter-based absorption photometers. We successfully estimated MAC values for these instruments through comparison with independent measurements of BC by a continuous soot monitoring system called COSMOS. These MAC values are consistent with each other and applicable to study spatial and temporal variation in BC in the Arctic.
Krista Luoma, Aki Virkkula, Pasi Aalto, Katrianne Lehtipalo, Tuukka Petäjä, and Markku Kulmala
Atmos. Meas. Tech., 14, 6419–6441, https://doi.org/10.5194/amt-14-6419-2021, https://doi.org/10.5194/amt-14-6419-2021, 2021
Short summary
Short summary
The study presents a comparison of three absorption photometers that measured ambient aerosol particles at a boreal forest site. The study aims to better understand problems related to filter-based measurements. Results show how different correction algorithms, which are used to produce the data, affect the derived optical properties of aerosol particles.
Jesús Yus-Díez, Vera Bernardoni, Griša Močnik, Andrés Alastuey, Davide Ciniglia, Matic Ivančič, Xavier Querol, Noemí Perez, Cristina Reche, Martin Rigler, Roberta Vecchi, Sara Valentini, and Marco Pandolfi
Atmos. Meas. Tech., 14, 6335–6355, https://doi.org/10.5194/amt-14-6335-2021, https://doi.org/10.5194/amt-14-6335-2021, 2021
Short summary
Short summary
Here we characterize the multiple-scattering factor, C, of the dual-spot Aethalometer AE33 and its cross-sensitivity to scattering and wavelength dependence for three background stations: urban, regional and mountaintop. C was obtained for two sets of filter tapes: M8020 and M8060. The cross-sensitivity to scattering and wavelength dependence of C were determined by inter-comparing with other absorption and scattering measurements including multi-angle off-line absorption measurements.
Hui Li, Boming Liu, Xin Ma, Shikuan Jin, Yingying Ma, Yuefeng Zhao, and Wei Gong
Atmos. Meas. Tech., 14, 5977–5986, https://doi.org/10.5194/amt-14-5977-2021, https://doi.org/10.5194/amt-14-5977-2021, 2021
Short summary
Short summary
Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer (PBL), and numerous methods have been proposed for retrieving PBL height (PBLH) from RS data. However, an algorithm that is suitable under all atmospheric conditions does not exist. This study evaluates the performance of four common PBLH algorithms under different thermodynamic stability conditions based on RS data.
Eija Asmi, John Backman, Henri Servomaa, Aki Virkkula, Maria I. Gini, Konstantinos Eleftheriadis, Thomas Müller, Sho Ohata, Yutaka Kondo, and Antti Hyvärinen
Atmos. Meas. Tech., 14, 5397–5413, https://doi.org/10.5194/amt-14-5397-2021, https://doi.org/10.5194/amt-14-5397-2021, 2021
Short summary
Short summary
Absorbing aerosols are warming the planet and accurate measurements of their concentrations in pristine environments are needed. We applied eight different absorbing-aerosol measurement methods in a field campaign at the Arctic Pallas station. The filter-based techniques were found to be the most sensitive to detect the minuscule amounts of black carbon present, showing a 40 % agreement between them. Our results help to reduce uncertainties in absorbing aerosol measurements.
Richard H. Moore, Elizabeth B. Wiggins, Adam T. Ahern, Stephen Zimmerman, Lauren Montgomery, Pedro Campuzano Jost, Claire E. Robinson, Luke D. Ziemba, Edward L. Winstead, Bruce E. Anderson, Charles A. Brock, Matthew D. Brown, Gao Chen, Ewan C. Crosbie, Hongyu Guo, Jose L. Jimenez, Carolyn E. Jordan, Ming Lyu, Benjamin A. Nault, Nicholas E. Rothfuss, Kevin J. Sanchez, Melinda Schueneman, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Nicholas L. Wagner, and Jian Wang
Atmos. Meas. Tech., 14, 4517–4542, https://doi.org/10.5194/amt-14-4517-2021, https://doi.org/10.5194/amt-14-4517-2021, 2021
Short summary
Short summary
Atmospheric particles are everywhere and exist in a range of sizes, from a few nanometers to hundreds of microns. Because particle size determines the behavior of chemical and physical processes, accurately measuring particle sizes is an important and integral part of atmospheric field measurements! Here, we discuss the performance of two commonly used particle sizers and how changes in particle composition and optical properties may result in sizing uncertainties, which we quantify.
Alexandra J. Boris, Satoshi Takahama, Andrew T. Weakley, Bruno M. Debus, Stephanie L. Shaw, Eric S. Edgerton, Taekyu Joo, Nga L. Ng, and Ann M. Dillner
Atmos. Meas. Tech., 14, 4355–4374, https://doi.org/10.5194/amt-14-4355-2021, https://doi.org/10.5194/amt-14-4355-2021, 2021
Short summary
Short summary
Infrared spectrometry can be applied in routine monitoring of atmospheric particles to give comprehensive characterization of the organic material by bond rather than species. Using this technique, the concentrations of particle organic material were found to decrease 2011–2016 in the southeastern US, driven by a decline in highly aged material, concurrent with declining anthropogenic emissions. However, an increase was observed in the fraction of more moderately aged organic matter.
Hongyu Guo, Pedro Campuzano-Jost, Benjamin A. Nault, Douglas A. Day, Jason C. Schroder, Dongwook Kim, Jack E. Dibb, Maximilian Dollner, Bernadett Weinzierl, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 3631–3655, https://doi.org/10.5194/amt-14-3631-2021, https://doi.org/10.5194/amt-14-3631-2021, 2021
Short summary
Short summary
We utilize a set of high-quality datasets collected during the NASA Atmospheric Tomography Mission to investigate the impact of differences in observable particle sizes across aerosol instruments in aerosol measurement comparisons. Very good agreement was found between chemically and physically derived submicron aerosol volume. Results support a lack of significant unknown biases in the response of an Aerodyne aerosol mass spectrometer (AMS) when sampling remote aerosols across the globe.
Xiaolu Zhang, Krystyna Trzepla, Warren White, Sean Raffuse, and Nicole Pauly Hyslop
Atmos. Meas. Tech., 14, 3217–3231, https://doi.org/10.5194/amt-14-3217-2021, https://doi.org/10.5194/amt-14-3217-2021, 2021
Short summary
Short summary
Three models of carbon analyzer were used in the past decade to measure carbonaceous particles from samples collected within the Chemical Speciation Network. This study compares results from these analyzer models to investigate the impact on long-term data from instrument differences. Good agreement was found among the three models for total carbon, organic carbon, and elemental carbon, while the reasons for and implications of some notable differences in their subtractions are investigated.
Hengnan Guo, Zefeng Zhang, Lin Jiang, Junlin An, Bin Zhu, Hanqing Kang, and Jing Wang
Atmos. Meas. Tech., 14, 2441–2450, https://doi.org/10.5194/amt-14-2441-2021, https://doi.org/10.5194/amt-14-2441-2021, 2021
Short summary
Short summary
Visibility is an indicator of atmospheric transparency and is widely used in many research fields. Although efforts have been made to improve the performance of visibility meters, a significant error exists in measured visibility data. This is because current methods of visibility measurement include a false assumption, which leads to the long-term neglect of an important source of visibility errors. Without major adjustments to current methods, it is not possible to obtain reliable data.
Rosaria E. Pileci, Robin L. Modini, Michele Bertò, Jinfeng Yuan, Joel C. Corbin, Angela Marinoni, Bas Henzing, Marcel M. Moerman, Jean P. Putaud, Gerald Spindler, Birgit Wehner, Thomas Müller, Thomas Tuch, Arianna Trentini, Marco Zanatta, Urs Baltensperger, and Martin Gysel-Beer
Atmos. Meas. Tech., 14, 1379–1403, https://doi.org/10.5194/amt-14-1379-2021, https://doi.org/10.5194/amt-14-1379-2021, 2021
Short summary
Short summary
Black carbon (BC), which is an important constituent of atmospheric aerosols, remains difficult to quantify due to various limitations of available methods. This study provides an extensive comparison of co-located field measurements, applying two methods based on different principles. It was shown that both methods indeed quantify the same aerosol property – BC mass concentration. The level of agreement that can be expected was quantified, and some reasons for discrepancy were identified.
Ondřej Tichý, Miroslav Hýža, Nikolaos Evangeliou, and Václav Šmídl
Atmos. Meas. Tech., 14, 803–818, https://doi.org/10.5194/amt-14-803-2021, https://doi.org/10.5194/amt-14-803-2021, 2021
Short summary
Short summary
We present an investigation of the usability of newly developed real-time concentration monitoring systems, which are based on the gamma-ray counting of aerosol filters. These high-resolution data were used for inverse modeling of the 106Ru release in 2017. Our inverse modeling results agree with previously published estimates and provide better temporal resolution of the estimates.
Martine Collaud Coen, Elisabeth Andrews, Alessandro Bigi, Giovanni Martucci, Gonzague Romanens, Frédéric P. A. Vogt, and Laurent Vuilleumier
Atmos. Meas. Tech., 13, 6945–6964, https://doi.org/10.5194/amt-13-6945-2020, https://doi.org/10.5194/amt-13-6945-2020, 2020
Short summary
Short summary
The Mann–Kendall trend test requires prewhitening in the presence of serially correlated data. The effects of five prewhitening methods and time granularity, autocorrelation, temporal segmentation and length of the time series on the statistical significance and the slope are studies for seven atmospheric datasets. Finally, a new algorithm using three prewhitening methods is proposed in order to optimize the power of the test, the amount of erroneous false positive trends and the slope estimate.
Charlotte M. Beall, Dolan Lucero, Thomas C. Hill, Paul J. DeMott, M. Dale Stokes, and Kimberly A. Prather
Atmos. Meas. Tech., 13, 6473–6486, https://doi.org/10.5194/amt-13-6473-2020, https://doi.org/10.5194/amt-13-6473-2020, 2020
Short summary
Short summary
Ice-nucleating particles (INPs) can influence multiple climate-relevant cloud properties. Previous studies report INP observations from precipitation samples that were stored prior to analysis, yet storage protocols vary widely, and little is known about how storage impacts INPs. This study finds that storing samples at −20 °C best preserves INP concentrations and that significant losses of small INPs occur across all storage protocols.
Benjamin A. Nault, Pedro Campuzano-Jost, Douglas A. Day, Hongyu Guo, Duseong S. Jo, Anne V. Handschy, Demetrios Pagonis, Jason C. Schroder, Melinda K. Schueneman, Michael J. Cubison, Jack E. Dibb, Alma Hodzic, Weiwei Hu, Brett B. Palm, and Jose L. Jimenez
Atmos. Meas. Tech., 13, 6193–6213, https://doi.org/10.5194/amt-13-6193-2020, https://doi.org/10.5194/amt-13-6193-2020, 2020
Short summary
Short summary
Collecting particulate matter, or aerosols, onto filters to be analyzed offline is a widely used method to investigate the mass concentration and chemical composition of the aerosol, especially the inorganic portion. Here, we show that acidic aerosol (sulfuric acid) collected onto filters and then exposed to high ammonia mixing ratios (from human emissions) will lead to biases in the ammonium collected onto filters, and the uptake of ammonia is rapid (< 10 s), which impacts the filter data.
Laurent Poulain, Gerald Spindler, Achim Grüner, Thomas Tuch, Bastian Stieger, Dominik van Pinxteren, Jean-Eudes Petit, Olivier Favez, Hartmut Herrmann, and Alfred Wiedensohler
Atmos. Meas. Tech., 13, 4973–4994, https://doi.org/10.5194/amt-13-4973-2020, https://doi.org/10.5194/amt-13-4973-2020, 2020
Short summary
Short summary
The stability and the comparability between ACSM and collocated filter sampling and MPSS measurements was investigated in order to examine the instruments robustness for year-long measurements. Specific attention was paid to the influence of the upper size cutoff diameter to better understand how it might affect the data validation. Recommendations are provided for better on-site quality assurance and quality control of the ACSM, which would be useful for either long-term or intensive campaigns.
Martin Rigler, Luka Drinovec, Gašper Lavrič, Athanasia Vlachou, André S. H. Prévôt, Jean Luc Jaffrezo, Iasonas Stavroulas, Jean Sciare, Judita Burger, Irena Kranjc, Janja Turšič, Anthony D. A. Hansen, and Griša Močnik
Atmos. Meas. Tech., 13, 4333–4351, https://doi.org/10.5194/amt-13-4333-2020, https://doi.org/10.5194/amt-13-4333-2020, 2020
Short summary
Short summary
Carbonaceous aerosols are a large fraction of fine particulate matter. They are extremely diverse, and they directly impact air quality, visibility, cloud formation and public health. In this paper we present a new instrument and new method to measure carbon content in particulate matter in real time and at a high time resolution. The new method was validated in a 1-month winter field campaign in Ljubljana, Slovenia.
Rosa Delia García-Cabrera, Emilio Cuevas-Agulló, África Barreto, Victoria Eugenia Cachorro, Mario Pó, Ramón Ramos, and Kees Hoogendijk
Atmos. Meas. Tech., 13, 2601–2621, https://doi.org/10.5194/amt-13-2601-2020, https://doi.org/10.5194/amt-13-2601-2020, 2020
Short summary
Short summary
Spectral direct UV–visible normal solar irradiance, measured with an EKO MS-711 grating spectroradiometer at the Izaña Atmospheric Observatory (Spain), has been used to determine aerosol optical depth (AOD) at several wavelengths, and has been compared to synchronous AOD measurements from a reference AERONET (Aerosol RObotic NETwork) Cimel sun photometer.
Yan Zheng, Xi Cheng, Keren Liao, Yaowei Li, Yong Jie Li, Ru-Jin Huang, Weiwei Hu, Ying Liu, Tong Zhu, Shiyi Chen, Limin Zeng, Douglas R. Worsnop, and Qi Chen
Atmos. Meas. Tech., 13, 2457–2472, https://doi.org/10.5194/amt-13-2457-2020, https://doi.org/10.5194/amt-13-2457-2020, 2020
Short summary
Short summary
This paper provides important information to help researchers to understand the mass quantification and source apportionment by Aerodyne aerosol mass spectrometers.
Minxing Si, Ying Xiong, Shan Du, and Ke Du
Atmos. Meas. Tech., 13, 1693–1707, https://doi.org/10.5194/amt-13-1693-2020, https://doi.org/10.5194/amt-13-1693-2020, 2020
Short summary
Short summary
The study evaluated the performance of a low-cost PM sensor in ambient conditions and calibrated its readings using simple linear regression (SLR), multiple linear regression (MLR), and two more powerful machine-learning algorithms with random search techniques for the best model architectures. The two machine-learning algorithms are XGBoost and a feedforward neural network (NN).
Zhe Jiang, Minzheng Duan, Huizheng Che, Wenxing Zhang, Teruyuki Nakajima, Makiko Hashimoto, Bin Chen, and Akihiro Yamazaki
Atmos. Meas. Tech., 13, 1195–1212, https://doi.org/10.5194/amt-13-1195-2020, https://doi.org/10.5194/amt-13-1195-2020, 2020
Short summary
Short summary
This study analyzed the aerosol optical properties derived by SKYRAD.pack versions 5.0 and 4.2 using the radiometer measurements over Qionghai and Yucheng in China, which are two new sites of SKYNET. The seasonal variability of the aerosol properties over the two sites were investigated based on SKYRAD.pack V5.0. The validation results provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.
Ernest Nyaku, Robert Loughman, Pawan K. Bhartia, Terry Deshler, Zhong Chen, and Peter R. Colarco
Atmos. Meas. Tech., 13, 1071–1087, https://doi.org/10.5194/amt-13-1071-2020, https://doi.org/10.5194/amt-13-1071-2020, 2020
Short summary
Short summary
This paper shows the importance of the nature of the aerosol phase function used in the retrieval of the stratospheric aerosol extinction from limb scattering measurements. The aerosol phase function is derived from the parameters using either a unimodal lognormal or gamma aerosol size distribution. These two distributions were fitted to the same aerosol concentration measurements at two altitudes, and depending on the nature of the measurements, each distribution shows its strengths.
Fan Mei, Jian Wang, Jennifer M. Comstock, Ralf Weigel, Martina Krämer, Christoph Mahnke, John E. Shilling, Johannes Schneider, Christiane Schulz, Charles N. Long, Manfred Wendisch, Luiz A. T. Machado, Beat Schmid, Trismono Krisna, Mikhail Pekour, John Hubbe, Andreas Giez, Bernadett Weinzierl, Martin Zoeger, Mira L. Pöhlker, Hans Schlager, Micael A. Cecchini, Meinrat O. Andreae, Scot T. Martin, Suzane S. de Sá, Jiwen Fan, Jason Tomlinson, Stephen Springston, Ulrich Pöschl, Paulo Artaxo, Christopher Pöhlker, Thomas Klimach, Andreas Minikin, Armin Afchine, and Stephan Borrmann
Atmos. Meas. Tech., 13, 661–684, https://doi.org/10.5194/amt-13-661-2020, https://doi.org/10.5194/amt-13-661-2020, 2020
Short summary
Short summary
In 2014, the US DOE G1 aircraft and the German HALO aircraft overflew the Amazon basin to study how aerosols influence cloud cycles under a clean condition and around a tropical megacity. This paper describes how to meaningfully compare similar measurements from two research aircraft and identify the potential measurement issue. We also discuss the uncertainty range for each measurement for further usage in model evaluation and satellite data validation.
Cited articles
Air quality index reporting: 64 Fed. Reg 42530, Office of the Federal Register, National Archives and Records Administration, Washington, DC, USA, available at:
https://www.govinfo.gov/app/details/FR-1999-08-04/99-19433/summary (last access: 17 June 2021), 1991.
Al-Thani, H., Koç, M., and Isaifan, R. J.: A review on the direct
effect of particulate atmospheric pollution on materials and its mitigation
for sustainable cities and societies, Environ. Sci. Pollut. R., 25, 27839–27857, https://doi.org/10.1007/s11356-018-2952-8, 2018.
Apte, J. S., Marshall, J. D., Cohen, A. J., and Brauer, M.: Addressing
Global Mortality from Ambient PM2.5, Environ. Sci. Technol., 49, 8057–8066, https://doi.org/10.1021/acs.est.5b01236, 2015.
Ardon-Dryer, K., Dryer, Y., Williams, J. N., and Moghimi, N.: Measurements of PM2.5 with PurpleAir under atmospheric conditions, Atmos. Meas. Tech., 13, 5441–5458, https://doi.org/10.5194/amt-13-5441-2020, 2020.
Barkjohn, K. K.: Dataset Development and Application of a United States wide
correction for PM2.5 data collected with the PurpleAir sensor, U.S. EPA
Office of Research and Development (ORD) [Data set], https://doi.org/10.23719/1522388, 2021.
Barkjohn, K. K., Bergin, M. H., Norris, C., Schauer, J. J., Zhang, Y.,
Black, M., Hu, M., and Zhang, J.: Using Low-cost sensors to Quantify the
Effects of Air Filtration on Indoor and Personal Exposure Relevant PM2.5
Concentrations in Beijing, China, Aerosol Air Qual. Res., 20, 297–313,
https://doi.org/10.4209/aaqr.2018.11.0394, 2020.
Barkjohn, K. K., Norris, C., Cui, X., Fang, L., Zheng, T., Schauer, J. J.,
Zhang, Y., Black, M., Zhang, J., and Bergin, M. H.: Real-time Measurements
of PM2.5 and Ozone to Assess the Effectiveness of Residential Indoor Air
Filtration in Shanghai Homes, Indoor Air, 31, 74–87, https://doi.org/10.1111/ina.12716, 2021.
Bell, M. L., Ebisu, K., and Belanger, K.: Ambient air pollution and low
birth weight in Connecticut and Massachusetts, Environ. Health Persp., 115,
1118–1124, https://doi.org/10.1289/ehp.9759, 2007.
Bi, J., Wildani, A., Chang, H. H., and Liu, Y.: Incorporating Low-Cost
Sensor Measurements into High-Resolution PM2.5 Modeling at a Large Spatial Scale, Environ. Sci. Technol., 54, 2152–2162, https://doi.org/10.1021/acs.est.9b06046, 2020.
Brook, R. D., Rajagopalan, S., Pope, C. A., Brook, J. R., Bhatnagar, A.,
Diez-Roux, A. V., Holguin, F., Hong, Y., Luepker, R. V., Mittleman, M. A.,
Peters, A., Siscovick, D., Smith, S. C., Whitsel, L., and Kaufman, J. D.:
Particulate Matter Air Pollution and Cardiovascular Disease, Circulation,
121, 2331–2378, https://doi.org/10.1161/CIR.0b013e3181dbece1, 2010.
Chakrabarti, B., Fine, P. M., Delfino, R., and Sioutas, C.: Performance
evaluation of the active-flow personal DataRAM PM2.5 mass monitor (Thermo Anderson pDR-1200) designed for continuous personal exposure measurements, Atmos. Environ., 38, 3329–3340, https://doi.org/10.1016/j.atmosenv.2004.03.007, 2004.
Chung, A., Chang, D. P. Y., Kleeman, M. J., Perry, K. D., Cahill, T. A.,
Dutcher, D., McDougall, E. M., and Stroud, K.: Comparison of Real-Time
Instruments Used To Monitor Airborne Particulate Matter,
J. Air Waste Manage., 51, 109–120, https://doi.org/10.1080/10473289.2001.10464254, 2001.
Clements, A. L., Reece, S., Conner, T., and Williams, R.: Observed data
quality concerns involving low-cost air sensors, Atmos. Environ., 3, 100034, https://doi.org/10.1016/j.aeaoa.2019.100034, 2019.
Davison, G., Barkjohn, K. K., Hagler, G. S. W., Holder, A. L., Coefield, S.,
Noonan, C., and Hassett-Sipple, B.: Creating Clean Air Spaces During
Wildland Fire Smoke Episodes: Web Summit Summary, Front. Public Health, 9, 508971, https://doi.org/10.3389/fpubh.2021.508971, 2021.
Day, D. E. and Malm, W. C.: Aerosol light scattering measurements as a
function of relative humidity: a comparison between measurements made at
three different sites, Atmos. Environ., 35, 5169–5176, https://doi.org/10.1016/S1352-2310(01)00320-X, 2001.
Delfino, R. J., Quintana, P. J. E., Floro, J., Gastañaga, V. M., Samimi,
B. S., Kleinman, M. T., Liu, L. J. S., Bufalino, C., Wu, C.-F., and McLaren,
C. E.: Association of FEV1 in asthmatic children with personal and
microenvironmental exposure to airborne particulate matter, Environ. Health Persp., 112, 932–941, https://doi.org/10.1289/ehp.6815, 2004.
Delp, W. W. and Singer, B. C.: Wildfire Smoke Adjustment Factors for
Low-Cost and Professional PM2.5 Monitors with Optical Sensors, Sensors-Basel, 20, 3683, https://doi.org/10.3390/s20133683, 2020.
Di, Q., Dai, L., Wang, Y., Zanobetti, A., Choirat, C., Schwartz, J. D., and
Dominici, F.: Association of Short-term Exposure to Air Pollution With
Mortality in Older Adults, JAMA, 318, 2446–2456, https://doi.org/10.1001/jama.2017.17923, 2017.
Dominici, F., Peng, R. D., Zeger, S. L., White, R. H., and Samet, J. M.:
Particulate air pollution and mortality in the United States: did the risks
change from 1987 to 2000?, Am. J. Epidemiol., 166, 880–888, https://doi.org/10.1093/aje/kwm222, 2007.
Durkin, A., Gonzalez, R., Isaksen, T. B., Walker, E., and Errett, N. A.:
Establishing a Community Air Monitoring Network in a Wildfire Smoke-Prone
Rural Community: The Motivations, Experiences, Challenges, and Ideas of
Clean Air Methow's Clean Air Ambassadors, Int. J. Env. Res. Pub. He., 17, 8393, https://doi.org/10.3390/ijerph17228393, 2020.
Duvall, R. M., Hagler, G. S. W., Clements, A. L., Benedict, K., Barkjohn, K. K., Kilaru, V., Hanley, T., Watkins, N., Kaufman, A., Kamal, A., Reece, S.,
Fransioli, P., Gerboles, M., Gillerman, G., Habre, R., Hannigan, M., Ning,
Z., Papapostolou, V., Pope, R., Quintana, P. J. E., and Lam Snyder, J.:
Deliberating Performance Targets: Follow-on workshop discussing PM10, NO2, CO, and SO2 air sensor targets, Atmos. Environ., 246, 118099, https://doi.org/10.1016/j.atmosenv.2020.118099, 2020.
Feenstra, B., Papapostolou, V., Hasheminassab, S., Zhang, H., Boghossian, B.
D., Cocker, D., and Polidori, A.: Performance evaluation of twelve low-cost
PM2.5 sensors at an ambient air monitoring site, Atmos. Environ.,
216, 116946, https://doi.org/10.1016/j.atmosenv.2019.116946, 2019.
Feinberg, S., Williams, R., Hagler, G. S. W., Rickard, J., Brown, R., Garver, D., Harshfield, G., Stauffer, P., Mattson, E., Judge, R., and Garvey, S.: Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado, Atmos. Meas. Tech., 11, 4605–4615, https://doi.org/10.5194/amt-11-4605-2018, 2018.
Ford, B., Martin, M. V., Zelasky, S. E., Fischer, E. V., Anenberg, S. C.,
Heald, C. L., and Pierce, J. R.: Future Fire Impacts on Smoke
Concentrations, Visibility, and Health in the Contiguous United States,
Geohealth, 2, 229–247, https://doi.org/10.1029/2018gh000144, 2018.
Ford, B., Pierce, J. R., Wendt, E., Long, M., Jathar, S., Mehaffy, J., Tryner, J., Quinn, C., van Zyl, L., L'Orange, C., Miller-Lionberg, D., and Volckens, J.: A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado, Atmos. Meas. Tech., 12, 6385–6399, https://doi.org/10.5194/amt-12-6385-2019, 2019.
Franklin, M., Zeka, A., and Schwartz, J.: Association between PM2.5 and
all-cause and specific-cause mortality in 27 US communities, J. Expo. Sci. Env. Epid., 17, 279–287, https://doi.org/10.1038/sj.jes.7500530, 2007.
Grande, G., Ljungman, P. L. S., Eneroth, K., Bellander, T., and Rizzuto, D.:
Association Between Cardiovascular Disease and Long-term Exposure to Air
Pollution With the Risk of Dementia, JAMA Neurol., 77, 801–809, https://doi.org/10.1001/jamaneurol.2019.4914, 2020.
He, M., Kuerbanjiang, N., and Dhaniyala, S.: Performance characteristics of
the low-cost Plantower PMS optical sensor, Aerosol Sci. Tech., 54, 232–241, https://doi.org/10.1080/02786826.2019.1696015, 2020.
Heintzenberg, J., Wiedensohler, A., Tuch, T. M., Covert, D. S., Sheridan,
P., Ogren, J. A., Gras, J., Nessler, R., Kleefeld, C., Kalivitis, N.,
Aaltonen, V., Wilhelm, R.-T., and Havlicek, M.: Intercomparisons and Aerosol
Calibrations of 12 Commercial Integrating Nephelometers of Three
Manufacturers, J. Atmos. Ocean. Tech., 23, 902–914, https://doi.org/10.1175/jtech1892.1, 2006.
Holder, A. L., Mebust, A. K., Maghran, L. A., McGown, M. R., Stewart, K. E.,
Vallano, D. M., Elleman, R. A., and Baker, K. R.: Field Evaluation of
Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke, Sensors-Basel,
20, 4796, https://doi.org/10.3390/s20174796, 2020.
Holm, S. M., Miller, M. D., and Balmes, J. R.: Health effects of wildfire
smoke in children and public health tools: a narrative review, J. Expo. Sci. Env. Epid., 31, 1–20, https://doi.org/10.1038/s41370-020-00267-4, 2020.
Jayaratne, R., Liu, X., Thai, P., Dunbabin, M., and Morawska, L.: The influence of humidity on the performance of a low-cost air particle mass sensor and the effect of atmospheric fog, Atmos. Meas. Tech., 11, 4883–4890, https://doi.org/10.5194/amt-11-4883-2018, 2018.
Jiao, W., Hagler, G., Williams, R., Sharpe, R., Brown, R., Garver, D., Judge, R., Caudill, M., Rickard, J., Davis, M., Weinstock, L., Zimmer-Dauphinee, S., and Buckley, K.: Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States, Atmos. Meas. Tech., 9, 5281–5292, https://doi.org/10.5194/amt-9-5281-2016, 2016.
Johnson, K. K., Bergin, M. H., Russell, A. G., and Hagler, G. S.: Field test
of several low-cost particulate matter sensors in high and low concentration
urban environments, Aerosol Air Qual. Res., 18, 565–578, 2018.
Karl, T. R. and Koss, W. J.: Regional and National Monthly, Seasonal, and
Annual Temperature Weighted by Area, 1895–1983, Historical Climatology
Series 4–3, National Climatic Data Center, Asheville, NC, USA, 38 pp., 1984.
Kelly, K. E., Whitaker, J., Petty, A., Widmer, C., Dybwad, A., Sleeth, D.,
Martin, R., and Butterfield, A.: Ambient and laboratory evaluation of a
low-cost particulate matter sensor, Environ. Pollut., 221, 491–500,
https://doi.org/10.1016/j.envpol.2016.12.039, 2017.
Kim, S., Park, S., and Lee, J.: Evaluation of Performance of Inexpensive
Laser Based PM2.5 Sensor Monitors for Typical Indoor and Outdoor Hotspots of South Korea, Appl. Sci.-Basel, 9, 1947, https://doi.org/10.3390/app9091947, 2019.
Kosmopoulos, G., Salamalikis, V., Pandis, S. N., Yannopoulos, P., Bloutsos,
A. A., and Kazantzidis, A.: Low-cost sensors for measuring airborne
particulate matter: Field evaluation and calibration at a South-Eastern
European site, Sci. Total Environ., 784, 141396, https://doi.org/10.1016/j.scitotenv.2020.141396, 2020.
Kuula, J., Mäkelä, T., Aurela, M., Teinilä, K., Varjonen, S., González, Ó., and Timonen, H.: Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensors, Atmos. Meas. Tech., 13, 2413–2423, https://doi.org/10.5194/amt-13-2413-2020, 2020a.
Kuula, J., Friman, M., Helin, A., Niemi, J. V., Aurela, M., Timonen, H., and
Saarikoski, S.: Utilization of scattering and absorption-based particulate
matter sensors in the environment impacted by residential wood combustion,
J. Aerosol Sci., 150, 105671, https://doi.org/10.1016/j.jaerosci.2020.105671, 2020b.
Lal, R. M., Das, K., Fan, Y., Barkjohn, K. K., Botchwey, N., Ramaswami, A.,
and Russell, A. G.: Connecting Air Quality with Emotional Well-Being and
Neighborhood Infrastructure in a US City, Environmental Health Insights, 14,
1178630220915488, https://doi.org/10.1177/1178630220915488, 2020.
Levy Zamora, M., Xiong, F., Gentner, D., Kerkez, B., Kohrman-Glaser, J., and
Koehler, K.: Field and Laboratory Evaluations of the Low-Cost Plantower
Particulate Matter Sensor, Environ. Sci. Technol., 53,
838–849, https://doi.org/10.1021/acs.est.8b05174, 2019.
Li, J. Y., Mattewal, S. K., Patel, S., and Biswas, P.: Evaluation of Nine
Low-cost-sensor-based Particulate Matter Monitors, Aerosol Air Qual. Res., 20, 254–270, https://doi.org/10.4209/aaqr.2018.12.0485, 2020.
Liu, X. G., Cheng, Y. F., Zhang, Y. H., Jung, J. S., Sugimoto, N., Chang, S.
Y., Kim, Y. J., Fan, S. J., and Zeng, L. M.: Influences of relative humidity
and particle chemical composition on aerosol scattering properties during
the 2006 PRD campaign, Atmos. Environ., 42, 1525–1536, https://doi.org/10.1016/j.atmosenv.2007.10.077, 2008.
LRAPA: LRAPA PurpleAir Monitor Correction Factor History, available at: https://www.lrapa.org/DocumentCenter/View/4147/PurpleAir-Correction-Summary (last access: 10 June 2021), 2018.
Lu, Y., Giuliano, G., and Habre, R.: Estimating hourly PM2.5 concentrations
at the neighborhood scale using a low-cost air sensor network: A Los Angeles
Case Study, Environ. Res., 195, 110653, https://doi.org/10.1016/j.envres.2020.110653, 2021.
Magi, B. I., Cupini, C., Francis, J., Green, M., and Hauser, C.: Evaluation
of PM2.5 measured in an urban setting using a low-cost optical particle
counter and a Federal Equivalent Method Beta Attenuation Monitor, Aerosol Sci. Tech., 54, 147–159, https://doi.org/10.1080/02786826.2019.1619915, 2019.
Malings, C., Tanzer, R., Hauryliuk, A., Saha, P. K., Robinson, A. L.,
Presto, A. A., and Subramanian, R.: Fine particle mass monitoring with
low-cost sensors: Corrections and long-term performance evaluation, Aerosol Sci. Tech., 54, 160–174, https://doi.org/10.1080/02786826.2019.1623863, 2020.
Mannshardt, E., Benedict, K., Jenkins, S., Keating, M., Mintz, D., Stone, S., and Wayland, R.: Analysis of short-term ozone and PM2.5 measurements: Characteristics and relationships for air sensor messaging, J. Air Waste Manage. Assoc., 67, 462–474, https://doi.org/10.1080/10962247.2016.1251995, 2017.
McFarlane, C., Isevulambire, P. K., Lumbuenamo, R. S., Ndinga, A. M. E.,
Dhammapala, R., Jin, X., McNeill, V. F., Malings, C., Subramanian, R., and
Westervelt, D. M.: First Measurements of Ambient PM2.5 in Kinshasa,
Democratic Republic of Congo and Brazzaville, Republic of Congo Using
Field-calibrated Low-cost Sensors, Aerosol Air Qual. Res., 21, 200619, https://doi.org/10.4209/aaqr.200619, 2021.
Mehadi, A., Moosmüller, H., Campbell, D. E., Ham, W., Schweizer, D.,
Tarnay, L., and Hunter, J.: Laboratory and field evaluation of real-time and
near real-time PM2.5 smoke monitors, J. Air Waste Manage., 70, 158–179, https://doi.org/10.1080/10962247.2019.1654036, 2020.
Morawska, L., Thai, P. K., Liu, X., Asumadu-Sakyi, A., Ayoko, G., Bartonova,
A., Bedini, A., Chai, F., Christensen, B., Dunbabin, M., Gao, J., Hagler, G.
S. W., Jayaratne, R., Kumar, P., Lau, A. K. H., Louie, P. K. K., Mazaheri,
M., Ning, Z., Motta, N., Mullins, B., Rahman, M. M., Ristovski, Z., Shafiei,
M., Tjondronegoro, D., Westerdahl, D., and Williams, R.: Applications of
low-cost sensing technologies for air quality monitoring and exposure
assessment: How far have they gone?, Environ. Int., 116,
286–299, https://doi.org/10.1016/j.envint.2018.04.018, 2018.
Mukherjee, A., Brown, S. G., McCarthy, M. C., Pavlovic, N. R., Stanton, L.
G., Snyder, J. L., D'Andrea, S., and Hafner, H. R.: Measuring Spatial and
Temporal PM2.5 Variations in Sacramento, California, Communities Using a
Network of Low-Cost Sensors, Sensors-Basel, 19, 4701, https://doi.org/10.3390/s19214701, 2019.
NOAA: U.S. Climate Regions, available at: https://www.ncdc.noaa.gov/monitoring-references/maps/us-climate-regions.php (last access: 10 June 2021), 2020.
OR DEQ: 2020 Oregon Annual Ambient Criteria Pollutant Air Monitoring Network Plan, available at: https://www.oregon.gov/deq/FilterDocs/AQmonitoringplan.pdf (last access: 15 June 2021), 2020.
Pawar, H. and Sinha, B.: 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), Aerosol Sci. Tech., 54, 685–703, https://doi.org/10.1080/02786826.2020.1719971, 2020.
Plantower: Digital universal particle concentration sensor: Plantower PMS5003 series data manual, available at: http://www.aqmd.gov/docs/default-source/aq-spec/resources-page/plantower-pms5003-manual_v2-3.pdf?sfvrsn=2 (last access: 10 June 2021), 2016.
Pope III, C. A., Burnett, R. T., Thun, M. J., Calle, E. E., Krewski, D.,
Ito, K., and Thurston, G. D.: Lung cancer, cardiopulmonary mortality, and
long-term exposure to fine particulate air pollution, JAMA, 287, 1132–1141, https://doi.org/10.1001/jama.287.9.1132, 2002.
R Development Core Team: A Language and Environment for Statistical
Computing, Vienna, Austria, 2019.
Robinson, D. L.: Accurate, Low Cost PM2.5 Measurements Demonstrate the Large
Spatial Variation in Wood Smoke Pollution in Regional Australia and Improve
Modeling and Estimates of Health Costs, Atmosphere-Basel, 11, 856, https://doi.org/10.3390/atmos11080856, 2020.
Sayahi, T., Butterfield, A., and Kelly, K. E.: Long-term field evaluation of
the Plantower PMS low-cost particulate matter sensors, Environ. Pollut., 245, 932–940, https://doi.org/10.1016/j.envpol.2018.11.065, 2019.
Schulte, N., Li, X., Ghosh, J. K., Fine, P. M., and Epstein, S. A.:
Responsive high-resolution air quality index mapping using model, regulatory
monitor, and sensor data in real-time, Environ. Res. Lett., 15, 10, https://doi.org/10.1088/1748-9326/abb62b, 2020.
Schwartz, J., Dockery, D. W., and Neas, L. M.: Is daily mortality associated
specifically with fine particles?, J. Air Waste Manage., 46, 927–939,
1996.
Si, M., Xiong, Y., Du, S., and Du, K.: Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods, Atmos. Meas. Tech., 13, 1693–1707, https://doi.org/10.5194/amt-13-1693-2020, 2020.
Snyder, E. G., Watkins, T. H., Solomon, P. A., Thoma, E. D., Williams, R.
W., Hagler, G. S. W., Shelow, D., Hindin, D. A., Kilaru, V. J., and Preuss,
P. W.: The Changing Paradigm of Air Pollution Monitoring, Environ. Sci. Technol., 47, 11369–11377, https://doi.org/10.1021/es4022602, 2013.
Soneja, S., Chen, C., Tielsch, J. M., Katz, J., Zeger, S. L., Checkley, W.,
Curriero, F. C., and Breysse, P. N.: Humidity and gravimetric equivalency
adjustments for nephelometer-based particulate matter measurements of
emissions from solid biomass fuel use in cookstoves, Int. J. Env. Res. Pub. He., 11, 6400–6416, https://doi.org/10.3390/ijerph110606400, 2014.
Stampfer, O., Austin, E., Ganuelas, T., Fiander, T., Seto, E., and Karr, C.:
Use of low-cost PM monitors and a multi-wavelength aethalometer to
characterize PM2.5 in the Yakama Nation reservation, Atmos. Environ., 224, 117292, https://doi.org/10.1016/j.atmosenv.2020.117292, 2020.
Stavroulas, I., Grivas, G., Michalopoulos, P., Liakakou, E., Bougiatioti,
A., Kalkavouras, P., Fameli, K. M., Hatzianastassiou, N., Mihalopoulos, N.,
and Gerasopoulos, E.: Field Evaluation of Low-Cost PM Sensors (Purple Air
PA-II) Under Variable Urban Air Quality Conditions, in Greece, Atmosphere-Basel, 11, 926, https://doi.org/10.3390/atmos11090926, 2020.
Tryner, J., Quinn, C., Windom, B. C., and Volckens, J.: Design and
evaluation of a portable PM2.5 monitor featuring a low-cost sensor in line with an active filter sampler, Environ. Sci.-Proc. Imp., 21, 1403–1415, https://doi.org/10.1039/c9em00234k, 2019.
Tryner, J., L'Orange, C., Mehaffy, J., Miller-Lionberg, D., Hofstetter, J.
C., Wilson, A., and Volckens, J.: Laboratory evaluation of low-cost
PurpleAir PM monitors and in-field correction using co-located portable
filter samplers, Atmos. Environ., 220, 117067, https://doi.org/10.1016/j.atmosenv.2019.117067, 2020a.
Tryner, J., Mehaffy, J., Miller-Lionberg, D., and Volckens, J.: Effects of
aerosol type and simulated aging on performance of low-cost PM sensors,
J. Aerosol Sci., 150, 105654, https://doi.org/10.1016/j.jaerosci.2020.105654, 2020b.
U.S. EPA: PM2.5 Continuous Monitor Comparability Assessments, available at:
https://www.epa.gov/outdoor-air-quality-data/pm25-continuous-monitor-comparability-assessments, last access: 11 March 2020a.
U.S. EPA: PM2.5 Data Quality Dashboard, available at:
https://sti-r-shiny.shinyapps.io/QVA_Dashboard/, last access: 11 March 2020b.
U.S. EPA: List of designated reference and equivalent methods, available at: http://www.epa.gov/ttn/amtic/criteria.html, last access: 15 June 2021.
van Donkelaar, A., Martin, R. V., Brauer, M., Hsu, N. C., Kahn, R. A., Levy,
R. C., Lyapustin, A., Sayer, A. M., and Winker, D. M.: Global Estimates of
Fine Particulate Matter using a Combined Geophysical-Statistical Method with
Information from Satellites, Models, and Monitors, Environ. Sci. Technol., 50, 3762–3772, https://doi.org/10.1021/acs.est.5b05833, 2016.
Wang, W.-C. V., Lung, S.-C. C., Liu, C. H., and Shui, C.-K.: Laboratory
Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost
Particle Sensing Devices in Sensor Networks, Sensors-Basel, 20, 3661, https://doi.org/10.3390/s20133661, 2020.
Wang, Z., Delp, W. W., and Singer, B. C.: Performance of low-cost indoor air
quality monitors for PM2.5 and PM10 from residential sources, Build. Environ., 171, 106654, https://doi.org/10.1016/j.buildenv.2020.106654, 2020.
Williams, R., Duvall, R., Kilaru, V., Hagler, G., Hassinger, L., Benedict,
K., Rice, J., Kaufman, A., Judge, R., Pierce, G., Allen, G., Bergin, M.,
Cohen, R. C., Fransioli, P., Gerboles, M., Habre, R., Hannigan, M., Jack,
D., Louie, P., Martin, N. A., Penza, M., Polidori, A., Subramanian, R., Ray,
K., Schauer, J., Seto, E., Thurston, G., Turner, J., Wexler, A. S., and
Ning, Z.: Deliberating performance targets workshop: Potential paths for
emerging PM2.5 and O3 air sensor progress, Atmos. Environ., 2,
100031, https://doi.org/10.1016/j.aeaoa.2019.100031, 2019.
Zhang, X., Turpin, B. J., McMurry, P. H., Hering, S. V., and Stolzenburg, M.
R.: Mie Theory Evaluation of Species Contributions to 1990 Wintertime
Visibility Reduction in the Grand Canyon, J. Air Waste Manage., 44, 153–162, https://doi.org/10.1080/1073161X.1994.10467244, 1994.
Zheng, T., Bergin, M. H., Johnson, K. K., Tripathi, S. N., Shirodkar, S., Landis, M. S., Sutaria, R., and Carlson, D. E.: Field evaluation of low-cost particulate matter sensors in high- and low-concentration environments, Atmos. Meas. Tech., 11, 4823–4846, https://doi.org/10.5194/amt-11-4823-2018, 2018.
Zikova, N., Masiol, M., Chalupa, D. C., Rich, D. Q., Ferro, A. R., and
Hopke, P. K.: Estimating Hourly Concentrations of PM2.5 across a
Metropolitan Area Using Low-Cost Particle Monitors, Sensors-Basel, 17, 1922, https://doi.org/10.3390/s17081922, 2017.
Zou, Y., Clark, J. D., and May, A. A.: A systematic investigation on the
effects of temperature and relative humidity on the performance of eight
low-cost particle sensors and devices, J. Aerosol Sci., 152, 105715,
https://doi.org/10.1016/j.jaerosci.2020.105715, 2020a.
Zou, Y., Young, M., Chen, J., Liu, J., May, A., and Clark, J. D.: Examining
the functional range of commercially available low-cost airborne particle
sensors and consequences for monitoring of indoor air quality in residences,
Indoor Air, 30, 213–234, https://doi.org/10.1111/ina.12621, 2020b.
Zusman, M., Schumacher, C. S., Gassett, A. J., Spalt, E. W., Austin, E.,
Larson, T. V., Carvlin, G., Seto, E., Kaufman, J. D., and Sheppard, L.:
Calibration of low-cost particulate matter sensors: Model development for a
multi-city epidemiological study, Environ. Int., 134, 105329,
https://doi.org/10.1016/j.envint.2019.105329, 2020.
Short summary
Although widely used, air sensor measurements are often biased. In this work we develop a correction with a relative humidity term that reduces the bias and improves consistency between different United States regions. This correction equation, along with proposed data cleaning criteria, has been applied to PurpleAir PM2.5 measurements across the US on the AirNow Fire and Smoke Map and has the potential to be successfully used in other air quality and public health applications.
Although widely used, air sensor measurements are often biased. In this work we develop a...
