Articles | Volume 16, issue 21
https://doi.org/10.5194/amt-16-5415-2023
© Author(s) 2023. 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-16-5415-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Nov 2023
Research article |
| 13 Nov 2023
| 13 Nov 2023
Spectral analysis approach for assessing the accuracy of low-cost air quality sensor network data
Vijay Kumar
Department of Mathematics, Clarkson University, Potsdam, NY 13699, USA
current address: Department of Environmental Health Sciences, Columbia University, New York, NY 10032, USA
Dinushani Senarathna
Department of Mathematics, Clarkson University, Potsdam, NY 13699, USA
Supraja Gurajala
Department of Computer Science, State University of New York, Potsdam, NY 13676, USA
William Olsen
Department of Civil and Environmental Engineering, Clarkson University, Potsdam, NY 13699, USA
Shantanu Sur
Department of Biology, Clarkson University, Potsdam, NY 13699, USA
Sumona Mondal
Department of Mathematics, Clarkson University, Potsdam, NY 13699, USA
Department of Mechanical & Aerospace Engineering, Clarkson University, Potsdam, NY 13699, USA
Related authors
No articles found.
Dongwook Kim, Pedro Campuzano-Jost, Hongyu Guo, Douglas A. Day, Da Yang, Suresh Dhaniyala, Leah Williams, Philip Croteau, John Jayne, Douglas Worsnop, Rainer Volkamer, and Jose L. Jimenez
Aerosol Research Discuss., https://doi.org/10.5194/ar-2025-6, https://doi.org/10.5194/ar-2025-6, 2025
Preprint under review for AR
Short summary
Short summary
Aerodyne aerosol mass spectrometer (AMS) is widely used to quantitatively measure the chemical compositions of aerosols in the atmosphere. This work presents a comprehensive analysis of the newly developed aircraft inlet system for AMS and tools for aerosol beam diagnostics to minimize particle losses. When the particle beam is properly monitored and aligned, the new inlet system can be operated at higher altitudes while sampling a wider size range of particles than previous versions.
Da Yang, Emmanuel Assaf, Roy Mauldin, Suresh Dhaniyala, and Rainer Volkamer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2390, https://doi.org/10.5194/egusphere-2024-2390, 2024
Short summary
Short summary
Sulfuric acid forms particles in the atmosphere, but the airborne sampling faces challenges due to vapor losses in inlet lines. An innovative aircraft sampling system to sample sulfuric acid from the sea surface into the lower stratosphere (0–15 km) is described and characterized. Our results challenge the widely held view that laminar core sampling is the best strategy to sample condensable vapors, and identify better strategies to sample condensable vapors.
Da Yang, Margarita Reza, Roy Mauldin, Rainer Volkamer, and Suresh Dhaniyala
Atmos. Meas. Tech., 17, 1463–1474, https://doi.org/10.5194/amt-17-1463-2024, https://doi.org/10.5194/amt-17-1463-2024, 2024
Short summary
Short summary
This paper evaluates the performance of an aircraft gas inlet. Here, we use computational fluid dynamics (CFD) and experiments to demonstrate the role of turbulence in determining sampling performance of a gas inlet and identify ideal conditions for inlet operation to minimize gas loss. Experiments conducted in a high-speed wind tunnel under near-aircraft speeds validated numerical results. We believe that the results obtained from this work will greatly inform future gas inlet studies.
Peter K. Peterson, Denis Pöhler, Holger Sihler, Johannes Zielcke, Stephan General, Udo Frieß, Ulrich Platt, William R. Simpson, Son V. Nghiem, Paul B. Shepson, Brian H. Stirm, Suresh Dhaniyala, Thomas Wagner, Dana R. Caulton, Jose D. Fuentes, and Kerri A. Pratt
Atmos. Chem. Phys., 17, 7567–7579, https://doi.org/10.5194/acp-17-7567-2017, https://doi.org/10.5194/acp-17-7567-2017, 2017
Short summary
Short summary
High-spatial-resolution aircraft measurements in the Arctic showed the sustained transport of reactive bromine in a lofted layer via heterogeneous reactions on aerosol particles. This process provides an explanation for free tropospheric reactive bromine and the significant spatial extent of satellite-observed bromine monoxide. The knowledge gained herein improves our understanding of the fate and transport of atmospheric pollutants in the Arctic.
A. Moharreri, L. Craig, P. Dubey, D. C. Rogers, and S. Dhaniyala
Atmos. Meas. Tech., 7, 3085–3093, https://doi.org/10.5194/amt-7-3085-2014, https://doi.org/10.5194/amt-7-3085-2014, 2014
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
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
Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor
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.
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.
Karoline K. Barkjohn, Brett Gantt, and Andrea L. Clements
Atmos. Meas. Tech., 14, 4617–4637, https://doi.org/10.5194/amt-14-4617-2021, https://doi.org/10.5194/amt-14-4617-2021, 2021
Short summary
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.
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
Afrifa-Yamoah, E., Mueller, U. A., Taylor, S., and Fisher, A.: Missing data imputation of high-resolution temporal climate time series data, Meteorol. Appl., 27, e1873, https://doi.org/10.1002/met.1873, 2020. a
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, 2020. a
Blanchard, C. L., Tanenbaum, S., and Lawson, D. R.: Differences between weekday and weekend air pollutant levels in Atlanta; Baltimore; Chicago; Dallas–Fort Worth; Denver; Houston; New York; Phoenix; Washington, DC; and surrounding areas, J. Air Waste Manage., 58, 1598–1615, 2008. a
Bureau, U. C.: US Census Bureau: Public Database, https://www.census.gov/geo/maps-data/data/tallies/tractblock.html (last access: 9 January 2023), 2021. a
Chaipitakporn, C., Athavale, P., Kumar, V., Sathiyakumar, T., Budisic, M., Sur, S., and Mondal, S.: COVID-19 in the United States during pre-vaccination period: Shifting impact of sociodemographic factors and air pollution, Front. Epidemiol., 2, 48, ISSN 2674-1199, https://doi.org/10.3389/fepid.2022.927189, 2022. a
Commodore, A., Wilson, S., Muhammad, O., Svendsen, E., and Pearce, J.: Community-based participatory research for the study of air pollution: A review of motivations, approaches, and outcomes, Environ. Monit. Assess., 189, 1–30, 2017. a
Dilmaghani, S.: Spectral analysis of air quality data, Ph.D. thesis, University of Southern California, 2007. a
EPA: US Environmental Protection Agency (EPA): Publically available air quality data API, https://aqs.epa.gov/aqsweb/documents/data_api.html (last access: 20 October 2022), 2021. a
Eskridge, R. E., Ku, J. Y., Rao, S. T., Porter, P. S., and Zurbenko, I. G.: Separating different scales of motion in time series of meteorological variables, B. Am. Meteorol. Soc., 78, 1473–1484, 1997. a
ESRI: Esri. “Navigation” [basemap], Scale Not Given, “World Navigation Map”, http://www.arcgis.com/home/item.html?id=30e5fe3149c34df1ba922e6f5bbf808f (last access: 9 January 2023), 2021. a
Fang, C., Qiu, J., Li, J., and Wang, J.: Analysis of the meteorological impact on PM2.5 pollution in Changchun based on KZ filter and WRF-CMAQ, Atmos. Environ., 271, 118924, ISSN 1352-2310, https://doi.org/10.1016/j.atmosenv.2021.118924, 2022. a
Giordano, M. R., Malings, C., Pandis, S. N., Presto, A. A., McNeill, V. F., Westervelt, D. M., Beekmann, M., and Subramanian, R.: From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors, J. Aerosol Sci., 158, 105833, https://doi.org/10.1016/j.jaerosci.2021.105833, 2021. a
Gupta, P., Doraiswamy, P., Levy, R., Pikelnaya, O., Maibach, J., Feenstra, B., Polidori, A., Kiros, F., and Mills, K.: Impact of California fires on local and regional air quality: the role of a low-cost sensor network and satellite observations, GeoHealth, 2, 172–181, 2018. a
Hadeed, S. J., O'Rourke, M. K., Burgess, J. L., Harris, R. B., and Canales, R. A.: Imputation methods for addressing missing data in short-term monitoring of air pollutants, Sci. Total Environ., 730, 139–140, 2020. a
Hirabayashi, S. and Kroll, C. N.: Single imputation method of missing air quality data for i-tree eco analyses in the conterminous united states, Retrieved 1 January 2021, http://www.itreetools.org/eco/resources/Single_imputation_method_of_missing_air_quality_data_for_i-Tree_Eco_analyses_in_the_conterminous_United_States.pdf (last access: 1 December 2021), 2017. a
Hogrefe, C., Rao, S. T., Zurbenko, I. G., and Porter, P. S.: Interpreting the information in ozone observations and model predictions relevant to regulatory policies in the eastern United States, B. Am. Meteorol. Soc., 81, 2083–2106, 2000. a
Hollaway, M., Wild, O., Yang, T., Sun, Y., Xu, W., Xie, C., Whalley, L., Slater, E., Heard, D., and Liu, D.: Photochemical impacts of haze pollution in an urban environment, Atmos. Chem. Phys., 19, 9699–9714, https://doi.org/10.5194/acp-19-9699-2019, 2019. a
Imtiaz, S. A. and Shah, S. L.: Treatment of missing values in process data analysis, The Can. J. Chem. Eng., 86, 838–858, 2008. a
IQAIR: Air quality in Chicago: Public Database, https://www.iqair.com/us/usa/illinois/chicago (last access: 20 October 2022), 2020. a
James, G., Witten, D., Hastie, T., and Tibshirani, R.: An introduction to statistical learning, Vol. 112, Springer, 2013. a
Jia, M., Zhao, T., Cheng, X., Gong, S., Zhang, X., Tang, L., Liu, D., Wu, X., Wang, L., and Chen, Y.: Inverse relations of PM2.5 and O3 in air compound pollution between cold and hot seasons over an urban area of east China, Atmosphere, 8, 59, https://doi.org/10.3390/atmos8030059, 2017. a
Kang, D., Mathur, R., Rao, S. T., and Yu, S.: Bias adjustment techniques for improving ozone air quality forecasts, J. Geophys. Res.-Atmos., 113, D23308, https://doi.org/10.1029/2008jd010151, 2008. a
Kim, T., Kim, J., Yang, W., Lee, H., and Choo, J.: Missing Value Imputation of Time-Series Air-Quality Data via Deep Neural Networks, Int. J. Environ. Res. Pu., 18, 12213, https://doi.org/10.3390/ijerph182212213, 2021. a
Kumar, V.: vijaykumar18/Airquality-Spectral-Analysis,
Airquality-Spectral-Analysis, GitHub [data set], https://github.com/vijaykumar18/Airquality-Spectral-Analysis (last access: 29 February 2023), 2023. a
Airquality-Spectral-Analysis, GitHub [data set], https://github.com/vijaykumar18/Airquality-Spectral-Analysis (last access: 29 February 2023), 2023. a
Kuula, J., Mäkelä, T., Hillamo, R., and Timonen, H.: Response characterization of an inexpensive aerosol sensor, Sensors, 17, 2915, https://doi.org/10.3390/s17122915, 2017. a
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, 2020. a
Landrigan, P. J., Fuller, R., Acosta, N. J. R., Adeyi, O., Arnold, R., Basu, N. N., Baldé, A. B., Bertollini, R., Bose-O’Reilly, S., Boufford, J. I., Breysse, P. N., Chiles, T., Mahidol, C., Coll-Seck, A. M., Cropper, M. L., Fobil, J., Fuster, V., Greenstone, M., Haines, A., Hanrahan, D., Hunter, D., Khare, M., Krupnick, A., Lanphear, B., Lohani, B., Martin, K., Mathiasen, K. V., McTeer, M. A., Murray, C. J. L., Ndahimananjara, J. D., Perera, F., Potoˇcnik, J., Preker, A. S., Ramesh, J., Rockström, J., Salinas, C., Samson, L. D., Sandilya, K., Sly, P. D., Smith, K. R., Steiner, A., Stewart, R. B., Suk, W. A., van Schayck, O. C. P., Yadama, G. N., Yumkella, K., and Zhong, M.: The Lancet Commission on pollution and health, The Lancet, 391, 462–512, https://doi.org/10.1016/s0140-6736(17)32345-0, 2018. a
Lewis, T. C., Robins, T. G., Dvonch, J. T., Keeler, G. J., Yip, F. Y., Mentz, G. B., Lin, X., Parker, E. A., Israel, B. A., Gonzalez, L., and Hill, Y.: Air Pollution–Associated Changes in Lung Function among Asthmatic Children in Detroit, Environ. Health Perspect., 113, 1068–1075, https://doi.org/10.1289/ehp.7533, 2005. a
Li, L., Losser, T., Yorke, C., and Piltner, R.: Fast inverse distance weighting-based spatiotemporal interpolation: a web-based application of interpolating daily fine particulate matter PM2.5 in the contiguous US using parallel programming and kd tree, Int. J. Environ. Res. Pub. Health, 11, 9101–9141, 2014. a
Li, T., Hu, R., Chen, Z., Li, Q., Huang, S., Zhu, Z., and Zhou, L.-F.: Fine particulate matter (PM2.5): The culprit for chronic lung diseases in China, Chronic Diseases and Translational Medicine, 4, 176–186, 2018. a
Lian, L. and Ma, H.: FDI and economic growth in western region of China and dynamic mechanism: Based on time-series data from 1986 to 2010, International Business Research, 6, 180, 2013. a
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. Technol., 54, 147–159, 2020. a
Mei, H., Han, P., Wang, Y., Zeng, N., Liu, D., Cai, Q., Deng, Z., Wang, Y., Pan, Y., and Tang, X.: Field evaluation of low-cost particulate matter sensors in Beijing, Sensors, 20, 4381, https://doi.org/10.3390/s20164381, 2020. a
Milanchus, M. L., Rao, S. T., and Zurbenko, I. G.: Evaluating the effectiveness of ozone management efforts in the presence of meteorological variability, J. Air Waste Manage., 48, 201–215, 1998. a
Milando, C., Huang, L., and Batterman, S.: Trends in PM2.5 emissions, concentrations and apportionments in Detroit and Chicago, Atmos. Environ., 129, 197–209, 2016. a
Mondal, S., Chaipitakporn, C., Kumar, V., Wangler, B., Gurajala, S., Dhaniyala, S., and Sur, S.: COVID-19 in New York state: Effects of demographics and air quality on infection and fatality, Sci. Total Environ., 807, 150536, https://doi.org/10.1016/j.scitotenv.2021.150536, 2022. a
Noble, C. A., Vanderpool, R. W., Peters, T. M., McElroy, F. F., Gemmill, D. B., and Wiener, R. W.: Federal reference and equivalent methods for measuring fine particulate matter, Aerosol Sci. Technol., 34, 457–464, 2001. a
Ostro, B., Broadwin, R., Green, S., Feng, W.-Y., and Lipsett, M.: Fine particulate air pollution and mortality in nine California counties: results from CALFINE, Environ. Health Persp., 114, 29–33, 2006. a
Ouimette, J. R., Malm, W. C., Schichtel, B. A., Sheridan, P. J., Andrews, E., Ogren, J. A., and Arnott, W. P.: Evaluating the PurpleAir monitor as an aerosol light scattering instrument, Atmos. Meas. Tech., 15, 655–676, https://doi.org/10.5194/amt-15-655-2022, 2022. a, b
Ouimette, J. R., Malm, W. C., Schichtel, B. A., Sheridan, P. J., Andrews, E., Ogren, J. A., and Arnott, W. P.: Evaluating the PurpleAir monitor as an aerosol light scattering instrument, Atmospheric Measurement Techniques, 15, 655–676, 2022. a
PA: Purple Air: Public Database of sensors installed in entire world, https://map.purpleair.com/1/mAQI/a10/p604800/cC0#11.44/41.8363/-87.6973 (last access: 10 February 2023), 2021. a
PurpleAir: PurpleAir: PublicLab, https://publiclab.org/wiki/purpleair (last access: 10 February 2023), 2020. a
Raaschou-Nielsen, O., Andersen, Z. J., Beelen, R., Samoli, E., Stafoggia, M., Weinmayr, G., Hoffmann, B., Fischer, P., Nieuwenhuijsen, M.J., Brunekreef, B., Xun, W. W., Katsouyanni, K., Dimakopoulou, K., Sommar, J., Forsberg, B., Modig, L., Oudin, A., Oftedal, B., Schwarze, P. E., and Nafstad, P.: Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE). The Lancet Oncology, [online] 14, 813–822, https://doi.org/10.1016/s1470-2045(13)70279-1, 2013. a
Rivera-Muñoz, L. M., Gallego-Villada, J. D., Giraldo-Forero, A. F., and Martinez-Vargas, J. D.: Missing data estimation in a low-cost sensor network for measuring air quality: A case study in Aburrá Valley, Water, Air, Soil Pollut., 232, 1–15, 2021. a
Sá, E., Tchepel, O., Carvalho, A., and Borrego, C.: Meteorological driven changes on air quality over Portugal: a KZ filter application, Atmos. Pollut. Res., 6, 979–989, 2015. a
Samoli, E., Analitis, A., Touloumi, G., Schwartz, J., Anderson, H. R., Sunyer, J., Bisanti, L., Zmirou, D., Vonk, J. M., Pekkanen, J., Goodman, P., Paldy, A., Schindler, C., and Klea, K.: Estimating the exposure–response relationships between particulate matter and mortality within the APHEA multicity project, Environ. Health Perspect., 113, 88–95, https://doi.org/10.1289/ehp.7387, 2005 a
Saputra, M. D., Hadi, A. F., Riski, A., and Anggraeni, D.: Handling Missing Values and Unusual Observations in Statistical Downscaling Using Kalman Filter, J. Phys. Conference Series, 1863, 012 035, https://doi.org/10.1088/1742-6596/1863/1/012035, 2021. a
Sayahi, T., Kaufman, D., Becnel, T., Kaur, K., Butterfield, A., Collingwood, S., Zhang, Y., Gaillardon, P.-E., and Kelly, K.: Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors, Environ. Pollut., 255, 113131, https://doi.org/10.1016/j.envpol.2019.113131, 2019. a
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, 11, 926, https://doi.org/10.3390/atmos11090926, 2020. a
Sun, L.: Spectral and time-frequency analyses of freeway traffic flow, J. Adv. Transport., 48, 821–857, 2014. a
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, 2020. a
Wallace, L., Bi, J., Ott, W. R., Sarnat, J., and Liu, Y.: Calibration of low-cost PurpleAir outdoor monitors using an improved method of calculating PM2.5, Atmos. Environ., 256, 118432, https://doi.org/10.1016/j.atmosenv.2021.118432, 2021. a
Wang, X., Wang, L., Liu, Y., Hu, S., Liu, X., and Dong, Z.: A data-driven air quality assessment method based on unsupervised machine learning and median statistical analysis: The case of China, J. Clean. Product., 328, 129531, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2021.129531, 2021. a
Wang, Y., Li, J., Jing, H., Zhang, Q., Jiang, J., and Biswas, P.: Laboratory evaluation and calibration of three low-cost particle sensors for particulate matter measurement, Aerosol Sci. Technol., 49, 1063–1077, 2015. a
Wijesekara, W. M. L. K. N. and Liyanage, L.: Comparison of imputation methods for missing values in air pollution data: Case study on Sydney air quality index, in: Advances in Information and Communication: Proceedings of the 2020 Future of Information and Communication Conference (FICC), Volume 2, 257–269 pp., Springer International Publishing, 2020. a
Woodall, G. M., Hoover, M. D., Williams, R., Benedict, K., Harper, M., Soo, J.-C., Jarabek, A. M., Stewart, M. J., Brown, J. S., Hulla, J. E., Caudill, M., Clements, A. L., Kaufman, A., Parker, A. J., Keating, M., Balshaw, D., Garrahan, K., Burton, L., Batka, S., Limaye, V. S., Hakkinen, P. J., and Thompson, B.: Interpreting mobile and handheld air sensor readings in relation to air quality standards and health effect reference values: Tackling the challenges, Atmosphere, 8, 182, https://doi.org/10.3390/atmos8100182, 2017. a
Wu, X., Nethery, R. C., Sabath, B. M., Braun, D., and Dominici, F.: Exposure to air pollution and COVID-19 mortality in the United States. MedRxiv, https://doi.org/10.1101/2020.04.05.20054502, 2020. a
Xing, Y.-F., Xu, Y.-H., Shi, M.-H., and Lian, Y.-X.: The impact of PM2.5 on the human respiratory system, J. Thorac. Dis., 8, E69, https://doi.org/10.3978/j.issn.2072-1439.2016.01.19, 2016. a
Zhang, Z., Kim, S.-J., and Ma, Z.: Significant decrease of PM2.5 in Beijing based on long-term records and Kolmogorov-Zurbenko filter approach, https://doi.org/10.4209/aaqr.2017.01.0011, 2018. a, b
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. a
Zhou, X., Josey, K., Kamareddine, L., Caine, M. C., Liu, T., Mickley, L. J., Cooper, M., and Dominici, F.: Excess of COVID-19 cases and deaths due to fine particulate matter exposure during the 2020 wildfires in the United States, Sci. Adv., 7, eabi8789, https://doi.org/10.1126/sciadv.abi8789, 2021. a
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.
Low-cost sensors are becoming increasingly important in air quality monitoring due to their...
