Articles | Volume 9, issue 6
https://doi.org/10.5194/amt-9-2615-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-2615-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Jun 2016
Research article |
| 21 Jun 2016
An automated baseline correction protocol for infrared spectra of atmospheric aerosols collected on polytetrafluoroethylene (Teflon) filters
Adele Kuzmiakova
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
Ann M. Dillner
University of California, Davis, California, USA
Satoshi Takahama
CORRESPONDING AUTHOR
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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Emily Y. Li, Amir Yazdani, Ann M. Dillner, Guofeng Shen, Wyatt M. Champion, James J. Jetter, William T. Preston, Lynn M. Russell, Michael D. Hays, and Satoshi Takahama
Atmos. Meas. Tech., 17, 2401–2413, https://doi.org/10.5194/amt-17-2401-2024, https://doi.org/10.5194/amt-17-2401-2024, 2024
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Infrared spectroscopy is a cost-effective measurement technique to characterize the chemical composition of organic aerosol emissions. This technique differentiates the organic matter emission factor from different fuel sources by their characteristic functional groups. Comparison with collocated measurements suggests that polycyclic aromatic hydrocarbon concentrations in emissions estimated by conventional chromatography may be substantially underestimated.
Marife B. Anunciado, Miranda De Boskey, Laura Haines, Katarina Lindskog, Tracy Dombek, Satoshi Takahama, and Ann M. Dillner
Atmos. Meas. Tech., 16, 3515–3529, https://doi.org/10.5194/amt-16-3515-2023, https://doi.org/10.5194/amt-16-3515-2023, 2023
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Organic sulfur compounds are used to identify sources and atmospheric processing of aerosol. Our paper evaluates the potential of using a non-destructive measurement technique to measure organic sulfur compounds in filter samples by assessing their chemical stability over time. Some were stable, but some evaporated or changed chemically. Future work includes evaluating the stability and potential interference of multiple organic sulfur compounds in laboratory mixtures and ambient aerosol.
Amir Yazdani, Satoshi Takahama, John K. Kodros, Marco Paglione, Mauro Masiol, Stefania Squizzato, Kalliopi Florou, Christos Kaltsonoudis, Spiro D. Jorga, Spyros N. Pandis, and Athanasios Nenes
Atmos. Chem. Phys., 23, 7461–7477, https://doi.org/10.5194/acp-23-7461-2023, https://doi.org/10.5194/acp-23-7461-2023, 2023
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Organic aerosols directly emitted from wood and pellet stove combustion are found to chemically transform (approximately 15 %–35 % by mass) under daytime aging conditions simulated in an environmental chamber. A new marker for lignin-like compounds is found to degrade at a different rate than previously identified biomass burning markers and can potentially provide indication of aging time in ambient samples.
Nikunj Dudani and Satoshi Takahama
Atmos. Meas. Tech., 15, 4693–4707, https://doi.org/10.5194/amt-15-4693-2022, https://doi.org/10.5194/amt-15-4693-2022, 2022
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We designed and fabricated an aerosol collector with high collection efficiency that enables quantitative infrared spectroscopy analysis. By collecting particles on optical windows, typical substrate interferences are eliminated. New methods for fabricating aerosol devices using 3D printing with post-treatment to reduce the time and cost of prototyping are described.
Amir Yazdani, Nikunj Dudani, Satoshi Takahama, Amelie Bertrand, André S. H. Prévôt, Imad El Haddad, and Ann M. Dillner
Atmos. Meas. Tech., 15, 2857–2874, https://doi.org/10.5194/amt-15-2857-2022, https://doi.org/10.5194/amt-15-2857-2022, 2022
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While the aerosol mass spectrometer provides high-time-resolution characterization of the overall extent of oxidation, the extensive fragmentation of molecules and specificity of the technique have posed challenges toward deeper understanding of molecular structures in aerosols. This work demonstrates how functional group information can be extracted from a suite of commonly measured mass fragments using collocated infrared spectroscopy measurements.
Bruno Debus, Andrew T. Weakley, Satoshi Takahama, Kathryn M. George, Anahita Amiri-Farahani, Bret Schichtel, Scott Copeland, Anthony S. Wexler, and Ann M. Dillner
Atmos. Meas. Tech., 15, 2685–2702, https://doi.org/10.5194/amt-15-2685-2022, https://doi.org/10.5194/amt-15-2685-2022, 2022
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In the US, routine particulate matter composition is measured on samples collected on three types of filter media and analyzed using several techniques. We propose an alternate approach that uses one analytical technique, Fourier transform-infrared spectroscopy (FT-IR), and one filter type to measure the chemical composition of particulate matter in a major US monitoring network. This method could be used to add low-cost sites to the network, fill-in missing data, or for quality control.
Mária Lbadaoui-Darvas, Satoshi Takahama, and Athanasios Nenes
Atmos. Chem. Phys., 21, 17687–17714, https://doi.org/10.5194/acp-21-17687-2021, https://doi.org/10.5194/acp-21-17687-2021, 2021
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Aerosol–cloud interactions constitute the most uncertain contribution to climate change. The uptake kinetics of water by aerosol is a central process of cloud droplet formation, yet its molecular-scale mechanism is unknown. We use molecular simulations to study this process for phase-separated organic particles. Our results explain the increased cloud condensation activity of such particles and can be generalized over various compositions, thus possibly serving as a basis for future models.
Amir Yazdani, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 14, 4805–4827, https://doi.org/10.5194/amt-14-4805-2021, https://doi.org/10.5194/amt-14-4805-2021, 2021
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We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM2.5 currently collected in existing air pollution monitoring networks and field campaigns.
Amir Yazdani, Nikunj Dudani, Satoshi Takahama, Amelie Bertrand, André S. H. Prévôt, Imad El Haddad, and Ann M. Dillner
Atmos. Chem. Phys., 21, 10273–10293, https://doi.org/10.5194/acp-21-10273-2021, https://doi.org/10.5194/acp-21-10273-2021, 2021
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Functional group compositions of primary and aged aerosols from wood burning and coal combustion sources from chamber experiments are interpreted through compounds present in the fuels and known gas-phase oxidation products. Infrared spectra of aged wood burning in the chamber and ambient biomass burning samples reveal striking similarities, and a new method for identifying burning-impacted samples in monitoring network measurements is presented.
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
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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.
Eirini Boleti, Christoph Hueglin, Stuart K. Grange, André S. H. Prévôt, and Satoshi Takahama
Atmos. Chem. Phys., 20, 9051–9066, https://doi.org/10.5194/acp-20-9051-2020, https://doi.org/10.5194/acp-20-9051-2020, 2020
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Long-term temporal evolution of ozone concentrations between 2000 and 2015 in Europe was estimated using a signal decomposition technique. The seasonal cycles are correlated with local climate conditions and vary according to geographic region, while ozone levels are indicative of distance to emission sources. The site's environment plays a key role in ozone trends, with the most polluted environments showing the least reduction in ozone, while in less polluted areas ozone has decreased.
Charlotte Bürki, Matteo Reggente, Ann M. Dillner, Jenny L. Hand, Stephanie L. Shaw, and Satoshi Takahama
Atmos. Meas. Tech., 13, 1517–1538, https://doi.org/10.5194/amt-13-1517-2020, https://doi.org/10.5194/amt-13-1517-2020, 2020
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Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Alexandra J. Boris, Satoshi Takahama, Andrew T. Weakley, Bruno M. Debus, Carley D. Fredrickson, Martin Esparza-Sanchez, Charlotte Burki, Matteo Reggente, Stephanie L. Shaw, Eric S. Edgerton, and Ann M. Dillner
Atmos. Meas. Tech., 12, 5391–5415, https://doi.org/10.5194/amt-12-5391-2019, https://doi.org/10.5194/amt-12-5391-2019, 2019
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Organic species are abundant in atmospheric particle-phase (aerosol) pollution and originate from a variety of biogenic and anthropogenic sources. Infrared spectrometry of filter-based atmospheric particle samples can afford a direct measurement of the particulate organic matter concentration and a characterization of its composition. This work discusses recent method improvements and compositions measured in samples from the SouthEastern Aerosol Research and Characterization (SEARCH) network.
Matteo Reggente, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 12, 2287–2312, https://doi.org/10.5194/amt-12-2287-2019, https://doi.org/10.5194/amt-12-2287-2019, 2019
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We compare state-of-the-art models for predicting functional group composition in atmospheric particulate matter across urban and rural samples collected in a US monitoring network. While trends across models are consistent, absolute abundances can be sensitive to selection of calibration standards, spectral processing procedures, and calibration algorithms. Recommendations for further method development for reducing uncertainties are outlined.
Matteo Reggente, Rudolf Höhn, and Satoshi Takahama
Atmos. Meas. Tech., 12, 2313–2329, https://doi.org/10.5194/amt-12-2313-2019, https://doi.org/10.5194/amt-12-2313-2019, 2019
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The infrared spectra of atmospheric particles are rich in chemical information but require sophisticated statistical methods to extract information on account of their complex absorption profiles. We present an open software suite which makes current algorithms used for analysis of such spectra available to the community, with a browser-based interface for general users and modular architecture that facilitates addition of new methods by developers.
Satoshi Takahama, Ann M. Dillner, Andrew T. Weakley, Matteo Reggente, Charlotte Bürki, Mária Lbadaoui-Darvas, Bruno Debus, Adele Kuzmiakova, and Anthony S. Wexler
Atmos. Meas. Tech., 12, 525–567, https://doi.org/10.5194/amt-12-525-2019, https://doi.org/10.5194/amt-12-525-2019, 2019
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Mid-infrared spectra of particulate matter (PM) samples are complex but chemically informative and present an opportunity for cost-effective measurement of PM provided that quantitative calibration models can be built. We review an emerging strategy for building statistical calibration models using collocated measurements, interpreting the physical bases for such models and evaluating the suitability of existing calibration models to new samples.
Satoshi Takahama and Giulia Ruggeri
Atmos. Chem. Phys., 17, 4433–4450, https://doi.org/10.5194/acp-17-4433-2017, https://doi.org/10.5194/acp-17-4433-2017, 2017
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We formalize a method for classifying carbon atoms in organic aerosols according to their functionalization. This conceptual approach allows estimation of carbon mass from functional group measurements, which previously required a series of assumptions that were not well constrained. We describe how the proposed strategy can lead to better comparisons among functional group measurements, chemically explicit model simulations, and other measurements.
Rob L. Modini and Satoshi Takahama
Atmos. Meas. Tech., 9, 3337–3354, https://doi.org/10.5194/amt-9-3337-2016, https://doi.org/10.5194/amt-9-3337-2016, 2016
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Aerosol measurement techniques with high detection limits often result in poorly time-resolved measurements. We investigated sampling strategies and post-processing methods for constructing hourly resolved aerosol concentration time series from samples collected for 4 to 8 h. We show that this is an effective way to increase measurement time resolution, and that under realistic experimental conditions, simple methods can perform as well as more sophisticated methods.
Satoshi Takahama, Giulia Ruggeri, and Ann M. Dillner
Atmos. Meas. Tech., 9, 3429–3454, https://doi.org/10.5194/amt-9-3429-2016, https://doi.org/10.5194/amt-9-3429-2016, 2016
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We introduce the application of statistical algorithms that allow us to associate various dimensions of aerosol composition to vibrational modes measured by infrared absorption spectroscopy. We demonstrate their use on four organic functional groups for which absorption bands are known and extend the application to interpret bands associated with ambient organic carbon and elemental carbon quantified by an independent measurement technique that is widely used in aerosol monitoring networks.
Giulia Ruggeri, Fabian A. Bernhard, Barron H. Henderson, and Satoshi Takahama
Atmos. Chem. Phys., 16, 8729–8747, https://doi.org/10.5194/acp-16-8729-2016, https://doi.org/10.5194/acp-16-8729-2016, 2016
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Functional groups provide an intermediate level of chemical resolution between full molecular speciation and elemental composition for describing complex mixtures and can be a useful metric in model–measurement comparison of reaction kinetics and secondary organic aerosol formation. We introduce tools to facilitate such comparisons and demonstrate its application in study of the photooxidation of two precursor volatile organic compounds and the gas–particle partitioning of their products.
Giulia Ruggeri and Satoshi Takahama
Atmos. Chem. Phys., 16, 4401–4422, https://doi.org/10.5194/acp-16-4401-2016, https://doi.org/10.5194/acp-16-4401-2016, 2016
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We present a set of tools for mapping molecular information to functional group composition. This allows us to reduce the complexity of representing the organic aerosol composition, as it consists of hundreds of thousands of different compounds. We describe the tools and methods for validation, and demonstrate several applications in which this tool can facilitate measurement intercomparisons and chemical modeling of aerosol chemistry.
Matteo Reggente, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 9, 441–454, https://doi.org/10.5194/amt-9-441-2016, https://doi.org/10.5194/amt-9-441-2016, 2016
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Organic carbon and elemental carbon are major components of atmospheric PM. Typically they are measured using destructive and relatively expensive methods (e.g., TOR). We aim to reduce the operating costs of large air quality monitoring networks using FT-IR spectra of ambient PTFE filters and PLS regression. We achieve accurate predictions for models (calibrated in 2011) that use samples collected at the same or different sites of the calibration data set and in a different year (2013).
B. R. Ayres, H. M. Allen, D. C. Draper, S. S. Brown, R. J. Wild, J. L. Jimenez, D. A. Day, P. Campuzano-Jost, W. Hu, J. de Gouw, A. Koss, R. C. Cohen, K. C. Duffey, P. Romer, K. Baumann, E. Edgerton, S. Takahama, J. A. Thornton, B. H. Lee, F. D. Lopez-Hilfiker, C. Mohr, P. O. Wennberg, T. B. Nguyen, A. Teng, A. H. Goldstein, K. Olson, and J. L. Fry
Atmos. Chem. Phys., 15, 13377–13392, https://doi.org/10.5194/acp-15-13377-2015, https://doi.org/10.5194/acp-15-13377-2015, 2015
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This paper reports atmospheric gas- and aerosol-phase field measurements from the southeastern United States in summer 2013 to demonstrate that the oxidation of biogenic volatile organic compounds by nitrate radical produces a substantial amount of secondary organic aerosol in this region. This process, driven largely by monoterpenes, results in a comparable aerosol nitrate production rate to inorganic nitrate formation by heterogeneous uptake of HNO3 onto dust particles.
A. M. Dillner and S. Takahama
Atmos. Meas. Tech., 8, 4013–4023, https://doi.org/10.5194/amt-8-4013-2015, https://doi.org/10.5194/amt-8-4013-2015, 2015
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Elemental carbon (EC), a constituent of atmospheric particulate matter (PM), adversely affects climate, visibility and human health. EC is measured in PM monitoring networks world-wide but the method is expensive and destructive to the samples. Here, methods are presented to accurately predict EC using Fourier transform infrared (FT-IR) analysis which is inexpensive and non-destructive. This method complements measurements of organic carbon and organic functional groups made using FT-IR.
H. M. Allen, D. C. Draper, B. R. Ayres, A. Ault, A. Bondy, S. Takahama, R. L. Modini, K. Baumann, E. Edgerton, C. Knote, A. Laskin, B. Wang, and J. L. Fry
Atmos. Chem. Phys., 15, 10669–10685, https://doi.org/10.5194/acp-15-10669-2015, https://doi.org/10.5194/acp-15-10669-2015, 2015
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We report ion chromatographic measurements of gas- and aerosol-phase inorganic species at the SOAS 2013 field study. Our particular focus is on inorganic nitrate aerosol formation via HNO3 uptake onto coarse-mode dust and sea salt particles, which we find to be the dominant source of episodic inorganic nitrate at this site, due to the high acidity of the particles preventing formation of NH4NO3. We calculate a production rate of inorganic nitrate aerosol.
A. M. Dillner and S. Takahama
Atmos. Meas. Tech., 8, 1097–1109, https://doi.org/10.5194/amt-8-1097-2015, https://doi.org/10.5194/amt-8-1097-2015, 2015
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We demonstrate the feasibility of using FT-IR spectra of aerosols and a multivariate calibration to estimate organic carbon (OC) from thermal-optical reflectance analysis. Using 800 IMPROVE samples, we establish that prediction error can be explained by differences in distributions of OC and aerosol composition between calibration and test set. This work is an initial step in proposing a non-destructive analysis method that can reduce the operating costs of large air quality monitoring networks.
Y. You, V. P. Kanawade, J. A. de Gouw, A. B. Guenther, S. Madronich, M. R. Sierra-Hernández, M. Lawler, J. N. Smith, S. Takahama, G. Ruggeri, A. Koss, K. Olson, K. Baumann, R. J. Weber, A. Nenes, H. Guo, E. S. Edgerton, L. Porcelli, W. H. Brune, A. H. Goldstein, and S.-H. Lee
Atmos. Chem. Phys., 14, 12181–12194, https://doi.org/10.5194/acp-14-12181-2014, https://doi.org/10.5194/acp-14-12181-2014, 2014
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Amiens play important roles in atmospheric secondary aerosol formation and human health, but the fast response measurements of amines are lacking. Here we show measurements in a southeastern US forest and a moderately polluted midwestern site. Our results show that gas to particle conversion is an important process that controls ambient amine concentrations and that biomass burning is an important source of amines.
A. L. Corrigan, L. M. Russell, S. Takahama, M. Äijälä, M. Ehn, H. Junninen, J. Rinne, T. Petäjä, M. Kulmala, A. L. Vogel, T. Hoffmann, C. J. Ebben, F. M. Geiger, P. Chhabra, J. H. Seinfeld, D. R. Worsnop, W. Song, J. Auld, and J. Williams
Atmos. Chem. Phys., 13, 12233–12256, https://doi.org/10.5194/acp-13-12233-2013, https://doi.org/10.5194/acp-13-12233-2013, 2013
Related subject area
Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization
Towards a hygroscopic growth calibration for low-cost PM2.5 sensors
Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry
Machine learning approaches for automatic classification of single-particle mass spectrometry data
A searchable database and mass spectral comparison tool for the Aerosol Mass Spectrometer (AMS) and the Aerosol Chemical Speciation Monitor (ACSM)
Numerical investigation on retrieval errors of mixing states of fractal black carbon aerosols using single-particle soot photometer based on Mie scattering and the effects on radiative forcing estimation
Performance evaluation of MOMA (MOment MAtching) – a remote network calibration technique for PM2.5 and PM10 sensors
Mapping the performance of a versatile water-based condensation particle counter (vWCPC) with numerical simulation and experimental study
Development and evaluation of an improved offline aerosol mass spectrometry technique
SMEARcore – modular data infrastructure for atmospheric measurement stations
A multiple-charging correction algorithm for a broad-supersaturation scanning cloud condensation nuclei (BS2-CCN) system
An evaluation of the U.S. EPA's correction equation for PurpleAir sensor data in smoke, dust, and wintertime urban pollution events
Typhoon-associated air quality over the Guangdong–Hong Kong–Macao Greater Bay Area, China: machine-learning-based prediction and assessment
Quantification of primary and secondary organic aerosol sources by combined factor analysis of extractive electrospray ionisation and aerosol mass spectrometer measurements (EESI-TOF and AMS)
A new method for calculating average visibility from the relationship between extinction coefficient and visibility
In situ particle sampling relationships to surface and turbulent fluxes using large eddy simulations with Lagrangian particles
The effect of the averaging period for PMF analysis of aerosol mass spectrometer measurements during offline applications
Calibrating networks of low-cost air quality sensors
Source apportionment resolved by time of day for improved deconvolution of primary source contributions to air pollution
Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data
Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Comprehensive detection of analytes in large chromatographic datasets by coupling factor analysis with a decision tree
Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens
Retrieval of the sea spray aerosol mode from submicron particle size distributions and supermicron scattering during LASIC
Automated identification of local contamination in remote atmospheric composition time series
Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques
Regularized inversion of aerosol hygroscopic growth factor probability density function: application to humidity-controlled fast integrated mobility spectrometer measurements
A systematic re-evaluation of methods for quantification of bulk particle-phase organic nitrates using real-time aerosol mass spectrometry
Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data
Data imputation in in situ-measured particle size distributions by means of neural networks
Analysis of mobile monitoring data from the microAeth® MA200 for measuring changes in black carbon on the roadside in Augsburg
New correction method for the scattering coefficient measurements of a three-wavelength nephelometer
Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network
Modeled source apportionment of black carbon particles coated with a light-scattering shell
Estimation of particulate organic nitrates from thermodenuder–aerosol mass spectrometer measurements in the North China Plain
Aerosol pH indicator and organosulfate detectability from aerosol mass spectrometry measurements
Determination of equivalent black carbon mass concentration from aerosol light absorption using variable mass absorption cross section
Effects of multi-charge on aerosol hygroscopicity measurement by a HTDMA
A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data
Estimation of pollen counts from light scattering intensity when sampling multiple pollen taxa – establishment of an automated multi-taxa pollen counting estimation system (AME system)
A novel lidar gradient cluster analysis method of nocturnal boundary layer detection during air pollution episodes
Assessment of particle size magnifier inversion methods to obtain the particle size distribution from atmospheric measurements
A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
Development of an automatic linear calibration method for high-resolution single-particle mass spectrometry: improved chemical species identification for atmospheric aerosols
A hybrid method for reconstructing the historical evolution of aerosol optical depth from sunshine duration measurements
The influence of the baseline drift on the resulting extinction values of a cavity attenuated phase shift-based extinction monitor (CAPS PMex)
Evaluation of equivalent black carbon source apportionment using observations from Switzerland between 2008 and 2018
Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations
Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles
Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi
Anton Rusanen, Anton Björklund, Manousos I. Manousakas, Jianhui Jiang, Markku T. Kulmala, Kai Puolamäki, and Kaspar R. Daellenbach
Atmos. Meas. Tech., 17, 1251–1277, https://doi.org/10.5194/amt-17-1251-2024, https://doi.org/10.5194/amt-17-1251-2024, 2024
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We present a Bayesian non-negative matrix factorization model that performs better on our test datasets than currently widely used models. Its advantages are better use of time information and providing a direct error estimation. We believe this could lead to better estimates of emission sources from measurements.
Milan Y. Patel, Pietro F. Vannucci, Jinsol Kim, William M. Berelson, and Ronald C. Cohen
Atmos. Meas. Tech., 17, 1051–1060, https://doi.org/10.5194/amt-17-1051-2024, https://doi.org/10.5194/amt-17-1051-2024, 2024
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Low-cost particulate matter (PM) sensors are becoming increasingly common in community monitoring and atmospheric research, but these sensors require proper calibration to provide accurate reporting. Here, we propose a hygroscopic growth calibration scheme that evolves in time to account for seasonal changes in hygroscopic growth. In San Francisco and Los Angeles, CA, applying a seasonal hygroscopic growth calibration can account for sensor biases driven by the seasonal cycles in PM composition.
Xinlei Ge, Yele Sun, Justin Trousdell, Mindong Chen, and Qi Zhang
Atmos. Meas. Tech., 17, 423–439, https://doi.org/10.5194/amt-17-423-2024, https://doi.org/10.5194/amt-17-423-2024, 2024
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This study aims to enhance the application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) in characterizing organic nitrogen (ON) species within aerosol particles and droplets. A thorough analysis was conducted on 75 ON standards that represent a diverse spectrum of ambient ON types. The results underscore the capacity of the HR-AMS in examining the concentration and chemistry of atmospheric ON compounds, thereby offering insights into their sources and environmental impacts.
Guanzhong Wang, Heinrich Ruser, Julian Schade, Johannes Passig, Thomas Adam, Günther Dollinger, and Ralf Zimmermann
Atmos. Meas. Tech., 17, 299–313, https://doi.org/10.5194/amt-17-299-2024, https://doi.org/10.5194/amt-17-299-2024, 2024
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This research aims to develop a novel warning system for the real-time monitoring of pollutants in the atmosphere. The system is capable of sampling and investigating airborne aerosol particles on-site, utilizing artificial intelligence to learn their chemical signatures and to classify them in real time. We applied single-particle mass spectrometry for analyzing the chemical composition of aerosol particles and suggest several supervised algorithms for highly reliable automatic classification.
Sohyeon Jeon, Michael J. Walker, Donna T. Sueper, Douglas A. Day, Anne V. Handschy, Jose L. Jimenez, and Brent J. Williams
Atmos. Meas. Tech., 16, 6075–6095, https://doi.org/10.5194/amt-16-6075-2023, https://doi.org/10.5194/amt-16-6075-2023, 2023
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A searchable database tool for the Aerosol Mass Spectrometer (AMS) and Aerosol Chemical Speciation Monitor (ACSM) mass spectral datasets was built to improve the efficiency of data analysis using Igor Pro. The tool incorporates the published mass spectra (MS) and sample information uploaded on the website. The tool allows users to compare their own mass spectrum with the reference MS in the database.
Jia Liu, Guangya Wang, Cancan Zhu, Donghui Zhou, and Lin Wang
Atmos. Meas. Tech., 16, 4961–4974, https://doi.org/10.5194/amt-16-4961-2023, https://doi.org/10.5194/amt-16-4961-2023, 2023
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Single-particle soot photometer (SP2) employs the core-shell model to represent coated BC particles, which introduces retrieval errors in the mixing state (Dp/Dc) of BC. We construct fractal models to represent thinly and thickly coated BC particles, and the retrieval errors of the mixing state are investigated from the numerical aspect. We find that errors in Dp/Dc are noteworthy, and the errors in Dp/Dc can further affect the evaluation accuracy of the radiative forcing of BC.
Lena Francesca Weissert, Geoff Steven Henshaw, David Edward Williams, Brandon Feenstra, Randy Lam, Ashley Collier-Oxandale, Vasileios Papapostolou, and Andrea Polidori
Atmos. Meas. Tech., 16, 4709–4722, https://doi.org/10.5194/amt-16-4709-2023, https://doi.org/10.5194/amt-16-4709-2023, 2023
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We apply a previously developed remote calibration framework to a network of particulate matter (PM) sensors deployed in Southern California. Our results show that a remote calibration can improve the accuracy of PM data, which was particularly visible for PM10. We highlight that sensor drift was mostly due to differences in particle composition than monitor operational factors. Thus, PM sensors may require frequent calibration if PM sources vary with different wind conditions or seasons.
Weixing Hao, Fan Mei, Susanne Hering, Steven Spielman, Beat Schmid, Jason Tomlinson, and Yang Wang
Atmos. Meas. Tech., 16, 3973–3986, https://doi.org/10.5194/amt-16-3973-2023, https://doi.org/10.5194/amt-16-3973-2023, 2023
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Airborne aerosol instrumentation plays a crucial role in understanding the spatial distribution of ambient aerosol particles. This study investigates a versatile water-based condensation particle counter through simulations and experiments. It provides valuable insights to improve versatile water-based condensation particle counter (vWCPC) aerosol measurement and operation for the community.
Christina N. Vasilakopoulou, Kalliopi Florou, Christos Kaltsonoudis, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 2837–2850, https://doi.org/10.5194/amt-16-2837-2023, https://doi.org/10.5194/amt-16-2837-2023, 2023
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The offline aerosol mass spectrometry technique is a useful tool for the source apportionment of organic aerosol in areas and periods during which an aerosol mass spectrometer is not available. In this work, an improved offline technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing the uncertainty of the corresponding source apportionment significantly.
Anton Rusanen, Kristo Hõrrak, Lauri R. Ahonen, Tuomo Nieminen, Pasi P. Aalto, Pasi Kolari, Markku Kulmala, Tuukka Petäjä, and Heikki Junninen
Atmos. Meas. Tech., 16, 2781–2793, https://doi.org/10.5194/amt-16-2781-2023, https://doi.org/10.5194/amt-16-2781-2023, 2023
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We present a framework for setting up SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) type measurement station data flows. This framework, called SMEARcore, consists of modular open-source software components that can be chosen to suit various station configurations. The benefits of using this framework are automation of routine operations and real-time monitoring of measurement results.
Najin Kim, Hang Su, Nan Ma, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech., 16, 2771–2780, https://doi.org/10.5194/amt-16-2771-2023, https://doi.org/10.5194/amt-16-2771-2023, 2023
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We propose a multiple-charging correction algorithm for a broad-supersaturation scanning cloud condensation nuclei (BS2-CCN) system which can obtain high time-resolution aerosol hygroscopicity and CCN activity. The correction algorithm aims at deriving the activation fraction's true value for each particle size. The meaningful differences between corrected and original κ values (single hygroscopicity parameter) emphasize the correction algorithm's importance for ambient aerosol measurement.
Daniel A. Jaffe, Colleen Miller, Katie Thompson, Brandon Finley, Manna Nelson, James Ouimette, and Elisabeth Andrews
Atmos. Meas. Tech., 16, 1311–1322, https://doi.org/10.5194/amt-16-1311-2023, https://doi.org/10.5194/amt-16-1311-2023, 2023
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PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM) concentrations. However, the raw PAS data have significant biases, so the sensors must be corrected. We analyzed data from numerous sites and found that the standard correction to the PAS Purple Air data is accurate in urban pollution events and smoke events but leads to a 6-fold underestimate in the PM2.5 concentrations in dust events. We propose a new correction algorithm to address this problem.
Yilin Chen, Yuanjian Yang, and Meng Gao
Atmos. Meas. Tech., 16, 1279–1294, https://doi.org/10.5194/amt-16-1279-2023, https://doi.org/10.5194/amt-16-1279-2023, 2023
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The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events related to typhoons. The present study leverages machine learning to predict typhoon-associated air quality over the area. The model evaluation shows that the model performs excellently. Moreover, the change in meteorological drivers of air quality on typhoon days and non-typhoon days suggests that air pollution control strategies should have different focuses on typhoon days and non-typhoon days.
Yandong Tong, Lu Qi, Giulia Stefenelli, Dongyu Simon Wang, Francesco Canonaco, Urs Baltensperger, André Stephan Henry Prévôt, and Jay Gates Slowik
Atmos. Meas. Tech., 15, 7265–7291, https://doi.org/10.5194/amt-15-7265-2022, https://doi.org/10.5194/amt-15-7265-2022, 2022
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We present a method for positive matrix factorisation (PMF) analysis on a single dataset that includes measurements from both EESI-TOF and AMS in Zurich, Switzerland. For the first time, we resolved and quantified secondary organic aerosol (SOA) sources. Meanwhile, we also determined the retrieved EESI-TOF factor-dependent sensitivities. This method provides a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment.
Zefeng Zhang, Hengnan Guo, Hanqing Kang, Jing Wang, Junlin An, Xingna Yu, Jingjing Lv, and Bin Zhu
Atmos. Meas. Tech., 15, 7259–7264, https://doi.org/10.5194/amt-15-7259-2022, https://doi.org/10.5194/amt-15-7259-2022, 2022
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In this study, we first analyze the relationship between the visibility, the extinction coefficient, and atmospheric compositions. Then we propose to use the harmonic average of visibility data as the average visibility, which can better reflect changes in atmospheric extinction coefficients and aerosol concentrations. It is recommended to use the harmonic average visibility in the studies of climate change, atmospheric radiation, air pollution, environmental health, etc.
Hyungwon John Park, Jeffrey S. Reid, Livia S. Freire, Christopher Jackson, and David H. Richter
Atmos. Meas. Tech., 15, 7171–7194, https://doi.org/10.5194/amt-15-7171-2022, https://doi.org/10.5194/amt-15-7171-2022, 2022
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We use numerical models to study field measurements of sea spray aerosol particles and conclude that both the atmospheric state and the methods of instrument sampling are causes for the variation in the production rate of aerosol particles: a critical metric to learn the aerosol's effect on processes like cloud physics and radiation. This work helps field observers improve their experimental design and interpretation of measurements because of turbulence in the atmosphere.
Christina Vasilakopoulou, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 15, 6419–6431, https://doi.org/10.5194/amt-15-6419-2022, https://doi.org/10.5194/amt-15-6419-2022, 2022
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Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols when online AMS measurements are not available. In this study, we examine whether and how the low time resolution (usually 24 h) of the offline technique affects source apportionment results. We concluded that use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis.
Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney
Atmos. Meas. Tech., 15, 6309–6328, https://doi.org/10.5194/amt-15-6309-2022, https://doi.org/10.5194/amt-15-6309-2022, 2022
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How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Sahil Bhandari, Zainab Arub, Gazala Habib, Joshua S. Apte, and Lea Hildebrandt Ruiz
Atmos. Meas. Tech., 15, 6051–6074, https://doi.org/10.5194/amt-15-6051-2022, https://doi.org/10.5194/amt-15-6051-2022, 2022
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We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
Alireza Moallemi, Rob L. Modini, Tatyana Lapyonok, Anton Lopatin, David Fuertes, Oleg Dubovik, Philippe Giaccari, and Martin Gysel-Beer
Atmos. Meas. Tech., 15, 5619–5642, https://doi.org/10.5194/amt-15-5619-2022, https://doi.org/10.5194/amt-15-5619-2022, 2022
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Aerosol properties (size distributions, refractive indices) can be retrieved from in situ, angularly resolved light scattering measurements performed with polar nephelometers. We apply an established framework to assess the aerosol property retrieval potential for different instrument configurations, target applications, and assumed prior knowledge. We also demonstrate how a reductive greedy algorithm can be used to determine the optimal placements of the angular sensors in a polar nephelometer.
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495, https://doi.org/10.5194/amt-15-5479-2022, https://doi.org/10.5194/amt-15-5479-2022, 2022
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This work presents the differences resulting from two techniques (rolling and seasonal) of the positive matrix factorisation model that can be run for organic aerosol source apportionment. The current state of the art suggests that the rolling technique is more accurate, but no proof of its effectiveness has been provided yet. This paper tackles this issue in the context of a synthetic dataset and a multi-site real-world comparison.
Sungwoo Kim, Brian M. Lerner, Donna T. Sueper, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 15, 5061–5075, https://doi.org/10.5194/amt-15-5061-2022, https://doi.org/10.5194/amt-15-5061-2022, 2022
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Atmospheric samples can be complex, and current analysis methods often require substantial human interaction and discard potentially important information. To improve analysis accuracy and computational cost of these large datasets, we developed an automated analysis algorithm that utilizes a factor analysis approach coupled with a decision tree. We demonstrate that this algorithm cataloged approximately 10 times more analytes compared to a manual analysis and in a quarter of the analysis time.
Olga Zografou, Maria Gini, Manousos I. Manousakas, Gang Chen, Athina C. Kalogridis, Evangelia Diapouli, Athina Pappa, and Konstantinos Eleftheriadis
Atmos. Meas. Tech., 15, 4675–4692, https://doi.org/10.5194/amt-15-4675-2022, https://doi.org/10.5194/amt-15-4675-2022, 2022
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A yearlong ToF-ACSM dataset was used to characterize ambient aerosols over a suburban Athenian site, and innovative software for source apportionment was implemented in order to distinguish the sources of the total non-refractory species of PM1. A comparison between the methodology of combined organic and inorganic PMF analysis and the conventional organic PMF took place.
Jeramy L. Dedrick, Georges Saliba, Abigail S. Williams, Lynn M. Russell, and Dan Lubin
Atmos. Meas. Tech., 15, 4171–4194, https://doi.org/10.5194/amt-15-4171-2022, https://doi.org/10.5194/amt-15-4171-2022, 2022
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A new method is presented to retrieve the sea spray aerosol size distribution by combining submicron size and nephelometer scattering based on Mie theory. Using available sea spray tracers, we find that this approach serves as a comparable substitute to supermicron size distribution measurements, which are limited in availability at marine sites. Application of this technique can expand sea spray observations and improve the characterization of marine aerosol impacts on clouds and climate.
Ivo Beck, Hélène Angot, Andrea Baccarini, Lubna Dada, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, Markus Lampimäki, Nicolas Bukowiecki, Matthew Boyer, Xianda Gong, Martin Gysel-Beer, Tuukka Petäjä, Jian Wang, and Julia Schmale
Atmos. Meas. Tech., 15, 4195–4224, https://doi.org/10.5194/amt-15-4195-2022, https://doi.org/10.5194/amt-15-4195-2022, 2022
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We present the pollution detection algorithm (PDA), a new method to identify local primary pollution in remote atmospheric aerosol and trace gas time series. The PDA identifies periods of contaminated data and relies only on the target dataset itself; i.e., it is independent of ancillary data such as meteorological variables. The parameters of all pollution identification steps are adjustable so that the PDA can be tuned to different locations and situations. It is available as open-access code.
Emily B. Franklin, Lindsay D. Yee, Bernard Aumont, Robert J. Weber, Paul Grigas, and Allen H. Goldstein
Atmos. Meas. Tech., 15, 3779–3803, https://doi.org/10.5194/amt-15-3779-2022, https://doi.org/10.5194/amt-15-3779-2022, 2022
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The composition of atmospheric aerosols are extremely complex, containing hundreds of thousands of estimated individual compounds. The majority of these compounds have never been catalogued in widely used databases, making them extremely difficult for atmospheric chemists to identify and analyze. In this work, we present Ch3MS-RF, a machine-learning-based model to enable characterization of complex mixtures and prediction of structure-specific properties of unidentifiable organic compounds.
Jiaoshi Zhang, Yang Wang, Steven Spielman, Susanne Hering, and Jian Wang
Atmos. Meas. Tech., 15, 2579–2590, https://doi.org/10.5194/amt-15-2579-2022, https://doi.org/10.5194/amt-15-2579-2022, 2022
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New nonparametric, regularized methods are developed to invert the growth factor probability density function (GF-PDF) from humidity-controlled fast integrated mobility spectrometer measurements. These algorithms are computationally efficient, require no prior assumptions of the GF-PDF distribution, and reduce the error in inverted GF-PDF. They can be applied to humidified tandem differential mobility analyzer data. Among all algorithms, Twomey’s method retrieves GF-PDF with the smallest error.
Douglas A. Day, Pedro Campuzano-Jost, Benjamin A. Nault, Brett B. Palm, Weiwei Hu, Hongyu Guo, Paul J. Wooldridge, Ronald C. Cohen, Kenneth S. Docherty, J. Alex Huffman, Suzane S. de Sá, Scot T. Martin, and Jose L. Jimenez
Atmos. Meas. Tech., 15, 459–483, https://doi.org/10.5194/amt-15-459-2022, https://doi.org/10.5194/amt-15-459-2022, 2022
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Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.
Markus D. Petters
Atmos. Meas. Tech., 14, 7909–7928, https://doi.org/10.5194/amt-14-7909-2021, https://doi.org/10.5194/amt-14-7909-2021, 2021
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Inverse methods infer physical properties from a measured instrument response. Measurement noise often interferes with the inversion. This work presents a general, domain-independent, accessible, and computationally efficient software implementation of a common class of statistical inversion methods. In addition, a new method to invert data from humidified tandem differential mobility analyzers is introduced. Results show that the approach is suitable for inversion of large-scale datasets.
Pak Lun Fung, Martha Arbayani Zaidan, Ola Surakhi, Sasu Tarkoma, Tuukka Petäjä, and Tareq Hussein
Atmos. Meas. Tech., 14, 5535–5554, https://doi.org/10.5194/amt-14-5535-2021, https://doi.org/10.5194/amt-14-5535-2021, 2021
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Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. However, due to the instrumental insufficiency and inversion limitations, the raw dataset contains missing gaps or negative values, which hinder further analysis. With a merged particle size distribution in Jordan, this paper suggests a neural network method to estimate number concentrations at a particular size bin by the number concentration at other size bins.
Xiansheng Liu, Hadiatullah Hadiatullah, Xun Zhang, L. Drew Hill, Andrew H. A. White, Jürgen Schnelle-Kreis, Jan Bendl, Gert Jakobi, Brigitte Schloter-Hai, and Ralf Zimmermann
Atmos. Meas. Tech., 14, 5139–5151, https://doi.org/10.5194/amt-14-5139-2021, https://doi.org/10.5194/amt-14-5139-2021, 2021
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A monitoring campaign was conducted in Augsburg to determine a suitable noise reduction algorithm for the MA200 Aethalometer. Results showed that centred moving average (CMA) post-processing effectively removed spurious negative concentrations without major bias and reliably highlighted effects from local sources, effectively increasing spatio-temporal resolution in mobile measurements. Evaluation of each method on peak sample reduction and background correction further supports the reliability.
Jie Qiu, Wangshu Tan, Gang Zhao, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 4879–4891, https://doi.org/10.5194/amt-14-4879-2021, https://doi.org/10.5194/amt-14-4879-2021, 2021
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Considering nephelometers' major problems of a nonideal Lambertian light source and angle truncation, a new correction method based on a machine learning model is proposed. Our method has the advantage of obtaining data with high accuracy while achieving self-correction, which means that researchers can get more accurate scattering coefficients without the need for additional observation data. This method provides a more precise estimation of the aerosol’s direct radiative forcing.
Amir Yazdani, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 14, 4805–4827, https://doi.org/10.5194/amt-14-4805-2021, https://doi.org/10.5194/amt-14-4805-2021, 2021
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We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM2.5 currently collected in existing air pollution monitoring networks and field campaigns.
Aki Virkkula
Atmos. Meas. Tech., 14, 3707–3719, https://doi.org/10.5194/amt-14-3707-2021, https://doi.org/10.5194/amt-14-3707-2021, 2021
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The Aethalometer model is used widely for estimating the contributions of fossil fuel emissions and biomass burning to black carbon. The calculation is based on measured absorption Ångström exponents, which is ambiguous since it not only depends on the dominant absorber but also on the size and internal structure of the particles, core size, and shell thickness. The uncertainties of the fractions of absorption by eBC from fossil fuel and biomass burning are evaluated with a core–shell Mie model.
Weiqi Xu, Masayuki Takeuchi, Chun Chen, Yanmei Qiu, Conghui Xie, Wanyun Xu, Nan Ma, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Meas. Tech., 14, 3693–3705, https://doi.org/10.5194/amt-14-3693-2021, https://doi.org/10.5194/amt-14-3693-2021, 2021
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Here we developed a method for estimation of particulate organic nitrates (pON) from the measurements of a high-resolution aerosol mass spectrometer coupled with a thermodenuder based on the volatility differences between inorganic nitrate and pON. The results generally had improvements in reducing negative values due to the influences of a high concentration of inorganic nitrate and a constant ratio of NO+ to NO2+ of organic nitrates (RON).
Melinda K. Schueneman, Benjamin A. Nault, Pedro Campuzano-Jost, Duseong S. Jo, Douglas A. Day, Jason C. Schroder, Brett B. Palm, Alma Hodzic, Jack E. Dibb, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 2237–2260, https://doi.org/10.5194/amt-14-2237-2021, https://doi.org/10.5194/amt-14-2237-2021, 2021
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This work focuses on two important properties of the aerosol, acidity, and sulfate composition, which is important for our understanding of aerosol health and environmental impacts. We explore different methods to understand the composition of the aerosol with measurements from a specific instrument and apply those methods to a large dataset. These measurements are confounded by other factors, making it challenging to predict aerosol sulfate composition; pH estimations, however, show promise.
Weilun Zhao, Wangshu Tan, Gang Zhao, Chuanyang Shen, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1319–1331, https://doi.org/10.5194/amt-14-1319-2021, https://doi.org/10.5194/amt-14-1319-2021, 2021
Chuanyang Shen, Gang Zhao, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1293–1301, https://doi.org/10.5194/amt-14-1293-2021, https://doi.org/10.5194/amt-14-1293-2021, 2021
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Aerosol hygroscopicity measured by the humidified tandem differential mobility analyzer (HTDMA) is affected by multiply charged particles from two aspects: (1) number contribution and (2) the weakening effect. An algorithm is proposed to do the multi-charge correction and applied to a field measurement. Results show that the difference between corrected and measured size-resolved κ can reach 0.05, highlighting that special attention needs to be paid to the multi-charge effect when using HTDMA.
Francesco Canonaco, Anna Tobler, Gang Chen, Yulia Sosedova, Jay Gates Slowik, Carlo Bozzetti, Kaspar Rudolf Daellenbach, Imad El Haddad, Monica Crippa, Ru-Jin Huang, Markus Furger, Urs Baltensperger, and André Stephan Henry Prévôt
Atmos. Meas. Tech., 14, 923–943, https://doi.org/10.5194/amt-14-923-2021, https://doi.org/10.5194/amt-14-923-2021, 2021
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Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF) to obtain source contributions and fingerprints. The new aspects of this paper involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.
Kenji Miki and Shigeto Kawashima
Atmos. Meas. Tech., 14, 685–693, https://doi.org/10.5194/amt-14-685-2021, https://doi.org/10.5194/amt-14-685-2021, 2021
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Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination.
Yinchao Zhang, Su Chen, Siying Chen, He Chen, and Pan Guo
Atmos. Meas. Tech., 13, 6675–6689, https://doi.org/10.5194/amt-13-6675-2020, https://doi.org/10.5194/amt-13-6675-2020, 2020
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Air pollution has an important impact on human health, climatic patterns, and the ecological environment. The complexity of the nocturnal boundary layer (NBL), combined with its strong physio-chemical effect, induces worse polluted episodes. Therefore, we present a new approach named cluster analysis of gradient method (CA-GM) to overcome the multilayer structure and remove the fluctuation of NBL height using raw data resolution.
Tommy Chan, Runlong Cai, Lauri R. Ahonen, Yiliang Liu, Ying Zhou, Joonas Vanhanen, Lubna Dada, Yan Chao, Yongchun Liu, Lin Wang, Markku Kulmala, and Juha Kangasluoma
Atmos. Meas. Tech., 13, 4885–4898, https://doi.org/10.5194/amt-13-4885-2020, https://doi.org/10.5194/amt-13-4885-2020, 2020
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Using a particle size magnifier (PSM; Airmodus, Finland), we determined the particle size distribution using four inversion methods and compared each method to the others to establish their strengths and weaknesses. Furthermore, we provided a step-by-step procedure on how to invert measured data using the PSM. Finally, we provided recommendations, code and data related to the data inversion. This is an important paper, as no operating procedure exists regarding how to process measured PSM data.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Shengqiang Zhu, Lei Li, Shurong Wang, Mei Li, Yaxi Liu, Xiaohui Lu, Hong Chen, Lin Wang, Jianmin Chen, Zhen Zhou, Xin Yang, and Xiaofei Wang
Atmos. Meas. Tech., 13, 4111–4121, https://doi.org/10.5194/amt-13-4111-2020, https://doi.org/10.5194/amt-13-4111-2020, 2020
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Single-particle aerosol mass spectrometry (SPAMS) is widely used to detect chemical compositions and sizes of individual aerosol particles. However, it has a major issue: the mass accuracy of high-resolution SPAMS is relatively low. Here we developed an automatic linear calibration method to greatly improve the mass accuracy of SPAMS spectra so that the elemental compositions of organic peaks, such as Cx, CxHy, CxHyOz and CxHyNO peaks, can be directly identified just based on their m / z values.
William Wandji Nyamsi, Antti Lipponen, Arturo Sanchez-Lorenzo, Martin Wild, and Antti Arola
Atmos. Meas. Tech., 13, 3061–3079, https://doi.org/10.5194/amt-13-3061-2020, https://doi.org/10.5194/amt-13-3061-2020, 2020
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This paper proposes a novel and accurate method for estimating and reconstructing aerosol optical depth from sunshine duration measurements under cloud-free conditions at any place and time since the late 19th century. The method performs very well when compared to AErosol RObotic NETwork measurements and operates an efficient detection of signals from massive volcanic eruptions. Reconstructed long-term aerosol optical depths are in agreement with the dimming/brightening phenomenon.
Sascha Pfeifer, Thomas Müller, Andrew Freedman, and Alfred Wiedensohler
Atmos. Meas. Tech., 13, 2161–2167, https://doi.org/10.5194/amt-13-2161-2020, https://doi.org/10.5194/amt-13-2161-2020, 2020
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The effect of the baseline drift on the resulting extinction values of three CAPS PMex monitors with different wavelengths was analysed for an urban background station. A significant baseline drift was observed, which leads to characteristic measurement artefacts for particle extinction. Two alternative methods for recalculating the baseline are shown. With these methods the extinction artefacts are diminished and the effective scattering of the resulting extinction values is reduced.
Stuart K. Grange, Hanspeter Lötscher, Andrea Fischer, Lukas Emmenegger, and Christoph Hueglin
Atmos. Meas. Tech., 13, 1867–1885, https://doi.org/10.5194/amt-13-1867-2020, https://doi.org/10.5194/amt-13-1867-2020, 2020
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Black carbon (BC) is an important atmospheric pollutant and can be monitored by instruments called aethalometers. A pragmatic data processing technique called the
aethalometer modelcan be used to apportion aethalometer observations into traffic and woodburning components. We present an exploratory data analysis evaluating the aethalometer model and use the outputs for BC trend analysis across Switzerland. The aethalometer model's robustness and utility for such analyses is discussed.
Charlotte Bürki, Matteo Reggente, Ann M. Dillner, Jenny L. Hand, Stephanie L. Shaw, and Satoshi Takahama
Atmos. Meas. Tech., 13, 1517–1538, https://doi.org/10.5194/amt-13-1517-2020, https://doi.org/10.5194/amt-13-1517-2020, 2020
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Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Kaixu Bai, Ke Li, Jianping Guo, Yuanjian Yang, and Ni-Bin Chang
Atmos. Meas. Tech., 13, 1213–1226, https://doi.org/10.5194/amt-13-1213-2020, https://doi.org/10.5194/amt-13-1213-2020, 2020
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A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function (DCCEOF) is proposed. Cross validation indicates that this method gives high accuracy in predicting missing values in daily PM2.5 time series by accounting for the local diurnal phases, especially by reconstructing daily extrema that cannot be accurately restored by other approaches. The DCCEOF method can be easily applied to other data sets because of its self-consistent capability.
Tongshu Zheng, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson
Atmos. Meas. Tech., 12, 5161–5181, https://doi.org/10.5194/amt-12-5161-2019, https://doi.org/10.5194/amt-12-5161-2019, 2019
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Here we present a simultaneous Gaussian process regression (GPR) and linear regression pipeline to calibrate and monitor dense wireless low-cost particulate matter sensor networks (WLPMSNs) on the fly by using all available reference monitors across an area. Our approach can achieve an overall 30 % prediction error at a 24 h scale, can differentiate malfunctioning nodes, and track drift. Our solution can substantially reduce manual labor for managing WLPMSNs and prolong their lifetimes.
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Short summary
We describe a new method for removing Teflon substrate interference from ambient aerosol infrared spectra such that functional group quantification and spectral clustering (for source classification) can be applied. We demonstrate that this technique produces similar results to a more labor-intensive method used in many field campaigns over the past several years, but is simpler and better constrained by physical criteria that we impose, leading to the possibility of widespread adoption.
We describe a new method for removing Teflon substrate interference from ambient aerosol...
