Articles | Volume 13, issue 12
https://doi.org/10.5194/amt-13-6675-2020
© Author(s) 2020. 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-13-6675-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Dec 2020
Research article |
| 09 Dec 2020
| 09 Dec 2020
A novel lidar gradient cluster analysis method of nocturnal boundary layer detection during air pollution episodes
Yinchao Zhang
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
Su Chen
CORRESPONDING AUTHOR
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
Siying Chen
CORRESPONDING AUTHOR
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
He Chen
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
Pan Guo
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
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In this study, the seasonal variation in Aeolus wind product performance over China is analyzed by using L-band radiosonde detection data and ERA5 reanalysis data. The results show that the Aeolus wind product performance is affected by seasonal factors, which may be caused by seasonal changes in wind direction and cloud distribution.
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In this study, the seasonal variation in Aeolus wind product performance over China is analyzed by using L-band radiosonde detection data and ERA5 reanalysis data. The results show that the Aeolus wind product performance is affected by seasonal factors, which may be caused by seasonal changes in wind direction and cloud distribution.
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Atmos. Chem. Phys., 18, 10645–10653, https://doi.org/10.5194/acp-18-10645-2018, https://doi.org/10.5194/acp-18-10645-2018, 2018
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Haze pollution has been a common problem in China. In this study, the traits of upper air visibility and the two-dimensional haze characteristic were investigated in the northwest of downtown Beijing by using a multi-platform analysis. An opposite tendency to PM2.5 mass concentration appears for upper air visibility by hourly and daily haze analysis. Moreover, the delayed variations of upper air visibility between high altitude and low altitude reveal the vertical transport of pollutants.
Related subject area
Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
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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
An evaluation of the U.S. EPA’s correction equation for Purple Air Sensor data in smoke, dust and wintertime urban pollution events
Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Typhoon-associated air quality over the Guangdong–Hong Kong–Macao Greater Bay Area, China: machine learning-based prediction and assessment
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
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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
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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
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The influence of the baseline drift on the resulting extinction values of a cavity attenuated phase shift-based extinction monitor (CAPS PMex)
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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
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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.
Daniel Jaffe, Colleen Miller, Katie Thompson, Manna Nelson, Brandon Finley, James Ouimette, and Elisabeth Andrews
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-265, https://doi.org/10.5194/amt-2022-265, 2022
Revised manuscript accepted for AMT
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PurpleAir Sensors (PAS) 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 algorithim to address this problem.
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.
Yilin Chen, Yuanjian Yang, and Meng Gao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-225, https://doi.org/10.5194/amt-2022-225, 2022
Revised manuscript accepted for AMT
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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. Besides, the change in meteorological drivers of air quality on typhoon days and non-typhoon days suggests that the air pollution control strategies should have different focuses on typhoon days and non-typhoon days.
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.
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.
Stina Ausmeel, Axel Eriksson, Erik Ahlberg, and Adam Kristensson
Atmos. Meas. Tech., 12, 4479–4493, https://doi.org/10.5194/amt-12-4479-2019, https://doi.org/10.5194/amt-12-4479-2019, 2019
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We present a method for identifying individual exhaust plumes of air pollution emitted from shipping, by linking these to specific ships using identification information which all ships transmit. We also quantify the contribution of these plumes to local particle levels, which has relevance for health effects. Ships emit a lot of nanometre-sized particles, which proved to be a good indicator of plumes at a distance of about 10 km downwind of a shipping lane in the Baltic Sea.
Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev
Atmos. Meas. Tech., 12, 3435–3452, https://doi.org/10.5194/amt-12-3435-2019, https://doi.org/10.5194/amt-12-3435-2019, 2019
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The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct a first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multistep algorithms with sequential discrimination of pollen can be a possible way forward.
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.
Xiaoli Shen, Harald Saathoff, Wei Huang, Claudia Mohr, Ramakrishna Ramisetty, and Thomas Leisner
Atmos. Meas. Tech., 12, 2219–2240, https://doi.org/10.5194/amt-12-2219-2019, https://doi.org/10.5194/amt-12-2219-2019, 2019
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Based on single-particle mass spectra from field measurements in the upper Rhine valley, we identified characteristic particle classes and estimated their mass contributions without the need of a reference instrument in the field. Our study provides a good example for quantitative interpretation of single-particle data. Together with the complimentary results from bulk measurements, we have shown how a better understanding of the mixing state of ambient aerosol particles can be achieved.
Tarjei Antonsen, Ove Havnes, and Andres Spicher
Atmos. Meas. Tech., 12, 2139–2153, https://doi.org/10.5194/amt-12-2139-2019, https://doi.org/10.5194/amt-12-2139-2019, 2019
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This paper presents measurements of changes in mesospheric aerosol populations on different length scales, as detected by the DUSTY and MUDD probes on the MAXIDUSTY-1B rocket on 8 July 2016. Identical probes recorded very different currents, which we attribute to adverse flow effects. We find a general anti-correlation for charged aerosols and electrons, but not consistently on all length scales. We conclude that there is no simple relationship between aerosols and PMSE (radar echoes).
Ove Havnes, Tarjei Antonsen, Gerd Baumgarten, Thomas W. Hartquist, Alexander Biebricher, Åshild Fredriksen, Martin Friedrich, and Jonas Hedin
Atmos. Meas. Tech., 12, 1673–1683, https://doi.org/10.5194/amt-12-1673-2019, https://doi.org/10.5194/amt-12-1673-2019, 2019
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We present a new method of analyzing data from rocket-borne aerosol detectors of the Faraday cup type (DUSTY). By using models for how aerosols are charged in the mesosphere and how they interact in a collision with the probes, fundamental parameters like aerosol radius, charge, and number density can be derived. The resolution can be down to ~ 10 cm, which is much lower than other available methods. The theory is furthermore used to analyze DUSTY data from the 2016 rocket campaign MAXIDUSTY.
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.
Runlong Cai, Dongsen Yang, Lauri R. Ahonen, Linlin Shi, Frans Korhonen, Yan Ma, Jiming Hao, Tuukka Petäjä, Jun Zheng, Juha Kangasluoma, and Jingkun Jiang
Atmos. Meas. Tech., 11, 4477–4491, https://doi.org/10.5194/amt-11-4477-2018, https://doi.org/10.5194/amt-11-4477-2018, 2018
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We tested the performance of four inversion methods to recover sub-3 nm aerosol size distributions using the particle size magnifier (PSM). The PSM is widely used in new particle formation study; however, the inversion methods used in previous studies may report false particle concentrations. Due to the results, we suggest using the expectation–maximization algorithm to address the PSM inversion problem. We also gave practical suggestions on PSM operation based on the inversion analysis.
Ye Kuang, Chun Sheng Zhao, Gang Zhao, Jiang Chuan Tao, Wanyun Xu, Nan Ma, and Yu Xuan Bian
Atmos. Meas. Tech., 11, 2967–2982, https://doi.org/10.5194/amt-11-2967-2018, https://doi.org/10.5194/amt-11-2967-2018, 2018
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Aerosol water has become an important topic recently because of its implications for multiphase secondary aerosol formation during severe haze events in Asia. This is a timely paper on this topic; a novel method is proposed to calculate ambient aerosol liquid water contents based only on measurements of a three-wavelength humidified nephelometer system. The advantage of this method is that this technique can provide continuous measurements of the changing ambient conditions.
Cheng Wu and Jian Zhen Yu
Atmos. Meas. Tech., 11, 1233–1250, https://doi.org/10.5194/amt-11-1233-2018, https://doi.org/10.5194/amt-11-1233-2018, 2018
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A new data generation scheme that employs the Mersenne twister (MT) pseudorandom number generator is proposed to conduct benchmark tests on a variety of linear regression techniques. With an appropriate weighting, Deming regression (DR), weighted ODR (WODR), and York regression (YR) are recommended for atmospheric studies when both x and y data have measurement errors. An Igor-based program (Scatter Plot) is developed to facilitate the regression implementation.
Qiao Zhu, Xiao-Feng Huang, Li-Ming Cao, Lin-Tong Wei, Bin Zhang, Ling-Yan He, Miriam Elser, Francesco Canonaco, Jay G. Slowik, Carlo Bozzetti, Imad El-Haddad, and André S. H. Prévôt
Atmos. Meas. Tech., 11, 1049–1060, https://doi.org/10.5194/amt-11-1049-2018, https://doi.org/10.5194/amt-11-1049-2018, 2018
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Organic aerosol constitutes one of the major components of atmospheric particulate matter globally and is emitted from various sources. Therefore, identifying and quantifying the sources of organic aerosol accurately is a key task in the field. In this study, we applied a rather novel procedure for an improved source apportionment method (ME-2) to resolve the
less meaningful or mixed factorsproblems for organic aerosol using the traditional method (PMF).
John Backman, Lauren Schmeisser, Aki Virkkula, John A. Ogren, Eija Asmi, Sandra Starkweather, Sangeeta Sharma, Konstantinos Eleftheriadis, Taneil Uttal, Anne Jefferson, Michael Bergin, Alexander Makshtas, Peter Tunved, and Markus Fiebig
Atmos. Meas. Tech., 10, 5039–5062, https://doi.org/10.5194/amt-10-5039-2017, https://doi.org/10.5194/amt-10-5039-2017, 2017
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Light absorption by aerosol particles is of climatic importance. A widely used means to measure aerosol light absorption is a filter-based measurement technique. In remote areas, such as the Arctic, filter-based instruments operate close to their detection limit. The study presents how a lower detection limit can be achieved for one such instrument, the Aethalometer. Additionally, the Aethalometer is compared to similar instruments, thus improving measurement inter-comparability in the Arctic.
Cited articles
Banks, R. F., Tiana-Alsina, J., María Baldasano, J., and Rocadenbosch, F.:
Retrieval of boundary layer height from lidar using extended Kalman filter approach, classic methods, and backtrajectory cluster analysis,
edited by: Comerón, A., Kassianov, E. I., Schäfer, K., Picard, R. H., Stein, K., and Gonglewski, J. D.,
Amsterdam, the Netherlands, p. 92420F, 2014.
Benavent-Oltra, J. A., Román, R., Casquero-Vera, J. A., Pérez-Ramírez, D., Lyamani, H., Ortiz-Amezcua, P., Bedoya-Velásquez, A. E., de Arruda Moreira, G., Barreto, Á., Lopatin, A., Fuertes, D., Herrera, M., Torres, B., Dubovik, O., Guerrero-Rascado, J. L., Goloub, P., Olmo-Reyes, F. J., and Alados-Arboledas, L.: Different strategies to retrieve aerosol properties at night-time with the GRASP algorithm, Atmos. Chem. Phys., 19, 14149–14171, https://doi.org/10.5194/acp-19-14149-2019, 2019.
Brooks, I. M.:
Finding boundary layer top: Application of a wavelet covariance transform to lidar backscatter profiles,
J. Atmos. Ocean. Tech.,
20, 1092–1105, 2003.
Caicedo, V., Rappenglück, B., Lefer, B., Morris, G., Toledo, D., and Delgado, R.: Comparison of aerosol lidar retrieval methods for boundary layer height detection using ceilometer aerosol backscatter data, Atmos. Meas. Tech., 10, 1609–1622, https://doi.org/10.5194/amt-10-1609-2017, 2017.
Campbell, J. R., Sassen, K., and Welton, E. J.:
Elevated Cloud and Aerosol Layer Retrievals from Micropulse Lidar Signal Profiles,
J. Atmos. Ocean. Tech.,
25, 685–700, https://doi.org/10.1175/2007JTECHA1034.1, 2008.
Chen, H., Chen, S., Zhang, Y., Chen, H., Guo, P., and Chen, B.:
Experimental determination of Raman lidar geometric form factor combining Raman and elastic return,
Opt. Commun.,
332, 296–300, 2014.
Comerón, A., Muñoz-Porcar, C., Rocadenbosch, F., Rodríguez-Gómez, A., and Sicard, M.:
Current Research in Lidar Technology Used for the Remote Sensing of Atmospheric Aerosols,
Sensors,
17, 1450, https://doi.org/10.3390/s17061450, 2017.
Dang, R., Yang, Y., Hu, X.-M., Wang, Z., and Zhang, S.:
A Review of Techniques for Diagnosing the Atmospheric Boundary Layer Height (ABLH) Using Aerosol Lidar Data,
Remote Sens.-Basel,
11, 1590, https://doi.org/10.3390/rs11131590, 2019a.
Dang, R., Yang, Y., Li, H., Hu, X.-M., Wang, Z., Huang, Z., Zhou, T., and Zhang, T.:
Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar,
Remote Sens.-Basel,
11, 263, https://doi.org/10.3390/rs11030263, 2019b.
Davis, K. J., Gamage, N., Hagelberg, C. R., Kiemle, C., Lenschow, D. H., and Sullivan, P. P.:
An objective method for deriving atmospheric structure from airborne lidar observations,
J. Atmos. Ocean. Tech.,
17, 1455–1468, 2000.
de Bruine, M., Apituley, A., Donovan, D. P., Klein Baltink, H., and de Haij, M. J.: Pathfinder: applying graph theory to consistent tracking of daytime mixed layer height with backscatter lidar, Atmos. Meas. Tech., 10, 1893–1909, https://doi.org/10.5194/amt-10-1893-2017, 2017.
Dong, Z., Li, Z., Yu, X., Cribb, M., Li, X., and Dai, J.: Opposite long-term trends in aerosols between low and high altitudes: a testimony to the aerosol–PBL feedback, Atmos. Chem. Phys., 17, 7997–8009, https://doi.org/10.5194/acp-17-7997-2017, 2017.
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.:
Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations,
J. Atmos. Sci.,
59, 590–608, https://doi.org/10.1175/1520-0469(2002)059<0590:VOAAOP>2.0.CO;2, 2002.
Dudeja, J. P.: Micro-Pulse Lidar for the Determination of Atmospheric Boundary Layer Height, Int. J. Res. Anal. Rev., 6, 810–817, 2019.
Emeis, S. and Schäfer, K.:
Remote Sensing Methods to Investigate Boundary-layer Structures relevant to Air Pollution in Cities,
Bound.-Lay. Meteorol.,
121, 377–385, https://doi.org/10.1007/s10546-006-9068-2, 2006.
Fernald, F. G.:
Analysis of atmospheric lidar observations: some comments,
Appl. Optics,
23, 652, https://doi.org/10.1364/AO.23.000652, 1984.
Frioud, M., Mitev, V., Matthey, R., Häberli, C., Richner, H., Werner, R., and Vogt, S.:
Elevated aerosol stratification above the Rhine Valley under strong anticyclonic conditions,
Atmos. Environ.,
37, 1785–1797, https://doi.org/10.1016/S1352-2310(03)00049-9, 2003.
Guo, J., Miao, Y., Zhang, Y., Liu, H., Li, Z., Zhang, W., He, J., Lou, M., Yan, Y., Bian, L., and Zhai, P.: The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data, Atmos. Chem. Phys., 16, 13309–13319, https://doi.org/10.5194/acp-16-13309-2016, 2016.
Haeffelin, M., Angelini, F., Morille, Y., Martucci, G., Frey, S., Gobbi, G. P., Lolli, S., O'Dowd, C. D., Sauvage, L., Xueref-Rémy, I., Wastine, B., and Feist, D. G.:
Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe,
Bound.-Lay. Meteorol.,
143, 49–75, https://doi.org/10.1007/s10546-011-9643-z, 2012.
Hänel, A., Baars, H., Althausen, D., Ansmann, A., Engelmann, R., and Sun, J. Y.:
One-year aerosol profiling with EUCAARI Raman lidar at Shangdianzi GAW station: Beijing plume and seasonal variations: One-year Aerosol Profiling Near Beijing,
J. Geophys. Res.-Atmos.,
117, https://doi.org/10.1029/2012JD017577, 2012.
Hao, L., Garmash, O., Ehn, M., Miettinen, P., Massoli, P., Mikkonen, S., Jokinen, T., Roldin, P., Aalto, P., Yli-Juuti, T., Joutsensaari, J., Petäjä, T., Kulmala, M., Lehtinen, K. E. J., Worsnop, D. R., and Virtanen, A.: Combined effects of boundary layer dynamics and atmospheric chemistry on aerosol composition during new particle formation periods, Atmos. Chem. Phys., 18, 17705–17716, https://doi.org/10.5194/acp-18-17705-2018, 2018.
Hayden, K. L., Anlauf, K. G., Hoff, R. M., Strapp, J. W., Bottenheim, J. W., Wiebe, H. A., Froude, F. A., Martin, J. B., Steyn, D. G., and McKendry, I. G.:
The vertical chemical and meteorological structure of the boundary layer in the Lower Fraser Valley during Pacific '93,
Atmos. Environ.,
31, 2089–2105, https://doi.org/10.1016/S1352-2310(96)00300-7, 1997.
Hennemuth, B. and Lammert, A.:
Determination of the Atmospheric Boundary Layer Height from Radiosonde and Lidar Backscatter,
Bound.-Lay. Meteorol.,
120, 181–200, https://doi.org/10.1007/s10546-005-9035-3, 2006.
Hooper, W. P. and Eloranta, E. W.:
Lidar measurements of wind in the planetary boundary layer: the method, accuracy and results from joint measurements with radiosonde and kytoon,
J. Clim. Appl. Meteorol.,
25, 990–1001, 1986.
Ji, H., Chen, S., Zhang, Y., Chen, H., Guo, P., and Chen, H.:
Calibration method for the reference parameter in Fernald and Klett inversion combining Raman and Elastic return,
J. Quant. Spectrosc. Ra.,
188, 71–78, https://doi.org/10.1016/j.jqsrt.2016.06.041, 2017.
Ji, H., Zhang, Y., Chen, S., Chen, H., and Guo, P.:
Aerosol characteristics inversion based on the improved lidar ratio profile with the ground-based rotational Raman–Mie lidar,
Opt. Commun.,
416, 54–60, https://doi.org/10.1016/j.optcom.2018.02.003, 2018a.
Ji, H., Chen, S., Zhang, Y., Chen, H., Guo, P., and Zhao, P.: Comparison of air quality at different altitudes from multi-platform measurements in Beijing, Atmos. Chem. Phys., 18, 10645–10653, https://doi.org/10.5194/acp-18-10645-2018, 2018b.
Kotthaus, S. and Grimmond, C. S. B.:
Atmospheric boundary-layer characteristics from ceilometer measurements. Part 1: A new method to track mixed layer height and classify clouds,
Q. J. Roy. Meteor. Soc.,
144, 1525–1538, https://doi.org/10.1002/qj.3299, 2018.
Kumar, Y. B.:
Portable lidar system for atmospheric boundary layer measurements,
Opt. Eng.,
45, 076201, https://doi.org/10.1117/1.2221555, 2006.
Leventidou, E., Zanis, P., Balis, D., Giannakaki, E., Pytharoulis, I., and Amiridis, V.:
Factors affecting the comparisons of planetary boundary layer height retrievals from CALIPSO, ECMWF and radiosondes over Thessaloniki, Greece,
Atmos. Environ.,
74, 360–366, https://doi.org/10.1016/j.atmosenv.2013.04.007, 2013.
Li, H., Yang, Y., Hu, X.-M., Huang, Z., Wang, G., and Zhang, B.:
Application of Convective Condensation Level Limiter in Convective Boundary Layer Height Retrieval Based on Lidar Data,
Atmosphere,
8, 79, https://doi.org/10.3390/atmos8040079, 2017a.
Li, H., Yang, Y., Hu, X.-M., Huang, Z., Wang, G., Zhang, B., and Zhang, T.:
Evaluation of retrieval methods of daytime convective boundary layer height based on lidar data: MEASUREMENT OF BOUNDARY LAYER HEIGHT,
J. Geophys. Res.-Atmos.,
122, 4578–4593, https://doi.org/10.1002/2016JD025620, 2017b.
Li, X., Song, H., Zhai, S., Lu, S., Kong, Y., Xia, H., and Zhao, H.:
Particulate matter pollution in Chinese cities: Areal-temporal variations and their relationships with meteorological conditions (2015–2017),
Environ. Pollut.,
246, 11–18, https://doi.org/10.1016/j.envpol.2018.11.103, 2019.
Liu, B., Ma, Y., Liu, J., Gong, W., Wang, W., and Zhang, M.: Graphics algorithm for deriving atmospheric boundary layer heights from CALIPSO data, Atmos. Meas. Tech., 11, 5075–5085, https://doi.org/10.5194/amt-11-5075-2018, 2018.
Liu, B., Ma, Y., Gong, W., Zhang, M., and Yang, J.:
Improved two-wavelength Lidar algorithm for retrieving atmospheric boundary layer height,
J. Quant. Spectrosc. Ra.,
224, 55–61, https://doi.org/10.1016/j.jqsrt.2018.11.003, 2019.
Lv, Z., Wei, W., Cheng, S., Han, X., and Wang, X.:
Mixing layer height estimated from AMDAR and its relationship with PMs and meteorological parameters in two cities in North China during 2014–2017,
Atmos. Pollut. Res.,
11, 443–453, https://doi.org/10.1016/j.apr.2019.11.017, 2020.
Ma, X., Wang, C., Han, G., Ma, Y., Li, S., Gong, W., and Chen, J.: Regional Atmospheric Aerosol Pollution Detection Based on LiDAR Remote Sensing, Remote Sens.-Basel, 11, 2339, https://doi.org/10.3390/rs11202339, 2019.
Mao, F., Gong, W., Song, S., and Zhu, Z.:
Determination of the boundary layer top from lidar backscatter profiles using a Haar wavelet method over Wuhan, China,
Opt. Laser Technol.,
49, 343–349, https://doi.org/10.1016/j.optlastec.2012.08.017, 2013.
Martucci, G., Matthey, R., Mitev, V., and Richner, H.:
Comparison between backscatter lidar and radiosonde measurements of the diurnal and nocturnal stratification in the lower troposphere,
J. Atmos. Ocean. Tech.,
24, 1231–1244, 2007.
Martucci, G., Milroy, C., and O'Dowd, C. D.:
Detection of Cloud-Base Height Using Jenoptik CHM15K and Vaisala CL31 Ceilometers,
J. Atmos. Ocean. Tech.,
27, 305–318, https://doi.org/10.1175/2009JTECHA1326.1, 2010.
McGrath-Spangler, E. L. and Denning, A. S.:
Estimates of North American summertime planetary boundary layer depths derived from space-borne lidar: PBL DEPTH ESTIMATES FROM CALIPSO LIDAR,
J. Geophys. Res., 117, D15101, https://doi.org/10.1029/2012JD017615, 2012.
Menut, L., Flamant, C., Pelon, J., and Flamant, P. H.:
Urban boundary-layer height determination from lidar measurements over the Paris area,
Appl. Optics,
38, 945, https://doi.org/10.1364/AO.38.000945, 1999.
Nakoudi, K., Giannakaki, E., Dandou, A., Tombrou, M., and Komppula, M.: Planetary boundary layer height by means of lidar and numerical simulations over New Delhi, India, Atmos. Meas. Tech., 12, 2595–2610, https://doi.org/10.5194/amt-12-2595-2019, 2019.
Neff, W. D. and Coulter, R. L.:
Acoustic Remote Sensing,
in: Probing the Atmospheric Boundary Layer,
edited by: Lenschow, D. H.,
American Meteorological Society, Boston, MA, 201–239, 1986.
Ortega, I., Berg, L. K., Ferrare, R. A., Hair, J. W., Hostetler, C. A., and Volkamer, R.:
Elevated aerosol layers modify the O2–O2 absorption measured by ground-based MAX-DOAS,
J. Quant. Spectrosc. Ra.,
176, 34–49, https://doi.org/10.1016/j.jqsrt.2016.02.021, 2016.
Palm, S. P., Hart, W. D., Hlavka, D. L., Welton, E. J., and Spinhirne, J. D.:
The Algorithm Theoretical Basis Document for the GLAS Atmospheric Data Products, NASA, NASA/TM-2012-208641/Vol 6, 148 pp., 2012.
Peng, J., Grimmond, C. S. B., Fu, X., Chang, Y., Zhang, G., Guo, J., Tang, C., Gao, J., Xu, X., and Tan, J.:
Ceilometer-Based Analysis of Shanghai's Boundary Layer Height (under Rain- and Fog-Free Conditions),
J. Atmos. Ocean. Tech.,
34, 749–764, https://doi.org/10.1175/JTECH-D-16-0132.1, 2017.
Pérez-Ramírez, D., Ruiz, B., Aceituno, J., Olmo, F. J., and Alados-Arboledas, L.:
Application of Sun/star photometry to derive the aerosol optical depth,
Int. J. Remote Sens.,
29, 5113–5132, https://doi.org/10.1080/01431160802036425, 2008.
Poltera, Y., Martucci, G., Collaud Coen, M., Hervo, M., Emmenegger, L., Henne, S., Brunner, D., and Haefele, A.: PathfinderTURB: an automatic boundary layer algorithm. Development, validation and application to study the impact on in situ measurements at the Jungfraujoch, Atmos. Chem. Phys., 17, 10051–10070, https://doi.org/10.5194/acp-17-10051-2017, 2017.
Rosati, B., Herrmann, E., Bucci, S., Fierli, F., Cairo, F., Gysel, M., Tillmann, R., Größ, J., Gobbi, G. P., Di Liberto, L., Di Donfrancesco, G., Wiedensohler, A., Weingartner, E., Virtanen, A., Mentel, T. F., and Baltensperger, U.: Studying the vertical aerosol extinction coefficient by comparing in situ airborne data and elastic backscatter lidar, Atmos. Chem. Phys., 16, 4539–4554, https://doi.org/10.5194/acp-16-4539-2016, 2016.
Sawyer, V. and Li, Z.:
Detection, variations and intercomparison of the planetary boundary layer depth from radiosonde, lidar and infrared spectrometer,
Atmos. Environ.,
79, 518–528, https://doi.org/10.1016/j.atmosenv.2013.07.019, 2013.
Seidel, D. J., Zhang, Y., Beljaars, A., Golaz, J.-C., Jacobson, A. R., and Medeiros, B.:
Climatology of the planetary boundary layer over the continental United States and Europe: Boundary Layer Climatology: U.S. and Europe,
J. Geophys. Res.-Atmos.,
117, https://doi.org/10.1029/2012JD018143, 2012.
Shi, Y., Hu, F., Fan, G., and Zhang, Z.: Multiple technical observations of the atmospheric boundary layer structure of a red-alert haze episode in Beijing, Atmos. Meas. Tech., 12, 4887–4901, https://doi.org/10.5194/amt-12-4887-2019, 2019.
Steyn, D. G., Baldi, M., and Hoff, R. M.:
The Detection of Mixed Layer Depth and Entrainment Zone Thickness from Lidar Backscatter Profiles, J. Atmos. Ocean. Tech., 16, 953–959, https://doi.org/10.1175/1520-0426(1999)016<0953:TDOMLD>2.0.CO;2, 1999.
Stull, R. B.: An Introduction to Boundary Layer Meteorology, Kluwer Academic Publishers, Dordrecht, 1988.
Su, J. and Patrick McCormick, M.:
Using multi-wavelength Mie–Raman lidar to measure low-level cloud properties,
J. Quant. Spectrosc. Ra.,
237, 106610, https://doi.org/10.1016/j.jqsrt.2019.106610, 2019.
Su, T., Li, Z., and Kahn, R.:
A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions,
Remote Sens. Environ.,
237, 111519, https://doi.org/10.1016/j.rse.2019.111519, 2020a.
Su, T., Li, Z., Li, C., Li, J., Han, W., Shen, C., Tan, W., Wei, J., and Guo, J.: The significant impact of aerosol vertical structure on lower atmosphere stability and its critical role in aerosol–planetary boundary layer (PBL) interactions, Atmos. Chem. Phys., 20, 3713–3724, https://doi.org/10.5194/acp-20-3713-2020, 2020b.
Toledo, D., Córdoba-Jabonero, C., and Gil-Ojeda, M.:
Cluster Analysis: A New Approach Applied to Lidar Measurements for Atmospheric Boundary Layer Height Estimation,
J. Atmos. Ocean. Tech.,
31, 422–436, https://doi.org/10.1175/JTECH-D-12-00253.1, 2014.
Toledo, D., Córdoba-Jabonero, C., Adame, J. A., De La Morena, B., and Gil-Ojeda, M.:
Estimation of the atmospheric boundary layer height during different atmospheric conditions: a comparison on reliability of several methods applied to lidar measurements,
Int. J. Remote Sens.,
38, 3203–3218, https://doi.org/10.1080/01431161.2017.1292068, 2017.
Tsaknakis, G., Papayannis, A., Kokkalis, P., Amiridis, V., Kambezidis, H. D., Mamouri, R. E., Georgoussis, G., and Avdikos, G.: Inter-comparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece, Atmos. Meas. Tech., 4, 1261–1273, https://doi.org/10.5194/amt-4-1261-2011, 2011.
Virmani, D., Taneja, S., and Malhotra, G.:
Normalization based K means Clustering Algorithm,
arXiv:1503.00900, 2015.
Wang, H., Lu, K., Chen, X., Zhu, Q., Wu, Z., Wu, Y., and Sun, K.: Fast particulate nitrate formation via N2O5 uptake aloft in winter in Beijing, Atmos. Chem. Phys., 18, 10483–10495, https://doi.org/10.5194/acp-18-10483-2018, 2018.
Wang, H., Li, Z., Lv, Y., Xu, H., Li, K., Li, D., Hou, W., Zheng, F., Wei, Y., and Ge, B.:
Observational study of aerosol-induced impact on planetary boundary layer based on lidar and sunphotometer in Beijing,
Environ. Pollut.,
252, 897–906, https://doi.org/10.1016/j.envpol.2019.05.070, 2019.
Wang, H., Li, Z., Lv, Y., Zhang, Y., Xu, H., Guo, J., and Goloub, P.: Determination and climatology of the diurnal cycle of the atmospheric mixing layer height over Beijing 2013–2018: lidar measurements and implications for air pollution, Atmos. Chem. Phys., 20, 8839–8854, https://doi.org/10.5194/acp-20-8839-2020, 2020.
Wang, X. and Wang, K.:
Homogenized Variability of Radiosonde-Derived Atmospheric Boundary Layer Height over the Global Land Surface from 1973 to 2014,
J. Climate,
29, 6893–6908, https://doi.org/10.1175/JCLI-D-15-0766.1, 2016.
Wang, Z. and Sassen, K.:
Cloud Type and Macrophysical Property Retrieval Using Multiple Remote Sensors,
J. Appl. Meteorol.,
40, 1665–1682, https://doi.org/10.1175/1520-0450(2001)040<1665:CTAMPR>2.0.CO;2, 2001.
Weil, J. C.: Stable Boundary Layer Modeling for Air Quality Applications. Air Pollution Modeling and its Application XXI, NATO Science for Peace and Security Series C: Environmental Security, Springer, Dordrecht, 57–61, https://doi.org/10.1007/978-94-007-1359-8_10, 2011.
Winker, D. M. and Vaughan, M. A.:
Vertical distribution of clouds over Hampton, Virginia observed by lidar under the ECLIPS and FIRE ETO programs,
Atmos. Res.,
34, 117–133, https://doi.org/10.1016/0169-8095(94)90084-1, 1994.
Yang, T., Wang, Z., Zhang, W., Gbaguidi, A., Sugimoto, N., Wang, X., Matsui, I., and Sun, Y.: Technical note: Boundary layer height determination from lidar for improving air pollution episode modeling: development of new algorithm and evaluation, Atmos. Chem. Phys., 17, 6215–6225, https://doi.org/10.5194/acp-17-6215-2017, 2017.
Yuval, Levi, Y., Dayan, U., Levy, I., and Broday, D. M.:
On the association between characteristics of the atmospheric boundary layer and air pollution concentrations,
Atmos. Res.,
231, 104675, https://doi.org/10.1016/j.atmosres.2019.104675, 2020.
Zhang, L., Wang, T., Lv, M., and Zhang, Q.:
On the severe haze in Beijing during January 2013: Unraveling the effects of meteorological anomalies with WRF-Chem,
Atmos. Environ.,
104, 11–21, https://doi.org/10.1016/j.atmosenv.2015.01.001, 2015.
Zhang, Y., Zhang, L., Guo, J., Feng, J., Cao, L., Wang, Y., Zhou, Q., Li, L., Li, B., Xu, H., Liu, L., An, N., and Liu, H.:
Climatology of cloud-base height from long-term radiosonde measurements in China,
Adv. Atmos. Sci.,
35, 158–168, https://doi.org/10.1007/s00376-017-7096-0, 2018.
Short summary
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.
Air pollution has an important impact on human health, climatic patterns, and the ecological...
