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Journal articles on the topic 'Coupled matrix factorization'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Wei, Chuyuan, Fangfang Li, Xiongzhong Fan, and Qiang Zhan. "Coupled Matrix Factorization for Question Similarity." Chinese Journal of Electronics 25, no. 4 (2016): 665–71. http://dx.doi.org/10.1049/cje.2016.06.034.

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Ermiş, Beyza, and A. Taylan Cemgİl. "Data Sharing via Differentially Private Coupled Matrix Factorization." ACM Transactions on Knowledge Discovery from Data 14, no. 3 (2020): 1–27. http://dx.doi.org/10.1145/3372408.

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3

Wu, Qing, Jie Wang, Jin Fan, et al. "Improved Coupled Tensor Factorization with Its Applications in Health Data Analysis." Complexity 2019 (February 5, 2019): 1–16. http://dx.doi.org/10.1155/2019/1574240.

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Coupled matrix and tensor factorizations have been successfully used in many data fusion scenarios where datasets are assumed to be exactly coupled. However, in the real world, not all the datasets share the same factor matrices, which makes joint analysis of multiple heterogeneous sources challenging. For this reason, approximate coupling or partial coupling is widely used in real-world data fusion, with exact coupling as a special case of these techniques. However, to fully address the challenge of tensor factorization, in this paper, we propose two improved coupled tensor factorization meth

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Xiao, Ding, Yugang Ji, Yitong Li, Fuzhen Zhuang, and Chuan Shi. "Coupled matrix factorization and topic modeling for aspect mining." Information Processing & Management 54, no. 6 (2018): 861–73. http://dx.doi.org/10.1016/j.ipm.2018.05.002.

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Yang, Yi, Lixin Han, Zhinan Gou, Baobin Duan, Jun Zhu, and Hong Yan. "Tagrec-CMTF: Coupled Matrix and Tensor Factorization for Tag Recommendation." IEEE Access 6 (2018): 64142–52. http://dx.doi.org/10.1109/access.2018.2877764.

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Li, Heng-Chao, Shuang Liu, Xin-Ru Feng, and Shao-Quan Zhang. "Sparsity-Constrained Coupled Nonnegative Matrix–Tensor Factorization for Hyperspectral Unmixing." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13 (2020): 5061–73. http://dx.doi.org/10.1109/jstars.2020.3019706.

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7

Bracken, Paul. "Factorization of second-order matrix differential operators and a matrix Darboux transformation." Canadian Journal of Physics 81, no. 8 (2003): 977–88. http://dx.doi.org/10.1139/p03-076.

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It is shown that a class of matrix Schrödinger operators can be factored into a product of two first-order matrix operators. The equations that relate the elements in these first-order operators to the elements of the potential matrix of the Schrödinger operator are obtained. They are found to be coupled first-order differential equations in the variables of the first-order matrix operators. Finally, an example of a factorization of a matrix operator is obtained, and a general solution associated to a value of the spectral parameter is given. PACS Nos.: 02.30.Mq, 12.39.Pn

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Yokoya, Naoto, Takehisa Yairi, and Akira Iwasaki. "Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion." IEEE Transactions on Geoscience and Remote Sensing 50, no. 2 (2012): 528–37. http://dx.doi.org/10.1109/tgrs.2011.2161320.

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Acar, Evrim, Gozde Gurdeniz, Morten A. Rasmussen, Daniela Rago, Lars O. Dragsted, and Rasmus Bro. "Coupled Matrix Factorization with Sparse Factors to Identify Potential Biomarkers in Metabolomics." International Journal of Knowledge Discovery in Bioinformatics 3, no. 3 (2012): 22–43. http://dx.doi.org/10.4018/jkdb.2012070102.

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Metabolomics focuses on the detection of chemical substances in biological fluids such as urine and blood using a number of analytical techniques including Nuclear Magnetic Resonance (NMR) spectroscopy and Liquid Chromatography-Mass Spectrometry (LC-MS). Among the major challenges in analysis of metabolomics data are (i) joint analysis of data from multiple platforms, and (ii) capturing easily interpretable underlying patterns, which could be further utilized for biomarker discovery. In order to address these challenges, the authors formulate joint analysis of data from multiple platforms as a

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Zare, Marzieh, Mohammad Sadegh Helfroush, Kamran Kazemi, and Paul Scheunders. "Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition." Remote Sensing 13, no. 15 (2021): 2930. http://dx.doi.org/10.3390/rs13152930.

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Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing research interest. In this paper, a novel approach based on coupled non-negative tensor decomposition is proposed. The proposed method performs a tucker tensor factorization of a low resolution hyperspectral image and a high resolution multispectral image under the constraint of non-negative tensor decomposition (NTD). The conventional matrix factorization methods essentially lose spatio-s

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Almutairi, Faisal M., Nicholas D. Sidiropoulos, and George Karypis. "Context-Aware Recommendation-Based Learning Analytics Using Tensor and Coupled Matrix Factorization." IEEE Journal of Selected Topics in Signal Processing 11, no. 5 (2017): 729–41. http://dx.doi.org/10.1109/jstsp.2017.2705581.

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Choi, Dongjin, Jun-Gi Jang, and U. Kang. "S3CMTF: Fast, accurate, and scalable method for incomplete coupled matrix-tensor factorization." PLOS ONE 14, no. 6 (2019): e0217316. http://dx.doi.org/10.1371/journal.pone.0217316.

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13

Wu, Ruiyuan, Hoi-To Wai, and Wing-Kin Ma. "Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-Resolution." IEEE Transactions on Signal Processing 68 (2020): 1728–43. http://dx.doi.org/10.1109/tsp.2020.2975910.

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14

Mosayebi, Raziyeh, and Gholam-Ali Hossein-Zadeh. "Correlated coupled matrix tensor factorization method for simultaneous EEG-fMRI data fusion." Biomedical Signal Processing and Control 62 (September 2020): 102071. http://dx.doi.org/10.1016/j.bspc.2020.102071.

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15

Zhao, Yang, Chao Wang, Jihong Pei, and Xuan Yang. "Nonlinear loose coupled non-negative matrix factorization for low-resolution image recognition." Neurocomputing 443 (July 2021): 183–98. http://dx.doi.org/10.1016/j.neucom.2021.02.068.

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Behie, A., D. Collins, P. A. Forsyth, and P. H. Sammon. "Fully Coupled Multiblock Wells in Oil Simulation." Society of Petroleum Engineers Journal 25, no. 04 (1985): 535–42. http://dx.doi.org/10.2118/11877-pa.

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Abstract A fully coupled treatment of oil wells that are completed in more than one zone results in a bordered matrix. This paper develops solution algorithms that incorporate paper develops solution algorithms that incorporate existing direct and iterative (incomplete LU) solutions in a straightforward manner. Timings in scalar and vector modes on the Cray for a typical reservoir simulation problem are presented. problem are presented. Introduction Numerical simulation of oil reservoirs requires the solution of coupled sets of highly nonlinear partial differential equations. These equations r

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SPARENBERG, JEAN-MARC, ANDREY M. PUPASOV, BORIS F. SAMSONOV, and DANIEL BAYE. "EXACTLY-SOLVABLE COUPLED-CHANNEL MODELS FROM SUPERSYMMETRIC QUANTUM MECHANICS." Modern Physics Letters B 22, no. 23 (2008): 2277–86. http://dx.doi.org/10.1142/s0217984908017023.

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Starting from a system of N radial Schrödinger equations with a vanishing potential and finite threshold differences between the channels, a coupled N × N exactly-solvable potential model is obtained with the help of a single non-conservative supersymmetric transformation. The obtained potential matrix, which subsumes a result obtained in the literature, has a compact analytical form, as well as its Jost matrix. It depends on N(N + 1)/2 unconstrained parameters and on one upper-bounded parameter, the factorization energy. For N = 2, previous results are reviewed, in particular regarding the nu

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Yang, Zhen, Weitong Chen, and Jian Huang. "Enhancing recommendation on extremely sparse data with blocks-coupled non-negative matrix factorization." Neurocomputing 278 (February 2018): 126–33. http://dx.doi.org/10.1016/j.neucom.2017.04.080.

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Zhang, Kai, Min Wang, Shuyuan Yang, Yinghui Xing, and Rong Qu. "Fusion of Panchromatic and Multispectral Images via Coupled Sparse Non-Negative Matrix Factorization." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, no. 12 (2016): 5740–47. http://dx.doi.org/10.1109/jstars.2015.2475754.

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Xue, Zhaohui, Sirui Yang, Hongyan Zhang, and Peijun Du. "Coupled Higher-Order Tensor Factorization for Hyperspectral and LiDAR Data Fusion and Classification." Remote Sensing 11, no. 17 (2019): 1959. http://dx.doi.org/10.3390/rs11171959.

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Hyperspectral and light detection and ranging (LiDAR) data fusion and classification has been an active research topic, and intensive studies have been made based on mathematical morphology. However, matrix-based concatenation of morphological features may not be so distinctive, compact, and optimal for classification. In this work, we propose a novel Coupled Higher-Order Tensor Factorization (CHOTF) model for hyperspectral and LiDAR data classification. The innovative contributions of our work are that we model different features as multiple third-order tensors, and we formulate a CHOTF model

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Yang, Feixia, Fei Ma, Ziliang Ping, and Guixian Xu. "Total Variation and Signature-Based Regularizations on Coupled Nonnegative Matrix Factorization for Data Fusion." IEEE Access 7 (2019): 2695–706. http://dx.doi.org/10.1109/access.2018.2879943.

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Lin, Chia-Hsiang, Fei Ma, Chong-Yung Chi, and Chih-Hsiang Hsieh. "A Convex Optimization-Based Coupled Nonnegative Matrix Factorization Algorithm for Hyperspectral and Multispectral Data Fusion." IEEE Transactions on Geoscience and Remote Sensing 56, no. 3 (2018): 1652–67. http://dx.doi.org/10.1109/tgrs.2017.2766080.

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Asadi, Soodabeh, and Janez Povh. "A Block Coordinate Descent-Based Projected Gradient Algorithm for Orthogonal Non-Negative Matrix Factorization." Mathematics 9, no. 5 (2021): 540. http://dx.doi.org/10.3390/math9050540.

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This article uses the projected gradient method (PG) for a non-negative matrix factorization problem (NMF), where one or both matrix factors must have orthonormal columns or rows. We penalize the orthonormality constraints and apply the PG method via a block coordinate descent approach. This means that at a certain time one matrix factor is fixed and the other is updated by moving along the steepest descent direction computed from the penalized objective function and projecting onto the space of non-negative matrices. Our method is tested on two sets of synthetic data for various values of pen

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Kutlimuratov, Alpamis, Akmalbek Abdusalomov, and Taeg Keun Whangbo. "Evolving Hierarchical and Tag Information via the Deeply Enhanced Weighted Non-Negative Matrix Factorization of Rating Predictions." Symmetry 12, no. 11 (2020): 1930. http://dx.doi.org/10.3390/sym12111930.

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Identifying the hidden features of items and users of a modern recommendation system, wherein features are represented as hierarchical structures, allows us to understand the association between the two entities. Moreover, when tag information that is added to items by users themselves is coupled with hierarchically structured features, the rating prediction efficiency and system personalization are improved. To this effect, we developed a novel model that acquires hidden-level hierarchical features of users and items and combines them with the tag information of items that regularizes the mat

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25

Salazar-Ramírez, M., D. Ojeda-Guillén, R. D. Mota, J. A. Martínez-Nuño, and M. R. Cordero-López. "Algebraic solution and coherent states for the Dirac oscillator interacting with the Aharonov–Casher system in the cosmic string background." Modern Physics Letters A 36, no. 21 (2021): 2150146. http://dx.doi.org/10.1142/s0217732321501467.

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In this paper, we introduce an SU(1, 1) algebraic approach to study the (2 + 1)-Dirac oscillator in the presence of the Aharonov–Casher effect coupled to an external electromagnetic field in the Minkowski spacetime and the cosmic string spacetime. This approach is based on a quantum mechanics factorization method that allows us to obtain the su(1, 1) algebra generators, the energy spectrum and the eigenfunctions. We obtain the coherent states and their temporal evolution for each spinor component of this problem. Finally, for these problems, we calculate some matrix elements and the Schrödinge

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Hristova, Elena, Blagorodka Veleva, Emilia Georgieva, and Hristomir Branzov. "Application of Positive Matrix Factorization Receptor Model for Source Identification of PM10 in the City of Sofia, Bulgaria." Atmosphere 11, no. 9 (2020): 890. http://dx.doi.org/10.3390/atmos11090890.

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The Positive Matrix Factorization (PMF) receptor model is used for identification of source contributions to PM10 sampled during the period January 2019–January 2020 in Sofia. More than 200 filters were analyzed by X-Ray Fluorescence (XRF), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and Ion chromatography for chemical elements and soluble ions. Seasonal patterns of PM10 mass and elements’ concentration are observed with minimum in the summer months and maximum in the cold period. The results from source apportionment (SAP) study showed that the resuspension factor is the main contr

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Filelis-Papadopoulos, Christos K., and George A. Gravvanis. "Hybrid multilevel solution of sparse least-squares linear systems." Engineering Computations 34, no. 8 (2017): 2752–66. http://dx.doi.org/10.1108/ec-10-2016-0353.

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Purpose Large sparse least-squares problems arise in different scientific disciplines such as optimization, data analysis, machine learning and simulation. This paper aims to propose a two-level hybrid direct-iterative scheme, based on novel block independent column reordering, for efficiently solving large sparse least-squares linear systems. Design/methodology/approach Herewith, a novel block column independent set reordering scheme is used to separate the columns in two groups: columns that are block independent and columns that are coupled. The permutation scheme leads to a two-level hiera

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Rebeyrol, Simon, Yannick Deville, Véronique Achard, Xavier Briottet, and Stephane May. "Using a Panchromatic Image to Improve Hyperspectral Unmixing." Remote Sensing 12, no. 17 (2020): 2834. http://dx.doi.org/10.3390/rs12172834.

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Hyperspectral unmixing is a widely studied field of research aiming at estimating the pure material signatures and their abundance fractions from hyperspectral images. Most spectral unmixing methods are based on prior knowledge and assumptions that induce limitations, such as the existence of at least one pure pixel for each material. This work presents a new approach aiming to overcome some of these limitations by introducing a co-registered panchromatic image in the unmixing process. Our method, called Heterogeneity-Based Endmember Extraction coupled with Local Constrained Non-negative Matri

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Wu, Jun, Yu He, Xiaohong Qin, Na Zhao, and Yingpeng Sang. "Click-boosted graph ranking for image retrieval." Computer Science and Information Systems 14, no. 3 (2017): 629–41. http://dx.doi.org/10.2298/csis170212020j.

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Graph ranking is one popular and successful technique for image retrieval, but its effectiveness is often limited by the well-known semantic gap. To bridge this gap, one of the current trends is to leverage the click-through data associated with images to facilitate the graph-based image ranking. However, the sparse and noisy properties of the image click-through data make the exploration of such resource challenging. Towards this end, this paper propose a novel click-boosted graph ranking framework for image retrieval, which consists of two coupled components. Concretely, the first one is a c

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Wang, T., H. Zhang, and H. Lin. "USING COUPLED NONNEGATIVE MATRIX FACTORIZATION (CNMF) UN-MIXING FOR HIGH SPECTRAL AND SPATIAL RESOLUTION DATA FUSION TO ESTIMATE URBAN IMPERVIOUS SURFACE AND URBAN ECOLOGICAL ENVIRONMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 919–23. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-919-2017.

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surfaces has increasingly roused widely interests of researchers in monitoring urban development and determining the overall environmental health of a watershed. However, studies on the impervious surface using multi-spectral imageries is insufficient and inaccurate due to the complexity of urban infrastructures base on the need to further recognize these impervious surface materials in a finer scale. Hyperspectral imageries have been proved to be sensitive to subtle spectral differences thus capable to exquisitely discriminate these similar materials while limited to the low spatial resolutio

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Ma, Fei, Feixia Yang, Ziliang Ping, and Wenqin Wang. "Joint Spatial-Spectral Smoothing in a Minimum-Volume Simplex for Hyperspectral Image Super-Resolution." Applied Sciences 10, no. 1 (2019): 237. http://dx.doi.org/10.3390/app10010237.

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The limitations of hyperspectral sensors usually lead to coarse spatial resolution of acquired images. A well-known fusion method called coupled non-negative matrix factorization (CNMF) often amounts to an ill-posed inverse problem with poor anti-noise performance. Moreover, from the perspective of matrix decomposition, the matrixing of remotely-sensed cubic data results in the loss of data’s structural information, which causes the performance degradation of reconstructed images. In addition to three-dimensional tensor-based fusion methods, Craig’s minimum-volume belief in hyperspectral unmix

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QUAINI, A., and A. QUARTERONI. "A SEMI-IMPLICIT APPROACH FOR FLUID-STRUCTURE INTERACTION BASED ON AN ALGEBRAIC FRACTIONAL STEP METHOD." Mathematical Models and Methods in Applied Sciences 17, no. 06 (2007): 957–83. http://dx.doi.org/10.1142/s0218202507002170.

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We address the numerical simulation of fluid-structure interaction problems characterized by a strong added-mass effect. We propose a semi-implicit coupling scheme based on an algebraic fractional-step method. The basic idea of a semi-implicit scheme consists in coupling implicitly the added-mass effect, while the other terms (dissipation, convection and geometrical nonlinearities) are treated explicitly. Thanks to this kind of explicit–implicit splitting, computational costs can be reduced (in comparison to fully implicit coupling algorithms) and the scheme remains stable for a wide range of

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Aboanber, Ahmed E. "Generalized and Stability Rational Functions for Dynamic Systems of Reactor Kinetics." International Journal of Nuclear Energy 2013 (August 13, 2013): 1–12. http://dx.doi.org/10.1155/2013/903904.

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The base of reactor kinetics dynamic systems is a set of coupled stiff ordinary differential equations known as the point reactor kinetics equations. These equations which express the time dependence of the neutron density and the decay of the delayed neutron precursors within a reactor are first order nonlinear and essentially describe the change in neutron density within the reactor due to a change in reactivity. Outstanding the particular structure of the point kinetic matrix, a semianalytical inversion is performed and generalized for each elementary step resulting eventually in substantia

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Weber, Samuël, Gaëlle Uzu, Aude Calas, et al. "An apportionment method for the oxidative potential of atmospheric particulate matter sources: application to a one-year study in Chamonix, France." Atmospheric Chemistry and Physics 18, no. 13 (2018): 9617–29. http://dx.doi.org/10.5194/acp-18-9617-2018.

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Abstract. Inhaled aerosolized particulate matter (PM) induces cellular oxidative stress in vivo, leading to adverse health outcomes. The oxidative potential (OP) of PM appears to be a more relevant proxy of the health impact of the aerosol rather than the total mass concentration. However, the relative contributions of the aerosol sources to the OP are still poorly known. In order to better quantify the impact of different PM sources, we sampled aerosols in a French city for one year (2014, 115 samples). A coupled analysis with detailed chemical speciation (more than 100 species, including org

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Stansfield, John C., Matthew Rusay, Roger Shan, et al. "Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination." Cancer Informatics 15 (January 2016): CIN.S32468. http://dx.doi.org/10.4137/cin.s32468.

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The goal of this study was to discover a minimally invasive pathway-specific biomarker that is immune to normal cell mRNA contamination for diagnosing head and neck squamous cell carcinoma (HNSCC). Using Elsevier's MedScan natural language processing component of the Pathway Studio software and the TRANSFAC database, we produced a curated set of genes regulated by the signaling networks driving the development of HNSCC. The network and its gene targets provided prior probabilities for gene expression, which guided our CoGAPS matrix factorization algorithm to isolate patterns related to HNSCC s

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Contreras Acosta, Isabel Cecilia, Mahdi Khodadadzadeh, and Richard Gloaguen. "Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping." Remote Sensing 13, no. 12 (2021): 2296. http://dx.doi.org/10.3390/rs13122296.

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Drill-core samples are a key component in mineral exploration campaigns, and their rapid and objective analysis is becoming increasingly important. Hyperspectral imaging of drill-cores is a non-destructive technique that allows for non-invasive and fast mapping of mineral phases and alteration patterns. The use of adapted machine learning techniques such as supervised learning algorithms allows for a robust and accurate analysis of drill-core hyperspectral data. One of the remaining challenge is the spatial sampling of hyperspectral sensors in operational conditions, which does not allow us to

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Jakub, Fabian, and Bernhard Mayer. "3-D radiative transfer in large-eddy simulations – experiences coupling the TenStream solver to the UCLA-LES." Geoscientific Model Development 9, no. 4 (2016): 1413–22. http://dx.doi.org/10.5194/gmd-9-1413-2016.

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Abstract. The recently developed 3-D TenStream radiative transfer solver was integrated into the University of California, Los Angeles large-eddy simulation (UCLA-LES) cloud-resolving model. This work documents the overall performance of the TenStream solver as well as the technical challenges of migrating from 1-D schemes to 3-D schemes. In particular the employed Monte Carlo spectral integration needed to be reexamined in conjunction with 3-D radiative transfer. Despite the fact that the spectral sampling has to be performed uniformly over the whole domain, we find that the Monte Carlo spect

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Hwang, Yunn Lin, and Shen Jenn Huang. "Kinematic and Dynamic Analysis for Closed-Loop Flexible Manufacturing Systems Using Nonlinear Recursive Method." Materials Science Forum 505-507 (January 2006): 1015–20. http://dx.doi.org/10.4028/www.scientific.net/msf.505-507.1015.

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In this paper, a nonlinear recursive method for the dynamic and kinematic analysis of a closed-loop flexible manufacturing system is presented. The kinematic and dynamic models are developed using absolute reference, joint relative, and elastic coordinates as well as joint reaction forces. This recursive method leads to a system of loosely coupled equations of motion. In a closed-loop manufacturing system, cuts are made at selected secondary joints in order to form spanning tree structures. Compatibility conditions and reaction force relationships at the secondary joints are adjoined to the eq

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Huang, Jingling, Yuying Wu, Jiaxun Sun, et al. "Health risk assessment of heavy metal(loid)s in park soils of the largest megacity in China by using Monte Carlo simulation coupled with Positive matrix factorization model." Journal of Hazardous Materials 415 (August 2021): 125629. http://dx.doi.org/10.1016/j.jhazmat.2021.125629.

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Lanz, V. A., S. Henne, J. Staehelin, et al. "Statistical analysis of anthropogenic non-methane VOC variability at a European background location (Jungfraujoch, Switzerland)." Atmospheric Chemistry and Physics 9, no. 10 (2009): 3445–59. http://dx.doi.org/10.5194/acp-9-3445-2009.

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Abstract. In-situ measurements of 7 volatile hydrocarbons, CxHy, and 3 chlorinated organic compounds, CxHyClz, were performed at Jungfraujoch (Switzerland) during eight years (2000–2007). The analysis of 4-h resolved non-methane volatile organic compounds (NMVOCs) was achieved by using gas-chromatography coupled with mass spectrometry (GC-MS). Variabilities in the NMVOC time series dataset were modeled by factor analysis (positive matrix factorization, PMF). Four factors defined the solution space and could be related to NMVOC sources and atmospheric processes. In order to facilitate factor in

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Wang, Liwei, Xinfeng Wang, Rongrong Gu, et al. "Observations of fine particulate nitrated phenols in four sites in northern China: concentrations, source apportionment, and secondary formation." Atmospheric Chemistry and Physics 18, no. 6 (2018): 4349–59. http://dx.doi.org/10.5194/acp-18-4349-2018.

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Abstract. Filter samples of fine particulate matters were collected at four sites in northern China (urban, rural, and mountain) in summer and winter, and the contents of nine nitrated phenols were quantified in the laboratory with the use of ultra-high-performance liquid chromatography coupled with mass spectrometry. During the sampling periods, the concentrations of particulate nitrated phenols exhibited distinct temporal and spatial variation. On average, the total concentration of particulate nitrated phenols in urban Jinan in the wintertime reached 48.4 ng m−3, and those in the summertime

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Han, Lixia, Linghong Chen, Kangwei Li, et al. "Source Apportionment of Volatile Organic Compounds (VOCs) during Ozone Polluted Days in Hangzhou, China." Atmosphere 10, no. 12 (2019): 780. http://dx.doi.org/10.3390/atmos10120780.

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A field sampling campaign of volatile organic compounds (VOCs) was conducted during ozone polluted days at three sites of botanic gardens (HP), industrial areas (XS), and traffic residential mixed areas (ZH) in Hangzhou. The sampling was performed using stainless steel canisters from 6:00 to 20:00 synchronously with a time interval of 2 h on 17 May, 26 June, 20 July, 24 August, and 26 September 2018. A total of 107 species of VOCs for each sample were quantified using two standard gases with a pre-concentrator coupled by GC/MS. The Positive Matrix Factorization (PMF) model was used to identify

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Moreno, T., T. Kojima, F. Amato, et al. "Daily and hourly chemical impact of springtime transboundary aerosols on Japanese air quality." Atmospheric Chemistry and Physics 13, no. 3 (2013): 1411–24. http://dx.doi.org/10.5194/acp-13-1411-2013.

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Abstract. The regular eastward drift of transboundary aerosol intrusions from the Asian mainland into the NW Pacific region has a pervasive impact on air quality in Japan, especially during springtime. Analysis of 24-h filter samples with Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) and Mass Spectrometry (ICP-MS), and hourly Streaker with Particle Induced X-ray Emission (PIXE) samples collected continuously for six weeks reveal the chemistry of successive waves of natural mineral desert dust ("Kosa") and metalliferous sulphatic pollutants arriving in western Japan during s

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Jin, Yali, Caiqing Yan, Amy P. Sullivan, et al. "Significant Contribution of Primary Sources to Water-Soluble Organic Carbon During Spring in Beijing, China." Atmosphere 11, no. 4 (2020): 395. http://dx.doi.org/10.3390/atmos11040395.

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Despite the significant role water-soluble organic carbon (WSOC) plays in climate and human health, sources and formation mechanisms of atmospheric WSOC are still unclear; especially in some heavily polluted areas. In this study, near real-time WSOC measurement was conducted in Beijing for the first time with a particle-into-liquid-sampler coupled to a total organic carbon analyzer during the springtime, together with collocated online measurements of other chemical components in fine particulate matter with a 1 h time resolution, including elemental carbon (EC), organic carbon (OC), multiple

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McGuire, M. L., C. H. Jeong, J. G. Slowik, et al. "Elucidating determinants of aerosol composition through particle-type-based receptor modeling." Atmospheric Chemistry and Physics Discussions 11, no. 3 (2011): 9831–85. http://dx.doi.org/10.5194/acpd-11-9831-2011.

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Abstract. An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed at a semi-rural site in Southern Ontario to characterize the size and chemical composition of individual particles. Particle-type-based receptor modelling of these data was used to investigate the determinants of aerosol chemical composition in this region. Individual particles were classified into particle-types and positive matrix factorization (PMF) was applied to their temporal trends to separate and cross-apportion particle-types to factors. The extent of chemical processing for each factor was assessed by evaluat

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McGuire, M. L., C. H. Jeong, J. G. Slowik, et al. "Elucidating determinants of aerosol composition through particle-type-based receptor modeling." Atmospheric Chemistry and Physics 11, no. 15 (2011): 8133–55. http://dx.doi.org/10.5194/acp-11-8133-2011.

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Abstract. An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed at a semi-rural site in southern Ontario to characterize the size and chemical composition of individual particles. Particle-type-based receptor modelling of these data was used to investigate the determinants of aerosol chemical composition in this region. Individual particles were classified into particle-types and positive matrix factorization (PMF) was applied to their temporal trends to separate and cross-apportion particle-types to factors. The extent of chemical processing for each factor was assessed by evaluat

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Saarikoski, S., H. Timonen, K. Saarnio, et al. "Sources of organic carbon in fine particulate matter in northern European urban air." Atmospheric Chemistry and Physics 8, no. 20 (2008): 6281–95. http://dx.doi.org/10.5194/acp-8-6281-2008.

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Abstract. A major fraction of fine particle matter consists of organic carbon (OC) but its origin is still inadequately known. In this study the sources of OC were investigated in the northern European urban environment in Helsinki, Finland. Measurements were carried out over one year and they included both filter (PM1) and online methods. From the filter samples OC, elemental carbon (EC), water-soluble OC (WSOC), levoglucosan and major ions were analyzed. Filter data together with the concentrations of inorganic gases were analyzed by Positive matrix factorization (PMF) in order to find the s

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Saarikoski, S., H. Timonen, K. Saarnio, et al. "Sources of organic carbon in PM<sub>1</sub> in Helsinki urban air." Atmospheric Chemistry and Physics Discussions 8, no. 2 (2008): 7805–46. http://dx.doi.org/10.5194/acpd-8-7805-2008.

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Abstract. A major fraction of fine particle matter consists of organic carbon (OC) but its origin is still inadequately known. In this study the sources of OC were investigated in the northern European urban environment in Helsinki, Finland. Measurements were carried out over one year and they included both filter (PM1) and online methods. From the filter samples OC, elemental carbon (EC), water-soluble OC (WSOC), levoglucosan and major ions were analyzed. Filter data together with the concentrations of inorganic gases were analyzed by Positive matrix factorization (PMF) method in order to fin

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Zhou, Shengzhen, Perry K. Davy, Minjuan Huang, et al. "High-resolution sampling and analysis of ambient particulate matter in the Pearl River Delta region of southern China: source apportionment and health risk implications." Atmospheric Chemistry and Physics 18, no. 3 (2018): 2049–64. http://dx.doi.org/10.5194/acp-18-2049-2018.

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Abstract. Hazardous air pollutants, such as trace elements in particulate matter (PM), are known or highly suspected to cause detrimental effects on human health. To understand the sources and associated risks of PM to human health, hourly time-integrated major trace elements in size-segregated coarse (PM2.5–10) and fine (PM2.5) particulate matter were collected at the industrial city of Foshan in the Pearl River Delta region, China. Receptor modeling of the data set by positive matrix factorization (PMF) was used to identify six sources contributing to PM2.5 and PM10 concentrations at the sit

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Xu, Weiqi, Conghui Xie, Eleni Karnezi, et al. "Summertime aerosol volatility measurements in Beijing, China." Atmospheric Chemistry and Physics 19, no. 15 (2019): 10205–16. http://dx.doi.org/10.5194/acp-19-10205-2019.

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Abstract. Volatility plays a key role in affecting mass concentrations and the lifetime of aerosol particles in the atmosphere, yet our knowledge of aerosol volatility in relatively polluted environment, e.g., north China, remains poor. Here aerosol volatility in Beijing in summer 2017 and 2018 was measured using a thermodenuder (TD) coupled with an Aerodyne high-resolution aerosol mass spectrometer (AMS) and a soot particle AMS. Our results showed overall similar thermograms for most non-refractory aerosol species compared with those reported in previous studies. However, high mass fraction r

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