4.6 Article

Characterization of Elemental Species in PM2.5 Samples Collected in Four Cities of Northeast China

Journal

WATER AIR AND SOIL POLLUTION
Volume 209, Issue 1-4, Pages 15-28

Publisher

SPRINGER
DOI: 10.1007/s11270-009-0176-8

Keywords

Particulate matter; Enrichment factor; Coefficient of divergence; Principal components analysis

Funding

  1. Liaoning Environmental Protection Agency [03008]
  2. Pre study on air quality criteria for particulate matter [200709048]

Ask authors/readers for more resources

A monitoring program of particulate matter was conducted at eight sampling sites in four highly industrialized cities (Shenyang, Anshan, Fushun, and Jinzhou) of Liaoning Province in Northeast China to identify the major potential sources of ambient PM2.5. A total of 814 PM2.5 and PM2.5-10 samples were collected between 2004 and 2005. All PM samples were collected simultaneously in four cities and analyzed gravimetrically for mass concentrations. A sum of 16 elemental species concentrations in the PM samples were determined using inductively coupled plasma atomic emission spectroscopy. Annual means of PM2.5 concentrations ranged from 65.0 to 222.0 mu g m(-3) in all the eight sampling sites, and the spatial and seasonal variations were discussed. Enrichment factors were calculated, and Cr, Cu, Zn, As, Cd, and Pb will be pollution-derived elements. Site-to-site comparisons of PM2.5 species in each city were examined using coefficient of divergence, revealing that the two sites in each city are similar in elemental species. Principle component analysis was used for preliminary source analysis of PM2.5. Three or four factors in each city were isolated, and similar sources (crustal source, coal combustion, vehicle exhaust, iron making, or some other metallurgical activities) were identified at four cities.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Engineering, Environmental

Natural Organic Matter (NOM) Imparts Molecular-Weight-Dependent Steric Stabilization or Electrostatic Destabilization to Ferrihydrite Nanoparticles

Zhixiong Li, Sheyda Shakiba, Ning Deng, Jiawei Chen, Stacey M. Louie, Yandi Hu

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2020)

Article Computer Science, Artificial Intelligence

Four-Dimensional Modeling of fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNNs)

Yu Zhao, Xiang Li, Heng Huang, Wei Zhang, Shijie Zhao, Milad Makkie, Mo Zhang, Quanzheng Li, Tianming Liu

IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS (2020)

Article Engineering, Environmental

Coprecipitation of Fe/Cr Hydroxides with Organics: Roles of Organic Properties in Composition and Stability of the Coprecipitates

Ning Deng, Zhixiong Li, Xiaobing Zuo, Jiawei Chen, Sheyda Shakiba, Stacey M. Louie, William G. Rixey, Yandi Hu

Summary: The study found that different types of organic matter have varying impacts on the sequestration of chromium in Fe/Cr-OM ternary systems and the stability of coprecipitates. Some organic matter exhibits strong complexation capabilities with Fe/Cr ions and Fe/Cr hydroxide particles, leading to structural disorder and fast aggregation of the coprecipitates.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2021)

Article Computer Science, Artificial Intelligence

Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-19

Aoxiao Zhong, Xiang Li, Dufan Wu, Hui Ren, Kyungsang Kim, Younggon Kim, Varun Buch, Nir Neumark, Bernardo Bizzo, Won Young Tak, Soo Young Park, Yu Rim Lee, Min Kyu Kang, Jung Gil Park, Byung Seok Kim, Woo Jin Chung, Ning Guo, Ittai Dayan, Mannudeep K. Kalra, Quanzheng Li

Summary: Deep learning-based image analysis methods have been valuable during the COVID-19 pandemic. Developing a CXR image retrieval model based on deep metric learning can provide clinically meaningful information and support clinical decisions effectively.

MEDICAL IMAGE ANALYSIS (2021)

Article Neurosciences

Characterization of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor in Alzheimer's Disease Using Susceptibility-Weighted Imaging

Peiting You, Xiang Li, Zhijiang Wang, Huali Wang, Bin Dong, Quanzheng Li

Summary: This study investigates the relationship between brain iron deposition measured by SWI and the progression of AD, evaluating the model on a dataset of AD patients, mild cognitive impairment patients, and normal controls. The identified regions related to AD progression overlap with previous genetic studies, and a new potential AD-related gene (MEF2C) has been identified in relation to iron deposition and AD progression in the brain.

FRONTIERS IN HUMAN NEUROSCIENCE (2021)

Article Biochemistry & Molecular Biology

Federated learning for predicting clinical outcomes in patients with COVID-19

Ittai Dayan, Holger R. Roth, Aoxiao Zhong, Ahmed Harouni, Amilcare Gentili, Anas Z. Abidin, Andrew Liu, Anthony Beardsworth Costa, Bradford J. Wood, Chien-Sung Tsai, Chih-Hung Wang, Chun-Nan Hsu, C. K. Lee, Peiying Ruan, Daguang Xu, Dufan Wu, Eddie Huang, Felipe Campos Kitamura, Griffin Lacey, Gustavo Cesar de Antonio Corradi, Gustavo Nino, Hao-Hsin Shin, Hirofumi Obinata, Hui Ren, Jason C. Crane, Jesse Tetreault, Jiahui Guan, John W. Garrett, Joshua D. Kaggie, Jung Gil Park, Keith Dreyer, Krishna Juluru, Kristopher Kersten, Marcio Aloisio Bezerra Cavalcanti Rockenbach, Marius George Linguraru, Masoom A. Haider, Meena AbdelMaseeh, Nicola Rieke, Pablo F. Damasceno, Pedro Mario Cruz E. Silva, Pochuan Wang, Sheng Xu, Shuichi Kawano, Sira Sriswasdi, Soo Young Park, Thomas M. Grist, Varun Buch, Watsamon Jantarabenjakul, Weichung Wang, Won Young Tak, Xiang Li, Xihong Lin, Young Joon Kwon, Abood Quraini, Andrew Feng, Andrew N. Priest, Baris Turkbey, Benjamin Glicksberg, Bernardo Bizzo, Byung Seok Kim, Carlos Tor-Diez, Chia-Cheng Lee, Chia-Jung Hsu, Chin Lin, Chiu-Ling Lai, Christopher P. Hess, Colin Compas, Deepeksha Bhatia, Eric K. Oermann, Evan Leibovitz, Hisashi Sasaki, Hitoshi Mori, Isaac Yang, Jae Ho Sohn, Krishna Nand Keshava Murthy, Li-Chen Fu, Matheus Ribeiro Furtado de Mendonca, Mike Fralick, Min Kyu Kang, Mohammad Adil, Natalie Gangai, Peerapon Vateekul, Pierre Elnajjar, Sarah Hickman, Sharmila Majumdar, Shelley L. McLeod, Sheridan Reed, Stefan Graf, Stephanie Harmon, Tatsuya Kodama, Thanyawee Puthanakit, Tony Mazzulli, Vitor Lima de Lavor, Yothin Rakvongthai, Yu Rim Lee, Yuhong Wen, Fiona J. Gilbert, Mona G. Flores, Quanzheng Li

Summary: Federated learning, a method for training artificial intelligence algorithms while protecting data privacy, was used to predict future oxygen requirements of symptomatic patients with COVID-19 using data from 20 different institutes globally. The study showed improved predictive accuracy and generalizability, setting the stage for wider applications in healthcare.

NATURE MEDICINE (2021)

Article Computer Science, Information Systems

Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data

Wufeng Xue, Jiahui Li, Zhiqiang Hu, Eric Kerfoot, James Clough, Ilkay Oksuz, Hao Xu, Vicente Grau, Fumin Guo, Matthew Ng, Xiang Li, Quanzheng Li, Lihong Liu, Jin Ma, Elias Grinias, Georgios Tziritas, Wenjun Yan, Angelica Atehortua, Mireille Garreau, Yeonggul Jang, Alejandro Debus, Enzo Ferrante, Guanyu Yang, Tiancong Hua, Shuo Li

Summary: This paper evaluated and compared different methods for automatic quantification of the left ventricle from cardiac magnetic resonance images. Results showed that both segmentation-based and direct regression methods can offer good LV quantification performance, with direct regression methods showing potential despite not requiring labeled masks for supervision.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

Article Engineering, Environmental

Selenite and Selenate Sequestration during Coprecipitation with Barite: Insights from Mineralization Processes of Adsorption, Nucleation, and Growth

Ning Deng, Xiaobing Zuo, Andrew G. Stack, Sang Soo Lee, Zehao Zhou, Juliane Weber, Yandi Hu

Summary: The coprecipitation of selenium with barite is influenced by ion-mineral interactions, solubility, and interfacial energy. In homogeneous precipitation, about 10% of sulfate ions are replaced by selenium oxyanions due to adsorption-induced entrapment. In heterogeneous precipitation, organic films enhance the sequestration of selenium oxyanions, while only small amounts of selenium oxyanions are detected.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2022)

Article Engineering, Environmental

(Fe, Cr)(OH)3 Coprecipitation in Solution and on Soil: Roles of Surface Functional Groups and Solution pH

Suona Zhang, Liang Cheng, Xiaobing Zuo, Dawei Cai, Ke Tong, Yandi Hu, Jinren Ni

Summary: The simultaneous precipitation of (Fe, Cr)(OH)3 nanoparticles in both homogeneous and heterogeneous phases was quantified using various characterization techniques. The interactions between the ions and surfaces, as well as the controlling mechanisms, were explored. The findings provide important insights into the sequestration of Cr in natural and engineered settings.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2023)

Proceedings Paper Acoustics

View Classification of Color Doppler Echocardiography via Automatic Alignment Between Doppler and B-Mode Imaging

Jerome Charton, Hui Ren, Jay Khambhati, Jeena DeFrancesco, Justin Cheng, Anam A. Waheed, Sylwia Marciniak, Filipe Moura, Rhanderson Cardoso, Bruno B. Lima, Erik Steen, Eigil Samset, Michael H. Picard, Xiang Li, Quanzheng Li

Summary: This study developed a general framework for view classification of Doppler echocardiography using deep learning techniques. By automatically aligning CDI and B-mode videos, it achieved analysis and diagnosis of heart images.

SIMPLIFYING MEDICAL ULTRASOUND, ASMUS 2022 (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Multi-label Detection and Classification of Red Blood Cells in Microscopic Images

Wei Qiu, Jiaming Guo, Xiang Li, Mengjia Xu, Mo Zhang, Ning Guo, Quanzheng Li

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) (2020)

Article Neurosciences

Assessing Fine-Granularity Structural and Functional Connectivity in Children With Attention Deficit Hyperactivity Disorder

Peng Wang, Xi Jiang, Hanbo Chen, Shu Zhang, Xiang Li, Qingjiu Cao, Li Sun, Lu Liu, Binrang Yang, Yufeng Wang

FRONTIERS IN HUMAN NEUROSCIENCE (2020)

Article Computer Science, Information Systems

Automated Semantic Segmentation of Red Blood Cells for Sickle Cell Disease

Mo Zhang, Xiang Li, Mengjia Xu, Quanzheng Li

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)

Proceedings Paper Engineering, Biomedical

ASCNET: ADAPTIVE-SCALE CONVOLUTIONAL NEURAL NETWORKS FOR MULTI-SCALE FEATURE LEARNING

Mo Zhang, Jie Zhao, Xiang Li, Li Zhang, Quanzheng Li

2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020) (2020)

Article Computer Science, Information Systems

Sparse Representation-Based Denoising for High-Resolution Brain Activation and Functional Connectivity Modeling: A Task fMRI Study

Seongah Jeong, Xiang Li, Jiarui Yang, Quanzheng Li, Vahid Tarokh

IEEE ACCESS (2020)

No Data Available