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Wang N, Gan Z, Duan F, Chen H, Ma C, Ji J, Sun Z. Adhesive surface-enhanced Raman scattering Cu-Au nanoassembly for the sensitive analysis of particulate matter. J Environ Sci (China) 2023; 128:35-44. [PMID: 36801040 DOI: 10.1016/j.jes.2022.07.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/05/2022] [Accepted: 07/17/2022] [Indexed: 06/18/2023]
Abstract
Surface-enhanced Raman scattering (SERS) has been used in atmospheric aerosol detection as it enables the high-resolution analysis of particulate matter. However, its use in the detection of historical samples without damaging the sampling membrane while achieving effective transfer and the high-sensitivity analysis of particulate matter from sample films remains challenging. In this study, a new type of SERS tape was developed, consisting of Au nanoparticles (NPs) on an adhesive double-sided Cu film (DCu). The enhanced electromagnetic field generated by the coupled resonance of the local surface plasmon resonances of AuNPs and DCu led to an enhanced SERS signal with an experimental enhancement factor of 107. The AuNPs were semi-embedded and distributed on the substrate, and the viscous DCu layer was exposed, enabling particle transfer. The substrates exhibited good uniformity and favorable reproducibility with relative standard deviations of 13.53% and 9.74% respectively, and the substrates could be stored for 180 days with no signs of signal weakening. The application of the substrates was demonstrated by the extraction and detection of malachite green and ammonium salt particulate matter. The results demonstrated that SERS substrates based on AuNPs and DCu are highly promising in real-world environmental particle monitoring and detection.
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Affiliation(s)
- Ning Wang
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Zhiqiang Gan
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hui Chen
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Chensheng Ma
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Jie Ji
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Zhenli Sun
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
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Liu T, Duan F, Ma Y, Ma T, Zhang Q, Xu Y, Li F, Huang T, Kimoto T, Zhang Q, He K. Classification and sources of extremely severe sandstorms mixed with haze pollution in Beijing. Environ Pollut 2023; 322:121154. [PMID: 36736562 DOI: 10.1016/j.envpol.2023.121154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 06/18/2023]
Abstract
Air quality has significantly improved in China; however, new challenges emerge when dust weather is combined with haze pollution during spring in northern China. On March 15, 2021, an extremely severe sandstorm occurred in Beijing, with hourly maximum PM10 and PM2.5 concentrations reaching 5267.7 μg m-3 and 963.9 μg m-3, respectively. Continuous sandstorm events usually lead to complicated pollution status in spring. Three pollution types were identified disregarding the time sequence throughout March. The secondary formation type was dominant, with high ratios of PM2.5/PM10 (mean 74%) and PM1/PM2.5 (mean 52%). This suggests that secondary transformations are the primary cause of heavy pollution, even during the dry seasons. Sandstorm type resulted in dramatic PM10 levels, with a noticeable decrease in PM2.5/PM10 levels (27%), although PM2.5 levels remain high. The transitional pollution type was distinguished by an independent increase in PM10 levels, although PM2.5 and PM1 levels differed from the PM10 levels. Throughout March, the sulfur oxidation rate varied considerably, with high levels during most periods (mean 0.52). A strong correlation indicated that relative humidity was the primary variable promoting the formation of secondary sulfate. Sandstorms promote heterogeneous reactions by providing abundant reaction surfaces from mineral particles, therefore aggravating secondary pollution. The sandstorm air mass from the northwest passing through the sand sources of Mongolia carried not only crustal matter but also organic components, such as bioaerosols, resulting in a sharp increase in the organic carbon in PM2.5.
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Affiliation(s)
- Tianyi Liu
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Fengkui Duan
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
| | - Yongliang Ma
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Tao Ma
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Qinqin Zhang
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yunzhi Xu
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Fan Li
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Tao Huang
- Kimoto Electric Co., Ltd, 3-1 Funahashi-cho Tennoji-ku, Osaka, 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co., Ltd, 3-1 Funahashi-cho Tennoji-ku, Osaka, 543-0024, Japan
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Kebin He
- State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
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Fu JX, Wang M, Duan F, Yan J, Wang Y, Yuan B, Ye H. Contrast-enhanced magnetic resonance angiography in the identification of prostatic arterial anatomy in patients with benign prostatic hyperplasia: prospective comparison with digital subtraction angiography. Clin Radiol 2023; 78:e169-e176. [PMID: 36650079 DOI: 10.1016/j.crad.2022.09.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/03/2022] [Accepted: 09/21/2022] [Indexed: 01/19/2023]
Abstract
AIM To evaluate the utility of contrast-enhanced magnetic resonance angiography (CE-MRA) for identifying prostatic artery (PA) anatomy in patients with benign prostatic hyperplasia (BPH) before PA embolisation (PAE), using digital subtraction angiography (DSA) as the reference standard. MATERIALS AND METHODS A total of 176 patients underwent pelvic CE-MRA at 3 T. DSA was performed within the following 7 days. Two interventional radiologists compared the CE-MRA findings with DSA findings to assess the anatomy of the PAs. The rates of correct identification of the origins and collaterals of the PAs by CE-MRA were calculated. The utility for predicting the optimal X-ray tube angle obliquity for visualising the origins of the PAs by CE-MRA was evaluated. An exact McNemar's test was used to compare the detection rates of the PAs and the collaterals with DSA versus CE-MRA. A two-sided p-value of <0.05 was considered statistically significant. RESULTS Of the 376 PAs identified by DSA, CE-MRA correctly identified the origins of 369 vessels (98.1%), with a 1.9% false-negative rate and no false-positive results. Of the 57 total collaterals identified by DSA, CE-MRA identified 50 vessels correctly (87.7%), with a 12.3% false-negative rate and no false-positive results. No significant differences were observed between CE-MRA and DSA in the identification of the PA origins (p=0.824) and the collaterals (p=0.327). The optimal degree for an oblique projection to visualise the origins of the PAs could be predicted accurately (100%) by pre-procedural CE-MRA. CONCLUSION CE-MRA before PAE can reliably predict the PA anatomy and facilitate procedural planning.
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Affiliation(s)
- J X Fu
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, PR China
| | - M Wang
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, PR China.
| | - F Duan
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, PR China
| | - J Yan
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, PR China
| | - Y Wang
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, PR China
| | - B Yuan
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, PR China
| | - H Ye
- Department of Diagnostic Radiology, Chinese PLA General Hospital, Beijing 100853, PR China
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Shen J, Song Y, Cheng C, Duan F, Liu C, Chai Y, Wang S, Xiong Q, Wu J. Spectroscopic and compositional profiles of dissolved organic matters in urban snow from 2019 to 2021: Focusing on pollution features identification. Water Res 2023; 229:119408. [PMID: 36462254 DOI: 10.1016/j.watres.2022.119408] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
Snow owns stronger adsorption capacity for organic pollutants compared with rain. Huge amounts of anthropogenic dissolved organic matters (DOMs) in the atmosphere may enter the water environment with urban snow and increase water pollution risk. Extracting stable pollution features of urban snow is conducive to identifying the urban snow pollution from the water environment. Herein, we systematically explored the spectroscopic and compositional profiles of urban snow in Beijing from three snow events by multiple analytical tools and extracted stable pollution features of urban snow for the first time. Results showed that conventional pollutants with high concentration were detected in urban snow. The fluorescence signals of humic-like and some protein-like materials, the molecular weight distributions of chromophoric DOM at 254 nm and humic-like materials, and 172 kinds of lignin-like molecular formulas were extracted as stable features for urban snow. These stable features of urban snow laid the foundation for the identification of urban snow pollution and the analysis of the impact mechanisms of atmospheric pollution sources on the water environment.
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Affiliation(s)
- Jian Shen
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yiming Song
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Cheng Cheng
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Chuanyang Liu
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yidi Chai
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China
| | - Siting Wang
- Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China
| | - Qiuran Xiong
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jing Wu
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
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Ma T, Furutani H, Duan F, Kimoto T, Ma Y, Zhu L, Huang T, Toyoda M, He K. Distinct diurnal chemical compositions and formation processes of individual organic-containing particles in Beijing winter. Environ Pollut 2023; 318:120846. [PMID: 36496065 DOI: 10.1016/j.envpol.2022.120846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 12/05/2022] [Accepted: 12/06/2022] [Indexed: 06/17/2023]
Abstract
Organic aerosols (OA) are major components of fine particulate matter, yet their formation mechanism remains unclear, especially in polluted environments. In this study, we investigated the diurnal chemical compositions and formation processes of OA in carbonaceous particles during winter in Beijing using aerosol time-of-flight mass spectrometry. We found that 84.5% of the measured carbonaceous particles underwent aging processes, characterized by larger diameter and more secondary species compared to fresh carbonaceous particles, and presented different chemical compositions of OA in the daytime and nighttime. During the day, under high O3 concentrations, organosulfates and oligomers existed in the aged carbonaceous particles, which were mixed with a higher signal of nitrate compared with sulfate. At night, under high relative humidity, distinct spectral signatures of hydroxymethanesulfonate and organic nitrogen compounds, and minor signals of other hydroxyalkylsulfonates and high molecular weight organic compounds were present in the aged carbonaceous particles, which were mixed with a higher signal of sulfate compared with nitrate. Our results indicated that photochemistry contributed to OA formation in the daytime, while aqueous chemistry played an important role in OA formation in the nighttime. The findings can help improve the performance of air quality and climate models on OA simulation.
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Affiliation(s)
- Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Hiroshi Furutani
- Support Center for Scientific Instrument Renovation and Custom Fabrication, Osaka University, Osaka, 560-0043, Japan; Project Research Center for Fundamental Sciences, Graduate School of Science, Osaka University, Osaka, 560-0043, Japan
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Takashi Kimoto
- Kimoto Electric Co., Ltd., 3-1 Funahashi-cho Tennoji-ku, Osaka 543-0024, Japan
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co., Ltd., 3-1 Funahashi-cho Tennoji-ku, Osaka 543-0024, Japan
| | - Michisato Toyoda
- Project Research Center for Fundamental Sciences, Graduate School of Science, Osaka University, Osaka, 560-0043, Japan
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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6
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Xu JE, Qi XK, Yao S, Han XC, Liu JG, Duan F, Sun CJ. [Motor neuron damage in late-onset Pompe disease: a case report and literature review]. Zhonghua Nei Ke Za Zhi 2023; 62:200-202. [PMID: 36740412 DOI: 10.3760/cma.j.cn112138-20220310-00167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- J E Xu
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
| | - X K Qi
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
| | - S Yao
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
| | - X C Han
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
| | - J G Liu
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
| | - F Duan
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
| | - C J Sun
- Department of Neurology, the Sixth Medical Center of PLA General Hospital, Beijing 100048, China
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Montazari E, Abdel-Wahab N, Johnson D, Spillson C, Elsayes K, Duan F, Yadav S, Allison J, Sharma P, Diab A. 151P Clinical outcome and preliminary immune analysis of phase II clinical trial of combination of tocilizumab with ipilimumab and nivolumab for patients with treatment naïve metastatic melanoma. Immuno-Oncology and Technology 2022. [DOI: 10.1016/j.iotech.2022.100263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Ma T, Duan F, Ma Y, Zhang Q, Xu Y, Li W, Zhu L, He K. Unbalanced emission reductions and adverse meteorological conditions facilitate the formation of secondary pollutants during the COVID-19 lockdown in Beijing. Sci Total Environ 2022; 838:155970. [PMID: 35588831 PMCID: PMC9109998 DOI: 10.1016/j.scitotenv.2022.155970] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 04/23/2022] [Accepted: 05/11/2022] [Indexed: 06/02/2023]
Abstract
During the coronavirus disease 2019 (COVID-19) lockdown in 2020, severe haze pollution occurred in the North China Plain despite the significant reduction in anthropogenic emissions, providing a natural experiment to explore the response of haze pollution to the reduction of human activities. Here, we study the characteristics and causes of haze pollution during the COVID-19 outbreak based on comprehensive field measurements in Beijing during January and February 2020. After excluding the Spring Festival period affected by fireworks activities, we found the ozone concentrations and the proportion of sulfate and nitrate in PM2.5 increased during the COVID-19 lockdown compared with the period before the lockdown, and sulfate played a more important role. Heterogeneous chemistry and photochemistry dominate the formation of sulfate and nitrate during the whole campaign, respectively, and the heterogeneous formation of nitrate at night was enhanced during the lockdown. The coeffects of more reductions in NOx than VOCs, weakened titration of NO, and increased temperature during the lockdown led to the increase in ozone concentrations, thereby promoting atmospheric oxidation capacity and photochemistry. In addition, the increase in relative humidity during the lockdown facilitated heterogeneous chemistry. Our results indicate that unbalanced emission reductions and adverse meteorological conditions induce the formation of secondary pollutants during the COVID-19 lockdown haze, and the formulation of effective coordinated emission-reduction control measures for PM2.5 and ozone pollution is needed in the future, especially the balanced control of NOx and VOCs.
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Affiliation(s)
- Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Qinqin Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Yunzhi Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Wenguang Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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Chen H, Duan F, He K, Du J, Sun Z, Wang S. Constructing a Raman and surface-enhanced Raman scattering spectral reference library for fine-particle analysis. J Environ Sci (China) 2022; 118:1-13. [PMID: 35305757 DOI: 10.1016/j.jes.2021.08.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 08/11/2021] [Accepted: 08/13/2021] [Indexed: 06/14/2023]
Abstract
Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scattering (SERS) are often used to analyze the composition of fine particles to determine their physical and chemical properties as well as reaction mechanisms. However, there is no comprehensive Raman spectral library of fine particles. Furthermore, various studies that used SERS for fine-particle composition analysis showed that the uniqueness of the SERS substrates and different excitation wavelengths can produce a different spectrum for the same fine-particle component. To overcome this limitation, we conducted SERS experiments with a portable Raman spectrometer using two common SERS substrates (silver (Ag) foil and gold nanoparticles (Au NPs)) and a 785 nm laser. Herein, we introduced three main particle component types (sulfate-nitrate-ammonium (SNA), organic material, and soot) with a total of 39 chemical substances. We scanned the solid Raman, liquid Raman, and SERS spectra of these substances and constructed a fine-particle reference library containing 105 spectra. Spectral results indicated that for soot and SNA, the differences in characteristic peaks mainly originated from the solid-liquid phase transition; Ag foil had little effect on this difference, while the Au NPs caused a significant red shift in the peak positions of polycyclic aromatic hydrocarbons. Moreover, with various characteristic peak positions in the three types of spectra, we could quickly and correctly distinguish substances. We hope that this spectral library will aid in the future identification of fine particles.
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Affiliation(s)
- Hui Chen
- Key Laboratory of Resources and Environmental System Optimization of Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jingjing Du
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Zhenli Sun
- Key Laboratory of Resources and Environmental System Optimization of Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
| | - Suhua Wang
- Key Laboratory of Resources and Environmental System Optimization of Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China; Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control, School of Environmental Science and Engineering, Guangdong University of Petrochemical Technology, Maoming 525000 China
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10
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An Z, Li X, Yuan Y, Duan F, Jiang J. Large contribution of non-priority PAHs in atmospheric fine particles: Insights from time-resolved measurement and nontarget analysis. Environ Int 2022; 163:107193. [PMID: 35339920 DOI: 10.1016/j.envint.2022.107193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 02/11/2022] [Accepted: 03/17/2022] [Indexed: 06/14/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs), detrimental to human health, are key components contributing to the carcinogenicity of fine particles. The 16 priority PAHs listed by the United States Environment Protection Agency have been studied extensively. However, other than them, there is a large diversity of PAH species, whose atmospheric concentrations, risks, and variations remain elusive. Here, we carried out a time-resolved nontarget measurement in atmospheric PM2.5 using an improved comprehensive two-dimensional gas chromatography mass spectrometry. The measurement conducted during a 5-day pollution episode at an urban site of Beijing with a time resolution of 2 h. The nontarget analysis of time-resolved chromatographic data was performed for screening PAHs. A total number of 85 PAHs were identified and quantified. We found that other than 16 EPA PAHs, other screened PAHs contributed 43.3% of the total PAH mass concentration and 40.8% poential health risks. Dynamic variations of mass concentrations and their potential health risks of the screened PAHs were captured during a short-term heavy pollution episode, during which the instantaneous PAHs concentrations were much higher than their average concentrations. This study shows the potential for application of nontarget analysis for online comprehensive two-dimensional gas chromatography mass spectrometry and highlights the importance of time-resolved measurement of PAHs in PM2.5 and attention on extended PAHs species other than 16 EPA PAHs.
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Affiliation(s)
- Zhaojin An
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Xue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yi Yuan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
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Li X, An Z, Shen Y, Yuan Y, Duan F, Jiang J. Dynamic variations of phthalate esters in PM 2.5 during a pollution episode. Sci Total Environ 2022; 810:152269. [PMID: 34902399 DOI: 10.1016/j.scitotenv.2021.152269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 11/11/2021] [Accepted: 12/04/2021] [Indexed: 06/14/2023]
Abstract
Phthalate esters (PAEs) as hazardous air pollutants can be easily released during the life cycle of plastic products. In this study, a thermal desorption aerosol comprehensive two-dimensional gas chromatography mass spectrometer coupled with a dual-trap was developed and used to measure the hourly-resolved PAEs characteristics in atmospheric PM2.5 at an urban site. Dimethyl phthalate (DMP), diethyl (DEP), dibutyl (DnBP), benzyl butyl (BBP), di(2-ethylhexyl) (DEHP), and di-n-octyl phthalate (DnOP) in PM2.5 were analyzed. The most abundant compounds were DEHP and DMP, followed by DnBP and DEP. The mass concentrations of the detected PAEs are comparable to those at other urban sites measured using offline methods with a lower time resolution. The concentrations of PAEs showed intense change with the variation of PM2.5 mass concentration. The proportion of DEHP increased while that of DMP decreased with the increase in PM2.5 pollution. Positive correlations between PAEs and PM2.5, organic carbon, and elemental carbon were observed, while PAEs had negative correlation with the ambient temperature. Our observation provides evidences on understanding the volatile and semi-volatile PAEs in the ambient aerosols.
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Affiliation(s)
- Xue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Zhaojin An
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Yicheng Shen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Yi Yuan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
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12
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Li H, Ma Y, Duan F, Huang T, Kimoto T, Hu Y, Huo M, Li S, Ge X, Gong W, He K. Characterization of haze pollution in Zibo, China: Temporal series, secondary species formation, and PM x distribution. Chemosphere 2022; 286:131807. [PMID: 34371362 DOI: 10.1016/j.chemosphere.2021.131807] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 07/13/2021] [Accepted: 08/03/2021] [Indexed: 06/13/2023]
Abstract
An online field observation was conducted in Zibo, China from September 1, 2018 to February 28, 2019, covering autumn and winter. Within the investigation period, the mean mass concentrations of PM1, PM2.5, and PM10 were 49.3, 86.1, and 136.5 μg m-3, respectively. OA (organic aerosol) was the most dominant species in PM2.5 (39.7 %), followed by NO3- (26.3 %) and SO42- (17.0 %), indicating the importance of secondary species on PM2.5. Increase of particles were always accompanied increasing relative humidity (RH), slow wind, and increasing precursors, contributing the secondary transition. SO42- was more susceptible to RH, indicating the dominant role of heterogeneous processes in its secondary formation. As RH increased, its strengthening effect on SO42- increased as well. Photochemistry was the main contributor to the secondary formation of NO3-. The morning and evening rush hours determined the peak of absolute NO3- throughout the day. By classifying particles into three bins, we found that smaller particles were the biggest contributors (larger PM1/PM2.5) of slight pollution (35 < PM2.5<115 μg m-3). When severe haze occurred, PM2.5 contributed more than particles of other sizes (PM1 or PM10). Secondary species contributed more to particles within 2.5 μm but less to larger particles. PM1/PM2.5 was high from 9:00 to 15:00, indicating the strong effect of photochemistry on smaller particles. In comparison, larger particles favored more humid conditions. NO3- preferentially existed in larger particles because the hygroscopicity of preexisting species (SO42- and NO3-) promoted partitioning. SO42- appeared a stable diurnal variation, replying its stable contribution to particles of different sizes.
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Affiliation(s)
- Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China.
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Yunxing Hu
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Mingyu Huo
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Shihong Li
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Xiang Ge
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Wanru Gong
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
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13
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Li W, Duan F, Zhao Q, Song W, Cheng Y, Wang X, Li L, He K. Investigating the effect of sources and meteorological conditions on wintertime haze formation in Northeast China: A case study in Harbin. Sci Total Environ 2021; 801:149631. [PMID: 34467910 DOI: 10.1016/j.scitotenv.2021.149631] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/09/2021] [Accepted: 08/09/2021] [Indexed: 06/13/2023]
Abstract
Heavy haze pollution has occurred frequently in the past few years in Northeast China during winters, which was distinct from other regions in China because of the particular meteorological conditions. In this study, we analyzed the temporal variation, source appointment, and influencing factors of PM2.5 from December 1, 2018 to February 28, 2019 in Harbin. The results showed obvious differences between the non-haze and haze periods. The source appointment based on a single-particle aerosol mass spectrometer showed that coal combustion, vehicle emissions, biomass burning, and secondary inorganic aerosols (SIAs) were the major contributors of PM2.5. It is interesting that from the non-haze to the haze period, contributions of coal combustion and SIAs increased (from 20.2% to 27.3%, and from 17.3% to 18.9%, respectively) while other sources decreased or increased little. It indicated the primary pollutants from heating supply were the most important contributor to haze formation due to the low temperature. Furthermore, from levels I (0 < PM2.5 ≤ 75 μg m-3) to III (115 < PM2.5 ≤ 150 μg m-3), SIAs increased from 15.3% to 19.4% (increased 4.1%), while coal combustion from 23.7% to 27.1% and increased 3.4%. It implied clearly that SIAs played a comparable role in the early stage of the evolution of haze episode as that of coal combustion. Combining data on prevailing winds and results of potential source contribution function indicated that PM2.5 during the haze period was primarily influenced by the air masses originating from the southwestern areas via regional transport. A positive correlation was observed between relative humidity (RH) and haze pollution when RH ≥ 60%, indicating that hygroscopic growth may be the principal factor promoting secondary formation. CAPSULE: Coal combustion was the most important source in Harbin due to the low temperature, and secondary aerosols promoted the early stage of the haze evolution.
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Affiliation(s)
- Wenguang Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Qing Zhao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China; Tsing-huan smart source (Beijing) Technology Co., Ltd., Beijing 100084, China.
| | - Weiwei Song
- School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Yuan Cheng
- School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Xiaoyan Wang
- Environment Monitoring Center, Harbin 150090, China
| | - Lei Li
- Environment Monitoring Center, Harbin 150090, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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14
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Zeba F, Yanning W, Melek J, Duan F, Atalay MK, Jankowich M, Rounds S. Prognostic Significance of Pulmonary Artery to Aorta Ratio and Other CT Markers in Pulmonary Fibrosis With and Without Emphysema. Lung 2021; 199:677-680. [PMID: 34741227 DOI: 10.1007/s00408-021-00490-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 10/25/2021] [Indexed: 11/28/2022]
Abstract
Pulmonary hypertension (PH) is associated with decreased survival in patients with pulmonary fibrosis and combined pulmonary fibrosis and emphysema. Main pulmonary artery (PA) diameter and PA diameter/ascending aortic diameter (PA/AA) ratio, as measured on CT, have recently emerged as specific markers for PH. Our single-center retrospective study found that PA/AA ratio > 1 is associated with decreased survival in individuals with pulmonary fibrosis, with or without emphysema. Our study also describes markers of cardiac remodeling, and the echocardiographic diagnosis of PH in this patient population.
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Affiliation(s)
- F Zeba
- Pulmonary Critical Care Medicine, Dartmouth Hitchcock Medical Center, Lebanon, USA.
| | - W Yanning
- Biostatistics and Center for Statistical Sciences, School of Public Health, Brown University, Providence, USA
| | - J Melek
- Health Informatics, Providence VA Medical Center, Providence, USA
| | - F Duan
- Biostatistics and Center for Statistical Sciences, School of Public Health, Brown University, Providence, USA
| | - M K Atalay
- Diagnostic Imaging and Cardiology, The Rhode Island Hospital, The Warren Alpert Medical School of Brown University, Providence, USA
| | - M Jankowich
- Vascular Research Laboratory, Pulmonary Critical Care Medicine, Providence VA Medical Center, The Warren Alpert Medical School of Brown University, Providence, USA
| | - S Rounds
- Vascular Research Laboratory, Pulmonary Critical Care Medicine, Providence VA Medical Center, The Warren Alpert Medical School of Brown University, Providence, USA
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15
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Zhang S, Sarwar G, Xing J, Chu B, Xue C, Sarav A, Ding D, Zheng H, Mu Y, Duan F, Ma T, He H. Improving the representation of HONO chemistry in CMAQ and examining its impact on haze over China. Atmos Chem Phys 2021; 21:15809-15826. [PMID: 34804135 PMCID: PMC8597575 DOI: 10.5194/acp-21-15809-2021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
We compare Community Multiscale Air Quality (CMAQ) model predictions with measured nitrous acid (HONO) concentrations in Beijing, China for December 2015. The model with the existing HONO chemistry in CMAQ severely under-estimates the observed HONO concentrations with a normalized mean bias of -97%. We revise the HONO chemistry in the model by implementing six additional heterogeneous reactions in the model: reaction of nitrogen dioxide (NO2) on ground surfaces, reaction of NO2 on aerosol surfaces, reaction of NO2 on soot surfaces, photolysis of aerosol nitrate, nitric acid displacement reaction, and hydrochloric acid displacement reaction. The model with the revised chemistry substantially increases HONO predictions and improves the comparison with observed data with a normalized mean bias of -5%. The photolysis of HONO enhances day-time hydroxyl radical by almost a factor of two. The enhanced hydroxyl radical concentrations compare favourably with observed data and produce additional sulfate via the reaction with sulfur dioxide, aerosol nitrate via the reaction with nitrogen dioxide, and secondary organic aerosols via the reactions with volatile organic compounds. The additional sulfate stemming from revised HONO chemistry improves the comparison with observed concentration; however, it does not close the gap between model prediction and the observation during polluted days.
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Affiliation(s)
- Shuping Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Golam Sarwar
- Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27711, USA
| | - Jia Xing
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Chaoyang Xue
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Arunachalam Sarav
- Institute for the Environment, The University of North Carolina at Chapel Hill, 100 Eurpoa Drive, Chapel Hill, NC 27514, USA
| | - Dian Ding
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Haotian Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yujing Mu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
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16
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Li H, Ma Y, Duan F, Zhu L, Ma T, Yang S, Xu Y, Li F, Huang T, Kimoto T, Zhang Q, Tong D, Wu N, Hu Y, Huo M, Zhang Q, Ge X, Gong W, He K. Stronger secondary pollution processes despite decrease in gaseous precursors: A comparative analysis of summer 2020 and 2019 in Beijing. Environ Pollut 2021; 279:116923. [PMID: 33751950 DOI: 10.1016/j.envpol.2021.116923] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/04/2021] [Accepted: 03/05/2021] [Indexed: 06/12/2023]
Abstract
To control the spread of COVID-19, China implemented a series of lockdowns, limiting various offline interactions. This provided an opportunity to study the response of air quality to emissions control. By comparing the characteristics of pollution in the summers of 2019 and 2020, we found a significant decrease in gaseous pollutants in 2020. However, particle pollution in the summer of 2020 was more severe; PM2.5 levels increased from 35.8 to 44.7 μg m-3, and PM10 increased from 51.4 to 69.0 μg m-3 from 2019 to 2020. The higher PM10 was caused by two sandstorm events on May 11 and June 3, 2020, while the higher PM2.5 was the result of enhanced secondary formation processes indicated by the higher sulfate oxidation rate (SOR) and nitrate oxidation rate (NOR) in 2020. Higher SOR and NOR were attributed mainly to higher relative humidity and stronger oxidizing capacity. Analysis of PMx distribution showed that severe haze occurred when particles within Bin2 (size ranging 1-2.5 μm) dominated. SO42-(1/2.5) and SO42-(2.5/10) remained stable under different periods at 0.5 and 0.8, respectively, indicating that SO42- existed mainly in smaller particles. Decreases in NO3-(1/2.5) and increases in NO3-(2.5/10) from clean to polluted conditions, similar to the variations in PMx distribution, suggest that NO3- played a role in the worsening of pollution. O3 concentrations were higher in 2020 (108.6 μg m-3) than in 2019 (96.8 μg m-3). Marked decreases in fresh NO alleviated the titration of O3. Furthermore, the oxidation reaction of NO2 that produces NO3- was dominant over the photochemical reaction of NO2 that produces O3, making NO2 less important for O3 pollution. In comparison, a lower VOC/NOx ratio (less than 10) meant that Beijing is a VOC-limited area; this indicates that in order to alleviate O3 pollution in Beijing, emissions of VOCs should be controlled.
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Affiliation(s)
- Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China.
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Yunzhi Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Fan Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Qinqin Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Nana Wu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Yunxing Hu
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Mingyu Huo
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xiang Ge
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Wanru Gong
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
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17
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Chen H, Duan F, Du J, Yin R, Zhu L, Dong J, He K, Sun Z, Wang S. Surface-enhanced Raman scattering for mixing state characterization of individual fine particles during a haze episode in Beijing, China. J Environ Sci (China) 2021; 104:216-224. [PMID: 33985724 DOI: 10.1016/j.jes.2020.12.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/04/2020] [Accepted: 12/08/2020] [Indexed: 06/12/2023]
Abstract
The nondestructive characterization of the mixing state of individual fine particles using the traditional single particle analysis technique remains a challenge. In this study, fine particles were collected during haze events under different pollution levels from September 5 to 11 2017 in Beijing, China. A nondestructive surface-enhanced Raman scattering (SERS) technique was employed to investigate the morphology, chemical composition, and mixing state of the multiple components in the individual fine particles. Optical image and SERS spectral analysis results show that soot existing in the form of opaque material was predominant during clear periods (PM2.5 ≤ 75 µg/m3). During polluted periods (PM2.5 > 75 µg/m3), opaque particles mixed with transparent particles (nitrates and sulfates) were generally observed. Direct classical least squares analysis further identified the relative abundances of the three major components of the single particles: soot (69.18%), nitrates (28.71%), and sulfates (2.11%). A negative correlation was observed between the abundance of soot and the mass concentration of PM2.5. Furthermore, mapping analysis revealed that on hazy days, PM2.5 existed as a core-shell structure with soot surrounded by nitrates and sulfates. This mixing state analysis method for individual PM2.5 particles provides information regarding chemical composition and haze formation mechanisms, and has the potential to facilitate the formulation of haze prevention and control policies.
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Affiliation(s)
- Hui Chen
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jingjing Du
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Ranhao Yin
- Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control, School of Environmental Science and Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jinlu Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Zhenli Sun
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
| | - Suhua Wang
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China; Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control, School of Environmental Science and Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
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18
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Duan F, Tang J, Kong FL, Zou HW, Ni BL, Yu JC. Identification of PTK7 as a promising therapeutic target for thyroid cancer. Eur Rev Med Pharmacol Sci 2021; 24:6809-6817. [PMID: 32633373 DOI: 10.26355/eurrev_202006_21670] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To evaluate the possible involvement of PTK7 in the progression of human thyroid cancer and assess its potential effects on the proliferation and apoptosis of thyroid cancer. PATIENTS AND METHODS Immunohistochemical (IHC) assays and clinical significance analysis were performed to explore the correlations between PTK7 expression and clinical characteristics of patients with thyroid cancer. Quantitative PCR assays and Immunoblot assays were performed to detect the expression of PTK7 in control or PTK7 shRNA plasmids transfected thyroid cancer cells. MTT assays were performed to detect the effects on the proliferation of thyroid cancer cells. Flow cytometry (FCM) assays were performed to assess the changes in cell apoptosis of thyroid cancer. Additionally, the effects of PTK7 on tumor growth were detected through in vivo tumor growth assays. RESULTS PTK7 is highly expressed in human thyroid cancer tissues, and its expression levels are associated with the clinical characteristics, including TNM stage (p=0.015*), and intraglandular dissemination (p=0.024*) of patients with thyroid cancer. PTK7 ablation inhibits cell proliferation and stimulates cell apoptosis of thyroid cancer in vitro. Additionally, PTK7 contributes to tumor growth of thyroid cancer cells in mice. CONCLUSIONS We demonstrated the involvement of PTK7in the progression of thyroid cancer, and therefore provided a novel and promising therapeutic target for thyroid cancer treatment.
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Affiliation(s)
- F Duan
- Department of Otolaryngology Head and Neck Surgery, Jiujiang First People's Hospital, Jiujiang, China.
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19
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Yang S, Duan F, Ma Y, Li H, Wang J, Du Z, Xu Y, Zhang T, Zhu L, Huang T, Kimoto T, Zhang L, He K. Characteristics and seasonal variations of high-molecular-weight oligomers in urban haze aerosols. Sci Total Environ 2020; 746:141209. [PMID: 32763608 DOI: 10.1016/j.scitotenv.2020.141209] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 07/19/2020] [Accepted: 07/22/2020] [Indexed: 06/11/2023]
Abstract
Organic aerosols (OA) undergo sophisticated physiochemical processes in the atmosphere, playing a crucial role in extreme haze formations over the Northern China Plain. However, current understandings of the detailed composition and formation pathways are limited. In this study, high-molecular weight (HMW) species were observed in samples collected year-round in urban Beijing, especially in autumn and winter, during 2016-2017. The positive-ion-mode mass spectra of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) showed that higher signal intensities were obtained in the mass-to-charge (m/z) ranges of 200-500 and 800-900, with repetitive mass difference patterns of m/z 12, 14, 16, and 18. This provided sound evidence that high-molecular-weight oligomers were generated as haze episodes became exacerbated. These oligomer signal intensities were enhanced in the presence of high relative humidity, aerosol water content, and PM2.5 (particles with an aerodynamic diameter ≤ 2.5 μm) mass, proving that the multiphase reaction processes play a fundamental role in haze formation in Beijing. Our study can form a basis for improved air pollution mitigation measures aimed at OA to improve health outcomes.
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Affiliation(s)
- Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Jiali Wang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Zhenyu Du
- National Research Center for Environmental Analysis and Measurement, Beijing 100029, China
| | - Yunzhi Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Ting Zhang
- National Research Center for Environmental Analysis and Measurement, Beijing 100029, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Lifei Zhang
- National Research Center for Environmental Analysis and Measurement, Beijing 100029, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
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Kong T, Chen L, Duan F, Wang L, Zhao X, Hou X, Zhou H, Miao W, Wang L, Hu S. 1797P Efficacy and safety analysis of EP / EC regimen combined with first-line anlotinib hydrochloride in the treatment of extensive small cell lung cancer: Results from a phase II single-arm trial. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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21
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Yang S, Duan F, Ma Y, Li H, Ma T, Zhu L, Huang T, Kimoto T, He K. Mixed and intensive haze pollution during the transition period between autumn and winter in Beijing, China. Sci Total Environ 2020; 711:134745. [PMID: 31822400 DOI: 10.1016/j.scitotenv.2019.134745] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 09/24/2019] [Accepted: 09/29/2019] [Indexed: 05/13/2023]
Abstract
In the Northern China Plain (NCP), extreme haze events with high concentrations of fine particles occur frequently during the winter but rarely occur in autumn. In this study, we present a synthetic analysis of particulate constituents during the historically polluted transition period of autumn-winter in 2018, revealing that mixed-type haze episodes are the result of regional transport, homogeneous/heterogeneous conversion, and sandstorm influences. The hydrolysis process of N2O5 at higher relative humidity levels (>70%), which feature an enhanced nitrate oxidation ratio (0.30-0.70) and NO3- concentration (>60 μg m-3), was the driving factor for high PM2.5 mass concentrations during the observation periods. The long-distance transport of sandstorms, characterized by decreasing PM2.5/PM10 ratios (<30%) from the north/northwest, is the most important factor for the explosive growth of PM10 concentration. These results can help us gain a comprehensive understanding of haze formation and highlight the importance of nitrate chemistry in the aqueous phase. The results suggest that persistent NOx emission reduction measures must be made to better achieve air quality standards in Beijing and the NCP region.
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Affiliation(s)
- Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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22
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Yuan B, Wang Y, Zhang JL, Yan JY, Yuan K, Wang XQ, Fu JX, Duan F, Wang MQ. [Value of lenvatinib for the treatment of advanced hepatocellular carcinoma]. Zhonghua Yi Xue Za Zhi 2020; 100:833-836. [PMID: 32234154 DOI: 10.3760/cma.j.cn112137-20190818-01832] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Objective: To observe the safety and efficacy of lenvatinib for the treatment of medium-advanced hepatocellular carcinoma. Methods: A total of 36 patients with medium-advanced hepatocellular carcinoma from the First Medical Center of the Chinese PLA General Hospital were retrospectively analyzed from January 2018 to May 2019. All patients had shown tumor progression after at least 2 sessions of TACE. The patients were consisted of 30 males and 6 females with age range of 35 to 76 (54±10) years. Patients received orally administered lenvatinib at a dose of 12 mg once daily for patients ≥ 60 kg and 8 mg once daily for patients<60 kg. According to modified RECIST criteria the tumor response, disease control rate, overall survival and progression free survival were evaluated once every 6-8 weeks. The adverse events were recorded. Results: No patient was in complete response, 2 cases (5.7%) in partial response, and 5 cases (14.3%) in stable disease, respectively. Disease control rate was 20.0% (7/35), the overall survival was 11.5 months, and the progression free survival was 5.3 months. The overall incidence of adverse events was 66.7% (24/36). The most frequent adverse events were hypertension, proteinuria, hand-foot skin reaction and abdominal distension. Conclusion: Lenvatinib can extend the overall survival in a percentage of medium-advanced hepatocellular carcinoma patients who were unresectable and refractory to TACE. Although the incidence of adverse events is high, most of them are mild and reversible.
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Affiliation(s)
- B Yuan
- Department of Interventional Radiology, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
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23
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Zhu Y, Qiu X, Yu T, Zhang C, Zhao X, Duan F, Hao D. Feasibility of three-dimensional constructive interference in steady state sequences for evaluating the anterolateral ligament. Clin Radiol 2019; 74:978.e9-978.e14. [PMID: 31582170 DOI: 10.1016/j.crad.2019.08.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 08/20/2019] [Indexed: 11/24/2022]
Abstract
AIM The purpose of the study was to determine the feasibility of three-dimensional (3D) constructive interference in steady state (CISS) sequences for evaluating the anterolateral ligament (ALL). MATERIALS AND METHODS Magnetic resonance imaging (MRI) of the right knee joint in 30 healthy volunteers was performed using a 3 T MRI machine. Axial T2-weighted imaging with fat saturation (T2WI-FS), coronal proton-density-weighted imaging with fat saturation (PDWI-FS), and 3D-CISS were included in the protocol. Multiplanar reconstruction (MPR) and rotating stretched curved planar reconstructions (CPRs) of the ALL at 30°, 60°, 90°, 120°, and 150° were generated from the 3D-CISS images. The visibility of the femoral part, meniscal part, tibial part, meniscal insertion, femoral footprint, and tibial footprint of the ALL on the imaging of all sequences was recorded. RESULTS Based on the CPR of 3D-CISS MRI, the presence of tibial and femoral footprints of the ALL was rated superior to MPR and PDWI-FS (96.67% and 96.67%, respectively; p<0.017). Rotating CPR of 3D-CISS MRI imaging was rated superior to PDWI-FS with respect to the tibial part, meniscal part, and meniscal insertion of the ALL (96.67%, 83.33%, and 83.33%, respectively; p<0.05). Rotating CPR of 3D-CISS MRI was rated superior to PDWI-FS with respect to the femoral part of the ALL, but the difference was not statistically significant (p=0.095). The angle between the ALL and lateral collateral ligament (LCL) on the oblique sagittal image was 18.34±1.88°. CONCLUSIONS The MRI 3D-CISS sequences significantly enhanced the ability to identify the ALL compared to the 2D MRI sequences.
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Affiliation(s)
- Y Zhu
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China
| | - X Qiu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China.
| | - T Yu
- Department of Sport Medicine, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China.
| | - C Zhang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China
| | - X Zhao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China
| | - F Duan
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China
| | - D Hao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China.
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24
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Campbell M, Martin S, Tam A, Sheth R, Singh S, Ahrar K, Slack Tidwell B, Rao P, Karam J, Wood C, Tannir N, Jonasch E, Gao J, Shah A, Blando J, Duan F, Basu S, Allison J, Sharma P, Singh S. A pilot study of tremelimumab (treme) with or without cryoablation (cryo) in patients (pts) in metastatic renal cell carcinoma (mRCC). Ann Oncol 2019. [DOI: 10.1093/annonc/mdz249.059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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25
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Peikert T, Duan F, Rajagopalan S, Karwoski R, Balar A, Lakhani D, Antic S, Bartholmai B, Tucker J, Massion P, Maldonado F. OA06.06 Independent Validation of a Novel High-Resolution Computed Tomography-Based Radiomic Classifier for Indeterminate Lung Nodules. J Thorac Oncol 2019. [DOI: 10.1016/j.jtho.2019.08.439] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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26
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Ye S, Ma T, Duan F, Li H, He K, Xia J, Yang S, Zhu L, Ma Y, Huang T, Kimoto T. Characteristics and formation mechanisms of winter haze in Changzhou, a highly polluted industrial city in the Yangtze River Delta, China. Environ Pollut 2019; 253:377-383. [PMID: 31325882 DOI: 10.1016/j.envpol.2019.07.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 07/03/2019] [Accepted: 07/03/2019] [Indexed: 06/10/2023]
Abstract
Changzhou, an industrial city in the Yangtze River Delta, has been experiencing serious haze pollution, particularly in winter. However, studies pertaining to the haze in Changzhou are very limited, which makes it difficult to understand the characteristics and formation of winter haze in this area, and develop effective control measures. In this study, we carried out continuous online observation of particulate matter, chemical components, and meteorology in Changzhou in February 2017. Our results showed that haze pollution occurred frequently in Changzhou winter and exhibited two patterns: dry haze with low relative humidity (RH) and wet haze with high RH. Water-soluble inorganic ions (SO42-, NO3-, and NH4+) accounted for ∼52.2% of the PM2.5 mass, of which sulfate was dominant in wet haze periods while nitrate was dominant in other periods. With the deterioration of haze pollution, the proportion of nitrate in PM2.5 increased, while sulfate proportion increased under wet haze and decreased under dry haze. Dry haze and wet haze appeared under slow north wind and south wind, respectively, and strong north wind or sea breeze scavenged pollution. We found that formation of nitrate occurred rapidly in daytime with high concentrations of odd oxygen (Ox = O3 + NO2), whereas formation of sulfate occurred rapidly during nighttime with high RH, indicating that photochemistry and heterogeneous reaction were the major formation mechanisms for nitrate and sulfate, respectively. Through the cluster analysis of 36-h backward trajectories, five sources of air masses from three directions were identified. High PM2.5 concentrations (84.1 μg m-3 on average) usually occurred under the influence of two clusters (46%) from the northwest, indicating that regional transport from northern China aggravated the winter haze pollution in Changzhou. Emission reduction, particularly the mobile sources, and regional joint prevention and control can help to mitigate the winter haze in Changzhou.
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Affiliation(s)
- Siqi Ye
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Jing Xia
- Changzhou Environmental Monitoring Center, Changzhou 213001, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
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Ma T, Duan F, He K, Qin Y, Tong D, Geng G, Liu X, Li H, Yang S, Ye S, Xu B, Zhang Q, Ma Y. Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014-2016. J Environ Sci (China) 2019; 83:8-20. [PMID: 31221390 DOI: 10.1016/j.jes.2019.02.031] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Revised: 02/27/2019] [Accepted: 02/28/2019] [Indexed: 05/24/2023]
Abstract
With rapid economic growth and urbanization, the Yangtze River Delta (YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014-2016. In recent years, the concentrations of all air pollutants, except O3, decreased. Spatially, the PM2.5, PM10, SO2, and CO concentrations were higher in the northern YRD region, and NO2 and O3 were higher in the central YRD region. Based on the number of non-attainment days (i.e., days with air quality index greater than 100), PM2.5 was the largest contributor to air pollution in the YRD region, followed by O3, PM10, and NO2. However, particulate matter pollution has declined gradually, while O3 pollution worsened. Meteorological conditions mainly influenced day-to-day variations in pollutant concentrations. PM2.5 concentration was inversely related to wind speed, while O3 concentration was positively correlated with temperature and negatively correlated with relative humidity. The air quality improvement in recent years was mainly attributed to emission reductions. During 2014-2016, PM2.5, PM10, SO2, NOx, CO, NH3, and volatile organic compound (VOC) emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and 0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.
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Affiliation(s)
- Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Yu Qin
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Dan Tong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China; Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Guannan Geng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Xuyan Liu
- National Satellite Meteorological Center, Beijing 100081, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Siqi Ye
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Beiyao Xu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100094, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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28
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Zhang JL, Wang MQ, Duan F, Yuan B. [A comparative study of prostatic artery embolization in the treatment of benign prostatic hyperplasia with different prostatic volume]. Zhonghua Yi Xue Za Zhi 2019; 99:2435-2439. [PMID: 31434423 DOI: 10.3760/cma.j.issn.0376-2491.2019.31.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To compare the efficacy of prostatic artery embolization (PAE) in the treatment of patients with benign prostatic hyperplasia (BPH) with different prostatic volume (PV). Methods: In this single-center, retrospective study, 137 patients, mean age (70±11) years, range 50-89 years, undergoing PAE for BPH between January 2015 and May 2017 in Chinese PLA General Hospital were involved and divided into three groups according to the PV (group A, >80 ml; group B, 40-80 ml; group C, <40 ml). The changes of international prostate symptoms (IPSS) score, quality of life (QoL) score, and maximum urinary flow rate (Q(max)) were compared among the three groups at 1, 6, and 12 months post-PAE. Correlation between the proportion of prostate ischemia at 1 month post-PAE and the proportion of PV reduction at 12 month post-PAE were analyzed, also the correlation between both of them with IPSS and QoL score were analyzed, respectively. Results: Mean baseline prostate volumes were 110 ml in group A (n=62), 67 ml in group B (n=47) and 33 ml in group C (n=28). At 12 months post-PAE, the outcomes of IPSS score and Q(max) in group A were better than those in group B and C (all P<0.05).The proportion of prostate ischemia at 1 month post-PAE and proportion of PV reduction at 12 month post-PAE in group A, B, and C were 61.4%, 49.3%, 38.0%, and 47.3%, 29.3%, 24.6%, respectively. The proportion of prostate ischemia in group A was larger than that in group B and C (P=0.049, 0.004), also the proportion of PV reduction in group A was greater than that in group B and C (P<0.01). The proportion of prostate ischemia at 1 month post-PAE in all three groups were positively correlated with the proportion of PV reduction at 12 month post-PAE (r=0.699, P=0.024; r=0.719, P=0.019; r=0.821, P=0.004), and there were positive correlations between both of them and the improvement of IPSS score at 12 month post-PAE (0.5<r<1.0, all P<0.05), while no correlation with the improvement of QoL score. Conclusions: Patients with BPH with PV larger than 80 ml are more suitable for PAE. The proportion of prostate ischemia and prostate volume reduction after PAE can predict the efficacy of PAE.
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Affiliation(s)
- J L Zhang
- The School of Medicine, Nankai University, Tianjin 300071, China
| | - M Q Wang
- The School of Medicine, Nankai University, Tianjin 300071, China
| | - F Duan
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, China
| | - B Yuan
- Department of Interventional Radiology, Chinese PLA General Hospital, Beijing 100853, China
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29
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Yang L, Duan F, Tian H, He K, Ma Y, Ma T, Li H, Yang S, Zhu L. Biotoxicity of water-soluble species in PM 2.5 using Chlorella. Environ Pollut 2019; 250:914-921. [PMID: 31085478 DOI: 10.1016/j.envpol.2019.04.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 04/04/2019] [Accepted: 04/04/2019] [Indexed: 06/09/2023]
Abstract
China has been faced with severe haze pollution, which is hazardous to human health. Among the air pollutants, PM2.5 (particles with an aerodynamic diameter ≤ 2.5 μm) is the most dangerous because of its toxicity and impact on human health and ecosystems. However, there has been limited research on PM2.5 particle toxicity. In the present study, we collected daily PM2.5 samples from January 1 to March 31, 2018 and selected samples to extract water-soluble species, including SO42-, NO3-, WSOC, and NH4+. These samples represented clean, good, slight, moderate, and heavy pollution days. After extraction using an ultrasonic method, PM2.5 solutions were obtained. We used Chlorella as the test algae and studied the content of chlorophyll a, as well as the variation in fluorescence when they were placed into the PM2.5 extraction solution, and their submicroscopic structure was analyzed using transmission electron microscopy (TEM). The results showed that when the air quality was relatively clean and good (PM2.5 concentration ≤ 75 μg m-3), the PM2.5 extraction solutions had no inhibiting effects on Chlorella, whereas when the air quality was polluted (PM2.5 concentration > 75 μg m-3) and heavily polluted (PM2.5 concentration > 150 μg m-3), with increasing PM2.5 concentrations and exposure time, the chlorophyll a content in Chlorella decreased. Moreover, the maximum photochemical quantum yield (Fv/Fm) of Chlorella obviously decreased, indicating chlorophyll inhibition during polluted days with increasing PM2.5 concentrations. The effects on the chlorophyll fluorescence parameters were also obvious, leading to an increase of energy dissipated per unit reaction center (DIo/RC), suggesting that Chlorella could survive when exposed to PM2.5 solutions, whereas the physiological activities were significantly inhibited. The TEM analysis showed that there were few effects on Chlorella cell microstructure during clean days, whereas plasmolysis occurred during light- and medium-polluted days. With increasing pollution levels, plasmolysis became more and more apparent, until the organelles inside the cells were thoroughly destroyed and most of the parts could not be recognized.
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Affiliation(s)
- Liu Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China; College of Geology and Environment, Xi'an University of Science and Technology, Xi'an, 710054, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China.
| | - Hua Tian
- College of Geology and Environment, Xi'an University of Science and Technology, Xi'an, 710054, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
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Zhang S, Xing J, Sarwar G, Ge Y, He H, Duan F, Zhao Y, He K, Zhu L, Chu B. Parameterization of heterogeneous reaction of SO 2 to sulfate on dust with coexistence of NH 3 and NO 2 under different humidity conditions. Atmos Environ (1994) 2019; 208:133-140. [PMID: 31186616 PMCID: PMC6559380 DOI: 10.1016/j.atmosenv.2019.04.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Sulfate plays an important role in atmospheric haze in China, which has received considerable attention in recent years. Various types of parameterization methods and heterogeneous oxidation rates of SO2 have been used in previous studies. However, properly representing heterogeneous sulfate formation in air quality models remains a big challenge. In this study, we quantified the heterogeneous oxidation reaction using experimental results that approximate the haze conditions in China. Firstly, a series of experiments were conducted to investigate the heterogeneous uptake of SO2 with different relative humidity (RH) levels and the presence of NH3 and NO2 on natural dust surfaces. Then the uptake coefficients for heterogeneous oxidation of SO2 to sulfate at different RH under NH3 and NO2coexistence were parameterized based on the experimental results and implemented in the Community Multiscale Air Quality modeling system (CMAQ). Simulation results suggested that this new parameterization improved model performance by 6.6% in the simulation of wintertime sulfate concentrations for Beijing. The simulated maximum growth rate of SO4 2- during a heavy pollution period increased from 0.97 μg m-3 h-1 to 10.11 μg m-3 h-1. The heterogeneous oxidation of SO2 in the presence of NH3 contributed up to 23% of the sulfate concentration during heavy pollution periods.
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Affiliation(s)
- Shuping Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jia Xing
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Golam Sarwar
- National Exposure Research Laboratory, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27711, USA
| | - Yanli Ge
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yan Zhao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
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Zhang JL, Wang MQ, Duan F, Ye HY, Shen YG, Sun CJ, Zhang XJ, Li ZQ, Jiang WH, Yuan K. [Significance of pelvic contrast enhanced MRA prior to prostatic artery embolization]. Zhonghua Yi Xue Za Zhi 2019; 98:3848-3852. [PMID: 30585028 DOI: 10.3760/cma.j.issn.0376-2491.2018.47.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To assess the values of pelvic contrast enhanced magnetic resonance angiography (MRA) in detection of prostatic artery prior to prostatic arterial embolization(PAE). Methods: This multicenter, prospective study from 5 hospitals in China consisted of 47 patients (mean age (69±16) years, range 56-83 years) who underwent PAE for benign prostatic hyperplasia (BPH) between January 2016 and April 2018, preprocedural prediction of prostatic arteries were determined using contrast enhanced MRA.CE-MRA findings were compared with subsequent intraprocedural digital subtraction angiography (DSA) or DSA combined with cone-beam computed tomography (CT) to assess the sensitivity and specificity with which contrast enhanced MRA predicted the number and origins of prostatic artery, also to assess the optimal oblique projection of PA. Results: In total, 47 patients (94 pelvic sides) with 97 PAs confirmed by DSA or DSA combined with cone-beam CT at the time of embolization, MR angiography successfully identified 88 PAs and their origins , the sensitivity and specificity was 90.7% (88/97) and 93.6% (88/94), respectively.MR angiography correctly determined the bilateral prostatic artery origins in 36 (76.6%) cases.According to the optimal oblique projection of PAs suggested by MR angiography, the origins and trajectory of PAs of all patients underwent PAE with the same oblique projection (20°-45°ipsilateral anterior oblique direction) were clearly displayed when performed the first arteriography. Conclusion: Pelvic contrast enhanced MR angiography with high sensitivity and specificity in detection the origin, trajectory and number of PAs, and it could provide useful information regarding prostatic arteries before PAE.
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Affiliation(s)
- J L Zhang
- School of Medicine, Nankai University, Tianjin 300071, China
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Sun Z, Duan F, He K, Du J, Zhu L. Sulfate-nitrate-ammonium as double salts in PM 2.5: Direct observations and implications for haze events. Sci Total Environ 2019; 647:204-209. [PMID: 30077849 DOI: 10.1016/j.scitotenv.2018.07.107] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 07/06/2018] [Accepted: 07/09/2018] [Indexed: 06/08/2023]
Abstract
Obtaining detailed information on sulfate-nitrate-ammonium (SNA) is fundamentally important to explain the formation of haze in China, since it is a dominant component of fine particulate matter (PM2.5) and plays a critical role in the deterioration of air quality. Several single-particle analysis methods have been applied to study and explain SNA formation; however, determining its mixture state remains a challenge. This study describes a direct observation of the SNA components in atmospheric particles on a single-particle scale, and details the first use of a non-destructive surface-enhanced Raman scattering (SERS) technique for SNA analysis. We studied PM2.5 collected at a site on the premises of Tsinghua University in Beijing, China, during a winter haze episode (12.15.2016-12.23.2016). The on-line data show that the SNA component accounted for 9.4% to 68.2% of the total mass of PM2.5, becoming dominant on heavy haze days, and the sulfate concentration increased with the nitrate concentration (R2 = 0.72). Furthermore, the off-line SERS and scanning electron microscopy-energy dispersive X ray analysis (SEM-EDS) results for the single particles collected also indicated that SNA increase with increasing haze pollution. The existing state of the SNA component on each haze day was observed directly in a non-destructive manner mainly in the form of double salts such as 3(NH4NO3)·(NH4)2SO4 and 2(NH4NO3)·(NH4)2SO4. A Raman mapping experiment further confirmed that the SNA was internally mixed. Our data also show that SNA can evaporate under high-vacuum scanning electron microscopy conditions, suggesting that SERS is an effective method to directly observe SNA without sample loss and may represent a promising single-particle technique to supplement traditional electron microscopy methods. This work will provide evidence for the SNA formation, particularly during haze events.
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Affiliation(s)
- Zhenli Sun
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
| | - Kebin He
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China.
| | - Jingjing Du
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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Yang S, Duan F, Ma Y, He K, Zhu L, Ma T, Ye S, Li H, Huang T, Kimoto T. Haze formation indicator based on observation of critical carbonaceous species in the atmosphere. Environ Pollut 2019; 244:84-92. [PMID: 30326389 DOI: 10.1016/j.envpol.2018.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2018] [Revised: 10/01/2018] [Accepted: 10/01/2018] [Indexed: 06/08/2023]
Abstract
Organic aerosol (OA) are always the most abundant species in terms of relative proportion to PM2.5 concentration in Beijing, while in previous studies, poor link between carbonaceous particles and their gaseous precursors were established based on field observation results. Through this study, we provided a comprehensive analysis of critical carbonaceous species in the atmosphere. The concentrations, diurnal variations, conversions, and gas-particle partitioning (F-factor) of 8 carbonaceous species, carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), volatile organic compounds (VOCs), non-methane hydrocarbon (NMHC), organic carbon (OC), elemental carbon (EC), and water soluble organic compounds (WSOCs), in Beijing were analyzed synthetically. Carbonaceous gases (CO, CO2, VOCs, and CH4) and OC/EC ratios exhibited double-peak diurnal patterns with a pronounced midnight peak, especially in winter. High correlation between VOCs and OC during winter nighttime indicated that OC was formed from VOCs precursors via an unknown mechanism at relative humidity greater than 50% and 80%, thereby promoting WSOC formation in PM1 and PM2.5 respectively. The established F-factor method was effective to describe gas-to-particle transformation of carbonaceous species and was a good indicator for haze events since high F-factors corresponded with enhanced PM2.5 level. Moreover, higher F-factors in winter indicated carbonaceous species were more likely to exist as particles in Beijing. These results can help gain a comprehensive understanding of carbon cycle and formation of secondary organic aerosols from gaseous precursors in the atmosphere.
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Affiliation(s)
- Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China.
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Siqi Ye
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka, 543-0024, Japan
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Sun Z, Duan F, He K, Du J, Yang L, Li H, Ma T, Yang S. Physicochemical analysis of individual atmospheric fine particles based on effective surface-enhanced Raman spectroscopy. J Environ Sci (China) 2019; 75:388-395. [PMID: 30473304 DOI: 10.1016/j.jes.2018.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 06/01/2018] [Accepted: 06/11/2018] [Indexed: 06/09/2023]
Abstract
Fine particles associated with haze pollution threaten the health of more than 400 million people in China. It is therefore of great importance to thoroughly investigate and understand their composition. To determine the physicochemical properties in atmospheric fine particles at the micrometer level, we described a sensitive and feasible surface-enhanced Raman scattering (SERS) method using Ag foil as a substrate. This novel method enhanced the Raman signal intensities up to 10,000 a.u. for ν(NO3-) in fine particles. The SERS effect of Ag foil was further studied experimentally and theoretically and found to have an enhancement factor of the order of ~104. Size-fractionated real particle samples with aerodynamic diameters of 0.4-2.5 μm were successfully collected on a heavy haze day, allowing ready observation of morphology and identification of chemical components, such as soot, nitrates, and sulfates. These results suggest that the Ag-foil-based SERS technique can be effectively used to determine the microscopic characteristics of individual fine particles, which will help to understand haze formation mechanisms and formulate governance policies.
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Affiliation(s)
- Zhenli Sun
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China.
| | - Jingjing Du
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Liu Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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Li H, Duan F, Ma Y, He K, Zhu L, Ma T, Ye S, Yang S, Huang T, Kimoto T. Case study of spring haze in Beijing: Characteristics, formation processes, secondary transition, and regional transportation. Environ Pollut 2018; 242:544-554. [PMID: 30007265 DOI: 10.1016/j.envpol.2018.07.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 04/28/2018] [Accepted: 07/01/2018] [Indexed: 05/13/2023]
Abstract
Continuous haze monitoring was conducted from 12:00 3 April to 12:00 8 April 2016 in Beijing, China to develop a more detailed understanding of spring haze characteristics. The PM2.5 concentration ranged from 6.30 to 165 μg m-3 with an average of 63.8 μg m-3. Nitrate was the most abundant species, accounting for 36.4% of PM2.5, followed by organic carbon (21.5%), NH4+ (19.3%), SO42- (18.8%), and elemental carbon (4.10%), indicating the key role of nitrate in this haze event. Species contribution varied based on the phase of the haze event. For example, sulfate concentration was high during the haze formation phase, nitrate was high during the haze, and secondary organic carbon (SOC) had the highest contribution during the scavenging phase. The secondary transition of sulfate was influenced by SO2, followed by relative humidity (RH) and Ox (O3+NO2). Nitrate formation occurred in two stages: through NO2 oxidation, which was vulnerable to Ox; and by the partitioning of N (+5) which was susceptible to RH and temperature. SOC tended to form when Ox and RH were balanced. According to hourly species behavior, sulfate and nitrate were enriched during haze formation when the mixed layer height decreased. However, SOC accumulated prior to the haze event and during formation, which demonstrated the strong contribution of secondary inorganic aerosols, and the limiting contribution of SOC to this haze case. Investigating backward trajectories showed that high speed northwestern air masses following a straight path corresponded to the clear periods, while southwesterly air masses which traversed heavily polluted regions brought abundant pollutants to Beijing and stimulated the occurrence of haze pollution. Results indicate that the control of NO2 needs to be addressed to reduce spring haze. Finally, the correlation between air mass trajectories and pollution conditions in Beijing reinforce the necessity of inter-regional cooperation and control.
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Affiliation(s)
- Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Siqi Ye
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka 543-0024, Japan
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Abstract
Epoxidized soybean oil methyl esters could be efficiently prepared with the transesterification of epoxidized soybean oil (ESBO) with a lower dosage of methanol using lipase Novozym 435 as catalyst. The optimum parameters were as follows: the molar ratio of 5:1 (methanol to ESBO), 5% Novozym 435 as catalyst, at 45 °C for 14 h, with a stirring speed of 600rpm, under which the epoxidized soybean oil methyl esters (ESBOME) could be obtained at a 95.7% yield. During the enzymatic transesterification process, the oxirane oxygen values were kept unchangeable, which indicated that excellent functional group tolerance could be achieved under such mild reaction conditions. In addition, the recyclability of the immobilized enzyme Novozym 435 in this transesterification process was examined and the results showed that the biocatalyst could be reused ten times without losing any reaction activity or selectivity. And the final products of ESBOME were also identified by IR and NMR analysis. The kinetic data obtained followed the Ping-Pong Bi mechanism model (Vmax = 6.132 mol·L-1min-1, Km,S = 0,0001 mol·L-1, Km, A = 796.148 mol·L-1, Ki, A = 0,0004 mol·L-1) with competitive inhibition by methanol.
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Duan F, Su XL, Wei ZX, Kong DW, Huang TY, Wang S. Efficacy of computed tomography-guided implantation of 125I seeds in the treatment of refractory malignant tumors accompanied with cancer pain and its influence on tumor markers in the serum. Eur Rev Med Pharmacol Sci 2018; 22:1595-1601. [PMID: 29630101 DOI: 10.26355/eurrev_201803_14564] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE This study intended to explore the efficacy of computed tomography (CT)-guided implantation of iodine-125 (125I) seeds in the treatment of refractory malignant tumors with cancer pain and its influence on tumor markers in the serum. PATIENTS AND METHODS 76 patients with refractory malignant tumors accompanied by cancer pain that received treatments in LongHua Hospital Shanghai University of Traditional Chinese Medicine from September 2013 to August 2014 were selected. They were divided into control group and observation group using a random number table (38 patients in each group). Patients in the control group received simple chemotherapy, while those in the observation group undergone CT-guided implantation of 125I seeds in combination with chemotherapy. Recent efficacy and 1-3-year survival rate were compared between the two groups of patients. The degree of pain relief after treatment was also compared between the two groups of patients. Electrochemiluminescence method was used to detect the concentrations of carcinoembryonic antigen (CEA), sugar chain antigen 199 (CA 199), sugar chain antigen 125 (CA 125), neuron-specific enolase (NSE) and cytokeratin-19-fragment (CYFRA21-1) in the two groups of patients before treatment, and 3 days, 7 days and 30 days after treatment. RESULTS Recent disease control rate of the patients in the observation group was higher than that of the patients in the control group (p<0.05). The 1-3-year survival rate after surgery in the observation group was significantly higher than that in the control group (p<0.05). The total efficiency of pain control in the observation group was significantly higher than that in the control group (p<0.05). The levels of tumor markers in the two groups of patients were significantly decreased after treatment, while the reduction in the observation group was more evident than that in the control group (p<0.05). CONCLUSIONS Our results showed that CT-guided implantation of 125I seeds is effective for the treatment of patients with refractory malignant tumors accompanied by cancer pain. It can reduce the levels of tumor markers, improve the survival rate and prolong the survival time of the patients.
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Affiliation(s)
- F Duan
- Department of Radiology, LongHua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, P.R. China.
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Young R, Hopkins R, Duan F, Greco E, Chiles C, Aberle D, Gamble G. OA 15.03 Gene-Based Risk Stratification of NLST-ACRIN Screening Participants Identifies The “Sweet Spot” of Screening (N=10,054). J Thorac Oncol 2017. [DOI: 10.1016/j.jtho.2017.09.415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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39
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Hopkins R, Young R, Duan F, Greco E, Chiles C, Aberle D, Gamble G. Lung cancer screening and the effects of competing causes of death in the ACRIN-NLST sub-study. Respir Med 2017. [DOI: 10.1016/j.rmed.2017.07.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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40
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Young R, Hopkins R, Duan F, Greco E, Chiles C, Aberle D, Gamble G. Stratification of NLST-ACRIN screening participants identifies the “sweet spot” of screening by identifying early stage lung cancers most amenable to curative surgery (N=10,054). Respir Med 2017. [DOI: 10.1016/j.rmed.2017.07.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Abstract
The strict control on emissions implemented in Beijing, China, during the 2015 China Victory Day Parade (V-day Parade) to commemorate the 70(th) Anniversary of Victory in World War II, provided a good opportunity to investigate the relationship between emission sources and aerosol chemistry in a heavily polluted megacity. From August 11 to September 3, 2015, an Aerosol Chemical Speciation Monitor was deployed in urban Beijing, together with other collocated instruments, for the real-time measurement of submicron aerosol characteristics. The average PM1 mass concentration was 11.3 (±6.7) μg m(-3) during the V-day Parade, 63.5% lower than that before the V-day Parade. Differently to the relatively smaller decrease of organics (53%), secondary inorganic aerosols (sulfate, nitrate and ammonium) showed significant reductions of 65-78% during the V-day Parade. According to the positive matrix factorization results, primary organic aerosol (POA) from traffic and cooking emissions decreased by 41.5% during the parade, whereas secondary organic aerosol (SOA) presented a much greater reduction (59%). The net effectiveness of emission control measures was investigated further under comparable weather conditions before and during the parade. By excluding the effects of meteorological parameters, the total PM1 mass was reduced by 52-57% because of the emission controls. Although the mass concentrations of aerosol species were reduced substantially, the PM1 bulk composition was similar before and during the control period as a consequence of synergetic control of various precursors. The emission restrictions also suppressed the secondary formation processes of sulfate and nitrate, indicated by the substantially reduced SOR and NOR (molar ratios of sulfate or nitrate to the sums of the sulfate and SO2 or nitrate and NO2) during the event. The study also explored the influence of emission controls on the evolution of organic aerosol using the mass ratios of SOA/POA and oxygen-to-carbon ratios. The results showed that for northwesterly airflows, emission restrictions during the V-day Parade also reduced the oxidation degree of organic aerosol.
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Affiliation(s)
- Haiyan Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China. and Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Bo Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China and Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China and State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
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Li H, Ma Y, Duan F, He K, Zhu L, Huang T, Kimoto T, Ma X, Ma T, Xu L, Xu B, Yang S, Ye S, Sun Z, An J, Zhang Z. Typical winter haze pollution in Zibo, an industrial city in China: Characteristics, secondary formation, and regional contribution. Environ Pollut 2017; 229:339-349. [PMID: 28609735 DOI: 10.1016/j.envpol.2017.05.081] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 05/09/2017] [Accepted: 05/29/2017] [Indexed: 06/07/2023]
Abstract
Heavy haze pollution occurs frequently in northern China, most critically in the Beijing-Tianjin-Hebei area (BTH). Zibo, an industrial city located in Shandong province, is often listed as one of the top ten most polluted cities in China, particularly in winter. However, no studies of haze in Zibo have been conducted, which limits the understanding of the source and formation of haze pollution in this area, as well as mutual effects with the BTH area. We carried out online and continuous integrated field observation of particulate matter in winter, from 11 to 25 January 2015. SO42-, NO3-, and NH4+ (SIA) and organics were the main constituents of PM2.5, contributing 59.4% and 33.6%, respectively. With the increasing severity of pollution, the contribution of SIA increased while that of organics decreased. Meteorological conditions play an important role in haze formation; high relative humidity (RH) and low wind speed increased both the accumulation of pollutants and the secondary transition from gas precursors (gas-particle phase partitioning). Since RH and the presence of O3 can indicate heterogeneous and photochemistry processes, respectively, we carried out correlation analysis and linear regression to identify their relative importance to the three main secondary species (sulfate, nitrate, and secondary organic carbon (SOC)). We found that the impact of RH is in the order of SO42- > NO3- > SOC, while the impact of O3 is reversed, in the order of SOC > NO3- > SO42-, indicating different effect of these factors on the secondary formation of main species in winter. Cluster analysis of backward trajectories showed that, during the observation period, six directional sources of air masses were identified, and more than 90% came from highly industrialized areas, indicating that regional transport from industrialized areas aggravates the haze pollution in Zibo. Inter-regional joint prevention and control is necessary to prevent further deterioration of the air quality.
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Affiliation(s)
- Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Xiaoxuan Ma
- School of Resources and Environmental Engineering, Shandong University of Technology, Zibo 255049, Shandong Province, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Lili Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Beiyao Xu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100094, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Siqi Ye
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Zhenli Sun
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Jiutao An
- School of Resources and Environmental Engineering, Shandong University of Technology, Zibo 255049, Shandong Province, China
| | - Zhaolu Zhang
- School of Resources and Environmental Engineering, Shandong University of Technology, Zibo 255049, Shandong Province, China
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Xu L, Duan F, He K, Ma Y, Zhu L, Zheng Y, Huang T, Kimoto T, Ma T, Li H, Ye S, Yang S, Sun Z, Xu B. Characteristics of the secondary water-soluble ions in a typical autumn haze in Beijing. Environ Pollut 2017; 227:296-305. [PMID: 28477554 DOI: 10.1016/j.envpol.2017.04.076] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 04/25/2017] [Accepted: 04/26/2017] [Indexed: 06/07/2023]
Abstract
Four haze episodes (EPs) were observed in October 2014 in Beijing, China. For better understanding of the characteristics and the formation mechanisms of PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm), especially secondary water-soluble inorganic species in these haze events, hourly concentrations of PM2.5, sulfate, nitrate, and ammonium (SNA) were measured in this study. Concentrations of gaseous pollutants and meteorological parameters were also measured. The average concentration of PM2.5 was 106.6 ± 83.5 μg m-3, which accounted for around 53% of PM10 (particulate matter with an aerodynamic diameter ≤ 10 μm) mass. Nitrogen dioxide (NO2) concentration was much higher than that of sulfur dioxide (SO2) since October is a non-heating month. SNA is the most abundant secondary water-soluble inorganic species and contributed to 33% of PM2.5 mass concentration. Sulfur oxidation ratio (SOR) was much higher than nitrogen oxidation ratio (NOR). NOR and SOR increased with elevated PM2.5 levels and heterogeneous processes seemed to be the most plausible explanation of this increase. Relative humidity (RH), which is of great influence on aerosol liquid water content (ALWC), played a considerable role in the formation of secondary inorganic aerosols, accelerated the secondary transformation of gaseous precursors, and further aggravated haze pollution. The positive feedback loop associated with high aerosol levels and low planetary boundary layer (PBL) height led to the evolution and exacerbation of heavy haze pollution. Fire maps and 48-h air mass backward trajectories supported the significant impact of biomass burning activities and regional transport on haze formation over Beijing in October 2014.
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Affiliation(s)
- Lili Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China.
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China.
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Yixuan Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku, Osaka 543-0024, Japan
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Siqi Ye
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Zhenli Sun
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
| | - Beiyao Xu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100094, China
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Wang Q, Duan F, Liu P, Wang PF, Wang MX. Expression of anti-SRP19 antibody in muscle tissues from patients with autoimmune necrotizing myopathy. Genet Mol Res 2016; 15:gmr8307. [PMID: 27525944 DOI: 10.4238/gmr.15038307] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
This study aimed to investigate the role of anti-SRP19 antibody in muscle tissues of patients with autoimmune necrotizing myopathy. Immunohistochemistry staining was used to determine the expression of anti-SRP19 antibodies in muscle tissues of autoimmune necrotizing myopathy patients. Results demonstrated that anti-SRP19 antibody was expressed in 71.4% (20/28) of muscle tissue specimens from patients with autoimmune necrotizing myopathy. Anti-SRP19 antibody expression was mainly localized in cytoplasm of necrotic muscle fibers surrounding the small blood vessels and interstitial cells. There were no significant differences in the age, course of disease, muscle, and creatine kinase levels between patients with positive or negative expression of anti-SRP19 antibodies. The expression levels of anti-SRP19, serum anti-nuclear antibodies, as well as anti-Ro-52, anti- SSA, anti-Sm, and anti-Jo-1 antibodies were not significantly different among groups. This study demonstrates that anti-SRP19 antibody is highly expressed in muscle tissues of patients with autoimmune necrotizing myopathy, and suggests that this protein may be involved in the origin and progression of the disease.
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Affiliation(s)
- Q Wang
- EmergencyDepartment, General Hospital of Chinese People's Armed Police Forces, Beijing, China
| | - F Duan
- Department of Neurology, Navy General Hospital, Beijing, China
| | - P Liu
- Department of VIP Neurology, Navy General Hospital, Beijing, China
| | - P F Wang
- Department of Neurology, Aerospace Center Hospital, Peking University Aerospace Clinical College, Beijing, China
| | - M X Wang
- Orthopaedics Department, General Hospital of Chinese People's Armed Police Forces, Beijing, China
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Zhao J, Shu P, Duan F, Wang X, Min L, Shen Z, Ruan Y, Qin J, Sun Y, Qin X. Loss of OLFM4 promotes tumor migration through inducing interleukin-8 expression and predicts lymph node metastasis in early gastric cancer. Oncogenesis 2016; 5:e234. [PMID: 27294866 PMCID: PMC4945743 DOI: 10.1038/oncsis.2016.42] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2016] [Revised: 01/15/2016] [Accepted: 05/11/2016] [Indexed: 12/26/2022] Open
Abstract
Endoscopic surgery is increasingly used for early gastric cancer (EGC) treatment worldwide, and lymph node metastasis remains the most important risk factor for endoscopic surgery in EGC patients. Olfactomedin 4 (OLFM4) is mainly expressed in the digestive system and upregulated in several types of tumors. However, the role of OLFM4 in EGC has not been explored. We evaluated OLFM4 expression by immunohistochemical staining in 105 patients with EGC who underwent gastrectomy. The clinicopathological factors and OLFM4 expression were co-analyzed to predict lymph node metastasis in EGC. The metastatic mechanism of OLFM4 in gastric cancer was also investigated. We found that OLFM4 was upregulated in EGC tumor sections, and relatively low expression of OLFM4 was observed in patients with lymph node metastasis. OLFM4 expression as well as tumor size and differentiation were identified as independent factors, which could be co-analyzed to generate a better model for predicting lymph node metastasis in EGC patients. In vitro studies revealed that knockdown of OLFM4 promoted the migration of gastric cancer cells through activating the NF-κB/interleukin-8 axis. Negative correlation between OLFM4 and interleukin-8 expression was also observed in EGC tumor samples. Our study implies that OLFM4 expression is a potential predictor of lymph node metastasis in EGC, and combing OLFM4 with tumor size and differentiation could better stratify EGC patients with different risks of lymph node metastasis.
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Affiliation(s)
- J Zhao
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - P Shu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - F Duan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.,Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - X Wang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - L Min
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Z Shen
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Y Ruan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - J Qin
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Y Sun
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - X Qin
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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46
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Zheng G, Duan F, Ma Y, Zhang Q, Huang T, Kimoto T, Cheng Y, Su H, He K. Episode-Based Evolution Pattern Analysis of Haze Pollution: Method Development and Results from Beijing, China. Environ Sci Technol 2016; 50:4632-4641. [PMID: 27050081 DOI: 10.1021/acs.est.5b05593] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Haze episodes occurred in Beijing repeatedly in 2013, resulting in 189 polluted days. These episodes differed in terms of sources, formation processes, and chemical composition and thus required different control policies. Therefore, an overview of the similarities and differences among these episodes is needed. For this purpose, we conducted one-year online observations and developed a program that can simultaneously divide haze episodes and identify their shapes. A total of 73 episodes were identified, and their shapes were linked with synoptic conditions. Pure-haze events dominated in wintertime, whereas mixed haze-dust (PM2.5/PM10 < 60%) and mixed haze-fog (Aerosol Water/PM2.5 ∼ 0.3) events dominated in spring and summer-autumn, respectively. For all types, increase of ratio of PM2.5 in PM10 was typically achieved before PM2.5 reached ∼150 μg/m(3). In all PM2.5 species observed, organic matter (OM) was always the most abundant component (18-60%), but it was rarely the driving factor: its relative contribution usually decreased as the pollution level increased. The only OM-driven episode observed was associated with intensive biomass-burning activities. In comparison, haze evolution generally coincided with increasing sulfur and nitrogen oxidation ratios (SOR and NOR), indicating the enhanced production of secondary inorganic species. Applicability of these conclusions required further tests with simultaneously multisite observations.
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Affiliation(s)
| | | | | | - Qiang Zhang
- Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China
| | - Tao Huang
- Kimoto Electric Co., Ltd., 3-1 Funahashi-cho Tennoji-ku, Osaka 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co., Ltd., 3-1 Funahashi-cho Tennoji-ku, Osaka 543-0024, Japan
| | - Yafang Cheng
- Multiphase Chemistry Department, Max Planck Institute for Chemistry , D-55128 Mainz, Germany
| | - Hang Su
- Multiphase Chemistry Department, Max Planck Institute for Chemistry , D-55128 Mainz, Germany
| | - Kebin He
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
- Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China
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Hu H, Wu J, Li Q, Asweto C, Feng L, Yang X, Duan F, Duan J, Sun Z. Fine particulate matter induces vascular endothelial activation via IL-6 dependent JAK1/STAT3 signaling pathway. Toxicol Res (Camb) 2016; 5:946-953. [PMID: 30090403 PMCID: PMC6062355 DOI: 10.1039/c5tx00351b] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 04/01/2016] [Indexed: 12/20/2022] Open
Abstract
Exposure to PM2.5 has been strongly linked to endothelial dysfunction. However, the underlying mechanism of PM2.5 on the vascular endothelial function is poorly understood. This study examined the toxic effect and underlying mechanism of PM2.5 on human umbilical vein endothelial cells (HUVECs). Decreased cell viability and increased LDH activity were observed in the PM2.5-treated HUVECs in a dose-dependent manner. The production of ROS, MDA, and the inhibition of SOD activity were also triggered by PM2.5 in HUVECs. In addition, PM2.5 increased the intracellular levels of proinflammatory cytokines (IL-6, TNF-a, IL-1β, IL-8 and CRP), cell adhesion molecules (ICAM-1, VCAM-1) and tissue factor (TF), resulted in endothelial activation. For an in-depth study, the protein levels of IL-6, JAK1 and STAT3 were up-regulated significantly, while the expression of JAK2 and SOCS1 were down-regulated gradually in PM2.5-treated HUVECs in a dose-dependent manner. These results show that PM2.5 triggered endothelial activation via upregulation of the IL-6 dependent JAK1/STAT3 signaling pathway. This will provide new insights into the toxic effects and mechanisms of cardiovascular diseases triggered by ambient air pollution.
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Affiliation(s)
- Hejing Hu
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Jing Wu
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Qiuling Li
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Collins Asweto
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Lin Feng
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Xiaozhe Yang
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Fengkui Duan
- School of Environment , Tsinghua University , Beijing 100084 , P.R. China
| | - Junchao Duan
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
| | - Zhiwei Sun
- Department of Toxicology and Sanitary Chemistry , School of Public Health , Capital Medical University , Beijing 100069 , P.R. China . ; ; ; Tel: +86 010 83911868, +86 010 83911507
- Beijing Key Laboratory of Environmental Toxicology , Capital Medical University , Beijing 100069 , P.R. China
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48
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Liang L, Engling G, Du Z, Cheng Y, Duan F, Liu X, He K. Seasonal variations and source estimation of saccharides in atmospheric particulate matter in Beijing, China. Chemosphere 2016; 150:365-377. [PMID: 26921589 DOI: 10.1016/j.chemosphere.2016.02.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 02/01/2016] [Accepted: 02/01/2016] [Indexed: 06/05/2023]
Abstract
Saccharides are important constituents of atmospheric particulate matter (PM). In order to better understand the sources and seasonal variations of saccharides in aerosols in Beijing, China, saccharide composition was measured in ambient PM samples collected at an urban site in Beijing. The highest concentrations of total saccharides in Beijing were observed in autumn, while an episode with abnormal high total saccharide levels was observed from 15 to 23 June, 2011, due to extensive agricultural residue burning in northern China during the wheat harvest season. Compared to the other two categories of saccharides, sugars and sugar alcohols, anhydrosugars were the predominant saccharide group, indicating that biomass burning contributions to Beijing urban aerosol were significant. Ambient sugar and sugar alcohol levels in summer and autumn were higher than those in spring and winter, while they were more abundant in PM2.5 during winter time. Levoglucosan was the most abundant saccharide compound in both PM2.5 and PM10, the annual contributions of which to total measured saccharides in PM2.5 and PM10 were 61.5% and 54.1%, respectively. To further investigate the sources of the saccharides in ambient aerosols in Beijing, the PM10 datasets were subjected to positive matrix factorization (PMF) analysis. Based on the objective function to be minimized and the interpretable factors identified by PMF, six factors appeared to be optimal as to the probable origin of saccharides in the atmosphere in Beijing, including biomass burning, soil or dust, isoprene SOA and the direct release of airborne fungal spores and pollen.
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Affiliation(s)
- Linlin Liang
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
| | - Guenter Engling
- Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan; Division of Atmospheric Sciences, Desert Research Institute, Reno, NV, USA
| | - Zhenyu Du
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; National Research Center for Environmental Analyses and Measurements, Beijing, China
| | - Yuan Cheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Xuyan Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; National Satellite Meteorological Center, China Meteorological Administration, Beijing, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
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Abstract
Maternally imprinted genes of makorin ring finger protein 3 (MKRN3) and nucleosome assembly protein 1-like 5 (NAP1L5) have been identified in many species but have not yet been investigated in rabbits. In this study, a polymorphism-based approach and bisulfite-sequencing PCR (BSP) were used to determine the imprinting status of MKRN3 and NAP1L5 in rabbits. The single nucleotide polymorphism (SNP)-based sequencing results demonstrated that MKRN3 and NAP1L5 were expressed preferentially from the paternal allele. Furthermore, the BSP results showed the gamete-specific methylation patterns and hemimethylation in brain and full methylation in liver were observed in MKRN3 and NAP1L5 respectively. Thus, we provide the first evidence that MKRN3 and NAP1L5 are paternally expressed genes and that the CpG islands located in the promoter region may be the putative differentially methylated region of these two genes in rabbits.
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Affiliation(s)
- L Yuan
- Jilin Provincial Key Laboratory of Animal Embryo Engineering, Jilin University, Changchun, 130062, China
| | - L Lai
- Jilin Provincial Key Laboratory of Animal Embryo Engineering, Jilin University, Changchun, 130062, China
| | - F Duan
- Jilin Provincial Key Laboratory of Animal Embryo Engineering, Jilin University, Changchun, 130062, China
| | - M Chen
- Jilin Provincial Key Laboratory of Animal Embryo Engineering, Jilin University, Changchun, 130062, China
| | - J Deng
- Jilin Provincial Key Laboratory of Animal Embryo Engineering, Jilin University, Changchun, 130062, China
| | - Z Li
- Jilin Provincial Key Laboratory of Animal Embryo Engineering, Jilin University, Changchun, 130062, China
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50
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Affiliation(s)
- D. Shi
- The Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, Jiangsu 214122, People's Republic of China
| | - T. Mei
- The Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, Jiangsu 214122, People's Republic of China
| | - Q. Chen
- The Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, Jiangsu 214122, People's Republic of China
| | - F. Duan
- The Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, Jiangsu 214122, People's Republic of China
| | - M. Chen
- The Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, Jiangsu 214122, People's Republic of China
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