1
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Yang W, Li J, Yao Z, Li M. A review on the alternatives to antibiotics and the treatment of antibiotic pollution: Current development and future prospects. Sci Total Environ 2024; 926:171757. [PMID: 38513856 DOI: 10.1016/j.scitotenv.2024.171757] [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: 12/11/2023] [Revised: 02/08/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024]
Abstract
Antibiotics, widely used in the fields of medicine, animal husbandry, aquaculture, and agriculture, pose a serious threat to the ecological environment and human health. To prevent antibiotic pollution, efforts have been made in recent years to explore alternative options for antibiotics in animal feed, but the effectiveness of these alternatives in replacing antibiotics is not thoroughly understood due to the variation from case to case. Furthermore, a systematic summary of the specific applications and limitations of antibiotic removal techniques in the environment is crucial for developing effective strategies to address antibiotic contamination. This comprehensive review summarized the current development and potential issues on different types of antibiotic substitutes, such as enzyme preparations, probiotics, and plant extracts. Meanwhile, the existing technologies for antibiotic residue removal were discussed under the scope of application and limitation. The present work aims to highlight the strategy of controlling antibiotics from the source and provide valuable insights for green and efficient antibiotic treatment.
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Affiliation(s)
- Weiqing Yang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Jing Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Mi Li
- Center for Renewable Carbon, School of Natural Resources, The University of Tennessee, Knoxville, TN 37996, USA
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2
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He L, Xu Y, Yang Z, Lu X, Yao X, Li C, Xu D, Wu C, Yao Z. Copper-decorated strategy based on defect-rich NH 2-MIL-125(Ti) boosts efficient photocatalytic degradation of methyl mercaptan under sunlight. Environ Pollut 2024; 344:123341. [PMID: 38211878 DOI: 10.1016/j.envpol.2024.123341] [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: 10/23/2023] [Revised: 01/08/2024] [Accepted: 01/09/2024] [Indexed: 01/13/2024]
Abstract
Photocatalysis has received significant attention as a technology that can solve environmental problems. Metal-organic frameworks are currently being used as novel photocatalysts but are still limited by the rapid recombination of photogenerated carriers, low photogenerated electron migration efficiency and poor solar light utilization rate. In this work, a novel photocatalyst was successfully constructed by introducing Cu species into thermal activated mixed-ligand NH2-MIL-125 (Ti) via defect engineering strategy. The constructed defect structure not only provided 3D-interconnected gas transfer channels, but also offered suitable space to accommodate introduced Cu species. For the most effective photocatalyst 0.2Cu/80%NH2-MIL-125 (300 °C) with optimized Cu content, the photocatalytic degradation rate of CH3SH achieved 4.65 times higher than that of pristine NH2-MIL-125 under visible light (λ > 420 nm). At the same time, it showed great degradation efficiency under natural sunlight, 100 ppm CH3SH was completely removed within 25 min in full solar light illumination. The improved catalytic efficiency is mainly due to the synergistic effect of the integrated Schottky junction and rich-defective NH2-MIL-125, which improved the bandgap and band position, and thus facilitated the separation and transfer of the photo-generated carriers. This work provided a facile way to integrate Schottky junctions and rich-defective MOFs with high stability. Due to its excellent degradation performance under sunlight, it also offered a prospective strategy for rational design of high-efficiency catalysts applied in environmental technologies.
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Affiliation(s)
- Li He
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Yuyao Xu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zichang Yang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xingkai Lu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xiaolong Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Changming Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Dong Xu
- CHN Energy New Energy Technology Research Institute Co., Ltd., Beijing 102209, China
| | - Chao Wu
- UKCRIC Advanced Infrastructure Materials Laboratory, Department of Civil and Environmental Engineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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3
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Yu W, Shen X, Yao Z, Cao X, Hao X, Li X, Wu B, Zhang H, Wang S, Zhou Q. Database of emission factors of volatile organic compound (VOC) species in motor vehicle exhaust in China. Sci Total Environ 2024; 914:169844. [PMID: 38190915 DOI: 10.1016/j.scitotenv.2023.169844] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/28/2023] [Accepted: 12/30/2023] [Indexed: 01/10/2024]
Abstract
The synergistic strategy for fine particulate matter (PM2.5) and O3 pollution prevention and control has emerged as a pivotal approach in combating air pollution. Volatile organic compounds (VOCs) serve as crucial precursors to both O3 and secondary organic aerosols (SOAs), with motor vehicles representing one of their significant sources. In this study, a standard for establishing a database of VOC species emission factors for motor vehicles was developed, and a database containing 134 VOC species was constructed through field tests and literature surveys. The VOC emissions of light-duty gasoline passenger vehicles (LDGPVs) comprised primarily alkanes and aromatics. The VOC emissions of light-duty diesel trucks (LDDTs) comprised mostly alkanes. Regarding low-speed trucks, 3-wheel vehicles, medium-duty diesel trucks (MDDTs) and heavy-duty diesel trucks (HDDTs), their VOC emissions comprised mainly oxygenated volatile organic compounds (OVOCs). The update of emission standards resulted in a reduction in VOC species emission factors while altering the composition of VOCs. Attention should be directed toward isopentane, benzene and dichloromethane emitted by LDGPVs, dodecane, undecane, ethene and propene emitted by LDDTs, and acetaldehyde emitted by HDDTs. VOC species originating from LDGPVs were more dispersed than those originating from LDDTs and HDDTs. In addition, variations in VOC species were observed among motor vehicles with different fuel types. Toluene, ethene, benzene, m,p-xylene, isopentane, hexanal, ethyne and 1,2,4-trimethylbenzene were the predominant VOC species emitted by gasoline vehicles. Diesel vehicles emitted mainly dodecane, formaldehyde, propene, undecane, acetaldehyde, ethene, decane and benzene. The results could enhance our comprehension of the emission characteristics of VOC species originating from motor vehicles and provide data support and a scientific foundation for achieving synergistic PM2.5 and O3 pollution prevention and control.
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Affiliation(s)
- Wenhan Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China.
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Siwen Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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4
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Nygård K, McDonald SA, González JB, Haghighat V, Appel C, Larsson E, Ghanbari R, Viljanen M, Silva J, Malki S, Li Y, Silva V, Weninger C, Engelmann F, Jeppsson T, Felcsuti G, Rosén T, Gordeyeva K, Söderberg L, Dierks H, Zhang Y, Yao Z, Yang R, Asimakopoulou EM, Rogalinski J, Wallentin J, Villanueva-Perez P, Krüger R, Dreier T, Bech M, Liebi M, Bek M, Kádár R, Terry AE, Tarawneh H, Ilinski P, Malmqvist J, Cerenius Y. ForMAX - a beamline for multiscale and multimodal structural characterization of hierarchical materials. J Synchrotron Radiat 2024; 31:363-377. [PMID: 38386565 PMCID: PMC10914163 DOI: 10.1107/s1600577524001048] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/30/2024] [Indexed: 02/24/2024]
Abstract
The ForMAX beamline at the MAX IV Laboratory provides multiscale and multimodal structural characterization of hierarchical materials in the nanometre to millimetre range by combining small- and wide-angle X-ray scattering with full-field microtomography. The modular design of the beamline is optimized for easy switching between different experimental modalities. The beamline has a special focus on the development of novel fibrous materials from forest resources, but it is also well suited for studies within, for example, food science and biomedical research.
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Affiliation(s)
- K. Nygård
- MAX IV Laboratory, Lund University, Lund, Sweden
| | | | | | - V. Haghighat
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - C. Appel
- MAX IV Laboratory, Lund University, Lund, Sweden
- Paul Scherrer Institut, Villigen PSI, Switzerland
| | - E. Larsson
- MAX IV Laboratory, Lund University, Lund, Sweden
- Division of Solid Mechanics, Lund University, Lund, Sweden
| | - R. Ghanbari
- MAX IV Laboratory, Lund University, Lund, Sweden
- Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden
| | - M. Viljanen
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - J. Silva
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - S. Malki
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - Y. Li
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - V. Silva
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - C. Weninger
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - F. Engelmann
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - T. Jeppsson
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - G. Felcsuti
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - T. Rosén
- Department of Fibre and Polymer Technology, Royal Institute of Technology, Stockholm, Sweden
- Wallenberg Wood Science Center (WWSC), Royal Institute of Technology, Stockholm, Sweden
| | - K. Gordeyeva
- Department of Fibre and Polymer Technology, Royal Institute of Technology, Stockholm, Sweden
| | - L. D. Söderberg
- Department of Fibre and Polymer Technology, Royal Institute of Technology, Stockholm, Sweden
- Wallenberg Wood Science Center (WWSC), Royal Institute of Technology, Stockholm, Sweden
| | - H. Dierks
- Synchrotron Radiation Research, Lund University, Lund, Sweden
| | - Y. Zhang
- Synchrotron Radiation Research, Lund University, Lund, Sweden
| | - Z. Yao
- Synchrotron Radiation Research, Lund University, Lund, Sweden
| | - R. Yang
- Synchrotron Radiation Research, Lund University, Lund, Sweden
| | | | | | - J. Wallentin
- Synchrotron Radiation Research, Lund University, Lund, Sweden
| | | | - R. Krüger
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - T. Dreier
- Medical Radiation Physics, Lund University, Lund, Sweden
- Excillum AB, Kista, Sweden
| | - M. Bech
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - M. Liebi
- Paul Scherrer Institut, Villigen PSI, Switzerland
- Institute of Materials, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Physics, Chalmers University of Technology, Gothenburg, Sweden
| | - M. Bek
- Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden
- FibRe-Centre for Lignocellulose-based Thermoplastics, Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - R. Kádár
- MAX IV Laboratory, Lund University, Lund, Sweden
- Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden
- FibRe-Centre for Lignocellulose-based Thermoplastics, Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Wallenberg Wood Science Center (WWSC), Chalmers University of Technology, Gothenburg, Sweden
| | - A. E. Terry
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - H. Tarawneh
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - P. Ilinski
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - J. Malmqvist
- MAX IV Laboratory, Lund University, Lund, Sweden
| | - Y. Cerenius
- MAX IV Laboratory, Lund University, Lund, Sweden
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5
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Li S, Jiang S, Jia W, Guo T, Wang F, Li J, Yao Z. Natural antimicrobials from plants: Recent advances and future prospects. Food Chem 2024; 432:137231. [PMID: 37639892 DOI: 10.1016/j.foodchem.2023.137231] [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: 05/04/2023] [Revised: 08/09/2023] [Accepted: 08/19/2023] [Indexed: 08/31/2023]
Abstract
Plant-based antimicrobial substances have emerged as promising alternatives to conventional antibiotics and preservatives. Although many review studies have been done in this field, many of these reviews solely focus on specific compounds from particular perspectives. This paper aims to provide a comprehensive review on the various types of plant-based antimicrobial substances, the extraction and purification processes, as well as the application and safety issues. Combining different natural plant-derived substances shows promise in enhancing antimicrobial activities. Moreover, despite the existence of various methods (e.g., microwave-assisted extraction, supercritical fluid extraction) to extract and purify antimicrobial substances, isolating pure compounds remains a laborious process. Sustainability issues should also be considered when developing extraction methods. Additionally, the extraction process generates a significant amount of plant waste, necessitating proper utilization to ensure economic viability. Lastly, not all plant-derived substances are safe, and further research is needed to investigate their toxicity before widespread application.
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Affiliation(s)
- Shuo Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China.
| | - Wenting Jia
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Tongming Guo
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Jing Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China.
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6
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Wu B, Wu Z, Yao Z, Shen X, Cao X. Refined mass absorption cross-section of black carbon from typical non-road mobile machinery in China based on real-world measurements. Sci Total Environ 2024; 908:168579. [PMID: 37967631 DOI: 10.1016/j.scitotenv.2023.168579] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/10/2023] [Accepted: 11/12/2023] [Indexed: 11/17/2023]
Abstract
Non-road mobile machinery (NRMM) is becoming a more prominent contribution of black carbon (BC), and mass absorption cross-section (MAC) as an essential parameter to characterize the BC optical property is still not clear. In this study, we explored the impacts of key factors on the MAC of BC based on real-world measurements from 41 typical NRMM. We characterized the organic carbon (OC) and elemental carbon (EC), and found MAC values of BC from NRMM increase as the OC/EC mass ratios increase, since the OC coating can enhance BC light absorption. With more stringent emission standards, the MAC values of all tested NRMM show a significant decreasing trend. Meanwhile, we found the absorption coefficients obtained by filter-based (bfilter) and in-situ-based (bin-situ) methods present good correlation for NRMM in this study, but bfilter are significantly higher than bin-situ when bfilter are above 40,000 Mm-1. Furthermore, we have refined the MAC values under different emission standards, and recommended a more appropriate MAC value (11.5 ± 3.4 m2/g) of NRMM at 550 nm wavelength, which is 1.5 times of the MAC value (7.5 m2/g) commonly used in previous studies. Our results will be indispensable for accurate BC quantification from NRMM and climate radiative effects prediction.
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Affiliation(s)
- Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zichun Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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7
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Jia W, Jiang S, Wang F, Li J, Wang Z, Yao Z. Natural antibacterial membranes prepared using Schisandra chinensis extracts and polyvinyl alcohol in an environment-friendly manner. Chemosphere 2024; 346:140524. [PMID: 37923017 DOI: 10.1016/j.chemosphere.2023.140524] [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: 02/20/2023] [Revised: 10/03/2023] [Accepted: 10/21/2023] [Indexed: 11/07/2023]
Abstract
Foodborne pathogens can cause food spoilage and lead to food safety issues. In recent years, food packaging has received a lot of attention. Traditional packaging membranes are non-biodegradable and remain in the environment for a long time. In this study, natural antimicrobial substances were extracted from Schisandra chinensis by a green extraction process using distilled water as the solvent, and the effects of different treatment on the antimicrobial activity of the extract were compared. At the same time, four types of Schisandra chinensis antimicrobial membranes were prepared using polyvinyl alcohol (PVA) as the substrate. The whole extraction and membrane preparation process did not involve organic solvents, making the process green and environment friendly. Material characterization included inverted biological microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), tensile strength test, pore size measurement, water uptake test, etc. Among them, no extract particles were observed with the naked eye on the surfaces of MⅡ and MⅣ. MⅡ has a uniformly transparent, nearly colorless morphology and is the most tensile. MⅣ surface is flat and smooth, the microstructure is dense and uniform. At the same time, the four types of membranes were tested against common pathogenic bacteria for 12 h, and the OD600 trend revealed the excellent antimicrobial activity of the membranes against S. aureus, MRSA, E. coli, and L. monocytogenes. The membranes could also be reused at least once. This study provides a new idea for preparing natural plant-based antimicrobial membranes.
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Affiliation(s)
- Wenting Jia
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Jing Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zeru Wang
- School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen 518055, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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8
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Wu B, Li J, Yao Z, Li X, Wang W, Wu Z, Zhou Q. Characteristics and reduction assessment of GHG emissions from crop residue open burning in China under the targets of carbon peak and carbon neutrality. Sci Total Environ 2023; 905:167235. [PMID: 37751839 DOI: 10.1016/j.scitotenv.2023.167235] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 09/28/2023]
Abstract
Driven by the goal of carbon peak and carbon neutrality, greenhouse gas (GHG) emissions from the crop residue open burning (CROB) in China cannot be ignored. In this study, we have established a high-resolution (0.05° × 0.05°) GHG emissions inventory (including CO2, CH4, and N2O) of CROB from 2012 to 2021 in China based on the VIIRS data and official statistics. To improve the results accuracy, we compared the two commonly used bases for grid allocation, fire counts (FC) and fire radiative power (FRP), in the construction of high-resolution inventory. In 2012, GHG emissions are overestimated by 599 t CO2e per grid on average in 24,577 grids, and underestimated by 1096 t CO2e per grid on average in 13,546 grids based on FC compared to FRP. Then, we characterized the spatial and temporal distribution of GHG emissions from CROB by using the FRP-based method. From 2012 to 2021, total GHG emissions from CROB in China have decreased by 31.2 %, of which the East and South-Central China contributed 22.51 and 9.12 Tg CO2e of GHG reductions, while the Northeast China contributed 10.73 Tg CO2e of GHG growth, respectively. In addition, GHG emissions from CROB on the time scale are mainly concentrated in April, June, and October, with variations between years and regions influenced by the policy, climate, and farmers' perceptions. Finally, we assessed the GHG emission reductions from CROB under different scenarios in the future. By 2060, GHG emissions would be significantly reduced by 57.3 %-77.9 % compared to 2021 under effective control measures. We believe the results will be of great significance for GHG policy formulation and emission reduction potential assessment.
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Affiliation(s)
- Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Jiahan Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Weijun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zichun Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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9
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Zhang H, Wang X, Lv L, Li G, Liu X, Li X, Yao Z. Insights into quantitative evaluation technology of PM 2.5 transport at multi-perspective and multi-spatial and temporal scales in the north China plain. Environ Pollut 2023; 338:122693. [PMID: 37802287 DOI: 10.1016/j.envpol.2023.122693] [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: 08/08/2023] [Revised: 09/14/2023] [Accepted: 10/03/2023] [Indexed: 10/08/2023]
Abstract
Cross-border transport is a crucial factor affecting air quality, while how to quantify the transport contribution through different technologies at multi-perspective and multi-scale have not been fully understood. This study established three quantification techniques, and conducted a systematic assessment of PM2.5 transport over the North China Plain (NCP) based on numerical simulations and vertical observations. Results suggested that the annual local emissions, inter-urban and outer-regional transport contributed 44.5%-64.6%, 15.2%-27.9% and 18.0%-28.2% of total surface PM2.5 concentrations, respectively, with transport intensity stronger in July and April, yet weaker in January and October. The southwest-northeast, northeast-southwest, and southeast-northwest were three prevailing transport directions near the surface. By comparison, the annual PM2.5 transport contribution below the atmospheric boundary layer height increased by 16.8%-24.5% in Beijing, Tianjin and Shijiazhuang, with inter-urban and outer-regional contribution of 29.8%-32.1% and 18.5%-23.1%. Furthermore, observed fluxes from fixed-point and vehicle-based mobile lidar were in good agreement with the simulated flux. PM2.5 net flux intensity varied with height, with generally larger at the middle- and high-altitude layer than that of low-altitude layer. In the early, during and late period of haze peak formation (Stage Ⅰ, Ⅱ, Ⅲ, respectively), the largest absolute flux intensity on average was Stage Ⅱ (566.7 t/d), followed by Stage Ⅲ (307.0 t/d) and Ⅰ (191.4 t/d). Besides, external transport may dominate the second concentration peak, while local emissions may play a more vital role in the first and third peaks. It has been noted that joint prevention and control measures should be proposed 1-2 days before reaching PM2.5 extremes. These findings could improve our understanding of transport influence mechanism of PM2.5 and propose effective emission reduction measures in the NCP region.
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Affiliation(s)
- Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xuejun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Longyue Lv
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Guohao Li
- Beijing Municipal Research Institute of Environmental Protection, Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, National Urban Environmental Pollution Control Engineering Research Center, Beijing, 100037, China
| | - Xiaoyu Liu
- Beijing Municipal Research Institute of Environmental Protection, Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, National Urban Environmental Pollution Control Engineering Research Center, Beijing, 100037, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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10
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Niu C, Yan M, Yao Z, Dou J. Antibiotic residues in milk and dairy products in China: occurrence and human health concerns. Environ Sci Pollut Res Int 2023; 30:113138-113150. [PMID: 37851252 DOI: 10.1007/s11356-023-30312-2] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/03/2023] [Indexed: 10/19/2023]
Abstract
Although veterinary antibiotics are essential in preventing and treating clinical diseases in cattle, the frequent use of antibiotics leads to antibiotic residues in milk and dairy products, consequently threatening human health. The massive milk consumption makes it necessary to assess antibiotic pollution and health impact comprehensively. Hence, we conducted a systematic review to evaluate antibiotics in milk and dairy products and their potential health risk. We searched four databases using multiple keyword combinations to retrieve 1582 pieces of literature and finally included eighteen articles to analyze antibiotic residues in milk and dairy products. These studies detected seven antibiotics in different regions of China. Quinolones and β-lactam antibiotics exceeded the MRL for raw and commercial milk. The maximum levels of sulfonamides and tetracyclines were detected in the same raw milk sample, exceeding the MRL. The estimated THQ and HI values in milk and dairy products are less than 1 for adults, indicating negligible noncarcinogenic health risk of antibiotics through consuming milk and dairy products. Children face higher health risks than adults, with the HI and THQ of quinolones exceeding 1. It is worth noting that quinolones accounted for nearly 89% of health risks associated with all antibiotics. Finally, we put forward possible research directions in the future, such as specific health effects of total dietary exposure to low levels of antibiotics. In addition, policymakers should effectively improve this problem from the perspectives of antibiotic use supervision, antibiotic residue analysis in food, and continuous environmental monitoring and control.
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Affiliation(s)
- Chenyue Niu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Meilin Yan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
- Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing, 100048, China.
| | - Jiahang Dou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
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11
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Yao Z, Yang X, Wang B, Shao X, Wen H, Deng Y, Zhang Z, Cao M, Lin L. Multidimensional beta-diversity across local and regional scales in a Chinese subtropical forest: The role of forest structure. Ecol Evol 2023; 13:e10607. [PMID: 37881223 PMCID: PMC10597745 DOI: 10.1002/ece3.10607] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 09/06/2023] [Accepted: 09/25/2023] [Indexed: 10/27/2023] Open
Abstract
Beta-diversity, or the spatio-temporal variation in community composition, can be partitioned into turnover and nestedness components in a multidimensional framework. Forest structure, including comprehensive characteristics of vertical and horizontal complexity, strongly affects species composition and its spatial variation. However, the effects of forest structure on beta-diversity patterns in multidimensional and multiple-scale contexts are poorly understood. Here, we assessed beta-diversity at local (a 20-ha forest dynamics plot) and regional (a plot network composed of 19 1-ha plots) scales in a Chinese subtropical evergreen broad-leaved forest. We then evaluated the relative importance of forest structure, topography, and spatial structure on beta-diversity and its turnover and nestedness components in taxonomic, functional, and phylogenetic dimensions at local and regional scales. We derived forest structural parameters from both unmanned aerial vehicle light detection and ranging (UAV LiDAR) data and plot inventory data. Turnover component dominated total beta-diversity for all dimensions at the two scales. With the exception of some components (taxonomic and functional turnover at the local scale; functional nestedness at the regional scale), environmental factors (i.e., topography and forest structure) contributed more than pure spatial variation. Explanations of forest structure for beta-diversity and its component patterns at the local scale were higher than those at the regional scale. The joint effects of spatial structure and forest structure influenced component patterns in all dimensions (except for functional turnover) to some extent at the local scale, while pure forest structure influenced taxonomic and phylogenetic nestedness patterns to some extent at the regional scale. Our results highlight the importance and scale dependence of forest structure in shaping multidimensional beta-diversity and its component patterns. Clearly, further studies need to link forest structure directly to ecological processes (e.g., asymmetric light competition and disturbance dynamics) and explore its roles in biodiversity maintenance.
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Affiliation(s)
- Zhiliang Yao
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Xin Yang
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
- School of Ecology and EnvironmentHainan UniversityHaikouChina
| | - Bin Wang
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
- School of Ecology and Environmental Sciences & Yunnan Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded EnvironmentsYunnan UniversityKunmingChina
- School of the EnvironmentUniversity of WindsorWindsorCanada
| | - Xiaona Shao
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
| | - Handong Wen
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
- National Forest Ecosystem Research Station at AilaoshanJingdongYunnanChina
| | - Yun Deng
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
- National Forest Ecosystem Research Station at XishuangbannaMenglaYunnanChina
| | - Zhiming Zhang
- School of Ecology and Environmental Sciences & Yunnan Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded EnvironmentsYunnan UniversityKunmingChina
| | - Min Cao
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
| | - Luxiang Lin
- CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical Garden, Chinese Academy of SciencesKunmingChina
- National Forest Ecosystem Research Station at XishuangbannaMenglaYunnanChina
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12
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Luo R, Su Z, Kang K, Yu M, Zhou X, Wu Y, Yao Z, Xiu W, Zhang X, Yu Y, Zhou L, Na F, Li Y, Xu Y, Liu Y, Zou B, Peng F, Wang J, Zhong R, Gong Y, Huang M, Bai S, Xue J, Yan D, Lu Y. Hybrid Immuno-RT for Bulky Tumors: Standard Fractionation with Partial Tumor SBRT. Int J Radiat Oncol Biol Phys 2023; 117:S166. [PMID: 37784416 DOI: 10.1016/j.ijrobp.2023.06.264] [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] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Bulky tumors remain challenging to be treated. Stereotactic body radiation therapy (SBRT) is effective against radioresistant tumor cells and can induce immunogenic cell death (ICD) that leads to T-cell-mediated antitumor effects. Low-dose radiation (LDRT) can inflame the tumor microenvironment (TME) by recruiting T cells. We designed a novel radiotherapy technique (RT, ERT) whose dose distribution map resembles the "eclipse" by concurrently delivering LDRT to the whole tumor, meanwhile SBRT to only a part of the same tumor. This study examined the safety and efficacy of ERT to bulky lesions with PD-1 inhibitors in mice and patients. MATERIALS/METHODS In mice with CT26 colon or LLC1 lung bulky tumors (400 - 500 cm3), the whole tumor was irradiated by LDRT (2 Gy x 3), meanwhile the tumor center was irradiated by SBRT (10 Gy x 3); αPD-1 was given weekly. The dependence of therapeutic effects on CD8+ T cells was determined using depleting antibodies. Frequencies of CD8+ T cells and M1 macrophages (Mφ) were determined by flow cytometry. Multiplex Immunohistochemistry (mIHC) was applied to analyze the number and the location of CD8+ T cells and their subpopulations, as well as the phospho-eIF2α level (the ICD marker) of tumor cells in TME. Patients with advanced lung or liver bulky tumors who failed standard treatment or with oncologic emergencies were treated. Kaplan-Meier method was applied to estimate patients' progression-free survival (PFS) and overall survival (OS). RESULTS ERT/αPD-1 is superior to SBRT/αPD-1 or LDRT/αPD-1 in controlling bulky tumors in both mouse models in a CD8+ T-cell dependent manner. In the CT26 model, ERT/αPD-1 resulted in complete tumor regression in 3/11 mice and induced more CD8+ T cells and M1 Mφ in TME compared to other groups. mIHC analysis showed that ERT/αPD-1 induced higher bulk, stem-like (TCF1+ TIM3- PD-1+), and more differentiated (TCF1- TIM3+ PD-1+) CD8+ T cells infiltration into the tumor center and periphery compared to other groups. Compared to untreated or LDRT-treated tumor centers, tumor centers irradiated with ERT or SBRT showed elevated phospho-eIF2α accompanied by higher dendritic cell infiltration. In total, 39 advanced cancer patients were treated with ERT/αPD-1 or plus chemotherapy. Radiation-induced pneumonitis occurred in 1 of 26 patients receiving thoracic ERT. There were two cases of grade III toxicity associated with PD-1 inhibitors. No toxicity above grade III was observed. The objective response rate was 38.5%. The median PFS was 5.6 months and median OS was not reached at a median follow-up of 11.7 months. CONCLUSION ERT/αPD-1 showed superior efficacy in controlling bulky tumor in two mouse models. The hybrid immuno-RT (ERT) combing PD-1 inhibitors was safe and effective in patients with bulky tumors. Further clinical trials in combination with bioimaging to identify the optimal SBRT target region for the bulky tumor are warranted.
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Affiliation(s)
- R Luo
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Z Su
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - K Kang
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - M Yu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - X Zhou
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Wu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Z Yao
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - W Xiu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - X Zhang
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Yu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - L Zhou
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - F Na
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Li
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Xu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Liu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - B Zou
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - F Peng
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - J Wang
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - R Zhong
- Division of Radiation Physics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Gong
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - M Huang
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - S Bai
- Division of Radiation Physics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - J Xue
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - D Yan
- Division of Radiation Physics, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Lu
- Thoracic Oncology Ward, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Huang Z, Liu S, Wang Y, Yao Z, Feng L, Lin Y, Ye J, Zhou T, Wang Z. Comparison of prevalence, resistance, biofilm-forming ability and virulence between carbapenem-non-susceptible and carbepenem-susceptible Enterobacter cloacae complex in clusters. J Hosp Infect 2023; 139:168-174. [PMID: 37348563 DOI: 10.1016/j.jhin.2023.06.017] [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: 03/01/2023] [Revised: 05/30/2023] [Accepted: 06/07/2023] [Indexed: 06/24/2023]
Abstract
OBJECTIVES This study aimed to explore differences in prevalence, resistance, biofilm-forming ability and virulence between carbapenem-non-susceptible and carbapenem-susceptible Enterobacter cloacae complex (ECC) in different clusters. METHODS Ninety-one carbapenem-non-susceptible isolates and an equal number of carbapenem-susceptible isolates and their clinical information were collected from a university teaching hospital in China. The strains were divided into different clusters based on hsp60 analysis. The agar dilution method was used to determine the minimum inhibitory concentrations of common antibiotics. The crystal violet assay was used to measure biofilm-forming ability. The Galleria mellonella infection model and polymerase chain reaction of virulence genes were used to evaluate virulence. RESULTS The isolates were divided into 12 clusters based on hsp60 analysis. Cluster VIII accounted for a greater proportion of carbapenem-non-susceptible isolates than the other clusters. The same clusters exhibited different resistance rates in carbapenem-non-susceptible and carbapenem-susceptible isolates. Moreover, carbapenem-non-susceptible isolates carried fewer virulence genes than carbapenem-susceptible isolates, and carbapenem-non-susceptible isolates in cluster II in did not carry the detected virulence genes. Virulence of carbapenem-non-susceptible and carbapenem-susceptible isolates differed significantly in clusters I, III, VIII and IX, as evaluated using the G. mellonella infection model. Carbapenem-non-susceptible isolates in cluster VIII showed higher prevalence, resistance, biofilm-forming ability and pathogenicity compared with the other clusters. CONCLUSIONS The study findings indicate the need to identify subgroups of ECC, and provide better advice and guidance for the use of carbapenems.
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Affiliation(s)
- Z Huang
- Department of Clinical Laboratory, First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Wenzhou, Zhejiang Province, China
| | - S Liu
- Department of Clinical Laboratory, Children's Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China
| | - Y Wang
- Department of Clinical Laboratory, First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Wenzhou, Zhejiang Province, China
| | - Z Yao
- School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - L Feng
- School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - Y Lin
- School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - J Ye
- Department of Clinical Laboratory, First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Wenzhou, Zhejiang Province, China
| | - T Zhou
- Department of Clinical Laboratory, First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Wenzhou, Zhejiang Province, China.
| | - Z Wang
- Department of Clinical Laboratory, First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Wenzhou, Zhejiang Province, China.
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14
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Wang F, Li X, Jiang S, Han J, Wu J, Yan M, Yao Z. Enantioselective Behaviors of Chiral Pesticides and Enantiomeric Signatures in Foods and the Environment. J Agric Food Chem 2023; 71:12372-12389. [PMID: 37565661 DOI: 10.1021/acs.jafc.3c02564] [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] [Indexed: 08/12/2023]
Abstract
Unreasonable application of pesticides may result in residues in the environment and foods. Chiral pesticides consist of two or more enantiomers, which may exhibit different behaviors. This Review intends to provide progress on the enantioselective residues of chiral pesticides in foods. Among the main chiral analytical methods, high performance liquid chromatography (HPLC) is the most frequently utilized. Most chiral pesticides are utilized as racemates; however, due to enantioselective dissipation, bioaccumulation, biodegradation, and chiral conversion, enantiospecific residues have been found in the environment and foods. Some chiral pesticides exhibit strong enantioselectivity, highlighting the importance of evaluation on an enantiomeric level. However, the occurrence characteristics of chiral pesticides in foods and specific enzymes or transport proteins involved in enantioselectivity needs to be further investigated. This Review could help the production of some chiral pesticides to single-enantiomer formulations, thereby reducing pesticide consumption as well as increasing food production and finally reducing human health risks.
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Affiliation(s)
- Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
- China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Xiaoyun Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
- China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
- China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Jiajun Han
- Department of Applied Chemistry, China Agricultural University, Beijing 100193, China
| | - Junxue Wu
- Institute of Plant and Environmental Protection, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China
| | - Meilin Yan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
- China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
- China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
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15
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Zhang H, Wang X, Shen X, Li X, Wu B, Li G, Bai H, Cao X, Hao X, Zhou Q, Yao Z. Chemical characterization of volatile organic compounds (VOCs) emitted from multiple cooking cuisines and purification efficiency assessments. J Environ Sci (China) 2023; 130:163-173. [PMID: 37032033 DOI: 10.1016/j.jes.2022.08.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 05/01/2022] [Revised: 07/25/2022] [Accepted: 08/02/2022] [Indexed: 06/19/2023]
Abstract
Cooking process can produce abundant volatile organic compounds (VOCs), which are harmful to environment and human health. Therefore, we conducted a comprehensive analysis in which VOCs emissions from multiple cuisines have been sampled based on the simulation and acquisition platform, involving concentration characteristics, ozone formation potential (OFP) and purification efficiency assessments. VOCs emissions varied from 1828.5 to 14,355.1 µg/m3, with the maximum and minimum values from Barbecue and Family cuisine, respectively. Alkanes and alcohol had higher contributions to VOCs from Sichuan and Hunan cuisine (64.1%), Family cuisine (66.3%), Shandong cuisine (69.1%) and Cantonese cuisine (69.8%), with the dominant VOCs species of ethanol, isobutane and n-butane. In comparison, alcohols (79.5%) were abundant for Huaiyang cuisine, while alkanes (19.7%), alkenes (35.9%) and haloalkanes (22.9%) accounted for higher proportions from Barbecue. Specially, carbon tetrachloride, n-hexylene and 1-butene were the most abundant VOCs species for Barbecue, ranging from 8.8% to 14.6%. The highest OFP occurred in Barbecue. The sensitive species of OFP for Huaiyang cuisine were alcohols, while other cuisines were alkenes. Purification efficiency assessments shed light on the removal differences of individual and synergistic control technologies. VOCs emissions exhibited a strong dependence on the photocatalytic oxidation, with the removal efficiencies of 29.0%-54.4%. However, the high voltage electrostatic, wet purification and mechanical separation techniques played a mediocre or even counterproductive role in the VOCs reduction, meanwhile collaborative control technologies could not significantly improve the removal efficiency. Our results identified more effective control technologies, which were conductive to alleviating air pollution from cooking emissions.
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Affiliation(s)
- Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xuejun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Guohao Li
- Beijing Municipal Research Institute of Environmental Protection, Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, National Urban Environmental Pollution Control Engineering Research Center, Beijing 100037, China
| | - Huahua Bai
- Beijing Municipal Research Institute of Environmental Protection, Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, National Urban Environmental Pollution Control Engineering Research Center, Beijing 100037, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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16
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Shen X, Che H, Yao Z, Wu B, Lv T, Yu W, Cao X, Hao X, Li X, Zhang H, Yao X. Real-World Emission Characteristics of Full-Volatility Organics Originating from Nonroad Agricultural Machinery during Agricultural Activities. Environ Sci Technol 2023. [PMID: 37419883 DOI: 10.1021/acs.est.3c02619] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/09/2023]
Abstract
Nonroad agricultural machinery (NRAM) emissions constitute a significant source of air pollution in China. Full-volatility organics originating from 19 machines under 6 agricultural activities were measured synchronously. The diesel-based emission factors (EFs) for full-volatility organics were 4.71 ± 2.78 g/kg fuel (average ± standard deviation), including 91.58 ± 8.42% volatile organic compounds (VOCs), 7.94 ± 8.16% intermediate-volatility organic compounds (IVOCs), 0.28 ± 0.20% semivolatile organic compounds (SVOCs), and 0.20 ± 0.16% low-volatility organic compounds (LVOCs). Full-volatility organic EFs were significantly reduced by stricter emission standards and were the highest under pesticide spraying activity. Our results also demonstrated that combustion efficiency was a potential factor influencing full-volatility organic emissions. Gas-particle partitioning in full-volatility organics could be affected by multiple factors. Furthermore, the estimated secondary organic aerosol formation potential based on measured full-volatility organics was 143.79 ± 216.80 mg/kg fuel and could be primarily attributed to higher-volatility-interval IVOCs (bin12-bin16 contributed 52.81 ± 11.58%). Finally, the estimated emissions of full-volatility organics from NRAM in China (2021) were 94.23 Gg. This study provides first-hand data on full-volatility organic EFs originating from NRAM to facilitate the improvement of emission inventories and atmospheric chemistry models.
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Affiliation(s)
- Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hongqian Che
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Tiantian Lv
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Wenhan Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xiaolong Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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17
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Liu S, Jiang S, Yao Z, Liu M. Aflatoxin detection technologies: recent advances and future prospects. Environ Sci Pollut Res Int 2023; 30:79627-79653. [PMID: 37322403 DOI: 10.1007/s11356-023-28110-x] [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: 11/25/2022] [Accepted: 06/01/2023] [Indexed: 06/17/2023]
Abstract
Aflatoxins have posed serious threat to food safety and human health. Therefore, it is important to detect aflatoxins in samples rapidly and accurately. In this review, various technologies to detect aflatoxins in food are discussed, including conventional ones such as thin-layer chromatography (TLC), high performance liquid chromatography (HPLC), enzyme linked immunosorbent assay (ELISA), colloidal gold immunochromatographic assay (GICA), radioimmunoassay (RIA), fluorescence spectroscopy (FS), as well as emerging ones (e.g., biosensors, molecular imprinting technology, surface plasmon resonance). Critical challenges of these technologies include high cost, complex processing procedures and long processing time, low stability, low repeatability, low accuracy, poor portability, and so on. Critical discussion is provided on the trade-off relationship between detection speed and detection accuracy, as well as the application scenario and sustainability of different technologies. Especially, the prospect of combining different technologies is discussed. Future research is necessary to develop more convenient, more accurate, faster, and cost-effective technologies to detect aflatoxins.
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Affiliation(s)
- Shenqi Liu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
| | - Minhua Liu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
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18
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Che H, Shen X, Yao Z, Wu B, Gou R, Hao X, Cao X, Li X, Zhang H, Wang S, Chen Z. Real-world emission characteristics and inventory of volatile organic compounds originating from construction and agricultural machinery. Sci Total Environ 2023:164993. [PMID: 37343865 DOI: 10.1016/j.scitotenv.2023.164993] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/03/2023] [Accepted: 06/16/2023] [Indexed: 06/23/2023]
Abstract
Volatile organic compound (VOC) emissions originating from nonroad mobile sources constitute an important but uncertain source of secondary organic aerosols (SOAs) and ozone (O3). In this study, we investigated the emission factors (EFs) of 120 individual VOC species for 40 machines via gas chromatography-mass spectrometry/flame ionization detection and high-performance liquid chromatography. The results showed that the diesel-based VOC EF for the tested machines was 4.18 ± 2.55 (average ± standard deviation) g/kg fuel, dominated by alkanes (38.20 % ± 18.08 %) and oxygenated VOCs (OVOCs; 30.94 % ± 15.71 %). The machine type, rated power, emission standards, and operating conditions affected the emissions of VOCs and their components, and this effect maybe mostly depends on the fuel combustion efficiency. The VOC species were primarily distributed in the C1-C2 and C4-C6 (based on the carbon number) and B4-B6 (based on the saturated vapor concentration) intervals. Furthermore, the estimated formation potential (FP) values of SOAs and O3 from VOCs were 21.02 ± 15.57 mg/kg fuel and 15.96 ± 11.87 g/kg fuel, respectively. VOC control based on the SOA formation potential (SOAFP) and ozone formation potential (OFP) could be more effective in the mitigation of fine particulate matter (PM2.5) and O3 pollution because the top 5 species ranked by percentage contribution accounted for 83.09 % ± 9.59 % and 51.78 % ± 14.38 % of the estimated SOAFP and OFP, respectively. Finally, the emission estimates showed that the VOC emissions originating from construction and agricultural machinery in China (2020) reached 64.05 and 95.24 Gg, respectively. We provide species-specific VOC EFs and detailed emission characteristics to facilitate a comprehensive understanding of gas emissions originating from nonroad mobile sources and an update of emission inventories and atmospheric chemistry models.
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Affiliation(s)
- Hongqian Che
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China.
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; China Food Flavor and Nutrition Health Innovation Center, Beijing Technology and Business University, Beijing 100048, China
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Runling Gou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Siwen Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zhenyi Chen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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19
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Niu C, Yao Z, Jiang S. Synthesis and application of quantum dots in detection of environmental contaminants in food: A comprehensive review. Sci Total Environ 2023; 882:163565. [PMID: 37080319 DOI: 10.1016/j.scitotenv.2023.163565] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/03/2023]
Abstract
Environmental pollutants can accumulate in the human body through the food chain, which may seriously impact human health. Therefore, it is of vital importance to develop quick, simple, accurate and sensitive (respond quickly) technologies to evaluate the concentration of environmental pollutants in food. Quantum dots (QDs)-based fluorescence detection methods have great potential to overcome the shortcomings of traditional detection methods, such as long detection time, cumbersome detection procedures, and low sensitivity. This paper reviews the types and synthesis methods of QDs with a focus on green synthesis and the research progress on rapid detection of environmental pollutants (e.g., heavy metals, pesticides, and antibiotics) in food. Metal-based QDs, carbon-based QDs, and "top-down" and "bottom-up" synthesis methods are discussed in detail. In addition, research progress of QDs in detecting different environmental pollutants in food is discussed, especially, the practical application of these methods is analyzed. Finally, current challenges and future research directions of QDs-based detection technologies are critically discussed. Hydrothermal synthesis of carbon-based QDs with low toxicity from natural materials has a promising future. Research is needed on green synthesis of QDs, direct detection without pre-processing, and simultaneous detection of multiple contaminants. Finally, how to keep the mobile sensor stable, sensitive and easy to store is a hot topic in the future.
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Affiliation(s)
- Chenyue Niu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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20
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Luo R, Su Z, Kang K, Yu M, Zhou X, Wu Y, Yao Z, Xiu W, Yu Y, Zhou L, Na F, Li Y, Zhang X, Zou B, Peng F, Wang J, Xue J, Gong Y, Lu Y. 197P Combining stereotactic body radiation and low-dose radiation (EclipseRT) with PD-1 inhibitor in mice models and patients with bulky tumor. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00450-1] [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: 04/03/2023]
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21
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Liu J, Peng L, Yu L, Liu X, Yao Z, Zhang Q. Reduced rural residential emissions in the Northern China Plain from 2015 to 2021. Sci Total Environ 2023; 865:161236. [PMID: 36592920 DOI: 10.1016/j.scitotenv.2022.161236] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 12/21/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
China's rapid economic growth over the past few decades has been fueled by the fossil-fuel dominated energy system. In Northern China, coal and biomass are important fuel types for household cooking and heating. The use of coal and biomass not only contributes to CO2 emissions, but also worsens the ambient air quality and further causes adverse health outcomes. Since 2016, action plans have been implemented annually to promote the substitution of solid fuel use in the rural households of the Beijing-Tianjin-Hebei and surrounding region ("2 + 26" region). However, a comprehensive evaluation of the emission reductions by the control policies is still lacking. In this study, we built a rural residential emission inventory in the "2 + 26" region based on two-phase national household surveys in 2010 and 2015. We evaluated the air pollutant and CO2 reduction benefits of various control measures from 2015 to 2021 and discussed the opportunities for the synergistical control of air pollutant and CO2 emissions. We estimated that, in 2015, the coal and biomass fuel consumption from rural households in the "2 + 26" region was 28.7 Mt. and 30.6 Mt., respectively, which resulted in 93.8 Mt., 416.5kt, 402.5kt, 80.1kt, 268.0kt, and 6122.2kt of CO2, PM2.5, SO2, NOx, VOCs, and CO emissions. With the implementation of household solid fuel substitution policies, air pollutant emissions were estimated to decrease by 53- 74 % from 2015 to 2021, while the percentage reduction of CO2 was only 39 % due to additional emissions from the alternative clean energy sources. If biomass was treated as carbon-neutral fuel, the CO2 reducing potential was even lower. Building a clean and sustainable rural energy system is a multi-win option for China to achieve the "Beautiful China", "Healthy China" and carbon-neutrality goals.
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Affiliation(s)
- Jun Liu
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China.
| | - Liqun Peng
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08544, USA
| | - Le Yu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Xiaoxuan Liu
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
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22
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Yu W, Shen X, Wu B, Kong L, Xuan K, Zhao C, Cao X, Hao X, Li X, Zhang H, Yao Z. Real-world emission characteristics of carbonyl compounds from agricultural machines based on a portable emission measurement system. J Environ Sci (China) 2023; 124:846-859. [PMID: 36182188 DOI: 10.1016/j.jes.2022.02.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [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: 09/13/2021] [Revised: 02/13/2022] [Accepted: 02/17/2022] [Indexed: 06/16/2023]
Abstract
Emissions of carbonyl compounds from agricultural machines cannot be ignored. Carbonyl compounds can cause the formation of ozone (O3) and secondary organic aerosols, which can cause photochemical smog to form. In this study, 20 agricultural machines were tested using portable emission measurement system (PEMS) under real-world tillage processes. The exhaust gases were sampled using 2,4-dinitrophenylhydrazine cartridges, and 15 carbonyl compounds were analyzed by high-performance liquid chromatography. Carbonyl compound emission factors for agricultural machines were 51.14-3315.62 mg/(kg-fuel), and were 2.58 ± 2.05, 0.86 ± 1.07 and 0.29 ± 0.20 g/(kg-fuel) for China 0, China II and China III emission standards, respectively. Carbonyl compound emission factor for sowing seeds of China 0 agricultural machines was 3.32 ± 1.73 g/(kg-fuel). Formaldehyde, acetaldehyde and acrolein were the dominant carbonyl compounds emitted. Differences in emission standards and tillage processes impact ozone formation potential (OFP). The mean OFP was 20.15 ± 16.15 g O3/(kg-fuel) for the China 0 emission standard. The OFP values decreased by 66.9% from China 0 to China II, and 67.4% from China II to China III. The mean OFP for sowing seeds of China 0 agricultural machines was 25.92 ± 13.84 g O3/(kg-fuel). Between 1.75 and 24.22 times more ozone was found to be formed during sowing seeds than during other processes for China 0 and China II agricultural machines. Total carbonyl compound emissions from agricultural machines in China was 19.23 Gg in 2019. The results improve our understanding of carbonyl compound emissions from agricultural machines in China.
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Affiliation(s)
- Wenhan Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China.
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Lei Kong
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Kaijie Xuan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Cheng Zhao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China.
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23
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Shen X, Che H, Lv T, Wu B, Cao X, Li X, Zhang H, Hao X, Zhou Q, Yao Z. Real-world emission characteristics of semivolatile/intermediate-volatility organic compounds originating from nonroad construction machinery in the working process. Sci Total Environ 2023; 858:159970. [PMID: 36347292 DOI: 10.1016/j.scitotenv.2022.159970] [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: 08/02/2022] [Revised: 10/26/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
Detailed emission characterization of semivolatile/intermediate-volatility organic compounds (S/IVOCs) originating from nonroad construction machines (NRCMs) remains lacking in China. Twenty-one NRCMs were evaluated with a portable emission measurement system in the working process. Gas phase S/IVOCs were collected by Tenax TA tubes and analyzed via thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Particle phase S/IVOCs were collected by quartz filters and analyzed via GC-MS. The average emission factors (EFs) for fuel-based total (gas + particle phase) IVOCs and SVOCs of the assessed NRCMs were 221.45 ± 194.60 and 11.68 ± 10.67 mg/kg fuel, respectively. Compared to excavators, the average IVOC and SVOC EFs of loaders were 1.32 and 1.55 times higher, respectively. Compared to the working mode, the average IVOC EFs under the moving mode (only moving forward or backward) were 1.28 times higher. The IVOC and SVOC EFs for excavators decreased by 69.06% and 38.37%, respectively, from China II to China III. These results demonstrate the effectiveness of emission control regulations. In regard to individual NRCMs, excavators and loaders were affected differently by emission standards. The volatility distribution demonstrated that IVOCs and SVOCs were dominated by gas- and particle-phase compounds, respectively. The mode of operation also affected S/IVOC gas-particle partitioning. Combined with previous studies, the mechanical type significantly affected the volatility distribution of IVOCs. IVOCs from higher volatile fuels are more distributed in the high-volatility interval. The total secondary organic aerosol (SOA) production potential was 104.36 ± 79.67 mg/kg fuel, which originated from VOCs (19.98%), IVOCs (73.87%), and SVOCs (6.15%). IVOCs were a larger SOA precursor than VOCs and SVOCs. In addition, normal (n-) alkanes were suitably correlated with IVOCs, which may represent a backup solution to quantify IVOC EFs. This work provides experimental data support for the refinement of the emission characteristics and emission inventories of S/IVOCs originating from NRCMs.
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Affiliation(s)
- Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Hongqian Che
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Tiantian Lv
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China.
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24
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Wu B, Wang W, Yao Z, Xuan K, Wu Z, Shen X, Li X, Zhang H, Xue Y, Cao X, Hao X, Zhou Q. Multi-pollutant emission characteristics of non-road construction equipment based on real-world measurement. Sci Total Environ 2022; 853:158601. [PMID: 36087679 DOI: 10.1016/j.scitotenv.2022.158601] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [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: 07/18/2022] [Revised: 08/30/2022] [Accepted: 09/04/2022] [Indexed: 06/15/2023]
Abstract
Non-road construction equipment (NRCE) has become a crucial contributor to urban air pollution. However, the current research on NRCE is still in its infancy, and the understanding of its pollutant emissions is not yet clear. In this study, multi-pollutant (CO, HC, NOx, PM2.5, and BC) and CO2 emissions from 12 excavators and 9 loaders under real-world conditions are investigated by using a synchronous platform based on portable emission measurement system (SP-PEMS). We find the instantaneous emission rates of multi-pollutant present significant variability under different operation modes, and pollutant emissions are significantly high under cold start. Generally, multi-pollutant emission factors (EFs) have been all effectively reduced with the tightening of emission standards except for CO and NOx. The BC and PM2.5 emissions are significantly affected by engine types, and those emitted by electronically-controlled fuel injection (EI) engines are at lower concentration levels compared with mechanical fuel injection (MI) engines. The mass ratios of BC/PM2.5 for EI engines are 2.05 times that for MI engines on average. Through comparison, we find the multi-pollutant EFs of NRCE reported by different studies and the Guide vary greatly, and those recommended by the Guide may be overestimated or underestimated to varying degrees. Finally, we recommend the multi-pollutant EFs of NRCE under different emission standards by combining the results of various studies, and which will provide scientific support for the accurately establish of emission inventory.
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Affiliation(s)
- Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Weijun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
| | - Kaijie Xuan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zichun Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Yifeng Xue
- National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Eco-Environmental Protection, Beijing 100037, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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25
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Yan M, Niu C, Li X, Wang F, Jiang S, Li K, Yao Z. Heavy metal levels in milk and dairy products and health risk assessment: A systematic review of studies in China. Sci Total Environ 2022; 851:158161. [PMID: 35988597 DOI: 10.1016/j.scitotenv.2022.158161] [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: 05/31/2022] [Revised: 08/02/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
Previous studies have indicated that heavy metal levels in milk vary partly depending on environmental metal concentrations. Given the increasing consumption of milk in China, it is essential to pay attention to milk safety. We performed a systematic review of relevant published studies to evaluate the heavy metal levels in milk and dairy products and the associated health risks, discuss environmental sources of heavy metals, and propose future research directions. A literature search was implemented in the Web of Science Core Collection and PubMed using multiple keywords such as "metal," "milk," "dairy products," and "China". A total of 16 published studies that analyzed metal levels in milk and dairy products in 20 provincial administrative regions were included. Most studies detected toxic heavy metals in milk and dairy products samples, including mercury, lead, cadmium, chromium, and arsenic. The lead concentration in milk from these studies did not exceed the Chinese standard for milk. However, three studies detected relatively high lead levels in both commercial and raw milk, exceeding the European Commission standard. The polluted environment surrounding the farm, feed, and packaging materials are likely sources of metals in milk and dairy products. The hazard index for the 11 analyzed metal elements in milk and dairy products was lower than 1, indicating negligible non-carcinogenic health risks from exposure to these metals. Children are at a higher risk than adults. This review illustrates that research in this field is limited to China. More research should be conducted in the future, such as evaluating the contribution of each environmental source of metal in milk and dairy products.
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Affiliation(s)
- Meilin Yan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Chenyue Niu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Ke Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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26
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Wu B, Wu Z, Yao Z, Li J, Wang W, Shen X, Hao X. Multi-type emission factors quantification of black carbon from agricultural machinery based on the whole tillage processes in China. Environ Pollut 2022; 314:120280. [PMID: 36167170 DOI: 10.1016/j.envpol.2022.120280] [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: 08/10/2022] [Revised: 09/19/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
Black carbon (BC), as one of the short-lived climate pollutants, is becoming more prominent contribution from non-road mobile source, especially for agricultural machinery (AM) in China. However, the understanding of BC emissions from AM is still not clear, and the BC emission factors (EFs) are also limited. In this study, we conducted real-world measurements on twenty AM to investigate the instantaneous BC emission characteristics and quantify BC EFs under the whole tillage processes. We find the instantaneous BC emissions and fuel consumptions are obvious differences and present good synchronization under different tillage processes. Multi-type (CO2-, fuel-, distance-, time-, and area-based) EFs of BC are developed, which are significantly affected by different tillage processes and emission standards of the used AM. While AM conducting rotary tillage, ploughing, harvest corn and harvest wheat on the same area of land, total BC emissions by using the China III emission standard AM will be reduced by 56%, 36%, 88%, and 87% than those by using China II emission standard AM, respectively. Furthermore, for corn and wheat production under the whole tillage processes, BC EFs are 16.90 (6.03-39.12) g/hm2 and 18.18 (5.91-38.69) g/hm2, CO2 EFs are 112.64 (72.07-195.98) g/hm2 and 103.72 (71.47-167.02) g/hm2, respectively. We estimate the BC and CO2 emissions from wheat and corn productions based on the average area-based EFs. The large fluctuation ranges of BC and CO2 emissions in different tillage processes and the whole processes can reflect that the use of AM in China is uneven. It also indicates that there is a large space for BC and CO2 emission reduction and optimization. Therefore, more attention should be paid to the control of BC and CO2 emissions from AM. We believe that the recommended multi-type EFs are applicable for the quantification of BC emissions from AM in China and other countries.
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Affiliation(s)
- Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zichun Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
| | - Jiahan Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Weijun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
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27
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Morvan A, Andersen TI, Mi X, Neill C, Petukhov A, Kechedzhi K, Abanin DA, Michailidis A, Acharya R, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores Burgos L, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Grajales Dau A, Gross JA, Habegger S, Hamilton MC, Harrigan MP, Harrington SD, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Malone F, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Nersisyan A, Newman M, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Olenewa R, Opremcak A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shvarts V, Skruzny J, Smith WC, Strain D, Sterling G, Su Y, Szalay M, Torres A, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Xing C, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Aleiner I, Ioffe LB, Roushan P. Formation of robust bound states of interacting microwave photons. Nature 2022; 612:240-245. [PMID: 36477133 PMCID: PMC9729104 DOI: 10.1038/s41586-022-05348-y] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/14/2022] [Indexed: 12/12/2022]
Abstract
Systems of correlated particles appear in many fields of modern science and represent some of the most intractable computational problems in nature. The computational challenge in these systems arises when interactions become comparable to other energy scales, which makes the state of each particle depend on all other particles1. The lack of general solutions for the three-body problem and acceptable theory for strongly correlated electrons shows that our understanding of correlated systems fades when the particle number or the interaction strength increases. One of the hallmarks of interacting systems is the formation of multiparticle bound states2-9. Here we develop a high-fidelity parameterizable fSim gate and implement the periodic quantum circuit of the spin-½ XXZ model in a ring of 24 superconducting qubits. We study the propagation of these excitations and observe their bound nature for up to five photons. We devise a phase-sensitive method for constructing the few-body spectrum of the bound states and extract their pseudo-charge by introducing a synthetic flux. By introducing interactions between the ring and additional qubits, we observe an unexpected resilience of the bound states to integrability breaking. This finding goes against the idea that bound states in non-integrable systems are unstable when their energies overlap with the continuum spectrum. Our work provides experimental evidence for bound states of interacting photons and discovers their stability beyond the integrability limit.
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Affiliation(s)
- A Morvan
- Google Research, Mountain View, CA, USA
| | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J Basso
- Google Research, Mountain View, CA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | - D Eppens
- Google Research, Mountain View, CA, USA
| | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Computation and Communication Technology, Centre for Quantum Software and Information, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Y Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - F Malone
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | - K C Miao
- Google Research, Mountain View, CA, USA
| | - M Mohseni
- Google Research, Mountain View, CA, USA
| | | | - E Mount
- Google Research, Mountain View, CA, USA
| | | | - O Naaman
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - R Olenewa
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | | | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - D Strain
- Google Research, Mountain View, CA, USA
| | | | - Y Su
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - I Aleiner
- Google Research, Mountain View, CA, USA.
| | - L B Ioffe
- Google Research, Mountain View, CA, USA.
| | - P Roushan
- Google Research, Mountain View, CA, USA.
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28
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Mi X, Sonner M, Niu MY, Lee KW, Foxen B, Acharya R, Aleiner I, Andersen TI, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Brill L, Broughton M, Buckley BB, Buell DA, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Debroy DM, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores L, Forati E, Fowler AG, Giang W, Gidney C, Gilboa D, Giustina M, Dau AG, Gross JA, Habegger S, Harrigan MP, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Kafri D, Kechedzhi K, Khattar T, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Lee J, Laws L, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Morvan A, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Newman M, O’Brien TE, Opremcak A, Petukhov A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schuster C, Shearn MJ, Shvarts V, Strain D, Su Y, Szalay M, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Chen Y, Kelly J, Smelyanskiy V, Abanin DA, Roushan P. Noise-resilient edge modes on a chain of superconducting qubits. Science 2022; 378:785-790. [DOI: 10.1126/science.abq5769] [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] [Indexed: 11/18/2022]
Abstract
Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the one-dimensional kicked Ising model, which exhibits nonlocal Majorana edge modes (MEMs) with
ℤ
2
parity symmetry. We find that any multiqubit Pauli operator overlapping with the MEMs exhibits a uniform late-time decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This characteristic allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Furthermore, the MEMs are found to be resilient against certain symmetry-breaking noise owing to a prethermalization mechanism. Our work elucidates the complex interplay between noise and symmetry-protected edge modes in a solid-state environment.
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Affiliation(s)
- X. Mi
- Google Research, Mountain View, CA, USA
| | - M. Sonner
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - M. Y. Niu
- Google Research, Mountain View, CA, USA
| | - K. W. Lee
- Google Research, Mountain View, CA, USA
| | - B. Foxen
- Google Research, Mountain View, CA, USA
| | | | | | | | - F. Arute
- Google Research, Mountain View, CA, USA
| | - K. Arya
- Google Research, Mountain View, CA, USA
| | - A. Asfaw
- Google Research, Mountain View, CA, USA
| | | | - J. C. Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J. Basso
- Google Research, Mountain View, CA, USA
| | | | | | | | - L. Brill
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Chen
- Google Research, Mountain View, CA, USA
| | - B. Chiaro
- Google Research, Mountain View, CA, USA
| | | | - P. Conner
- Google Research, Mountain View, CA, USA
| | | | | | | | - S. Demura
- Google Research, Mountain View, CA, USA
| | | | - D. Eppens
- Google Research, Mountain View, CA, USA
| | | | - L. Faoro
- Google Research, Mountain View, CA, USA
| | - E. Farhi
- Google Research, Mountain View, CA, USA
| | - R. Fatemi
- Google Research, Mountain View, CA, USA
| | - L. Flores
- Google Research, Mountain View, CA, USA
| | - E. Forati
- Google Research, Mountain View, CA, USA
| | | | - W. Giang
- Google Research, Mountain View, CA, USA
| | - C. Gidney
- Google Research, Mountain View, CA, USA
| | - D. Gilboa
- Google Research, Mountain View, CA, USA
| | | | - A. G. Dau
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - S. Hong
- Google Research, Mountain View, CA, USA
| | - T. Huang
- Google Research, Mountain View, CA, USA
| | - A. Huff
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Jiang
- Google Research, Mountain View, CA, USA
| | - C. Jones
- Google Research, Mountain View, CA, USA
| | - D. Kafri
- Google Research, Mountain View, CA, USA
| | | | | | - S. Kim
- Google Research, Mountain View, CA, USA
| | - A. Y. Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | | | - A. N. Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P. Laptev
- Google Research, Mountain View, CA, USA
| | - K.-M. Lau
- Google Research, Mountain View, CA, USA
| | - J. Lee
- Google Research, Mountain View, CA, USA
| | - L. Laws
- Google Research, Mountain View, CA, USA
| | - W. Liu
- Google Research, Mountain View, CA, USA
| | | | - O. Martin
- Google Research, Mountain View, CA, USA
| | | | - M. McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | | | | | | | - A. Morvan
- Google Research, Mountain View, CA, USA
| | - E. Mount
- Google Research, Mountain View, CA, USA
| | | | - O. Naaman
- Google Research, Mountain View, CA, USA
| | - M. Neeley
- Google Research, Mountain View, CA, USA
| | - C. Neill
- Google Research, Mountain View, CA, USA
| | - M. Newman
- Google Research, Mountain View, CA, USA
| | | | | | | | - R. Potter
- Google Research, Mountain View, CA, USA
| | | | | | - N. Saei
- Google Research, Mountain View, CA, USA
| | - D. Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - D. Strain
- Google Research, Mountain View, CA, USA
| | - Y. Su
- Google Research, Mountain View, CA, USA
| | - M. Szalay
- Google Research, Mountain View, CA, USA
| | - G. Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T. White
- Google Research, Mountain View, CA, USA
| | - Z. Yao
- Google Research, Mountain View, CA, USA
| | - P. Yeh
- Google Research, Mountain View, CA, USA
| | - J. Yoo
- Google Research, Mountain View, CA, USA
| | | | - Y. Zhang
- Google Research, Mountain View, CA, USA
| | - N. Zhu
- Google Research, Mountain View, CA, USA
| | - H. Neven
- Google Research, Mountain View, CA, USA
| | - D. Bacon
- Google Research, Mountain View, CA, USA
| | - J. Hilton
- Google Research, Mountain View, CA, USA
| | - E. Lucero
- Google Research, Mountain View, CA, USA
| | | | - S. Boixo
- Google Research, Mountain View, CA, USA
| | | | - Y. Chen
- Google Research, Mountain View, CA, USA
| | - J. Kelly
- Google Research, Mountain View, CA, USA
| | | | - D. A. Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
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29
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Li Q, Jiang S, Jia W, Wang F, Wang Z, Cao X, Shen X, Yao Z. Novel silver-modified carboxymethyl chitosan antibacterial membranes using environment-friendly polymers. Chemosphere 2022; 307:136059. [PMID: 35977569 DOI: 10.1016/j.chemosphere.2022.136059] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [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: 05/23/2022] [Revised: 07/17/2022] [Accepted: 08/09/2022] [Indexed: 06/15/2023]
Abstract
The rapid reproduction of foodborne bacteria in food packaging threatens the health of consumers, the massive use and waste of packaging also causes serious environmental pollution. In this study, novel biodegradable antibacterial membranes based on silver-modified carboxymethyl chitosan (Ag-CMCS) were prepared. Polylactic acid (PLA) and polybutylene adipate-co-terephthalate (PBAT) were used as the base membrane materials. Characterization of the prepared membranes was performed by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), atomic force microscope (AFM), X-ray photoelectron spectroscopy (XPS), water contact angle, and so on. Especially, the silver on the surface of Ag-CMCS was proved to be metallic silver. For the first cycle of zone of inhibition test, the diameter of inhibition zone could reach up to 17 mm while the mass of silver released was negligible. The prepared antibacterial membranes could kill almost 100% of bacteria under certain conditions and inhibition zone still existed after more than 7 cycles of tests, indicating the prepared antibacterial membranes were effective. This study could provide new ideas for preparing efficient and environment-friendly antibacterial food packaging membranes.
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Affiliation(s)
- Qirun Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China
| | - Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China
| | - Wenting Jia
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China
| | - Zeru Wang
- School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing, Technology and Business University, Beijing 100048, China.
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30
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Li X, Chen W, Zhang H, Xue T, Zhong Y, Qi M, Shen X, Yao Z. Emissions of biogenic volatile organic compounds from urban green spaces in the six core districts of Beijing based on a new satellite dataset. Environ Pollut 2022; 308:119672. [PMID: 35764185 DOI: 10.1016/j.envpol.2022.119672] [Citation(s) in RCA: 4] [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: 01/01/2022] [Revised: 06/18/2022] [Accepted: 06/20/2022] [Indexed: 06/15/2023]
Abstract
Urban green spaces (UGSs) are often positively associated with the health of urban residents. However, UGSs may also have adverse health effects by releasing biogenic volatile organic compounds (BVOCs) and increasing the ambient concentrations of ozone (O3) and secondary organic aerosols in urban areas. BVOC emissions from UGSs might be underestimated because of the lack of consideration of the UGS land-use type in urban areas. As such, in this study, we used a newly released satellite dataset, Sentinel-2, with a resolution of 10 m, to derive the classification distribution of UGSs and predict the UGS emissions of BVOCs in Beijing in 2019. The results showed that the annual emissions of BVOCs from UGSs were approximately 2.9 Gg C (95% confidence interval (CI): 2.4-3.3) in the six core districts, accounting for approximately 39% of the total UGS emissions in Beijing. Compared with the results based on Sentinel-2, the BVOC emissions might be underestimated by approximately 37% (95% CI: 11-63) using the commonly used satellite dataset. UGSs produced the highest BVOC emissions in summer (from June to August), accounting for 75.2% of the annual emissions. UGSs contributed the most to the O3 formation potential in summer, accounting for 41.5% of the total. We could attribute a considerable amount of the O3 concentration (27.0 μg m-3, 95% CI: 21.4-32.6) to the UGS BVOCs produced in the core districts of Beijing in July. The new BVOC emissions dataset based on Sentinel-2 vegetation information facilitates modeling studies on the formation of surface O3 in urban areas and assessments of the impact of UGSs on public health.
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Affiliation(s)
- Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Wenjing Chen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Tao Xue
- Institute of Reproductive and Child Health / Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, 100191, China
| | - Yuanwei Zhong
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Min Qi
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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31
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Yu D, Niu J, Zhong L, Chen K, Wang G, Yan M, Li D, Yao Z. Biochar raw material selection and application in the food chain: A review. Sci Total Environ 2022; 836:155571. [PMID: 35490824 DOI: 10.1016/j.scitotenv.2022.155571] [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: 01/19/2022] [Revised: 04/24/2022] [Accepted: 04/24/2022] [Indexed: 06/14/2023]
Abstract
As one of the largest carbon emitters, China promises to achieve carbon emissions neutrality by 2060. Various industries are developing businesses to reduce carbon emissions. As an important greenhouse gas emissions scenario, the reduction of carbon emissions in the food chain can be achieved by preparing the wastes into biochar. The food chain, as one of the sources of biochar, consists of production, processing and consumption, in which many wastes can be transferred into biochar. However, few studies use the food chain as the system to sort out the raw materials of biochar. A systematic review of the food chain application in serving as raw materials for biochar is helpful for further application of such technique, providing supportive information for the development of biochar preparation and wastes treating. In addition, there are many pollution sources in the food production process, such as agricultural contaminated soil and wastewater from livestock and aquatic, that can be treated on-site to achieve the goal of treating wastes with wastes within the food chain. This study focuses on waste resource utilization and pollution remediation in the food chain, summarizing the sources of biochar in the food chain and analyzing the feasibility of using waste in food chain to treat contaminated sites in the food chain and discussing the impacts of the greenhouse gas emissions. This review provides a reference for the resource utilization of waste and pollution reduction in the food chain.
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Affiliation(s)
- Dayang Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Jinjia Niu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Longchun Zhong
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Kaiyu Chen
- Department of Chemical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Guanyi Wang
- State Grid UHV Engineering Construction Company, Beijing 100052, China
| | - Meilin Yan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Dandan Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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32
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Jiang S, Li Y, Wang F, Sun H, Wang H, Yao Z. A state-of-the-art review of CO 2 enhanced oil recovery as a promising technology to achieve carbon neutrality in China. Environ Res 2022; 210:112986. [PMID: 35192806 DOI: 10.1016/j.envres.2022.112986] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [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: 10/15/2021] [Revised: 01/25/2022] [Accepted: 02/18/2022] [Indexed: 06/14/2023]
Abstract
Although there are some review papers on carbon capture, utilization and storage (CCUS), hardly any of these reviews are focused on the role of CO2 enhanced oil recovery (EOR) in accelerating carbon neutrality in China. In this review, strategies to achieve carbon neutrality is briefly but critically discussed, followed by a review of CO2-EOR as a promising technology. Especially, data analysis, including the number of publications on China's carbon neutrality, per capita CO2 emissions, China's power generation, and the crude oil production of China's large oilfields, is carried out to make the discussion more comprehensive. Given the large amount of coal consumed in China, the high percent of electricity generated with coal, and the slow penetration of renewables already observed, it seems unlikely that 2060 targets will be met without CCUS. In order to achieve carbon neutrality, both reduction in carbon emissions and increase in carbon sequestration are inevitable. Furthermore, it is concluded that CO2 storage through EOR is likely to have a bright future. However, there are some critical issues to be solved, including the technical issues, leakage and safety issues, cost issues, policy issues, etc. In order to turn CO2-EOR into a reliable and more favorable technology, more research and efforts are needed to solve these issues, including advancing carbon capture technologies, improving storage technologies, developing effective monitoring technologies, deploying government support and incentive policies, etc.
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Affiliation(s)
- Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Yuening Li
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265, Military Trail, Toronto, Ontario, Canada
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Haishu Sun
- Department of Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Huijiao Wang
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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33
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Wu B, Xuan K, Zhang X, Wu Z, Wang W, Shen X, Li X, Zhang H, Cao X, Hao X, Zhou Q, Yao Z. Quantitative of instantaneous BC emissions based on vehicle specific power from real-world driving diesel trucks in China. Sci Total Environ 2022; 819:153230. [PMID: 35051463 DOI: 10.1016/j.scitotenv.2022.153230] [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: 12/04/2021] [Revised: 01/05/2022] [Accepted: 01/13/2022] [Indexed: 06/14/2023]
Abstract
In-depth exploration of the potential links between instantaneous black carbon (BC) emissions and driving parameters from real-world diesel trucks (DTs) is a key step toward development of a highly flexible vehicle emissions estimation system. In this study, we conducted real-world measurements on 22 DTs with mainstream types and emission standards, and obtained instantaneous data of BC emissions and vehicle driving. Since vehicle specific power (VSP) is an excellent surrogate for engine load, we characterize the instantaneous BC emissions and VSP distributions, and then establish links between VSP and fuel consumption, VSP and BC emission rates, VSP and BC emission factors (EFs), respectively. We find that BC emission rates of China V light-duty DTs installed with diesel particulate filter (DPF) are significantly lower (2 to 3 orders of magnitude) than those with China III and China IV. Frequent acceleration and deceleration of vehicles maybe the main reason leads to high BC emissions. The distribution of VSP is mainly concentrated in the ranges of -30 to 35 kW/t in the scope of this study. We find that VSP and BC EFs did not show a consistent pattern for all tested DTs, and BC EFs present obvious fluctuations with the VSP variation. The average fuel-based BC EFs vary by factors of 2.27-8.25 from the lowest to highest EFs. Through a fitting of the third-order polynomial function, we finally quantify and provide fitting formulas of BC EFs and VSP under more detailed categorization. Our results can provide important data support for accurate quantification of BC EFs, and even emission inventory calculations.
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Affiliation(s)
- Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Kaijie Xuan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zichun Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Weijun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China.
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34
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Jiang S, Li Q, Jia W, Wang F, Cao X, Shen X, Yao Z. Expanding the application of ion exchange resins for the preparation of antimicrobial membranes to control foodborne pathogens. Chemosphere 2022; 295:133963. [PMID: 35167836 DOI: 10.1016/j.chemosphere.2022.133963] [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: 10/11/2021] [Revised: 02/09/2022] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
Although ion exchange resins (IERs) have been extensively adopted in water treatment, there are no reports on the application thereof for synthesizing antibacterial materials against pathogenic bacteria. The present study is the first in which the ion exchange characteristic of IERs was utilized to introduce silver ions that possess efficient antibacterial properties. The resulting antibacterial materials were incorporated into polylactic acid (PLA) and/or polybutylene adipate terephthalate (PBAT) to prepare antibacterial membranes. XPS spectra revealed the occurrence of in-situ reduction of silver ions to metallic silver, which was preferable since the stability of silver in the materials was improved. EDS mapping analysis indicated that the distribution of silver was consistent with the distribution of sulfur in the membranes, verifying the ion exchange methodology proposed in the present study. To investigate the antibacterial performance of the prepared membranes, zone of inhibition tests and bacteria-killing tests were performed. The results revealed that neither bare polymeric membranes of PLA and PBAT nor IER-incorporated polymeric membranes exhibited noticeable antibacterial activities. In comparison, the antibacterial membranes demonstrated effective and sustainable antibacterial activities against pathogenic bacteria Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). The prepared antibacterial membranes exhibited potential in food-related applications such as food packaging to delay food spoilage due to microbial growth.
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Affiliation(s)
- Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Qirun Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Wenting Jia
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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35
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Li C, He L, Yao X, Yao Z. Recent advances in the chemical oxidation of gaseous volatile organic compounds (VOCs) in liquid phase. Chemosphere 2022; 295:133868. [PMID: 35131275 DOI: 10.1016/j.chemosphere.2022.133868] [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: 11/12/2021] [Revised: 01/05/2022] [Accepted: 02/02/2022] [Indexed: 06/14/2023]
Abstract
The chemical oxidation of gaseous volatile organic compounds (VOCs) in liquid phase may possess great advantages in its high removal efficiency, mild conditions, good reliability, wide applicability, and little potential secondary pollution, which has aroused extensive research interests in the past decade. This Overview Article summarizes the latest achievements to eliminate VOCs by chemical oxidation in liquid phase including gas-liquid mass transfer, homogeneous/heterogeneous oxidation, electrochemical oxidation, and coupling technologies. Important research contributions are highlighted in terms of mass transfer, catalytic materials, removal/mineralization efficiency, and reaction mechanism to evaluate their potential industrial applications. The current challenges and future strategies are discussed from the viewpoint of the deep degradation of refractory VOC substrates and their intermediates. It is anticipated that this review will attract more attention toward the development and application of chemical oxidation methods to clear complex industrial organic exhaust gas.
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Affiliation(s)
- Changming Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Li He
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Xiaolong Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
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36
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Wang F, Gao J, Li P, Jiang S, Wu J, Yao Z. Herbicidal activity and differential metabolism of lactofen in rat and loach on an enantiomeric level. Environ Sci Pollut Res Int 2022; 29:28307-28316. [PMID: 34993807 DOI: 10.1007/s11356-021-17986-2] [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: 09/02/2021] [Accepted: 12/03/2021] [Indexed: 06/14/2023]
Abstract
Enantioselectivity of chiral compounds is receiving growing concern. Lactofen, a chiral herbicide widely used in field crops and vegetables to control broadleaf weeds, is still sold as racemate. In this work, the herbicidal activity and metabolism behavior of lactofen were investigated on an enantiomeric level. Two common broadleaf weeds (Eclipta prostrata L. and Portulaca oleracea L.) were used to evaluate the herbicidal activity of rac-/R- and S-lactofen, and their metabolism behavior in loach and rat liver microsomes was explored. Higher herbicidal activity of S-lactofen was observed, with the 20d-EC50 values being 1.9-3.4 times lower than R-lactofen. Both loach and rat liver microsomes had ability to metabolize rac-lactofen, with half-lives of 1.93 and 1.28 h, respectively. Enantioselective metabolism behaviors were observed in loach and rat liver microsomes and the direction of enantioselectivity were different. R-lactofen was preferentially metabolized in loach liver microsome, while S-lactofen was preferentially metabolized in rat liver microsome. No interconversion of R- and S-lactofen was found. Besides, the main metabolic pathways of R- and S-lactofen were found to be significantly different. R-lactofen was metabolized to R-desethyl lactofen in both loach and rat liver microsomes without further metabolism. However, S-lactofen was metabolized to both S-desethyl lactofen and acifluorfene in rat liver microsome, which was mainly metabolized to acifluorfene in loach liver microsome. This study indicated enantioselectivity and metabolites should be taken into consideration when overall evaluating the environmental behavior of lactofen.
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Affiliation(s)
- Fang Wang
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, People's Republic of China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, People's Republic of China
- Beijing Advanced Innovation Centre for Food Nutrition and Human Health. Department of Applied Chemistry, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Jing Gao
- Beijing Advanced Innovation Centre for Food Nutrition and Human Health. Department of Applied Chemistry, China Agricultural University, Beijing, 100193, People's Republic of China
- School of Environment, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Peize Li
- Beijing Advanced Innovation Centre for Food Nutrition and Human Health. Department of Applied Chemistry, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Shanxue Jiang
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, People's Republic of China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, People's Republic of China
| | - Junxue Wu
- Institute of Plant and Environmental Protection, Beijing Academy of Agriculture and Forestry Science, Beijing, 100097, People's Republic of China
| | - Zhiliang Yao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, People's Republic of China.
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, People's Republic of China.
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Xu Y, Li B, Shen X, Li K, Cao X, Cui G, Yao Z. Digital soil mapping of soil total nitrogen based on Landsat 8, Sentinel 2, and WorldView-2 images in smallholder farms in Yellow River Basin, China. Environ Monit Assess 2022; 194:282. [PMID: 35294667 DOI: 10.1007/s10661-022-09902-z] [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: 11/03/2021] [Accepted: 02/25/2022] [Indexed: 06/14/2023]
Abstract
Predicting spatial explicit information of soil nutrients is critical for sustainable soil management and food security under climate change and human disturbance in agricultural land. Digital soil mapping (DSM) techniques can utilize soil-landscape information from remote sensing data to predict the spatial pattern of soil nutrients, and it is important to explore the effects of remote sensing data types on DSM. This research utilized Landsat 8 (LT), Sentinel 2 (ST), and WorldView-2 (WV) remote sensing data and employed partial least squares regression (PLSR), random forest (RF), and support vector machine (SVM) algorithms to characterize the spatial pattern of soil total nitrogen (TN) in smallholder farm settings in Yellow River Basin, China. The overall relationships between TN and spectral indices from LT and ST were stronger than those from WV. Multiple red edge band-based spectral indices from ST and WV were relevant variables for TN, while there were no red band-based spectral indices from ST and WV identified as relevant variables for TN. Soil moisture and vegetation were major driving forces of soil TN spatial distribution in this area. The research also concluded that farmlands of crop rotation had relatively higher TN concentration compared with farmlands of monoculture. The soil prediction models based on WV achieved relatively lower model performance compared with those based on ST and LT. The effects of remote sensing data spectral resolution and spectral range on enhancing soil prediction model performance are higher than the effects of remote sensing data spatial resolution. Soil prediction models based on ST can provide location-specific soil maps, achieve fair model performance, and have low cost. This research suggests DSM research utilizing ST has relatively high prediction accuracy, and can produce soil maps that are fit for the spatial explicit soil management for smallholder farms.
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Affiliation(s)
- Yiming Xu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Bin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Ke Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Guannan Cui
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
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38
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Yu D, Yu Y, Tang J, Li X, Ke C, Yao Z. Application fields of kitchen waste biochar and its prospects as catalytic material: A review. Sci Total Environ 2022; 810:152171. [PMID: 34875332 DOI: 10.1016/j.scitotenv.2021.152171] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [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: 10/03/2021] [Revised: 11/30/2021] [Accepted: 11/30/2021] [Indexed: 06/13/2023]
Abstract
In China, a large amount of kitchen waste (KW) is generated each year, and the resource utilisation of the KW has become a problem. KW has a high carbon content and can be used as a raw material for biochar. Kitchen waste biochar (KWB) can be used to prepare adsorption materials, soil amendments, energy materials, carbon quantum dots, and electrode materials. However, few studies have used KWB as a raw material for catalytic materials. The application of sulfur (S) and nitrogen (N) doped biochar in the field of catalysis has proved effective and feasible. KWB contained a certain mass percentage of N and S elements, which has good application potential for use in the field of catalysis by KWB. In the process of preparing KWB by KW, keeping S and N as much as possible and converting them into pyridine N and thiophene S benefit the application of catalysis. This review provides a reference for the future application of KWB in China.
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Affiliation(s)
- Dayang Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Yan Yu
- School of Chemical & Environmental Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
| | - Jiawei Tang
- State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 100011, China
| | - Xiuqing Li
- Shandong Provincial Research Institute of Coal Geology Planning and Exploration, Jinan 250104, China
| | - Chao Ke
- Baohang Environment Company Limited, Beijing 100012, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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39
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Yu D, Pei Y, Ji Z, He X, Yao Z. A review on the landfill leachate treatment technologies and application prospects of three-dimensional electrode technology. Chemosphere 2022; 291:132895. [PMID: 34780739 DOI: 10.1016/j.chemosphere.2021.132895] [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: 09/21/2021] [Revised: 10/30/2021] [Accepted: 11/11/2021] [Indexed: 06/13/2023]
Abstract
With the expansion of urbanisation, the total amount of solid waste produced by urban residents has been increasing, and the problem of municipal solid waste disposal has also been aggravated. Landfill leachate treatment technologies could be divided into three categories: biological, physical and advanced oxidation treatment technology. Among them, advanced oxidation treatment technology has a good effect on the treatment of landfill leachate with little secondary pollution and has excellent application potential. Three-dimensional (3D) electrode technology, as a new type of advanced oxidation technology, could remove refractory pollutants in water and has attracted considerable attention. This article aims to (1) compare existing landfill leachate treatment technologies, (2) summarise 3D electrode technology application scenarios, (3) discuss the advantages of 3D electrode technology in landfill leachate treatment and (4) look ahead the future directions of 3D electrode technology in landfill leachate treatment. We hope that this article will be helpful to researchers who are interested in the field of landfill leachate treatment.
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Affiliation(s)
- Dayang Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Yuansheng Pei
- The Key Laboratory of Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Zehua Ji
- School of Environment, Tsinghua University, Beijing, 100083, China
| | - Xudan He
- Institute of Resources and Environment, Beijing Academy of Science and Technology, Beijing, 100089, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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40
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Jiang S, Li Q, Wang F, Wang Z, Cao X, Shen X, Yao Z. Highly effective and sustainable antibacterial membranes synthesized using biodegradable polymers. Chemosphere 2022; 291:133106. [PMID: 34848235 DOI: 10.1016/j.chemosphere.2021.133106] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [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: 09/25/2021] [Revised: 11/21/2021] [Accepted: 11/26/2021] [Indexed: 06/13/2023]
Abstract
In order to reduce foodborne diseases caused by bacterial infections, antibacterial membranes have received increasing research interests in recent years. In this study, highly effective antibacterial membranes were prepared using biodegradable polymers, including polylactic acid (PLA), polybutylene adipate terephthalate (PBAT), and carboxymethyl cellulose (CMC). The cation exchange property of CMC was utilized to introduce silver to prepare antibacterial materials. The presence of silver in the membranes was confirmed by EDS mapping, and the reduction of silver ions to metallic silver was confirmed by the Ag3d XPS spectrum which displayed peaks at 374.46 eV and 368.45 eV, revealing that the oxidation state of silver changed to zero. Two common pathogenic bacteria, Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), were used to investigate the antibacterial performance of the prepared membranes. Zone of inhibition and bacteria-killing tests revealed that the antibacterial membranes were efficient in inhibiting the growth of bacteria (diameters of inhibition zone ranged from 16 mm to 19 mm for fresh membranes) and capable of killing 100% of bacteria under suitable conditions. Furthermore, after 6 cycles of continuous zone of inhibition tests, the membranes still showed noticeable antibacterial activities, which disclosed the sustainable antibacterial properties of the membranes.
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Affiliation(s)
- Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Qirun Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zeru Wang
- School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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41
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Yao X, Shi Y, Wang K, Wang C, He L, Li C, Yao Z. Highly efficient degradation of hydrogen sulfide, styrene, and m-xylene in a bio-trickling filter. Sci Total Environ 2022; 808:152130. [PMID: 34863757 DOI: 10.1016/j.scitotenv.2021.152130] [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: 09/07/2021] [Revised: 11/21/2021] [Accepted: 11/28/2021] [Indexed: 06/13/2023]
Abstract
Controlling the release of malodorous gas discharged from wastewater treatment plants (WWTPs) has become an urgent environmental problem in recent years. In this study, a bio-trickling filter (BTF) inoculated with microorganisms acclimated to activated sludge in a WWTP was used as the degradation equipment. A continuous degradation experiment with hydrogen sulfide, styrene, and m-xylene in the BTF lasted for 84 days (12 weeks). The degradation capacities of the BTF for hydrogen sulfide, styrene, and m-xylene were evaluated, and the synergy and inhibition among the substrates during biodegradation are discussed. The results indicated that the degradation efficiencies of the BTF were as high as 99.2% for hydrogen sulfide, 94.6% for styrene, and 100.0% for m-xylene. When the empty bed residence time was 30 s, the maximum elimination capacities (EC) achieved for hydrogen sulfide was 38 g m-3 h-1, for styrene was 200 g m-3 h-1, and for m-xylene was 75 g m-3 h-1. Furthermore, the microbial species and quantity of microorganisms in the middle and top of the BTF were much higher than those at the bottom of the BTF. A variety of microorganisms in the BTF can efficiently degrade the typical and highly toxic malodorous gases released from WWTPs. This study can help increase the understanding of the degradation of a mixture of sulfur-containing substances and aromatic hydrocarbons in BTF degradation and promote the development of technologies for the reduction of a complex mixture of malodorous gas emissions from organic wastewater treatment.
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Affiliation(s)
- Xiaolong Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Yue Shi
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Ke Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Chun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Li He
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Changming Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China.
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42
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Chen F, Wang Y, Wang X, Yao Z, Li M. Complex genetic models in dystrophic epidermolysis bullosa families with marked intra-familial phenotypic heterogeneity. J Eur Acad Dermatol Venereol 2022; 36:e550-e553. [PMID: 35181940 DOI: 10.1111/jdv.18020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 01/19/2022] [Accepted: 02/08/2022] [Indexed: 11/30/2022]
Affiliation(s)
- F Chen
- Department of Dermatology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Institute of Dermatology, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Y Wang
- Department of Dermatology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Institute of Dermatology, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - X Wang
- Institute of Dermatology, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Z Yao
- Department of Dermatology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Institute of Dermatology, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - M Li
- Department of Dermatology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Institute of Dermatology, Shanghai Jiaotong University School of Medicine, Shanghai, China
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Xu Y, Wang X, Cui G, Li K, Liu Y, Li B, Yao Z. Source apportionment and ecological and health risk mapping of soil heavy metals based on PMF, SOM, and GIS methods in Hulan River Watershed, Northeastern China. Environ Monit Assess 2022; 194:181. [PMID: 35157146 DOI: 10.1007/s10661-022-09826-8] [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: 09/08/2021] [Accepted: 01/29/2022] [Indexed: 06/14/2023]
Abstract
Heavy metals in agricultural soils not only affect the food security and soil security, but also endanger the human health through the food chain. Based on the incorporation of index analysis, positive matrix factorization (PMF), self-organizing map (SOM), and geostatistical methods, this research performed the assessment of source apportionment and ecological and health risks of soil heavy metals in Hulan River Watershed, Northeastern China. According to the Pollution Load Index (PLI), 83.08% of the soil samples were slightly or mildly polluted, and 1.54% of the soil samples were severely polluted. The ecological risk index (EI) showed that about 80.77% and 60.77% of the soil samples were beyond the low risk level for Hg and Cd, respectively. In this research, the non-carcinogenic and carcinogenic risk indices for children were higher than adult males and adult females. Four potential sources were revealed based on the PMF and SOM analysis including atmospheric deposition and industrial emission; transportation source; agricultural source; and a combination of agricultural, industrial, and natural sources. Considerable and high ecological risk from Hg existed in the area close to the coal steam-electric plant, and considerable and high ecological risk from Cd existed in the Hulan River estuary area. The eastern part of the study area experienced higher non-carcinogenic and carcinogenic risks for adults and children than the western part of the study area. The source apportionment and ecological and health risk mapping provide important role in reducing pollution sources. Zonal pollution control and soil restoration measures should be performed in the areas with high ecological and health risks.
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Affiliation(s)
- Yiming Xu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianxia Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Guannan Cui
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Ke Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Yanfeng Liu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Bin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
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Li C, Zhao S, Yao X, He L, Xu S, Shen X, Yao Z. The catalytic mechanism of intercalated chlorine anions as active basic sites in MgAl-layered double hydroxide for carbonyl sulfide hydrolysis. Environ Sci Pollut Res Int 2022; 29:10605-10616. [PMID: 34528201 DOI: 10.1007/s11356-021-16204-3] [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: 07/05/2021] [Accepted: 08/24/2021] [Indexed: 06/13/2023]
Abstract
In order to make clear the role of intercalated anions in layered double hydroxides (LDHs) for catalytic hydrolysis of carbonyl sulfide (COS), the adsorption and reaction characteristics of COS over the simple Mg2Al-Cl-LDH model catalyst were studied by both theoretical and experimental methods. Density functional theory (DFT) calculations by CASTEP found that the chloride ions in LDH function as the key Brønsted base sites to activate the adsorbed H2O with enlarged bond length and angle, facilitate the dissociative adsorption of intermediates including mono-thiocarbonic acid (MTA) and hydrogen thiocarbonic acid (HTA), and participate in the formation of transient states and subsequent hydrogen transfer process with decreased energy barriers during COS hydrolysis. COS hydrolysis will preferentially go through the dissociated intermediates of mono-thiocarbonates (MT) and hydrogen thiocarbonates (HT) with dramatically decreased energy barriers, and the rate-determining step of COS hydrolysis over Mg2Al-Cl-LDH will be the nucleophilic addition of C=O in COS by H2O (Ea = 1.10 eV). The experimental results further revealed that the apparent activation energy (0.89 eV) of COS hydrolysis over Mg2Al-Cl-LDH is close to theoretical value (1.10 eV), and the accumulated intermediates of MT, HT, or carbonate were also observed by FT-IR around 1363 cm-1 on the used Mg2Al-Cl-LDH, which are well in accordance with the theoretical prediction. The demonstrated participation of intercalated chlorine anions in the evolution of intermediates and transient states as Brønsted base sites during COS hydrolysis will give new insight into the basic sites in LDH materials.
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Affiliation(s)
- Changming Li
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Shuying Zhao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Xiaolong Yao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Li He
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Simin Xu
- College of Chemistry, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Xianbao Shen
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
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45
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Wu B, Xuan K, Shen X, Zhao Q, Shi Y, Kong L, Hu J, Li X, Zhang H, Cao X, Hao X, Zhou Q, Yao Z. Non-negligible emissions of black carbon from non-road construction equipment based on real-world measurements in China. Sci Total Environ 2022; 806:151300. [PMID: 34736751 DOI: 10.1016/j.scitotenv.2021.151300] [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: 09/19/2021] [Revised: 10/23/2021] [Accepted: 10/24/2021] [Indexed: 06/13/2023]
Abstract
Non-road construction equipment (NRCE) has become a vital contributor to urban air pollutants with the rapid urbanization in China. Black carbon (BC), as a key pollutant emitted from NRCE (mainly diesel-fueled), has attracted considerable concerns due to adverse impacts on climate change, visibility, and human health. However, the understanding of its emissions is still unclear based on limited research results. In this study, we conducted real-world measurements on BC emissions from 12 excavators and 9 loaders to characterize the variation and quantify fuel-based emission factors (EFs) by using a synchronous platform based on PEMS (SP-PEMS). We analyzed the impacts of key factors (operation mode, emission standard, and engine rated power) on BC emission comprehensively. High BC emission in working mode may be mainly owing to the increase of fuel consumption and the deterioration of air-fuel ratio. With more stringent emission standards, BC EFs of all tested NRCE present significant decreasing trends. Interestingly, NRCE with high rated power generally exhibits lower BC emissions. Through comparison, we find BC EFs in this study are generally higher than elemental carbon (EC) EFs reported in previous studies, which will lead BC emissions from NRCE to be underestimated while EC EFs are used instead of BC EFs. Furthermore, BC EFs of NRCE with Stage III are significantly higher (1-3 orders of magnitude) than those of on-road diesel trucks with the current mainstream emission standards of China IV and China V, which reinforces the urgency and importance of controlling BC emissions from NRCE in China. Finally, we recommend BC EFs of excavators and loaders under different emission standards and operation modes, and which preliminarily fills the gap in localized BC EFs of typical NRCE to relieve the urgent needs for emission inventory calculation.
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Affiliation(s)
- Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Kaijie Xuan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Qiangqiang Zhao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Yue Shi
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Lei Kong
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Jinfeng Hu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China.
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46
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Jiang S, Wang F, Cao X, Slater B, Wang R, Sun H, Wang H, Shen X, Yao Z. Novel application of ion exchange membranes for preparing effective silver and copper based antibacterial membranes. Chemosphere 2022; 287:132131. [PMID: 34492413 DOI: 10.1016/j.chemosphere.2021.132131] [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: 07/27/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 06/13/2023]
Abstract
Ion exchange membranes (IEMs) are widely used in water treatment applications such as electrodialysis. However, the exploration of IEMs as effective antibacterial food contact materials (e.g., food packaging membranes) against pathogenic bacteria to ensure food safety has not been reported. Here, we report a simple but effective method to prepare high performance antibacterial membranes via ion exchange coupled with in-situ reduction. The general membrane properties are characterized using SEM, EDS, FTIR, XPS, XRD, DSC, TGA, water uptake, etc. The distribution of silver and copper in the membranes are generally in line with the distribution of sulfur, indicating that the antibacterial ions are introduced into the membranes via ion exchange and are bonded with the sulfonate groups in the membranes. The antibacterial performance is investigated using zone of inhibition tests and continuous bacteria growth inhibition tests. All of the prepared membranes show obvious antibacterial activities compared to the bare cation exchange membranes. The diameters of inhibition zone against Staphylococcus aureus (S. aureus) are all larger than those of Escherichia coli (E. coli), indicating that the prepared membranes are more efficient in inhibiting S. aureus compared to E. coli. Furthermore, the silver-based membrane shows more sustainable antibacterial activities compared to the copper-based membrane. Especially, the results clearly reveal that the silver-based membrane is capable of killing bacteria instead of just inhibiting the growth of bacteria. We have shown for the first time that membranes derived from IEMs have the potential as food contact materials to inhibit the growth of pathogenic bacteria so as to eliminate the risk of bacterial infections and meanwhile delay food spoilage due to bacteria growth.
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Affiliation(s)
- Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Ben Slater
- Institute of Porous Materials, Ecole Normale Supérieure, 24 Rue Lhomond, 75005, Paris, France
| | - Rongrong Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Haishu Sun
- Department of Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Huijiao Wang
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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47
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Shen X, Lv T, Zhang X, Cao X, Li X, Wu B, Yao X, Shi Y, Zhou Q, Chen X, Yao Z. Real-world emission characteristics of black carbon emitted by on-road China IV and China V diesel trucks. Sci Total Environ 2021; 799:149435. [PMID: 34365271 DOI: 10.1016/j.scitotenv.2021.149435] [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] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/20/2021] [Accepted: 07/30/2021] [Indexed: 06/13/2023]
Abstract
Diesel vehicle is an important source of black carbon (BC). A portable emission measurement system including a photo-acoustic extinctiometer and SEMTECH-LDV was used to measure the real-world emissions of 14 light-duty and heavy-duty diesel trucks (LDDTs and HDDTs, meeting the China IV and China V standards) in Beijing. BC emission factors and the BC/PM2.5 ratio were obtained, and the effects of the vehicle type, emission standard and driving cycle on emissions were analyzed. The tightening of emission standards and the advancement of vehicle technology have reduced BC emissions from the China II standard to the China V standard. The emission reductions of BC are lower than those of other components of PM2.5 from the China II standard to the China IV standard but higher from the China IV standard to the China V standard. The BC and PM2.5 had the same main sources for the HDDTs and China IV LDDTs but had different sources for the China V LDDTs having diesel particulate filters. The BC/PM2.5 ratios of LDDTs, and HDDTs decreased from the China IV standard to the China V standard by 97.2% and 38.2%, respectively. The BC/PM2.5 ratio for China V LDDTs was 10 to 20 times lower than that for other diesel vehicles. The BC emissions tested under the highway driving cycle were 39.4% ± 16.7% lower than those under the no-highway driving cycle, but the BC/PM2.5 ratios had the opposite tendency. More China V and China VI heavy-duty diesel vehicles equipped with diesel particulate filters need to be tested to obtain more accurate BC/PM2.5 data and to improve the readiness of emission inventory calculations. The findings of this study help clarify the BC emission characteristics of diesel vehicles on actual roads and provide scientific basis for the formulation of emission control strategies for diesel vehicles in China.
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Affiliation(s)
- Xianbao Shen
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Tiantian Lv
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China.
| | - Bobo Wu
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xiaolong Yao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Yue Shi
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Qi Zhou
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xi Chen
- Beijing North Vehicle Group Corporation, Beijing 100072, China
| | - Zhiliang Yao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China.
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48
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Satzinger KJ, Liu YJ, Smith A, Knapp C, Newman M, Jones C, Chen Z, Quintana C, Mi X, Dunsworth A, Gidney C, Aleiner I, Arute F, Arya K, Atalaya J, Babbush R, Bardin JC, Barends R, Basso J, Bengtsson A, Bilmes A, Broughton M, Buckley BB, Buell DA, Burkett B, Bushnell N, Chiaro B, Collins R, Courtney W, Demura S, Derk AR, Eppens D, Erickson C, Faoro L, Farhi E, Fowler AG, Foxen B, Giustina M, Greene A, Gross JA, Harrigan MP, Harrington SD, Hilton J, Hong S, Huang T, Huggins WJ, Ioffe LB, Isakov SV, Jeffrey E, Jiang Z, Kafri D, Kechedzhi K, Khattar T, Kim S, Klimov PV, Korotkov AN, Kostritsa F, Landhuis D, Laptev P, Locharla A, Lucero E, Martin O, McClean JR, McEwen M, Miao KC, Mohseni M, Montazeri S, Mruczkiewicz W, Mutus J, Naaman O, Neeley M, Neill C, Niu MY, O'Brien TE, Opremcak A, Pató B, Petukhov A, Rubin NC, Sank D, Shvarts V, Strain D, Szalay M, Villalonga B, White TC, Yao Z, Yeh P, Yoo J, Zalcman A, Neven H, Boixo S, Megrant A, Chen Y, Kelly J, Smelyanskiy V, Kitaev A, Knap M, Pollmann F, Roushan P. Realizing topologically ordered states on a quantum processor. Science 2021; 374:1237-1241. [PMID: 34855491 DOI: 10.1126/science.abi8378] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
[Figure: see text].
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Affiliation(s)
| | - Y-J Liu
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, 80799 München, Germany
| | - A Smith
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, UK.,Centre for the Mathematics and Theoretical Physics of Quantum Non-Equilibrium Systems, University of Nottingham, Nottingham NG7 2RD, UK
| | - C Knapp
- Department of Physics and Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA.,Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, USA
| | - M Newman
- Google Quantum AI, Mountain View, CA, USA
| | - C Jones
- Google Quantum AI, Mountain View, CA, USA
| | - Z Chen
- Google Quantum AI, Mountain View, CA, USA
| | - C Quintana
- Google Quantum AI, Mountain View, CA, USA
| | - X Mi
- Google Quantum AI, Mountain View, CA, USA
| | | | - C Gidney
- Google Quantum AI, Mountain View, CA, USA
| | - I Aleiner
- Google Quantum AI, Mountain View, CA, USA
| | - F Arute
- Google Quantum AI, Mountain View, CA, USA
| | - K Arya
- Google Quantum AI, Mountain View, CA, USA
| | - J Atalaya
- Google Quantum AI, Mountain View, CA, USA
| | - R Babbush
- Google Quantum AI, Mountain View, CA, USA
| | - J C Bardin
- Google Quantum AI, Mountain View, CA, USA.,Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - R Barends
- Google Quantum AI, Mountain View, CA, USA
| | - J Basso
- Google Quantum AI, Mountain View, CA, USA
| | | | - A Bilmes
- Google Quantum AI, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Quantum AI, Mountain View, CA, USA
| | - B Burkett
- Google Quantum AI, Mountain View, CA, USA
| | - N Bushnell
- Google Quantum AI, Mountain View, CA, USA
| | - B Chiaro
- Google Quantum AI, Mountain View, CA, USA
| | - R Collins
- Google Quantum AI, Mountain View, CA, USA
| | - W Courtney
- Google Quantum AI, Mountain View, CA, USA
| | - S Demura
- Google Quantum AI, Mountain View, CA, USA
| | - A R Derk
- Google Quantum AI, Mountain View, CA, USA
| | - D Eppens
- Google Quantum AI, Mountain View, CA, USA
| | - C Erickson
- Google Quantum AI, Mountain View, CA, USA
| | - L Faoro
- Laboratoire de Physique Theorique et Hautes Energies, Sorbonne Université, 75005 Paris, France
| | - E Farhi
- Google Quantum AI, Mountain View, CA, USA
| | - A G Fowler
- Google Quantum AI, Mountain View, CA, USA
| | - B Foxen
- Google Quantum AI, Mountain View, CA, USA
| | - M Giustina
- Google Quantum AI, Mountain View, CA, USA
| | - A Greene
- Google Quantum AI, Mountain View, CA, USA.,Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - J A Gross
- Google Quantum AI, Mountain View, CA, USA
| | | | | | - J Hilton
- Google Quantum AI, Mountain View, CA, USA
| | - S Hong
- Google Quantum AI, Mountain View, CA, USA
| | - T Huang
- Google Quantum AI, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Quantum AI, Mountain View, CA, USA
| | - S V Isakov
- Google Quantum AI, Mountain View, CA, USA
| | - E Jeffrey
- Google Quantum AI, Mountain View, CA, USA
| | - Z Jiang
- Google Quantum AI, Mountain View, CA, USA
| | - D Kafri
- Google Quantum AI, Mountain View, CA, USA
| | | | - T Khattar
- Google Quantum AI, Mountain View, CA, USA
| | - S Kim
- Google Quantum AI, Mountain View, CA, USA
| | - P V Klimov
- Google Quantum AI, Mountain View, CA, USA
| | - A N Korotkov
- Google Quantum AI, Mountain View, CA, USA.,Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | - D Landhuis
- Google Quantum AI, Mountain View, CA, USA
| | - P Laptev
- Google Quantum AI, Mountain View, CA, USA
| | - A Locharla
- Google Quantum AI, Mountain View, CA, USA
| | - E Lucero
- Google Quantum AI, Mountain View, CA, USA
| | - O Martin
- Google Quantum AI, Mountain View, CA, USA
| | | | - M McEwen
- Google Quantum AI, Mountain View, CA, USA.,Department of Physics, University of California, Santa Barbara, CA, USA
| | - K C Miao
- Google Quantum AI, Mountain View, CA, USA
| | - M Mohseni
- Google Quantum AI, Mountain View, CA, USA
| | | | | | - J Mutus
- Google Quantum AI, Mountain View, CA, USA
| | - O Naaman
- Google Quantum AI, Mountain View, CA, USA
| | - M Neeley
- Google Quantum AI, Mountain View, CA, USA
| | - C Neill
- Google Quantum AI, Mountain View, CA, USA
| | - M Y Niu
- Google Quantum AI, Mountain View, CA, USA
| | | | - A Opremcak
- Google Quantum AI, Mountain View, CA, USA
| | - B Pató
- Google Quantum AI, Mountain View, CA, USA
| | - A Petukhov
- Google Quantum AI, Mountain View, CA, USA
| | - N C Rubin
- Google Quantum AI, Mountain View, CA, USA
| | - D Sank
- Google Quantum AI, Mountain View, CA, USA
| | - V Shvarts
- Google Quantum AI, Mountain View, CA, USA
| | - D Strain
- Google Quantum AI, Mountain View, CA, USA
| | - M Szalay
- Google Quantum AI, Mountain View, CA, USA
| | | | - T C White
- Google Quantum AI, Mountain View, CA, USA
| | - Z Yao
- Google Quantum AI, Mountain View, CA, USA
| | - P Yeh
- Google Quantum AI, Mountain View, CA, USA
| | - J Yoo
- Google Quantum AI, Mountain View, CA, USA
| | - A Zalcman
- Google Quantum AI, Mountain View, CA, USA
| | - H Neven
- Google Quantum AI, Mountain View, CA, USA
| | - S Boixo
- Google Quantum AI, Mountain View, CA, USA
| | - A Megrant
- Google Quantum AI, Mountain View, CA, USA
| | - Y Chen
- Google Quantum AI, Mountain View, CA, USA
| | - J Kelly
- Google Quantum AI, Mountain View, CA, USA
| | | | - A Kitaev
- Google Quantum AI, Mountain View, CA, USA.,Department of Physics and Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA.,Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, USA
| | - M Knap
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, 80799 München, Germany.,Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany
| | - F Pollmann
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, 80799 München, Germany
| | - P Roushan
- Google Quantum AI, Mountain View, CA, USA
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49
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Chen X, Li J, Yang Y, Yao Z, Tu Z, Liao S, Zhu Q, Li P. Suprafascial plane endoscopy versus open carpal tunnel release for idiopathic carpal tunnel syndrome: Use of the Accordion Severity Grading System. Hand Surg Rehabil 2021; 41:113-118. [PMID: 34774842 DOI: 10.1016/j.hansur.2021.11.002] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 07/03/2021] [Accepted: 11/04/2021] [Indexed: 12/31/2022]
Abstract
This study aimed to assess the safety and effectiveness of modified endoscopic technique with a single portal from an external carpal tunnel approach for surgical operations in a suprafascial plane superficial to the transverse carpal ligament. Reversible nerve injury risk is threefold greater with a conventional endoscopic method than with open carpal tunnel release (OCTR), and this suprafascial plane endoscopic release (SPER) should circumvent the problem of hardware in the carpal tunnel encountered with the conventional endoscopic method and liable to cause iatrogenic damage to the median nerve. However, the surgical consequences of the new technique have not been studied. To fill this gap, a retrospective therapeutic study was conducted to compare negative outcomes versus open surgery. The Accordion Severity Grading System was used to grade complications from 0 to 3 according to necessity of treatment. Sequela and failure rates were also compared between the SPER and OCTR groups. Eighty-eight cases in 72 patients with idiopathic carpal tunnel syndrome (ICTS) met the inclusion criteria. SPER was performed in 28 hands in 27 patients, and OCTR in 60 hands in 49 patients. The results showed no significant difference in complication, sequela, or failure rates between groups (p > 0.05). Suprafascial plane endoscopic release, has certain advantages over the open method and was validated as a safe and effective method of treating ICTS.
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Affiliation(s)
- X Chen
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China; Guangdong Provincial Key Laboratory of Orthopedics and Traumatology, Orthopaedic Research Institute, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China
| | - J Li
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China
| | - Y Yang
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China
| | - Z Yao
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China
| | - Z Tu
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China
| | - S Liao
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China
| | - Q Zhu
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China; Guangdong Provincial Key Laboratory of Orthopedics and Traumatology, Orthopaedic Research Institute, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China.
| | - P Li
- Department of Microsurgery, Orthopedic Trauma and Hand Surgery, First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou, China.
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50
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Jiang S, Sun H, Wang H, Ladewig BP, Yao Z. A comprehensive review on the synthesis and applications of ion exchange membranes. Chemosphere 2021; 282:130817. [PMID: 34091294 DOI: 10.1016/j.chemosphere.2021.130817] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [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: 03/18/2021] [Revised: 05/01/2021] [Accepted: 05/05/2021] [Indexed: 06/12/2023]
Abstract
Ion exchange membranes (IEMs) are undergoing prosperous development in recent years. More than 30,000 papers which are indexed by Science Citation Index Expanded (SCIE) have been published on IEMs during the past twenty years (2001-2020). Especially, more than 3000 papers are published in the year of 2020, revealing researchers' great interest in this area. This paper firstly reviews the different types (e.g., cation exchange membrane, anion exchange membrane, proton exchange membrane, bipolar membrane) and electrochemical properties (e.g., permselectivity, electrical resistance/ionic conductivity) of IEMs and the corresponding working principles, followed by membrane synthesis methods, including the common solution casting method. Especially, as a promising future direction, green synthesis is critically discussed. IEMs are extensively applied in various applications, which can be generalized into two big categories, where the water-based category mainly includes electrodialysis, diffusion dialysis and membrane capacitive deionization, while the energy-based category mainly includes reverse electrodialysis, fuel cells, redox flow battery and electrolysis for hydrogen production. These applications are comprehensively discussed in this paper. This review may open new possibilities for the future development of IEMs.
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Affiliation(s)
- Shanxue Jiang
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China; Barrer Centre, Department of Chemical Engineering, Imperial College London, Exhibition Road, London, SW7 2AZ, United Kingdom
| | - Haishu Sun
- Department of Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Huijiao Wang
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Bradley P Ladewig
- Barrer Centre, Department of Chemical Engineering, Imperial College London, Exhibition Road, London, SW7 2AZ, United Kingdom; Institute for Micro Process Engineering (IMVT), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Zhiliang Yao
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China; Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
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