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Bakhchin D, Ravi R, Douadi O, Faqir M, Essadiqi E. Integrated catalytic systems for simultaneous NOx and PM reduction: a comprehensive evaluation of synergistic performance and combustion waste energy utilization. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:46840-46857. [PMID: 38980481 DOI: 10.1007/s11356-024-34287-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 07/03/2024] [Indexed: 07/10/2024]
Abstract
The global transition towards sustainable automotive vehicles has driven the demand for energy-efficient internal combustion engines with advanced aftertreatment systems capable of reducing nitrogen oxides (NOx) and particulate matter (PM) emissions. This comprehensive review explores the latest advancements in aftertreatment technologies, focusing on the synergistic integration of in-cylinder combustion strategies, such as low-temperature combustion (LTC), with post-combustion purification systems. Selective catalytic reduction (SCR), lean NOx traps (LNT), and diesel particulate filters (DPF) are critically examined, highlighting novel catalyst formulations and system configurations that enhance low-temperature performance and durability. The review also investigates the potential of energy conversion and recovery techniques, including thermoelectric generators and organic Rankine cycles, to harness waste heat from the exhaust and improve overall system efficiency. By analyzing the complex interactions between engine operating parameters, combustion kinetics, and emission formation, this study provides valuable insights into the optimization of integrated LTC-aftertreatment systems. Furthermore, the review emphasizes the importance of considering real-world driving conditions and transient operation in the development and evaluation of these technologies. The findings presented in this article lay the foundation for future research efforts aimed at overcoming the limitations of current aftertreatment systems and achieving superior emission reduction performance in advanced combustion engines, ultimately contributing to the development of sustainable and efficient automotive technologies.
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Affiliation(s)
- Dikra Bakhchin
- School of Aerospace and Automotive Engineering, LERMA Laboratory, International University of Rabat, 11000, Rabat, Morocco
| | - Rajesh Ravi
- School of Aerospace and Automotive Engineering, LERMA Laboratory, International University of Rabat, 11000, Rabat, Morocco.
| | - Oumaima Douadi
- School of Aerospace and Automotive Engineering, LERMA Laboratory, International University of Rabat, 11000, Rabat, Morocco
| | - Mustapha Faqir
- School of Aerospace and Automotive Engineering, LERMA Laboratory, International University of Rabat, 11000, Rabat, Morocco
| | - Elhachmi Essadiqi
- School of Aerospace and Automotive Engineering, LERMA Laboratory, International University of Rabat, 11000, Rabat, Morocco
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Xu Y, Wang Z, Pei C, Wu C, Huang B, Cheng C, Zhou Z, Li M. Single particle mass spectral signatures from on-road and non-road vehicle exhaust particles and their application in refined source apportionment using deep learning. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 930:172822. [PMID: 38688364 DOI: 10.1016/j.scitotenv.2024.172822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 05/02/2024]
Abstract
With advances in vehicle emission control technology, updating source profiles to meet the current requirements of source apportionment has become increasingly crucial. In this study, on-road and non-road vehicle particles were collected, and then the chemical compositions of individual particles were analyzed using single particle aerosol mass spectrometry. The data were grouped using an adaptive resonance theory neural network to identify signatures and establish a mass spectral database of mobile sources. In addition, a deep learning-based model (DeepAerosolClassifier) for classifying aerosol particles was established. The objective of this model was to accomplish source apportionment. During the training process, the model achieved an accuracy of 98.49 % for the validation set and an accuracy of 93.36 % for the testing set. Regarding the model interpretation, ideal spectra were generated using the model, verifying its accurate recognition of the characteristic patterns in the mass spectra. In a practical application, the model performed hourly source apportionment at three specific field monitoring sites. The effectiveness of the model in field measurement was validated by combining traffic flow and spatial information with the model results. Compared with other machine learning methods, our model achieved highly automated source apportionment while eliminating the need for feature selection, and it enables end-to-end operation. Thus, in the future, it can be applied in refined and online source apportionment of particulate matter.
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Affiliation(s)
- Yongjiang Xu
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-, Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Zaihua Wang
- Institute of Resources Utilization and Rare Earth Development, Guangdong Academy of Sciences, Guangzhou 510650, Guangdong, China
| | - Chenglei Pei
- Guangzhou Ecological and Environmental Monitoring Center of Guangdong Province, Guangzhou 510030, China
| | - Cheng Wu
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-, Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Bo Huang
- Guangzhou Hexin Instrument Co., Ltd., Guangzhou 510530, Guangdong, China
| | - Chunlei Cheng
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-, Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Zhen Zhou
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-, Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Mei Li
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-, Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China.
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Warthon J, Alvarez M, Olarte A, Quispe Y, Jalixto V, Valencia N, Mio-Diaz M, Zamalloa A, Warthon B. Reduction of the concentration of particulate material at a sampling point in Cusco city at the beginning of the pandemic. Sci Rep 2024; 14:849. [PMID: 38191800 PMCID: PMC10774446 DOI: 10.1038/s41598-023-50955-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 12/28/2023] [Indexed: 01/10/2024] Open
Abstract
The pandemic produced by SARS-CoV-2 generated various impacts on public health, the environment and other anthropogenic activities. The purpose of this study was to evaluate the reduction of air pollution due to [Formula: see text] and [Formula: see text] particulate matter in Cusco city at the beginning of the pandemic. Social confinement in Peru began on March 16, 2020, until the end of June. These health measures caused strict isolation that resulted in a significant decrease in vehicle flow on the streets and avenues of the city of Cusco. In the first days of May, even during the time of confinement, we managed to measure air quality at a sampling point located on the campus of the Universidad Nacional de San Antonio Abad de Cusco; a reduction in air pollution due to particulate matter was observed. The evaluation was carried out using an high-volume (HiVol) 3000 particulate matter sampler and the mass of particulate matter adhered to the filters was determined by gravimetry. The concentrations of particulate matter [Formula: see text] and [Formula: see text] obtained pre-pandemic were compared with those recorded at the beginning of the pandemic. The results revealed a significant average reduction in the concentration of [Formula: see text] and [Formula: see text], reaching - 57.43% and - 59.52%, respectively, compared to pre-pandemic values. At the same time, its relationship with meteorological parameters and Google mobility data was evaluated and it was concluded that these parameters did not significantly affect the reduction of particulate matter. This study reveals the positive effects of the pandemic in reducing air pollution and the confinement measures had as a secondary effect on the decrease in air pollution in Cusco City.
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Affiliation(s)
- Julio Warthon
- Departamento Académico de Física, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru.
| | - Modesta Alvarez
- Departamento Académico de Biología, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Amanda Olarte
- Departamento Académico de Química, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Yanett Quispe
- Departamento Académico de Física, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Victor Jalixto
- Departamento Académico de Física, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Nazaria Valencia
- Departamento Académico de Química, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Mirian Mio-Diaz
- Departamento Académico de Biología, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Ariatna Zamalloa
- Departamento Académico de Física, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru
| | - Bruce Warthon
- Departamento Académico de Física, Universidad Nacional de San Antonio Abad del Cusco, Av. De La Cultura 733, Cusco, 08003, Peru.
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Murphy BN, Sonntag D, Seltzer KM, Pye HOT, Allen C, Murray E, Toro C, Gentner DR, Huang C, Jathar S, Li L, May AA, Robinson AL. Reactive organic carbon air emissions from mobile sources in the United States. ATMOSPHERIC CHEMISTRY AND PHYSICS 2023; 23:13469-13483. [PMID: 38516559 PMCID: PMC10953806 DOI: 10.5194/acp-23-13469-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Mobile sources are responsible for a substantial controllable portion of the reactive organic carbon (ROC) emitted to the atmosphere, especially in urban environments of the United States. We update existing methods for calculating mobile source organic particle and vapor emissions in the United States with over a decade of laboratory data that parameterize the volatility and organic aerosol (OA) potential of emissions from on-road vehicles, nonroad engines, aircraft, marine vessels, and locomotives. We find that existing emission factor information from Teflon filters combined with quartz filters collapses into simple relationships and can be used to reconstruct the complete volatility distribution of ROC emissions. This new approach consists of source-specific filter artifact corrections and state-of-the-science speciation including explicit intermediate-volatility organic compounds (IVOCs), yielding the first bottom-up volatility-resolved inventory of US mobile source emissions. Using the Community Multiscale Air Quality model, we estimate mobile sources account for 20 %-25 % of the IVOC concentrations and 4.4 %-21.4 % of ambient OA. The updated emissions and air quality model reduce biases in predicting fine-particle organic carbon in winter, spring, and autumn throughout the United States (4.3 %-11.3 % reduction in normalized bias). We identify key uncertain parameters that align with current state-of-the-art research measurement challenges.
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Affiliation(s)
- Benjamin N. Murphy
- Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, United States
| | - Darrell Sonntag
- Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, United States
| | - Karl M. Seltzer
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, United States
| | - Havala O. T. Pye
- Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, United States
| | - Christine Allen
- General Dynamics Information Technology, 79 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States
| | - Evan Murray
- Office of Transportation and Air Quality, U.S. Environmental Protection Agency, Ann Arbor, MI 48105, United States
| | - Claudia Toro
- Office of Transportation and Air Quality, U.S. Environmental Protection Agency, Ann Arbor, MI 48105, United States
| | - Drew R. Gentner
- Department of Chemical and Environmental Engineering, Yale University, New Haven, CT 06511, United States
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Cause and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
| | - Shantanu Jathar
- Department of Mechanical Engineering, Colorado State University, Fort Collins, CO 80523, United States
| | - Li Li
- Department of Chemical and Environmental Engineering, Yale University, New Haven, CT 06511, United States
| | - Andrew A. May
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH 43210, United States
| | - Allen L. Robinson
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA15213, United States
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Beauchamp M, Bessagnet B. An iterative optimization scheme to accommodate inequality constraints in air quality geostatistical estimation of multivariate PM. Heliyon 2023; 9:e17413. [PMID: 37408884 PMCID: PMC10318523 DOI: 10.1016/j.heliyon.2023.e17413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 06/14/2023] [Accepted: 06/15/2023] [Indexed: 07/07/2023] Open
Abstract
The kriging-based estimation of the different types of atmospheric particulate matter (PM) pollutions defined in the air quality regulation raises some operational problems because the (co)kriging equations are obtained by minimizing a linear combination of the estimation variances subject to unbiasedness constraints. As a consequence, the estimation process can result in total PM10 concentrations that are less than the PM2.5 concentrations which would be physically impossible. In a previous publication, it was shown that a convenient external drift modeling can reduce the number of spatial locations where the inequality constraint is not satisfied, without completely solving the problem. In this work, the formulation of the cokriging system is modified, inspired by previous works focusing on positive kriging. The introduction of additional constraints on the cokriging weights are presented, leading to a unique and optimal solution to the problem of cokriging under inequality constraints between two variables. Some computational and algorithmic details are introduced. An evaluation of the penalized cokriging is provided by using the European PM monitoring sites dataset: some maps and performance scores are given to assess the relevance of our iterative optimization scheme.
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Affiliation(s)
- Maxime Beauchamp
- IMT Atlantique Bretagne-Pays de la Loire, Campus de Brest Technopôle, Brest-Iroise CS 83818, 29238, Brest cedex 03, France
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Patel H, Talbot N, Dirks K, Salmond J. The impact of low emission zones on personal exposure to ultrafine particles in the commuter environment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162540. [PMID: 36870513 DOI: 10.1016/j.scitotenv.2023.162540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/06/2023] [Accepted: 02/25/2023] [Indexed: 06/18/2023]
Abstract
Auckland is a city with limited industrial activity, road traffic being the dominant source of air pollution. Thus, the time periods when social contact and movement in Auckland were severely curtailed due to COVID-19 restrictions presented a unique opportunity to observe impacts on pedestrian exposure to air pollution under a range of different traffic flow scenarios, providing insights into the impacts of potential future traffic calming measures. Pedestrian exposure to ultrafine particles (UFPs), was measured using personal monitoring along a customised route through Central Auckland during different COVID-19-affected traffic flow conditions. Results showed that reduced traffic flows led to statistically significant reductions in average exposure to UFP under all traffic reduction scenarios (TRS). However, the size of the reduction was variable in both time and place. Under the most stringent TRS (traffic reduction of 82 %), median ultrafine particle (UFP) concentrations reduced by 73 %. Under the less stringent scenario, the extent of reduction varied in time and space; a traffic reduction of 62 % resulted in a 23 % reduction in median UFP concentrations in 2020 but in 2021 similar traffic reductions led to a decrease in median UFP concentrations of 71 %. Under all scenarios, the magnitude of the impact of traffic reductions on UFP exposure varied along the route, with areas dominated by emissions from construction and ferry/port activities showing little correlation between traffic flow and exposure. Shared traffic spaces, previously pedestrianised, also recorded consistently high concentrations with little variability observed. This study provided a unique opportunity to assess the potential benefits and risks of such zones and to help decision-makers evaluate future traffic management interventions (such as low emissions zones). The results suggest that controlled traffic flow interventions can result in a significant reduction in pedestrian exposure to UFPs, but that the magnitude of reductions is sensitive to local-scale variations in meteorology, urban land use and traffic flow patterns.
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Affiliation(s)
- Hamesh Patel
- School of Environment, Faculty of Science, University of Auckland, Private Bag 92019, Auckland, New Zealand; Mote Ltd, 40a George Street, Mount Eden, Auckland, New Zealand.
| | - Nick Talbot
- School of Environment, Faculty of Science, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Kim Dirks
- Department of Civil and Environmental Engineering, Faculty of Engineering, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Jennifer Salmond
- School of Environment, Faculty of Science, University of Auckland, Private Bag 92019, Auckland, New Zealand
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Calderón-Garcidueñas L, Torres-Jardón R, Greenough GP, Kulesza R, González-Maciel A, Reynoso-Robles R, García-Alonso G, Chávez-Franco DA, García-Rojas E, Brito-Aguilar R, Silva-Pereyra HG, Ayala A, Stommel EW, Mukherjee PS. Sleep matters: Neurodegeneration spectrum heterogeneity, combustion and friction ultrafine particles, industrial nanoparticle pollution, and sleep disorders-Denial is not an option. Front Neurol 2023; 14:1117695. [PMID: 36923490 PMCID: PMC10010440 DOI: 10.3389/fneur.2023.1117695] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 02/01/2023] [Indexed: 03/02/2023] Open
Abstract
Sustained exposures to ubiquitous outdoor/indoor fine particulate matter (PM2.5), including combustion and friction ultrafine PM (UFPM) and industrial nanoparticles (NPs) starting in utero, are linked to early pediatric and young adulthood aberrant neural protein accumulation, including hyperphosphorylated tau (p-tau), beta-amyloid (Aβ1 - 42), α-synuclein (α syn) and TAR DNA-binding protein 43 (TDP-43), hallmarks of Alzheimer's (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS). UFPM from anthropogenic and natural sources and NPs enter the brain through the nasal/olfactory pathway, lung, gastrointestinal (GI) tract, skin, and placental barriers. On a global scale, the most important sources of outdoor UFPM are motor traffic emissions. This study focuses on the neuropathology heterogeneity and overlap of AD, PD, FTLD, and ALS in older adults, their similarities with the neuropathology of young, highly exposed urbanites, and their strong link with sleep disorders. Critical information includes how this UFPM and NPs cross all biological barriers, interact with brain soluble proteins and key organelles, and result in the oxidative, endoplasmic reticulum, and mitochondrial stress, neuroinflammation, DNA damage, protein aggregation and misfolding, and faulty complex protein quality control. The brain toxicity of UFPM and NPs makes them powerful candidates for early development and progression of fatal common neurodegenerative diseases, all having sleep disturbances. A detailed residential history, proximity to high-traffic roads, occupational histories, exposures to high-emission sources (i.e., factories, burning pits, forest fires, and airports), indoor PM sources (tobacco, wood burning in winter, cooking fumes, and microplastics in house dust), and consumption of industrial NPs, along with neurocognitive and neuropsychiatric histories, are critical. Environmental pollution is a ubiquitous, early, and cumulative risk factor for neurodegeneration and sleep disorders. Prevention of deadly neurological diseases associated with air pollution should be a public health priority.
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Affiliation(s)
- Lilian Calderón-Garcidueñas
- College of Health, The University of Montana, Missoula, MT, United States.,Universidad del Valle de México, Mexico City, Mexico
| | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Glen P Greenough
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Randy Kulesza
- Department of Anatomy, Lake Erie College of Osteopathic Medicine, Erie, PA, United States
| | | | | | | | | | | | | | - Héctor G Silva-Pereyra
- Instituto Potosino de Investigación Científica y Tecnológica A.C., San Luis Potosi, Mexico
| | - Alberto Ayala
- Sacramento Metropolitan Air Quality Management District, Sacramento, CA, United States.,Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, United States
| | - Elijah W Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Partha S Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata, India
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Zhou X, Yan Z, Zhou X, Wang C, Liu H, Zhou H. RETRACTED: An assessment of volatile organic compounds pollutant emissions from wood materials: A review. CHEMOSPHERE 2022; 308:136460. [PMID: 36116618 DOI: 10.1016/j.chemosphere.2022.136460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 08/29/2022] [Accepted: 09/11/2022] [Indexed: 06/15/2023]
Affiliation(s)
- Xihe Zhou
- Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, Jiangsu, 210037, China
| | - Zhisong Yan
- Zhejiang Shiyou Timber Co., Ltd., 1111 Shiyuan West Road, Huzhou, Zhejiang, 313009, China
| | - Xiang Zhou
- Sinomaple Furnishing (Jiangsu) Co., Ltd., 99 Fen'an Dong Lu, Wujiang District, Suzhou, Jiangsu, 215200, China
| | - Chengming Wang
- Holtrop & Jansma (Qingdao) Environmental Protection Equipment Co., Ltd., 8 Tongshun Road, High-tech District, Qingdao, Shandong, 266114, China
| | - Hailiang Liu
- Jiangsu Shenmao Plastic Products Co., Ltd., Wood Industrial District, Siyang, Jiangsu, 223798, China
| | - Handong Zhou
- Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, Jiangsu, 210037, China.
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