1
|
Zhang Y, Du J, Shan Y, Wang F, Liu J, Wang M, Liu Z, Yan Y, Xu G, He G, Shi X, Lian Z, Yu Y, Shan W, He H. Toward synergetic reduction of pollutant and greenhouse gas emissions from vehicles: a catalysis perspective. Chem Soc Rev 2025; 54:1151-1215. [PMID: 39687940 DOI: 10.1039/d4cs00140k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2024]
Abstract
It is a great challenge for vehicles to satisfy the increasingly stringent emission regulations for pollutants and greenhouse gases. Throughout the history of the development of vehicle emission control technology, catalysts have always been in the core position of vehicle aftertreatment. Aiming to address the significant demand for synergistic control of pollutants and greenhouse gases from vehicles, this review provides a panoramic view of emission control technologies and key aftertreatment catalysts for vehicles using fossil fuels (gasoline, diesel, and natural gas) and carbon-neutral fuels (hydrogen, ammonia, and green alcohols). Special attention will be given to the research advancements in catalysts, including three-way catalysts (TWCs), NOx selective catalytic reduction (SCR) catalysts, NOx storage-reduction (NSR) catalysts, diesel oxidation catalysts (DOCs), soot oxidation catalysts, ammonia slip catalysts (ASCs), methane oxidation catalysts (MOCs), N2O abatement catalysts (DeN2O), passive NOx adsorbers (PNAs), and cold start catalysts (CSCs). The main challenges for industrial applications of these catalysts, such as insufficient low-temperature activity, product selectivity, hydrothermal stability, and poisoning resistance, will be examined. In addition, the future development of synergistic control of vehicle pollutants and greenhouse gases will be discussed from a catalysis perspective.
Collapse
Affiliation(s)
- Yan Zhang
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Ningbo, 315800, China.
| | - Jinpeng Du
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Yulong Shan
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Fei Wang
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China
| | - Jingjing Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Meng Wang
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Ningbo, 315800, China.
| | - Zhi Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Yong Yan
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou 341000, China
| | - Guangyan Xu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Guangzhi He
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Xiaoyan Shi
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Zhihua Lian
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Yunbo Yu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou 341000, China
| | - Wenpo Shan
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Ningbo, 315800, China.
| | - Hong He
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| |
Collapse
|
2
|
Zhang B, Li X, Zuo Q, Yin Z, Zhang J, Chen W, Lu C, Tan D. Effects analysis on hydrocarbon light-off performance of a catalytic gasoline particulate filter during cold start. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:76890-76906. [PMID: 35670934 DOI: 10.1007/s11356-022-20519-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 04/25/2022] [Indexed: 06/15/2023]
Abstract
In order to study the hydrocarbon combustion in the low-temperature catalytic process of a catalytic gasoline particulate filter (CGPF) during cold start, a mathematical model of the CGPF is established and verified firstly. Then, take T50 (a temperature when the hydrocarbon conversion rate reaches 50%) as hydrocarbon light-off (LO) temperature; the effects of different exhaust parameters and structural parameters on hydrocarbon light-off performance and reaction rate are investigated based on simulation results. Finally, orthogonal experiment analysis is employed to further obtain the most significant factors and suggested parameter solution. The results show that the hydrocarbon LO performance of the CGPF during cold start is positively correlated with exhaust oxygen concentration, porosity, and filter length, but it is negatively correlated with exhaust flow rate and exhaust water vapor concentration. In addition, the inlet of the channel has a significant HC reaction when the oxygen concentration reaches 2.2%, and porosity mainly influences the front half part of the filter. Moreover, the influence degree relationship of the five factors is oxygen > mass flow > porosity > length > water vapor, and the optimum solution of length, vapor, mass flow, porosity, and oxygen is 150 mm, 12.31%, 0.002 kg/s, 0.55, and 2.2%, respectively. This work offers us great reference value for CGPF performance enhancement and hydrocarbon abatement of a GDI engine.
Collapse
Affiliation(s)
- Bin Zhang
- College of Mechanical Engineering, Xiangtan University, Xiangtan, 411105, China
- Fujian Province Key Laboratory of Ship and Ocean Engineering, Jimei University, Xiamen, 361021, China
| | - Xuewei Li
- College of Mechanical Engineering, Xiangtan University, Xiangtan, 411105, China
| | - Qingsong Zuo
- College of Mechanical Engineering, Xiangtan University, Xiangtan, 411105, China.
| | - Zibin Yin
- Fujian Province Key Laboratory of Ship and Ocean Engineering, Jimei University, Xiamen, 361021, China
| | - Jianping Zhang
- College of Mechanical Engineering, Xiangtan University, Xiangtan, 411105, China
| | - Wei Chen
- College of Mechanical Engineering, Xiangtan University, Xiangtan, 411105, China
- Foshan Green Intelligent Manufacturing Research Institute of Xiangtan University, Foshan, 528311, Guangdong, China
| | - Chun Lu
- College of Mechanical Engineering, Xiangtan University, Xiangtan, 411105, China
| | - Dongli Tan
- School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, 545006, China
| |
Collapse
|
3
|
Soot Distribution Characteristics and Its Influence Factors in Burner-Type Regeneration Diesel Particulate Filter. Processes (Basel) 2022. [DOI: 10.3390/pr10102029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The burner-type regeneration diesel particulate filter is one of the most widely used diesel particulate filters. Using AVL FIRE, a 3D model of a burner-type regeneration diesel particulate filter (DPF) was established, and simulation analyses were carried out. The effects of the exhaust parameters (temperature, exhaust mass flow rate, and soot load) and the structural parameters (channel density, inlet/outlet channel ratio, and the length–diameter ratio) on soot distribution (soot mass concentration and soot thickness) were analyzed. The results show that the soot distribution characteristics of regenerative DPF with a burner are as follows: the soot mass concentration first rapidly rises to the maximum value and then rapidly decreases to a low value, and the dust thickness gradually increases with the increase in location. With the increase in exhaust mass flow rate and soot load, soot mass concentration and soot thickness increase. With the increase in temperature, the mass concentration and thickness of the ash decreased. When the temperature exceeds 750 K, soot begins to regenerate. Among the exhaust parameters, the mass flow rate of the exhaust has the greatest influence on the soot distribution. The length–diameter ratio, the ratio of the inlet and the outlet channel, and channel density have little effect on the mass concentration of soot, and the soot mass concentration increases with the increase in channel density. In addition to the length–diameter ratio of 2.1, the soot thickness increases with the increase in the length–diameter ratio, and the rising rate is also accelerated. The thickness of soot decreased with the increase in channel density and the ratio of the inlet and the outlet channels. When the channel density is more than 250, the change in soot thickness is basically the same. When the ratio of the inlet and the outlet channels exceeds 1.3, the change in the soot thickness is basically the same. Among the structural parameters, channel density has the greatest influence on the soot distribution.
Collapse
|
4
|
Walter R, Neumann J, Velroyen A, Hinrichsen O. Applying 3D X-ray Microscopy to Model Coated Gasoline Particulate Filters under Practical Driving Conditions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:12014-12023. [PMID: 35994629 DOI: 10.1021/acs.est.2c01244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Recent progress in 3D X-ray microscopy allows the analysis of coated gasoline particulate filters on a detailed pore-scale level. However, derivable detailed three-dimensional models for filter simulation are not applicable under transient driving conditions of automotive aftertreatment systems due to their inherent complexity. Here, we present a novel concept to utilize highly resolved 3D X-ray microscopy scans and their quantitative analysis for a macroscopic model of coated gasoline particulate filters intended to be applied in a driving cycle. A previously developed filtration model build on a 1D + 1D flow model on the channel scale of a filter is utilized. Accompanying measurements conducted on a dynamic engine test bench serve as validation for pressure drop and filtration characteristics. With the determined properties from 3D X-ray microscopy, the macroscopic model successfully replicates the measurements. Regarding the filter coating, the reduced porosity and a decrease of medium sized pores relative to an uncoated substrate reduce the filtration efficiency under steady-state as well as transient conditions.
Collapse
Affiliation(s)
- Raimund Walter
- Development Powertrain, BMW Group, Schleißzheimer Str. 422, 80937 Munich, Germany
- Department of Chemistry, Technical University of Munich, Lichtenbergstraßze 4, 85748 Garching near Munich, Germany
- Catalysis Research Center, Technical University of Munich, Ernst-Otto-Fischer-Straßze 1, 85748 Garching near Munich, Germany
| | - Jens Neumann
- Development Powertrain, BMW Group, Schleißzheimer Str. 422, 80937 Munich, Germany
| | - Astrid Velroyen
- Technology Material and Process Analysis, BMW Group, Hufelandstr. 5, 80937 Munich, Germany
| | - Olaf Hinrichsen
- Department of Chemistry, Technical University of Munich, Lichtenbergstraßze 4, 85748 Garching near Munich, Germany
- Catalysis Research Center, Technical University of Munich, Ernst-Otto-Fischer-Straßze 1, 85748 Garching near Munich, Germany
| |
Collapse
|