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This study reassesses an overview of the potential of the radio frequency (RF)-based state diagnostics of three-way catalysts (TWC) based on a previous study with an emphasis on the defect chemistry of the catalyst material during reoxidation and reduction. Some data are based on the previous works but are newly processed, and the signal parameters resonant frequency and inverse quality factor are evaluated with respect to applicability. The RF-based method uses electromagnetic resonances in a cavity resonator to provide information on the storage level of the oxygen storage component. The analysis focuses on a holistic investigation and evaluation of the major effects influencing the RF signal during operation. On the one hand, the response to the oxygen storage behavior and the resolution of the measurement method are considered. Therefore, this study merges original data from multiple former publications to provide a comprehensive insight into important measurement effects and their defect chemistry background. On the other hand, the most important cross-sensitivities are discussed and their impact during operation is evaluated. Additionally, the effect of catalyst aging is analyzed. The effects are presented separately for the two resonant parameters: resonant frequency and (unloaded) quality factor. Overall, the data suggest that the quality factor has a way higher signal quality at low temperatures (<400 °C) and the resonant frequency is primarily suitable for high operating temperatures. At most operating points, the quality factor is even more robust against interferences such as exhaust gas stoichiometry and water content. Correctly estimating the catalyst temperature is the most important factor for reliable results, which can be achieved by combining the information of both resonant signals. In the end, the data indicate that microwave-based state diagnosis is a powerful system for evaluating the oxygen storage level over the entire operating range of a TWC. As a research tool and in its application, the system can therefore contribute to the improvement of the emission control of future gasoline vehicles.
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With the global emphasis on environmental protection and increasingly stringent emission regulations for internal combustion engines, there is an urgent need to overcome the problem of large hydrocarbon (HC) emissions caused by unstable engine cold starts. Synergistic engine pre-treatment (reducing hydrocarbon production) as well as after-treatment devices (adsorbing and oxidizing hydrocarbons) is the fundamental solution to emissions. In this paper, the improvement of hydrocarbon emissions is summarized from two aspects: pre-treatment and after-treatment. The pre-treatment for engine cold start mainly focuses on summarizing the intake control, fuel, and engine timing parameters. The after-treatment mainly focuses on summarizing different types of adsorbents and modifications (mainly including different molecular sieve structures and sizes, preparation conditions, silicon aluminum ratio, ion exchange modification, and heterogeneity, etc.), adsorptive catalysts (mainly including optimization of catalytic performance and structure), and catalytic devices (mainly including coupling with thermal management equipment and HC trap devices). In this paper, a SWOT (strength, weakness, opportunity, and threat) analysis of pre-treatment and after-treatment measures is conducted. Researchers can obtain relevant research results and seek new research directions and approaches for controlling cold start HC emissions.
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Automóveis , Gasolina , Gasolina/análise , Emissões de Veículos/análise , Adsorção , Hidrocarbonetos/análiseRESUMO
Recently, radio frequency (RF) technology was introduced as a tool to determine the oxygen storage level of a three-way catalyst (TWC) for gasoline vehicles. Previous studies on the investigation of commercial catalysts mostly use only the resonant frequency to describe the correlation of oxygen storage level and RF signal. For the first time this study presents a comparison under defined laboratory conditions considering both, resonance frequency and also the quality factor as measurands. Furthermore, various advantages over the sole use of the resonant frequency in the technical application are discussed. Experiments with Ø4.66'' catalysts and Ø1.66'' catalyst cores with alternating (rich/lean) gas compositions showed that the relative change in signal amplitude due to a change in oxygen storage is about 100 times higher for the inverse quality factor compared to the resonant frequency. In addition, the quality factor reacts more sensitively to the onset of the oxygen-storage ability, and delivers precise information about the necessary temperature, which is not possible when evaluating the resonant frequency due to the low signal amplitude. As investigations on aged catalysts confirm, the quality factor also provides a new approach to determine operando the ageing state of a TWC.
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We studied engine-out soot samples collected from a heavy-duty direct-injection diesel engine and port-fuel injection gasoline spark-ignition engine. The two types of soot samples were characterized using Raman spectroscopy with different laser powers. A Matlab program using least-square-method with trust-region-reflective algorithm was developed for curve fitting. A DOE (design of experiments) method was used to avoid local convergence. The method was used for two-band fitting and three-band fitting. The fitting results were used to determine the intensity ratio of D (for "Defect" or "Disorder") and G (for "Graphite") Raman bands. It is found that high laser power may cause oxidation of soot sample, which gives higher D/G intensity ratio. Diesel soot has consistently higher amorphous/graphitic carbon ratio, and thus higher oxidation reactivity, compared to gasoline soot, which is reflected by the higher D/G intensity ratio in Raman spectra measured under the same laser power.
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Fuligem/análise , Emissões de Veículos/análise , Gasolina , Lasers , Análise Espectral RamanRESUMO
OBJECTIVES: To determine whether occupational exposure to gasoline engine emissions (GEE) increased the risk of lung cancer and more specifically whether leaded or unleaded GEE increased the risk. METHODS: Two population-based case-control studies were conducted in Montreal, Canada. The first was conducted in the early 1980s and included many types of cancer including lung cancer. The second was conducted in the late 1990s and focused on lung cancer. Population controls were used in both studies. Altogether, there were 1595 cases and 1432 population controls. A comprehensive expert-based exposure assessment procedure was implemented and exposure was assessed for 294 agents, including unleaded GEE, leaded GEE and diesel engine emissions (DEE). Logistic regression analyses were conducted to estimate ORs between various metrics of GEE exposure and lung cancer, adjusting for smoking, DEE and other potential confounders. RESULTS: About half of all controls were occupationally exposed to GEE. Irrespective of the metrics of exposure (any exposure, duration of exposure and cumulative exposure) and the type of lung cancer, and the covariates included in models, none of the point estimates of the ORs between occupational exposure to leaded or unleaded GEE and lung cancer were above 1.0. Pooling two studies, the OR for any exposure to leaded GEE was 0.82 (0.68-1.00). CONCLUSIONS: Our results do not support the hypothesis that occupational exposure to GEE increases the risk of lung cancer.
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Gasolina/efeitos adversos , Exposição por Inalação/efeitos adversos , Chumbo/efeitos adversos , Neoplasias Pulmonares/induzido quimicamente , Exposição Ocupacional/efeitos adversos , Emissões de Veículos/toxicidade , Adulto , Idoso , Estudos de Casos e Controles , Feminino , Humanos , Exposição por Inalação/estatística & dados numéricos , Modelos Logísticos , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/etiologia , Masculino , Pessoa de Meia-Idade , Exposição Ocupacional/estatística & dados numéricos , Quebeque/epidemiologia , Fatores de RiscoRESUMO
The rapid development of electronic techniques in automobile has led to an increase of potential safety hazards, thus, a strong on-board diagnostic (OBD) system is desperately needed. To solve the problem of OBD insensitivity to manufacture errors or aging faults, the paper proposes a novel multi information fusion method. The diagnostic model is composed of a data fusion layer, feature fusion layer, and decision fusion layer. They are based on the back propagation (BP) neural network, support vector machine (SVM), and evidence theory, respectively. Algorithms are mainly focused on the reliability allocation of diagnostic results, which come from the data fusion layer and feature fusion layer. A fault simulator system was developed to simulate bias and drift faults of the intake pressure sensor. The real vehicle experiment was carried out to acquire data that are used to verify the availability of the method. Diagnostic results show that the multi-information fusion method improves diagnostic accuracy and reliability effectively. The study will be a promising approach for the diagnosis bias and drift fault of sensors in electronic control systems.
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Light-duty gasoline vehicles have drawn public attention in China due to their significant primary emissions of particulate matter and volatile organic compounds (VOCs). However, little information on secondary aerosol formation from exhaust for Chinese vehicles and fuel conditions is available. In this study, chamber experiments were conducted to quantify the potential of secondary aerosol formation from the exhaust of a port fuel injection gasoline engine. The engine and fuel used are common in the Chinese market, and the fuel satisfies the China V gasoline fuel standard. Substantial secondary aerosol formation was observed during a 4-5hr simulation, which was estimated to represent more than 10days of equivalent atmospheric photo-oxidation in Beijing. As a consequence, the extreme case secondary organic aerosol (SOA) production was 426±85mg/kg-fuel, with high levels of precursors and OH exposure. The low hygroscopicity of the aerosols formed inside the chamber suggests that SOA was the dominant chemical composition. Fourteen percent of SOA measured in the chamber experiments could be explained through the oxidation of speciated single-ring aromatics. Unspeciated precursors, such as intermediate-volatility organic compounds and semi-volatile organic compounds, might be significant for SOA formation from gasoline VOCs. We concluded that reductions of emissions of aerosol precursor gases from vehicles are essential to mediate pollution in China.
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Aerossóis/análise , Poluentes Atmosféricos/análise , Modelos Químicos , Emissões de Veículos/análise , Aerossóis/química , Poluentes Atmosféricos/química , China , Compostos Orgânicos Voláteis/análise , Compostos Orgânicos Voláteis/químicaRESUMO
The present study was conducted to investigate the effectiveness of new, less toxic, less harmful, and nonmetallic graphite (G) and metallic iron oxide (Fe2O3) nanofuel additives by analyzing experimentally their consequences on exhaust emissions and performance of an air cooled, single cylinder, 4-stroke gasoline engine. Fe2O3 and graphite nanoparticles at 40, 80, and 120 mg/l of gasoline concentrations were mixed with gasoline by means of a magnetic stirrer. Brake power (BP), brake-specific fuel consumption (BSFC), torque (T), brake thermal efficiency (BTE), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HC), and carbon dioxide (CO2) emissions were the investigated parameters. Experimental results indicated that G-blends showed a higher rise in brake power, brake thermal efficiency and torque and a greater reduction in the brake-specific fuel consumption as compared to that of Fe2O3 fuel blends. Moreover, the G-blends produced less NOx and CO2 than Fe2O3 blends but produced more emissions of CO and HC than that of Fe2O3 blends. On average, G-blends produced 0.46%, 0.71%, and 1.71% more torque, power, and BTE and 2.43%, 1.87%, and 13.39% less brake-specific fuel consumption (BSFC), NOx, and CO2 than Fe2O3 blends, respectively. So, in terms of the eight parameters, four performance parameters (i.e., T, BP, BSFC, BTE), and four engine emission exhaust indicators (i.e., CO, NOx, HC, CO2), graphite nanoparticles showed more positive results for 6 parameters (T, BP, BSFC, BTE, NOx, CO2), while two parameters HC and CO showed negative results with graphite as compared to that of Fe2O3 nanoparticles. So, overall, we conclude that nanoparticles of graphite are more engine and environment friendly than that of iron oxide fuel additives.
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Particulate matter (PM) causes several diseases, including cardiovascular diseases (CVDs). Previous studies compared the gene expression patterns in airway epithelial cells and keratinocytes exposed to PM. However, analysis of differentially expressed gene (DEGs) in endothelial cells exposed to PM2.5 (diameter less than 2.5 µm) from fossil fuel combustion has been limited. Here, we exposed human umbilical vein endothelial cells (HUVECs) to PM2.5 from combustion of gasoline, performed RNA-seq analysis, and identified DEGs. Exposure to the IC50 concentrations of gasoline engine exhaust PM2.5 (GPM) for 24 h yielded 1081 (up-regulation: 446, down-regulation: 635) DEGs. The most highly up-regulated gene is NGFR followed by ADM2 and NUPR1. The most highly down-regulated gene is TNFSF10 followed by GDF3 and EDN1. Gene Ontology enrichment analysis revealed that GPM regulated genes involved in cardiovascular system development, tube development and circulatory system development. Kyoto Encyclopedia of Genes and Genomes and Reactome pathway analyses showed that genes related to cytokine-cytokine receptor interactions and cytokine signaling in the immune system were significantly affected by GPM. We confirmed the RNA-seq data of some highly altered genes by qRT-PCR and showed the induction of NGFR, ADM2 and IL-11 at a protein level, indicating that the observed gene expression patterns were reliable. Given the adverse effects of PM2.5 on CVDs, our findings provide new insight into the importance of several DEGs and pathways in GPM-induced CVDs.
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Improving the NOx conversion efficiency and particulate combustion efficiency under cold-start conditions (low-temperature conditions) is still the main challenge faced by catalytic gasoline particulate filter systems (CGPFs). In this study, the physical and mathematical models of novel CGPFs are proposed based on the computational fluid dynamics software. Then, the models are validated based on experiments, and the performances of conventional and novel CGPFs are analyzed comparatively. The comparison conclusions indicate that the NOx conversion efficiency of the novel CGPFs increases by 3.2% and the particulate combustion efficiency increases by 2.7% under the same operating condition. Finally, the effects of exhaust flow vf, exhaust oxygen mass fraction Co, exhaust NO mass fraction CNO, and electric heating power Pe on the NOx conversion efficiency and particulate combustion efficiency are investigated. The weights of each influencing parameter on the NOx conversion efficiency and particulate combustion efficiency are explored by orthogonal tests. The conclusions show that the NOx conversion efficiency is increased by 3.6% and the particulate combustion efficiency is increased by 16.7% compared to the initial condition. This study has an important reference value for improving the purification efficiency of vehicle emission under cold-start conditions.
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Poluentes Atmosféricos , Poluentes Ambientais , Poluentes Atmosféricos/análise , Poeira , Gasolina/análise , Minerais , Material Particulado/análise , Emissões de Veículos/análiseRESUMO
This paper proposes a model-based nonlinear receding horizon optimal control scheme for the engine torque tracking problem. The controller design directly employs the nonlinear model exploited based on mean-value modeling principle of engine systems without any linearizing reformation, and the online optimization is achieved by applying the Continuation/GMRES (generalized minimum residual) approach. Several receding horizon control schemes are designed to investigate the effects of the integral action and integral gain selection. Simulation analyses and experimental validations are implemented to demonstrate the real-time optimization performance and control effects of the proposed torque tracking controllers.
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Long-term inhalation of gasoline engine exhaust (GEE) increases the risk of respiratory disease. Studies have suggested involvement of platelets in the development of some lung diseases. Hydroxysafflor yellow A (HSYA), a flavonoid compound, prevents hemostasis. Therefore, we investigated its effects on GEE-induced lung injury, and role of platelets in injury. Sixty-week-old male Sprague-Dawley rats were exposed to GEE for 4h/day for 6 weeks, and then grouped as follows: control, GEE, GEE+HSYA, GEE+HSYA+GW9662, and GEE+GW9662. Arterial oxygen tension (PaO2), carbon dioxide tension (PaCO2), pH, and the PaO2/fraction of inspired oxygen ratio (PaO2/FiO2) in the blood were detected using a blood gas analyzer. Wet/dry lung weight ratio, total protein in bronchoalveolar lavage fluid (BALF), and cytokine concentrations in serum and BALF were determined. Furthermore, cyclic adenosine monophosphate (cAMP) level and expression levels of target proteins were analyzed. Platelets were counted and their state was evaluated. HSYA attenuated GEE-mediated decreases in PaO2, PaO2/FiO2, platelet cAMP level, protein kinase A (PKA) activity, and peroxisome proliferator-activated receptor γ (PPARγ) expression. HSYA also attenuated GEE-mediated increases in lung permeability, cytokine levels in serum and BALF, plasma platelet count, and ADP-mediated platelet aggregation. Moreover, it suppressed GEE-induced increases in the expression of adhesion molecules and proinflammatory cytokines in platelets and lung tissue. Therefore, HSYA is therapeutically effective for GEE-mediated lung injury and acts by enhancing PKA activity and inhibiting platelet activation.