scholarly journals Impact of the Emission Control of Diesel Vehicles on Black Carbon (BC) Concentrations over China

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 696 ◽  
Author(s):  
Jiamao Zhou ◽  
Xuexi Tie ◽  
Yunbo Yu ◽  
Shuyu Zhao ◽  
Guohui Li ◽  
...  
Keyword(s):  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Vehicle Emissions ◽  
High Efficiency ◽  
Model Simulation ◽  
Emission Control ◽  
The Other ◽  
Particulate Filter ◽  
Diesel Vehicles ◽  
Diesel Vehicle

In order to reduce black carbon (BC) emissions from diesel vehicles, a regional atmospheric chemistry model (WRF-Chem) was used to investigate the effects of installing a high-efficiency device for vehicle exhaust control, a diesel particulate filter (DPF), on diesel vehicles in China. To reduce the uncertainty of estimation, three sensitivity experiments were designed and conducted for different emission scenarios. The first experiment uses the standard black carbon emissions of diesel vehicles without engaging in any emission control actions (referred to as CTRL), and the other two experiments were conducted using different DPF devices to reduce BC emissions by 65% (CASE1) and 39% (CASE2), respectively. The results show that the model simulation reasonably represents the measured BC concentrations. The highest BC concentrations occurred in large cities of the North China Plain (NCP) and present important seasonal variations. The results suggest that the reduction in diesel vehicle emissions has great benefits for reducing BC pollution not only in winter but also in other seasons. Sensitivity studies show that in CASE1, the average BC concentrations decreased about ~6% in January and by more than 10% in the other seasons. The greatest reduction exceeded 50%. In CASE2, the average BC concentrations decreased by about ~3.5% in January and by more than 7% in the other seasons. This study suggests that adding DPF to a diesel vehicle can have a significant influence on reducing BC concentrations in China. Thus, this study provides a practical basis by which diesel vehicle emissions can be reduced.

scholarly journals Characterizing Black Carbon Emissions from Gasoline, LPG, and Diesel Vehicles via Transient Chassis-Dynamometer Tests

2020 ◽  
Vol 10 (17) ◽  
pp. 5856
Author(s):  
Gyutae Park ◽  
Kyunghoon Kim ◽  
Taehyun Park ◽  
Seokwon Kang ◽  
Jihee Ban ◽  
...  
Keyword(s):  
Black Carbon ◽  
Coal Combustion ◽  
Gasoline Direct Injection ◽  
Environmental Research ◽  
Particulate Filter ◽  
Biomass Combustion ◽  
Liquefied Petroleum Gas ◽  
Chassis Dynamometer ◽  
Diesel Vehicles ◽  
Gasoline Vehicles

With global anthropogenic black carbon (BC) emissions increasing, automobiles are significantly contributing as the major source of emissions. However, the appropriate regulations of BC emissions from vehicles are not in place. This study examined BC emissions following fuel types (gasoline, liquefied petroleum gas (LPG), and diesel) and engine combustion (gasoline direct injection (GDI) and multi-port injection (MPI) for gasoline vehicles) with emission regulations. To this end, chassis dynamometer and aethalometer (AE33) were used. Driving modes created by the National Institute of Environmental Research (NIER) and emission certification modes (CVS-75 and NEDC) for vehicles in Korea were used to determine BC emissions for various vehicle speeds. In addition, the contributions of biomass and coal combustion to the data of AE33 were analyzed to determine the possibility of tracking the BC sources. MPI, LPG, and EURO 6 with diesel particulate filter (DPF) vehicles emitted the lowest BC emissions in NIER modes. Among gasoline vehicles, MPI vehicles showed the lower BC content in PM emissions. Also, older vehicles in MPI vehicles emitted the high PM and BC emissions. The BC emissions of EURO 3 vehicles without DPF were the highest as the results of previous studies, and it was found that as emissions regulations were tightened, the level of BC results of diesel vehicles became similar with MPI vehicles. The average absorption Ångström exponent (AAE) from difference emissions sources were biomass combustion (oak wood) > coal combustion (the power plant stack) > automobile emissions (gasoline, LPG, diesel).

scholarly journals Modeling of the chemistry in oxidation flow reactors with high initial NO

2017 ◽  
Vol 17 (19) ◽  
pp. 11991-12010 ◽  
Author(s):  
Zhe Peng ◽  
Jose L. Jimenez
Keyword(s):  
Atmospheric Chemistry ◽  
Vehicle Emissions ◽  
High Efficiency ◽  
Input Parameter ◽  
High Water ◽  
Peroxy Radicals ◽  
Aerosol Formation ◽  
Experimental Conditions ◽  
Flow Reactors ◽  
Chemistry Research

Abstract. Oxidation flow reactors (OFRs) are increasingly employed in atmospheric chemistry research because of their high efficiency of OH radical production from low-pressure Hg lamp emissions at both 185 and 254 nm (OFR185) or 254 nm only (OFR254). OFRs have been thought to be limited to studying low-NO chemistry (in which peroxy radicals (RO2) react preferentially with HO2) because NO is very rapidly oxidized by the high concentrations of O3, HO2, and OH in OFRs. However, many groups are performing experiments by aging combustion exhaust with high NO levels or adding NO in the hopes of simulating high-NO chemistry (in which RO2 + NO dominates). This work systematically explores the chemistry in OFRs with high initial NO. Using box modeling, we investigate the interconversion of N-containing species and the uncertainties due to kinetic parameters. Simple initial injection of NO in OFR185 can result in more RO2 reacted with NO than with HO2 and minor non-tropospheric photolysis, but only under a very narrow set of conditions (high water mixing ratio, low UV intensity, low external OH reactivity (OHRext), and initial NO concentration (NOin) of tens to hundreds of ppb) that account for a very small fraction of the input parameter space. These conditions are generally far away from experimental conditions of published OFR studies with high initial NO. In particular, studies of aerosol formation from vehicle emissions in OFRs often used OHRext and NOin several orders of magnitude higher. Due to extremely high OHRext and NOin, some studies may have resulted in substantial non-tropospheric photolysis, strong delay to RO2 chemistry due to peroxynitrate formation, VOC reactions with NO3 dominating over those with OH, and faster reactions of OH–aromatic adducts with NO2 than those with O2, all of which are irrelevant to ambient VOC photooxidation chemistry. Some of the negative effects are the worst for alkene and aromatic precursors. To avoid undesired chemistry, vehicle emissions generally need to be diluted by a factor of > 100 before being injected into an OFR. However, sufficiently diluted vehicle emissions generally do not lead to high-NO chemistry in OFRs but are rather dominated by the low-NO RO2 + HO2 pathway. To ensure high-NO conditions without substantial atmospherically irrelevant chemistry in a more controlled fashion, new techniques are needed.

scholarly journals Modeling of the chemistry in oxidation flow reactors with high initial NO

2017 ◽  
Author(s):  
Zhe Peng ◽  
Jose L. Jimenez
Keyword(s):  
Atmospheric Chemistry ◽  
Vehicle Emissions ◽  
High Efficiency ◽  
Input Parameter ◽  
High Water ◽  
Peroxy Radicals ◽  
Aerosol Formation ◽  
Experimental Conditions ◽  
Flow Reactors ◽  
Chemistry Research

Abstract. Oxidation flow reactors (OFRs) are increasingly employed in atmospheric chemistry research because of their high efficiency of OH radical production from low-pressure Hg lamp emissions at both 185 and 254 nm (OFR185) or 254 nm only (OFR254). OFRs have been thought to be limited to studying low-NO chemistry (where peroxy radicals (RO2) react preferentially with HO2) because NO is very rapidly oxidized by the high concentrations of O3, HO2, and OH in OFRs. However, many groups are performing experiments aging combustion exhaust with high NO levels, or adding NO in the hopes of simulating high-NO chemistry (where RO2 + NO dominates). This work systematically explores the chemistry in OFRs with high initial NO. Using box modeling, we investigate the interconversion of N-containing species and the uncertainties due to kinetic parameters. Simple initial injection of NO in OFR185 can result in more RO2 reacted with NO than with HO2 and minor non-tropospheric photolysis, but only under a very narrow set of conditions (high water mixing ratio, low UV intensity, low external OH reactivity (OHRext), and initial NO concentration (NOin) of tens to hundreds of ppb) that account for a very small fraction of the input parameter space. These conditions are generally far away from experimental conditions of published OFR studies with high initial NO. In particular, studies of aerosol formation from vehicle emissions in OFR often used OHRext and NOin several orders of magnitude higher. Due to extremely high OHRext and NOin, some studies may have resulted in substantial non-tropospheric photolysis, strong delay to RO2 chemistry due to peroxynitrate formation, VOC reactions with NO3 dominating over those with OH, and faster reactions of OH-aromatic adducts with NO2 than those with O2, all of which are irrelevant to ambient VOC photooxidation chemistry. Some of the negative effects are worst for alkene and aromatic precursors. To avoid undesired chemistry, vehicle emissions generally need to be diluted by a factor of > 100 before being injected into OFR. However, sufficiently diluted vehicle emissions generally do not lead to high-NO chemistry in OFR, but are rather dominated by the low-NO RO2 + HO2 pathway. To ensure high-NO conditions without substantial atmospherically irrelevant chemistry in a more controlled fashion, new techniques are needed.

scholarly journals Fast Accurate and Automatic Brushstroke Extraction

2021 ◽  
Vol 17 (2) ◽  
pp. 1-24
Author(s):  
Yunfei Fu ◽  
Hongchuan Yu ◽  
Chih-Kuo Yeh ◽  
Tong-Yee Lee ◽  
Jian J. Zhang
Keyword(s):  
Neural Network ◽  
Efficient Algorithm ◽  
Deep Neural Network ◽  
High Efficiency ◽  
State Of The Art ◽  
High Reliability ◽  
The Other ◽  
Manual Annotation ◽  
Stroke Extraction ◽  
Art Research

Brushstrokes are viewed as the artist’s “handwriting” in a painting. In many applications such as style learning and transfer, mimicking painting, and painting authentication, it is highly desired to quantitatively and accurately identify brushstroke characteristics from old masters’ pieces using computer programs. However, due to the nature of hundreds or thousands of intermingling brushstrokes in the painting, it still remains challenging. This article proposes an efficient algorithm for brush Stroke extraction based on a Deep neural network, i.e., DStroke. Compared to the state-of-the-art research, the main merit of the proposed DStroke is to automatically and rapidly extract brushstrokes from a painting without manual annotation, while accurately approximating the real brushstrokes with high reliability. Herein, recovering the faithful soft transitions between brushstrokes is often ignored by the other methods. In fact, the details of brushstrokes in a master piece of painting (e.g., shapes, colors, texture, overlaps) are highly desired by artists since they hold promise to enhance and extend the artists’ powers, just like microscopes extend biologists’ powers. To demonstrate the high efficiency of the proposed DStroke, we perform it on a set of real scans of paintings and a set of synthetic paintings, respectively. Experiments show that the proposed DStroke is noticeably faster and more accurate at identifying and extracting brushstrokes, outperforming the other methods.

scholarly journals Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters

2015 ◽  
Vol 8 (3) ◽  
pp. 2881-2912 ◽  
Author(s):  
J. M. Wang ◽  
C.-H. Jeong ◽  
N. Zimmerman ◽  
R. M. Healy ◽  
D. K. Wang ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Black Carbon ◽  
Time Resolution ◽  
Real World ◽  
Vehicle Emissions ◽  
Particle Number ◽  
Emission Factors ◽  
Air Pollutant ◽  
Automated Identification ◽  
Vehicle Fleet

Abstract. An automated identification and integration method has been developed to investigate in-use vehicle emissions under real-world conditions. This technique was applied to high time resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada during four seasons, through month-long campaigns in 2013–2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number, black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the light-duty gasoline dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mg kg−1 and 7.7 × 1014 kg−1, respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of co-emitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25%) contributed significantly to total fleet emissions; 95, 93, 76, and 75% for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter. However, regulatory strategies to more efficiently target multi-pollutants mixtures may be better developed by considering the co-emitted pollutants as well.

Fractality of Simulated Fracture

2009 ◽  
Vol 409 ◽  
pp. 154-160 ◽  
Author(s):  
Petr Frantík ◽  
Zbyněk Keršner ◽  
Václav Veselý ◽  
Ladislav Řoutil
Keyword(s):  
Numerical Model ◽  
Elastic Plate ◽  
Model Simulation ◽  
Element Model ◽  
The Other ◽  
Particle Model ◽  
Discrete Element Model ◽  
Fractal Nature ◽  
Discrete Elements ◽  
The Impact

The paper is focussed on numerical simulations of the fracture of a quasi-brittle specimen due to its impact onto a fixed rigid elastic plate. The failure of the specimen after the impact is modelled in two ways based on the physical discretization of continuum: via physical discrete elements and pseudo-particles. Advantages and drawbacks of both used methods are discussed. The size distribution of the fragments of the broken specimen resulting from physical discrete element model simulation follows a power law, which indicates the ability of the numerical model to identify the fractal nature of the fracture. The pseudo-particle model, on the other side, can successfully predict the kinematics of the fragments of the specimen under impact failure.

scholarly journals Potential reductions in ambient NO 2 concentrations from meeting diesel vehicle emissions standards

2017 ◽  
Vol 12 (11) ◽  
pp. 114025 ◽  
Author(s):  
Erika von Schneidemesser ◽  
Friderike Kuik ◽  
Kathleen A Mar ◽  
Tim Butler
Keyword(s):  
Vehicle Emissions ◽  
Diesel Vehicle
Sign in / Sign up

Export Citation Format

Share Document