An analysis of emission reduction strategy for light and heavy-duty vehicles pollutions in high spatial–temporal resolution and emission

Khazini, Leila; Kalajahi, Mina Jamshidi; Blond, Nadège

doi:10.1007/s11356-021-17497-0

Cited by 7 publications

(5 citation statements)

References 72 publications

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“…( 2) Using the IVE model and Monte Carlo simulation, this study calculated the uncertainties associated with regional daily road traffic emissions for different spatial or temporal coverage levels and then analysed the variation patterns in uncertainties. (3) This study calculated the uncertainties associated with different spatiotemporal coverage combinations of regional daily road traffic emissions, and constructed a requirement model for the spatiotemporal sampling coverage of fleet composition for the quantification of regional daily road traffic emissions.…”

Section: Methodsmentioning

confidence: 99%

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Managing Uncertainty in Urban Road Traffic Emissions Associated with Vehicle Fleet Composition: From the Perspective of Spatiotemporal Sampling Coverage

Cai,

Zeng,

et al. 2024

Sustainability

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With pronounced differences in emission factors among vehicle types and marked spatiotemporal heterogeneity of vehicle fleet composition, extrapolating fleet composition from insufficient sample hour periods and road segments will introduce significant uncertainty in calculating regional daily road traffic emissions. We proposed a framework to manage uncertainty in urban road traffic emissions associated with vehicle fleet composition from the perspective of spatiotemporal sampling coverage. Initially, the respective relationships of the temporal and spatial sampling coverages of fleet composition with the resulting regional daily road traffic emission uncertainties were determined, using the core area of a typical small and medium-sized city in China with the widely-used International Vehicle Emissions (IVE) model as example. Subsequently, function models were developed to explore the determination of the spatiotemporal sampling coverage of fleet composition. These results of emission uncertainties and function models implied that gases with larger emission factor discrepancies between vehicle types, such as NOx, required greater spatiotemporal sampling coverage than gases with smaller discrepancies, such as CO2, under the same uncertainties target. Therefore, sampling efforts should be prioritized for gases with larger emission factor discrepancies. Additionally, increasing sampling coverage in one dimension (either spatial or temporal) can reduce the minimum required coverage in the other dimension. To further reduce uncertainty, enhancing both spatial and temporal sampling coverage of the fleet composition is more effective than enhancing one type of coverage alone. The framework and results proposed in this work can reduce the uncertainty of emissions calculations caused by insufficient sampling coverage and contribute to more accurate transport emission reduction policy formulation.

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Section: Methodsmentioning

confidence: 99%

“…As a major source of urban air pollution and greenhouse gases, road traffic emissions are a significant consideration when implementing reduction policies for urban emissions [1][2][3]. Quantification of urban road traffic emissions with low uncertainty is fundamental to effective emission reduction policies [4,5].…”

Section: Introductionmentioning

confidence: 99%

Managing Uncertainty in Urban Road Traffic Emissions Associated with Vehicle Fleet Composition: From the Perspective of Spatiotemporal Sampling Coverage

Cai,

Zeng,

et al. 2024

Sustainability

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“…Vehicle CO 2 emission is typically influenced by a combination of multiple factors, so it is necessary to reveal the impacts of simultaneous multi-factor variables on emission factors, in order to summarize the methods for constructing a high-resolution database of the carbon emission factor. At present, existing multi-factor variable analysis models, such as COPERT [18,19], MOBILE [20,21], IVE [22], etc., are all based on static factors such as vehicle type, vehicle mileage, fuel quality, and fuel volatility to study the vehicle emission factors of motor vehicles. The traditional one-at-a-time (OAT) sensitivity analysis applied in the sensitivity analysis can only predict the relative sensitivity of a single input parameter at a time, so that it precludes the synergistic effects between multiple input parameters.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Traffic Carbon Emission Factor Based on Sensitivity and Uncertainty Analysis

Chen,

Yu,

et al. 2024

Energies

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The premise for formulating effective emission control strategies is to accurately and reasonably evaluate the actual emission level of vehicles. Firstly, the active subspace method is applied to set up a low-dimensional model of the relationship between CO2 emission and multivariate vehicle driving data, in which the vehicle specific power (VSP) is identified as the most significant factor on the CO2 emission factor, followed by speed. Additionally, acceleration and exhaust temperature had the least impact. It is inferred that the changes in data sampling transform the establishment of subspace matrices, affecting the calculation of eigenvector components and the fitting of the final quadratic response surface, so that the emission sensitivity and final fitting accuracy are impressionable by the data distribution form. For the VSP, the best fitting result can be obtained when the VSP conforms to a uniform distribution. Moreover, the Bayesian linear regression method accounts for fitting parameters between the VSP and CO2 emission factor with uncertainties derived from heteroscedastic measurement errors, and the values and distributions of the intercept and slope α and β are obtained. In general, the high-resolution inventory of the carbon emission factor of the tested vehicle is set up via systematically analyzing it, which brings a bright view of data processing in further counting the carbon footprint.

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“…Most areas of the world have adopted modes of transport such as trains and trucks for transporting freight [1]. However, some of the associated problems concerning pollution in the environment and the use of non-renewable fuels have become more serious [2], especially in urbanized areas and areas with sensitive ecosystems [3]. Increasing attention has been focused on sustainable transport that is eco-friendly.…”

Section: Introductionmentioning

confidence: 99%

Transient Model for the Hydrodynamic Force in a Hydraulic Capsule Pipeline Transport System

Zhao,

Li,

Sun

2023

Sustainability

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The hydraulic capsule pipeline (HCP) is an eco-friendly and sustainable pipeline transport option. The freight-carrying capsule is driven by hydraulic pipe flow. Fluid drag is generated by the principal dynamic force effect on the capsule, which could influence the capsule’s motion speed. To make the HCP more efficient, a transient model for the hydrodynamic force in an HCP was developed in this study. From a numerical simulation, the coherent vortex structures of fluctuating modes were observed, and the velocity iso-surfaces of the coherent vortex of the wake flow exhibited an annular trend in circumferential connection. Then, the hydrodynamic force was analyzed: the steady component and transient component were resolved, and the general trend in forces in terms of the transient components was that the maximum amplitude of forces reduced with an increase in mode order. Through short-term Fourier transform, the frequency components and their variations in terms of the entire time range could be acquired. The transient model in this study provided a perspective to build the connection between the flow structures and the hydrodynamic force. By the transient model, the transient component of hydrodynamic force can be explained as the fluctuation of coherent vortex structures.

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An analysis of emission reduction strategy for light and heavy-duty vehicles pollutions in high spatial–temporal resolution and emission

Cited by 7 publications

References 72 publications

Managing Uncertainty in Urban Road Traffic Emissions Associated with Vehicle Fleet Composition: From the Perspective of Spatiotemporal Sampling Coverage

Managing Uncertainty in Urban Road Traffic Emissions Associated with Vehicle Fleet Composition: From the Perspective of Spatiotemporal Sampling Coverage

Investigation on Traffic Carbon Emission Factor Based on Sensitivity and Uncertainty Analysis

Transient Model for the Hydrodynamic Force in a Hydraulic Capsule Pipeline Transport System

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