Validation of road vehicle and traffic emission models – A review and meta-analysis

Smit, Robin; Ntziachristos, Leónidas; Boulter, P G

doi:10.1016/j.atmosenv.2010.05.022

Cited by 236 publications

(137 citation statements)

References 53 publications

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“…Estimating the exact amount of carbon dioxide emission with detailed input data is the advantage of this model, but it is impossible to collect the exact driving cycle data of all vehicles on the road. The macro-scale model (e.g., COPERT, MOBILE, EMFAC) uses emission factors (EFs) and vehicle kilometers traveled (VKT) per average speed of different vehicle types to calculate the amount of emission per link unit [14]. The macro-scale model can calculate the total carbon dioxide emission of all vehicles within the given link on the base of average speed, so it is more appropriate than the micro-scale model.…”

Section: Introductionmentioning

confidence: 99%

“…The models used for calculating carbon dioxide emissions on the road can be divided into the micro-scale model and the macro-scale model. The micro-scale model (e.g., Comprehensive Modal Emissions Model, CMEM) calculates the amount of instantaneous emission [14,15] using the driving cycles of vehicles, vehicle data, road gradient and so on. Estimating the exact amount of carbon dioxide emission with detailed input data is the advantage of this model, but it is impossible to collect the exact driving cycle data of all vehicles on the road.…”

Section: Introductionmentioning

confidence: 99%

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Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions

et al. 2015

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Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide emissions. The objective function of the upper level model is to minimize the sum of travel costs and the carbon dioxide emissions costs. The lower level is a multi-modal transportation network equilibrium model. To solve the model, the method of successive averages (MSA) and the shuffled frog leaping algorithm (SFLA) are introduced. The proposed method and algorithm are tested through the numerical example. The results show that the proposed congestion pricing strategy can mitigate traffic congestion and reduce carbon emissions effectively.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions

et al. 2015

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“…도로 이동 오염원의 배출계수는 오염원의 단위 주행거리 , 단위 에너지 소비량 (Lim et al, 2009), 또는 단위 연료 소비량 (Wang et al, 2012;Yli-Tuomia et al, 2005) 당의 대기 오염물질 배출량으로 정의된다 (Smit et al, 2010). (Franco et al, 2013).…”

Section: 서 론unclassified

Evaluations for Representativeness of Light-Duty Diesel Vehicles' Fuel-based Emission Factors on Vehicle Operating Conditions

Lee¹,

Kwon²,

Son³

et al. 2013

Journal of Korean Society for Atmospheric Environment

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The purpose of this study is to evaluate representativeness of fuel-based emission factors. Twelve light-duty diesel vehicles which meet Euro-3 to 5 legislative emission limits were selected for emission tests. Second-bysecond modal emission rates of vehicles were measured on a standard laboratory chassis dynamometer system. An off-cycle driving cycle was developed as a representative Korean real-world on-road driving cycle. Fuel-based emission factors were developed for short trip segments that involved in the selected driving cycle. Each segment was defined to have unit travel distance, which is 1 km, and characterized by its average speed and Relative Positive Acceleration (RPA). Fuel-based NO x emission factors demonstrate relatively good representativeness in terms of vehicle operation conditions. NO x emission factors are estimated to be within ±20% of area-wide emission factor under more than 40% of total driving situations. This result implies that the fuel-based NO x emission factor could be practically implemented into the on-road emission management strategies, such as a remote sensing device (RSD). High emitting vehicles as well as high emitting operating conditions heavily affect on the mean values and distributions of CO and THC emission factors. Few high emitting conditions are pulling up the mean value and biasing the distributions, which weaken representativeness of fuel-based CO and THC emission factors.

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“…in a specified geographical region (i.e., South Coast Air Basin). In general, it provides good estimates of PM 10 and PM 2.5 emission factors relative to other modeling programs (Smit et al, 2010;Park et al, 2011). Emission factors were generated for the experimental runs on the I-710 and I-405 freeways using the corresponding temperature, humidity, and vehicle speed data.…”

Section: Model Estimation Of Pm 25mentioning

confidence: 99%

Particle Concentration on Freeways: Affecting Factors and a Simple Model Development

Fung

Zhou

Hinds

et al. 2013

Aerosol Air Qual. Res.

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A few field studies have reported high levels of in-cabin ultrafine particles and discussed certain contributing factors such as vehicle operations and atmospheric meteorological conditions. However, to generalize limited field study results to a wide range of conditions, a deeper understanding of affecting factors and a simple model that can predict on-road particle concentrations are essential. This paper has two objectives, first, to analyze the effects of surrounding vehicle density, relative freeway lane position, and vehicle speed on measured particle concentrations on two California freeways, I-405 (5% diesel) and I-710 (25% diesel). The second objective is to test the use of Emission Factor (EMFAC) 2007 and Caline4 (CL4) models in predicting on-road particle concentrations. Particle number and mass concentrations were collected using a mobile laboratory driving on the I-710 and I-405 freeways. Particle number concentration was found to be affected by the density of surrounding heavy duty diesel trucks which is consistent with previous studies. The highest particle number concentrations were measured in the outer lanes on the freeway and the lowest was in the inner lanes. The highest levels of particles were measured at vehicle speeds of 40-50 mph. Analysis of CL4 model was conducted using factor-of-two test. For the I-710, 85% of values were within the factor-of-two envelope, and for the I-405, 77% were within the envelope. Regression analysis showed that the model is able to account for 43% of the variability on the I-710 and 26% of the variability on the I-405. The use of CL4 in conjunction with EMFAC shows promise as a simple tool to estimate on-road PM 2.5 concentration.

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Validation of road vehicle and traffic emission models – A review and meta-analysis

Cited by 236 publications

References 53 publications

Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions

Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions

Evaluations for Representativeness of Light-Duty Diesel Vehicles' Fuel-based Emission Factors on Vehicle Operating Conditions

Particle Concentration on Freeways: Affecting Factors and a Simple Model Development

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