scholarly journals Fuel Consumption and Vehicle Emission Models for Evaluating Environmental Impacts of the ETC System

2015 ◽  
Vol 7 (7) ◽  
pp. 8934-8949 ◽  
Author(s):  
Jiancheng Weng ◽  
Ru Wang ◽  
Mengjia Wang ◽  
Jian Rong
Keyword(s):  
Fuel Consumption ◽  
Environmental Impacts ◽  
Vehicle Emission ◽  
Emission Models

Multiobjective Evaluation in Countermeasure Selection at Two-Way Stop-Controlled Intersections: Considering Traffic Operation, Safety, and Environment

2017 ◽  
Vol 2635 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Zhao Yang ◽  
Yuanyuan Zhang ◽  
Renwei Zhu ◽  
Yin Zhang
Keyword(s):  
Fuel Consumption ◽  
Environmental Impacts ◽  
Life Cycle Cost ◽  
Vehicle Emissions ◽  
Selection Process ◽  
Simulation Models ◽  
Simulation Method ◽  
Economic Benefits ◽  
Average Delay ◽  
Input Variables

This study developed a procedure to conduct multiobjective evaluations in the traffic countermeasure (CM) selection process at two-way stop-controlled (TWSC) intersections. The economic benefits of three vehicle safety–related CMs were calculated considering not only safety impacts, but also operational and environmental impacts. First, for each CM, VISSIM simulation models were developed to obtain the average delay, vehicle emissions, and fuel consumption for the intersection before and after the treatment. The traffic operational impacts were calculated as the change in delay costs. The environmental impacts were calculated as the change in vehicle emissions and fuel consumption costs. Next, safety performance functions and crash modification factors were used to calculate the safety impacts as the crash reduction benefits for various CMs. Finally, the life-cycle cost method was used to combine the different components into the total benefit. The Monte Carlo simulation method was used to conduct uncertainty analysis through random sampling from probability descriptions of uncertain input variables to generate a probabilistic description of results. The findings showed, first, that the operational and environmental impacts accounted for a large proportion of the total impacts, which can significantly affect the selection of CMs. Second, the rankings of the CMs differ depending on whether the safety impacts alone are considered or different impacts are considered together. The study illustrates the detailed process of evaluating projects considering multiple objectives. The findings also explain how different objectives can have countervailing effects in improving motorist safety at TWSC intersections.

scholarly journals Designing On-Road Vehicle Test Programs for the Development of Effective Vehicle Emission Models

2005 ◽  
Vol 1941 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Theodore Younglove ◽  
George Scora ◽  
Matthew Barth
Keyword(s):  
Estimation Error ◽  
Vehicle Emission ◽  
Emission Measurement ◽  
Mobile Source ◽  
Emission Data ◽  
Data Set ◽  
Mobile Vehicle ◽  
Emission Models ◽  
Road Emission ◽  
Source Emission

Mobile source emission models for years have depended on laboratory-based dynamometer data. Recently, however, portable emission measurement systems (PEMS) have become commercially available and in widespread use, and make on-road real-world measurements possible. As a result, the newest mobile source emission models (e.g., U.S. Environmental Protection Agency's mobile vehicle emission simulator) are becoming increasingly dependent on PEMS data. Although on-road measurements are made under more realistic conditions than laboratory-based dynamometer test cycles, they introduce influencing variables that must be carefully measured for properly developed emission models. Further, test programs that simply measure in-use driving patterns of randomly selected vehicles will result in models that can effectively predict current-year emission inventories for typical driving conditions. However, when predicting more aggressive transportation operations than current typical operations (e.g., higher speeds, accelerations), the model predictions will be less certain. In this paper, various issues associated with on-road emission measurements and modeling are presented. Further, an example on-road emission data set and the reduction in estimation error through the addition of a short aggressive driving test to the in-use data are examined. On the basis of these results, recommendations are made on how to improve the on-road test programs for developing more robust emission models.

scholarly journals Vehicle Emission Computation Through Microscopic Traffic Simulation Calibrated Using Genetic Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 67-80 ◽  
Author(s):  
Yun Wei ◽  
Ying Yu ◽  
Lifeng Xu ◽  
Wei Huang ◽  
Jianhua Guo ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Vehicle Emissions ◽  
Traffic Simulation ◽  
Urban Region ◽  
Vehicle Emission ◽  
Activity Data ◽  
Microscopic Traffic Simulation ◽  
Emission Models ◽  
Vehicle Activity

Abstract Vehicle emission calculation is critical for evaluating motor vehicle related environmental protection policies. Currently, many studies calculate vehicle emissions from integrating the microscopic traffic simulation model and the vehicle emission model. However, conventionally vehicle emission models are presented as a stand-alone software, requiring a laborious processing of the simulated second-by-second vehicle activity data. This is inefficient, in particular, when multiple runs of vehicle emission calculations are needed. Therefore, an integrated vehicle emission computation system is proposed around a microscopic traffic simulation model. In doing so, the relational database technique is used to store the simulated traffic activity data, and these data are used in emission computation through a built-in emission computation module developed based on the IVE model. In order to ensure the validity of the simulated vehicle activity data, the simulation model is calibrated using the genetic algorithm. The proposed system was implemented for a central urban region of Nanjing city. Hourly vehicle emissions of three types of vehicles were computed using the proposed system for the afternoon peak period, and the results were compared with those computed directly from the IVE software with a trivial difference in the results from the proposed system and the IVE software, indicating the validity of the proposed system. In addition, it was found for the study region that passenger cars are critical for controlling CO, buses are critical for controlling CO and VOC, and trucks are critical for controlling NOx and CO2. Future work is to test the proposed system in more traffic management and control strategies, and more vehicle emission models are to be incorporated in the system.

Research on the Test for Complete-Vehicle Emission and Fuel Consumption of the Refuse Truck by Chassis Dynamometer

2013 ◽  
Vol 718-720 ◽  
pp. 1825-1830
Author(s):  
Kong Jian Qin ◽  
Chang Yuan Wang ◽  
Jia Yan ◽  
Xue Hao Liu
Keyword(s):  
Fuel Consumption ◽  
Fuel Economy ◽  
Emission Factor ◽  
Vehicle Emission ◽  
Emission Characteristics ◽  
Chassis Dynamometer ◽  
Heavy Duty ◽  
Vehicle Type ◽  
Heavy Duty Vehicle ◽  
Significant Difference

Refuse truck accounted for 70% of the sanitation vehicle, which was the major heavy duty vehicle type in city. Therefore its fuel economy and emission characteristics were under higher requirements. This research did the emission test on the chassis dynamometer by using compressed truck, testing C-WTCV and CCBC circle emission, and fuel consumption respectively. The research showed the Km fuel consumption of CCBC circle was about 1.3 times of the C-WTVC from the analysis of fuel consumption and the emission of CO2.From the analysis of emission factor, the emission of NOX and CO of the CCBC circle was both higher than the C-WTVC, respectively 1.9 times and 1.4 times. However, the emission of HC was only 36% of the C-WTVC. C-WTVC was very similar to the motor of the CCBC circle in city, however the motorway cycle and emission both had significant difference from CCBC circle.

Research Needs for Determining Spatially Resolved Subfleet Characteristics

1998 ◽  
Vol 1625 (1) ◽  
pp. 139-146 ◽  
Author(s):  
William Bachman ◽  
Jessica Granell ◽  
Randall Guensler ◽  
John Leonard
Keyword(s):  
Data Availability ◽  
Vehicle Emission ◽  
Research Needs ◽  
Research Issues ◽  
Spatially Resolved ◽  
Registration Data ◽  
Regional Registration ◽  
Emission Models ◽  
Future Emission ◽  
Mobile Emission

Future emission models will need spatially resolved subfleet characteristics to determine mobile emission inventories. The use of geographic information systems and regional registration data for developing location-specific vehicle characteristics that can feed future models is addressed. Issues regarding data availability and quality are explored to define gaps in the research that may prevent development of comprehensive and accurate estimates. As a component of a larger research project studying vehicle emission modeling, a six-step process was developed and implemented for a 100 km2 area in Atlanta. Vehicles were geocoded by using registration addresses, and vehicle characteristics were determined through a series of computer programs, commercial software, and related datasets. During the process, many research issues were identified that prevent a comprehensive assessment of spatially resolved fleet characteristics. The data and research needed to further improve the capability to generate spatially resolved subfleet characteristics were identified.

Interactive effects of vegetation, soil moisture and bulk density on depth of burning of thick organic soils

2011 ◽  
Vol 20 (3) ◽  
pp. 418 ◽  
Author(s):  
B. W. Benscoter ◽  
D. K. Thompson ◽  
J. M. Waddington ◽  
M. D. Flannigan ◽  
B. M. Wotton ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Bulk Density ◽  
Fuel Consumption ◽  
Wildland Fire ◽  
Interactive Effects ◽  
Organic Soils ◽  
Boreal Ecosystems ◽  
Modified Model ◽  
Emission Models ◽  
Moisture Profiles

The boreal biome is characterised by extensive wildfires that frequently burn into the thick organic soils found in many forests and wetlands. Previous studies investigating surface fuel consumption generally have not accounted for variation in the properties of organic soils or how this affects the severity of fuel consumption. We experimentally altered soil moisture profiles of peat monoliths collected from several vegetation types common in boreal bogs and used laboratory burn tests to examine the effects of depth-dependent variation in bulk density and moisture on depth of fuel consumption. Depth of burning ranged from 1 to 17 cm, comparable with observations following natural wildfires. Individually, fuel bulk density and moisture were unreliable predictors of depth of burning. However, they demonstrated a cumulative influence on the thermodynamics of downward combustion propagation. By modifying Van Wagner’s surface fuel consumption model to account for stratigraphic changes in fuel conditions, we were able to accurately predict the maximum depth of fuel consumption for most of the laboratory burn tests. This modified model for predicting the depth of surface fuel consumption in boreal ecosystems may provide a useful framework for informing wildland fire management activities and guiding future development of operational fire behaviour and carbon emission models.

Life-cycle assessment of ships: The effects of fuel consumption reduction and light displacement tonnage

2019 ◽  
Vol 234 (1) ◽  
pp. 143-153 ◽  
Author(s):  
Duc Tuan Dong ◽  
Wei Cai
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Fuel Consumption ◽  
Environmental Impacts ◽  
Assessment Method ◽  
Environmental Indicators ◽  
Environmental Benefits ◽  
Fuel Consumption Reduction ◽  
Consumption Reduction ◽  
The Impact

Life-cycle assessment has been widely applied in many industry sectors for years and there are some applications of this method in the shipping sector. Fuel consumption and material consumption are considered as crucial factors in the life cycle of ship. This study uses the life-cycle assessment method to show the effects of fuel consumption reduction and light displacement tonnage on the environmental performance of ships. This is done by comparing the environmental impacts of 25 investigated scenarios with different fuel consumption and light displacement tonnage. CML2001 methodology is used to evaluate the impact assessment and the results are calculated using GaBi software. The results show that fuel consumption reduction could cut down the environmental impacts. However, some scenarios are not environmentally beneficial due to the increase in light displacement tonnage. The effects of fuel consumption and light displacement tonnage on 12 CML2001 environmental indicators are different. It is recommended that the life-cycle assessment method should be used to fully assess the environmental impacts of ships before applying any techniques in order to achieve the environmental benefits.

scholarly journals THE IMPACT OF DRIVING CONDITIONS ON LIGHT-DUTY VEHICLE EMISSIONS IN REAL-WORLD DRIVING

Transport ◽  
2020 ◽  
Vol 35 (4) ◽  
pp. 379-388
Author(s):  
Dong Guo ◽  
Jinbao Zhao ◽  
Yi Xu ◽  
Feng Sun ◽  
Kai Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Real World ◽  
Vehicle Emissions ◽  
Emission Rate ◽  
Vehicle Emission ◽  
Road Test ◽  
Light Duty ◽  
Emission Models ◽  
Light Duty Vehicle ◽  
Driving Conditions

To accurately estimate the effect of driving conditions on vehicle emissions, an on-road light-duty vehicle emission platform was established based on OEM-2100TM, and each second data of mass emission rate corresponding to the driving conditions were obtained through an on-road test. The mass emission rate was closely related to the velocity and acceleration in real-world driving. This study shows that a high velocity and acceleration led to high real-world emissions. The vehicle emissions were the minimum when the velocity ranged from 30 to 50 km/h and the acceleration was less than 0.5 m/s2. Microscopic emission models were established based the on-road test, and single regression models were constructed based on velocity and acceleration separately. Binary regression and neural network models were established based on the joint distribution of velocity and acceleration. Comparative analysis of the accuracy of prediction and evaluation under different emission models, total error, second-based error, related coefficient, and sum of squared error were considered as evaluation indexes to validate different models. The results show that the three established emission models can be used to make relatively accurate prediction of vehicle emission on actual roads. The velocity regression model can be easily combined with traffic simulation models because of its simple parameters. However, the application of neural network model is limited by a complex coefficient matrix.

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