scholarly journals CORRELATION ANALYSIS OF DRIVING CONDITIONS AND ON-ROAD EMISSIONS TRENDS FOR VEHICLES

2017 ◽  
pp. 63-72
Author(s):  
Jawad Hilmi Al-rifai
Keyword(s):  
Vehicle Emissions ◽  
Measurement Unit ◽  
Vehicle Speed ◽  
Emission Rates ◽  
Gas Emissions ◽  
The Road ◽  
Grade Parameter ◽  
Road Grade ◽  
Driving Conditions ◽  
The Impact

This paper presents the impact of road grade, vehicle speed, number of vehicles and vehicle type on vehicle emissions. ANOVA analyses were conducted among different driving conditions and vehicle emissions to discover the significant effects of driving conditions on measured emission rates. This study is intended to improve the understanding of vehicle emission levels in Jordan. Gas emissions in real-world driving conditions were measured by a portable emissions measurement unit over six sections of an urban road. The road grade, speed, type and number of vehicles were found to have a significant influence on the rate of gas emissions. Road grade and diesel-fueled vehicles were positively correlated with average emission rates. The average emission rates were higher at speeds ranging between 60–69 km/hr than at three other speed ranges. The results of ANOVA showed a strong and consistent regression between rates of emissions measured and grade, speed and diesel vehicle parameters. The grade parameter contributed the most to the rate of emissions compared to other parameters. Gasoline vehicles contributed the least.

Minimizing Cost of Highway Maintenance Considering the Impact of Vehicle Emissions using an Artificial Bee Colony Approach

2020 ◽  
Vol 2674 (6) ◽  
pp. 60-72
Author(s):  
Celina Semaan ◽  
Steven Chien ◽  
Ching-Jung Ting
Keyword(s):  
Vehicle Emissions ◽  
Artificial Bee Colony ◽  
Motor Vehicle ◽  
Well Being ◽  
Work Zone ◽  
Emission Rates ◽  
Traffic Demand ◽  
Abc Algorithm ◽  
Bee Colony ◽  
The Impact

The increasing traffic demand has reduced the efficiency of road networks and intensified the maintenance need for mobility and safety, increasing vehicle emissions, reducing air quality, and affecting climate change. To mitigate the negative impacts of work zone activities, a reliable method that can optimize spatio-temporal work zone activities is desirable. Previous studies have aimed to minimize the total cost, including maintenance, user delay, and accident costs, yet the associated environmental impact has been neglected. This study aims to optimize work zone activities using the artificial bee colony (ABC) algorithm, considering the cost of vehicle emissions in addition to the aforementioned costs for an environmentally sustainable optimization. MOtor Vehicle Emission Simulator (MOVES) is applied to calculate emission rates. The results show that the ABC algorithm is very efficient to search for the optimal solution that yields the minimum cost taking into account the well-being of the environment.

scholarly journals Capturing the Variability in Instantaneous Vehicle Emissions Based on Field Test Data

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 765
Author(s):  
Zhiqiang Zhai ◽  
Ran Tu ◽  
Junshi Xu ◽  
An Wang ◽  
Marianne Hatzopoulou
Keyword(s):  
Vehicle Emissions ◽  
Specific Power ◽  
Vehicle Speed ◽  
Emission Rates ◽  
Traffic Emission ◽  
Catalyst Temperature ◽  
Torque Load ◽  
Emission Models ◽  
Vehicle Activity ◽  
Activity Catalyst

Emission models are important tools for traffic emission and air quality estimates. Existing instantaneous emission models employ the steady-state “engine emissions map” to estimate emissions for individual vehicles. However, vehicle emissions vary significantly, even under the same driving conditions. Variability in the emissions at a specific driving condition depends on various influencing factors. It is important to gain insight into the effects of these factors, to enable detailed modeling of individual vehicle emissions. This study employs a portable emissions measurement system (PEMS), to collect vehicle emissions including the corresponding parameters of engine condition, vehicle activity, catalyst temperature, geography, and meteorology, to analyze the variability in emission rates as a function of those factors, across different vehicle specific power (VSP) categories. We observe that carbon dioxide, carbon monoxide, nitrogen oxides, and particle number emissions are strongly correlated with engine parameters (engine speed, torque, load, and air-fuel ratio) and vehicle activity parameters (vehicle speed and acceleration). In the same VSP bin, emissions per second on highways and ramps are higher than those on arterial roads, and the emissions when the vehicle is traveling downhill tend to be higher than the emissions during uphill traveling, because of higher observed speeds and accelerations. Morning emissions are higher than afternoon emissions, due to lower temperatures.

scholarly journals Evaluating the Dynamic Response of the Bridge-Vehicle System considering Random Road Roughness Based on the Moment Method

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fan Feng ◽  
Fanglin Huang ◽  
Weibin Wen ◽  
Zhe Liu ◽  
Xiang Liu
Keyword(s):  
Random Process ◽  
Moment Method ◽  
System Response ◽  
Vehicle Speed ◽  
The Road ◽  
Bridge Span ◽  
Road Roughness ◽  
System Vibration ◽  
The Moment ◽  
The Impact

The bridge-vehicle interaction (BVI) system vibration is caused by the vehicles passing through the bridge. The road roughness has a great impact on the system vibration. In this regard, poor road roughness is known to affect the comfort of the vehicle crossing the bridge and aggravate the fatigue damage of the bridge. Road roughness is usually regarded as a random process in numerical calculation. To fully consider the influence of road roughness randomness on the response of the BVI system, a random BVI model was established. Thereafter, the random process of road roughness was expressed by Karhunen–Loeve expansion (KLE), after which the moment method was used to calculate the maximum probability value of the BVI system response. The proposed method has higher accuracy and efficiency than the Monte Carlo simulation (MCS) calculation method. Subsequently, the influences of vehicle speed, roughness grade, and bridge span on the impact factor (IMF) were analyzed. The results show that the road roughness grade has a greater impact on the bridge IMF than the bridge span and vehicle speed.

scholarly journals Road Pricing Effect on the Emission of Traffic Pollutants, a Case Study in Tehran

2016 ◽  
Vol 2 (7) ◽  
pp. 306-315 ◽  
Author(s):  
Mansour Hadji Hosseinlou ◽  
Abbas Zolfaghari ◽  
Mahdi Yazdanpanah
Keyword(s):  
Fuel Consumption ◽  
Traffic Flow ◽  
Traffic Management ◽  
Stated Preference ◽  
Road Pricing ◽  
Simulation Software ◽  
Emission Rates ◽  
The Road ◽  
Fuel Consumption Rate ◽  
The Impact

Road pricing is one of the main purposes of traffic management policies in order to reduce personal car use. Understanding the behaviour of drivers under the impact of the road pricing policy, can assist transportation planners in making better and more efficient decisions. This research aims at investigating the reactions of private car users to road pricing using stated preference (SP) method on the one hand, and on the other hand, studies the road pricing effect on traffic flow and pollutants. To this aim, the acceptance rate of pricing, which is obtained from modeling of survey data, as well as real traffic flow data in Shahid Hemmat Highway in Tehran, Iran, are applied as the simulation software input. Based on the results of this research, at the lowest price (TN11000), the contribution of toll acceptance is equal to 64/91 percent. The fuel consumption rate at this price decreases to 49/91% and the emission rate of CO2, NOx, particle material (PM) and volatile organic compounds (VOCs) pollutants decrease to 56.82%, 49.46%, 36.8% and 63.17%, respectively. At the highest price (TN10000), toll acceptability, fuel consumption, CO2, NOx, PM and VOC emission rates decrease to 5.47%, 3.57%, 3.98%, 2.85%, 1.22% and 4.86%, respectively.

scholarly journals Assessment of the Road Traffic Air Pollution in Urban Contexts: A Statistical Approach

2021 ◽  
Author(s):  
Concettina Marino ◽  
Antonino Nucara ◽  
Maria Francesca Panzera ◽  
Matilde Pietrafesa
Keyword(s):  
Air Pollution ◽  
Statistical Approach ◽  
Road Traffic ◽  
Pollutant Emission ◽  
Vehicle Speed ◽  
Emission Rates ◽  
Urban Context ◽  
The Road ◽  
Specific Category ◽  
Yearly Average

In the article a statistical approach to the assessment of the emission rates discharged by the road traffic in a spatial context is proposed. It exploits an indicator, the Yearly Average Vehicle, representing the pollutant emission rate of the average vehicle belonging to a specific category, and considers the statistical variability of most of the involved traffic parameters: vehicle speed and mileage travelled in the considered time period. Finally, indicators, assessing both the most probable value among the possible emission rates and the extent of their variability range, are proposed. They may also be used to underpin decision making-processes, when the effects of different policies addressing air pollution issues, are to be evaluated. Therefore, they are suitable for the analysis supporting urban planning activities, with a view to addressing and mitigating the effects and the consequences of pollution due to the transportation sector of the urban context.

scholarly journals Assessment of Landfill Odorous Gas Effect on Surrounding Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Si-liang Shen ◽  
Bin-hai Wu ◽  
Hui Xu ◽  
Zhen-ying Zhang
Keyword(s):  
Emission Rate ◽  
In Situ Monitoring ◽  
Emission Rates ◽  
Gas Emission ◽  
The Road ◽  
On The Road ◽  
The Impact ◽  
Odor Dispersion ◽  
Gas Effect

Landfill odorous gas emission has been a serious environmental problem, especially for the residents or passersby on the road near the landfill. In this paper, in situ monitoring and the numerical CALPUFF model were adopted to analyze the odor nuisance problem caused by municipal solid waste (MSW) degradation in a large landfill. The static chamber technique was used to measure the odorous gas emission rate on the working area, temporary cover area, and final cover area of the landfill during Dec. 2016 and Apr. 2018. The results showed that the emission rate of H2S on the working area varied from 0.003 mg/m2/min to 0.98 mg/m2/min, and it was positively correlated with the ambient temperature. The emission of H2S varied between 0.125 kg/h and 1.09 kg/h on the working area, and it varied between 9.2 × 10−6 kg/h and 6.8 × 10−4 kg/h on the temporary cover when considering the impact of the holes in a high-density polyethylene (HDPE) membrane, and it was negligible on the final cover. The contribution rates of H2S emission in the whole landfill were 90.79%∼98.59% and 0.0008%∼0.52% for the working area and the temporary cover area, respectively. The numerical simulation showed that wind velocity and gas emission rates were the critical factors that affect odor dispersion. To limit the H2S-influenced area within the landfill site, proper engineering measures should be taken to ensure the H2S emission rate of lower than 15% of its original value.

scholarly journals Analysis of the Impact of Traffic Violation Monitoring on the Vehicle Speeds of Urban Main Road: Taking China as an Example

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Fuquan Pan ◽  
Yongzheng Yang ◽  
Lixia Zhang ◽  
Changxi Ma ◽  
Jinshun Yang ◽  
...  
Keyword(s):  
Probability Density ◽  
Road Traffic ◽  
Maximum Speed ◽  
Vehicle Speed ◽  
Main Road ◽  
The Road ◽  
Before And After ◽  
Traffic Violation ◽  
The Impact ◽  
Monitoring Area

In recent years, there are more and more applications of traffic violation monitoring in some countries. The present work aims to analyze the vehicle speeds nearby road traffic violation monitoring area on urban main roads and find out the impact of road traffic violation monitoring on the vehicle speeds. A representative urban main road section was selected and the traffic flow was recorded by camera method. The vehicle speeds before, within, and after the road traffic violation monitoring area were obtained by the calculation method. The speed data was classified and processed by SPSS software and mathematical method to establish the vehicle speed probability density models before, within, and after the road traffic violation monitoring area. The results show that the average speed and maximum speed within the traffic violation monitoring area are significantly slower than those before and after the traffic violation monitoring area. 70.1% of the vehicles before the road traffic violation monitoring area were speeding, and 80.2% of the vehicles after the road traffic violation monitoring area were speeding, while within the road traffic violation monitoring area, the speeding vehicles were reduced to 15.9%. When vehicles pass through the road traffic violation monitoring area, the vehicle speeds tend to first decrease and subsequently increase. In its active area, road traffic violation monitoring can effectively regulate driving behaviors and reduce speeding, but this effect is limited to the vicinity of the traffic violation monitoring. The distribution of vehicle speeds can be calculated from vehicle speed probability density models.

Bayesian approach in estimating the road grade impact on vehicle speed and acceleration on freeways

2020 ◽  
Vol 16 (3) ◽  
pp. 602-625
Author(s):  
Haobing Liu ◽  
Michael O. Rodgers ◽  
Fang “Cherry” Liu ◽  
Randall Guensler
Keyword(s):  
Bayesian Approach ◽  
Vehicle Speed ◽  
The Road ◽  
Road Grade

scholarly journals Driving Safety Analysis Using Grid-Based Water-Filled Rut Depth Distribution

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiao Yan ◽  
Hongwei Zhang ◽  
Bing Hui
Keyword(s):  
Water Depth ◽  
Three Dimensional ◽  
Element Model ◽  
Road Surface ◽  
Driving Safety ◽  
Vehicle Speed ◽  
Adhesion Coefficient ◽  
The Road ◽  
Left And Right ◽  
The Impact

The water accumulated in the rutted road sections poses a threat to the safety of vehicles. Water-filled ruts will cause partial or complete loss of the friction between tires and the road surface, leading to driving safety hazards such as hydroplaning and sliding. At present, the maximum water depth of left and right ruts is mostly adopted to analyze the safety of water-filled ruts, ignoring the uneven change of ruts in the driving direction and the cross-section direction, which cannot fully reflect the actual impact of asymmetric or uneven longitudinal ruts on the vehicle. In order to explore the impact of water-filled ruts on driving safety, a three-dimensional (3D) tire-road finite element model is established in this paper to calculate the adhesion coefficient between the tire and the road surface. Moreover, a model of the 3D water-filled rut-adhesion coefficient vehicle is established and simulated by the dynamics software CarSim. In addition, the influence of the water depth difference between the left and right ruts on the driving safety is quantitatively analyzed, and a safety prediction model for the water-filled rut is established. The results of the case study show that (1) the length of dangerous road sections based on vehicle skidding is longer than that based on hydroplaning, and the length of dangerous road sections based on hydroplaning is underestimated by 9.4%–100%; (2) as the vehicle speed drops from 120 km/h to 80 km/h, the length of dangerous road sections obtained based on vehicle sliding analysis is reduced by 93.8%. Therefore, in order to ensure driving safety, the speed limit is controlled within 80 km/h to ensure that the vehicle will not skid. The proposed method provides a good foundation for the vehicles to actively respond to the situation of the water-filled road section.

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