scholarly journals An overview of emissions of reactive nitrogen compounds from modern light duty vehicles featuring SI engines

2014 ◽  
Vol 159 (4) ◽  
pp. 48-53
Author(s):  
Piotr BIELACZYC ◽  
Andrzej SZCZOTKA ◽  
Joseph WOODBURN
Keyword(s):  
Reactive Nitrogen ◽  
Nitrogen Compounds ◽  
Exhaust Gas ◽  
Environmental Aspects ◽  
Technical Literature ◽  
Research Directions ◽  
Light Duty ◽  
Si Engines ◽  
Light Duty Vehicles ◽  
The Impact

This paper examines emissions of reactive nitrogen compounds in the exhaust gas flux of vehicles featuring spark ignition (SI) engines. A range of technical, legal and environmental aspects are considered. A discussion of the fundamentals of the phenomenona of emission of these compounds is presented, together with a brief summary of the negative environmental impacts of these gases. Selected data obtained during chassis dynamometer testing at BOSMAL are presented, together with certain important observations presented in the technical literature. The reader is directed to recent publications of note for further information on emissions to the less well known reactive nitrogen compounds, namely NH3 and N2O. The orders of magnitude of the various reactive nitrogen compounds found in the exhaust gas emitted from SI engines are briefly considered and commented upon. Data are presented on the impact of different fuel types used in SI engines and the reader is directed to various publications on that subject. Finally, important research directions (both current and future) are identified.

scholarly journals Monte Carlo Simulation Methodology to Assess the Impact of Ambient Wind on Emissions from a Light-Commercial Vehicle Running on the Worldwide-Harmonized Light-Duty Vehicles Test Cycle (WLTC)

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 661
Author(s):  
Alexandros T. Zachiotis ◽  
Evangelos G. Giakoumis
Keyword(s):  
Monte Carlo Simulation ◽  
Energy Consumption ◽  
Commercial Vehicle ◽  
Ambient Wind ◽  
Simulation Methodology ◽  
Road Load ◽  
Light Duty ◽  
Light Commercial Vehicle ◽  
Light Duty Vehicles ◽  
The Impact

A Monte Carlo simulation methodology is suggested in order to assess the impact of ambient wind on a vehicle’s performance and emissions. A large number of random wind profiles is generated by implementing the Weibull and uniform statistical distributions for wind speed and direction, respectively. Wind speed data are drawn from eight cities across Europe. The vehicle considered is a diesel-powered, turbocharged, light-commercial vehicle and the baseline trip is the worldwide harmonized light-duty vehicles WLTC cycle. A detailed engine-mapping approach is used as the basis for the results, complemented with experimentally derived correction coefficients to account for engine transients. The properties of interest are (engine-out) NO and soot emissions, as well as fuel and energy consumption and CO2 emissions. Results from this study show that there is an aggregate increase in all properties, vis-à-vis the reference case (i.e., zero wind), if ambient wind is to be accounted for in road load calculation. Mean wind speeds for the different sites examined range from 14.6 km/h to 24.2 km/h. The average increase in the properties studied, across all sites, ranges from 0.22% up to 2.52% depending on the trip and the property (CO2, soot, NO, energy consumption) examined. Based on individual trip assessment, it was found that especially at high vehicle speeds where wind drag becomes the major road load force, CO2 emissions may increase by 28%, NO emissions by 22%, and soot emissions by 13% in the presence of strong headwinds. Moreover, it is demonstrated that the adverse effect of headwinds far exceeds the positive effect of tailwinds, thus explaining the overall increase in fuel/energy consumption as well as emissions, while also highlighting the shortcomings of the current certification procedure, which neglects ambient wind effects.

Fuel Use and CO2 Emissions Under Uncertainty From Light-Duty Vehicles in the U.S. to 2050

2011 ◽  
Author(s):  
Parisa Bastani ◽  
John B. Heywood ◽  
Chris Hope
Keyword(s):  
Co2 Emissions ◽  
Alternative Fuels ◽  
Fuel Use ◽  
Policy Makers ◽  
Light Duty ◽  
Co2 Equivalent ◽  
The Future ◽  
Light Duty Vehicles ◽  
The Impact ◽  
The U.S

On-road transportation contributes 22% of the total CO2 emissions and more than 44% of oil consumption in the U.S. Technological advancements and use of alternative fuels are often suggested as ways to reduce these emissions. However, many parameters and relationships that determine the future characteristics of the light-duty vehicle fleet and how they change over time are inherently uncertain. Policy makers need to make decisions today given these uncertainties, to shape the future of light-duty vehicles. Decision makers thus need to know the impact of uncertainties on the outcome of their decisions and the associated risks. This paper explores a carefully constructed detailed pathway that results in a significant reduction in fuel use and GHG emissions in 2050. Inputs are assigned realistic uncertainty bounds, and the impact of uncertainty on this pathway is analyzed. A novel probabilistic fleet model is used here to quantify the uncertainties within advanced vehicle technology development, and life-cycle emissions of alternative fuels and renewable sources. Based on the results from this study, the expected fuel use is about 500 and 350 billion litres gasoline equivalent, with a standard deviation of about 40 and 80 billion litres in years 2030 and 2050 respectively. The expected CO2 emissions are about 1,360 and 840 Mt CO2 equivalent with a spread of about 130 and 260 Mt CO2 equivalent in 2030 and 2050 respectively. Major contributing factors in determining the future fuel consumption and emissions are also identified and include vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel consumption of naturally-aspirated engines, and percentage of gasoline displaced by cellulosic ethanol. This type of analysis allows policy makers to better understand the impact of their decisions and proposed policies given the technological and market uncertainties that we face today.

Fuel Use and CO2 Emissions Under Uncertainty From Light-Duty Vehicles in the U.S. to 2050

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Parisa Bastani ◽  
John B. Heywood ◽  
Chris Hope
Keyword(s):  
Co2 Emissions ◽  
Alternative Fuels ◽  
Fuel Use ◽  
Policy Makers ◽  
Light Duty ◽  
Co2 Equivalent ◽  
The Future ◽  
Light Duty Vehicles ◽  
The Impact ◽  
The U.S

On-road transportation contributes 22% of the total CO2 emissions and more than 44% of oil consumption in the U.S. technological advancements and use of alternative fuels are often suggested as ways to reduce these emissions. However, many parameters and relationships that determine the future characteristics of the light-duty vehicle (LDV) fleet and how they change over time are inherently uncertain. Policy makers need to make decisions today given these uncertainties, to shape the future of light-duty vehicles. Decision makers thus need to know the impact of uncertainties on the outcome of their decisions and the associated risks. This paper explores a carefully constructed detailed pathway that results in a significant reduction in fuel use and greenhouse gases (GHG) emissions in 2050. Inputs are assigned realistic uncertainty bounds, and the impact of uncertainty on this pathway is analyzed. A novel probabilistic fleet model is used here to quantify the uncertainties within advanced vehicle technology development, and life-cycle emissions of alternative fuels and renewable sources. Based on the results from this study, the expected fuel use is about 500 and 350 × 109 l gasoline equivalent, with a standard deviation of about 40 and 80 × 109 l in years 2030 and 2050, respectively. The expected CO2 emissions are about 1360 and 840 Mt CO2 equivalent with a spread of about 130 and 260 Mt CO2 equivalent in 2030 and 2050, respectively. Major contributing factors in determining the future fuel consumption and emissions are also identified and include vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel consumption of naturally aspirated engines, and percentage of gasoline displaced by cellulosic ethanol. This type of analysis allows policy makers to better understand the impact of their decisions and proposed policies given the technological and market uncertainties that we face today.

Potential of energy recuperation in the exhaust gas of state of the art light duty vehicles with thermoelectric elements

Fuel ◽  
2018 ◽  
Vol 224 ◽  
pp. 271-279 ◽  
Author(s):  
Thibaut Durand ◽  
Panayotis Dimopoulos Eggenschwiler ◽  
Yinglu Tang ◽  
Yujun Liao ◽  
Daniel Landmann
Keyword(s):  
State Of The Art ◽  
Exhaust Gas ◽  
Energy Recuperation ◽  
Light Duty ◽  
Light Duty Vehicles

Analysis of Driving Cycles for Emission Test of Light-Duty Vehicles in China

2012 ◽  
Vol 616-618 ◽  
pp. 1154-1160
Author(s):  
Jin Lin Xue
Keyword(s):  
Real World ◽  
Gasoline Engine ◽  
The Real ◽  
Driving Behaviors ◽  
Traffic Conditions ◽  
Driving Cycles ◽  
Driving Pattern ◽  
Light Duty ◽  
Light Duty Vehicles ◽  
The Impact

The driving cycles employed to measure the emissions from automotive vehicles should adequately represent the real-world driving pattern of the vehicle to provide the most realistic estimation of emissions levels. The driving cycles used for light-duty gasoline engine vehicles in China were reviewed in this paper firstly. Then the impact of various factors, such as driving behaviors, driving conditions, road conditions, traffic conditions, on real-world emission levels were analyzed. Finally, the shortages of the existing driving cycles were pointed out. It can be concluded that the emissions levels from automotive vehicles are underestimated because of the characteristics of the existing drive cycles, so it is urgent to research and develop new driving cycles to fit the situation of China.

scholarly journals Estimation of Real-world Fuel Consumption Rate of Light-duty Vehicles Based on Big Data

2021 ◽  
Author(s):  
Isabella Yunfei Zeng ◽  
Shiqi Tan ◽  
Jianliang Xiong ◽  
Xuesong Ding ◽  
Yawen Li ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Consumption Rate ◽  
Effective Control ◽  
Fuel Consumption Rate ◽  
Light Duty ◽  
Light Duty Vehicle ◽  
Light Duty Vehicles ◽  
The Impact ◽  
Engine Power

Private vehicle travel is the most basic mode of transportation, and the effective control of the real-world fuel consumption rate of light-duty vehicles plays a vital role in promoting sustainable economic development as well as achieving a green low-carbon society. Therefore, the impact factors of individual carbon emission must be elucidated. This study builds five different models to estimate real-world fuel consumption rate of light-duty vehicles in China. The results reveal that the Light Gradient Boosting Machine (LightGBM) model performs better than the linear regression, Naïve Bayes regression, Neural Network regression, and Decision Tree regression models, with mean absolute error of 0.911 L/100 km, mean absolute percentage error of 10.4%, mean square error of 1.536, and R squared (R2) of 0.642. This study also assesses a large number of factors, from which three most important factors are extracted, namely, reference fuel consumption rate value, engine power and light-duty vehicle brand. Furthermore, a comparative analysis reveals that the vehicle factors with greater impact on real-world fuel consumption rate are vehicle brand, engine power, and engine displacement. Average air pressure, average temperature, and sunshine time are the three most important climate factors.

scholarly journals Correcting high-frequency losses of reactive nitrogen flux measurements

2020 ◽  
Vol 13 (6) ◽  
pp. 2923-2948
Author(s):  
Pascal Wintjen ◽  
Christof Ammann ◽  
Frederik Schrader ◽  
Christian Brümmer
Keyword(s):  
High Frequency ◽  
Mixed Forest ◽  
Nitrogen Compound ◽  
Power Spectra ◽  
Reactive Nitrogen ◽  
Nitrogen Compounds ◽  
Forest Site ◽  
Atmospheric Nitrogen ◽  
Flux Measurements ◽  
The Impact

Abstract. Flux measurements of reactive nitrogen compounds are of increasing importance to assess the impact of unintended emissions on sensitive ecosystems and to evaluate the efficiency of mitigation strategies. Therefore, it is necessary to determine the exchange of reactive nitrogen gases with the highest possible accuracy. This study gives insight into the performance of flux correction methods and their usability for reactive nitrogen gases. The eddy-covariance (EC) technique is today widely used in experimental field studies to measure land surface–atmosphere exchange of a variety of trace gases. In recent years, applying the EC technique to reactive nitrogen compounds has become more important since atmospheric nitrogen deposition influences the productivity and biodiversity of (semi)natural ecosystems and their carbon dioxide (CO2) exchange. Fluxes, which are calculated by EC, have to be corrected for setup-specific effects like attenuation in the high-frequency range. However, common methods for correcting such flux losses are mainly optimized for inert greenhouse gases like CO2 and methane or water vapor. In this study, we applied a selection of correction methods to measurements of total reactive nitrogen (ΣNr) conducted in different ecosystems using the Total Reactive Atmospheric Nitrogen Converter (TRANC) coupled to a chemiluminescence detector (CLD). Average flux losses calculated by methods using measured cospectra and ogives were approximately 26 %–38 % for a seminatural peatland and about 16 %–22 % for a mixed forest. The investigation of the different methods showed that damping factors calculated with measured heat and gas flux cospectra using an empirical spectral transfer function were most reliable. Flux losses of ΣNr with this method were on the upper end of the median damping range, i.e., 38 % for the peatland site and 22 % for the forest site. Using modified Kaimal cospectra for damping estimation worked well for the forest site but underestimated damping for the peatland site by about 12 %. Correction factors of methods based on power spectra or on site-specific and instrumental parameters were mostly below 10 %. Power spectra of ΣNr were heavily affected – likely by white noise – and deviated substantially at lower frequencies from the respective temperature (power) spectra. Our study supports the use of an empirical method for estimating flux losses of ΣNr or any reactive nitrogen compound and the use of locally measured cospectra.

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