Use of a vehicle-modelling tool for predicting CO2 emissions in the framework of European regulations for light goods vehicles

The reduction of CO₂ emissions and fuel consumption from road transportation constitutes an important pillar of the EU commitment for implementing the Kyoto Protocol. Efforts to monitor and limit CO₂ emissions from vehicles can effectively be supported by the use of vehicle modelling tools. This paper presents the application of such a tool for predicting CO₂ emissions of vehicles under different operating conditions and shows how the results from simulations can be used for supporting policy analysis and design aiming at further reductions of the CO₂ emissions. For this purpose, the case of light duty goods (N1 category) vehicle CO₂ emissions control measures adopted by the EU is analysed. In order to understand how certain design and operating aspects affect fuel consumption, a number of N1 vehicles were simulated with ADVISOR for various operating conditions and the numerical results were validated against chassis dynamometer tests. The model was then employed for analysing and evaluating the new EU legislative framework that addresses CO₂ emissions from this vehicle class. The results of this analysis have shown the weaknesses of the current regulations and revealed new potential in CO₂ emissions control. Finally the TREMOVE model was used for simulating a possible scenario for reducing CO₂ emissions at fleet level.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Characteristics of Real-World Vehicular Emissions in Chinese Cities

Abstract

On-board emission measurements were performed on 49 light-duty gasoline vehicles in seven cities of China. Vehicle-specific power mode distribution and emission characteristics were analyzed based on the data collected. The results of our study show that there were significant differences in different types of roads. The emission factors and fuel consumption rates on arterial roads and residential roads were approximately 1.4–2 times those on freeways. The carbon monoxide, hydrocarbon, and nitrogen oxides emission factors of Euro II vehicles were on average 86.2, 88.2, and 64.5% lower than those of carburetor vehicles, respectively. The new vehicle emission standards implemented in China had played an important role in reducing individual vehicle emissions. More comprehensive measures need to be considered to reduce the total amount of emissions from vehicles.     

Emissions from India's transport sector: Statewise synthesis

A decentralized emission inventories are prepared for road transport sector of India in order to design and implement suitable technologies and policies for appropriate mitigation measures. Globalization and liberalization policies of the government in 90's have increased the number of road vehicles nearly 92.6% from 1980–1981 to 2003–2004. These vehicles mainly consume non-renewable fossil fuels, and are a major contributor of green house gases, particularly CO₂ emission. This paper focuses on the statewise road transport emissions (CO₂, CH₄, CO, NO_x, N₂O, SO₂, PM and HC), using region specific mass emission factors for each type of vehicles. The country level emissions (CO₂, CH₄, CO, NO_x, N₂O, SO₂ and NMVOC) are calculated for railways, shipping and airway, based on fuel types. In India, transport sector emits an estimated 258.10 Tg of CO₂, of which 94.5% was contributed by road transport (2003–2004). Among all the states and Union Territories, Maharashtra's contribution is the largest, 28.85 Tg (11.8%) of CO₂, followed by Tamil Nadu 26.41 Tg (10.8%), Gujarat 23.31 Tg (9.6%), Uttar Pradesh 17.42 Tg (7.1%), Rajasthan 15.17 Tg (6.22%) and, Karnataka 15.09 Tg (6.19%). These six states account for 51.8% of the CO₂ emissions from road transport.     

Further Validation of Artificial Neural Network-Based Emissions Simulation Models for Conventional and Hybrid Electric Vehicles

Abstract

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO₂] and oxides of nitrogen [NO_x]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO₂ and NO_x in the case of a class-8 truck but were more accurate as the truck weight increased.     

An Evaluation of the Aerometric Probe

Exhaust emissions from automobiles in a low-altitude city will be compared with emissions from autos in a high-altitude city (Denver, Colorado). The comparison will be based on samples collected from thirty five cars driven under actual road conditions in each city.

Results will be discussed on the basis of CO, CO₂ and hydrocarbon concentrations versus average route speeds and on pounds of CO, CO₂ and hydrocarbons, emitted per mile, versus average route speed.     

Evaluation of particulate matter emissions from non-passenger diesel vehicles in Qatar

ABSTRACT

Road traffic is one of the main sources of particulate matter (PM) in the atmosphere. Despite its importance, there are significant challenges in the quantitative evaluation of its contribution to airborne concentrations. In order to propose effective mitigation scenarios, the proportions of PM traffic emissions, whether they are exhaust or non-exhaust emissions, should be evaluated for any given geographical location. In this work, we report on the first study to evaluate particulate matter emissions from all registered heavy duty diesel vehicles in Qatar. The study was applied to an active traffic zone in urban Doha. Dust samples were collected and characterized for their shape and size distribution. It was found that the particle size ranged from few to 600 μm with the dominance of small size fraction (less than 100 μm). In-situ elemental composition analysis was conducted for side and main roads traffic dust, and compared with non-traffic PM. The results were used for the evaluation of the enrichment factor and preliminary source apportionment. The enrichment factor of anthropogenic elements amounted to 350. The traffic source based on sulfur elemental fingerprint was almost 5 times higher in main roads compared with the samples from non-traffic locations. Moreover, PM exhaust and non-exhaust emissions (tyre wear, brake wear and road dust resuspension) were evaluated. It was found that the majority of the dust was generated from tyre wear with 33% followed by road dust resuspension (31%), brake wear (19%) and then exhaust emissions with 17%. The low contribution of exhaust PM₁₀ emissions was due to the fact that the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies.

Implication: This study reports on the first results related to the evaluation of PM emission from all registered diesel heavy duty vehicles in Qatar. In-situ XRF elemental analysis from main, side roads as well as non-traffic dust samples was conducted. Several characterization techniques were implemented and the results show that the majority of the dust was generated from tyre wear, followed by road dust resuspension and then brake wear; whereas exhaust emissions were tremendously reduced since the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies. This implies that policy makers should place stringent measures on old vehicle license renewals and encourage the use of metro and public transportation.     

Idle Emissions from Heavy-Duty Diesel Vehicles: Review and Recent Data

Abstract

Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NO_x), particulate matter (PM), and carbon dioxide (CO₂) have been reported. Idle CO₂ emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted [~20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NO_x, 1 g/hr of PM, and 4636 g/hr of CO₂ during idle. MFI equipped vehicles emitted ~35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NO_x, 4 g/hr of PM, and 4484 g/hr of CO₂, on average, during idle. Vehicles with EFI emitted less idleCO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NO_x, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO₂ and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO₂, NO_x, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO₂ and NO_x emissions and fuel consumption increased by >150%, whereas PM and HC emissions increased by ~100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NO_x, and PM emissions and consumed fuel at only 75%of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.     

Limited provision of roads as a bottleneck on vehicle CO2 emissions in Asia: an international comparison of national trends

This paper explores the relationship between road infrastructure, economic growth and road CO₂ emissions. The basic premise is that many developing nations have achieved sufficient wealth to generate substantial demand for road vehicles, but that actual use is constrained by limited provision of surfaced roads. Our main result is that for comparable levels of income (GDP/capita), CO₂ emissions per length of paved road are far higher in rapidly developing Asia as compared to the USA. These findings suggest existence of an 'infrastructure bottleneck', that when relieved, may influence the future trajectory of road transport CO₂ emissions in developing Asia.     

Testing Re-entrained Aerosol Kinetic Emissions from Roads : a new approach to infer silt loading on roadways

PM₁₀ and PM_2.5 emissions from roadways are currently estimated using the silt loading on the road surface as a surrogate for the emissions potential of road dust. While the United States Environmental Protection Agency prescribes this method in AP-42, there is considerable cost associated with silt loading measurements; it is feasible to sample only a small portion of a roadway network. A new approach for measuring the concentration of suspendable PM₁₀ above road surfaces has been developed to obtain a more spatially representative estimate of a road's potential to emit dust. The Testing Re-entrained Aerosols Kinetic Emissions from Roads (TRAKER) system uses real-time aerosol sensors mounted on a vehicle to measure the concentration of dust suspended from the road while the vehicle is in motion. When coupled with a Global Positioning System (GPS) instrument, TRAKER can be used to efficiently survey the changes in suspendable particles due to varying road conditions over a large spatial domain.In a recent study on paved roads in Las Vegas, the TRAKER system was compared with collocated silt loading measurements. The TRAKER system was also used to survey the relative amounts of suspendable road dust on approximately 300 miles of paved roads. The system provides a unique perspective on road dust sources and their spatial distribution.Results of this study indicated that the difference of the PM₁₀ concentrations measured behind the tire and on the hood is exponentially related to vehicle speed. This was an interesting finding because current AP-42 road dust emissions estimation methods do not include vehicle speed as a factor in the emissions calculations. The experiment also demonstrated that the distribution of suspendable material on roadways is highly variable and that a large number of samples are needed to represent road dust emissions potential on an urban scale for a variety of road and activity conditions.     

Characteristics of real-world vehicular emissions in Chinese cities

On-board emission measurements were performed on 49 light-duty gasoline vehicles in seven cities of China. Vehicle-specific power mode distribution and emission characteristics were analyzed based on the data collected. The results of our study show that there were significant differences in different types of roads. The emission factors and fuel consumption rates on arterial roads and residential roads were approximately 1.4-2 times those on freeways. The carbon monoxide, hydrocarbon, and nitrogen oxides emission factors of Euro II vehicles were on average 86.2, 88.2, and 64.5% lower than those of carburetor vehicles, respectively. The new vehicle emission standards implemented in China had played an important role in reducing individual vehicle emissions. More comprehensive measures need to be considered to reduce the total amount of emissions from vehicles.     

On-road emission characteristics of heavy-duty diesel vehicles in Shanghai

On-road vehicle tests of nine heavy-duty diesel trucks were conducted using SEMTECH-D, an emissions measuring instrument provided by Sensors, Inc. The total length of roads for the tests was 186 km. Data were obtained for 37,255 effective driving cycles, including 17,216 on arterial roads, 15,444 on residential roads, and 4595 on highways. The impacts of speed and acceleration on fuel consumption and emissions were analyzed. Results show that trucks spend an average of 16.5% of the time in idling mode, 25.5% in acceleration mode, 27.9% in deceleration mode, and only 30.0% at cruise speed. The average emission factors of CO, total hydrocarbons (THC), and NO_x for the selected vehicles are (4.96±2.90), (1.88±1.03) and (6.54±1.90) g km⁻¹, respectively. The vehicle emission rates vary significantly with factors like speed and acceleration. The test results reflect the actual traffic situation and the current emission status of diesel trucks in Shanghai. The measurements show that low-speed conditions with frequent acceleration and deceleration, particularly in congestion conditions, are the main factors that aggravate vehicle emissions and cause high emissions of CO and THC. Alleviating congestion would significantly improve vehicle fuel economy and reduce CO and THC emissions.     

Ammonia emissions from a representative in-use fleet of light and medium-duty vehicles in the California South Coast Air Basin

We used Fourier Transform Infrared Spectroscopy (FTIR) to measure tailpipe ammonia emissions from a representative fleet of 41 light and medium-duty vehicles recruited in the California South Coast Air Basin. A total of 121 chassis dynamometer emissions tests were conducted on these vehicles and the test results were examined to determine the effects of several key variables on ammonia emissions. Variables included vehicle type, driving cycle, emissions technology, ammonia precursor emissions (i.e. CO and NOx) and odometer readings/model year as a proxy for catalyst age. The mean ammonia emissions factor was 46 mg km^?1 (σ = 48 mg km^?1) for the vehicle fleet. Average emission factors for specific vehicle groups are also reported in this study. Results of this study suggest vehicles with the highest ammonia emission rates possess the following characteristics: medium-duty vehicles, older emissions technologies, mid-range odometer readings, and higher CO emissions. In addition, vehicles subjected to aggressive driving conditions are likely to be higher ammonia emitters. Since the vehicles we studied were representative of recent model year vehicles and technologies in urban airsheds, the results of our study will be useful for developing ammonia emissions inventories in Los Angeles and other urban areas where California-certified vehicles are driven. However, efforts should also be made to continue emissions testing on in-use vehicles to ensure greater confidence in the ammonia emission factors reported here.     

Cost of lower NOx emissions: Increased CO2 emissions from heavy-duty diesel engines

This paper highlights the effect of emissions regulations on in-use emissions from heavy-duty vehicles powered by different model year engines. More importantly, fuel economy data for pre- and post-consent decree engines are compared.The objective of this study was to determine the changes in brake-specific emissions of NO_x as a result of emission regulations, and to highlight the effect these have had on brake-specific CO₂ emission; hence, fuel consumption. For this study, in-use, on-road emission measurements were collected. Test vehicles were instrumented with a portable on-board tailpipe emissions measurement system, WVU's Mobile Emissions Measurement System, and were tested on specific routes, which included a mix of highway and city driving patterns, in order to collect engine operating conditions, vehicle speed, and in-use emission rates of CO₂ and NO_x. Comparison of on-road in-use emissions data suggests NO_x reductions as high as 80% and 45% compared to the US Federal Test Procedure and Not-to-Exceed standards for model year 1995–2002. However, the results indicate that the fuel consumption; hence, CO₂ emissions increased by approximately 10% over the same period, when the engines were operating in the Not-to-Exceed region.     

Monitoring of dust emission on gravel roads: Development of a mobile methodology and examination of horizontal diffusion

Traffic-generated fugitive dust on gravel roads impairs visibility and deposits on the adjacent environment. Particulate matter smaller than 10 μm in diameter (PM₁₀) is also associated with human health problems. Dust emission strength depends on the composition of granular material, road moisture, relative humidity, local climate (precipitation, wind velocity, etc.), and vehicle characteristics.The objectives of this study were to develop a reliable and rapid mobile methodology to measure dust concentrations on gravel roads, evaluate the precision and repeatability of the methodology and correspondence with the currently used visual assessment technique. Downwind horizontal diffusion was studied to evaluate the risk of exceeding the maximum allowed particulate matter concentration in ambient air near gravel roads according to European Council Directive [European Council Directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air. Official Journal of the European Communities. L163/41.].A TSI DustTrak Aerosol Monitor was mounted on an estate car travelling along test sections treated with various dust suppressants. Measured PM₁₀ concentrations were compared to visual assessments performed at the same time. Airborne particles were collected in filters mounted behind the vehicle to compare the whole dust fraction with the PM₁₀ concentration. For measuring the horizontal diffusion, DustTraks were placed at various distances downwind of a dusty road section.The mobile methodology was vehicle and speed dependent but not driver dependent with pre-specified driving behaviours. A high linear correlation between PM₁₀ of different vehicles makes relative measurements of dust concentrations possible. The methodology gives continuous data series, mobility, and easy handling and provides fast, reliable and inexpensive measurements for estimating road conditions to make road maintenance more efficient.Good correlations between measured PM₁₀-values, visually assessed dust generation and dust collected in filters were obtained. PM₁₀ seems to be correlated to the whole dust fraction that impairs visibility on gravel roads.A decay in PM₁₀ concentration as a function of distance from the road was observed. Measured particles principally did not travel further than 45 m from the road. The risk of exceeding the PM₁₀ concentration stated in the EC-directive seems small.     

Analysis and modelling of the pollutant emissions from European cars regarding the driving characteristics and test cycles

Within the European research project ARTEMIS, significant works have been conducted to analyse the hot emissions of pollutant from the passenger cars regarding the driving cycles and to propose modelling approaches taking into account large but heterogeneous datasets recorded in Europe. The review and analysis of a large range of test cycles enabled first the building-up of a set of contrasted cycles specifically designed for characterizing the influence of the driving conditions. These cycles were used for the measurement of the pollutants emission rates from nine passenger cars on a chassis dynamometer.Emissions measured on 30 vehicles tested on cycles adapted to their motorization (i.e., cycles for high- or low-powered cars, inducing thus a significant difference in the dynamic) were also considered for analysing the influence of the cycles and of the kinematic parameters on the hot emission rates of the regulated pollutants (CO, HC, NO_x, CO₂, PM). An analyses of variance demonstrated the preponderance of the driving type (urban, rural road, motorway), of the vehicle category (fuel, emission standard) and emitting status (high/normal emitter) and thus the pertinence of analysing and modelling separately the corresponding emissions. It also demonstrated that Urban driving led systematically to high diesel emission rates and to high CO₂, HC and NO_x emissions from petrol cars. Congested driving implied high CO₂ (diesel and petrol) and high diesel NO_x emission. On motorway, the very high speeds generated high CO₂, while unsteady speeds induced diesel NO_x and petrol CO over-emissions. A search for pertinent kinematic parameters showed that urban diesel emissions were mostly sensitive to stops and speed parameters, while petrol emissions were rather sensitive to acceleration parameters. On the motorway, diesel NO_x and CO₂ emissions rates increased with the speed variability and occurrence of high speeds, while CO₂ and CO over-emission from petrol cars were linked to the occurrence of strong acceleration at high speeds.A modelling approach based on partial least square regression was tested, which demonstrates its ability to discriminate satisfactorily the emissions according to dynamic related parameters and in particular when considering the two-dimensionnal distribution of instantaneous speed and acceleration.Finally, a strategy was proposed to analyse the large but heterogeneous set of hot emission data collected within the ARTEMIS project. The approach consisted in analysing the similarity of the numerous cycles as regards their kinematic, grouping them into reference test patterns through an automatic clustering, and then computing reference emissions for these patterns. These principles enabled the development of a method to compute the emissions at a low spatial scale, i.e. the so-called traffic situation approach, which was implemented in the European Artemis model for estimating the cars’ pollutant emissions.     

Evaluating Speed Differences between Passenger Vehicles and Heavy Trucks for Transportation-Related Emissions Modeling

Abstract

Heavy-duty trucks make up only 3% of the on-road vehicle fleet, yet they account for >7% of vehicle miles traveled in the United States. They also contribute a significant proportion of regulated ambient emissions. Heavy vehicles emit emissions at different rates than passenger vehicles. They may also behave differently on‐road, yet may be treated similarly to passenger vehicles in emissions modeling. Input variables to the MOBILE software, such as average vehicle speed, are typically specified the same for heavy trucks as for passenger vehicles. Although not frequently considered in modeling emissions, speed differences between passenger vehicles and heavy trucks may influence emissions, because emission rates are correlated to average speed. Differences were evaluated by collecting average and spot speeds for heavy trucks and passenger vehicles on arterials and spot speeds on freeways in Des Moines, IA, and Minneapolis/St. Paul, MN. Speeds were compared by study site. Space mean speeds for heavy trucks were lower than passenger vehicle speeds for all of the arterials with differences ranging from 0.8 to 19 mph. Spot speeds for heavy trucks were also lower at all of the arterial and freeway locations with differences ranging from 0.8 to 6.1 mph. The impact that differences in on‐road speeds had on emissions was also evaluated using MOBILE version 6.2. Misspecification of average truck speed is the most significant at lower and higher speed ranges.     

Improved Version of Anion-exchange Resin-based Desulfurization Process for Alkali Metal Sulfates

Abstract

Vehicle gaseous emissions (NO, CO, CO₂, and hydrocarbon [HC]) and driver’s particle exposures (particulate matter <1 μm [PM₁], <2.5 μm [PM_2.5], and<10 μm [PM₁₀]) were measured using a mobile laboratory to follow a wide variety of vehicles during very heavy traffic congestion in Macao, Special Administrative Region, People’s Republic of China, an urban area having one of the highest population densities in the world. The measurements were taken with high time resolution so that fluctuations in the emissions can be seen readily during vehicle acceleration, cruising, deceleration, and idling. The tests were conducted in close proximity to the vehicles, with the inlet of a five-gas analyzer mounted on the front bumper of the mobile laboratory, and the distance between the vehicles was usually within several meters. To measure the driver’s particle exposures, the inlets of the particle analyzers were mounted at the height of the driver’s breathing position in the mobile laboratory, with the driver’s window open. A total of 178 and 113 vehicles were followed individually to determine the gaseous emission factor and the driver’s particle exposures, respectively, for motorcycle, passenger car, taxi, truck, and bus. The gaseous emission factors were used to model the roadside air quality, and good correlations between the modeled and monitored CO, NO₂, and nitrogen oxide (NO_x) verified the reliability of the experiments. Compared with petrol passenger cars and petrol trucks, diesel taxies and diesel trucks emitted less CO but more NO_x. The impact of urban canyons is shown to cause a significant increase in the PM₁ peak. The background concentrations contributed a significant amount of the driver’s particle exposures.     

Trends in onroad transportation energy and emissions

Globally, 1.3 billion on-road vehicles consume 79 quadrillion BTU of energy, mostly gasoline and diesel fuels, emit 5.7 gigatonnes of CO₂, and emit other pollutants to which approximately 200,000 annual premature deaths are attributed. Improved vehicle energy efficiency and emission controls have helped offset growth in vehicle activity. New technologies are diffusing into the vehicle fleet in response to fuel efficiency and emission standards. Empirical assessment of vehicle emissions is challenging because of myriad fuels and technologies, intervehicle variability, multiple emission processes, variability in operating conditions, and varying capabilities of measurement methods. Fuel economy and emissions regulations have been effective in reducing total emissions of key pollutants. Real-world fuel use and emissions are consistent with official values in the United States but not in Europe or countries that adopt European standards. Portable emission measurements systems, which uncovered a recent emissions cheating scandal, have a key role in regulatory programs to ensure conformity between “real driving emissions” and emission standards. The global vehicle fleet will experience tremendous growth, especially in Asia. Although existing data and modeling tools are useful, they are often based on convenience samples, small sample sizes, large variability, and unquantified uncertainty. Vehicles emit precursors to several important secondary pollutants, including ozone and secondary organic aerosols, which requires a multipollutant emissions and air quality management strategy. Gasoline and diesel are likely to persist as key energy sources to mid-century. Adoption of electric vehicles is not a panacea with regard to greenhouse gas emissions unless coupled with policies to change the power generation mix. Depending on how they are actually implemented and used, autonomous vehicles could lead to very large reductions or increases in energy consumption. Numerous other trends are addressed with regard to technology, emissions controls, vehicle operations, emission measurements, impacts on exposure, and impacts on public health.

Implications: Without specific policies to the contrary, fossil fuels are likely to continue to be the major source of on-road vehicle energy consumption. Fuel economy and emission standards are generally effective in achieving reductions per unit of vehicle activity. However, the number of vehicles and miles traveled will increase. Total energy use and emissions depend on factors such as fuels, technologies, land use, demographics, economics, road design, vehicle operation, societal values, and others that affect demand for transportation, mode choice, energy use, and emissions. Thus, there are many opportunities to influence future trends in vehicle energy use and emissions.     

深圳市在用柴油公交车排放研究

以公交车为例,利用OBS-2200和ELPI(electrical low pressure impactor)对深圳市重型柴油车(high-duty diesel vehicles,HDDVs)进行了3次在实际道路上的车载排放测试.根据测试数据计算了NOx和PM排放因子及百公里油耗,并分析了不同道路、不同工况对NOx...