Real world CO2 and NOx emissions from 149 Euro 5 and 6 diesel, gasoline and hybrid passenger cars

Effect of driving characteristics and ambient temperature on the particle emissions during engine restart of spark ignition hybrid electric vehicle

In this study, we analyzed particle emission characteristics in the engine restart (ER) phase of a hybrid electric vehicle (HEV) based on driving characteristics and ambient temperature. The ambient temperature was set at intervals of 10 °C from - 10 °C to 20 °C. ES-582.1, PPS-M, EEPS, and temperature sensors were installed to acquire hybrid control unit (HCU), particle number (PN), PN size distribution, and exhaust temperature data. The on board test route was conducted in the South Korean real driving emissions (RDE) certification route, consisting of urban, rural, and motorway phases. The test HEV was controlled by dividing the engine operation during driving into ER and normal phases. Within 5 s immediately after ER, it emitted PN equivalent to 90% of the total test emissions. The count of ER was higher in urban phases compared to rural and motorway phases. As the ambient temperature decreased, PN emissions increased regardless of the driving mode, but the ER PN percent decreased. Immediately after ER, PN emissions increased rapidly, peaked at around 2-3 s, and then decreased thereafter. The average engine-off time before ER was the longest in the urban phase, and the average ER exhaust temperature was the highest in the motorway phase. The size fraction of large particles increased as the ambient temperature decreased.

Evaluating the real-world emissions of diesel passenger Car in Indian heterogeneous traffic

A 30 portable emission measurement system (PEMS) test was conducted in this study to examine the effect of driving modes (aggressive and normal) and road type (urban and rural) on tailpipe emissions. Driving modes were assessed using relative positive acceleration and velocity × positive acceleration factors. The findings revealed that aggressive and normal driving modes differed significantly on urban and rural roads, as evident from paired sample t-test (p < 0.05). Furthermore, aggressive driving exhibited more prominent speed and acceleration on rural roads, while normal driving modes showed consistent acceleration or speed patterns regardless of road conditions as observed from kernel density estimation and box plot analysis. Emission rates (CO, CO2, HC, and NOx) significantly varied between aggressive and normal driving modes on urban and rural roads, as indicated by paired sample t-test analysis (p < 0.05). Aggressive driving increased CO2, CO, and HC emission rates for acceleration and deceleration modes by 18% to 40% compared to normal driving. Aggressive driving modes increased the emission factors (CO, HC, and CO2) by 5% to 25% compared to the normal driving mode on both urban and rural roads. Moreover, the NOx emission factors were also found significant during normal driving conditions on urban roads. This study provides real-world emission factors of diesel cars considering the impact of route, vehicle familiarity, and driving behavior induced by varying traffic conditions, which will contribute to improve the current emissions inventory on both a local and global level.

Impacts on real-world extra cold start emissions: Fuel injection, powertrain, aftertreatment and ambient temperature

Vehicles emit substantial amounts of pollutants during start periods. Engine starts mainly occur in urban areas, causing serious harm to humans. To investigate the impacts on extra cold start emissions (ECSEs), eleven China 6 vehicles with various control technologies (fuel injection, powertrain, and aftertreatment) were monitored with a portable emission measurement system (PEMS) at different temperatures. For conventional internal combustion engine vehicles (ICEVs), the average ECSEs of CO₂ increased by 24%, while the average ECSEs of NOx and particle number (PN) decreased by 38% and 39%, respectively, with air conditioning (AC) on. Gasoline direct injection (GDI) vehicles had 5% lower CO₂ ECSEs, but 261% higher NOx ECSEs and 318% higher PN ECSEs than port fuel injection (PFI) vehicles at 23 °C. The average PN ECSEs were significantly reduced by gasoline particle filters (GPFs). The GPF filtration efficiency was higher in GDI than PFI vehicles due to particle size distribution. Hybrid electric vehicles (HEVs) generated excessive PN extra start emissions (ESEs), resulting in a 518% increase compared to ICEVs. The start times of the GDI-engine HEV accounted for 11% of the whole test time, but the proportion of PN ESEs relative to total emissions were 23%. Linear simulation based on the decrease in ECSEs with increasing temperature underestimated the PN ECSEs from PFI and GDI vehicles by 39% and 21%, respectively. For ICEVs, CO ECSEs varied with temperature in a U shape with a minimum at 27 °C; NOx ECSEs decreased as ambient temperature increased; PFI vehicles generated more PN ECSEs at 32 °C than GDI vehicles, stressing the significance of ECSEs at high temperature. These results are useful for improving emission models and assessing air pollution exposure in urban aeras.

Inferred vehicular emissions at a near-road site: Impacts of COVID-19 restrictions, traffic patterns, and ambient air temperature

Vehicles are a major source of anthropogenic emissions of carbon monoxide (CO), nitrogen oxides (NO_x), and black carbon (BC). CO and NO_x are known to be harmful to human health and contribute to ozone formation, while BC absorbs solar radiation that contributes to global warming and also has negative impacts on human health and visibility. Travel restrictions implemented during the COVID-19 pandemic provide researchers the opportunity to study the impact of large, on-road traffic reductions on local air quality. Traffic counts collected along Interstate-95, a major eight-lane highway in Maryland (US), reveal a 60% decrease in passenger car totals and an 8.6% (combination-unit) and 21% (single-unit) decrease in truck traffic counts in April 2020 relative to prior Aprils. The decrease in total on-road vehicles led to the near-elimination in stop-and-go traffic and a 14% increase in the mean vehicle speed during April 2020. Ambient near-road (NR) BC, CO, NO_x, and carbon dioxide (CO₂) measurements were used to determine vehicular emission ratios (ΔBC/ΔCO, ΔBC/ΔCO₂, ΔNO_x/ΔCO, ΔNO_x/ΔCO₂, and ΔCO/ΔCO₂), with each ratio defined as the slope value of a linear regression performed on the concentrations of two pollutants within an hour. A decrease of up to a factor of two in ΔBC/ΔCO, ΔBC/ΔCO₂, ΔNO_x/ΔCO₂, and in the fraction of on-road diesel vehicles from weekdays to weekends shows diesel vehicles to be the dominant source of BC and NO_x emissions at this NR site. We estimate up to a 70% reduction in BC emissions in April 2020 compared to earlier years, and attribute much of this to lower diesel BC emissions resulting from improvements in traffic flow and fewer instances of acceleration and braking. Future efforts to reduce vehicular BC emissions should focus on improving traffic flow or turbocharger lag within diesel engines. Inferred BC emissions from the NR site also depend on ambient temperature, with an increase of 54% in ΔBC/ΔCO from -5 to 20 °C during the cold season, similar to previous studies that reported increasing BC emissions with rising temperature. The default setting of MOVES3, the current version of the mobile emission model used by the US EPA, does not adjust hot-running BC emissions for ambient temperature. Future work will focus on improving the accuracy of mobile emissions in air quality modeling by incorporating the effects of temperature and traffic flow in the system used to generate mobile emissions input for commonly used air quality models.

Tunnel measurements reveal significant reduction in traffic-related light-absorbing aerosol emissions in China

Light-absorbing aerosols (LAA), including black carbon (BC) and brown carbon (BrC), profoundly impact regional and global climate. Vehicle emission is an important source of LAA in urban areas, but real-world emission features of LAA from the urban vehicle fleet are not fully understood. This study evaluates traffic-related BC and BrC emission factors (EFs) and their vehicular emission inventories via road tunnel measurements in Tianjin, China, in 2017 and 2021. The distance-based and fuel-based EFs of BC for the mixed fleet were 1.05 ± 1.28 mg km^-1 veh^-1 and 0.057 ± 0.057 g (kg-fuel)^-1, respectively, in 2021, with a dramatic decrease of 80.6 % compared to those in 2017. The BC EFs for gasoline vehicles (GVs, including traditional gasoline and hybrid vehicles) and diesel vehicles (DVs) were 0.55 ± 0.065 mg km^-1 veh^-1 and 10.5 ± 2.52 mg km^-1 veh^-1, respectively, in 2021. Compared to 2017, the BrC EFs also decreased significantly in 2021, by 10.8-53.6 %, with 0.32 ± 0.45 mg km^-1 veh^-1 and 0.018 ± 0.020 g (kg-fuel)^-1 of distance-based and fuel-based EFs for mixed fleet. The BrC EFs for GVs and DVs were 0.091 ± 0.024 mg km^-1 veh^-1 and 3.06 ± 0.91 mg km^-1 veh^-1, respectively, in 2021. Based on the BC and BrC EFs for GVs and DVs and annual mileage for each vehicle category, the annual vehicular LAA emission inventories were estimated. From 2017 to 2021, the annual vehicular LAA emissions in Tianjin have been significantly reduced, by 69 % for BC and 10 % for BrC. DVs account for a small amount of the vehicle population (8.4 %), but contribute to most of the BC (83 %) and BrC (86 %). Our study demonstrates the significant reduction of vehicular light-absorbing aerosols emission due to vehicle pollution prevention and control in China.

Effect of Exhaust Gas Recirculation Combined with Selective Catalytic Reduction on NO x Emission Characteristics and Their Matching Optimization of a Heavy-Duty Diesel Engine

Exhaust gas recirculation (EGR) and selective catalytic reduction (SCR) have become important technologies to reduce the NO _x emission of heavy-duty diesel engines and meet the increasingly stringent emission regulations. This paper studied the effect of EGR combined with SCR on the NO _x emission characteristics of a heavy-duty diesel engine based on the engine bench test. The results showed that the NO reduction rate of EGR-coupled SCR increased with the increase of engine load, and the effect was no longer significant when the NO reduction rate exceeded a certain limit under the same working conditions. EGR combined with SCR has little effect on NO₂ emission reduction, and the increase of engine speed can significantly improve the efficiency of the NO₂ reduction rate at 75 and 100% load. 25% opening of the EGR valve (OEV) and 50% OEV have very similar effects on the NO _x reduction rate when the engine speed is at a low level. Compared with low engine speeds, increased OEV or ammonia NO _x molar ratio (ANR) had a more obvious effect on the NO _x reduction rate at high engine speeds. SCR combined with low valve-opening EGR had a more significant effect on the NO _x reduction rate. The increase of OEV led to the increase of fuel consumption rate, but the effect on the fuel consumption rate decreased gradually with the increase of diesel engine speed. Meanwhile, this study optimized the matching relationship between OEV and ANR based on the data of the genetic algorithm, which provides a theoretical research method and application basis for diesel engine-matching of EGR and SCR.

Detecting candidate high NOx emitting light commercial vehicles using vehicle emission remote sensing

Vehicle emission remote sensing devices have been widely used for monitoring and assessing the real-world emission performance of vehicles. They are also well-suited to identify candidate high emitting vehicles as remote sensing surveys measure the on-road, real-driving emissions (RDE) of a high proportion of the operational vehicle fleet passing through a testing site. This study uses the Gumbel distribution to characterize the fuel-specific NO_x emission rates (g·kg^-1) from diesel vans (formally referred to as light commercial vehicles or LCVs) and screen candidate high emitting vehicles. Van emission trends of four European countries (Belgium, Sweden, Switzerland and the UK) from Euro 3 to Euro 6a/b have been studied, and the impact of road grade on candidate Euro 6a/b high-emitters is also evaluated. The measurements of Euro 6a/b fleets from four countries are pooled together, and a consistent 4% of candidate high-emitters are found in both class II and class III Euro 6a/b vans, accounting for an estimated 24% and 21% total NO_x emissions respectively. The pooled four country data is differentiated by vehicle models and manufacture groups. Engine downsizing of Euro 6a/b class II vans is suspected to worsen the emission performance when vehicles are driven under high engine load. The VW Group is found to be the manufacture with cleanest NO_x emission performance in the Euro 6a/b fleets. By distinguishing high-emitters from normally behaving vehicles, a more robust description of fleet behaviour can be provided and high-emitting vehicles targeted for further testing by plume chasing or in an inspection garage. If the vehicle is found to have a faulty, deteriorated or tampered emission after-treatment system, the periodic vehicle inspection safety and environmental performance certificate could be revoked.

Effect of Tampering on On-Road and Off-Road Diesel Vehicle Emissions

Illegal manipulation (i.e., tampering) of vehicles is a severe problem because vehicle emissions increase orders of magnitude and significantly impact the environment and human health. This study measured the emissions before and after representative approaches of tampering of two Euro 6 Diesel light-duty passenger cars, two Euro VI Diesel heavy-duty trucks, and a Stage IV Diesel non-road mobile machinery (NRMM) agricultural tractor. With tampering of the selective catalytic reduction (SCR) for NOx, the NOx emissions increased by more than one order of magnitude exceeding 1000 mg/km (or mg/kWh) for all vehicles, reaching older Euro or even pre-Euro levels. The tampering of the NOx sensor resulted in relatively low NOx increases, but significant ammonia (NH3) slip. The particle number emissions increased three to four orders of magnitude, reaching 6–10 × 1012 #/km for the passenger car (one order of magnitude higher than the current regulation limit). The tampered passenger car’s NOx and particle number emissions were one order of magnitude higher even compared to the emissions during a regeneration event. This study confirmed that (i) tampering with the help of an expert technician is still possible, even for vehicles complying with the current Euro standards, although this is not allowed by the regulation; (ii) tampering results in extreme increases in emissions.

Effect of the Air Flow on the Combustion Process and Preheating Effect of the Intake Manifold Burner

Diesel engines show poor performance and high emissions under cold-start conditions. The intake manifold burner is an effective method to increase the intake air temperature and improve engine performance. In this paper, a visualization system was employed to investigate the combustion process of the intake manifold burner. The effects of diesel flow rate and airflow velocity on combustion performance were investigated. The combustion process of the intake manifold burner showed four stages: preparing stage A, rapid development stage B, steady-development stage C, and stable stage D. Flame stripping was found in stages C and D, presenting the instability of the combustion process. With the increase in air flow velocity from 1.4 m/s to 3.0 m/s, the flame stripping was enhanced, leading to the increasing combustion instability and regular flame penetration fluctuations. The average temperature rise and combustion efficiency increased with the increasing diesel flow rate, indicating the combustion enhancement. Comparison of temperature rise and combustion efficiency under 2.0 m/s and 10.0 m/s showed that stronger cross wind enhances the heat convection, improving the temperature uniformity and combustion efficiency.

A Deep Learning Approach for Meter-Scale Air Quality Estimation in Urban Environments Using Very High-Spatial-Resolution Satellite Imagery

High-spatial-resolution air quality (AQ) mapping is important for identifying pollution sources to facilitate local action. Some of the most populated cities in the world are not equipped with the infrastructure required to monitor AQ levels on the ground and must rely on other sources, like satellite derived estimates, to monitor AQ. Current satellite-data-based models provide AQ mapping on a kilometer scale at best. In this study we focus on producing hundred-meter-scale AQ maps for urban environments in developed cities. We examined the feasibility of an image-based object-detection analysis approach using very high-spatial-resolution (2.5 m) commercial satellite imagery. We fed the satellite imagery to a deep neural network (DNN) to learn the association between visual urban features and air pollutants. The developed model, which solely uses satellite imagery, was tested and evaluated using both ground monitoring observations and land-use regression modeled PM2.5 and NO2 concentrations over London, Vancouver (BC), Los Angeles, and New York City. The results demonstrate a low error with a total RMSE < 2 µg/m3 and highlight the contribution of specific urban features, such as green areas and roads, to continuous hundred-meter-scale AQ estimation. This approach offers promise for scaling to global applications in developed and developing urban environments. Further analysis on domain transferability will enable application of a parsimonious model based merely on satellite images to create hundred-meter-scale AQ maps in developing cities, where current and historical ground data is limited.

Hybrid Vehicles as a Transition for Full E-Mobility Achievement in Positive Energy Districts: A Comparative Assessment of Real-Driving Emissions

Air pollution is a major concern, particularly in developing countries. Road transport and mobile sources are considered the root causes of air pollutants. With the implementation of zero-carbon and zero-energy concepts at the district scale, cities can make great strides towards sustainable development. Urban planning schemes are moving from mere building solutions to the larger positive energy district (PED) scale. Alongside other technology systems in PEDs, increased uptake of electro-mobility solutions can play an important role in CO2 mitigation at the district level. This paper aims to quantify the exhaust emissions of six conventional and two fully hybrid vehicles using a portable emission measurement system (PEMS) in real driving conditions. The fuel consumption and exhaust pollutants of the conventional and hybrid vehicles were compared in four different urban and highway driving routes during autumn 2019 in Iran. The results showed that hybrid vehicles presented lower fuel consumption and produced relatively lower exhaust emissions. The conventional group’s fuel consumption (CO2 emissions) was 11%, 41% higher than that of the hybrids. In addition, the hybrid vehicles showed much better fuel economy in urban routes, which is beneficial for PEDs. Micro-trip analysis showed that although conventional vehicles emitted more CO2 at lower speeds, the hybrids showed a lower amount of CO2. Moreover, in conventional vehicles, NOx emissions showed an increasing trend with vehicle speed, while no decisive trend was found for NOx emissions versus vehicle speed in hybrid vehicles.

Emission from Internal Combustion Engines and Battery Electric Vehicles: Case Study for Poland

The paper compares the emissions from vehicles including ICEVs (internal combustion engine vehicles) with equivalent emissions from BEVs (battery electric vehicles). Additionally, it analyzes the available source research and the specific energy mix for Poland based on carbon. Mathematical calculations estimate air pollutant emissions. To carry out the analysis and calculations, data were provided by the manufacturers of electricity consumption in the case of vehicles equipped with electric motors and the COPERT model for internal combustion engines. Air pollutants are considered: CO2, NOx, SOx, CO, and Total Suspended Particles (TSP). In addition to exhaust emissions, all solids emissions from road abrasion and tire and brake wear are also considered. The emission of pollutants is estimated based on the emission factors using the average mileage in Polish conditions. The paper compares emissions for three scenarios considering electric vehicles, combustion engine cars, and hybrid cars. Analyses show that introducing cars with electric engines into traffic at the expense of withdrawing vehicles with internal combustion engines is not favorable in Polish conditions. The analysis indicates that CO, CO2, and TSP emissions have decreased, while NOx and SOx emissions have increased.

Automated Estimation of Construction Equipment Emission Using Inertial Sensors and Machine Learning Models

The construction industry is one of the main producers of greenhouse gasses (GHG). With the looming consequences of climate change, sustainability measures including quantifying the amount of air pollution during a construction project have become an important project objective in the construction industry. A major contributor to air pollution during construction projects is the use of heavy equipment. Therefore, efficient operation and management can substantially reduce a project’s carbon footprint and other environmental harms. Using unintrusive and indirect methods to predict on-road vehicle emissions has been a widely researched topic. Nevertheless, the same is not true in the case of construction equipment. This paper describes the development and deployment of a framework that uses machine learning (ML) methods to predict the level of emissions from heavy construction equipment. Data is collected via an Internet of Things (IoT) approach with accelerometer and gyroscope sensors as data collection nodes. The developed framework was validated using an excavator performing real-world construction work. A portable emission measurement system (PEMS) was used along with the inertial sensors to record the amount of CO, NOX, CO2, SO2, and CH4 pollution emitted by the equipment. Different ML algorithms were developed and compared to identify the best model to predict emission levels from inertial sensors data. The results show that Random Forest with the coefficient of determination (R2) of 0.94, 0.91, and 0.94, and normalized root-mean-square error (NRMSE) of 4.25, 6.42, and 5.17 for CO, NOX, and CO2, respectively, was the best algorithm among different models evaluated in this study.

Variations of significant contribution regions of NOx and PN emissions for passenger cars in the real-world driving

Nitrogen oxides (NO_x) and particulate number (PN) emissions are the main concerns of the passenger cars in the real-world driving. NO_x and PN emissions are greatly dependent on the driving behaviors which differ significantly between standard driving cycles and real-world driving. However, the significant contribution regions (short durations corresponding to high proportions of total emissions) of NO_x and PN emissions regarding different driving behaviors (e.g. vehicle speed and acceleration) are still uncovered. NO_x20% and NO_x50% refer to instantaneous NO_x emission rates when NO_x emission rates are ranked from high to low level where the sums of NO_x emission rates being higher than NO_x20% and NO_x50% correspond to 20% and 50% of total NO_x emissions, respectively. t_20% and t_50% are corresponding durations where NO_x emission rates are higher than NO_x20% and NO_x50%. In this paper, three Euro-6 compliant direct injection gasoline passenger cars and a diesel passenger car are tested in a real-world driving trial in which nineteen drivers are involved. Novel key performance indicators with reference to the regimes of specific NO_x and PN contributions to total emissions are defined. Instantaneous NO_x and PN emissions are monitored using a portable emission measurement system (PEMS) in the test. The results indicate that the maximum and minimum average speed over the four cars being approximately 32.3 km/h s and 42.6 km/h, respectively. Average PN emission factor of the diesel car is the lowest among the four given cars. Average t_20% and t_50% corresponding to NO_x20% and NO_x50% are lower than 3% and 12%, respectively, for all the passenger cars; additionally, these two parameters show the same pattern. The corresponding t_20% and t_50% variations of the Euro-6a gasoline car and the diesel car are much lower than the other two. Average acceleration corresponding to 20% and 50% of total NO_x emissions for the given diesel car is approximately 1.25 m/s² and 0.6 m/s², respectively, being much higher than that of the other three gasoline cars (lower than 1 m/s² and 0.4 m/s² respectively) over the specific driving route and drivers. The average PN_20% and PN_50% of the given diesel car are approximately 7 × 10⁷#/s and 3 × 10⁷#/s respectively, being much lower than the three given gasoline cars (higher than 8 ×10⁹#/s and 2 ×10⁹#/s respectively) under the given test conditions; the corresponding t_20% and t_50% are lower than 4% and 17% respectively for all the three gasoline cars.

Super-learner model realizes the transient prediction of CO2 and NOx of diesel trucks: Model development, evaluation and interpretation

The transient simulation of CO₂ and NO_X from motor vehicles has essential applications in evaluating vehicular greenhouse gas emissions and pollutant emissions. However, accurately estimating vehicular transient emissions is challenging due to the heterogeneity between different vehicles and the continuous upgrading of vehicle exhaust purification technology. To accurately characterize the transient emissions of motor vehicles, a Super-learner model is used to build CO₂ and NOx transient emission models. The actual onboard test data of 9 China VI N₂ vehicles were used to train the model, and the test data of another China VI N₂ vehicle were selected for further robustness verification. There were significant differences in the emissions between the vehicles, but the constructed transient model could capture the common law of transient emissions from China VI N₂ vehicles. The R² values of CO₂ and NOx emission in the test data of the validation vehicle were 0.71 and 0.82, respectively. In addition, to further prove the model's robustness, the training data were synchronously modelled based on the Moves-method. The Super-learner model has a smaller RMSE on the validation set than the model based on the Moves-method, indicating that the Super-learner model has more transient simulation advantages. The marginal contributions of the model characteristics to the model results were analysed by SHapley Additive exPlanation (SHAP) value interpretation, and the marginal contributions of different pollutant characteristic parameters varied. Therefore, when establishing transient models of different pollutants, the selection of the model parameters demands considering the generation and purification process of different pollutants. The present work provides novel insights into the parameter selection, construction, and interpretation of the transient vehicle emission model.

Comparison of NOx and PN emissions between Euro 6 petrol and diesel passenger cars under real-world driving conditions

With emission standards becoming stricter, nitrogen oxides (NO_x) and particle number (PN) emissions are the main concerns of modern passenger cars, especially for the real-world driving. In this paper, two direct injection (DI) petrol passenger cars and a diesel passenger car are tested on the same routes, driven by the same driver. Instantaneous NO_x and PN emissions are monitored by a portable emission measurement system (PEMS) in the tests. During the real-world driving, the exhaust temperatures of the two petrol cars are sufficiently high to ensure high efficiency of three-way catalysts (TWCs). On the other hand, the exhaust temperatures of the diesel car in some sections of the route are lower than the crucial light-off temperature of the selective catalytic reduction (SCR) below which its effectiveness in NO_x reduction would be much affected. NO_x and PN concentrations are low during motorway driving for the petrol passenger car equipped with a gasoline particulate filter (GPF); however, they are high and change frequently in the whole journey for the petrol passenger car without a GPF. NO_x emission factors are quite low over most of the driving sections for the diesel car, but some significant high peaks are observed in the acceleration process. NO_x emission distributions over speed and acceleration are similar for both petrol cars; and they differ significantly from the diesel counterpart. Particle size from the diesel car is the largest, followed by the petrol car with a GPF.

A New Approach for Static NOx Measurement in PTI

NOx emissions in vehicles are currently only controlled through the homologation process. There is a lack of knowledge to assess and control real NOx emissions of vehicles reliably. Even if vehicles in EU-27 are subject to Periodical Technical Inspection (PTI), NOx are not among the pollutants currently being controlled. For PTIs, tests need to be simple, quick, inexpensive, representative, and accurate. Ideally, tests need to be carried out under static conditions, without the need for a power bench or complex equipment. In this paper, a new approach for measuring NOx in PTI is proposed. The method has been developed and validated at a PTI Spanish station to ensure feasibility and repeatability. This method is based on the relationship between the “% engine load” value and exhaust NOx concentration at idle engine speed. Starting from the state of minimum possible power demand in a vehicle (idling and without any consumption), a load state with an average 98% increase in engine power demand is generated by connecting elements of the vehicle’s equipment. The relationship between power demand (through the “% engine load” value) and NOx concentration is then analyzed. The quality and representativity of this relationship have been checked with a p-value lower than 0.01. The method has been compared with a different NOx measurement technique, based on the simulation on a test bench and the ASM 2050 cycle, showing better performance in terms of repeatability and representativeness. The “% engine load” dispersion with the new approach is 7%, which ensures the reliability and repeatability of the method. The results show that the proposed method could be a valuable tool in PTI to detect high NOx emitting vehicles and to obtain information from the diesel vehicles fleet.

Electrification of Road Transport and the Impacts on Air Quality and Health in the UK

Currently, many cities in Europe are affected by concentrations of PM2.5 and NO2 above the WHO guidelines on the protection of human health. This is a global problem in which the growth of road transport constitutes a major factor. Looking to the future, electric vehicles (EVs) are considered to be the choice technology for reducing road transport greenhouse gas emissions, but their impact on air quality needs to be considered. Taking the UK as a case study, this paper begins by understanding the trajectory of a future scenario without the introduction of EVs, reflecting on the latest emission control improvements in internal combustion engine vehicles (ICEVs). This is then compared to a 2050 scenario in which the introduction of EVs, based on the UK government’s Transport Decarbonisation Plan, is reviewed. This plan includes a ban on the sale of ICEV cars and LGVs, beginning in 2030, with the subsequent electrification of heavier vehicles. By 2030, population exposure to NOx was found to be significantly reduced in the ICEV scenario, with a marginal further reduction found for the EV scenario. The EV scenario further reduced NOx exposure by 2050, with most of the benefits being realized before 2040. For the ICEV and EV scenario, PM2.5 emissions were largely unchanged due to the primary contribution of non-exhaust emissions, suggesting that EVs are likely to yield relatively smaller changes in exposure to PM2.5 than for NOx.

Real Driving Emissions in Extended Driving Conditions

The real driving emission (RDE) testing for certification of vehicles is performed in conditions that are well defined in legislation. For emissions inventories and for research, the influences of some extended driving conditions on emissions are an interesting issue. In the present work, some examples of RDE results from two common passenger cars with gasoline and diesel propulsion are given. The varying driving conditions were “winter/summer”, “mild/aggressive”, and “higher altitude/slop”. The driving conditions: “winter”, “aggressive”, and “higher slope/altitude” generally require more energy, cause higher fuel consumption, and therefore, higher CO2-emissions. The condition of “winter driving”, especially in the urban type of operation, may cause some longer phases with not enough warmed-up exhaust aftertreatment and consequently some increased gaseous emissions. The DPF eliminates the nanoparticles (PN) independently on the driving conditions. Nevertheless, the DPF regeneration has an influence on the CO2-normality of the trip. The CO2-normality primary tolerance range can also be exceeded with aggressive driving. The elaborated results confirm the usefulness of the existing legal limits for the driving conditions of RDE homologation tests.

A Method of Analyzing the Residual Values of Low-Emission Vehicles Based on a Selected Expert Method Taking into Account Stochastic Operational Parameters

Increasing the market share of low-emission vehicles in relation to individual mobility is one of the main postulates of modern transport policy. In the discussion on low-emission and the new structure of the car fleet, the role of new vehicles is emphasized above all, ignoring the importance of the secondary market. In recent years, both in Poland and in other European Union countries, there has been a noticeable dynamic development of electromobility implementation processes in urban areas, the initial effect of which is increasing market accessibility to commercial vehicles with electric EV/BEV, hybrid HEV/PHEV and fuel cell powered FCEV. As in the case of vehicles powered by conventional ICEV fuels, also in relation to those defined as low-emission, their residual value is lost along with the operational process. Information on this variable is important both for the owner of a newly purchased vehicle, which after the period of its operation will decide to sell it as well as to the future buyer. The scientific aim of the study is to analyze the residual values of selected vehicle models from the primary and secondary market, with particular emphasis on stochastic operational phenomena. The subject of the research is to obtain extensive knowledge on the achieved changes in the residual values of low-emission vehicles in relation to ICEVs. For this purpose, a comparative analysis of the commercial program, data approximated from auction portals and own numerical modeling tool based on a neural network was performed. The research sample included, among others, selected models of passenger cars, the purchase offer of which included the choice of a drive unit powered by conventional and low-emission fuels. The use of this method allowed to answer the question whether low-emission vehicles are characterized by a greater or lesser loss of value in relation to conventionally powered vehicles ICEV.

Characteristics of NOx emission of light-duty diesel vehicle with LNT and SCR system by season and RDE phase

As the regulations on vehicle emissions have become more stringent internationally and real-driving emissions (RDE) have been established, the on-road characteristics of emissions have gained importance in vehicle research and development. The results of the fuel consumption levels and emissions from on-road tests are affected by many factors, such as driving conditions, routes and environmental conditions. Therefore, more research and analysis are needed for the effects of environmental factors and driving conditions according to RDE phase on the NOx emissions. In this study, RDE tests were conducted by season to analyze the on-road NOx emission characteristics of lean NOx trap (LNT)- and selective catalytic reduction (SCR)-equipped diesel vehicles corresponding to the Euro 6b regulation prior to the application of the RDE regulation. The purpose of this study is to analyze the effects of seasonal factors and phases of the RDE routes on the NOx emission and NOx conversion efficiency of catalyst. In spring/autumn and summer, the engine-out and tail-pipe NOx emissions were higher 1.3-5.9 times for vehicle A and 1.3-28.4 times for vehicle B in the urban phase than in other phases. In the urban phase, the engine bay temperature was probable to rise owing to frequent stops and low-speed driving, leading to a high intake air temperature, which causes excessive NOx emission, particularly in summer. The average air filter temperature in urban phase was 11-15 °C higher than the environment temperature for vehicle A. The NOx conversion efficiency of the LNT was highest at 54.1% on motorway and the efficiency was dependent on the phase of the test route. The NOx conversion efficiency of the SCR, which is dependent on the catalyst temperature, was highest at 98.7% in spring motorway and the efficiency was affected by the combined factors of season and phases.

The UK Integrated Assessment Model for source apportionment and air pollution policy applications to PM2.5

Source apportionment and the effect of reducing individual sources is important input for the development of strategies to address air pollution. The UK Integrated Assessment Model, UKIAM, has been developed for this purpose as a flexible framework, combining information from different atmospheric dispersion models to cover different pollutant contributions, and span the range from European to local scale. In this paper we describe the UKIAM as developed for SO₂, NOx, NH₃, PM_2.5 and VOCs. We illustrate its versatility and application with assessment of current PM_2.5 concentrations and exposure of the UK population, as a case-study that has been used as the starting point to investigate potential improvement towards attainment of the WHO guideline of 10 µg/m³.

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO2, O3, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO2 and particulate matter with aerodynamic diameters <2.5 μm by -30.1% and -17.5%, respectively, but a 5.7% increase in O3 Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO2 levels.

A preliminary study into the use of tree-ring and foliar geochemistry as bio-indicators for vehicular NOx pollution in Malta

Emissions from traffic over the past few decades have become a significant source of air pollution. Among the pollutants emitted are nitrogen oxides (NO_x), exposure to which can be detrimental to public health. Recent studies have shown that nitrogen (N) stable isotope ratios in tree-rings and foliage express a fingerprint of their major N source, making them appropriate for bio-monitoring purposes. In this study, we have applied this proxy to Aleppo pines (Pinus halepensis) at three distances from one of the busiest roads in Malta, a country known to suffer from intense traffic pollution. Our results showed that N and organic carbon (C) stable isotope ratios in tree-rings do not vary over the period 1980-2018 at any of the investigated sites; however, statistically significant spatial trends were apparent in both tree-rings and foliage. The roadside and transitional sites exhibited more positive δ¹⁵N and more negative δ¹³C values compared to those at a rural control site. This is likely due to the incorporation of ¹⁵N-enriched NO_x and ¹³C-depleted CO₂ from traffic pollution. Sampled top-soil also exhibited the δ¹⁵N trend. Our results constitute the first known application of dendrogeochemistry to atmospheric pollution monitoring in Malta.

Investigations of Exhaust Emissions from Rail Machinery during Track Maintenance Operations

The paper presents the investigations of exhaust emissions under actual operation of two rail vehicles: a track geometry vehicle and a clearance vehicle. The environmental assessment of this type of objects is difficult due to the necessity of adapting the measurement equipment and meeting the safety requirements during the tests (particularly regarding the distance from the overhead electrical lines). The authors have proposed and developed a unique research methodology, based on which a detailed exhaust emissions analysis (CO, HC, NOx, and PM) was carried out. The complex assessment included the unit and on-track exhaust emissions. In the analyses, the authors also included the operating conditions of the powertrains of the tested machinery. The obtained environmental indexes were referred to the homologation standards, according to which the vehicles were approved for operation. Due to the nature of operation of the tested vehicles, the authors carried out a comprehensive environmental assessment in the daily and annual approach as well as in the aspect of their operation as combined vehicles, which is a novel approach to the assessment of the environmental performance of this type of objects.

Total Cost of Ownership and Its Potential Consequences for the Development of the Hydrogen Fuel Cell Powered Vehicle Market in Poland

Electromobility is a growing technology for land transport, constituting an important element of the concept of sustainable economic development. The article presents selected research results concerning one of the segments of this market-vehicles powered by hydrogen fuel cells. The subject of the research was to gain extensive knowledge on the economic factors influencing the future purchasing decisions of the demand side in relation to this category of vehicles. The research was based on a numerical experiment. For this purpose, a comparative analysis of purchase prices in relation to the TCO of the vehicle after 3–5 years of use was performed. The research included selected models that are powered by both conventional and alternative fuels. The use of this method will allow to assess the real costs associated with the hydrogen vehicle. The authors emphasize the important role of economic factors in the form of the TCO index for the development of this market. The experimental approach may be helpful in understanding the essence of economic relations that affect the development of the electro-mobility market and the market demand for hydrogen fuel cell-powered vehicles in Poland.

More mileage in reducing urban air pollution from road traffic

Road traffic emissions are considered a major contributor to urban air pollution, but clean air actions have led to a huge reduction in emissions per vehicle. This raises a pressing question on the potential to further reduce road traffic emissions to improve air quality. Here, we analysed ~11 million real-world data to estimate the contribution of road traffic to roadside and urban concentrations for several major cities. Our results confirm that road traffic remains a dominant source of nitrogen dioxide and a significant source of primary coarse particulate matter in the European cities. However, it now represents a relatively small component of overall PM_2.5 at urban background locations in cities with strong controls on traffic emissions (including European cities and Beijing) and many roadside sites will exceed the WHO guideline (10 μg m^-3 annual mean) even when this source is eliminated. This suggests that further controls on traffic emissions, including the transition to a battery-electric fleet, are needed to reduce NO₂ concentrations, but this will have limited benefit to reduce the concentration of fine particles, except in countries where the use of diesel particle filters is not mandatory. There are substantial differences between cities and the optimal solution will differ from one to another.

Real-world CO2 and NOX emissions from refrigerated vans

Refrigerated vans used for home deliveries are attracting attention as online grocery shopping in the UK is expanding rapidly and contributes to the increasing greenhouse gas (CO₂) and nitrogen oxides (NO_X) emissions. These vans are typically 3.5-tonne gross weight vehicles equipped with temperature-controlled units called Transport Refrigeration Units (TRUs), which are usually powered off the vehicles' engine. It is obvious that vehicles with added weight of TRUs consume more fuel and emit more NO_X, let alone the vehicles' diesel engines are also powering the refrigeration units, which further elevates the emissions. This research uses an instantaneous vehicle emission model PHEM (version 13.0.3.21) to simulate the real-world emissions from refrigerated vans. A validation of PHEM is included using data from laboratory (chassis dynamometer) tests over a realistic driving profile (the London Drive Cycle), to assess its ability to quantify the impact of changing vehicle weights and carrying loads. The impact of the TRU weight, greater frontal area increasing aerodynamic drag and refrigeration load on van emissions is then estimated by PHEM. The influence of ambient temperature, cargo weight and driving condition on CO₂ and NO_X emission from refrigerated van are also assessed. Overall CO₂ emissions of vans with TRUs are found to be 15% higher than standard vehicles, with NO_X emissions estimated to be elevated by 18%. This confirms the need to take into account the impact of additional engine load when predicting van emissions in this and other sectors such as ambulances which are relatively heavy, high powered vehicles. Moreover, findings of the impact of TRUs on fuel consumptions can be used to optimize fuel-saving strategies for refrigerated vans and test cases for alternative low- or zero-emission technologies, to support progress to a sustainable net-zero society.

Effects of ambient temperature and cold starts on excess NOx emissions in a gasoline direct injection vehicle

Studies have demonstrated that vehicles with gasoline direct injection (GDI) engines produce significantly higher emissions during a cold start than under hot-stabilized periods. A cold start is typically defined by the temperature of the engine or the catalytic converter; its extended effect on emissions, after the vehicle reaches the warm-up stage, has seldom been investigated. In this study, the influence of the post cold start period on nitrogen oxides (NO_x) emissions was evaluated using real-world measurements. Vehicle on-board diagnostic data, fuel consumption, and emissions of multiple pollutants were collected on a 2020 GDI sports utility vehicle equipped with a Portable Emission Measurement System (PEMS). A total of 31 trips, with two drives per day, were conducted along arterial roads and highways in Toronto, Canada. The results indicate that during the first trip of the day after an overnight soak, the average NO_x emission rate was 0.27 g/litre and 0.037 g/km, 384% and 299% higher than the emission rate on the second trip of the day. The amount of trip total NO_x emissions is positively associated with the length of the catalytic converter warm-up period with correlation coefficient 0.67. We also observe that the catalyst warm-up time is negatively correlated with ambient temperature, and a negative relationship between ambient temperature and NO_x emissions throughout the trip is depicted with correlation coefficient -0.44. The measured data reveal an extended effect of the cold start on NO_x emissions even after the temperatures of the engine coolant and catalyst reach a stable level.

The Status of Air Quality in the United States During the COVID-19 Pandemic: A Remote Sensing Perspective

The recent COVID-19 pandemic has prompted global governments to take several measures to limit and contain the spread of the novel virus. In the United States (US), most states have imposed a partial to complete lockdown that has led to decreased traffic volumes and reduced vehicle emissions. In this study, we investigate the impacts of the pandemic-related lockdown on air quality in the US using remote sensing products for nitrogen dioxide tropospheric column (NO2), carbon monoxide atmospheric column (CO), tropospheric ozone column (O3), and aerosol optical depth (AOD). We focus on states with distinctive anomalies and high traffic volume, New York (NY), Illinois (IL), Florida (FL), Texas (TX), and California (CA). We evaluate the effectiveness of reduced traffic volume to improve air quality by comparing the significant reductions during the pandemic to the interannual variability (IAV) of a respective reference period for each pollutant. We also investigate and address the potential factors that might have contributed to changes in air quality during the pandemic. As a result of the lockdown and the significant reduction in traffic volume, there have been reductions in CO and NO2. These reductions were, in many instances, compensated by local emissions and, or affected by meteorological conditions. Ozone was reduced by varying magnitude in all cases related to the decrease or increase of NO2 concentrations, depending on ozone photochemical sensitivity. Regarding the policy impacts of this large-scale experiment, our results indicate that reduction of traffic volume during the pandemic was effective in improving air quality in regions where traffic is the main pollution source, such as in New York City and FL, while was not effective in reducing pollution events where other pollution sources dominate, such as in IL, TX and CA. Therefore, policies to reduce other emissions sources (e.g., industrial emissions) should also be considered, especially in places where the reduction in traffic volume was not effective in improving air quality (AQ).

A novel method for comparing passenger car fleets and identifying high-chance gross emitting vehicles using kerbside remote sensing data

The quantification and comparison of NO_X emission from in-situ car fleets, and identification of the highest emitters is an ongoing challenge. This challenge will become more important as new and increasingly complex emissions removal systems penetrate the market. We combine real-world data with new-to-the-field statistical methods to describe fleet-scale emissions behaviours and identify candidate gross-emitter vehicles. 19,605 passenger cars were observed using a Remote Sensing Device across Aberdeen in 2015. Of these, 736 were Euro 6 Passenger Cars. The distribution of observed pollutant per unit of fuel burnt ratios for most fuel type and Euro standards followed an asymmetrical shape best characterised by the Gumbel distribution. The Gumbel distribution approach was not able to fully replicate the distribution of measurements of petrol or Euro 6 diesel cars due to the presence of a subset of high-emitting outliers, ranging from the 13^th percentile for Euro 3 petrol to the 2^nd percentile for Euro 6 petrol, with Euro 6 diesel having a 5^th percentile outlier value. No outlier fraction was observed for pre-Euro 6 diesels. The off-model fractions resembled Gumbel distributed data and in some cases could be modelled as a separate distribution with the fleet behaving as a superposition of them. It is shown that VSP was not directly linked to this behaviour and it is hypothesised that it is caused by the emissions control systems operating sub-optimally. The reasons for sub-optimal operation are beyond the scope of this paper but may be linked to air-fuel mixture sensors, cold-start running and deterioration of the catalytic converter. Larger data-sets with more Euro 6 passenger cars are required to fully test this. Application of this methodology to larger data sets from more widely deployed remote sensing devices will allow observers to identify potentially problematic vehicles for further investigation into their emission control systems.

Monitoring Euro 6 diesel passenger cars NOx emissions for one year in various ambient conditions with PEMS and NOx sensors

In this study, the NO_x emissions of four Euro 6 diesel passenger cars ranging from Euro 6 b to Euro 6 d-TEMP in different ambient conditions and driving routes were investigated with a Portable Emissions Measurement System (PEMS) and continuous NO_x concentration monitoring device. A model was also generated for translating NO_x concentration values into a gram basis. The results suggest that there is a marked difference in NO_x emissions based on the Euro 6 step for the car is type approved. The study showed that the conformity factor for NO_x emissions on a route in a city environment ("City route") changed from 0.65 to 5.2 depending on the Euro 6 step and car. Surprisingly, a Euro 6 b car equipped with Selective Catalytic Reduction SCR system and updated engine control unit (ECU) software for lower tailpipe NO_x emissions provided lower average NO_x emissions than a Euro 6 d-TEMP diesel car equipped with dual lean-NO_x traps. Results for the City route also showed that the road infrastructure (crossroads and speed limitations) can have a noticeable effect on promoting driving that leads to higher NO_x emissions even with a Euro 6 d-TEMP car. Estimations of NO_x emissions with modelling based on continuous NO_x concentration monitoring suggested that Euro 6 b diesel cars can provide NO_x emissions close to the current RDE legislation. In addition, the modelling suggested that the Euro 6 b car with updated ECU software and the Euro 6 d-TEMP diesel car are capable of extremely low daily average NO_x emissions, even close to 20 mg/km, in normal daily usage. Nevertheless, the monitoring results and model also suggest that cold ambient temperature has a high effect on the NO_x emissions reduction performance of these vehicles, occasionally increasing their daily average emissions to as high as 900 mg/km.

Accurate prediction of NOx emissions from diesel engines considering in-cylinder ion current

The main purpose of current study is accurate prediction of NOx emissions from diesel engines considering in-cylinder ion current. To reach this goal, a validated thermodynamic multi-zone model was used. A modified chemical kinetics mechanism of diesel fuel oxidation was used too. A chemical kinetics mechanism of NO_X formation including 103 reactions was added to the main mechanism. A set of ions and ionic reactions was added to the developed chemical kinetics mechanism and finally a modified chemical kinetics mechanism with 445 reactions and 100 species was formed. The developed mechanism was coupled to the multi-zone model and a diesel engine was simulated. The importance of Zeldovich mechanism, prompt mechanism, N₂O mechanism and NNH mechanism were investigated. The progress rates of reactions were calculated and important reactions were identified. The results show that the oxygenated ions, NO⁺, O⁺ and O₂⁺, has more effects on NO production than other ions. The prompt mechanism plays an important role in predicting the ion current inside the chamber. Because this mechanism has reactions that can lead to CH production. The CH radicals produced by this mechanism can be employed by basic ionic reactions and lead to ion production. The results show that using NOx related ionic reactions results in accurate prediction of engine exhaust NOx.

Effects of Cross Level Air Interaction within Multilevel Underground Carparks on Indoor Air Quality

Ventilation for underground carparks is critical to indoor air quality (IAQ) due to carbon monoxide (CO) emissions from cars. The IAQ within a multi-level underground carpark of a shopping mall has been investigated using computational fluid dynamics (CFD) model based on ANSYS-FLUENT (18.1) software. The effects of car engines types, porosity of supply and exhaust air louvers and ventilation flow rates on IAQ were examined. A mesh sensitivity study was conducted and the CFD model was validated against the fully mixed mathematical formulations of IAQ with a maximum difference in values of 1.5 ppm and an error of 3.4%. The results showed that the ventilation system must be operated at ACH value of more than 2.7 in order to meet the required CO concentration of 50 ppm within the carpark and should be based on running cars within each level rather than the parking capacity of each level. Porosity of louvers affected air flow distribution between parking levels and led to higher dilution of CO. Therefore, modelling a multilevel underground carpark requires closer attention to cross level interaction across Ramps which could affect the CO concentration within a given level.

Investigation of the Emission Characteristics of Light-Duty Diesel Vehicles in Korea Based on EURO-VI Standards According to Type of After-Treatment System

This study analyzed the characteristics and distribution of emissions from diesel vehicles that are sold in Korea and satisfy the Euro-6 standards, according to after-treatment systems. To identify the emission distribution of diesel vehicles according to after-treatment systems, results of the certification tests conducted on 266 vehicle models were examined. Results of the certification tests on 86 vehicle models that were manufactured based on the standards for RDE after 2017 were examined according to the engine displacement and power. The emission characteristics of six vehicle models equipped with different types of after-treatment systems were verified through certification tests in the New European Driving Cycle and Worldwide Harmonized Light Vehicle Test Procedure modes and RDE tests, according to the after-treatment systems. Specifically, a chassis dynamometer and an emission analyzer were used in the certification test modes; a portable emissions measurement system was used in the RDE test. The results indicated that the amount of NOx emissions from diesel vehicles has been constantly decreasing since 2017 due to the implementation of standards for RDE and advancements in after-treatment systems. Furthermore, it was found that selective catalyst reduction systems must be installed in vehicles to satisfy Euro-6 standards for permissible emissions on real-roads.

Real-world assessment of vehicle air pollutant emissions subset by vehicle type, fuel and EURO class: New findings from the recent UK EDAR field campaigns, and implications for emissions restricted zones

This paper reports upon and analyses vehicle emissions measured by the Emissions Detecting and Reporting (EDAR) system, a Vehicle Emissions Remote Sensing System (VERSS) type device, used in five UK based field campaigns in 2016 and 2017. In total 94,940 measurements were made of 75,622 individual vehicles during the five campaigns. The measurements are subset into vehicle type (bus, car, HGV, minibus, motorcycle, other, plant, taxi, van, and unknown), fuel type for car (petrol and diesel), and EURO class, and particulate matter (PM), nitric oxide (NO) and nitrogen dioxide (NO₂) are reported. In terms of recent EURO class emission trends, NO and NO_x emissions decrease from EURO 5 to EURO 6 for nearly all vehicle categories. Interestingly, taxis show a marked increase in NO₂ emissions from EURO 5 to EURO 6. Perhaps most concerningly is a marked increase in PM emissions from EURO 5 to EURO 6 for HGVs. Another noteworthy observation was that vans, buses and HGVs of unknown EURO class were often the dirtiest vehicles in their classes, suggesting that where counts of such vehicles are high, they will likely make a significant contribution to local emissions. Using Vehicle Specific Power (VSP) weighting we provide an indication of the magnitude of the on-site VERSS bias and also a closer estimate of the regulatory test/on-road emissions differences. Finally, a new 'EURO Updating Potential' (EUP) factor is introduced, to assess the effect of a range of air pollutant emissions restricted zones either currently in use or marked for future introduction. In particular, the effects of the London based Low Emission Zone (LEZ) and Ultra-Low Emissions Zone (ULEZ), and the proposed Birmingham based Clean Air Zone (CAZ) are estimated. With the current vehicle fleet, the impacts of the ULEZ and CAZ will be far more significant than the LEZ, which was introduced in 2008.

Real world fuel consumption prediction via a combined experimental and modeling technique

This study investigates the possibility to evaluate real-world fuel consumption and CO₂ emissions based on a simulation approach and usage of generic vehicle simulation models, calibrated on the basis of experimental data recorded during on-road tests. A methodology for the development, calibration and validation of the models is described and the proposed simulation approach is applied on three Euro 6 vehicles, one diesel, one gasoline and one plug-in hybrid vehicle. The validation of the developed models is conducted using experimental data recorded during the testing campaign of the above mentioned vehicles. Furthermore, an internal database of vehicle specifications is used to derive the necessary parameters for building the simulation models. With the current study, the capabilities and the boundary conditions for the model-based assessment of real-world CO₂ emissions are investigated. Results indicate that the maximum error in the calculation is lower than 4 g/km, proving a robust simulation approach with an accuracy of ±5% for the estimation of CO₂ emissions under real world conditions.

Perspectives for Mitigation of CO2 Emission due to Development of Electromobility in Several Countries

The creep trend method is used for the analysis of the development of electric car production in three regions: The United States, the European Union and Japan. Based on vehicle registration and population growth data for each year the creep trend method using historical data for the years 2007–2017 is applied for forecasting development up to 2030. Moreover, the original method for calculating the primary energy factor (PEF) was applied to the analysis of power engineering systems in the regions investigated. The assessment of the effects of electromobility development on air quality has been performed, reduction values for pollutant and greenhouse gas emissions have been determined, which was the main objective of this manuscript. Mitigation of air pollutant emissions, i.e., carbon dioxide (CO2), carbon monoxide (CO) and nitrogen oxides (NOx) was estimated and compared to the eventual expected increase of emissions from power plants due to an increase of the demand for electricity. It can be concluded that electricity powered cars along with appropriate choices of energetic resources as well as electricity distribution management will play the important role to achieve the sustainable energy economy. Based on the emission reduction projections resulting from the projected increase in the number of electric cars, (corrected) emissions will be avoided in 2030 in the amount of over 14,908,000 thousand tonnes CO2 in European Union, 3,786,000 thousand tonnes CO2 in United States and 111,683 thousand tonnes CO2 in Japan.

Assessment of Gaseous and Particulate Emissions of a Euro 6d-Temp Diesel Vehicle Driven >1300 km Including Six Diesel Particulate Filter Regenerations

Diesel-fueled vehicles have classically had high particulate and NOx emissions. The introduction of Diesel Particulate Filters (DPFs) and Selective Catalytic Reduction for NOx (SCR) systems have decreased the Particle Number (PN) and NOx emissions, respectively, to very low levels. However, there are concerns regarding the emissions released during the periodic DPF regenerations, which are necessary to clean the filters. The absolute emission levels and the frequency of the regenerations determine the contribution of regenerations, but where they happen (city or highway) is also important due to different contributions to human exposure. In this study, we measured regulated and non-regulated emissions of a Euro 6d-temp vehicle both in the laboratory and on the road. PN and NOx emissions were similar in the laboratory and on-the road, ranging around 1010 p/km and 50 mg/km, respectively. Six regeneration events took place during the 1300 km driven, with an average distance between regeneration events of only 200 km. During regeneration events, the laboratory limits for PN and NOx, although not applicable, were exceeded in one of the two measured events. However, the on-road emissions were below the applicable not-to-exceed limits when regenerations occurred. The weighted PN and NOx emissions over the regeneration distance were approximately two times below the applicable limits. The N2O emissions were <14 mg/km and NH3 at instrument background level (<1 ppm), reaching 8 ppm only during regeneration. The results of this study indicate that due to the short interval between regenerations, studies of diesel vehicles should report the emissions during regeneration events.

Computer Simulation as a Tool for Managing the Technical Development of Methods for Diagnosing the Technical Condition of a Vehicle

Introduced by the Civil Code, the rules of road safety are introducing continuously increasingly strict requirements on motor vehicles. These requirements relate to various aspects of the technical condition of vehicles, both those that determine traffic safety and those that affect the vehicle’s environmental impact. The law requires regular diagnosis of the technical condition of vehicles in service. Diagnostic tests conducted in the form of road tests or the tests performed in workshop conditions allow to determine the symptoms of dysfunctions of the tested vehicle, not always clearly defining the causes and location of damage. The purpose of the work is the design the simulation of a station for of vehicle dynamics tests up to 3.5 t using simulation programs OpenModelica and SciLab. A simulation of the work of the stand for testing the dynamics of vehicles in the form of a chassis dynamometer was achieved. The program enables the simulation of tests: NEDC (New European Drive Cycle), WLTP (Worldwide Harmonized Light Vehicle Test Procedure), CADCM150 (joint Artemis driving cycle—Motorway at vMax = 150 kph), CADCU (Common Artemis Driving Cycle—Urban), FTP75 EPA (Federal Test Procedure, Environmental Protection Agency). The simulator (for any assumed type of vehicle) can be used in two modes: 1. Introduction of the presumed cause—Generates the expected results in the functioning of the vehicle. This function can be used to create a cause–effect relational database. 2. Analysis of data from the actual diagnostic system suggesting the causes of the observed (measured) errors in the functioning of the system. The simulator can be used both to design and implement the technological development of intelligent diagnostic systems, and to support the creation of application software for a workshop diagnostic system. Introducing the simulator into practice will also enable the improvement of road safety management.

Particulate emissions from gasoline direct injection engines: A review of how current emission regulations are being met by automobile manufacturers

Gasoline direct injection (GDI), which is one of the fuel injection technologies extensively used in internal combustion engines, is a viable alternative for port fuel injection technology in premium gasoline (petrol)-run vehicles; furthermore, it provides a better fuel economy, higher thermal efficiency, and greater power output. However, the particulate emissions ejected from modern GDI engines are an environmental and health hazard. As a result, stringent emission legislations are imposed on the production/incorporation of GDI engines. This study reviews the particle masses (PMs) and particle numbers (PNs) of various GDI engines. The backgrounds and highlights of current and future PM emission regulations (Euro 5-6 and China 5-6 GDI engine legislations) are discussed. In addition to the effects of cold-start and oxygenated fuel on PM emissions, this paper also reviews the impacts of engine parameters. Another area of discussion is the particulate filter technology as a solution for pollution control. Concerns about PM emissions from GDI engines are conceptually similar to those about emissions from diesel engines. Finally, this paper discusses the technical and commercial aspects of the use of the particulate matter control technology of GDI engines, such as particulate gasoline filters, as dedicated GDI filtration devices.

Inspection of PN, CO2, and Regulated Gaseous Emissions Characteristics from a GDI Vehicle under Various Real-World Vehicle Test Modes

Although the chassis dynamometer type approval test considers real-world conditions, there are a few limitations to the experimental test environment that may affect gaseous or particulate emissions such as road conditions, traffic, decreasing tire pressure, or fluctuating ambient temperature. Furthermore, the real driving emission (RDE) test takes a long time, and it is too long to repeat under different experimental conditions. The National Institute of Environmental Research (NIER) test modes that reflect the driving pattern of Korea are not certification test modes, but can be used to evaluate the influence of traffic conditions because these modes consist of a total of 15 test modes that vary according to average speed. The use of the NIER #03, #09, and #13 modes as low-, medium-, and high-speed modes allow for gaseous and particulate emissions to be measured and analyzed. Additionally, the worldwide harmonized light-duty vehicle test procedure (WLTP), the certification mode of Europe, is used to test cycles to investigate the difference under cold- and hot-engine start conditions. The engine operating parameters are also measured to evaluate the relationships between the various test conditions and test cycles. The regulated and greenhouse gas levels decrease under various driving conditions, but the particle number (PN) emission level shows a different trend with gaseous emissions. While the PN and CO2 results dramatically increase when the air conditioner is on, tire pressure conditions show different PN size distributions: a large-sized PN fraction, which contains particles larger than 100 nm, increases and a sub-23 nm-sized PN fraction decreases. Under cold-start conditions in the WLTP modes, there are much higher PN emissions than that of an engine under hot-start conditions, and the sub-23-nm-sized PN fraction also increases.

On-road gaseous and particulate emissions from GDI vehicles with and without gasoline particulate filters (GPFs) using portable emissions measurement systems (PEMS)

This study assessed the on-road gaseous and particulate emissions from three current technology gasoline direct injection (GDI) vehicles using portable emissions measurement systems (PEMS). Two vehicles were also retrofitted with catalyzed gasoline particulate filters (GPFs). All vehicles were exercised over four routes with different topological and environmental characteristics, representing urban, rural, highway, and high-altitude driving conditions. The results showed strong reductions in particulate mass (PM), soot mass, and particle number emissions with the use of GPFs. Particle emissions were found to be highest during urban and high-altitude driving compared to highway driving. The reduction efficiency of the GPFs ranged from 44% to 99% for overall soot mass emissions. Similar efficiencies were found for particle number and PM mass emissions. In most cases, nitrogen oxide (NOx) emissions showed improvements with the catalyzed GPFs in the underfloor position with the additional catalytic volume. No significant differences were seen in carbon dioxide (CO₂) and carbon monoxide (CO) emissions with the vehicles retrofitted with GPFs.

Variation trends and principal component analysis of nitrogen oxide emissions from motor vehicles in Wuhan City from 2012 to 2017

In addition to fine particulate matter and oxysulfides, nitrogen oxides (NO_x) emitted by motor vehicles are among the most important pollutants affecting air quality and public health in those urban areas where centralized heating and chemical industry absent. We utilized correlation analysis (pearson correlation coefficient and spearman correlation coefficient) and principal component analysis (PCA) to identify the variation trends and main causes of NO_x emissions from motor vehicles in Wuhan City. We considered the total number of motor vehicles (TN), ratios of motor vehicles of different emission standards (RE), rations of labeled motor vehicles (RL), and rations of motor vehicles' fuel types (RF). The results show that: 1) with an increase in the total amount of motor vehicles, the NO_x emissions of motor vehicles have been decreasing since 2015; 2) three sub-categories (the ratio of the State III emission standard, the ration of yellow label diesel vehicles, and the ration of diesel vehicles) were recognized as key indexes of PE, PL and PF, respectively, in the PCA; 3) a new parameter, the ES_index is proposed as an index to represent the variation trend of the NO_x emissions of motor vehicles in Wuhan City.

A remote sensing emissions monitoring programme reduces emissions of gasoline and LPG vehicles

Vehicle emissions are a major source of air pollution in Hong Kong affecting human health. A 'strengthened emissions control of gasoline and liquefied petroleum gas (LPG) vehicles' programme has been operating in Hong Kong since September 2014 utilising remote sensing (RS) technology. RS has provided measurement data to successfully identify high emitting gasoline and LPG vehicles which then need to be repaired or removed from the on-road vehicle fleet. This paper aims to evaluate the effectiveness of this globally unique RS monitoring programme. A large RS dataset of 2,144,422 records was obtained covering the period from 6th January 2012 to 30th December 2016, of which 1,206,762 records were valid and suitable for further investigation. The results show that there have been significant reductions of emissions factors (EF) for 40.5% HC, 45.3% CO and 29.6% NO for gasoline vehicles. Additionally, EF reductions of 48.4% HC, 41.1% CO and 58.7% NO were achieved for LPG vehicles. For the combined vehicle fleet, the reductions for HC, CO and NO were 55.9%, 50.5% and 60.9% respectively during this survey period. The findings demonstrate that the strengthened emissions control programme utilising RS has been very effective in identifying high emitting vehicles for repair so as to reduce the emissions from gasoline and LPG vehicles under real driving.

On-road emissions of passenger cars beyond the boundary conditions of the real-driving emissions test

Passenger cars are an important source of air pollution, especially in urban areas. Recently, real-driving emissions (RDE) test procedures have been introduced in the EU aiming to evaluate nitrogen oxides (NOx) and particulate number (PN) emissions from passenger cars during on-road operation. Although RDE accounts for a large variety of real-world driving, it excludes certain driving situations by setting boundary conditions (e.g., in relation to altitude, temperature or dynamic driving). The present work investigates the on-road emissions of NOx, NO₂, CO, particle number (PN) and CO₂ from a fleet of 19 Euro 6b, 6c and 6d-TEMP vehicles, including diesel, gasoline (GDI and PFI) and compressed natural gas (CNG) vehicles. The vehicles were tested under different on-road driving conditions outside boundaries. These included 'baseline' tests, but also testing conditions beyond the RDE boundary conditions to investigate the performance of the emissions control devices in demanding situations. Consistently low average emission rates of PN and CO were measured from all diesel vehicles tested under most conditions. Moreover, the tested Euro 6d-TEMP and Euro 6c diesel vehicles met the NOx emission limits applicable to Euro 6d-TEMP diesel vehicles during RDE tests (168 mg/km). The Euro 6b GDI vehicle equipped with a gasoline particulate filter (GPF) presented PN emissions < 6 × 10¹¹ #/km. These results, in contrast with previous on-road measurements from earlier Euro 6 vehicles, indicate more efficient emission control technologies are currently being used in diesel and gasoline vehicles. At the same time, the results suggest that particular attention should be given to CO and PN emissions of certain types of vehicles when driven under dynamic conditions, and possibly additional work is necessary. In particular, the emissions of CO (measured in this study during the regulated RDE test, but without an emission limit associated to it) or PN from PFI vehicles (presently not covered by the Euro 6 standard) showed elevated results in some occasions. Emissions of CO were up to 7.5 times higher when the more dynamic tests were conducted and the highest PN emissions were measured from a PFI gasoline vehicle during dynamic driving. Although based on a limited sample of cars, our work points to the relevance of a technology- and fuel-neutral approach to vehicle emission standards, whereby all vehicles must comply with the same emission limits for all pollutants.

The Development of Electromobility in Poland and EU States as a Tool for Management of CO2 Emissions

The article analyzes the dynamics of the development of the electromobility sector in Poland in the context of the European Union and due to the economic situation and development of the electromobility sector in the contexts of Switzerland and Norway. On the basis of obtained data, a forecast was made which foresees the most likely outlook of the electric car market in the coming years. The forecast was made using the creeping trend method, and extended up to 2030. As part of the analysis of the effect of the impact of electromobility, an original method was proposed for calculating the primary energy factor (PEF) primary energy ratio in the European Union and in its individual countries, which illustrates the conversion efficiency of primary energy into electricity and the overall efficiency of the power system. The original method was also verified, referring to the methods proposed by the Fraunhofer-Institut. On the basis of all previous actions and analyses, an assessment was made of the impact of the development of the electromobility sector on air quality in the countries studied. Carbon dioxide tank-to-wheels emission reductions which result from the conversion of the car fleet from conventional vehicles to electric motors were then calculated. In addition to reducing carbon dioxide emissions, other pollutant emissions were also calculated, such as carbon monoxide (CO), nitrogen oxides (NOx) and particulate matter (PM). The increase in the demand for electricity resulting from the needs of electric vehicles was also estimated. On this basis, and also on the basis of previously calculated primary energy coefficients, the emission reduction values have been adjusted for additional emissions resulting from the generation of electricity in power plants.

Strong Temperature Dependence for Light-Duty Diesel Vehicle NO x Emissions

Diesel-powered road vehicles are important sources for nitrogen oxide (NO _x) emissions, and the European passenger fleet is highly dieselised, which has resulted in many European roadside environments being noncompliant with legal air quality standards for nitrogen dioxide (NO₂). On the basis of vehicle emission remote sensing data for 300000 light-duty vehicles across the United Kingdom, light-duty diesel NO _x emissions were found to be highly dependent on ambient temperature with low temperatures resulting in higher NO _x emissions, i.e., a "low temperature NO _x emission penalty" was identified. This feature was not observed for gasoline-powered vehicles. Older Euro 3 to 5 diesel vehicles emitted NO _x similarly, but vehicles compliant with the latest Euro 6 emission standard emitted less NO _x than older vehicles and demonstrated less of an ambient temperature dependence. This ambient temperature dependence is overlooked in current emission inventories but is of importance from an air quality perspective. Owing to Europe's climate, a predicted average of 38% more NO _x emissions have burdened Europe when compared to temperatures encountered in laboratory test cycles. However, owing to the progressive elimination of vehicles demonstrating the most severe low temperature NO _x penalty, light-duty diesel NO _x emissions are likely to decrease more rapidly throughout Europe than currently thought.

A study on the CO2 and NOx emissions performance of Euro 6 diesel vehicles under various chassis dynamometer and on-road conditions including latest regulatory provisions

The current study presents a detailed analysis of the gaseous emissions, focusing on CO₂ and NO_x, of diesel vehicles under several operating conditions. An assessment is also made on the impact and effectiveness of the Real Driving Emissions (RDE) test, which is mandatory by the European Union (EU) type approval regulation for passenger cars since September 2017. The method followed comprises emissions measurement tests on three Euro 6 diesel vehicles, under laboratory and various on-road operation conditions. Chassis dynamometer tests in the laboratory showed that emissions over the current type approval test (World-wide harmonized Light-duty Test Procedure or WLTP), and over the former one (New European Driving Cycle or NEDC), poorly reflect real-world levels. However, the most demanding CADC testing comes closer to real drive emissions. Comparison of driving conditions on the chassis dynamometer over different driving cycles and on the road reveals that the emission performance substantially varies between different tests, even for apparently similar operation conditions. The NO_x emissions reduction strategy of pre-RDE monitoring Euro 6 vehicles seems to be optimized for the NEDC driving conditions, which are not representative of the real-world driving conditions. The real-world emissions during normal driving conditions are effectively captured with the new RDE test, however driving the vehicle dynamically, at conditions outside the RDE regulation boundaries, results to disproportional high emissions. This is a significant shortcoming which might be critical for populations living on hilly areas or those close to specific micro-environments, such as highway entrance ramps, traffic lights, etc.