Search Results (168)

Although particulate matter (PM) pollution from vehicles’ exhaust has decreased significantly over the years, the contribution from non-exhaust sources (brakes, tyres) has remained at the same levels. In the European Union (EU), Euro 7 regulation introduced PM limits for vehicles’ brake systems. Regenerative braking, i.e., recuperation of the deceleration kinetic and potential energy to the vehicle battery, is one of the strategies to reduce the brake emission levels and improve vehicle efficiency. According to the regulation, the shares of friction and regenerative braking can be determined with actual testing of the vehicle on a chassis dynamometer. In this study we tested the regenerative capabilities of a plug-in hybrid vehicle, both in the laboratory and on the road, under different protocols (including both smooth and aggressive braking) and covering a wide range of driving conditions (urban, rural, motorway) over 10,000 km of driving. Good agreement was obtained between laboratory and on-road tests, with the use of the friction brakes being on average 7% and 5.3%, respectively. However, at the same time it was demonstrated that the friction braking share can vary over a wide range (up to around 30%), depending on the driver’s behaviour. Full article

Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse spatial and traffic conditions. This study investigates the influence of concrete pavement macrotexture—specifically the Mean Texture Depth (MTD) and surface wavelength—on PM₁₀ resuspension. Field data were collected using a vehicle-mounted DustTrak 8530 sensor following the TRAKER protocol, enabling real-time monitoring near the tire–pavement interface. A multivariable linear regression model was used to evaluate the effects of MTD, wavelength, and the interaction between silt loading (sL) and PM₁₀ content, achieving a high adjusted R² of 0.765. The surface wavelength and sL–PM₁₀ interaction were statistically significant (p < 0.01). The PM₁₀ concentrations increased with the MTD up to a threshold of approximately 1.4 mm, after which the trend plateaued. A short wavelength (<4 mm) resulted in 30–50% higher PM₁₀ emissions compared to a longer wavelength (>30 mm), likely due to enhanced air-pumping effects caused by more frequent aggregate contact. Among pavement types, Transverse Tining (T.Tining) exhibited the highest emissions due to its high MTD and short wavelength, whereas Exposed Aggregate Concrete Pavement (EACP) and the Next-Generation Concrete Surface (NGCS) showed lower emissions with a moderate MTD (1.0–1.4 mm) and longer wavelength. Mechanistically, a low MTD means there is a lack of sufficient voids for dust retention but generates less turbulence, producing moderate emissions. In contrast, a high MTD combined with a very short wavelength intensifies tire contact and localized air pumping, increasing emissions. Therefore, an intermediate MTD and moderate wavelength configuration appears optimal, balancing dust retention with minimized turbulence. These findings offer a texture-informed framework for integrating pavement surface characteristics into PM emission models, supporting sustainable and emission-conscious pavement design. Full article

Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NO_x and EGR), a factor of 3 or more (NO_x and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NO_x), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NO_x (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article

Evaluating the impact on roadside environments of NH₃ from vehicle emissions is important for protecting the ecosystem from air pollution by fine particulate matter and nitrogen deposition. This study used passive samplers to measure NH₃ and NO_X at multiple points near a major road to observe the distribution of these gases in the area. The impact of NH₃ emitted from vehicles on a major road on the environmental concentration of NH₃ at different distances from the roadside was found to be similar to that of NO_X and NO₂. The concentration of NH₃ rapidly decreased due to dilution and diffusion within approximately 50 m of the road, and after 100 m the concentration remained almost the same or decreased slowly. Furthermore, CO₂ observations taken in the same period along the roadside and in the background yielded a vehicular emission factor of 4–50 mg/km for NH₃, which is comparable with previous research. This emission factor level contributes 4–11 ppb to the NH₃ concentrations in roadside air through the dilution and diffusion process. A correlation was found between the emission factors of NH₃ and NO_X that was different from the trade-off relationship seen when single-vehicle exhaust is measured. Full article

Motor vehicles emit a large amount of air pollutants. Inspection and Maintenance (I/M) systems serve as a pivotal strategy for mitigating emissions from operational diesel trucks. However, the prevalent issue of blind repairs persists due to insufficient diagnostic capabilities at maintenance stations (M stations). To address this challenge, a multi-source information fusion methodology is proposed, integrating load deceleration testing from inspection stations (I stations), on-board diagnostics (OBD) data, and manual measurements at M stations. Critical diagnostic parameters—including nitrogen oxides (NOx) and particulate matter (PM) emissions, the ratio of measured wheel-side power to rated power, intake volume, common rail pressure, and exhaust back pressure—are systematically selected through statistical analysis and expert evaluations. An adaptive membership function is developed to resolve ambiguities in emission thresholds, enabling the construction of a robust fault diagnosis framework. Validation using 800 National V diesel truck maintenance records from a provincial automotive electronic health platform (2022 data) demonstrates a diagnostic accuracy of 92.8% for 153 emission-exceeding vehicles, surpassing traditional machine learning approaches by over 20%. By minimizing unnecessary repairs and optimizing maintenance efficiency, this approach significantly reduces resource waste and the lifecycle environmental footprints of diesel fleets. The proposed fuzzy-logic-based model effectively detects latent faults during routine maintenance, directly contributing to sustainable transportation through reductions in NOx and PM emissions—critical for improving air quality and advancing global climate objectives. This establishes a scalable technical framework for the effective implementation of I/M systems in alignment with sustainable urban mobility policies. Full article

To address the current issues with diesel vehicle exhaust after-treatment system particulate sensors—such as low accuracy and inability to perform continuous measurements of particulate mass concentration—a new sensor based on the light scattering method is proposed. During the research, it was found that the light scattering method can be affected by soot particles in the exhaust, which contaminate the optical components and reduces measurement accuracy. To solve this issue, a structure with alumina ceramic embedded lenses and optical fibers was designed, effectively improving the sensor’s resistance to contamination. The detection device is based on the principle of light scattering, and a particulate concentration measurement system with a 90° scattering angle was built. Calibration experiments were conducted using the dust particles generated by the device. The experimental results show that this sensor can measure particulate concentrations accurately, in real time, and with good stability, achieving a calibration error of less than ±5%. Full article

Vehicle exhaust is a major source of air pollution that contributes to environmental degradation and poses risks to public health. This paper presents an image-based method to estimate opacity (OP) and particulate matter (PM) from vehicle exhaust. In the proposed method, YOLOv7 was used to identify vehicles and, thus, the region of interest (ROI). Then, a support vector regression was trained, with four image features extracted from the ROI as the input vectors, while OP or PM was used as the output. The proposed method was verified by experiments where moving and static scenarios with three ROIs were considered. The ROIs used in the experiments were exhaust pipe area (EPA), vehicle bounding box (VBB), and white background (WBG). In the moving scenario, the EPA and VBB ROIs were considered. For the VBB ROI, the average R² values for OP and PM in the given examples were 0.834 and 0.894, respectively. For the EPA ROI, the average R² values for OP and PM were 0.838 and 0.910, respectively. In the static scenario, the EPA and WBG ROIs were considered. For the EPA ROI, the average R² values for OP and PM were 0.619 and 0.612, respectively. For the WBG ROI, the average R² values for OP and PM were 0.748 and 0.732, respectively. The results suggest that the EPA ROI is preferable in the moving scenario and the WBG ROI in the static scenario to estimate OP and PM from vehicle exhaust. The proposed method is promising in the estimation of OP and PM from vehicle exhaust because satisfactory R² values were achieved. Full article

In recent years, the transition to electric vehicles has accelerated significantly. However, this shift does not imply the complete elimination of diesel engine vehicles, particularly in commercial and cargo transport, where diesel engines remain essential due to their high thermal efficiency and torque. Despite their advantages, diesel engines produce particulate matter (PM) in their exhaust, which poses environmental and health risks. To mitigate PM emissions, diesel particulate filters (DPFs) are integrated into exhaust systems. However, as PM accumulates in the DPF, pressure drops occur, increasing the load on the engine. Therefore, periodic removal of PM through oxidation, known as regeneration, is required. Optimizing the PM combustion temperature improves fuel efficiency, but since diesel engine exhaust temperatures typically range from 100 to 500 °C, catalysts that facilitate PM oxidation at lower temperatures are necessary. This study focuses on PM oxidation catalysts designed for low-temperature diesel exhaust conditions. One of the key challenges in this area is the difficulty in directly observing PM trapping and oxidation behavior within a catalyzed DPF. Additionally, changing the catalyst during experiments is not straightforward. To address these challenges, we have developed a numerical model that simulates the entire process—from PM deposition to oxidation—inside a DPF. This model allows for easy modification of catalyst properties, providing a flexible framework for analyzing PM oxidation behavior under various conditions. In this study, numerical simulations were conducted to analyze the PM deposition and oxidation processes within the DPF. The results were derived from a simplified model developed specifically for this research. The proposed calculation method allows for the qualitative assessment of DPF performance when catalysts are altered, contributing to the optimization of DPF design. Full article

Diesel-engine Heavy-Duty Vehicle (HDV) exhaust gas mixture contains pollutants including unburned hydrocarbons, carbon monoxide, nitrogen oxides, and particulate matter. A catalyst-based emission control system is commonly used to eliminate the above pollutants. However, the excess of oxygen that exists in the exhaust gasses of diesel engines hinders the efficient and selective reduction of nitrogen oxides over conventional catalytic converters. The AdBlue^® solution, which is currently used to eliminate nitrogen oxides, is based on ammonia. The latter is toxic in high concentrations. The aim of this work is to develop an Oxygen Reduction System (ORS) to remove oxygen from the exhaust gas of diesel engines, allowing the successful catalytic reduction of nitrogen oxides on a reduction catalyst without the need for ammonia. The ORS device consists of dense composite dual-phase membranes that allow the permeation of oxygen and carbon dioxide. Even though the oxygen concentration gradient across the membranes favors oxygen spontaneous diffusion from the atmosphere to the exhaust gas, the carbonate ion-based technology proposed herein utilizes the big difference in the concentration of carbon dioxide across the membrane to remove oxygen without any power consumption requirement. The results of this study are promising for the application of O₂ reduction in diesel HDVs. Full article

Diesel vehicles are recognized as significant mobile sources of particulate matter emissions. As a renewable and environmentally friendly alternative to conventional fossil diesel, biodiesel offers the benefit of reducing greenhouse gas emissions. However, existing research on biodiesel emissions primarily focuses on primary emissions, with a limited understanding of their impact on secondary organic aerosol (SOA) formation. In this study, a diesel engine test bench was employed under idle conditions using three commonly used biodiesel blends. Exhaust emissions were directly introduced into the HAP-SWFU chamber, a quartz glass smog chamber designed to characterize both primary emissions and SOA formation during the photochemical oxidation process. The black carbon and primary organic aerosol (POA) emission factors for the three biodiesel blends under idle conditions ranged from 0.31 to 0.58 g kg⁻¹ fuel and 0.99 to 1.06 g kg⁻¹ fuel, respectively. The particle size of exhaust particulates peaked between 20 and 30 nm, and nucleation-idle conditions were found to be the dominating mode. The SOA production factor was between 0.92 and 1.15 g kg⁻¹ fuel, and the SOA/POA ratio ranged from 1.35 to 2.37, with an average of 1.86. This study concludes that the POA emission factor for biodiesel under idle conditions is comparable to values reported in previous studies on pure diesel exhaust, with the maximum SOA production factor reduced by 38%. Full article

Particle number concentration (PN) in vehicle exhaust and ambient air describes the number of ultrafine particles (UFPs) below 500 nm, which are recognized as a toxic and carcinogenic component of pollution and are regulated in several countries. Metal nuclei, ash, and organic matter contribute significantly to the ultrafine particle size fraction and, thus, to the particle number concentration. Exhaust gas filtration is increasingly being used worldwide to significantly reduce this pollution, both on diesel particulate filter (DPF) and gasoline particulate filter (GPF) engines. In recent years, the EU has also funded research projects dealing with the possibilities of retrofitting gasoline vehicles with GPFs. This paper presents the results and compares the PN emissions of different vehicles. An original equipment manufacturer (OEM) diesel car with a DPF is considered as a benchmark. The PN emissions of this car are compared with a CNG car without filtration and with gasoline cars equipped with GPFs. It can be concluded that the currently used GPFs still have some potential to improve their filtration efficiency and that a modern CNG car would still have remarkable possibilities to reduce PN emissions with an improved quality GPF. Full article

This research proposed the method of using cumulative positive and negative elevation increment indicators based on road segment to identify the slope characteristics of mountain city roads. Furthermore, it proposed the adoption of these indicators, combined with driving dynamics and emission theory, to analyze the correlation mechanism between the road slope and the actual driving fuel consumption and emissions. Three routes with different slope characteristics were selected in the mountain city of Chongqing, and six road driving tests were conducted using a Class N2 heavy-duty diesel vehicle. Finally, a comprehensive and in-depth study on fuel consumption and emission characteristics was carried out. The results show that the cumulative positive and negative elevation increment indicators based on road segment can correctly identify the complex slope characteristics of mountain city roads. Moreover, using the above indicators, the research method based on the theory of driving dynamics and emission successfully revealed the correlation mechanism between the slope of mountain city roads and the fuel consumption and emissions. Overall, the changes in fuel consumption factor and pollutants CO, NO_X, and PN are positively correlated with the change in slope. The increase in slope leads to a rise in load, thereby increasing the required power, fuel consumption, and rich combustion conditions, ultimately leading to an increase in pollutants. It should be noted that driving dynamics also affect fuel consumption and emissions, leading to the specific rate of change between slope and fuel consumption not being consistent and a significant increase in the PN (Particulate Number) on some road sections. In addition, exhaust gas temperature may have a certain impact on emissions. Full article

Thousands of particle number (PN) counters have been introduced to the European market, following the implementation of PN tests during the periodic technical inspection (PTI) of diesel vehicles equipped with particulate filters. Expanding the PN-PTI test to gasoline vehicles may face several challenges due to the different exhaust aerosol characteristics. In this study, two PN-PTI instruments, type-examined for diesel vehicles, measured fifteen petrol passenger cars with different test protocols: low and high idling, with or without additional load, and sharp accelerations. The instruments, one based on diffusion charging and the other on condensation particle counting, demonstrated good linearity compared to the reference instrumentation with R-squared values of 0.93 and 0.92, respectively. However, in a considerable number of tests, they registered higher particle concentrations due to the presence of high concentrations below their theoretical 23 nm cut-off size. The evaluation of the different test protocols showed that gasoline direct injection engine vehicles without particulate filters (GPFs) generally emitted an order of magnitude or higher PN compared to those with GPFs. However, high variations in concentration levels were observed for each vehicle. Port-fuel injection vehicles without GPFs mostly emitted PN concentrations near the lower detection limit of the PN-PTI instruments. Full article

In the current global scenario, it is essential to find more effective and practical solutions to mitigate the problem of particulate emissions from vehicles. In this research, particulate emission characteristics with changing GDI pressure or applying a split GDI strategy with different second injection timings were initially explored in a Dual-Fuel Spark Ignition (DFSI) engine, which employs Ethanol Port Injection (EPI) plus Gasoline Direct Injection (GDI). The experimental results show that by increasing GDI pressure ($P_{GDI}$) from 5.5 MPa to 18 MPa, ignition delay (${\theta }_F$) shows a small decrease of 0.68 degrees. The parameters, such as maximum in-cylinder temperature ($T_{MI}$) and exhaust gas temperature ($T_{EG}$), each increase by 53.75 K and 13.84 K. An apparent reduction of 59.5% and 36.26% was achieved for the concentrations of particulate number ($N_P$) and particulate mass ($M_P$), respectively. Particulate emissions are effectively reduced by a split GDI strategy with an appropriate range of second injection timing ($t_{GDI2}$). Under $t_{GDI2}$ = −260 °CA, $N_P$ and $M_P$ concentrations exhibit a relatively lower level. However, by delaying $t_{GDI2}$ from −260 °CA to −140 °CA, there is an increase of more than 60% in $N_P$ concentration. The research findings help offer new and valuable insights into optimising particulate number and mass emissions from DFSI engines. Moreover, the findings could contribute novel and valuable insights into the optimisation of particulate emission characteristics in DFSI engines. Full article

In this study, online ambient volatile organic compounds (VOCs) were collected at an urban site of Zhengzhou in Central China during February 2018. The VOCs characteristics, source contributions and the Chinese New Year (CNY) effects have been investigated. During the sampling period, three haze periods have been identified, with the corresponding VOCs concentrations of (92 ± 45) ppbv, (62 ± 18) ppbv and (83 ± 34) ppbv; in contrast, the concentration during non-haze days was found to be (57 ± 27) ppbv. In addition, the festival effects of the CNY were investigated, and the concentration of particulate matter precursor decreased significantly. Meanwhile, firework-displaying events were identified, as the emission intensity had been greatly changed. Both potential source contribution function (PSCF) and the concentration weighted trajectory (CWT) models results indicated that short-distance transportation was the main influencing factor of the local VOCs pollution, especially by transport from the northeast. Source contribution results by the positive matrix factorization (PMF) model showed that vehicle exhaust (24%), liquid petroleum gas and natural gas (LPG/NG, 23%), coal combustion (21%), industrial processes (16%) and solvent usages (16%) were the major sources of ambient VOCs. Although industry and solvents have low contribution to the total VOCs, their secondary organic aerosol (SOA) contribution were found to be relatively high, especially in haze-1 and haze-3 periods. The haze-2 period had the lowest secondary organic aerosol potential (SOAp) during the sampling period; this is mainly caused by the reduction of industrial and solvent emissions due to CNY. Full article