Light-duty Diesel Vehicles Research Articles

NOx reduction scenarios under real-world driving conditions for light-duty diesel vehicles

This study analyze analyzes the impact of stringent emissions regulations on future NOx reductions. Using scenario analysis, NOx emissions of diesel light-duty vehicles from 2019 to 2040 are estimated using emission factors from real driving emissions data. The baseline scenario assumes current regulations will be maintained, while other scenarios assess the impact of implementing specific Euro standards as final regulations. If Euro 5 regulations are implemented by 2040, cumulative emissions will increase by 229.1 % compared to the baseline scenario. Implementing Euro 6 a/b/c regulations will increase by 156.2 %, while Euro 6 d-temp and Euro 6 d regulations will increase by 8.4 % and 0.7 %, respectively. These findings highlight the significant contribution of real driving emission test introduced with Euro 6 d-temp to NOx reduction. Furthermore, they indicate that Euro 6 d regulation has already achieved emission levels similar to those of the upcoming Euro 7 regulation.

Engine & vehicle modeling for fuel assessment under local driving conditions

Automotive biofuels offer a promising alternative to traditional fossil fuels. Accurate evaluation of combustion and emissions in IC engines and vehicles is crucial. This research aimed at developing and validating an engine and vehicle simulation methodology to assess the fuel effect on vehicle consumption and emissions considering different driving cycles and the road slope (barely evaluated for fuels widely used in emerging markets). Two blends were tested: 20 % biodiesel (B20) and 20 % hydrotreated vegetable oil (HVO20) with Ultra-Low-Sulfur Diesel (ULSD). A light-duty diesel vehicle model was developed in GTSuite®, using emission maps from a calibrated steady-state engine model. Good agreement with experiments was found. Road slope in local DC significantly increased fuel consumption and CO, CO2, NOx, and PN emissions, reducing HC. Compared to ULSD, B20 reduced PN and HC by 27–35 % and 12–22.5 %, respectively. HVO20 had a smaller effect on PN but reduced HC emissions by up to 19.5 %. Neither blend significantly affected CO and CO2. B20 slightly increased NOx and fuel consumption, while HVO20 had no significant impact on these.

Challenges and Solutions to Meet the Euro 7 NOx Emission Requirements for Diesel Light-Duty Commercial Vehicles

AbstractThe improvement of air quality requires a further reduction of pollutant emissions, especially in urban areas. The Euro 7 regulations aim at the development of a new generation of internal combustion engine vehicles capable of achieving ultra-low pollutant emissions under demanding, real-world operating conditions. They introduce new technical challenges in the holistic design of a vehicle’s powertrain and emission control system. To identify these, four real-world Euro 7 driving scenarios are investigated, covering demanding urban, highway and mountain driving situations. Technical solutions are then presented to address these challenges and ensure compliance with the Euro 7 emission requirements as set out in the latest regulation proposal of the European Commission. The study focuses on the NOx emissions of an N1 Class III light commercial vehicle with 3.5 t mass and a P2 diesel mild-hybrid powertrain. To ensure emission compliance, a Euro 6e exhaust gas aftertreatment system with enlarged catalysts is combined with NOx raw emission improvements. For low-load cold starts, a 4-kW electric heater in the exhaust system is considered in addition to a 2-l DOC and a 6-l DPF with SCR coating. For high-load cycles with high raw emissions, a 10-l underfloor SCR is considered to ensure the necessary deNOx performance.

Emission characteristic, spatial distribution, and health risk of polycyclic aromatic compounds (PAHs, NPAHs, and OPAHs) from light-duty gasoline and diesel vehicles based on on-road measurements

Vehicle exhaust is the primary source of polycyclic aromatic compounds (PACs). Real road tests using a portable vehicle measurement system on light-duty gasoline vehicles and light-duty diesel trucks were conducted to investigate gas- and particle-phase polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs (NPAHs), and oxy-PAHs (OPAHs) in vehicle exhaust with different emission standards, fuel types, and altitudes. The results showed that with the tightening of emission standards, the overall emission factors (EFs) of PACs decreased. Compared with China V diesel vehicles, the emissions of PAHs, OPAHs, and NPAHs from China VI diesel vehicles were 75.1 %, 84.4 %, and 61.2 % lower, respectively. With a ∼100 m increase in altitude, the EFs of PAHs, OPAHs, and NPAHs of diesel vehicles increased 1.88, 1.92, and 1.59 times due to incomplete combustion. In addition, the EFs of PAHs and OPAHs in gasoline vehicles were lower than those in diesel vehicles. In contrast, the proportion of PAHs with highly toxic components, such as dibenzo[a,h]anthracene (DahA) and benzo[a]pyrene (BaP), and the EFs of gas-phase NPAHs in gasoline vehicles were higher than those in diesel vehicles. Furthermore, the emissions of 1,8-DNP from diesel vehicles cannot be disregarded. 1,8-DNP was the main gas-phase NPAHs emitted by China VI and China V diesel vehicles, accounting for 49.3 % and 26.0 %, respectively. Moreover, gas-phase PACs contributed more to the EFs than particle-phase PACs, whereas particle-phase PACs have greater toxic effects. Although the EFs of PAHs are more than 100 times those of NPAHs, the toxic equivalent concentrations (TEQBaP) of PAHs in diesel and gasoline vehicles were approximately 6.5 times and 35 times those of NPAHs. The spatial distribution characteristics revealed that PACs emissions were mainly concentrated in urban areas and highways, and the differences in the toxicity of PACs emissions between different cities depended on the proportion of diesel vehicles. The average TEQBaP of PAHs and NPAHs in Haidong, Haibei, Huangnan, Hainan, Guoluo, and Yushu was 8.42 μg/m3 and 0.36 μg/m3, respectively, while those of Xining and Haixi were 0.24–0.29 μg/m3 and 0.09–0.108 μg/m3 higher, respectively. This study provides a comprehensive understanding of the emission characteristics, health risks, and spatial distribution of PACs from diesel and gasoline vehicle PACs in urban areas.

Investigating the impact of high-altitude on vehicle carbon emissions: A comprehensive on-road driving study

This study addresses the literature gap concerning accurately identifying vehicle carbon emission characteristics in high-altitude areas. Utilizing a portable emission measurement system (PEMS) for real-world testing, we quantified the influence of altitude on carbon emissions from light-duty gasoline (LDGV) and diesel vehicles (LDDV). The Random Forest (RF) algorithm was employed to analyze the complex nonlinear relationships between altitude, meteorological conditions, driving patterns, and carbon dioxide (CO2) emissions, enabling predictions across different altitudes. The results showed that CO2 emissions progressively increase with elevation. Furthermore, as altitude increases, combustion efficiency declines, and the overall impact of driving conditions on emission rates diminishes. Altitude and meteorological factors significantly contributed to CO2 emissions, whereas driving conditions and road grades contributed less. Compared with the COPERT model, the RF model demonstrates strong accuracy in predicting carbon emissions at different altitudes. Specifically, the CO2 emission rate nearly triples as altitude increases from 2.0 km to 4.5 km. This research bridges a critical gap in the understanding carbon emissions from high-altitude vehicles, offering insights into policy development for emission reduction strategies in such regions. Future studies should integrate diverse testing methodologies and comprehensive surveys to validate and extend the findings.

Effect of a retrofitted metallic microfiber partial flow diesel particulate filter on a light duty diesel vehicle particle emission characteristics

This study was conducted two distinct experiments, using a light-duty diesel vehicle at various engine speeds and loads as well as the new European driving cycle (NEDC) comparing commercial diesel fuel (B7) and pure biodiesel (B100). The NEDC involves a combination of urban and extra urban driving conditions. It aims to study a diesel vehicle's thermal efficiency as well as its gaseous and particulate matter (PM) emissions. This involves comparing results with and with no diesel oxidative catalyst (DOC) and a partial flow diesel particulate filter (PDPF) system. The surface morphology, micro- and nanostructure of a diesel vehicle's PM were also examined using scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and thermogravimetric analysis (TGA) to determine nanostructural and dimensional changes after mounting a DOC-PDPF system. Comparison of B7 and B100 combustion showed that B100 had around 1 % increase in brake thermal efficiency (BTE) at 1500 and 2000 rpm compared to B7 since B100 is a more oxygenated biofuel. At 2500 rpm, similar BTE values were observed. Introduction of a DOC-PDPF system resulted in an approximately 1 % BTE reduction for both fuels. This was due to greater friction losses caused by backpressure from the DOC-PDPF system. Increased exhaust backpressure was progressive, ranging from 1 kPa at idle speed to 6 kPa at high engine speeds for both tested fuels. The DOC-PDPF system respectively minimized PM emissions and particle numbers (PNs) by more than 50 % and 35 % for B7 and 71 % and 31 % for B100. These results are average values under the various phases of NEDC testing. A 30 % decrease in PM and a 44 % reduction in PNs under the overall test cycle were found when B100 was tested compared to B7. The soot primary particle size was reduced from 34.69 to 29.08 nm and the carbon fringe length diminished from 1.25 to 0.949 nm at different pre- and post-DOC-PDPF locations. This was due to partial oxidation on the surfaces of the PDPF metallic microstructure. PM undergoes simultaneous partial oxidation after passing through the DOC-PDPF system, as confirmed by TGA analysis.

Study on Control Strategies on NOX Emissions to Meet Real Driving Emissions.

The aim of this study was to fulfill the NOx emissions standards for a light-duty diesel vehicle under real driving emissions (RDE) testing conditions by implementing various control strategies. In this study, RDE tests were performed by adjusting the air mass quantity and postinjection quantity in order to analyze engine-out and tail-pipe nitrogen oxides (NOx) emissions for different phases of RDE. The results showed that reducing in air mass quantity enabled the engine to operate in higher exhaust gas recirculation (EGR) rate regions, resulting in a 32.5% reduction in engine-out NOx emissions and an 80.4% decrease in tail-pipe NOx emissions. Increasing the postinjection quantity primarily enhanced the NOx conversion efficiency for the urban phase by 7.5%, leading to a 22.6% reduction in tail-pipe NOx emissions. By employing both strategies, vehicles can comfortably meet the CN6b emission regulations by a substantial margin.

Development of AI-Augmented optimization technique for analysis & prediction of modal mix in road transportation.

Transport sector contribution to global emissions is a known fact, however, the mitigation path to achieve nationally determined goals for carbon reduction is often not specified, A simplified technique based on minimax optimization using Grey relational grade and Random forest narrows down on most contributing input variables from twelve road transport modes. This is a region-specific, scenario-based technique applied to north Punjab, Province of Pakistan that first categorizes modes based on their emission and then integrates with AI modeling using Deep Neural Network to develop sustainable trade-offs for carbon reduction. The output parameter translates the problem into a systematic iterative technique that predicts optimization options with different scenarios to bring out an environment-friendly transport mix. A 25% reduction applied to the five most emission-releasing modes like Diesel Light and Heavy Duty vehicles, Gas Light and heavy-duty vehicles, and Gas-Cars results in 16.54 MT of Carbon dioxide which is 54.35% reduced to the predicted 36.24 MT for the year 2044. Similarly in another scenario replacing 25% Gas and Diesel Light Duty vehicles respectively by adding 50% Petrol Light Duty vehicles leads to 18.94 MT of emissions which brings the emission value in 2044 at par with emission releases of the year 2014. The technique offers a forward path that allows environment-friendly modal mix combinations based on business-as-usual to offer transport mix solutions for carbon reduction. It is a generalized model that is based on a customized transport mix. Future studies can also be applied to intermodal tradeoffs like rail, air, waterways, etc.

Real-driving CO2, NOx and fuel consumption estimation using machine learning approaches

Real driving emissions (RDE) testing are gaining attention for monitoring and regulatory purposes because of providing more realistic emission and fuel consumption measurements compared to laboratory tests. This study aims to develop machine learning (ML) based emission and fuel consumption estimation models using real-driving measurement data. A light-duty diesel vehicle equipped with a portable emissions measurement system (PEMS) was driven in an urban test route by 30 participant drivers of disparate backgrounds to obtain a wide variety of data in terms of driving behaviour and traffic conditions. The Pearson correlation coefficient was used to select the input variables among 36 driving behaviours and 6 engine parameters. The CO2, NOx and fuel consumption prediction models were developed using linear regression (LR), support vector machine (SVM) and Gaussian process regression (GPR). The results showed that all three models could predict CO2 with an absolute relative error (ARE) of less than 9%. The GPR model showed the best performance in CO2 prediction with an R2 of 0.74 and ARE of 3.30%. LR model showed the best prediction accuracy for NOx with an R2 of 0.80 and ARE of 8.91%. All three models worked well for fuel consumption prediction, however, GPR showed the best accuracy with an R2 of 0.81 and ARE of 3.52%. This method lays a foundation for developing route/region specific emission and fuel consumption models that will help to monitor and reduce the environmental impact and the amount of burned fuel. Moreover, developing models from different driver classes will provide valuable insights into emission-optimal driving behaviour which could be used to train new drivers.

Emission Reduction from a Light-Duty Diesel Vehicle over Two Driving Cycles through Dynamic Correction Calibration.

The potential of a method of transient control of model-based engine charge control (MCCT) is investigated to minimize nitrogen oxide (NOx) emissions of a light-duty diesel vehicle over two driving cycles, the worldwide harmonized light-duty test cycle (WLTC) and real driving emission (RDE) cycle. The MCCT function was switched on by calibrating factor maps corrected for several parameters. In addition, the relationship between electronic control unit signals and nitrogen oxide (NOx) emissions was analyzed under the WLTC and RDE. The engine-out and tail-pipe NOx emissions in the WLTC and RDE could achieve varying degrees of reduction with MCCT.

Assessment of a NOx Measurement Procedure for Periodic Technical Inspection (PTI) of Light-Duty Diesel Vehicles

Assessment of a NOx Measurement Procedure for Periodic Technical Inspection (PTI) of Light-Duty Diesel Vehicles

Emission Factors of Carbonaceous Aerosol and Stable Carbon Isotope for In-use Vehicles

Vehicle exhaust is an important anthropogenic source of atmospheric carbonaceous aerosols; of which, the emission factors and stable carbon isotope composition are important basic data. In-use motor vehicles of different types were selected to conduct dynamometer tests using different test cycles and under cold/hot start conditions. The exhaust of each test stage was collected to analyze the carbonaceous components and stable carbon isotopes and to discuss the influencing factors. The total carbon emission factors follow the order:heavy-duty diesel vehicles>light-duty diesel vehicles>light-duty gasoline vehicles. Although the emission factors of light-duty natural gas vehicles were very low at the low- and medium-speed stages, they were similar to those of heavy-duty diesel vehicles at the high-speed stage. The emission factors of cold start were higher than those of hot start, and the emission factors of the NEDC test cycle were lower than those of WLTC (which should be related to the driving speed). The emission factors of organic carbon (OC) of gasoline and natural gas vehicles were much higher than those of elemental carbon (EC) in every test stage. The emission factors of OC and EC of diesel vehicles were similar. The OC/EC of all types of vehicles increased with the increase in driving speed. Stable carbon isotopes in EC were higher than those in OC. The stable carbon isotope in different vehicles follow the order:light-duty gasoline vehicles<light-duty natural gas vehicles<light-duty diesel vehicles<heavy-duty diesel vehicles. The results revealed that the source signatures of stable carbon isotope in vehicles used in current source apportionment could not well represent gasoline vehicles and natural gas vehicles. In future emission control and source apportionment, attention should be paid to the changes in emission factors and isotope signatures caused by the use of natural gas and the aging of motor vehicles.

Assessment of light-duty versus heavy-duty diesel on-road mobile source emissions using general additive models applied to traffic volume and air quality data and COVID-19 responses

ABSTRACT Following the outbreak of the COVID-19 pandemic, several papers have examined the effect of the pandemic response on urban air pollution worldwide. This study uses observed traffic volume and near-road air pollution data for black carbon (BC), oxides of nitrogen (NOx), and carbon monoxide (CO) to estimate the emissions contributions of light-duty and heavy-duty diesel vehicles in five cities in the continental United States. Analysis of mobile source impacts in the near-road environment has several health and environmental justice implications. Data from the initial COVID-19 response period, defined as March to May in 2020, were used with data from the same period over the previous two years to develop general additive models (GAMs) to quantify the emissions impact of each vehicle class. The model estimated that light-duty traffic contributes 4–69%, 14–65%, and 21–97% of BC, NOx, and CO near-road levels, respectively. Heavy-duty diesel traffic contributes an estimated 26–46%, 17–63%, and −7–18% of near-road levels of the three pollutants. The estimated mobile source impacts were used to calculate NOx to CO and BC to NOx emission ratios, which were between 0.21–0.32 μg m−3 NOx (μg m−3 CO)−1 and 0.013–0.018 μg m−3 BC (μg m−3 NOx)−1. These ratios can be used to assess existing emission inventories for use in determining air pollution standards. These results agree moderately well with recent National Emissions Inventory estimates and other empirically-derived estimates, showing similar trends among the pollutants. However, a limitation of this study was the recurring presence of an implausible air pollution impact estimate in 41% of the site-pollutant combinations, where a vehicle class was estimated to account for either a negative impact or an impact higher than the total estimated pollutant concentration. The variations seen in the GAM estimates are likely a result of location-specific factors, including fleet composition, external pollution sources, and traffic volumes. Implications: Drastic reductions in traffic and air pollution during the lockdowns of the COVID-19 pandemic present a unique opportunity to assess vehicle emissions. A General Additive Modeling approach is developed to relate traffic levels, observed air pollution, and meteorology to identify the amount vehicle types contribute to near-road levels of traffic-related air pollutants (TRAPs), which is important for future emission regulation and policy, given the significant health and environmental justice implications of vehicle-related pollution along major roadways. The model is used to evaluate emission inventories in the near-road environment, which can be used to refine existing estimates. By developing a locally data-driven method to readily characterize impacts and distinguish between heavy and light duty vehicle effects, local regulations can be used to target policies in major cities around the country, thus addressing local health disbenefits and disparities occurring as a result of exposure to near-road air pollution.

Emission Characteristics of Organic Carbon and Elemental Carbon in PM10 and PM2.5 from Vehicle Exhaust and Civil Combustion Fuels

To study the emission characteristics of carbonaceous aerosol in particulate matter emitted from vehicle exhaust and main civil combustion fuels, organic carbon (OC) and elemental carbon (EC) in PM10 and PM2.5 samples from vehicle sources (gasoline vehicles, light duty diesel vehicles, and heavy duty diesel vehicles), civil coal (chunk coal and briquette coal), and biomass fuels (wheat straw, wood plank, and grape branches) were collected and analyzed by using a multifunctional portable dilution channel sampler and the Model 5L-NDIR OC/EC analyzer. The results showed that there were significant differences in the proportion of carbonaceous aerosols in PM10 and PM2.5from different emission sources. The proportions of total carbon (TC) in PM10 and PM2.5 of different emission sources were 40.8%-68.5% and 30.5%-70.9%, respectively, and the OC/EC were 1.49-31.56 and 1.90-87.57, respectively. The carbon components produced by different emission sources were dominated by OC, and the OC/TC values in PM10 and PM2.5 were 56.3%-97.0% and 65.0%-98.7%, respectively. The proportions of OC in carbonaceous aerosols in PM10and PM2.5 were in the descending order of:briquette coal>chunk coal>gasoline vehicle>wood plank>wheat straw>light duty diesel vehicle>heavy duty diesel vehicle and briquette coal>gasoline car>grape branches>chunk coal>light duty diesel vehicle>heavy duty diesel vehicle, respectively. The main components of carbonaceous aerosols in PM10 and PM2.5 emitted from the various emission sources were different, and source apportionment of carbonaceous aerosols could be accurately distinguished by their ingredient composition profiles.

Simulation of CRDI Vehicle and Effect of Aftertreatment Devices

The project aims at simulation of diesel vehicle and the effect of after treatment devices on emissions of vehicle in mathematical environment. Environmental degradation due to pollution is increasing also emission norms of vehicles are becoming more and more stringent. Newer technologies are developing to attain the target of reduction in emissions. After treatment devices like diesel oxidation catalyst (DOC) is used to oxidize CO and HC, diesel particulate filter (DPF) is used to trap particulate matter and selective catalytic reduction (SCR) is used for reduction of NOx. In this project, simulation of light-duty diesel vehicle is performed and results are validated with actual data. Simulation of above devices provided reliable results as well as variation of different parameters within the components helped to improve the efficiency of system. Based on the reduction of emission, the conversion efficiency of after treatment system is calculated. Optimization of geometrical parameters of diesel oxidation catalyst and diesel particulate filter is done to further improve the performance of system.

Real-Time Measurement of NOx Emissions from Modern Diesel Vehicles Using On-Board Sensors

In this work, the performance of on-board vehicle exhaust emission sensors is investigated and compared to reference laboratory and on-road instrumentation for two modern diesel light-duty commercial vehicles, type-approved as Euro 6d-TEMP-EVAP-ISC and Euro 6d-ISC-FCM. The first step of the analysis was to perform emissions tests in the laboratory and compare the NOx concentrations registered by the vehicle sensors available at the engine-out and tailpipe positions with those recorded by reference laboratory instrumentation. In a second step, tests were also conducted on road, comparing the performance of on-board sensors with those of Portable Emission Measurement System (PEMS) analysers, which were taken as references. The uncertainty related to exhaust flow measurements was also addressed. In particular, emissions factors calculated using the flow rates measured either in the laboratory or on-road were compared to those obtained by computing exhaust flows with on-board recorded data available from the vehicle electronic control unit. Results showed maximum deviations on the order of 34% in laboratory tests and of 21% during on-road measurements. Finally, measurements were also carried out during a diesel particulate filter regeneration event, showing the good performance of the on-board sensors even when high NOx concentrations were present. These conditions can be similar to those experienced in the case of an after-treatment system malfunction or of a high-emitting event, and can thus be of interest for real-time malfunction identification and monitoring.

Advances and perspectives from a decade of collaborative efforts on zeolites for selective catalytic reduction of NOx

Nitrogen oxides (NOx) is a major air pollutant and its release is regulated by increasingly stringent legislation. Selective catalytic reduction using ammonia as a reductant (NH3-SCR) is the most widely applied method to reduce NOx from diesel vehicle exhaust. Significant technological achievements have been developed in the last 10–15 years to minimize NOx by NH3-SCR, particularly using Cu-containing small-pore zeolites as active and stable catalysts. In the present perspective, we highlight some of the most noteworthy advances achieved by industry and academia on the understanding of the unique reaction mechanism of NH3-SCR over Cu-zeolites. With the increased understanding, researchers have been able to rationalize the design and realization of new Cu-zeolite catalysts. Although light-duty diesel vehicles will be electrified in the near future, heavy-duty diesel vehicles will continue to play a large role in future powertrain solutions even beyond 2030. Hence, we highlight some of the challenges and perspectives moving forward.

Development of vehicle emission rates based on vehicle-specific power and velocity

The US Environmental Protection Agency developed the MOtor Vehicle Emission Simulator (MOVES) operating modes, which defines modal emission rates according to vehicle speed and vehicle-specific power using binning method. However, as MOVES was based on emissions data for vehicle fleets in the US, it is used primarily to estimate US emissions. To adopt this approach in other regions, here, we take into account regional conditions, such as vehicle fleet composition, emissions regulations, and driving environments. Real-world emissions test data for 17 light-duty gasoline and diesel vehicles mainly sold in Korea were used to develop CO2, NOx, and CO emission rates. Typically, the vehicle experiment and data acquisition are costly and time consuming, the amount of data needed to develop robust emission rates were considered. In addition, we studied how a re-binning of vehicle-specific power and velocity could lead to better emission rates estimates from on-road vehicles. To compare the estimates by different binning methods and real-world emissions, root mean square error (RMSE) and R-squared (R2) values were adopted. The comparison result shows that the re-binning method-based emission predictions were more accurate than MOVES prediction results under the real-world condition. The R2 of CO2 and NOx predictions were increased from 075 to 0.78 and from 0.17 to 0.2, respectively. The CO prediction accuracy was slightly increased. These findings provide the re-binning method is advantageous for developing modal-based emission rates using real-world emissions test data.

Real-Time Measurements of Formaldehyde Emissions from Modern Vehicles

Formaldehyde (HCHO), a carcinogenic carbonyl compound and precursor of tropospheric ozone, can be found in vehicle exhaust. Even though the continuous monitoring of HCHO has been recommended, the real-world emissions from the road transport sector are not commonly available. The main reason for this knowledge gap has been the difficulty to measure HCHO in real-time and during real-world testing. This, for instance, increases the uncertainty of the O3 simulated by air quality models. The present study investigates real-time HCHO measurements comparing three Fourier Transform InfraRed spectrometers (FTIRs) and one Quantum Cascade Laser InfraRed spectrometer (QCL-IR) directly sampling from the exhaust of one gasoline passenger car, one Diesel commercial vehicle and one Diesel heavy-duty vehicle, all meeting recent European emission standards (Euro 6/VI). Non-negligible emissions of HCHO were measured from the Diesel light-duty vehicle, with emissions increasing as temperature decreased. Relatively low emissions were measured for the gasoline car and the Diesel heavy-duty vehicle. The results showed a good correlation between the different instruments under all the conditions tested (in most cases R2 &gt; 0.9). Moreover, it was shown that HCHO can be accurately measured during on-road and real-world-like tests using instruments based on FTIR and QCL-IR technologies.

Research on Analysis Method of Remote Sensing Results of NO Emission from Diesel Vehicles

Remote sensing technology has been used for gasoline vehicle gaseous emissions monitoring for nearly 30 years. However, the application effect of the remote sensing detection of diesel vehicle tailpipe emission concentrations is unsatisfactory. Therefore, several approaches were proposed to analyze the remote sensing results for gaseous exhaust emissions from diesel vehicles, including the concentration ratios of gaseous emission components to carbon dioxide (CO2) and fuel-based emission factors. Based on our experimental results, these two metrics have some high values in low-speed or low-load conditions of vehicles, which introduces uncertainty when evaluating vehicle emission levels. Therefore, an inversion calculation method originally developed for remote sensing light duty diesel vehicle gaseous emissions was used for the remote sensing of nitrogen monoxide (NO) tailpipe concentrations in heavy duty diesel vehicles, and validated by PEMS tested emission results. For the first time, the above three options for evaluating the NOx emission level of diesel vehicles, including the concentration ratio of NO to CO2, the fuel-based NO emission factor and the estimated tailpipe NO emission concentration were investigated, and some influencing factors were also discussed. The remote sensing tailpipe NO emission concentration can be directly used to evaluate diesel vehicle NO emission levels compared with the two other metrics.