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On-road driving tests are performed to determine the emission of harmful exhaust compounds from vehicles. These primarily include carbon dioxide, nitrogen oxides, and particle number. However, there is a lack of indicators that combine the first three substances that are the most important in assessing the environmental aspects of vehicles. The purpose of this article is to indicate the possibility of assessing emissions in real driving conditions from light-duty and heavy-duty vehicles of different categories. In order to do so, a portable emissions measurement system (PEMS) and an instrument for measuring the particle number were used. The tests were carried out on routes designed to comply with the requirements and regulations laid down in the European Union legislation. On-road emissions of carbon dioxide, nitrogen oxides and particle number have been determined. Factors have been determined as the multiplication of these compounds for each vehicle category in three phases of the test: urban, rural, and motorway. A new way of assessing emissions from vehicles using new factors has been proposed.

The objective in present study is to develop a regression analysis model to estimate real-world CO2 emissions of light-duty diesel vehicles considering domestic road conditions. For regression analysis variables, OBD data such as vehicle speed, acceleration, engine speed (rpm), and engine power were used. Regression analysis results were compared with CO2 emissions measured using PEMS on the test routes of the real driving emissions-light duty vehicles (RDE-LDV). In results, the vehicle speed and air/fuel data from the OBD signals maintained a linear relationship with the GPS and exhaust gas flowmeter-based vehicle speed and exhaust flow data. All determination coefficients were ≥0.99, indicating that the OBD data provided by the test vehicle in this study exhibited strong reliability. To investigate the accuracy of the regression equation estimated using the trip variables of the OBD data, the driving variables were substituted into the equation to obtain CO2 estimations and the real CO2 emissions measured using PEMS were compared. A strong linear relationship was observed between the regression equation-based CO2 estimations and real CO2 measurements. The determination coefficient was approximately 0.93, supporting the reliability of the estimation results.

A surge in the size of the automobile population has caused vehicular emissions to become a major source of urban atmospheric pollution. Elevating standards is an effective method of controlling vehicular emissions and improving air quality. Light-duty vehicles are the major contributors to HC and CO emissions as they constitute a large proportion of all vehicles. Consequently, controlling light-duty vehicular emissions has been the primary means of air pollution prevention in China. This paper first reviews the progress of emission control standards in mainland China. Second, it analyzes features of the China 6 emissions standards, namely the continuation of European standards, the harmony of global technology regulations, and fusion with the standards of the USA. This is followed by a description and discussion of the status of research on mainstream after-treatment technologies such as the gasoline particulate filter, lean-NOx trap, and selective catalytic reduction. Finally, this study argues that the technical routes for implementing three-way catalysts, gasoline particulate filters, and onboard refueling vapor recovery in gasoline vehicles and diesel oxidation catalysts, diesel particulate filters, and selective catalyst reduction in diesel vehicles meet China 6 standards. Moreover, onboard diagnostics-based control of light vehicle emissions is introduced, and the development directions of vehicle gasoline (the reduction in sulfur, olefin, and aromatic content and vapor pressure control in summer) and vehicle diesel (an increase in the Cetane number and reduction in the forecasted polycyclic aromatic content) are discussed.Graphic abstractState-of-the-art outlook for light-duty vehicle emission control standards in China

In the China VI regulations for light-duty vehicles, the (RDE) test is introduced as a supplementary test procedure. In the actual test process, the RDE results are more significantly influenced by driving behavior and vehicle type. To reduce the test cost, the NOx and PN prediction models are established based on the GA-BP method. The results showed that the coefficients of determination of the GA-BP model for NOx and PN predictions are all greater than 0.9 and are linearly highly correlated at the instantaneous emission level. At the overall emission level, the overall error of the GA-BP model is less than 7% for NOx prediction and less than 6% for PN prediction. The model has high accuracy for both instantaneous and overall emissions of light-duty vehicles. This provides practical engineering value for guiding the RDE test.

A compact sedan vehicle powered by a 1.4 dm 3 spark ignition engine fueled with compressed natural gas (CNG), Brazilian gasoline, hydrous ethanol 95% v/v and wet ethanol 88% v/v was evaluated throughout the Worldwide harmonized Light vehicles Test Cycle (WLTC) key points. The vehicle operating points with longest residence time on the WLTC were selected to fuel consumption and emissions evaluation at steady state conditions. The top five key operating points reported in this work accounted for 22% of the total time spent in the entire cycle. The results indicated a significant reduction on greenhouse gases (GHG) emissions and energy demand for operation with CNG. The ethanol–water blends provided reduced emissions of nitrogen oxides (NO x ), but increased specific fuel consumption, carbon monoxide (CO) and GHG emissions in comparison to CNG and gasoline. The operation with gasoline resulted in the minimum CO emissions for all fuels tested, as well as the best fuel consumption between liquid fuels, despite the highest values of carbon dioxide (CO 2 ), and increased NO x . Even though ethanol produced little total unburned hydrocarbons (THC), the emissions of alcohols and aldehydes raised an alert for this renewable fuel, whereas CNG emitted the least amount of such pollutants.

The CO 2 moving average window(MAW) method is used to process RDE (real drive emissions) emissions data in China 6 light duty vehicle emissions regulations, while the Euro 6 light duty vehicle emission regulations allow to use both of MAW and power binning(PB) method to deal with RDE emission data. In order to study the difference between the two data processing methods and analyze the differences in the emission results, 10 different types of light duty vehicles are conducted RDE test with PEMS (portable emissions measurement system), and the test data are processed by the two methods separately. The results show that there is a little difference between MAW and PB, while both of them can satisfy the vehicle emission assessment. The PB method calculates the emission factors higher than the MAW method. After removing the cold start and idle condition data, the results of PB is similar to MAW. Besides, reducing the average speed limit of urban working conditions in PB has a greater impact on the urban driving condition emission factor, but less on the whole cycle emission factor.

The emission characteristics under worldwide harmonized light vehicles test cycle (WLTC) was investigated for a 48V hybrid light-duty vehicle which carried a 2.0 L naturally aspirated engine on engine test bed after the WLTC cycle was converted to the corresponding engine transient cycle. The influence of electric heating catalyst on exhaust emission was analyzed. The results show that electric heating catalyst can effecively speed up the temperature rise rate then significantly decreases the exhaust emission. Electric heating has a more pronounced effect for ceramic carrier catalyst.

Hydrogen fuel cell vehicles can complement other electric vehicle technologies as a zero-emission technology and contribute to global efforts to achieve the emission reduction targets. This article spotlights the current deployment status of fuel cells in road transport. For this purpose, data collection was performed by the Advanced Fuel Cells Technology Collaboration Programme. Moreover, the available incentives for purchasing a fuel cell vehicle in different countries were reviewed and future perspectives summarized. Based on the collected information, the development trends in the last five years were analyzed and possible further trends that could see the realization of the defined goals derived. The number of registered vehicles was estimated to be 51,437 units, with South Korea leading the market, with 90% of the vehicles being concentrated in four countries. A total of 729 hydrogen refueling stations were in operation, with Japan having the highest number of these. The analysis results clearly indicate a very positive development trend for fuel cell vehicles and hydrogen refueling stations in 2021, with the highest number of new vehicles and stations in a single year, paralleling the year’s overall economic recovery. Yet, a more ambitious ramp-up in the coming years is required to achieve the set targets.

The U.S. federal government has established goals of electrifying 50% of new light-duty vehicle sales by 2030 and reducing economy-wide greenhouse gas emissions 50-52% by 2030, from 2005 levels. Here we evaluate the vehicle electrification goal in the context of the economy-wide emissions goal. We use a vehicle fleet model and a life cycle emissions model to project vehicle sales, stock, and emissions. To account for state-level variability in electric vehicle adoption and electric grid emissions factors, we apply the models to each state. By 2030, greenhouse gas emissions are reduced by approximately 25% (from 2005) for the light-duty vehicle fleet, primarily due to fleet turnover of conventional vehicles. By 2035, emissions reductions approach 45% if both vehicle electrification and grid decarbonization goals (100% by 2035) are met. To meet climate goals, the transition to electric vehicles must be accompanied by an accelerated decarbonization of the electric grid and other actions. Electric vehicle sales goals alone will not achieve light duty vehicle emissions targets. Other actions including decarbonizing the electric grid, mode shifting, vehicle downsizing, reducing travel demand, and accelerating fleet turnover, are needed.

PurposeThe rapid growth of vehicle sales and usage has highlighted the need for greenhouse gas (GHG) emission reduction in Macau, a special administrative region (SAR) of China. As the most primary vehicle type, light-duty vehicles (LDV, including light-duty gasoline vehicles (LDGVs) and light-duty diesel vehicles (LDDVs)) play a key role in promoting the GHG reduction and development of green transportation system in Macau.MethodsThis study, on the basis of real-world tested and statistical data, firstly performed a streamlined life-cycle assessment (SLCA) on LDVs, to evaluate the potential GHG emissions and reduction through shifting to hybrid electric vehicles (HEVs) and electric vehicles (EVs).Results and discussionThe results show that the mean GHG emissions from the LDGVs, LDDVs, and HEVs per 100 km were 25.16, 20.30, and 15.00 kg CO2 eq, respectively. Under the current electricity mix in Macau, EVs with the emissions of 12.39 kg CO2 eq/100 km can achieve a significant GHG emission reduction of LDVs in Macau. The total GHG emissions from LDVs increased from 124.99 to 247.82 thousand metric tons over the periods 2001–2014, with a 5.42% annual growth rate. A scenario analysis indicated that the development of HEVs and EVs—especially EVs—has the potential to control the GHG emissions from LDVs. Under the electricity mix of natural gas (NG) and solar energy (SE), the GHG emissions from EVs would drop by about 22 and 28%, respectively, by 2030.ConclusionsThis study develops a useful approach to evaluate the potential GHG emissions and its reduction strategies in Macau. All the obtained results could be useful for decision makers, providing robust support for drawing up an appropriate plan for improving green transportation systems in Macau.