Vehicle restrictions and CO2 emissions in Beijing – A simple projection using available data

The Beijing Government launched a new policy on restricting vehicle ownership in late 2010 to regulate the faster motorization and the excessive vehicular carbon dioxide (CO₂) emissions. In this paper, we first analyzed this policy and its effect on private passenger vehicle population. The private passenger vehicle population in Beijing from 2011 to 2020 was predicted under three different scenarios: no constraint (NC), current constraint (CC) and tighter constraint (TC). Then the assessment of vehicular emissions reduction benefits was made on the basis of private passenger vehicle population, vehicle kilometers traveled and CO₂ emission factors. It was projected that the CO₂ emissions in 2020 will reach 23.90, 15.55 and 13.23 million tons under NC, CC and TC respectively. The policy is very effective in controlling the faster motorization and reducing CO₂ emissions.     

Effects of battery chemistry and performance on the life cycle greenhouse gas intensity of electric mobility

Lithium traction batteries are a key enabling technology for plug-in electric vehicles (PEVs). Traction battery manufacture contributes to vehicle production emissions, and battery performance can have significant effects on life cycle greenhouse gas (GHG) emissions for PEVs. To assess emissions from PEVs, a life cycle perspective that accounts for vehicle production and operation is needed. However, the contribution of batteries to life cycle emissions hinge on a number of factors that are largely absent from previous analyses, notably the interaction of battery chemistry alternatives and the number of electric vehicle kilometers of travel (e-VKT) delivered by a battery. We compare life cycle GHG emissions from lithium-based traction batteries for vehicles using a probabilistic approach based on 24 hypothetical vehicles modeled on the current US market. We simulate life-cycle emissions for five commercial lithium chemistries. Examining these chemistries leads to estimates of emissions from battery production of 194–494 kg CO₂ equivalent (CO₂e) per kWh of battery capacity. Combined battery production and fuel cycle emissions intensity for plug-in hybrid electric vehicles is 226–386 g CO₂e/e-VKT, and for all-electric vehicles 148–254 g CO₂e/e-VKT. This compares to emissions for vehicle operation alone of 140–244 g CO₂e/e-VKT for grid-charged electric vehicles. Emissions estimates are highly dependent on the emissions intensity of the operating grid, but other upstream factors including material production emissions, and operating conditions including battery cycle life and climate, also affect life cycle GHG performance. Overall, we find battery production is 5–15% of vehicle operation GHG emissions on an e-VKT basis.     

The impact of road grade on carbon dioxide (CO2) emission of a passenger vehicle in real-world driving

To accurately estimate real-world vehicle emission at 1 Hz the road grade for each second of data must be quantified. Failure to incorporate road grade can result in over or underestimation of a vehicle’s power output and hence cause inaccuracy in the instantaneous emission estimate. This study proposes a simple LiDAR (Light Detection And Ranging) – GIS (Geographic Information System) road grade estimation methodology, using GIS software to interpolate the elevation for each second of data from a Digital Terrain Map (DTM). On-road carbon dioxide (CO₂) emissions from a passenger car were recorded by Portable Emission Measurement System (PEMS) over 48 test laps through an urban-traffic network. The test lap was divided into 8 sections for micro-scale analysis. The PHEM instantaneous emission model (Hausberger, 2003) was employed to estimate the total CO₂ emission through each lap and section. The addition of the LiDAR-GIS road grade to the PHEM modelling improved the accuracy of the CO₂ emission predictions. The average PHEM estimate (with road grade) of the PEMS measured section total CO₂ emission (n = 288) was 93%, with 90% of the PHEM estimates between 80% and 110% of the PEMS recorded value. The research suggests that instantaneous emission modelling with LiDAR-GIS calculated road grade is a viable method for generating accurate real-world micro-scale CO₂ emission estimates. The sensitivity of the CO₂ emission predictions to road grade was also tested by lessening and exaggerating the gradient profiles, and demonstrates that assuming a flat profile could cause considerable error in real-world CO₂ emission estimation.     

Carbon emission from urban passenger transportation in Beijing

Urban passenger transport significantly contributes to global greenhouse gas emissions, especially in developing countries owing to the rapid motorization, thus making it an important target for carbon reduction. This article established a method to estimate and analyze carbon emission from urban passenger transport including cars, rail transit, taxis and buses. The scope of research was defined based on car registration area, transport types and modes, the stages of rail transit energy consumption. The data availability and gathering were fully illustrated. A city level emission model for the aforementioned four modes of passenger transport was formulated, and parameters including emission factor of electricity and fuel efficiency were tailored according to local situations such as energy structure and field survey. The results reveal that the emission from Beijing’s urban passenger transport in 2012 stood at 15 million tonnes of CO₂, of which 75.5% was from cars, whereas car trip sharing constitutes only 42.5% of the total residential trips. Bus travel, yielding 28.6 g CO₂, is the most efficient mode of transport under the current situations in terms of per passenger kilometer (PKM) emission, whereas car or taxi trips emit more than 5 times that of bus trips. Although a decrease trend appears, Beijing still has potential for further carbon reduction in passenger transport field in contrast to other cities in developed countries. Development of rail transit and further limitation on cars could assist in reducing 4.39 million tonnes CO₂ emission.     

Development of a corrected average speed model for calculating carbon dioxide emissions per link unit on urban roads

The purpose of our study is to develop a “corrected average emission model,” i.e., an improved average speed model that accurately calculates CO₂ emissions on the road. When emissions from the central roads of a city are calculated, the existing average speed model only reflects the driving behavior of a vehicle that accelerates and decelerates due to signals and traffic. Therefore, we verified the accuracy of the average speed model, analyzed the causes of errors based on the instantaneous model utilizing second-by-second data from driving in a city center, and then developed a corrected model that can improve the accuracy. We collected GPS data from probe vehicles, and calculated and analyzed the average emissions and instantaneous emissions per link unit. Our results showed that the average speed model underestimated CO₂ emissions with an increase in acceleration and idle time for a speed range of 20 km/h and below, which is the speed range for traffic congestion. Based on these results, we analyzed the relationship between average emissions and instantaneous emissions according to the average speed per link unit, and we developed a model that performed better with an improved accuracy of calculated CO₂ emissions for 20 km/h and below.     

Influence of driving patterns on vehicle emissions: A case study for Latin American cities

On-board real-time emission experiments were conducted on 78 light-duty vehicles in Bogota. Direct emissions of carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_x) and hydrocarbons (HC) were measured. The relationship between such emissions and vehicle specific power (VSP) was established. The experimental matrix included both gasoline-powered and retrofit dual fuel (gasoline–natural gas) vehicles. The results confirm that VSP is an appropriate metric to obtain correlations between driving patterns and air pollutant emissions. Ninety-five percent of the time vehicles in Bogota operate in a VSP between −15.2 and 17.7 kW ton⁻¹, and 50% of the time they operate between −2.9 and 1.2 kW ton⁻¹, representing low engine-load and near-idling conditions, respectively. When engines are subjected to higher loads, pollutant emissions increase significantly. This demonstrates the relevance of reviewing smog check programs and command-and-control measures in Latin America, which are widely based on static (i.e., idling) emissions testing. The effect of different driving patterns on the city’s emissions inventory was determined using VSP and numerical simulations. For example, improving vehicle flow and reducing sudden and frequent accelerations could curb annual emissions in Bogota by up to 12% for CO₂, 13% for CO and HC, and 24% for NO_x. This also represents possible fuel consumption savings of between 35 and 85 million gallons per year and total potential economic benefits of up to 1400 million dollars per year.     

Will technological progress be sufficient to stabilize CO2 emissions from air transport in the mid-term?

This article investigates whether anticipated technological progress can be expected to offset the CO₂ emissions resulting from rapid air traffic growth. Global aviation CO₂ emissions projections are examined for eight geographical zones until 2025. Air traffic flows are forecast using a dynamic panel-data econometric model, and then converted into corresponding quantities of air traffic CO₂ emissions using specific hypotheses and energy factors. None of our nine scenarios appears compatible with the objective of 450 ppm CO₂-eq. recommended by the Intergovernmental Panel on Climate Change. Nor is any compatible with the Panel’s aim of limiting global warming to 3.2 °C.     

Are HOV/eco-lanes a sustainable option to reducing emissions in a medium-sized European city?

Innovative traffic management measures are needed to reduce transportation-related emissions. While in Europe, road lane management has focused mainly on introduction of bus lanes, the conversion to High Occupancy Vehicles (HOV) and eco-lanes (lanes dedicated to vehicles running on alternative fuels) has not been studied comprehensively. The objectives of this research are to: (1) Develop an integrated microscopic modeling platform calibrated with real world data to assess both traffic and emissions impacts of future Traffic Management Strategies (TMS) in an urban area; (2) Evaluate the introduction of HOV/eco-lanes in three different types of roads, freeway, arterial and urban routes, in an European medium-sized city and its effects in terms of emissions and traffic performance. The methodology consists of three distinct phases: (a) Traffic and road inventory data collection; (b) Traffic and emissions simulation using an integrated platform of microscopic simulation; and (c) Evaluation of scenarios. For the baseline scenario, the statistical analysis shows valid results. The results show that HOV and eco-lanes in a medium European city are feasible, and when the Average Occupancy of Vehicles (AOV) increases, on freeways, the majority of vehicles can reduce their travel time (2%) with a positive impact in terms of total emissions (−38% NO_x, −39% HC, −43% CO and −37% CO₂). On urban and arterial corridors, the reduction in emissions could be achieved only if the AOV increases from 1.50 to 1.70 passengers/vehicle. Total emissions of the corridor with an AOV of 1.70 passengers/vehicle can be reduced up to 35–36% for the urban route while the values can be reduced by 36–39% for the arterial road. With the introduction of Hybrid Electric Vehicles (HEV) and Electric Vehicles (EV) it is possible to reduce emissions, although the introduction of eco-lanes did not show significant reductions in emissions. When both policies are simulated together, an emissions improvement is observed for the arterial route and for two of the scenarios.     

An optimization model of energy and transportation systems: Assessing the high-speed rail impacts in the United States

This paper presents a long-term investment planning model that co-optimizes infrastructure investments and operations across transportation and electric infrastructure systems for meeting the energy and transportation needs in the United States. The developed passenger transportation model is integrated within the modeling framework of a National Long-term Energy and Transportation Planning (NETPLAN) software, and the model is applied to investigate the impact of high-speed rail (HSR) investments on interstate passenger transportation portfolio, fuel and electricity consumption, and 40-year cost and carbon dioxide (CO₂) emissions. The results show that there are feasible scenarios under which significant HSR penetration can be achieved, leading to reasonable decrease in national long-term CO₂ emissions and costs. At higher HSR penetration of approximately 30% relative to no HSR in the portfolio promises a 40-year cost savings of up to $0.63 T, gasoline and jet fuel consumption reduction of up to 34% for interstate passenger trips, CO₂ emissions reduction by about 0.8 billion short tons, and increased resilience against petroleum price shocks. Additionally, sensitivity studies with respect to light-duty vehicle mode share reveal that in order to realize such long-term cost and emission benefits, a change in the passenger mode choice is essential to ensure higher ridership for HSR.     

Six years of CO2-based tax incentives for new passenger cars in The Netherlands: Impacts on purchasing behavior trends and CO2 effectiveness

There is growing evidence that consumers respond more effectively to upfront price signals, such as vehicle purchase taxes and feebate policies, and to tax incentives that are more salient than others, such as company car taxes graded by CO₂ emissions. This paper examines tax changes in The Netherlands, which are among the most stringent and most salient in Europe, and assesses the ex-post purchasing impacts and CO₂ effectiveness of six years of CO₂-based tax incentives for low-carbon cars in The Netherlands. Dutch tax incentives resulted in 13 g/km, or 11% lower average CO₂ emissions in 2013. The Netherlands has moved from the 12th position before the tax changes in 2007 to become Europe’s number one in terms of the lowest average new car CO₂ emissions and highest share of electric vehicles in 2013. Tax incentives for new cars sold between 2008 and 2013 have resulted in 4.6 million tons of potential lifetime CO₂ abatement at the cost of a drop in tax revenues of 30–50%. However, when corrected for the Dutch policy-induced increasing real-world fuel-economy shortfall and leakage of carbon reduction potential through vehicle export of low-carbon cars, only 3.5 million tons or 75% of the CO₂ reduction remains. CO₂-based tax incentives for company cars seem to have contributed the most to the observed turnaround in purchasing behavior towards lower CO₂-emitting passenger cars.     

Prospects for plug-in hybrid electric vehicles in the United States and Japan: A general equilibrium analysis

The plug-in hybrid electric vehicle (PHEV) may offer a potential near term, low-carbon alternative to today’s gasoline- and diesel-powered vehicles. A representative vehicle technology that runs on electricity in addition to conventional fuels was introduced into the MIT Emissions Prediction and Policy Analysis (EPPA) model as a perfect substitute for internal combustion engine (ICE-only) vehicles in two likely early-adopting markets, the United States and Japan. We investigate the effect of relative vehicle cost and all-electric range on the timing of PHEV market entry in the presence and absence of an advanced cellulosic biofuels technology and a strong (450 ppm) economy-wide carbon constraint. Vehicle cost could be a significant barrier to PHEV entry unless fairly aggressive goals for reducing battery costs are met. If a low-cost PHEV is available we find that its adoption has the potential to reduce CO₂ emissions, refined oil demand, and under a carbon policy the required CO₂ price in both the United States and Japan. The emissions reduction potential of PHEV adoption depends on the carbon intensity of electric power generation. Thus, the technology is much more effective in reducing CO₂ emissions if adoption occurs under an economy-wide cap and trade system that also encourages low-carbon electricity generation.     

Assessing CO2 emissions of electric vehicles in Germany in 2030

Electric vehicles are often said to reduce carbon dioxide (CO₂) emissions. However, the results of current comparisons with conventional vehicles are not always in favor of electric vehicles. We outline that this is not only due to the different assumptions in the time of charging and the country-specific electricity generation mix, but also due to the applied assessment method. We, therefore, discuss four assessment methods (average annual electricity mix, average time-dependent electricity mix, marginal electricity mix, and balancing zero emissions) and analyze the corresponding CO₂ emissions for Germany in 2030 using an optimizing energy system model (PERSEUS-NET-TS). Furthermore, we distinguish between an uncontrolled (i.e. direct) charging and an optimized controlled charging strategy. For Germany, the different assessment methods lead to substantial discrepancies in CO₂ emissions for 2030 ranging from no emissions to about 0.55 kg/kWh_el (110 g/km). These emissions partly exceed the emissions from internal combustion engine vehicles. Furthermore, depending on the underlying power plant portfolio and the controlling objective, controlled charging might help to reduce CO₂ emissions and relieve the electricity grid. We therefore recommend to support controlled charging, to develop consistent methodologies to address key factors affecting CO₂ emissions by electric vehicles, and to implement efficient policy instruments which guarantee emission free mobility with electric vehicles agreed upon by researchers and policy makers.     

Prediction of vehicle CO2 emission and its application to eco-routing navigation

Transportation sector accounts for a large proportion of global greenhouse gas and toxic pollutant emissions. Even though alternative fuel vehicles such as all-electric vehicles will be the best solution in the future, mitigating emissions by existing gasoline vehicles is an alternative countermeasure in the near term. The aim of this study is to predict the vehicle CO₂ emission per kilometer and determine an eco-friendly path that results in minimum CO₂ emissions while satisfying travel time budget. The vehicle CO₂ emission model is derived based on the theory of vehicle dynamics. Particularly, the difficult-to-measure variables are substituted by parameters to be estimated. The model parameters can be estimated by using the current probe vehicle systems. An eco-routing approach combining the weighting method and k-shortest path algorithm is developed to find the optimal path along the Pareto frontier. The vehicle CO₂ emission model and eco-routing approach are validated in a large-scale transportation network in Toyota city, Japan. The relative importance analysis indicates that the average speed has the largest impact on vehicle CO₂ emission. Specifically, the benefit trade-off between CO₂ emission reduction and the travel time buffer is discussed by carrying out sensitivity analysis in a network-wide scale. It is found that the average reduction in CO₂ emissions achieved by the eco-friendly path reaches a maximum of around 11% when the travel time buffer is set to around 10%.     

The potential mitigation of CO2 emissions via modal substitution of high-speed rail for short-haul air travel from a life cycle perspective – An Australian case study

The objective of this study is to provide a strategic evaluation of the mitigation of CO₂ emissions via modal substitution of high-speed rail for short-haul air travel on the Sydney–Melbourne, Australia city-pair from a life cycle perspective. It has been demonstrated that when considering CO₂ emissions from vehicle operations, the modal shift from air to high-speed rail on this city-pair has the potential to provide a means of CO₂ mitigation. However, uncertainty exists with regard to the level of mitigation potential when considering the whole-of-life performance of the systems. Given the significant difference in the infrastructure requirements between the air mode and the high-speed rail mode, this study quantifies the life cycle CO₂ load attributable to each system and examines the effect on CO₂ mitigation potential. The study concluded that while the inclusion of the linehaul infrastructure did increase the CO₂ load associated with high-speed rail mode, it did not equate to or exceed the CO₂ load per trip as experienced by the air mode. The avoided annual life cycle CO₂ emission in the target year 2056 was 0.37 Mt representing an 18% reduction when compared to the air mode only on the city pair. In fact, the scenario comparison indicated that the substitution of high-speed rail for short-haul air travel on the city pair resulted in CO₂ emissions avoidance throughout the longitudinal period.     

Measuring foregone output under industry emission reduction target in the transportation sector

Numerous countries have implemented or are considering a range of policies to lower emissions from transportation. An analysis of the impacts of environmental regulation is a crucial issue, which has not been properly highlighted in the transportation literature, particularly in terms of the foregone output by such regulation. This study develops a novel DEA model that measures the foregone output when the industry emissions target is imposed. This model reflects the real regulatory process more appropriately than other models in that the authority in charge sets the emission reduction target first, and the transport operators respond to it. In addition, the model can test the industrywide impacts over a wide range of emission target values, which can help policy makers determine the optimal emission target. Finally, the proposed model was applied to the port industry in Korea. The results suggest that Korean ports can reduce their emissions by a maximum of 239,850 tons of CO₂, which accounts for 13% of the total emissions in 2010. The 13% reduction in emission, however, would result in $ 91,109,000 of foregone cargo traffic to the Korean economy. In addition, the foregone cargo traffic increases at much faster rate than the emission reduction rate. For example, the shadow price of emission differs by 2.25 times between the most moderate and strictest emission targets. This suggests that the government needs to impose moderate emission targets at the initial stages if it decides to minimize the regulatory impacts on the industry.     

Energy use and emissions of two stroke-powered tricycles in Metro Manila

CO, CO₂, NO_x and HC emissions of two stroke-powered tricycles in Metro Manila are examined using an instantaneous emissions model. Results show that fuel consumption and HC emissions in middle class residential areas and main roads are similar but lower than levels in low income residential areas. On the average, tricycles in Metro Manila consume 24.41 km/l of fuel and produces 9.5, 9.7, 40.5 and 0.07 g/km of HC, CO, CO₂ and NO_x, respectively. They fail to satisfy HC, CO and NO_x emission limits set by reference standards in the Philippines and other Asian countries. They produce greater HC and CO emissions than gasoline fueled private cars and diesel powered public jeepneys, taxis and buses on a per passenger-km basis but significantly lower NO_x emissions. Tricycles account for 15.4% of the total HC emissions from mobile sources in the metropolis while their contributions to CO, CO₂ and NO_x are minimal.     

Biofuels in aviation: Fuel demand and CO2 emissions evolution in Europe toward 2030

This article presents the results of a scenario-based study carried out at the European Commission’s Joint Research Centre aimed at analyzing the future growth of aviation, the resulting fuel demand and the deployment of biofuels in the aviation sector in Europe. Three scenarios have been produced based on different input assumptions and leading to different underlying patterns of growth and resulting volumes of traffic. Data for aviation growth and hence fuel demand have been projected on a year by year basis up to 2030, using 2010 as the baseline. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, the type of aircrafts, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The target of the European Advanced Biofuels Flightpath to ensure the commercialization and consumption of 2 million tons of sustainably produced paraffinic biofuels in the aviation sector by 2020, has also been taken into account. Results regarding CO₂ emission projections to 2030, reveal a steady annual increase in the order of 3%, 1% and 4% on average, for the three different scenarios, providing also a good correlation compared to the annual traffic growth rates that are indicated in the three corresponding scenarios. In absolute values, these ratios correspond to the central, the pessimistic and the optimistic scenarios respectively, corresponding to 360 million tonnes CO₂ emissions in 2030, ranging from 271 to 401 million tonnes for the pessimistic and optimistic scenarios, respectively. This article also reports on the supply potential of aviation biofuels (clustered in HEFA/HVOs and biojet) based on the production capacity of facilities around the world and provides an insight on the current and future trends in aviation based on the European and national policies, innovations and state-of-the art technologies that will influence the future of sustainable fuels in aviation.     

CO2 emissions and expansion of railway,road, airline and in-land waterway networks over the 1985–2013 period in China: A time series analysis

China, the world’s largest CO₂ emitter, is continuing its long-term strategy to use transportation investments as a tool for development. With the expectation that transportation will contribute 30–40% of the total CO₂ emissions in China in the near future, there is an imminent need to identify how the development of different transportation modes may have different long-term effects on CO₂ emissions. Using time series data over the period of 1985–2013, this paper applies the combined autoregressive distributed lag (ARDL) and vector error correction model (VECM) approach to identify short- and long-run causal relationships between CO₂ emissions and mode-specific transportation development, including railway, road, airline, and inland waterway. We find that China’s domestic expansions of road, airline, and waterway infrastructure lead to long-run increases in CO₂ emissions. Among them, waterway has the strongest positive impact on CO₂ emissions, followed by road. Despite a short-run, positive impact on CO₂ emissions, railway expansion leads to long-run decreases in CO₂ emissions. The results are especially encouraging for the central government of China given its long-standing and on-going efforts to expand railway infrastructure at the national level. Looking forward, it is recommended that China continues its national investments in railway infrastructure to achieve both environment and economy goals.     

CO2 emissions efficiency and marginal abatement costs of the regional transportation sectors in China

Nowadays, evaluating CO₂ emissions efficiency and its marginal abatement cost in transportation sectors has been a hot topic. However, while evaluating the CO₂ marginal abatement cost using data envelopment analysis approach, the weak disposability of CO₂ may imply positive abatement cost, which undoubtedly violates our common sense. To obtain non-positive marginal abatement cost, CO₂ emissions should be treated as an input. To reconcile this contradiction, this paper intends to propose a global, directional distance function model based on previous study to investigate the productivity, economic efficiency, CO₂ emissions efficiency, and marginal abatement cost of the China’s regional transportation sectors during 2007–2012. The results show that: (1) the productivity, economic efficiency and CO₂ emissions efficiency of different regions differ widely. More specifically, the coastal areas of south China perform better than the other areas in terms of productivity, economic efficiency, and CO₂ emissions efficiency. (2) Generally, the economic efficiency is greater than CO₂ emissions efficiency, which is relatively low in most areas. (3) A negative correlation is found between CO₂ emissions efficiency and its marginal abatement cost. For a 1% increase in CO₂ emissions efficiency, the CO₂ marginal abatement cost declines by 102 Yuan (in 2004 constant price). The results imply that improving CO₂ emissions efficiency plays an important role in marginal abatement cost reduction, and it also provides us a new approach to reduce abatement cost besides the technical progress.     

Analysis of fuel consumption and pollutant emissions of regulated and alternative driving cycles based on real-world measurements

Discrepancies between real-world use of vehicles and certification cycles are a known issue. This paper presents an analysis of vehicle fuel consumption and pollutant emissions of the European certification cycle (NEDC) and the proposed worldwide harmonized light vehicles test procedure (WLTP) Class 3 cycle using data collected on-road. Sixteen light duty vehicles equipped with different propulsion technologies (spark-ignition engine, compression-ignition engine, parallel hybrid and full hybrid) were monitored using a portable emission measurement system under real-world driving conditions. The on-road data obtained, combined with the Vehicle Specific Power (VSP) methodology, was used to recreate the dynamic conditions of the NEDC and WLTP Class 3 cycle. Individual vehicle certification values of fuel consumption, CO₂, HC and NO_x emissions were compared with test cycle estimates based on road measurements. The fuel consumption calculated from on-road data is, on average, 23.9% and 16.3% higher than certification values for the recreated NEDC and WLTP Class 3 cycle, respectively. Estimated HC emissions are lower in gasoline and hybrid vehicles than certification values. Diesel vehicles present higher estimated NO_x emissions compared to current certification values (322% and 326% higher for NO_x and 244% and 247% higher for HC + NO_x for NEDC and WLTP Class 3 cycle, respectively).