Martin Weilenmann

Molecular hydrogen (H2) emissions from gasoline and diesel vehicles.

This study assesses individual-vehicle molecular hydrogen (H2) emissions in exhaust gas from current gasoline and diesel vehicles measured on a chassis dynamometer. Absolute H2 emissions were found to be highest for motorcycles and scooters (141+/-38.6 mg km(-1)), approximately 5 times higher than for gasoline-powered automobiles (26.5+/-12.1 mg km(-1)). All diesel-powered vehicles emitted marginal amounts of H2 ( approximately 0.1 mg km(-1)). For automobiles, the highest emission factors were observed for sub-cycles subject to a cold-start (mean of 53.1+/-17.0 mg km(-1)). High speeds also caused elevated H2 emission factors for sub-cycles reaching at least 150 km h(-1) (mean of 40.4+/-7.1 mg km(-1)). We show that H2/CO ratios (mol mol(-1)) from gasoline-powered vehicles are variable (sub-cycle means of 0.44-5.69) and are typically higher (mean for automobiles 1.02, for 2-wheelers 0.59) than previous atmospheric ratios characteristic of traffic-influenced measurements. The lowest mean individual sub-cycle ratios, which correspond to high absolute emissions of both H2 and CO, were observed during cold starts (for automobiles 0.48, for 2-wheelers 0.44) and at high vehicle speeds (for automobiles 0.73, for 2-wheelers 0.45). This finding illustrates the importance of these conditions to observed H2/CO ratios in ambient air. Overall, 2-wheelers displayed lower H2/CO ratios (0.48-0.69) than those from gasoline-powered automobiles (0.75-3.18). This observation, along with the lower H2/CO ratios observed through studies without catalytic converters, suggests that less developed (e.g. 2-wheelers) and older vehicle technologies are largely responsible for the atmospheric H2/CO ratios reported in past literature.

Fuel Consumption and CO2/Pollutant Emissions of Mobile Air Conditioning at Fleet Level - New Data and Model Comparison

Mobile air conditioning (MAC) systems are the second-largest energy consumers in cars after driving itself. While different measurement series are available to illustrate their behavior in hot ambient conditions, little data are available for lower temperatures. There are also no data available on diesel vehicles, despite these being quite common in Europe (up to 70% of the fleet in some countries). In the present study, six representative modern diesel passenger cars were tested. In combination with data from previous measurements on gasoline cars, a new model was developed - EEMAC = Empa Emission model for Mobile Air Conditioning systems - to predict emissions from air conditioning. The measurements obtained show that A/C activity still occurs at temperatures below the desired interior temperature. The EEMAC model was applied to the average meteorological year of a central European region and compared with the US EPA MOBILE6 model. As temperatures in central Europe are often below 20 degrees C (the point below which the two models differ), the overall results differ clearly. The estimated average annual CO(2) output according to EEMAC is six times higher than that of MOBILE6. EEMAC also indicates that around two-thirds of the fuel used for air conditioning could be saved by switching the MAC system off below 18 degrees C.

Static and dynamic instantaneous emission modelling

Emission models can be categorised into three categories: average speed models; traffic situation models, used at macro-scale or meso-scale level (national, regional, city level); and instantaneous (modal) models, useful at micro-scale level (street, vehicle level). To improve the existing instantaneous emission models, some preconditions must be fulfilled: the emission signals should be measured on a 10 Hz basis, due to their frequency content. Additionally, the transport dynamics from the engine to the analysers must be compensated by time-varying approaches. With these preconditions fulfilled, a new static instantaneous emission model is developed and the improvement in quality is checked by comparing it statistically with older models. A dynamic instantaneous model, able to include the transient generation of emissions, is subsequently created and the quality of prediction of engine-out emissions is determined. When a catalyst model is added, more accurate predictions of emissions for vehicles with af...

The cold start emissions of light-duty-vehicle fleets: A simplified physics-based model for the estimation of CO2 and pollutants

The emissions from hot driving conditions, in which the exhaust-after-treatment systems are working properly, continue to decrease, which is why the emissions of cold starts have gained in importance. Traffic emission models are used to estimate and predict vehicle fleet emissions and the air quality of countries, regions, cities, etc. In addition to the statistical input of fleet activities, these models are mostly based on the use of separate emission sub-models for hot driving and cold start driving. In reality, the cold start models are almost entirely empirical and of limited accuracy. In this work, a model is developed that is based on physical reasoning, i.e., it is based on energy balances. Because many details, such as the thermal conductivities and the engine control decisions, are unknown, the model must be able to address different simplifications. The model can be parameterized with as few as two tests per vehicle. It is applied to several car samples (six to eight vehicles each) of different technical generations and shows reliable prediction for any combination of the driving pattern (including gradient), the ambient temperature, the stop time before the ride and the duration of the ride (if shorter than the warm-up phase).

Pollutant emissions from vehicles with regenerating after-treatment systems in regulatory and real-world driving cycles

Regenerating exhaust after-treatment systems are increasingly employed in passenger cars in order to comply with regulatory emission standards. These systems include pollutant storage units that occasionally have to be regenerated. The regeneration strategy applied, the resultant emission levels and their share of the emission level during normal operation mode are key issues in determining realistic overall emission factors for these cars. In order to investigate these topics, test series with four cars featuring different types of such after-treatment systems were carried out. The emission performance in legislative and real-world cycles was monitored as well as at constant speeds. The extra emissions determined during regeneration stages are presented together with the methodology applied to calculate their impact on overall emissions. It can be concluded that exhaust after-treatment systems with storage units cause substantial overall extra emissions during regeneration mode and can appreciably affect the emission factors of cars equipped with such systems, depending on the frequency of regenerations. Considering that the fleet appearance of vehicles equipped with such after-treatment systems will increase due to the evolution of statutory pollutant emission levels, extra emissions originating from regenerations of pollutant storage units consequently need to be taken into account for fleet emission inventories. Accurately quantifying these extra emissions is achieved by either conducting sufficient repetitions of emission measurements with an individual car or by considerably increasing the size of the sample of cars with comparable after-treatment systems.

VOC composition and ozone-forming potential of the exhaust gas of in-use motorcycles

The emission profile of volatile organic compounds (VOC) and the ozone-forming potential (OP) of the exhaust gas of six in-use motorcycles (four 4-stroke- and two 2-stroke-engines) were determined. The motorcycles were tested on a chassis dynamometer in a real-world driving cycle. The analysis involved the C2–C12-hydrocarbons as well as the aldehydes and ketones. Additionally, the regulated THC and NOx emissions were measured according to the test procedure for type approval (ECE 40). Two vehicles did not fulfil the THC emission standard, whereas all vehicles met the requirements for NOx emission. The aromatic fuel components toluene and xylene, and the combustion products ethene and propene contributed most to the OP of the VOC emission. The highest OP was found with the 2-stroke engines. The VOC profile of the emissions varied with vehicle and driving conditions. The reactivity of the exhaust gas, defined as gram ozone per gram of non-methane organic gases (NMOG), increased with vehicle speed.

Real-world and type-approval emission evolution of passenger cars

The investigation of several passenger car generations with gasoline engines shows that the emissions depend very strongly on the driving cycle. Official type approval cycles allow just very inaccurate predications about their real-world emissions. The measured gasoline vehicles have up to factor 11 higher real-life emissions than in type approval cycles. However, a clear reduction of real-world emissions can be seen over the different investigated generations of gasoline cars. In addition, it can be seen that the cold start emissions depend strongly on ambient temperature levels for all generations of cars and that the cold start accounts for an increasing part of the total pollutant emissions. As an extreme example, the cold start hydrocarbon emissions of Euro-3 cars at -20°C ambient temperature correspond approximately to those of 1,000 km driving with warm engines.

The benzene problem: impact of three-way catalyst technology: potential for further improvement

Chemical ionisation mass spectrometry (CI-MS) was applied to study the benzene emission characteristics of a TWC-vehicle at a time resolution of one Hertz. Three important operating conditions with increased emissions were identified: at vehicle start; at extended stop-and-go situations; and whenever a catalyst-induced benzene formation occurs. The cold start influence was detectable for about 200 seconds of driving corresponding to a distance of 1.2 km. At hot engine/catalyst mean pre- and post-catalyst emission rates of 25–150 mg km-1 and 0.1–135 mg km-1 were determined. Catalyst conversion varied from 0.07 to >0.99. Even negative conversion efficiencies were observed at several occasions, indicating that benzene can be formed de novo in a TWC. It is of importance to lower benzene emissions at these critical operating conditions to further reduce ambient air levels in cities and with it the cancer risk for large proportions of our population.

A fleet-prediction oriented catalyst model for highly transient driving in cold and hot mode conditions

Various models for simulating catalytic converters are given in the literature. They deal with a wide range of different aspects. In addition to the type of catalytic converter (three-way catalytic converter, diesel oxidation catalytic converter, etc.), the aspect of complexity versus accuracy and speed can be tackled using different approaches. Moreover, the desired use has an influence on the model structure: optimization of catalyst design or prediction of emissions from real-world traffic situations or optimization of air–fuel ratio control? The model described here has been developed to predict emissions in arbitrary real-world driving patterns, both for hot driving as well as for cold-start situations. As these tests mainly last over 30 minutes (real time), the calculation effort should be small. The model should be easy to parameterize, as it should be applicable to vehicles from traffic. A model with a reduced set of chemical reactions has been developed with a particular focus on the thermal balance for cold-start cycles. Its outputs are the pollutant emissions at the tailpipe if the emissions, exhaust mass flow and temperature from the engine are given. It is applied to three-way catalytic converters. It models the chemical phenomena almost entirely based on oxygen storage and release reactions, which dominate highly transient situations. The model has been validated against a large database of measured driving cycles, carried out using different types of cars. It presents an acceptable degree of correlation between simulated and experimental results.