Simultaneous measurement of NO and NO(2) by dual-wavelength quantum cascade laser spectroscopy.

The concept of a multi-wavelength quantum cascade laser emitting at two or more spectrally well-separated wavelengths is highly appealing for applied spectroscopy, as it allows detecting several species with compact and cost-efficient optical setups. Here we present a practical realization of such a dual-wavelength setup, which is based on a room-temperature quantum cascade laser emitting single-mode at 1600 cm-1 and 1900 cm-1 and is thus well-suited for simultaneous NO and NO2 detection. Operated in a time-division multiplexed mode, our spectrometer reaches detection limits of 0.5 and 1.5 ppb for NO2 and NO, respectively. The performance of the system is validated against the well-established chemiluminescence detection while measuring the NOx emissions on an automotive test-bench, as well as upon monitoring the pollution at a suburban site.

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).