The results of experiments performed by gasoline and natural gas fuels in a single cylinder research engine were evaluated in this study. The main objective of this study is to compare exhaust gas emissions, efficiency, and burn durations for both fuels in stoichiometric and lean mixture. At the same time, cycle to cycle variation in these operating conditions should not exceed an acceptable value. In the ultra-lean mixture, gasoline fuel exceeded this determined limit before Compressed Natural Gas (CNG). Therefore, the reduction in NO was restricted by cyclic variations. In combustion analysis, although the burn duration of the gasoline in stoichiometric conditions was shorter than CNG, this situation reversed in favor of CNG in the ultra-lean mixtures. Contrary to some studies in the literature, the spark advance and ignition delay for CNG were the same or shorter than gasoline in this study. The primary reasons for this change are the high compression ratio and the different combustion chamber geometry. The increase in turbulence intensity has different effects on CNG and gasoline. As a result, it has been observed that NO emissions can meet the limits without a loss of efficiency for this engine operated with CNG under the ultra-lean mixture.

Interest for particulate matter (PM) sensors has increased significantly during last decade. Having a proper experimental setup to test these sensors is necessary. Most of the devices that are used in the PM test setups for both PM generating and measuring are bulky and expensive. In this study a cost-effective experimental setup has been designed with a custom made PM generator and small size laser and quartz crystal microbalance (QCM) sensors. The generator has the capability of producing PM from three different sources: dry powder, liquid suspension and combustion. The QCM completes the weakness of small laser sensors for sensing the ultra-fine particles. Moreover, performance of the QCM sensor has been investigated with different PM sources and different ambient conditions. It has been found that the response of QCM could be affected from PM source and ambient condition. The change in PM composition and size causes notable impact on QCM response. Relative humidity (RH) also could change the sensor response up to 22%. While changing the temperature of the flow has not significant effect on QCM response, increasing the temperature from 25°C to 30°C caused 12% change in QCM response in grease-coated one. The QCM sensor has the best response with small size smoke PM’s with lowest effect from ambient conditions.