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This study investigates particulate matter (PM) and regulated emissions from renewable rapeseed oil methyl ester (RME) biodiesel in pure and blended forms and contrasts that to conventional diesel fuel. Environmental and health concerns are the major motivation for combustion engines research, especially finding sustainable alternatives to fossil fuels and reducing diesel PM emissions. Fatty acid methyl esters (FAME), including RME, are renewable fuels commonly used from low level blends with diesel to full substitution. They strongly reduce the net carbon dioxide emissions. It is largely unknown how the emissions and characteristics of PM get altered by the combined effect of adding biodiesel to diesel and implementing modern engine concepts that reduce nitrogen oxides (NOx) emissions by exhaust gas recirculation (EGR).

The focus has recently been directed towards the engine out soot from Diesel engines. Running an engine in PPC (Partially Premixed Combustion) mode has a proven tendency of reducing these emissions significantly. In addition to combustion strategy, several studies have suggested that using alcohol fuels aid in reducing soot emissions to ultra-low levels. This study analyzes and compares the characteristics of PM emissions from naphtha gasoline PPC, ethanol PPC, methanol PPC and methanol diffusion combustion in terms of soot mass concentration, number concentration and particle size distribution in a single cylinder Scania D13 engine, while varying the intake O2. Intake temperature and injection pressure sweeps were also conducted. The fuels emitting the highest mass concentration of particles (Micro Soot Sensor) were gasoline and methanol followed by ethanol. The two alcohols tested emitted nucleation mode particles only, whereas gasoline emitted accumulation mode particles as well.

In order to reduce nitrogen oxides (NOx) and soot emissions while maintaining high thermal efficiency, more advanced combustion concepts have been developed over the years, such as Homogeneous Charge Compression Ignition (HCCI) and Partially Premixed Combustion (PPC), as possible combustion processes in commercial engines. Compared to HCCI, PPC has advantages of lower unburned hydrocarbon (UHC) and carbon monoxide (CO) emissions; however, due to increased fuel stratifications, soot emissions can be a challenge when adding Exhaust-Gas Recirculation (EGR) gas. The current work presents particle size distribution measurements performed from HCCI-like combustion with very early (120 CAD BTDC) to PPC combustion with late injection timing (11 CAD BTDC) at two intake oxygen rates, 21% and 15% respectively. Particle size distributions were measured using a differential mobility spectrometer DMS500.

The major challenge of the post-processing of soot aggregates in transmission electron microscope (TEM) images is the detection of soot primary particles that have no clear boundaries, vary in size within the fractal aggregates, and often overlap with each other. In this study, we propose an automated detection code for primary particles implementing the Canny Edge Detection (CED) and Circular Hough Transform (CHT) on pre-processed TEM images for particle edge enhancement using unsharp filtering as well as image inversion and self-subtraction. The particle detection code is tested for soot TEM images obtained at various ambient and injection conditions, and from five different combustion facilities including three constant-volume combustion chambers and two diesel engines.