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Abstract: Biodiesels are promoted as alternative fuels and their applications in diesel engines have been investigated by many researchers. However, the particle size distribution emitted from heavy-duty diesel engines fueled with palm-biodiesel blended with premium diesel fuel and paraffinic fuel blended with palm-biodiesel has seldom been addressed. Thus, five test fuels were used in this work to study the particle size distribution: D100 (premium diesel fuel), B100 (100% palm-biodiesel), B20 (20vol% palm-biodiesel+80vol% D100), BP9505 (95vol% paraffinic fuel+5vol% palm-biodiesel) and BP8020 (80vol% paraffinic fuel+20vol% palm-biodiesel). A Micro-Orifice Uniform Deposit Impactor (MOUDI) equipped with aluminum filters was used to collect size-resolved samples. Experimental results indicated that palm-biodiesel blends and paraffinic fuel blends could improve combustion efficiency in diesel engines, but pure palm-biodiesel could cause incomplete combustion. Adding palm-biodiesel to diesel fuel would slightly increase particles with diameter <0.31μm but paraffinic fuel blends could decrease particles with diameter <1μm. The mass median diameter of overall particles (MMDo) and σ g,o are 0.439μm and 3.88 for D100; 0.380μm and 3.24 for B20; 0.465μm and 4.22 for B100; 1.40μm and 4.92 for BP9505; 1.46μm and 2.25 for BP8020. There are more particles with low aerodynamic diameters (diameter <0.31μm) in the exhaust of D100, B20 and B100 fuels. On the other hand, a greater fraction of particulate matter of BP9505 and BP8020 existed in coarse particles (diameter: 2.5–10μm). Energy efficiency also increases significantly by 12.3–15.1% with the introduction of paraffinic fuel blends into the engine. Nevertheless, paraffinic fuel blends also reduce the emission of particulate matters by 36.0–38.4%. Carbon monoxide was decreased by 36.8–48.5%. Total hydrocarbon is 39.6–41.7% less than diesel fuel combustion. Nitrogen oxides emission is about 5% lower for paraffinic fuel. These results show that paraffinic fuel can be very competitive and replaced diesel fuels in the future. [Copyright &y& Elsevier]

Background: The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment.Methods: To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm.Results: A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively.Conclusions: The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures. [ABSTRACT FROM AUTHOR]