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Alternative fuels and injection technologies are a necessary component of particulate emission reduction strategies for compression ignition engines. Consequently, this study undertakes a physicochemical characterization of diesel particulate matter (DPM) for engines equipped with alternative injection technologies (direct injection and common rail) and alternative fuels (ultra low sulfur diesel, a 20% biodiesel blend, and a synthetic diesel). Particle physical properties were addressed by measuring particle number size distributions, and particle chemical properties were addressed by measuring polycyclic aromatic hydrocarbons (PAHs) and reactive oxygen species (ROS). Particle volatility was determined by passing the polydisperse size distribution through a thermodenuder set to 300 °C. The results from this study, conducted over a four point test cycle, showed that both fuel type and injection technology have an impact on particle emissions, but injection technology was the more important factor. Significant particle number emission (54%-84%) reductions were achieved at half load operation (1% increase-43% decrease at full load) with the common rail injection system; however, the particles had a significantly higher PAH fraction (by a factor of 2 to 4) and ROS concentrations (by a factor of 6 to 16) both expressed on a test-cycle averaged basis. The results of this study have significant implications for the health effects of DPM emissions from both direct injection and common rail engines utilizing various alternative fuels. © 2011 American Chemical Society.

This study undertook a physicochemical characterization of particle emissions from a single compression ignition engine operated at one test mode with 3 biodiesel fuels made from 3 different feedstocks (i.e., soy, tallow, and canola) at 4 different blend percentages (20%, 40%, 60%, and 80%) to gain insights into their particle-related health effects. Particle physical properties were inferred by measuring particle number size distributions both with and without heating within a thermodenuder (TD) and also by measuring particulate matter (PM) emission factors with an aerodynamic diameter less than 10 μm (PM10). The chemical properties of particulates were investigated by measuring particle and vapor phase Polycyclic Aromatic Hydrocarbons (PAHs) and also Reactive Oxygen Species (ROS) concentrations. The particle number size distributions showed strong dependency on feedstock and blend percentage with some fuel types showing increased particle number emissions, while others showed particle number reductions. In addition, the median particle diameter decreased as the blend percentage was increased. Particle and vapor phase PAHs were generally reduced with biodiesel, with the results being relatively independent of the blend percentage. The ROS concentrations increased monotonically with biodiesel blend percentage but did not exhibit strong feedstock variability. Furthermore, the ROS concentrations correlated quite well with the organic volume percentage of particles - a quantity which increased with increasing blend percentage. At higher blend percentages, the particle surface area was significantly reduced, but the particles were internally mixed with a greater organic volume percentage (containing ROS) which has implications for using surface area as a regulatory metric for diesel particulate matter (DPM) emissions. © 2011 American Chemical Society.

Environmental contextAirborne fine particles affect local, regional and global air quality and deteriorate the environment. Therefore comprehensive information on the locations and strengths of particle sources is critical for the development of strategies for mitigating the adverse effects of aerosols. The multivariate data analysis techniques used in this paper allowed the benefits of a previous control measure to be assessed and provided vital information for the application of further pollution reduction strategies to this and other areas of the world. AbstractAirborne fine particles were collected at a suburban site in Queensland, Australia between 1995 and 2003. The samples were analysed for 21 elements and Positive Matrix Factorisation (PMF), Preference Ranking Organisation Methods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) were applied to the data. PROMETHEE provided information on the ranking of pollutant levels from the sampling years whereas PMF provided insights into the sources of the pollutants, their chemical composition, most likely locations and relative contribution to the levels of particulate pollution at the site. PROMETHEE and GAIA found that the removal of lead from fuel in the area had a significant effect on the pollution patterns whereas PMF identified six pollution sources, including railways (5.5%), biomass burning (43.3%), soil (9.2%), sea salt (15.6%), aged sea salt (24.4%) and motor vehicles (2.0%). Thus the results gave information that can assist in the formulation of mitigation measures for air pollution.