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Log wood burning is a significant source of volatile organic compounds including aromatic hydrocarbons (ArHC). ArHC are harmful, are reactive in the ambient atmosphere, and are important secondary organic aerosol (SOA) precursors. Consequently, SOA represents a major fraction of the sub-micron organic aerosol pollution from log wood burning. ArHC reduction is thus critical in the mitigation of adverse health and environmental effects of log wood burning. In this study, two Pt-based catalytic converters were prepared and tested for the mitigation of real-world log wood burning emissions, including ArHC and SOA formation, as well as toxic carbon monoxide and methane, a greenhouse gas. Substantial removal of mono- and polycyclic ArHC and phenolic compounds was achieved with both catalysts operated at realistic chimney temperatures (50% conversion was achieved at 200 and 300 degrees C for non-methane hydrocarbons in our experiments for Pt/Al2O3 and Pt/CeO2-Al2O3, respectively). The catalytically cleaned emissions exhibited a substantially reduced SOA formation already at temperatures as low as 185-310 degrees C. This reduces the sub-micron PM burden of log wood burning significantly. Thus, catalytic converters can effectively reduce primary and secondary log wood burning pollutants and, thereby, their adverse health impacts and environmental effects.

Surface-enhanced Raman spectroscopy (SERS) coupled with density functional theory (DFT) computations can characterise the adsorption orientation of a molecule on a nanoparticle surface. When using DFT to simulate SERS on a silver surface, one typically employs an atom (Ag), ion (Ag+), or cluster (Ag-x or Ag-x(+)) as the model surface. Here, by examining the nucleobase 2,6-diaminopurine (2,6-DAP) and then generalising our strategy to three other molecules, we show that employing silver oxide (Ag2O) as the model surface can quantitatively improve the accuracy of simulated SERS.