Do aerosols act as catalysts in the OH radical initiated atmospheric oxidation of volatile organic compounds?

Smog chamber/FTIR techniques were used to study the relative reactivity of OH radicals with methanol, ethanol, phenol, C₂H₄, C₂H₂, and p-xylene in 750 Torr of air diluent at 296±2 K. Experiments were performed with, and without, 500–8000 μg m⁻³ (4000–50 000 μm² cm⁻³ surface area per volume) of NaCl, (NH₄)₂SO₄ or NH₄NO₃ aerosol. In contrast to the recent findings of Oh and Andino (Atmospheric Environment 34 (2000) 2901, 36 (2002) 149; International Journal of Chemical Kinetics 33 (2001) 422) there was no discernable effect of aerosol on the rate of loss of the organic compounds via reaction with OH radicals. Gas kinetic theory arguments cast doubt upon the findings of Oh and Andino. The available data suggest that the answer to the title question is “No”. As part of this work the rate constants for reactions of OH radicals with methanol, ethanol, and phenol in 750 Torr of air at 296 K were determined to be: k_OH+CH3OH=(8.12±0.54)×10⁻¹³, k_OH+C2H5OH=(3.47±0.32)×10⁻¹² and k_OH+phenol=(3.27±0.31)×10⁻¹¹ cm³ molecule⁻¹ s⁻¹.     

Insights into the structure of urea-like compounds as inhibitors of the juvenile hormone epoxide hydrolase (JHEH) of the tobacco hornworm Manduca sexta: analysis of the binding modes and structure-activity relationships of the inhibitors by docking and CoMFA calculations

Substituted urea compounds are well-known as potent inhibitors of juvenile hormone epoxide hydrolase (JHEH) of the tobacco hornworm Manduca sexta. Docking simulations of 47 derivatives inside JHEH were performed to gain insight into the structural characteristics of these complexes. The obtained orientations show a strong similitude with the observed in the known X-ray crystal structures of human soluble epoxide hydrolase (sEH) complexed with dialkylurea inhibitors. In addition, the predicted inhibitor concentration (IC₅₀) of the above-mentioned compounds as JHEH inhibitors were obtained by a quantitative structure-activity relationship (QSAR) method by using comparative molecular field analysis (CoMFA) applied to aligned dataset. The best models included steric and electrostatic fields and had adequate predictive abilities. In addition, these models were used to predict the activity of an external test set of compounds that was not used for building the model. Furthermore, plots of the CoMFA fields allowed conclusions to be drawn for the choice of suitable inhibitors.