No abstract

A 73-day field study of in situ aerobic biodegradation of polychlorinated biphenyls (PCBs) in the Hudson River shows that indigenous aerobic microorganisms can degrade the lightly chlorinated PCBs present in these sediments. Addition of inorganic nutrients, biphenyl, and oxygen enhanced PCB biodegradation, as indicated both by a 37 to 55 percent loss of PCBs and by the production of chlorobenzoates, intermediates in the PCB biodegradation pathway. Repeated inoculation with a purified PCB-degrading bacterium failed to improve biodegradative activity. Biodegradation was also observed under mixed but unamended conditions, which suggests that this process may occur commonly in river sediments, with implications for PCB fate models and risk assessments.

No abstract

Since the pioneering works of Michels et. al., followed by Sommerfeld and Welker, over eighty years ago, there is much interest in modelling confinement of the ground state hydrogen atom by an impenetrable sphere of confining radius, Rc. The literature “truncated probability density” model assumes that, upon confinement, the nodeless free hydrogen atom ground state probability density is replaced by the innermost node of an excited state probability density, fitted to Rc by a non-quantum parameter, λ. Since the literature model is an excited state, the confined electron energy, E1c, is inversely proportional to the excited state Bohr radius, Rλ (or aoλ2), which becomes larger than Rc as λ increases. However, due to the infinite potential barrier at radii greater than Rc, such large values of Rλ are not allowed. In contrast, for the Particle in an Infinite Box (PIB), Harmonic Oscillator (HO) and the proposed compressed probability density ground state models, the particle energy is inversely proportional to the confined length (Lc or Rc), the maximum length allowed. Additionally, the Dirac/Sommerfeld fine structure formula calculation of E1c is in agreement with the proposed model, but does not support the literature truncated probability density model, indicating the literature model is incorrect.