AERMOD as a Gaussian dispersion model for planning tracer gas dispersion tests for landfill methane emission quantification

The measurement of methane emissions from landfills is important to the understanding of landfills' contribution to greenhouse gas emissions. The Tracer Dispersion Method (TDM) is becoming widely accepted as a technique, which allows landfill emissions to be quantified accurately provided that measurements are taken where the plumes of a released tracer-gas and landfill-gas are well-mixed. However, the distance at which full mixing of the gases occurs is generally unknown prior to any experimental campaign.To overcome this problem the present paper demonstrates that, for any specific TDM application, a simple Gaussian dispersion model (AERMOD) can be run beforehand to help determine the distance from the source at which full mixing conditions occur, and the likely associated measurement errors. An AERMOD model was created to simulate a series of TDM trials carried out at a UK landfill, and was benchmarked against the experimental data obtained. The model was used to investigate the impact of different factors (e.g. tracer cylinder placements, wind directions, atmospheric stability parameters) on TDM results to identify appropriate experimental set ups for different conditions.The contribution of incomplete vertical mixing of tracer and landfill gas on TDM measurement error was explored using the model. It was observed that full mixing conditions at ground level do not imply full mixing over the entire plume height. However, when full mixing conditions were satisfied at ground level, then the error introduced by variations in mixing higher up were always less than 10%.</p

Cholesterol in negatively charged lipid bilayers modulates the effect of the antimicrobial protein granulysin

The release of granulysin, a 9-kDa cationic protein, from lysosomal granules of cytotoxic T lymphocytes and natural killer cells plays an important role in host defense against microbial pathogens. Granulysin is endocytosed by the infected target cell via lipid rafts and kills subsequently intracellular bacteria. The mechanism by which granulysin binds to eukaryotic and prokaryotic cells but lyses only the latter is not well understood. We have studied the effect of granulysin on large unilamellar vesicles (LUVs) and supported bilayers with prokaryotic and eukaryotic lipid mixtures or model membranes with various lipid compositions and charges. Binding of granulysin to bilayers with negative charges, as typically found in bacteria and lipid rafts of eukaryotic cells, was shown by immunoblotting. Fluorescence release assays using LUV revealed an increase in permeability of prokaryotic, negatively charged and lipid raft-like bilayers devoid of cholesterol. Changes in permeability of these bilayers could be correlated to defects of various sizes penetrating supported bilayers as shown by atomic force microscopy. Based on these results, we conclude that granulysin causes defects in negatively charged cholesterol-free membranes, a membrane composition typically found in bacteria. In contrast, granulysin is able to bind to lipid rafts in eukaryotic cell membranes, where it is taken up by the endocytotic pathway, leaving the cell intac