Explore an Approach to Determine Odour Emissions from Water Surfaces

摘要

Odour emissions from water surfaces such as primary tanks or aeration tanks in waste water treatment plant have become an increasing nuisance to the neighboring communities. In order to assess the odour nuisance level, the flux chamber technique has been used to quantify the odour emissions from the water surfaces. However, field measurements with portable wind tunnels have indicated that the odour emissions are highly dependent on environmental variables, such as wind speed and temperature. In the past some studies indicated that flux chamber technique underestimates the odour emissions. The transfer of odour between the air and water is governed by turbulent and molecular transport processes. Both transport processes can be characterized by diffusion coefficients and the concentration gradient between air and water surface. Away from the water surface, the turbulent transfer is typically orders of magnitude higher than the molecular transfer. We developed a two-step approach for estimating odour emissions from the water surfaces and our approach is based on turbulent transfer. The first step uses the static flux chamber to measure the odour concentration gradient between the air and water surface. The second step quantifies the odour emission rates by applying the turbulent transfer rates estimated by a micrometeorological model. We applied this approach to one waste water treatment plant to quantify the odour emission rates from aeration tanks and aerobic bio-solids complexes. In order to verify our approach, we measured the ambient odour concentrations at various downwind distances under different meteorological conditions and input the quantified odour emission rates into an air dispersion model (the US EPA AERMOD model), to predict the downwind odour concentrations. In this study, the modelled and measured downwind ambient odour concentrations agree well, demonstrating that this approach is plausible and can be applied to other surfaces as well.