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%.

Cryptosporidium oocyst persistence in agricultural streams -a mobile-immobile model framework assessment.

Rivers are a means of rapid and long-distance transmission of pathogenic microorganisms from upstream terrestrial sources. Pathogens enter streams and rivers via overland flow, shallow groundwater discharge, and direct inputs. Of concern is the protozoal parasite, Cryptosporidium, which can remain infective for weeks to months under cool and moist conditions, with the infectious stage (oocysts) largely resistant to chlorination. We applied a mobile-immobile model framework to assess Cryptosporidium transport and retention in streams, that also accounts for inactivation. The model is applied to California's Central Valley where Cryptosporidium exposure can be at higher risk due to agricultural and wildlife nonpoint sources. The results demonstrate that hyporheic exchange is an important process to include in models characterizing pathogen dynamics in streams, delaying downstream transmission and allowing for immobilization processes, such as reversible filtration in the sediments, to occur. Although in-stream concentrations decrease relatively quickly (within hours), pathogen accumulation of up to 66% of the inputs due to immobilization processes in the sediments and slower moving surface water could result in long retention times (months to years). The model appropriately estimates baseflow pathogen accumulation and can help predict the potential loads of resuspended pathogens in response to a storm event.

Changes in bacteria composition and efficiency of constructed wetlands under sustained overloads: A modeling experiment.

The average organic and hydraulic loads that Constructed Wetlands (CWs) receive are key parameters for their adequate long-term functioning. However, over their lifespan they will inevitably be subject to either episodic or sustained overloadings. Despite that the consequences of sustained overloading are well known (e.g., clogging), the threshold of overloads that these systems can tolerate is difficult to determine. Moreover, the mechanisms that might sustain the buffering capacity (i.e., the reduction of peaks in nutrient load) during overloads are not well understood. The aim of this work is to evaluate the effect of sudden but sustained organic and hydraulic overloads on the general functioning of CWs. To that end, the mathematical model BIO_PORE was used to simulate five different scenarios, based on the features and operation conditions of a pilot CW system: a control simulation representing the average loads; 2 simulations representing +10% and +30% sustained organic overloads; one simulation representing a sustained +30% hydraulic overload; and one simulation with sustained organic and hydraulic overloads of +15% each. Different model outputs (e.g., total bacterial biomass and its spatial distribution, effluent concentrations) were compared among different simulations to evaluate the effects of such operation changes. Results reveal that overloads determine a temporary decrease in removal efficiency before microbial biomass adapts to the new conditions and COD removal efficiency is recovered. Increasing organic overloads cause stronger temporary decreases in COD removal efficiency compared to increasing hydraulic loads. The pace at which clogging develops increases by 10% for each 10% increase on the organic load.