Further investigation of constructed wetland clog state using spin-lattice relaxation measurements

Constructed wetlands are an efficient method of wastewater treatment for both domestic and industrial applications. A typical wetland comprises a gravel matrix in which plants are grown. The pore spaces between the gravel particles become occluded over time leading to a reduction in treatment efficiency. Many beds will employ forced aeration to improve their effectiveness. Magnetic resonance is a powerful tool for determining the clog state of a wetland, which can be achieved using T₁ relaxation measurements¹. This offers an instant determination of the clog state which is not possible with conventional tracer dyes.

Earlier work² has seen a Helmholtz-style magnetic resonance sensor developed for long term deployment into constructed wetlands with the relationship between clog state and T₁ identified. In a scenario where the probe is deployed in a wetland other factors such as temperature or motion of the fluid due to an aeration system will change the recorded values. Additionally, the T₁ relaxation has only been explored for samples using domestic waste. Industrial wastewater might contain chemical compounds with a large number of protons, such as airstrip runoff, which will significantly change the T₁ values.

In this work we present additional lab tests as well as a series of field tests to better understand these unknown variables. Initially we explored the effect that the use of forced aeration had on the collected T₁ relaxation data in a wetland where the use of aeration reduced the recorded T₁ relaxation time from 1438 ± 66 ms to 966 ± 37 ms. Further laboratory experiments then looked at the relaxation times of differing concentrations of propylene glycol (a potential component of industrial wastewater) observing that there is an exponential functional relationship between the percentage of propylene glycol and the recorded T₁ relaxation time. When monitoring in a wetland such a relationship will make extracting useful information about the clog state difficult and a way to practically implement an MR sensor network in a wetland with this type of wastewater influent will be discussed.

This work was part of an EU FP7 project to develop an Autonomous Reed Bed Installation (www.ARBI-EU.com) with the aim to provide an efficient wastewater treatment system with a focus on the optimisation of the clog state to significantly increase the operational lifetime of the wetland.