Poster Presentation Freshwater Sciences 2023

Nitrate biosorption: from lab-theory to field-practicality. (#690)

Nayla Rhein 1 , Rhonda J Rosengren 1
  1. University of Otago, Dunedin, OTAGO, New Zealand

Nitrates are a common cause of waterway pollution. Many remediation techniques exist, however they are often expensive, highly technical and very anthropocentric. Adsorption is an alternative that can be much cheaper and easier to implement for environmental purposes. Transforming biowaste into biosorbents to target specific aquatic toxicants has been a popular field of research, though most of these studies are not suited for environmental applications. We have developed a spent coffee ground biosorbent, chemically modified for nitrate remediation. It was first optimized in the lab, on a small scale with field-relevant parameters such as water temperature, pH and complex matrixes. Up to 90% of the nitrates were removed from 25 mg/L spiked stream water. With this success, we aimed to test this system in a mesocosm experiment. However, scaling up was much more problematic than anticipated. For example, choline chloride is a chemical that is often labelled as ‘easily accessible’ but sourcing 7 kg of lab-grade choline chloride, storing it and handling it caused numerous problems. Additionally, glassware, basic lab equipment, space and resources that are typically available in a university lab were ill-adapted for large scale reactions. This led to inconsistent and ineffective biosorbent preparation. All of these factors are rarely discussed by researchers developing products that have ‘field-application potential’, yet, they are crucial in order to design systems able to cross from lab-theory to field-practicality. Scientific articles tend to focus solely on end results rather than the processes and optimizations that lead to them. Sharing what didn’t work is important so that others do not waste time, effort, and resources. Therefore, this presentation will address in detail the issues encountered when scaling-up for field relevance.