How Heat Transfer Indirectly Affects Performance of Algae-Bacteria Raceways
| Type | : | ACL |
|---|---|---|
| Nature | : | Production scientifique |
| Au bénéfice du Laboratoire | : | Oui |
| Statut de publication | : | Publié |
| Année de publication | : | 2022 |
| Auteurs (2) | : | CASAGLI Francesca BERNARD Olivier |
| Revue scientifique | : | Microorganisms |
| Volume | : | 10 |
| Fascicule | : | 8 |
| Pages | : | |
| DOI | : | 10.3390/microorganisms10081515 |
| URL | : | https://www.mdpi.com/2076-2607/10/8/1515 |
| Abstract | : | Oxygenation in wastewater treatment leads to a high energy demand. High-rate algal-bacterial ponds (HRABP) have often been considered an interesting solution to reduce this energy cost, as the oxygen is provided by microalgae during photosynthesis. These complex dynamic processes are subject to solar fluxes and consequently permanent fluctuations in light and temperature. The process efficiency therefore highly depends on the location and the period of the year. In addition, the temperature response can be strongly affected by the process configuration (set-up, water depth). Raised pilot-scale raceways are typically used in experimental campaigns, while raceways lying on the ground are the standard reactor configuration for industrial-scale applications. It is therefore important to assess what the consequences are for the temperature patterns of the different reactor configurations and the water levels. The long-term validated algae-bacteria (ALBA) model was used to represent algae-bacteria dynamics in HRABPs. The model was previously validated over 600 days of outdoor measurements, at two different locations and for the four seasons. However, the first version of the model, like all the existing algae-bacteria models, was not fully predictive, since, to be run, it required the measurement of water temperature. The ALBA model was therefore updated, coupling it with a physical model that predicts the temperature evolution in the HRABP. A heat transfer model was developed, and it was able to accurately predict the temperature during the year (with a standard error of 1.5 ∘C). The full predictive model, using the temperature predictions, degraded the model’s predictive performances by less than 3%. N2O predictions were affected by ±7%, highlighting the sensitivity of nitrification to temperature The temperature response for two different process configurations were then compared. The biological process can be subjected to different temperature dynamics, with more extreme temperature events when the raceway does not lie on the ground and for thinner depths. Such a situation is more likely to lead to culture crashes. |
| Mots-clés | : | microalgae; bacteria; modelling; wastewater treatment; liquid depth; temperature |
| Commentaire | : | - |
| Tags | : | - |
| Fichier attaché | : | - |
| Citation | : |
Casagli F, Bernard O (2022) How Heat Transfer Indirectly Affects Performance of Algae-Bacteria Raceways. Microorganisms 10 | doi: 10.3390/microorganisms10081515
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