Abstract

The first objective of this study is to assess the predictive capability of the ALBA (ALgae-BActeria) model for a pilot-scale (3.8 m2) high-rate algae-bacteria pond treating agricultural digestate. The model, previously calibrated and validated on a one-year data set from a demonstrative-scale raceway (56 m2), successfully predicted data from a six-month monitoring campaign with a different wastewater (urban wastewater) under different climatic conditions. Without changing any parameter value from the previous calibration, the model accurately predicted both online monitored variables (dissolved oxygen, pH, temperature) and off-line measurements (nitrogen compounds, algal biomass, total and volatile suspended solids, chemical oxygen demand). Supported by the universal character of the model, different scenarios under variable weather conditions were tested, to investigate the effect of key operating parameters (hydraulic retention time, pH regulation, kLa) on algae biomass productivity and nutrient removal efficiency. Surprisingly, despite pH regulation, a strong limitation for inorganic carbon was found to hinder the process efficiency and to generate conditions that are favorable for N2O emission. The standard operating parameters have a limited effect on this limitation, and alkalinity turns out to be the main driver of inorganic carbon availability. This investigation offers new insights in algae-bacteria processes and paves the way for the identification of optimal operational strategies.

Highlights

  • High Rate Alga-Bacterial Pond (HRABP) is a promising technology for wastewater treatment.[1,2] The process overcomes some critical aspects of conventional biological processes by reducing the oxygen demand and opening new routes for nitrogen and phosphorus recovery

  • The volumetric mass transfer coefficient of the HRABP was experimentally determined during abiotic tests, resulting in a final value of 30.5 d−1 which is very close to 34 d−1 estimated for the 56-m2 pond on the basis of which the model was calibrated.[23]

  • The model quality score confirmed the good predicting ability of the model, considering that the model is said to be accurate for TIC values below 0.3.41,52 For all the tested seasons, experimental data were well simulated

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Summary

Introduction

High Rate Alga-Bacterial Pond (HRABP) is a promising technology for wastewater treatment.[1,2] The process overcomes some critical aspects of conventional biological processes by reducing the oxygen demand and opening new routes for nitrogen and phosphorus recovery. The combination between algae and nitrifying bacteria has some drawbacks, inducing negative interactions like the competition for CO2 or micronutrients[12] or the inhibition of bacterial growth when the photosynthesis increases the pH level.[13] These complex interplays make the overall dynamics of nitrifiers/algae especially challenging to understand and predict, as well as highly dependent on the composition of the wastewater to be treated and on the operation parameters.[14] The HRABP efficiency is seasonal-dependent, and low temperature and solar radiation conditions can seriously affect the overall microalgae growth and its synergy with bacteria,[15] potentially leading to the collapse of the system.[16] the overall dynamics of the algae/bacteria community can affect atmospheric emissions, in terms of free ammonia stripping and by modulating the conditions promoting N2O emission.[17−19]

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