Laurent Lardon

Life-cycle assessment of microalgae culture coupled to biogas production.

Due to resource depletion and climate change, lipid-based algal biofuel has been pointed out as an interesting alternative because of the high productivity of algae per hectare and per year and its ability to recycle CO(2) from flue gas. Another option for taking advantage of the energy content of the microalgae is to directly carry out anaerobic digestion of raw algae in order to produce methane and recycle nutrients (N, P and K). In this study, a life-cycle assessment (LCA) of biogas production from the microalgae Chlorella vulgaris is performed and the results are compared to algal biodiesel and to first generation biodiesels. These results suggest that the impacts generated by the production of methane from microalgae are strongly correlated with the electric consumption. Progresses can be achieved by decreasing the mixing costs and circulation between different production steps, or by improving the efficiency of the anaerobic process under controlled conditions. This new bioenergy generating process strongly competes with others biofuel productions.

Experimental study on a coupled process of production and anaerobic digestion of Chlorella vulgaris

The main goal of this present study is to investigate the feasibility of coupling algae production (Chlorella vulgaris) to an anaerobic digestion unit. An intermediate settling device was integrated in order to adapt the feed-flow concentration and the flow rate. Digestion of C. vulgaris was studied under 16 and 28 days hydraulic retention times (HRT), with a corresponding organic loading rate of 1g(COD)L(-1). Increasing the HRT achieved 51% COD removal with a methane production measured at 240 mL g(VSS)(-1). Performing different HRTs and dynamic monitoring during degradation highlighted differential hydrolysis of microalgae compartments. However, 50% of the biomass did not undergo anaerobic digestion, even under long retention times. This points out the interest for further studies on pre-treatment performances and more generally speaking on the need for intensifying microalgae biomass digestion.

Modeling anaerobic digestion of microalgae using ADM1

The coupling between a microalgal pond and an anaerobic digester is a promising alternative for sustainable energy production by transforming carbon dioxide into methane using solar energy. In this paper, we demonstrate the ability of the original ADM1 model and a modified version (based on Contois kinetics for the hydrolysis steps) to represent microalgae anaerobic digestion. Simulations were compared to experimental data of an anaerobic digester fed with Chlorella vulgaris. The modified ADM1 fits adequately the data for the considered 140 day experiment encompassing a variety of influent load and flow rates. It turns out to be a reliable predictive tool for optimising the coupling of microalgae with anaerobic digestion processes.

A new dynamic model for bioavailability and cometabolism of micropollutants during anaerobic digestion.

Organic micropollutants (OMPs) are present in wastewater and sludge. Their possible impact to the environment contributes to their increasing scientific and social interest. Anaerobic digestion has been shown as a potential biological process for removal of these compounds. An accurate description of OMP distribution in the environmental system can be used to better understand which compartment is used for degradation and to improve their depletion in conventional wastewater treatment technologies. In this work, we proposed a dynamical model with a four-compartment distribution to describe the Polycyclic Aromatic Hydrocarbons (PAHs) fate during anaerobic digestion. The model is calibrated and validated using experimental data obtained from two continuous reactors fed with primary and secondary sludge operated under mesophilic conditions. A non-linear least square method was used to optimize the model parameters. The resulted model is in accordance with the experimental data. The PAH biodegradation rate is well modeled when considering the aqueous fraction (including free and sorbed to dissolved/colloidal matter PAHs) as the bioavailable compartment. It was also demonstrated in the simulations that the PAHs biodegradation is linked to a mechanism of cometabolism. The model proposed is potentially useful to better understand the micropollutant distribution, predict the fate of PAHs under anaerobic condition and help to optimize the operation process for their depletion.

Life-Cycle Assessment of Microalgal-Based Biofuels

Abstract Fossil-fuel depletion and attempts at global-warming mitigation have motivated the development of biofuels. Several feedstock and transformation pathways into biofuel have been proposed as an alternative to the usual fuels. Recently, microalgae have attracted a good deal of attention because of the promise of reduced competition with food crops and lowered environmental impacts. Over the last years, several life-cycle assessments (LCAs) have been realized to evaluate the energy benefit and potential global-warming reduction of biofuel and bioenergy produced from microalgae. This chapter presents a bibliographic review of 15 LCAs of microalgae production and/or transformation into biofuel. These studies often differ by the perimeter of the study, the functional unit, and the production technologies or characteristics. Methods for environmental impact assessment and the energy balance computation also diverge. This review aims to identify the main options and variations among LCAs and concludes with some recommendations and guidelines to improve the contribution of an LCA and to facilitate comparisons among studies.

Three-Reaction Model for the Anaerobic Digestion of Microalgae

Coupling an anaerobic digester to a microalgal culture has received increasing attention as an alternative process for combined bioenergy production and depollution. In this article, a dynamic model for anaerobic digestion of microalgae is developed with the aim of improving the management of such a coupled system. This model describes the dynamics of inorganic nitrogen and volatile fatty acids since both can lead to inhibition and therefore process instability. Three reactions are considered: Two hydrolysis–acidogenesis steps in parallel for sugars/lipids and for proteins, followed by a methanogenesis step. The proposed model accurately reproduces experimental data for anaerobic digestion of the freshwater microalgae Chlorella vulgaris with an organic loading rate of 1 gCOD L−1 d−1. In particular, the three‐reaction pathway allows to adequately represent the observed decoupling between biogas production and nitrogen release. The reduced complexity of this model makes it suitable for developing advanced, model‐based control and monitoring strategies. Biotechnol. Bioeng. 2012; 109:415–425.

Time and Life Cycle Assessment: How to Take Time into Account in the Inventory Step?

Life cycle assessment is usually an assessment tool which only considers steady state processes: the temporal and spatial properties of extractions, usage and emissions are lost during the life cycle inventory step. This approach significantly reduces the environmental relevance of some results. As the development of dynamic impact methods is based on dynamic inventory data, it seems essential to develop a general methodology to achieve a temporal life cycle inventory. This study presents a method to select steps, in the whole network tree, for which dynamics have to be considered while the others are approximated by steady state representation. The selection procedure is based on the main contributors in term of impact. The approach is illustrated by the life cycle assessment of simplified rapeseed oil production as biofuel system.

A Dynamic Model for Anaerobic Digestion of Microalgae

Abstract The coupling between a microalgal pond and an anaerobic digester is a promising alternative for sustainable energy production by transforming carbon dioxide into methane (which is a biofuel). In this paper, a dynamic model for anaerobic digestion of microalgae is developed with the objective of helping in the coupled process management. This model includes the dynamics of ammonium and volatile fatty acids since both can lead to inhibition and process instability. Three reactions are considered: two hydrolysis-acetogenesis steps in parallel for the sugars-lipids and for the proteins, and a methanogenesis step. Simulation results were compared with experimental data for Chlorella vulgaris digestion. The model fits the data of the considered 140 day experiment.

Anaerobic Digestion of Microalgae: Identification for Optimization and Control

Abstract Coupling an anaerobic digester to a microalgal culture is currently considered one of the most promising avenues towards the production of renewable bioenergy, either in the form of biodiesel or biogas. Accurate mathematical models are crucial tools to assess the potential of such coupled biotechnological processes and help optimize their design, operation and control. This paper focuses on the compartment of anaerobic digestion of microalgae. Using experimental data for the anaerobic digestion of Chlorella vulgaris, a grey-box model is developed that allows good prediction capabilities and retains low complexity. The proposed methodology proceeds in two steps, namely a structural and a parametric identification steps. The fitted model is then used to conduct preliminary optimization for the production of biogas from Chlorella vulgaris. The results provide some insight into the potential for bioenergy production from the digestion of microalgae and, more generally, the coupled process.

The Use of Models to Account for the Variability of Agricultural Data

LCA outputs are often presented as point estimates measuring potential impacts although average impacts values may be misleading to rank different options, especially in the case of agricultural products. In an LCA study comparing different slurry application techniques, NH3 and N2O emissions have been estimated through two approaches, experimental data collected from the literature and mathematical simulations over different soil and climate conditions. Both approaches lead to similar ranges of emissions; however the simulation-based approach allows us to construct a probability distribution of emissions whereas the limited number of experimental studies leads only to the definition of a range of emissions. A better knowledge of the variability of emissions helps the practitioner to sort alternatives and to detect situations where they are not discernable. Moreover the knowledge of the distribution and of its most impacting sources of variability leads to the definition of more informative and significant typologies.