Aquatic organisms are exposed to several organic compounds including biocides. These compounds are widely used, for instance as disinfectants, in antifouling paints, or as material preservatives. Biocides can originate from different sources such as agricultural, urban and industrial runoff. Their presence in the aquatic environment is cause of concern, as they can be highly toxic, not only to target, but also to non-target organisms. Each type of biocide has specific effects according to its mode of action (MoA). Additionally, they may exist in complex mixtures and affect organisms through combined toxicity. This study intended to characterise the single and combined effects of five environmentally relevant biocides, aclonifen, bifenox, dichlofluanid, metribuzin and triclosan on the unicellular algae Chlamydomonas reinhardtii. Biocide toxicity was examined by analysing their effects in the freshwater microalgae through three different toxic endpoints: inhibition of growth, Photosystem II (PSII) efficiency and formation of Reactive Oxygen Species (ROS). The combined toxicity assessment was conducted using the concentration (CA) and independent action (IA) prediction models to analyse if the compounds in a mixture caused toxicity by similar or dissimilar MoA, respectively. For the compounds/mixtures which MoA and adverse outcomes were understood, preliminary Adverse Outcome Pathways (AOPs) were developed to collect, organize and evaluate all the relevant information. The results were also used to assess the potential environmental risk of the biocides to algae when present as single chemicals and in mixtures, by using a Risk Quotients (RQs) and Toxic Units (TUs) approach. The growth inhibition test allowed verifying the general toxicity of each biocide and of the mixture with all the compounds. The order of toxic potency was: bifenox> metribuzin> dichlofluanid> aclonifen> triclosan. The IA model best predicted the mixture involving all the biocides at 48 h and 72 h, thus suggesting that the compounds had different MoA. A potential antagonism was observed particularly at 24 h for low to median effect levels, possible due to the fact that the different compounds required longer time to propagate the effects to the apical level (growth). In this study, metribuzin, dichlofluanid, bifenox and triclosan showed a potential risk to algae, although the risk by dichlofluanid might be overestimated due to lack of adequate exposure information. The mixture with all the compounds presented a potential environmental risk for algae. From the 5 tested compounds (aclonifen, bifenox, dichlofluanid, metribuzin and triclosan), only aclonifen and metribuzin showed effects on the PSII efficiency, with the first being the most toxic. This effect was correlated with the inhibition of growth, showing that the inhibition of PSII was the main toxic MoA for these compounds. The effects of the binary mixture were best described by the IA model, consistent with these herbicides displaying additive effects by dissimilar MoA. For the growth, IA best fitted the data in the beginning of exposure, whereas the data was best predicted by CA at longer exposures. A concentration-dependent deviation from additivity, interpreted as synergy, was observed for medium to high concentrations of this mixture. While the single compounds did not present a risk at environmentally relevant concentrations, the effects of the binary mixture were higher than expected and a potential environmental risk was identified. The formation of ROS was a potential MoA for aclonifen and metribuzin; therefore, a high-throughput assay for ROS detection was used to analyse the 5 compounds (aclonifen, bifenox, dichlofluanid, metribuzin and triclosan). Among these, only aclonifen, metribuzin and bifenox induced ROS in a significant and concentrationdependent manner. The combined effects of the three herbicides were also studied in binary and ternary mixtures. The best predictions were achieved by the CA model when testing the ternary mixture and the binary mixture of aclonifen and bifenox at low to median effect levels, whereas synergism was observed at higher effects levels. The binary mixture of aclonifen and metribuzin was best predicted by the IA model, while the binary mixture of bifenox and metribuzin was equally well predicted by the two models. The combination of ROS formation and inhibition of photosynthesis was proposed to explain the observed combined effects. The present work demonstrated that C. reinhardtii is a suitable model organism to evaluate the toxicity of biocides and their mixtures. The applied methods were able to determine both sublethal and lethal effects of the studied compounds and provided a better understanding on their MoA. The CA and IA models provided good predictions for the observed effects of the mixtures of biocides with similar and dissimilar MoA. The cumulative risk assessment using TUs and RQs based approaches were shown to be an applicable way for predicting the risk of the biocides mixtures to algae. The present work has contributed to advance the field of ecotoxicology by providing a better understanding of the MoA of commonly used biocides, deciphering the combined toxicity of simple mixtures of these and identifying whether these biocides and their mixtures represent a risk to algae under ecological relevant exposure scenarios. Given the limited data available on the studied biocides, the knowledge gathered in the present work contributed to the characterization of their MoA and ecotoxicological effects in C. reinhardtii. This information can be integrated to further develop risk assessment tools for a better understanding and protection of the aquatic environment.