Abstract: Phenolic compounds can be found everywhere in our daily lives but exhibit high toxicity, low (bio)degradability and hormone-disrupting effects when they are released in the environment. It is for this reason imperative to develop detection strategies for these pollutants. A promising approach involves the use of a photoelectrochemical (PEC) sensor. In this sensor, a photosensitiser (PS) type II, which generates 1O2 under illumination, is used to oxidise phenolic compounds present in the sample. The oxidised phenols are reduced at the electrode surface leading to the generation of an electrocatalytic redox cycle. In this thesis, an in-depth understanding, through the identification of the reactive oxygen species (ROS) in the PEC sensing mechanism, is obtained. The detection strategy is optimised by choosing the PS with the highest 1O2 production and by optimising the detection parameters so that the PEC sensor can be successfully applied for the detection of phenols in industrial samples. First, it was determined that the use of highly fluorinated zinc phthalocyanine derivatives, F52PcZn and F64PcZn, as photocatalysts was optimal for the sensing of phenol due to their high 1O2 production and improved single-site isolation. However, next to 1O2, it was shown that the ROS O2•- and H2O2 were also generated in the PEC sensor. Their contribution to the photocurrent response was studied by rotating disk electrode measurements in function of the pH and applied potential. After this, the PEC detection strategy was optimised in terms of pH and applied potential for the detection of doxycycline, cefadroxil, and phenol. It was found that the use of alkaline pH-levels led to nmol L-1-level detection limits. The combination with square wave voltammetry (SWV) was, also, proposed to allow the quantification and identification of phenolic compounds in a specific sample. At last, the developed PEC and SWV sensors were applied for the measurement of phenolic compounds in industrial water samples. The PEC sensor could follow the decrease of the phenolic concentration throughout the wastewater treatment process while the SWV sensor provided the electrochemical fingerprints of these samples. The thesis concluded that the use of the PEC sensor was advantageous in the measurement of lower concentrated phenolic samples due to its high sensitivity and fast measurement time in comparison to commercial test kits.