Construction workers' valence, which is an important dimension of emotions by representing intrinsic attractiveness and aversiveness, significantly influences their awareness, attention, motivation, etc. Recently, a wearable electroencephalogram (EEG) device has opened a door to measure and understand construction workers' valence levels at the workplace. However, acquiring high quality EEG signals is very difficult at the field due to signal artefacts prevalent in construction sites. In this regard, a signal processing framework was previously developed by the authors to remove the most common artefacts recorded in the EEG signals. In this paper, we further demonstrate how construction workers' valence can be identified by applying this framework. Significant differences in the valence levels were captured while subjects were working in various real work conditions (e.g., working at ground level, top of the ladder, and in confined space). The results show the feasibility of using a wearable EEG device to monitor a worker's valence.