In this paper, we explore the affective contents of Impressionism paintings. While past analysis of artworks concentrated on artistic concept annotation, like styles and periods, a more perceptual aspect is to investigate the emotions artists projected into. We propose affective space to fuse all affective factors from features. Since the combination of colors is more sensitive and intuitive to emotions, a meta-level feature, color harmony, is introduced to bridge the semantic gaps. By considering the correlation relationships among features and emotions, the affective space is explored through multiple-type latent semantic analysis. Experimental results show the effectiveness of harmonic feature and affective space via multi-label emotion annotation. Some potential applications are demonstrated based on affective space as well, including painting emotionalization and emotion-based slideshow system.