This study aimed at establishing the relationship between annoyance scores and modelled air pollution in "Chemical Valley", Sarnia, Ontario (Canada). Annoyance scores were taken from a community health survey (N = 774); and respondents' exposure to nitrogen dioxide (NO(2)) and sulphur dioxide (SO(2)) were estimated using land use regression (LUR) models. The associations were examined by univariate analysis while multivariate logistic regression was used to examine the determinants of odour annoyance. The results showed that odour annoyance was significantly correlated to modelled pollutants at the individual (NO(2), r = 0.15; SO(2), r = 0.13) and census tract (NO(2), r = 0.56; SO(2), r = 0.67) levels. The exposure-response relationships show that residents of Sarnia react to very low pollution concentrations levels even if they are within the Ontario ambient air quality criteria. The study found that exposure to high NO(2) and SO(2) concentrations, gender, and perception of health effects were significant determinants of individual odour annoyance reporting. The observed association between odour annoyance and modelled ambient pollution suggest that individual and census tract level annoyance scores may serve as proxies for air quality in exposed communities because they capture the within area spatial variability of pollution. However, questionnaire-based odour annoyance scores need to be validated longitudinally and across different scales if they are to be adopted for use at the national level.