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The assessment of air pollution exposures in epidemiological studies does not always account for spatio-temporal variability of pollutants concentrations. In the case of odor studies, a common approach is to use yearly averaged odorant exposure estimates with low spatial resolution, which may not capture the spatio-temporal variability of emissions and therefore distort the epidemiological results. This study explores the use of different exposure assessment methods for time-variant ammonia exposures with high spatial resolution, in rural communities exposed to odors from agricultural and livestock farming activities. Exposure estimations were based on monthly ammonia concentrations from emission-dispersion models. Seven time-dependent residential NH 3 exposures variables were investigated: 1) Annual mean of NH 3 exposures; 2) Maximum annual NH 3 exposure; 3) Area under the exposure curve; 4) Peak area; 5) Peak-to-mean ratio; 6) Area above the baseline (annual mean of NH 3 exposures); and 7) Maximum positive slope of the exposure curve. We developed binomial and multinomial logistic regression models for frequency of odor perception and odor annoyance responses based on each temporal exposure variable. Odor responses estimates, goodness of fit and predictive abilities derived from each model were compared. All time-dependent NH 3 exposure variables, except peak-to-mean ratio, were positively associated with odor perception and odor annoyance, although the results differ considerably in terms of magnitude and precision. The best goodness of fit of the predictive binomial models was obtained when using maximum monthly NH 3 exposure as exposure assessment variable, both for odor perception and annoyance. The best predictive performance for odor perception was found when annual mean was used as exposure variable (accuracy = 71.82%, Cohen's Kappa = 0.298) whereas odor annoyance was better predicted when using peak area (accuracy = 68.07%, Cohen's Kappa = 0.290). Our study highlights the importance of taking temporal variability into account when investigating odor-related responses in non-urban residential areas.

Perceived air pollution, including environmental odor pollution, is known to be an environmental stressor that affects individuals' psychosocial health and well-being. However, very few studies have been able to quantify exposure-response associations based on individual-specific residential exposures to a proxy gas and to examine the mechanisms underlying these associations. In this study, individual-specific exposures in non-urban residential environments during 2005-2010 on a gas released from animal biodegradable wastes (ammonia, NH 3) were calculated by the Danish Eulerian long-range transport model and the local-scale transport deposition model. We used binomial and multinomial logistic regression and mediation analyses to examine the associations between average exposures and questionnaire-based data on psychosocial responses, after controlling for person-specific covariates. About 45% of the respondents were annoyed by residential odor pollution. Exposures were associated with annoyance (adjusted odds ratio [OR adj]=3.54, 95% confidence interval [CI]=2.33-5.39), health risk perception (OR adj=4.94; 95% CI=1.95-12.5) and behavioral interference (OR adj=3.28; 95% CI=1.77-6.11), for each unit increase in log e(NH 3 exposure). Annoyance was a strong mediator in exposure-behavior interference and exposure-health risk perception relationships (81% and 44% mediation, respectively). Health risk perception did not play a mediating role in exposure-annoyance or exposure-behavioral interference relationships. This is the first study to provide a quantitative estimation of the dose-response associations between ambient NH 3 exposures and psychosocial effects caused by odor pollution in non-urban residential outdoor environments. It further shows that these effects are both direct and mediated by other psychosocial responses. The results support the use of NH 3 as a proxy gas of air pollution from animal biodegradable wastes in epidemiologic studies.