The assessment of long-term effects of air pollution in humans relies on epidemiologic studies. A widely used design consists of cross-sectional or cohort studies in which ecologic assignment of exposure, based on a fixed-site ambient monitor, is employed. Although health outcome and usually a large number of covariates are measured in individuals, these studies are often called ecological. We will introduce the term semi-individual design for these studies. We review the major properties and limitations with regard to causal inference of truly ecologic studies, in which outcome, exposure, and covariates are available on an aggregate level only. Misclassification problems and issues related to confounding and model specification in truly ecologic studies limit etiologic inference to individuals. In contrast, the semi-individual study shares its methodological and inferential properties with typical individual-level study designs. The major caveat relates to the case where too few study areas, e.g., two or three, are used, which render control of aggregate level confounding impossible. The issue of exposure misclassification is of general concern in epidemiology and not an exclusive problem of the semi-individual design. In a multicenter setting, the semi-individual study is a valuable tool to approach long-term effects of air pollution. Knowledge about the error structure of the ecologically assigned exposure allows consideration of the impact of ecologically assigned exposure on effect estimation. Semi-individual studies, i.e., individual level air pollution studies with ecologic exposure assignment, more readily permit valid inference to individuals and should not be labeled as ecologic studies.