This means that during regular atmospheric mixing conditions (unstable conditions) no pollutant accumulation is possible: on the contrary, during stable conditions (i.e., when pollutant dispersion is not favored) smog photochemical episodes can occur.
Unstable results for the gaseous pollutants highlight the difficulty in determining appropriate methods for controlling for meteorology in air pollution epidemiologic models, particularly when analyzing covarying pollutants that are highly driven by meteorologic processes.
This method can yield unstable parameter estimates when the pollutants involved suffer high intercorrelation; therefore, traditional approaches to dealing with multicollinearity, such as principal component analysis (PCA), have been promoted in this context.
While the pollutant tends to be well mixed in the street canyons in neutral and unstable conditions, a mildly improved pollutant removal in unstable conditions is observed because of the enhanced roof-level buoyancy-driven turbulence.
PCA avoids the problem of unstable parameter estimates sometimes obtained in multiple pollutant studies because of the high correlations between pollutants.
Cohort specific hazard ratios for incidence of acute coronary events (myocardial infarction and unstable angina) per fixed increments of the pollutants with adjustment for sociodemographic and lifestyle risk factors, and pooled random effects meta-analytic hazard ratios.
A noted problem with the standard model is that the pollutant-effect parameter estimates may be unstable (i.e., have unduly high covariance structure) because of high correlation among pollutants (Burnett et al. 2003).
In two-pollutant models including indoor and outdoor measures simultaneously, only associations of eNO with indoor metrics remained for PM10 2.5 and PM2.5 (two-pollutant models for BC were unstable; data not shown).
The associations between PM2.5 and all three outcomes were stronger when adjusted for PM2.5 10, but estimates from these models were unstable because of the high correlation between the two pollutants.
The disadvantage of the weighted methods is that they do not avoid the problem of unstable parameter estimates that can arise because of the positive correlation among pollutants.
