nary 1-OHP was quantified using reverse phase high-performance liquid chromatography (HPLC) using a modification of a previously described method  as described in Cavanagh and co-workers . The lower limit of detection was 0.23 nmol/L. Hydroxypyrene concentrations were corrected for urinary creatinine to account for hydration status and expressed as μmol 1-OHP/mol creatinine.
Exhaled breath condensate (EBC) collection
Exhaled breath condensate (EBC) was collected using the RTube™ system (Respiratory Research Inc, Charlottesville, USA), using an aluminium cooling tube. The aluminium cooling tube was stored at -20°C for at least 24 hours prior to collection. EBC was collected for ten minutes on each sampling occasion, after rinsing the mouth to reduce saliva contamination. Approximately 2 ml of condensate was collected from each student at each collection.
EBC pH was immediately measured by applying approximately 30 μl of EBC to a pre-calibrated Shindengen ISFET pH meter (model KS701). EBC was not de-gassed prior to pH measurement.
EBC hydrogen peroxide
H2O2 was measured in EBC samples using fluorometry with 4-hydroxyphenylacetic acid . Briefly, following the H2O2-dependent conversion of 4-HPAA to the dimer 2,2'-dihydroxybiphenyl-5,5'-diacetate, the fluorescence of each sample was quantified within four hours using a Hitachi F4500 Fluorescence Spectrophotometer (excitation 295 nm, emission 405 nm; slit width 5 nm ex/10 nm em; PMT voltage 700 V). Linear regression analysis allowed the estimation of the concentration of H2O2 in samples based upon a corresponding standard curve. More details of the H2O2 assay as used in our laboratory, including validation and optimisation can be found in Brooks and co-workers . The limit of detection of the assay used for these experiments was 3.4 nM H2O2.
Statistics and sample size
For seasonal and event data comparisons of EBC pH, hydrogen peroxide, and 1-OHP concentrations were compared using the non-parametric Friedman's test and Wilcoxon-signed rank tests as appropriate to allow for repeated observations on individuals and due to the extreme non-normality of these measures. Readings below the limit of detection for any assay were arbitrarily assigned a value corresponding to 50% of the limit of detection to avoid division by zero in any subsequent calculation. Longitudinal data was cleaned to exclude spurious or physiologically impossible data points by an a priori defined protocol. Peak flow and FEV1 data for each student was expressed as a Z-score relative to the student's mean score over the period of the study. Longitudinal data analysis exploring bivariate association between lung function (Z-scores of PEFR or FEV1) or symptom data and pooled air pollution measures (both indoor and outdoor) and climate related measures were conducted using the non-parametric Spearman's correlation coefficient. The air pollution measures were lagged daily out to seven days and correlated with lung function and symptom scores. In this manner the potential for any lagged effect of air pollution on these measures was analysed. Variables showing some association (p < 0.15) with lung function or symptom data from these analyses were then entered into a mixed-model linear regression analysis which included the daily use of a reliever as a covariate to confirm the independent association with lung function or symptoms. These analyses were undertaken for the dataset as a whole and repeated separately for asthmatic and non-asthmatic students.
In addition, mean levels of each of the longitudinal outcome variables for each student were calculated within moderate/high (24 hour average> 20 μm/m3 outdoor) pollution days and low pollution days. These levels were compared using Mann-Whitney U tests. Longitudinal data analysis exploring bivariate association between lung function (Z-scores of PEFR or FEV1) and pooled air pollution measures on moderate/high pollution (24 hour average> 20 μm/m3 outdoor) days alone were then conducted using the non-parametric Spearman's correlation coefficient.
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