From measures to models: an evaluation of air pollution exposure assessment for epidemiological studies of pregnant women.

OBJECTIVES: To evaluate exposure estimation methods such as spatially resolved land-use regression models and ambient monitoring data in the context of epidemiological studies of the impact of air pollution on pregnancy outcomes. METHODS: The study measured personal 48 h exposures (NO, NO(2), PM(2.5) mass and absorbance) and mobility (time activity and GPS) for 62 pregnant women during 2005-2006 in Vancouver, Canada, one to three times during pregnancy. Measurements were compared to modelled (using land-use regression and interpolation of ambient monitors) outdoor concentrations at subjects' home and work locations. RESULTS: Personal NO and absorbance (ABS) measurements were moderately correlated (NO: r = 0.54, ABS: r = 0.29) with monitor interpolations and explained primarily within-subject (temporal) variability. Land-use regression estimates including work location improved correlations for NO over those based on home postal code (for NO: r = 0.49 changed to NO: r = 0.55) and explained more between-subject variance (4-20%); limiting to a subset of samples (n = 61) when subjects spent >65% time at home also improved correlations (NO: r = 0.72). Limitations of the GPS equipment precluded assessment of including complete GPS-based mobility information. CONCLUSIONS: The study found moderate agreement between short-term personal measurements and estimates of ambient air pollution at home based on interpolation of ambient monitors and land-use regression. These results support the use of land-use regression models in epidemiological studies, as the ability of such models to characterise high resolution spatial variability is "reflected" in personal exposure measurements, especially when mobility is characterised.

Characterization of humus microbial communities in adjacent forest types that differ in nitrogen availability.

To address the link between soil microbial community composition and soil processes, we investigated the microbial communities in forest floors of two forest types that differ substantially in nitrogen availability. Cedar-hemlock (CH) and hemlock-amabilis fir (HA) forests are both common on northern Vancouver Island, B.C., occurring adjacently across the landscape. CH forest floors have low nitrogen availability and HA high nitrogen availability. Total microbial biomass was assessed using chloroform fumigation-extraction and community composition was assessed using several cultivation-independent approaches: denaturing gradient gel electrophoresis (DGGE) of the bacterial communities, ribosomal intergenic spacer analysis (RISA) of the bacterial and fungal communities, and phospholipid fatty acid (PLFA) profiles of the whole microbial community. We did not detect differences in the bacterial communities of each forest type using DGGE and RISA, but differences in the fungal communities were detected using RISA. PLFA analysis detected subtle differences in overall composition of the microbial community between the forest types, as well as in particular groups of organisms. Fungal PLFAs were more abundant in the nitrogen-poor CH forests. Bacteria were proportionally more abundant in HA forests than CH in the lower humus layer, and Gram-positive bacteria were proportionally more abundant in HA forests irrespective of layer. Bacterial and fungal communities were distinct in the F, upper humus, and lower humus layers of the forest floor and total biomass decreased in deeper layers. These results indicate that there are distinct patterns in forest floor microbial community composition at the landscape scale, which may be important for understanding nutrient availability to forest vegetation.