Biomedical subjects

Junxiang Luo

Publications and source records attributed to Junxiang Luo.

3 recordsLinked to original sources

PubMed2006

Estimating sampling frequency in pollen exposure assessment over time.

A time series model was fitted to the pollen concentration data collected in the Greater Cincinnati area for the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). A traditional time series analysis and temporal variogram approach were applied to the regularly spaced databases (collected in 2003) and irregularly spaced ones (collected in 2002), respectively. The aim was to evaluate the effect of the sampling frequency on the sampling precision in terms of inverse of standard error of the overall level of mean value across time. The presence of high autocorrelation in the data was confirmed and indicated some degree of temporal redundancy in the pollen concentration data. Therefore, it was suggested that sampling frequency could be reduced from once a day to once every several days without a major loss of sampling precision of the overall mean over time. Considering the trade-offs between sampling frequency and the possibility of sampling bias increasing with larger sampling interval, we recommend that the sampling interval should take values from 3 to 5 days for the pollen monitoring program, if the goal is to track the long-term average.

Air Pollution↗

PubMed2005

Sampling over time: developing a cost effective and precise exposure assessment program.

Studies requiring ambient exposure assessments invariably ask: How often should measurements be taken? Answer to such questions is dictated by budgetary considerations as well as spatial and temporal variability in the data. For example, do we obtain measurements during all seasons, all months within seasons, weeks within months and days within weeks? On one hand, we can obtain a one-time snapshot sample and regard it as representing the "true" mean exposure. On the other hand, we may obtain a large number of measurements over time and then average these in order to represent this "true" mean exposure. The former estimate is the least expensive but may also be the least precise while the latter, may be very precise but prohibitively costly. In this paper, we demonstrate how a pilot study can be undertaken with a potentially promising and feasible sampling plan for the full-scale study. By applying the statistical methodology of variance component analysis (VCA) to the pilot study data and exploiting mathematical relationship between the variance of the overall mean exposure and posited variance components, we can develop a sampling design with decreased sampling costs and/or increased precision of the mean exposure. Our approach was applied to determine sampling design choices for an on-going study that aimed at assessing ambient particulate matter exposure. We conclude that a pilot study followed by the VCA analysis may often lead to sampling design choices that offer considerable cost savings and, at the same time, promise to provide relatively precise estimates of the mean exposure for the subsequent full-scale study.

Analysis of Variance↗

PubMed2004

Evaluation and optimization of an urban PM2.5 monitoring network.

The objective of this study was to evaluate the PM(2.5) monitoring network established in the Greater Cincinnati and Northern Kentucky metropolitan area for measuring the 24 h integrated PM(2.5) concentration, as well as-at selected sites-hourly PM(2.5) concentration and 24 h integrated PM(2.5) speciation. The data collected during three years at 13 measurement sites were analyzed for spatial and temporal variations. It was found that both daily and hourly concentrations of PM(2.5) have low spatial variation due to a regional influence of secondary ammonium sulfate. In contrast, the trace element concentrations had high spatial variation. Seasonal variation accounted for most of the total temporal variation (60%), while yearly, monthly, weekly and daily variations were lower. The variance components and cluster analyses were applied to optimize the number of sites for measuring the 24 h PM(2.5) concentration. It was found that the 13-site network may be optimized by reducing the number of sites to 8, which would result in a relative precision reduction of 9% and a relative cost reduction of 36%. At the same time, the data suggest that the spatial resolution of speciation monitors and real-time PM(2.5) mass monitors should be increased to better represent spatial and temporal variations of the markers of local air pollution sources.

Air Pollutants↗