Suchergebnisse

In environmental monitoring, the ability to obtain high-quality data across space and time is often limited by the cost of purchasing, deploying and maintaining a large collection of equipment, and the employment of personnel to perform these tasks. An ideal design for a monitoring campaign would be dense enough in time to capture short-range variation at each site, long enough in time to examine trends at each site and across all sites, and dense enough in space to allow modelling of the relationship between the means at each of the sites. This paper outlines a methodology for semiparametric spatiotemporal modelling of data that is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected as part of the International Laboratory for Air Quality and Health's Ultrafine Particles from Traffic Emissions and Children's Health (UPTECH) project. The panel design comprises two weeks of continuous measurements taken at each of a number of government primary schools in the Brisbane Metropolitan Area, with each school visited sequentially. The school data are augmented by data from long-term monitoring stations at three locations in Brisbane, Australia. The temporal part of the model explains daily and weekly cycles in PNC at the schools. The temporal variation is modelled hierarchically with a penalised random walk term common to all sites and a similar term accounting for the remaining temporal trend at each site. The modelling of temporal trends requires an acknowledgement that the observations are correlated rather than independent. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school-to-school variation in mean PNC at each school and within each school ground. The spatial term in the model is derived from a stochastic partial differential equation and approximates a Gaussian process with a Gaussian Markov Random field. Fitting the model helps describe spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites, which can be used to estimate the exposure of school children to ultrafine particles. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA.

BACKGROUND: There is a significant lack of scientific knowledge on population exposure to ultrafine particles (UFP) in China to date. This paper quantifies and characterises school children's personal UFP exposure and exposure intensity against their indoor and outdoor activities during a school day (home, school and commuting) in the city of Heshan within the Pearl River Delta (PRD) region, southern China. METHODS: Time-series of UFP number concentrations and average size were measured over 24 h for 24 children (9-13 years old), using personal monitors over two weeks in April 2016. Time-activity diaries and a questionnaire on the general home environment and potential sources of particles at home were also collected for each participating child. The analysis included concurrently measured size distributions of ambient UFP at a nearby fixed reference site (Heshan Supersite). RESULTS: Hourly average UFP concentrations exhibited three peaks in the morning, midday and evening. Time spent indoors at home was found to have the highest average exposure (1.26 × 104 cm-3 during sleeping) and exposure intensity (2.41). While there is always infiltration of outdoor particles indoors (from nearby traffic and general urban background sources), indoor exposure at home was significantly higher than outdoor exposure. Based on the collected questionnaire data, this was considered to be driven predominantly by adults smoking and the use of mosquito repellent incense during the night. Outdoor activities at school were associated with the lowest average exposure (6.87 × 102 cm-3) and exposure intensity (0.52). CONCLUSION: Despite the small sample size, this study characterised, for the first time, children's personal UFP exposure in a city downwind of major pollution sources of the PRD region in China. Particularly, the results highlighted the impact of smoking at home on children's exposure. While the study could not apportion the specific contributions of second hand-smoking and mosquito coil burning, considering the prevalence of smokers among the parents who smoke at home, smoking is a very significant factor. Exposure to second-hand smoke is avoidable, and these findings point out to the crucial role of government authorities and public health educators in engaging with the community on the role of air quality on health, and the severity of the impact of second-hand smoke on children's health.