APM Inside Classrooms
Air particulate sources and activity inside school classrooms
Pilot study was undertaken to investigate the air quality in two primary school classrooms (ages 5 –9) over a three week period, during August 2013.PM10was monitored and sampled (hourly, 24/7) in two classrooms and outside of the Palmerston North School, New Zealand.
Children are more affected by air pollution than other groups within the population(e.g. Kulkarni and Grigg 2008, Dockerty and Pope 1994). As there is a lack of research on the healthiness of schools and early childhood centres, this particulate matter (PM) monitoring study is an essential starting point for documenting the existing condition of the environments where children spend a large proportion of their lives.
So far, PM monitoring has been primarily focused on outdoor locations through ambient air quality monitoring networks. In winter 2010, a wintertime monitoring study outside two NZ schools found that PM10 largely originated from wood burning and traffic emissions (Ancelet et.al.2012). However, there is no data on the impact of the outdoor PM10 concentrations on the indoor environment.
A pilot study was undertaken to investigate the air quality in two primary school classrooms (ages 5 –9) over a three-week period, during August 2013. PM10 was monitored and sampled (hourly, 24/7) in two classrooms and outside of the Palmerston North School, New Zealand. One of the classrooms chosen was fitted with a positive pressure ventilation system (solar collector) to determine its effect on air quality within the classroom. Each classroom was equipped with a sampler monitoring PM2.5 and PM10-2.5 on an hourly time-scale. Elemental composition of the particulate matter was measured using Ion Beam Analysis (IBA) (Trompetter et. al.2005). Multivariate receptor modelling techniques were used to determine the PM sources and their hourly contributions. Results showed that significantly higher concentrations occurred within both classrooms during school hours 9:00–16:00, as shown in Figure 1. It is also apparent from the diurnal plot that on average 1.5 times higher concentrations occurred in the unventilated classroom. The source apportionment results showed some infiltration of marine and traffic PM however the increased PM in the classrooms was predominantly from crustal sources, most likely related to re-entrained dust due to activities within the classrooms. More detailed results and discussion are presented within the paper.
Figure 1.Weekday diurnal plot of PM10 concentrations in the unventilated classroom, ventilated classroom and outdoors.
2014 International Aerosol Conference Aug. 28 – Sep. 2, 2014 @BEXCO, Busan, Korea
WilliamTrompetter1*, Mikael Boulic2, Travis Ancelet1, Juan Carlos Garcia Ramirez2, Perry Davy1 and Robyn Phipps2
1GNS Science, Lower Hutt, New Zealand 2Massey University, Palmerston North, New Zealand
Contacting author: William (Bill) Trompetter, air quality scientist
Components of this work were supported by the Housing, Heating and Healthy Research Group/He Kainga Oranga, and GNS Science Direct Core Funding. We also thank C. Purcell of GNS Science for technical assistance with accelerator operation.
Ancelet, T., Davy, P.K., Mitchell, T., Trompetter, W.J., Markwitz, A., Weatherburn, D.C.,(2012) Identification of Particulate Matter Sources on an hourly time scale in a wood burning community. Environ. Sci. Technol., 46, 4767-4774.
Dockery D.W., Pope C.A.(1994) Acute Respiratory Effects of Particulate Air Pollution, Annual Review of Public Health, 15 107-132.
Kulkarni, N.,Grigg, J., (2008)Effect of air pollution on children, Paediatrics and Child Health,18(5)238–243.
Trompetter W.J. Markwitz A. and Davy P., (2005) Air Particulate Research Capability at the New Zealand Ion Beam Analysis
Facility using PIXE and IBA Techniques, International Journal of PIXE,15(3-4)249 –255.