Journals / Atmospheric Pollution Research / 2019 / Cilt: 10 - Sayı: 2

Sources of indoor air pollution at a New Zealand urban primary school; a case study

Pages
435–444
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Thefindings from this study will be applicable to many other schools and public buildings with high foot traffic.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Children are particularly vulnerable to the health effects of air pollution and as they spend a large proportion oftime at school, this is an important environment for children's exposure to air pollution.
📊
Key Findings & Data:This study analysed the concentration and sources of air pollution at an urban primary school (5–11years) in Wellington, the capital of New Zealand.
💡
Conclusion & Impact:Thefindings from this study will be applicable to many other schools and public buildings with high foot traffic.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

Children are particularly vulnerable to the health effects of air pollution and as they spend a large proportion oftime at school, this is an important environment for children's exposure to air pollution. Understanding thefactors that influence indoor air quality in schools is critical for the assessment and control of indoor air pollution. This study analysed the concentration and sources of air pollution at an urban primary school (5–11years) in Wellington, the capital of New Zealand. Over a three-week period during spring, indoor measures ofparticulate matter ($PM_{2.5}$, $PM_{10}$), temperature, humidity, carbon dioxide ($CO_2$) and nitrogen dioxide ($NO_2$) weretaken and hourly air particulate matter samples ($PM_{2.5}$, $PM_{10}$) were collected inside and outside for elementalspeciation analysis. Indoor PM10 concentrations during the school day were significantly (p < 0.001) higherthan outdoor concentrations 30.1 (range 10.0–75.0, SD 1.9) μg $m^{-3}$ c.f. 8.9 (range < 1.0–35.0, SD 6.8) μg $m^{-3}$.Elemental analysis and receptor modelling of PM samples showed that indoor PM10 was primarily composed ofcrustal matter (soil) elements, possibly brought in on children's footwear. The primary driver of indoor $PM_{2.5}$,was from the infiltration of outdoor pollutants inside, with by-products of motor vehicle emissions the maincontributor to indoor $PM_{2.5}$, There is a need for mitigation strategies to reduce exposure to indoor air pollution atschool, such as improved cleaning methods, reducing the use of carpet in schools and improved ventilation. Thefindings from this study will be applicable to many other schools and public buildings with high foot traffic.

🔖

Cite This Article

BENNET, J., DAVY, P., TROMPETTER, B., WANG, Y. J., PİERSE, N., BOULIC, M., PHIPPS, R., CHAPMAN, P. H. (2019). Sources of indoor air pollution at a New Zealand urban primary school; a case study. Atmospheric Pollution Research, Cilt: 10 - Sayı: 2, 435–444. https://ajindex.com/articles/351324

References (11)

  1. Almeida, S.M., Canha, N., Silva, A., do Carmo Freitas, M., Pegas, P., Alves, C., Evtyungina, M., Pio, C.A., 2011. Children exposure to atmospheric particles in indoor of Lisbon primary schools. Atmos. Environ. 45 (40), 7594–7599. https://doi.org/10.1016/j. atmosenv.2010.11.052. American Society of Heating and Air Conditioning Engineers, 1989. Ventilation for Acceptable Air Quality. ASHRAE 62 -1989.
  2. Amram, O., Abernethy, R., Brauer, M., Davies, H., Allen, R., 2011. Proximity of public elementary schools to major roads in Canadian urban areas. Int. J. Health Geogr. 10 (68). https://doi.org/10.1186/1476-072X-10-68.
  3. Ancelet, T., Davy, P.K., Trompetter, W.J., Markwitz, A., Weatherburn, D.C., 2011. Carbonaceous aerosols in an urban tunnel. Atmos. Environ. 45, 4463–4469.
  4. 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.
  5. Annegarn, H.J., Cahill, T.A., Sellschop, J.F.P., Zucchiatti, A., 1988. Time sequence particulate sampling and nuclear analysis. Phys. Scripta 37, 282–290.
  6. Annesi-Maesano, I., Baiz, N., Banerjee, S., Rudnai, P., Rive, S., SINPHONE Group, 2013. Indoor air quality and sources in schools and related health effects. J. Toxicol. Environ. Health B 16 (8), 491–550.
  7. Bako-Biro, Z., Clements-Croome, D.J., Kochhar, N., Awbi, H.B., Williams, M.J., 2012. Ventilation rates in schools and pupils' performance. Build. Environ. 48, 215–223.
  8. Bennett, W.D., Zeman, K.L., Jarabek, A.M., 2008. Nasal contribution to breathing and fine particle deposition in children versus adults. J. Toxicol. Environ. Health A 71 (3), 227–237.
  9. Brook, R.D., 2008. Cardiovascular effects of air pollution. Clin. Sci. (Lond.) 115 (6), 175–187. https://doi.org/10.1042/CS20070444.
  10. Brown, S.G., Eberly, S., Paatero, P., Norris, G.A., 2015. Methods for estimating uncertainty in PMF solutions: examples with ambient air and water quality data and guidance on reporting PMF results. Sci. Total Environ. 518, 626–635.
  11. Carslaw, D.C., Ropkins, K., 2012. Openair — an R Package for Air Quality. CEN Standard EN15251, 2007. Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics Bruxelles. European committee for Standardisation. Chen, B.Y., Jasmine Chao, H., Wu, C.F., Kim, H., Honda, Y., Guo, Y.L., 2014. High ambien