In Journal of trace elements and minerals
BACKGROUND : Exposure to particulate air pollution is one of the greatest environmental risk factors for adverse human health outcomes. However, the constituents that may be responsible for such adverse health effects have not been fully studied.
METHODS : Total suspended particulates filters collected every 6 days in 2011 from three South Carolina locations were used in this case study. An inductively coupled plasma mass spectrometer interfaced with a laser ablation system (LA-ICP-MS) was used to directly analyze 41 inorganic elemental species on air pollution filters. Then, machine learning and multivariate statistical methods was employed to identify combinatorial patterns in the data and classify sites based on their elemental composition.
RESULTS : Forty-one elements were assessed and 33 were used in subsequent analysis. Correlations between United States Environmental Protection Agency (US EPA)'s chemical analysis dataset and data from the current study revealed significant associations between 7/15 elements with enough variation for comparison (r between 0.28 to 0.66, p<0.05). Subsequent multivariate analyses revealed four distinct patterns in the distribution of elements by sample location throughout the year.
CONCLUSION : The different airborne elements may need to be assessed to understand combinations of elements which occur together over space and/or time. Such information can be helpful in planning effective counter measures and strategies to control particulate air pollution.
Commodore Sarah, Christopher Steven, Wolf Bethany, Svendsen Erik
2023-Mar
Air filter media, Air quality, Laser ablation ICP-MS, Spatio-temporal patterns, Total suspended particulates
