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• W4321440915 abstract "Poor air quality is recognised as the most important environmental health issue of our time. Meteorological variables like temperature and wind speed can strongly influence air quality and these variables often show clear annual cycles. It is therefore common to analyse atmospheric pollutants within a seasonal framework. However, the commonly used seasons in Australia do not align well with all of the most important annual weather patterns that influence air quality in the Sydney Basin. We used Indigenous perspectives on ‘seasons’ as identified by the co-authors and combined these with statistical analysis of the local climatology. This enabled us to create a set of locally informed ‘quasi-seasons’ that we named IKALC-seasons (Indigenous Knowledge Applied to Local Climatology). Engaging with the IKALC-seasons improved our understanding of temporal variability of air pollution in western Sydney, mainly due to a better identification of the time of year when cold, still weather conditions result in higher levels of fine particulate pollution, carbon monoxide and nitrogen oxides. Although the IKALC seasons identified in this study are intrinsically local in nature, the methodology developed has broadscale application. This approach can be used to identify the times of year when micrometeorological conditions are most likely to drive poor air quality thereby helping to inform effective decision-making about emission controls." @default.
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• W4321440915 date "2023-02-22" @default.
• W4321440915 modified "2023-10-09" @default.
• W4321440915 title "Indigenous Knowledge of seasons delivers a new way of considering annual cycles in atmospheric dispersion of pollutants" @default.
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• W4321440915 doi "https://doi.org/10.1071/es22027" @default.
• W4321440915 hasPublicationYear "2023" @default.
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