id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-329414-zueqafmn	Mallet, Marc Daniel	Meteorological normalisation of PM(10) using machine learning reveals distinct increases of nearby source emissions in the Australian mining town of moranbah	2020-08-17		.txt	text/plain	2228	137	52	title: Meteorological normalisation of PM(10) using machine learning reveals distinct increases of nearby source emissions in the Australian mining town of moranbah Here, two machine learning algorithms (gradient boosted regression and random forest) have been implemented to model and then meteorologically normalise PM(10) mass concentrations measured in Moranbah. The objective of this study is to exploit the recent advances in machine learn-88 ing to investigate the trends in PM 10 in Moranbah and assess the impact of 89 changes in local industrial actions on air quality using open-access datasets 90 and techniques. The secondary intent is to establish a methodology for this meteorological 95 normalisation that accounts for the influence of nearby fires, which are an 96 important source of particulate matter in the Australian dry season, as well 97 as other environmental factors such as soil water content.	./cache/cord-329414-zueqafmn.txt	./txt/cord-329414-zueqafmn.txt