Ensemble classification for identifying neighbourhood sources of fugitive dust and associations with observed PM 10

Makhanya, Sibusisiwe; Stein, Alfred; Breytenbach, André; Gxumisa, Athi A; Dudeni-Tlhone, Nontembeko; Debba, Pravesh

doi:10.1016/j.atmosenv.2017.07.017

Cited by 1 publication

(1 citation statement)

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“…The sources of fugitive dust are divided into natural sources and anthropogenic sources [12][13][14][15]. Among them, natural sources refer to natural dust caused by unfavorable climatic conditions, mainly bare surfaces and various aerosol particles settled on the ground.…”

Section: Introductionmentioning

confidence: 99%

Morphology and Dust-Suppression Evaluation of Fugitive Dust Particles in Beijing

Yang

Wang

et al. 2022

Sci

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Fugitive dust particles are important contributors to urban ambient particulate matter (PM), while their emissions have been ignored or greatly underestimated in previous studies, leading to the underestimation of PM concentrations and health impacts. Thus, studying the morphology of fugitive dust, taking appropriate dust-suppression measures, and evaluating dust-suppression effects are crucial to the prevention and control of fugitive dust. In this study, we investigated the morphology and composition of dust particles from different dust sources, including bare land, stock dump, construction, and road dust. Afterwards, different dust-suppression measures including fence interception nets, bare ground mesh nets, and road dust-suppressants were undertaken to simulate and analyze their dust-suppression effects. Finally, the height concentration profiling method was used to comprehensively evaluate the on-site dust-suppression effect, which can not only accurately evaluate the dust-suppression effect, but also predict the dust-suppression ability in a wide range. Gaining insights into the morphology and composition of dust from representative sources is an important step forward to prevent and control fugitive dust, and selecting an appropriate dust-suppression effect evaluation method will provide a beneficial guide for effectively controlling PM pollution in the future.

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Section: Introductionmentioning

confidence: 99%