Big data analytics to classify earthwork-related locations: A Chengdu study

arXiv:2402.14698v1 Announce Type: new
Abstract: Air pollution has significantly intensified, leading to severe health consequences worldwide. Earthwork-related locations (ERLs) constitute significant sources of urban dust pollution. The effective management of ERLs has long posed challenges for governmental and environmental agencies, primarily due to their classification under different regulatory authorities, information barriers, delays in data updating, and a lack of dust suppression measures for various sources of dust pollution. To address these challenges, we classified urban dust pollution sources using dump …

abstract air pollution analytics arxiv big big data big data analytics challenges classification consequences cs.ai cs.lg data data analytics dust environmental health information locations management pollution regulatory study type urban