Spatial and Seasonal Dynamics of Air Quality in the Beijing-Tianjin-Hebei Region: An Analysis Using K-means Clustering and BP Neural Networks
Journal Title: Opportunities and Challenges in Sustainability - Year 2023, Vol 2, Issue 4
Abstract
In the context of rapid economic development, air pollution has emerged as a critical environmental issue, particularly in the Beijing-Tianjin-Hebei region. This study, through the application of Air Quality Index (AQI) data and K-means clustering, investigates the seasonal variations and spatial distribution of air quality in this region. It has been identified that air pollution in this area is not only subject to seasonal fluctuation but also exhibits distinct patterns of local spatial aggregation. Utilizing a Back Propagation (BP) Neural Network model, this research predicts AQI values, offering foresight into the development and transformation of haze weather conditions. The findings of this investigation are instrumental in enhancing the understanding of air pollution dynamics, facilitating the formulation of effective air control strategies. Such strategies are vital for the issuance of accurate pollution warnings and reminders, thereby contributing to the mitigation of severe pollution impacts.
Authors and Affiliations
Yuanyuan Wang, Zhuang Wu, Wanshu Fu, Jiaqi Du, Yi Zhang
Keywords
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- EP ID EP732083
- DOI https://doi.org/10.56578/ocs020402
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