空气质量指数
空气污染物
污染物
比例(比率)
污染
环境科学
空气污染
气象学
环境工程
地理
地图学
生态学
生物
作者
Peng Wei,Hao Song,Yuan Shi,Abhishek Anand,Wang Ya,Mengyuan Chu,Zhi Ning
标识
DOI:10.1016/j.envint.2024.108992
摘要
Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monitoring stations may be unable to predict and characterize fine-scale TRAP, especially in complex urban environments influenced by various features. This study aims to estimate fine-scale (50 m) concentrations of nitrogen oxides (NO and NO₂) in Hong Kong using a deep learning (DL) structured model.
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