都市形態、氣象因素與空氣品質：對河內市 PM2.5 濃度的分析

Abstract

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The relationship between urban forms, meteorological factors, and air quality in three densely populated residential areas of Hanoi city was explored through on-site data collection and statistical evaluation. Data was compared between the city lockdown period in the summer of 2021, when there were reduced human activities, and the same period in 2022 under normal conditions. Urban form metrics including building density, average building height, greenery ratio, road density and average road width were calculated for each area using geospatial analysis. Meteorological data including temperature, humidity, and wind features were obtained from a weather station in Noi Bai Airport. A descriptive analysis using Python visualization examined comparisons between urban form and PM2.5 levels. Additionally, three machine learning models were applied to determine the correlation levels between PM2.5 concentrations and meteorological data. The results highlight the potential impacts of urban spatial patterns and weather on air quality. It reveals that meteorological conditions, specifically temperature, humidity and wind speed have effect on PM2.5 concentrations, which are critical for air quality management. The study demonstrates a consistent impact of temperature and humidity across different predictive models, with higher values correlating with increased PM2.5 levels in the normal period. Conversely, wind speed exhibits a more complex interaction, suggesting that its relationship with air quality is influenced by other factors like urban geometry. The investigation into urban form metrics confirms that urban design elements such as building density, height, and greenery cover ratio significantly affect local air quality. The observed increase in PM2.5 levels in the area with denser and taller buildings points to the negative implications of urban structures on air quality, while another area with a higher greenery cover ratio experienced improved air quality, underscoring the positive role of vegetation. The study also finds that weather and city factors work together intricately, meaning urban planning must look at both to truly help air quality. Changes in PM2.5 levels over the years suggest tweaks to city design, like adding more green space or better organizing buildings could alter local meteorological conditions in ways that help mitigate adverse impacts on air quality. The differences in model predictions show we need a range of advanced modeling approaches to accurately check and predict impacts on air quality. By bridging urban planning and environmental health, this research gives important insights into making plans to cut air pollution in cities. The findings recommend a data-driven, cross-disciplinary approach to urban design and policy to achieve sustainable air quality improvements in crowded cities like Hanoi. Overall, this work shows the importance of collaboration across fields and multi-step strategies when tackling complex city air pollution.