Impact of urban expansion on the air pollution landscape: A case study of Hanoi, Vietnam

• Published in: The Science of the total environment Vol. 702; p. 134635
• Main Authors: Hien, P.D., Men, N.T., Tan, P.M., Hangartner, M.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01-02-2020
• Subjects: Kriging; Land use regression; Motorcycles; Peri-urban pollution; Population density; Land use regression; Peri-urban pollution; Motorcycles; Kriging; Population density
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2019.134635

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•NO2 and SO2 concentrations were measured at 176 sites across 14 districts of Hanoi.•NO2/SO2 decrease from 70/51 µg m−3 in urban core to 5/1 µg m−3 in peri-urban area.•Numerous traffic and industrial emission hot spots occur in the peri-urban area.•Land use regression models were built using pollution and socioeconomic data.
The rapid urban expansion of Hanoi over the last few decades has transformed a lot of agricultural land into urban land uses accompanying pollution by traffic, industrial, and residential emission sources. In this work, the impact of urban expansion on the air pollution landscape has been assessed using the NO2 and SO2 ambient concentrations measured by passive diffusion samplers at 176 sites across the nine urban and the five peri-urban districts of Hanoi spanning an area of 921 km2. The NO2 values ranged from 5.5 to 70 µg m−3 with an arithmetic mean of 34.3 µg m−3. The corresponding figures for SO2 are 1, 51, and 14.5 µg m−3. The pollutant concentrations decrease from the city center outward, reflecting the history of urban expansion with the city fringe being urbanized in the 1980s and the peri-urban area having undergone development from the early 1990s. The pollution landscapes show elevated concentration levels in the recently built-up areas at 6, 10, and 21 km from the city center. The NO2 and SO2 digital maps generated from monitoring data by the kriging technique show numerous traffic and industrial emission hot spots in the peri-urban area. As revealed by the land use regression models, the factors driving the spatial variations of pollutant concentrations across the city include the population density, the road density, and the distances of the monitoring site to the urban center and the nearest roadway.