How does urban morphology impact cities air quality? A modelling study

Abstract

With the rise of population living in cities an increase in urbanization is expected, with consequent changes to the morphology of urban areas, and thus, impacts in the urban environment. Air pollution is one of these impacts, affecting ecosystem and human health. The objective of this study is to assess the ability of urban morphologies to minimize air quality problems for future multi-core regions. Three urban morphology scenarios were designed, focused on Aveiro, Portugal: two scenarios representing urban compaction (Focused City and Independent City Scenario); and one representing an extreme version of the current urban dispersion (Dispersed City). The impact of urban scenarios on air quality was compared against the current urban morphology (baseline). The modelling system composed by the Weather Research and Forecast meteorological model, coupled with the chemistry model CAMx, adapted to consider a differentiation of urban land use classes (high- and low-density urban areas, and industrial areas), was applied. Annual results show that the compact urban morphology scenarios led to a decrease of air pollutant concentrations (NO₂ = -20 %, PM₁₀ = -3 %, PM_2.5 = −2 % for IC; and NO₂ = -17 %, PM₁₀ = -2 %, PM_2.5 = −1 %, for FC), with increases in industrial hotspots, that affect population exposure. The Disperse City scenario showed an increase in NO₂ concentrations (+98 %), due to the influence of road transport and lack of active mobility policies, with little change to PM concentrations. Despite population dispersion, the increase in NO₂ concentrations increased exposure. This study provides novel insights by applying a comprehensive methodology to assess the urban morphology's impact on air quality, highlighting the importance of the location and distribution of industrial areas, and the role of road transport emissions, and has the potential to provide urban planners and policy makers with the tools to prepare for more sustainable and healthier future urban areas. The applied methodology and modelling tools can be replicated worldwide.