Air pollution is considered the largest single environmental health risk by the World Health Organization. Despite several studies on NO2 changes in megacities, a systematic analysis in relation to settlement growth is still pending. In addition, previous studies do not refer to consistent spatial city concepts, which distorts statistics in the comparison. In this study, we examine the trends of NO2 air pollution in megacities in relation to urban settlement growth: Time series of tropospheric NO2 from GOME, SCIAMACHY, GOME-2A, and GOME-2B are evaluated regarding yearly settlement growth as derived from the World Settlement Footprint for the period from 1996 to 2015. Compared to previous studies, this work strictly uses remote sensing data and the spatial concept of Functional Urban Areas. Uncertainties due to incomparable administrative units, heterogeneously reported local data, and population counts are thus widely excluded to enable a reliable comparison of megacities across the globe. We find a wide spectrum of NO2 pollution trends and settlement growth rates. Despite this variety, the results exhibit a pronounced relation to the income group following the world’s economies classification by the World Bank.
This study presents a methodology for conducting a retrospective and indirect health risk assessment in urban areas, due to the long-term exposure to particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3). Specifically, the risk of all-causes mortality is investigated.
The methodology combines satellite-based settlement data, model-based air pollution data, land use information, demographic data, and regional-scale mobility patterns. The study examines the impact of population mobility on the population exposure and daily variations in pollutant levels on health risks. The results from the study show that neglecting the mobility patterns and the diurnal cycles of pollutants can lead to an underestimation of the health risk.
The incorporation of satellite and model data makes this methodology scalable to perform a health risk assessment also in remote regions, where local sensors are limited. Additional studies are required to assess the uncertainty in the exposure when using these medium to- low resolution data.
The majority of the population in Europe that is exposed to air pollution levels exceeding the WHO limit values lives in metropolitan areas. There are already several studies that assess the linkage between air pollution and adverse effects on health. With the technology at our disposition, today, we can identify air pollution hotspots. The assessment of the pollution situation alone represents, however, only one component of the whole picture. In order to be able to build a scale that identifies the most critical regions in higher need of intervention, also the probability of exposure and the number of people exposed to defined pollution concentrations must be considered. For this purpose, we can benefit from satellite-derived data products of settlement extent, population density and land use. To improve the health risk assessment, novel data sets have been synergistically exploited for the first time. In this work a method is proposed to perform an assessment of the increased health risk within urban areas in Europe due to the exposure to PM2.5 and to calculate the health burden index HBI: a useful parameter for the assessment of health risk that provides a measure of the impact of air pollution and enables to perform comparisons between different cities. This is a first approach showing the potential of this easily scalable tool that can be of support in the decision-making process and in the research on air pollution/health relationship. Further work is required for the verification and tuning of the initial hypotheses by means of validation with real-life data.
Conference Committee Involvement (3)
Remote Sensing Technologies and Applications in Urban Environments X
15 September 2025 | Madrid, Spain
Remote Sensing Technologies and Applications in Urban Environments IX
16 September 2024 | Edinburgh, United Kingdom
Remote Sensing Technologies and Applications in Urban Environments VIII
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