HYPERCITY - Hyperspectral biomonitoring: air quality and the city

Context and objectives

A significant proportion of Europe’s population lives in urban areas where exceedances of air quality standards occur and pose serious health risks. A major contribution to the urban air pollution is provided by burning of fossil fuels in road transport, with the emission of particulate matter (PM). PM pollution is causing tremendous costs to society due to a significant increase in health problems and morbidity. To make reliable risk assessments and take adequate urban management decisions, it is important to get a detailed insight in the spatial distribution of air pollution.
As conventional air pollution monitoring stations only provide coarse-scale information on exposure to pollutants, a growing interest has risen in monitoring and modelling urban air pollution with a high spatial resolution, e.g. through biomonitoring of urban vegetation.

Remote sensing techniques are frequently applied within the context of environmental monitoring. However, many techniques needs further development, or were never tested for their biomonitoring potential. The dorsiventral leaf asymmetry (the difference between the upper and lower leaf side), and the resulting differences in hyperspectral leaf reflectance, is hardly considered. The overall objective of this research proposal is to develop, test and validate a plant-based passive biomonitoring methodology based on hyperspectral observations and considering leaf asymmetry.

This project will make use of a dual approach:

1. Large solitary trees growing in various contrasting urban environments in terms of air pollution used for scaling up exercises from leaf to canopy, and
2. Trees spatially distributed over the entire urban area for mapping purposes.

The study area are two urban environments with different climate: Antwerp (Belgium) and Valencia (Spain). Several tree species will be selected and at least one, Platanus x. acerifolia, will be monitored in common at both test sites to check the robustness of the methodology.