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Tropospheric ozone (O3) causes widespread damage to vegetation; however, monitoring of O3 induced damage is often reliant on manual leaf inspection. Reflectance spectroscopy of vegetation can identify and detect unique spectral signatures of different abiotic and biotic stressors. In this study, we tested the use of hyperspectral leaf reflectance to detect O3 stress in alder, beech, birch, crab apple, and oak saplings exposed to five long-term O3 regimes (ranging from daily target maxima of 30 ppb O3 to 110 ppb). Hyperspectral reflectance varied significantly between O3 treatments, both in whole spectra analysis and when simplified to representative components. O3 damage had a multivariate impact on leaf reflectance, underpinned by changes in pigment balance, water content and structural composition. Vegetation indices derived from reflectance which characterised the visible green peak were able to differentiate between O3 treatments. Iterative normalised difference spectral indices across the hyperspectral wavelength range were correlated to visual damage scores to identify significant wavelengths for O3 damage detection. We propose a new Ozone Damage Index (OzDI), which characterises the reflectance peak in the shortwave infrared region and outperformed existing vegetation indices in terms of correlation to O3 treatment. These results demonstrate the potential application of hyperspectral reflectance as a high throughput method of O3 damage detection in a range of common broadleaf. species.

Original publication

DOI

10.1016/j.envpol.2024.124642

Type

Journal article

Journal

Environ Pollut

Publication Date

31/07/2024

Volume

360

Keywords

Air pollution, Forest monitoring, Reflectance spectroscopy, Temperate forest, Tropospheric ozone, Vegetation index