Mapping ozone deposition to winter wheat in Northern Italy: integrated use of measured data to assess stomatal uptake at different spatio-temporal resolutions

Tropospheric ozone (O₃) is a secondary atmospheric pollutant that poses a significant threat to vegetation, leading to oxidative stress, growth reduction, and yield losses. Research activities have demonstrated that O₃ damage is related more to the ozone flux absorbed by leaves, rather than simple O₃ exposure, and dose-response relationships accounting for O₃ stomatal flux effects on biomass growth have been defined for several crop species within the ICP-Vegetation program.

This study aimed at calculating and mapping the O₃ deposition to winter wheat (Triticum aestivum L.) in the Lombardy region (Italy) by applying a dual-sink big-leaf model to estimate the stomatal uptake by crop, i.e. the POD₆ which is the seasonal Phytotoxic Ozone Dose above a threshold of 6 nmol m^-2 s^-1.

The model run on spatialized measured data of air temperature, relative humidity, precipitation, wind speed, global radiation and O₃ concentration provided by regional monitoring networks for year 2017, and included calculations of the evolution of crop’s geometry and phenology, light penetration within the canopy, stomatal conductance, atmospheric turbulence, and soil water availability to the plants.
This workflow was also used to assess the effect of different spatio-temporal resolutions on POD₆ patterns, testing a wide array of configurations, from 1×1 km²  to 50×50 km², and from 1h to 6h.

Results revealed that in 2017 POD₆ was on average 2.03 ± 0.81 mmol m^-2 PLA (Projected Leaf Area), leading to an estimation of 7.5 ± 3.1% relative grain loss. The analysis on the involved environmental factors identified air temperature as the most limiting factor to O₃ stomatal conductance, while soil water emerged as the key factor influencing the POD₆ spatial patterns.
Assessment of different spatio-temporal resolutions suggested that finer resolutions are the only ones being able to detect local features (thus being able to, e.g., guide spatially based mitigation measures), and that coarser resolutions might lead to lower POD₆ values, even though they are much affordable from a computational point of view and represents a good compromise if only a general risk assessments is requested.