Disentangling climate change from air pollution effects on epiphytic bryophytes

At the interface between atmosphere and vegetation, epiphytic floras have been largely used as indicators of air quality. The recovery of epiphytes from high levels of SO2 pollution has resulted in major range changes, whose interpretation has, however, been challenged by concomitant variation in other pollutants as well as climate change. Here, we combine historical and contemporary information on epiphytic bryophyte species distributions, climatic conditions and pollution loads since the 1980s in southern Belgium to disentangle the relative impact of climate change and air pollution on temporal shifts in species composition. The relationship between the temporal variation of species composition, climatic conditions, SO2, NO2, O3, and fine particle concentrations was analyzed by variation partitioning. The temporal shift in species composition was such, that it was, on average, more than twice larger than the change in species composition observed today among communities scattered across the study area. The main driver, contributing to 38% of this temporal shift in species composition, was the variation of air quality. Climate change alone did not contribute to the substantial compositional shifts in epiphytic bryophyte communities in the course of the last 40 years. As a consequence of the substantial drop of N and S loads over the last decades, present-day variations of epiphytic floras were, however, better explained by the spatial variation of climatic conditions than by extant pollution loads. The lack of any signature of recolonization delays of formerly polluted areas in the composition of modern floras suggests that epiphytic bryophytes efficiently disperse at the landscape scale. We suggest that a monitoring of epiphyte communities at 10-year intervals would be desirable to assess the impact of raising pollution sources, and especially pesticides, whose impact on bryophytes remains poorly documented

Morphology informed by phylogeny reveals unexpected patterns of species differentiation in the aquatic moss Rhynchostegium riparioides s.l

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Assessment of the sensitivity of model responses to urban emission changes in support of emission reduction strategies

© 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The sensitivity of air quality model responses to modifications in input data (e.g. emissions, meteorology and boundary conditions) or model configurations is recognized as an important issue for air quality modelling applications in support of air quality plans. In the framework of FAIRMODE (Forum of Air Quality Modelling in Europe, https://fairmode.jrc.ec.europa.eu/) a dedicated air quality modelling exercise has been designed to address this issue. The main goal was to evaluate the magnitude and variability of air quality model responses when studying emission scenarios/projections by assessing the changes of model output in response to emission changes. This work is based on several air quality models that are used to support model users and developers, and, consequently, policy makers. We present the FAIRMODE exercise and the participating models, and provide an analysis of the variability of O3 and PM concentrations due to emission reduction scenarios. The key novel feature, in comparison with other exercises, is that emission reduction strategies in the present work are applied and evaluated at urban scale over a large number of cities using new indicators such as the absolute potential, the relative potential and the absolute potency. The results show that there is a larger variability of concentration changes between models, when the emission reduction scenarios are applied, than for their respective baseline absolute concentrations. For ozone, the variability between models of absolute baseline concentrations is below 10%, while the variability of concentration changes (when emissions are similarly perturbed) exceeds, in some instances 100% or higher during episodes. Combined emission reductions are usually more efficient than the sum of single precursor emission reductions both for O3 and PM. In particular for ozone, model responses, in terms of linearity and additivity, show a clear impact of non-linear chemistry processes. This analysis gives an insight into the impact of model’ sensitivity to emission reductions that may be considered when designing air quality plans and paves the way of more in-depth analysis to disentangle the role of emissions from model formulation for present and future air quality assessments.Peer reviewe