The EU project SHIVA (Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere) was initiated by a larger international consortium, in order to study the contribution of mostly naturally emitted halogenated very short-lived substances (VSLS) to the stratospheric inventory of ozone destroying halogens. Today the SHIVA consortium comprises about 120 full or associated partners coming from 19 institutions in 9 countries.
SHIVA’s scientific objectives infer from past research that mostly brominated and less likely iodinated VSLS, predominately emitted from biologically active surface waters of the global oceans, are eventually significantly contributing to the halogen load of the global stratosphere. Moreover, theoretical studies revealed that only the combination of sufficiently strong VSLS sources together with efficient vertical atmospheric transport would support a relevant contribution of VSLS to the stratospheric halogen burden. Both conditions are likely to be met in the western Pacific during the wet season (November to March). Since details of the relevant processes and their relevance for stratospheric ozone are yet largely unexplored, four major objectives of EU-SHIVA were identified, namely investigations of the following:
- the oceanic emission strengths of a suite of halogenated VSLS;
- the atmospheric transport and transformation of the halogenated VSLS;
- the past, present and likely future trend of the total stratospheric halogen burden;
- the impact of long and short-lived halogenated trace gases and their inorganic product gases for past, present and future ozone within the upper troposphere, TTL and global stratosphere.
The special ACP-AMT-BG-OS SI is intended to cover the research performed within the EU project SHIVA and related undertakings. Contributing manuscripts may cover investigations of halogenated VSLS emissions from marine micro- and macroalgae, to their atmospheric transport and transformation as well as impacts of VSLS for global ozone studied in the laboratory, field and by theoretical models.