In support of the first Tropospheric Ozone Assessment Report (TOAR) a relational database of global surface ozone observations has been developed and populated with hourly measurement data and enhanced metadata. A comprehensive suite of ozone data products including standard statistics, health and vegetation impact metrics, and trend information, are made available through a common data portal and a web interface. These data form the basis of the TOAR analyses focusing on human health, vegetation, and climate relevant ozone issues, which are part of this special feature.Cooperation among many data centers and individual researchers worldwide made it possible to build the world's largest collection of in-situ hourly surface ozone data covering the period from 1970 to 2015. By combining the data from almost 10,000 measurement sites around the world with global metadata information, new analyses of surface ozone have become possible, such as the first globally consistent characterisations of measurement sites as either urban or rural/remote. Exploitation of these global metadata allows for new insights into the global distribution, and seasonal and long-term changes of tropospheric ozone and they enable TOAR to perform the first, globally consistent analysis of present-day ozone concentrations and recent ozone changes with relevance to health, agriculture, and climate.Considerable effort was made to harmonize and synthesize data formats and metadata information from various networks and individual data submissions. Extensive quality control was applied to identify questionable and erroneous data, including changes in apparent instrument offsets or calibrations. Such data were excluded from TOAR data products. Limitations of a posteriori data quality assurance are discussed. As a result of the work presented here, global coverage of surface ozone data for scientific analysis has been significantly extended. Yet, large gaps remain in the surface observation network both in Schultz et al: Tropospheric Ozone Assessment Report Art. 58, page 2 of 26 terms of regions without monitoring, and in terms of regions that have monitoring programs but no public access to the data archive. Therefore future improvements to the database will require not only improved data harmonization, but also expanded data sharing and increased monitoring in data-sparse regions.

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Purpose This study aimed at investigating correlations between heavy metal concentrations in mosses and modelled deposition values as well as other site-specific and regional characteristics to determine which factors primarily affect cadmium, lead and mercury concentrations in mosses. The resulting relationships could potentially be used to enhance the spatial resolution of heavy metal deposition maps across Europe. Materials and methods Modelled heavy metal deposition data and data on the concentration of heavy metals in naturally growing mosses were integrated into a geographic information system and analysed by means of bivariate rank correlation analysis and multivariate decision trees. Modelled deposition data were validated annually with deposition measurements at up to 63 EMEP measurement stations within the European Monitoring and Evaluation Programme (EMEP), and mosses were collected at up to 7,000 sites at 5-year intervals between 1990 and 2005. Results and discussion Moderate to high correlations were found between cadmium and lead concentrations in mosses and modelled atmospheric deposition of these metals: Spearman rank correlation coefficients were between 0.62 and 0.67, and 0.67 and 0.73 for cadmium and lead, respectively (p<0.001). Multivariate decision tree analyses showed that cadmium and lead concentrations in mosses were primarily determined by the atmospheric deposition of these metals, followed by emissions of the metals. Low to very low correlations were observed between mercury concentrations in mosses and modelled atmospheric deposition of mercury. According to the multivariate analyses, spatial variations of the mercury concentration in mosses was primarily associated with the sampled moss species and not with the modelled deposition, but regional differences in the atmospheric chemistry of mercury and corresponding interactions with the moss may also be involved. Conclusions At least for cadmium and lead, concentrations in mosses are a valuable tool in determining and mapping the spatial variation in atmospheric deposition across Europe at a high spatial resolution. For mercury, more studies are needed to elucidate interactions of different chemical species with the moss.

The NERC and CEH trade marks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. 1 European Heavy Metals in Mosses Survey AbstractThe aim of this study was to identify the factors influencing Cd, Hg and Pb concentrations in mosses sampled within the framework of the European Heavy Metals in Mosses Surveys 1990Surveys -2005. The analyses encompassed data from 4661 (1990), 7301 (1995), 6764 (2000) and 5600 (2005) sampling sites. As exemplary case studies revealed that other factors besides atmospheric deposition of metals influence the element concentrations in mosses, the moss datasets of the above mentioned surveys were analysed by means of bi-and multivariate statistics in order to identify factors influencing metal bioaccumulation. In the analyses we used the metadata recorded during the sampling as well as additional geodata e.g. on depositions, emissions and land use. Bivariate Spearman correlation analyses showed the highest correlations between Cd and Pb concentrations in mosses and EMEP modelled total deposition data (0.62 ≤ r s ≤ 0.73). For Hg the correlations with all the tested factors were considerably lower (e.g. total deposition r s ≤ 0.24). Multivariate decision tree analyses by means of Classification and Regression Trees (CART) identified the total deposition as the statistically most significant factor for the Cd and Pb concentrations in the mosses in all four monitoring campaigns. For Hg, the most significant factor 8 in 1990 as identified by CART was the distance to the nearest Hg source recorded in the European Pollutant Emission Register, in 1995 and 2000 it was the analytical method, and in 2005 CART identified the sampled moss species. The strong correlations between the Cd and Pb concentrations in the mosses and the total deposition can be used to calculate deposition maps with a regression kriging approach on the basis of surface maps on the element concentrations in the mosses.