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.

[1] Dry deposition is a major component of total atmospheric nitrogen deposition and thus an important source of bioavailable nitrogen to ecosystems. However, relative to wet deposition, less is known regarding the sources and spatial variability of dry deposition. This is in part due to difficulty in measuring dry deposition and associated deposition velocities. Passive sampling techniques offer potential for improving our understanding of the spatial distribution and sources of gaseous and aerosol N species, referred to here as dry deposition. We report dual nitrate isotopic composition ( O values between actively and passively collected samples; the causes for this offset warrant further investigation. Nonetheless, passive sample collection represents a significant cost savings over active sampling techniques and could allow a more extensive understanding of patterns of dry deposition and associated insights to nitrogen sources across landscapes.

h i g h l i g h t sA novel approach was developed to produce estimates of total nitrogen and sulfur. The approach merges data from measurements and models. Measurement data have greater weight near monitoring sites. Modeled data are used for deposition species that are not measured. This total deposition data set is useful for ecological assessments. a r t i c l e i n f o b s t r a c tAtmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Network (NTN) to develop values of total deposition of sulfur and nitrogen. Data developed using this method are made available via the CASTNET website.Published by Elsevier Ltd.

Abstract. Ambient air monitoring as part of the US Environmental Protection Agency's (US EPA's) Clean Air Status and Trends Network (CASTNet) currently uses filter packs to measure weekly integrated concentrations. The US EPA is interested in supplementing CASTNet with semi-continuous monitoring systems at select sites to characterize atmospheric chemistry and deposition of nitrogen and sulfur compounds at higher time resolution than the filter pack. The Monitor for AeRosols and GAses in ambient air (MARGA) measures water-soluble gases and aerosols at an hourly temporal resolution. The performance of the MARGA was assessed under the US EPA Environmental Technology Verification (ETV) program. The assessment was conducted in Research Triangle Park, North Carolina, from 8 September to 8 October 2010 and focused on gaseous SO2, HNO3, and NH3 and aerosol SO42-, NO3-, and NH4+. Precision of the MARGA was evaluated by calculating the median absolute relative percent difference (MARPD) between paired hourly results from duplicate MARGA units (MUs), with a performance goal of ≤ 25%. The accuracy of the MARGA was evaluated by calculating the MARPD for each MU relative to the average of the duplicate denuder/filter pack concentrations, with a performance goal of ≤ 40%. Accuracy was also evaluated by using linear regression, where MU concentrations were plotted against the average of the duplicate denuder/filter pack concentrations. From this, a linear least squares line of best fit was applied. The goal was for the slope of the line of best fit to be between 0.8 and 1.2. The MARGA performed well in comparison to the denuder/filter pack for SO2, SO42−, and NH4+, with all three compounds passing the accuracy and precision goals by a significant margin. The performance of the MARGA in measuring NO3- could not be evaluated due to the different sampling efficiency of coarse NO3- by the MUs and the filter pack. Estimates of "fine" NO3- were calculated for the MUs and the filter pack. Using this and results from a previous study, it is concluded that if the MUs and the filter pack were sampling the same particle size, the MUs would have good agreement in terms of precision and accuracy. The MARGA performed moderately well in measuring HNO3 and NH3, though neither met the linear regression slope goals. However, recommendations for improving the measurement of HNO3 and NH3 are discussed. It is concluded that SO42-, SO2, NO3-, HNO3, NH4+, and NH3 concentrations can be measured with acceptable accuracy and precision when the MARGA is operated in conjunction with the recommendations outlined in the manuscript.

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