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The paper provides the annual update of the European air quality concentration maps and population exposure estimates for human health related indicators of pollutants PM10 (annual average, 90.4 percentile of daily means), PM2.5 (annual average), ozone (93.2 percentile of maximum daily 8-hour means, SOMO35) and NO2 (annual average), and vegetation related ozone indicators (AOT40 for vegetation and for forests) for the year 2016. The report contains also NOx annual average concentration map for 2016. The trends in exposure estimates in the period 2005-2016 for PM10 and ozone, resp. in the period 2007-2016 for PM2.5 are summarized. The analysis is based on interpolation of annual statistics of the 2016 observational data reported by EEA Member countries in 2015 and stored in the Air Quality e-reporting database. The mapping method is the Regression – Interpolation – Merging Mapping. It combines monitoring data, chemical transport model results and other supplementary data using linear regression model followed by kriging of its residuals (residual kriging). The paper presents the mapping results and gives an uncertainty analysis of the interpolated maps, including the probabilities of exceeding relevant thresholds. These maps, with their spatial exceedance and exposure estimates, are intended to be used for the assessment of European air quality by the EEA and its ETC/ACM, and for (interactive visual) public information purposes through the EEA website.

New low-cost technologies for monitoring air quality have enabled a number of projects by civil society or individuals, with the broad aim to assess the quality of air locally. This new source of information is emerging in a highly technical and thoroughly regulated area. We have to address both the technical and the social aspects of such projects, try to find scientifically appropriate ways to use the new information, and explain the differences between information obtained by different technologies. In this report, we would like to provide a practically oriented overview of use of low-cost sensor system technologies within the ecosystem of air quality monitoring and measurements. Sensing techniques are rapidly evolving. This ‘ever’ improving capability implies among other, that there is currently no traceable method of evaluation of data quality. Despite the efforts of numerous groups, including within the European standardization system, a certification system will take some time to develop. This has important implications for example, when comparing measurements taken in time, by different technologies or their versions. Fitness for purpose – why are we measuring or monitoring and how do we intend to use the information we obtain – should always be the main criterion for the technological choice. The report starts with an overview of elements of a monitoring system and proceeds to describe briefly the new technologies. Then, we give examples of how low-cost sensor technologies are being used by citizens. These examples are followed by reflections on how to provide actionable information. Having learned from practical implementation of sensor systems, we also discuss how the data from citizen activities can be used to develop new information, and finally, we reflect on developing low cost sensor systems monitoring on a larger scale.

The calculated projections show that the number of people exposed to high noise levels would increase in all noise sources (roads, railways and aircraft noise) except for industries inside agglomerations by 2020 (short term scenario). Prediction of exposure values for Lnight follow the same pattern obtained with the calculations for Lden in short and mid-term scenario. Specific findings concerning projections for road traffic noise exposure , rail traffic noise exposure and the aviation sector exposure have been analysed, based on the assumption that current policies and planned objectives related to population and transport trends will be achieved and implemented, as well as land use change projections corresponding to a baseline or reference scenario

Methodological report summarizing the steps followed to obtain estimated results of a complete noise exposure covering the END sources. The process followed is described in different sections, from the input data being used until the final gap filling exercise to obtain the exposure numbers at EEA (39) level, if data available. The method differs depending on the noise souce being gap filled, detailed in the different sections of the summary. Results of the exercise are posted in ETC/ATNI Forum and will be used in different publications foreseen in 2019 by the EEA.