etc-atni-reports

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.

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

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 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.

The purpose of this study has been to investigate the quantitative effect of vehicle taxation and incentives offered in seven different countries on CO2, NOx and PM10 emissions. The countries examined in our study vary considerably in the vehicle tax system that have followed. There are some countries that implemented an aggressive policy and gave robust incentives to introduce many EVs into the fleet but there are also those that followed a more moderate policy regarding the incentives they offered for EVs. In a brief summary, the major facts of each country's vehicle tax policy have been presented. For the calculation process two scenarios have been evaluated, one scenario that simulates the observed situation in the EVs market (baseline) and one scenario in which the market was not influenced by the introduction of vehicle-related taxes (EV scenario). The emissions difference between these two scenarios can be considered as the quantitative effect of vehicle taxation and measures taken from each country on CO2, NOx and PM10 emissions. The effectiveness of the policy and measures applied by a Member State can be determined in terms of total reduction of CO2 emissions. At this point, we should emphasize that the results of our calculations are real-world emissions as COPERT was used for the computational process. The major outcome of our analysis is that the countries that promoted the EVs market managed to avoid a significant amount of emissions. The leading country in terms of emission savings is Norway. One likely reason for this relatively high performance is strong incentives for promoting purchase and ownership of PHEVs and BEVs. To fully understand the value of Norway's incentives, it can be said that the purchase price for a BEV is more or less equal to the price of a similar ICEV. Follow-up country is the Netherlands which has also implemented policies favoring EVs and penalizing high- emitting ICEVs It is important to stress that a lot of BEVs and PHEVs were introduced into the fleets of these countries because policies were more targeted to these two technologies. These vehicle categories can bring the most benefits. Conversely, countries that did not offer special incentives to close the cost competitiveness gap between EVs and equivalent ICE vehicles failed to achieve high reductions in emissions. Examples of countries in this category are Greece and Poland. Exception of the above rule is Ireland where, despite the financial incentives to support EVs, their sales have not taken off. The Irish government should explore and find out the reasons holding back the expected surge in adoption of these cars (e.g. due to insufficient charging stations) and make the necessary modifications in its vehicle taxation system. For Greece, we also examined the effect of lifting the ban on diesel cars (that took place in 2012), as it brought a dieselization of the fleet which produced very large CO2 emission savings but had adverse effects on air quality, as much more NOx emissions were emitted. Another fact that should be underlined is the consumer's sensitivity to modifications in the tax system. An example that confirmed this conclusion, is sales of PHEVs in the Netherlands in 2017. Due to withdrawal of some incentives, PHEV sales dropped dramatically. That is why Member states should be very careful when developing long-term vehicle taxation policies.

The industrial emissions country profiles present the emissions of air and water pollutants and greenhouse gases in fact sheets for each country. The significance of industry, given by gross value added, energy consumption and water use, as well as generation of waste are added to the presentation. The trend in emissions and waste generation are given in relative numbers. The scope of industry in this respect includes in short all industrial activities reported under the European Pollutant Release and Transfer Register (E-PRTR) excluding agriculture (activity code 7.(a) and 7.(b)). The data sources to the country profiles include Eurostat, the E-PRTR, greenhouse gas (GHG) emissions reported under the Monitoring Mechanism Regulation (MMR) and air pollutant emission inventories reported under the Convention on Long-range Transboundary Air Pollution (CLRTAP).