etc-atni-reports

ETC/ATNI Report 9/2019: European air quality maps for 2017. PM10, PM2.5, Ozone, NO2 and NOx spatial estimates and their uncertainties.

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, SOMO10) and NO2 (annual average), and vegetation related ozone indicators (AOT40 for vegetation and for forests) for the year 2017. The report contains also NOx annual average concentration map for 2017. The trends in exposure estimates in the period 2005-2017 for PM10 and ozone, resp. in the period 2007-2017 for PM2.5 are summarized. The analysis is based on interpolation of annual statistics of the 2017 observational data reported by EEA Member countries in 2016 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.

ETC/ATNI Report 14/2019: Statistical modelling for long-term trends of pollutants. Use of a GAM model for the assessment of measurements of O3, NO2 and PM.

Previous studies under the European Topic Centre on Air pollution and Climate change Mitigation (ETC/ACM) on the link between trends and meteorology have shown that these links could be estimated by CTMs (chemical transport models). CTMs are useful tools for explaining pollutant trends in terms of the separate impact of individual physio-chemical drivers, such as emissions, and meteorology. It requires, however, multi-year calculations with CTMs designed in specific ways to allow the subtraction of various model scenarios. The method could also be sensitive to the years selected for calculating the perturbations in boundary conditions and meteorology and to uncertainties in emission data. The statistical GAM model that has been developed under ETC/ACM and European Topic Centre on Air pollution, noise, transport and industrial pollution (ETC/ATNI) provides a complementary method for separating the influence of meteorological variability from other processes. This model represents a completely different approach that is based only on observed links between local meteorological parameters (like temperature, wind, etc) and observed pollutant concentration levels. Thus, the model does not contain any representation of the real processes in the atmosphere. We found clear differences in model performance both with respect to geographical area and atmospheric species. In general, the best performance was found for O3 (although not for the peak levels) with gradually lower performance for NO2, PM10 and PM2.5 in that order. With respect to area, the model generally produced the best predictions for Central Europe (Germany, Netherlands, Belgium, France, Austria, Czech Republic) and the poorest for (southern Europe). For wintertime NO2, particularly poor agreement between the GAM model and the measurements was found for the North Italian region. The model agreement for southern Europe and the Iberian Peninsula was also fairly low, although it is variable from site to site. The number of stations with measurements of PM10 and PM2.5 with sufficient length was substantially lower than for O3 and NO2, and thus, a region-by-region comparison of the model performance was not really possible. In general, the PM10 data indicated a better agreement between the model and the measurements for summer than for winter. Furthermore, the GAM model seemed to perform better for the background urban than for rural sites. Poorest performance for PM10 was found for background rural sites in winter. Withdrawing the meteorological factor by the GAM model can help in identifying significant trends. The main reason for this is that meteorology introduces a year-to-year variability which could mask the underlying trend. Meteorology could also induce a trend in the concentrations but this is a matter of length of the timeseries. For short time periods (typically less than 10 years) the variations in meteorology could lead to spurious effects reflecting the weather conditions at the start and end year. On a long timescale the effects of climate change (trends in temperature, precipitation etc) will certainly lead to trends in the concentration of pollutants, but this is beyond the scope of this report. For rural ozone, a statistically significant decline is calculated in the meteorologically adjusted trends in all regions except for the inflow region at the north-western boundary of Europe that shows only minor variations during the 2000-2017 period. Such a decline is also found in the non-adjusted record, but then it is non-significant because of the meteorological variability. For the 2000-2017 period we could, however, not conclude that meteorology alone has caused significant trends in the ozone levels. Some regions show a steady decline in ozone while others show a curve peaking in the early 2000s. Many of the regions indicate a flattening of the ozone trend in the last part of the period. The meteorology adjusted trends for NO2 show a similar pattern as for O3 with decreasing levels in all regions. As for O3 the NO2 trends are seen as a steady decline in some regions and a curve peaking in the early 2000s in other regions. Marked downward meteorology adjusted trends are found for PM10 as well a substantial variability from year to year caused by meteorology. The GAM model estimates a significant meteorologically induced increase in PM10 in the North Italian region, but the number of stations is too few to make strict conclusions on this trend. For PM2.5 the amount of data is insufficient and the monitoring history is considerably shorter and thus we focus on the period 2008-2017 only. A small downward meteorology adjusted trend is estimated for PM2.5, except for the Iberian Peninsula region. To sum up, the GAM model is now in a phase that makes it ready for implementation and use on a regular (annual basis) for areas where its performance is satisfactory.

ETC/ATNI Report 15/2019: Factors affecting the CO2 emissions performance of five EU car manufacturers

Since 2010, the year that EEA started collecting data from all EU Member States, the officially reported CO2 tailpipe emissions of new passenger cars, based on laboratory testing, have reduced substantially. The scope of this report is to estimate and assess the most important technologies and strategies contributing to the observed CO2 reduction for selected car manufacturers based on new vehicles registered in the time period 2010 to 2018. These reductions can be attributed to both the overall improvement of vehicle energy efficiency as well as to a change in the mix of vehicle models sold in favour of more efficient powertrains/technologies. In particular, car manufacturers (OEMs) are using a broad spectrum of technologies to improve fuel efficiency for their vehicles in response to EU CO2 targets. In summary, these technologies can be grouped in the following major categories: • Internal combustion engine (ICE) related technologies (e.g. Downsizing/Turbocharging, Direct Injection) • Different degrees of hybridisation/electrification • Transmission technologies • Improved vehicle design and aerodynamics

ETC/ATNI Report 8/2019: Noise Action Plans. Managing exposure to noise in Europe.

The Environmental Noise Directive (END, Directive 2002/49/EC) sets legally binding obligations for reduction and management of environmental noise. Based upon noise mapping results, action plans have to be drawn up for major transport sources and the largest urban areas. However, the specific types of measures included in these action plans are decided at Member State level. This report provides an overview of the reported noise action plans up to April 2019, and the type of measures implemented to reduce environmental noise.

ETC/ATNI Report 10/2019: Status of quiet areas in European urban agglomerations

This report assess the available (potential) quiet areas in European cities and their accessibility. Information was obtained in two ways. The EEA Eionet network was activated and noise experts representing countries, regions and cities, were asked to complete an online questionnaire. In parallel, an analysis of availability and accessibility of quiet areas was undertaken using a combined spatial assessment of noise exposure and land use and land cover data for selected European cities.

ETC/ATNI Report 12/2019: The impact of vehicle taxations system on vehicle emissions

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.

ETC/ACM Report 2018/8: European air quality maps for 2016

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.

ETC/ACM report no. 2018/21 - Low cost sensor systems for air quality assessment: possibilities and challenges

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.

ETC/ATNI Report 3/2019: Noise exposure scenarios in 2020 and 2030 outlooks for EU 28

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

ETC/ATNI Report 1/2019: Noise indicators under the Environmental Noise Directive. Methodology for estimating missing data.

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.

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