Found 10481 publications. Showing page 91 of 420:
2021
Potential use of CAMS modelling results in air quality mapping under ETC/ATNI
ir quality European-wide annual maps based on the Regression – Interpolation – Merging Mapping (RIMM) data fusion methodology have been regularly produced, using the Air Quality e-Reporting validated (E1a) monitoring data, the EMEP modelling data and other supplementary data. In this report, we examine the use of the preliminary (E2a) monitoring data as provided up-to-date (UTD) by many European countries and as also stored in the Air Quality e-Reporting database, together with the EMEP or the Copernicus Atmospheric Monitoring Service (CAMS) modelling data in two variants (i.e. CAMS Ensemble Interim Reanalysis and CAMS Ensemble Forecast) for potential preparing of preliminary spatial maps. With respect to the availability, the CAMS Ensemble Forecast is the most useful in the potential interim mapping. Such preliminary maps could be constructed approximately one year earlier than the validated maps. Even though we have demonstrated the feasibility, the mapping performance presented in the report is influenced by the lack of the E2a data in some areas.
Next to the evaluation of potential interim maps, regular RIMM maps based on the validated E1a measurement data using three different chemical transport model outputs have been compared, i.e. using the CAMS Ensemble Forecast, the CAMS Ensemble Interim Reanalysis and the EMEP model outputs. Based on the evaluation of the results presented, it is not possible to conclude that any of the three model datasets gives definitively better results compared to the others. The results do not provide strong reasons for a potential change of the model used in the regular mapping.
In addition, the RIMM mapping results have been compared with the CAMS Ensemble Forecast and the CAMS Ensemble Interim Reanalysis outputs. The comparison shows that the data fusion RIMM method gives better results, both in the rural and urban background areas, presumably because of the higher spatial resolution, introduction of additional ancillary data in the data fusion and not fully reduced bias in some data assimilation methods used in CAMS.
ETC/ATNI
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Long-term trends of air pollutants at national level 2005-2019
Trend calculations of air pollutants for the periods 2005-2019 have been applied. Sulphur dioxide shows the largest decrease of all pollutants with a reduction of the order of 60-70 %. The agreement between reported emission data and measured concentrations are quite good. For NO2, a mismatch between the trend in air concentrations and NOx emissions is found. While the overall NOx emissions are reported to be reduced by 45 %, the measured NO2 data indicate a decline of the order of 30 % although marked differences between the countries are found. This mismatch could not be explained by changes in meteorology as this is accounted for. Possible reasons for the mismatch could be the NO2/NOx ratio of the emissions, changes in baseline hemispheric ozone concentration and natural emissions. For PM data (PM10 and PM2.5) we find an opposite mismatch, meaning that the PM concentrations show stronger downward trends than the reported emissions. This is likely an effect of the importance of secondary aerosols which are mitigated by other activities than the direct PM emissions. An overall reduction in PM10 of the order of 30-38 % is found during 2005-2019 while the direct emissions give a reduction that is 5-10 percentage units smaller. Similar results are found for PM2.5, but these findings are uncertain due to the less amount of long-term data. For O3, our findings are in line with earlier studies noting that the annual mean ozone concentration has increased while the high peaks have been reduced. But the reduction of the peaks is now within only a few percent and non-significant, while for the 2000-2017 period it was significant and about 10%.
ETC/ATNI
2021
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