Eurodelta multi-model simulated and observed particulate matter trends in Europe in the period of 1990-2010

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990-2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000-2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty.The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) mu g m(-3) (or between 10 % and 30 %) across most of Europe (by 0.5-2 mu g m(-3) in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large interannual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %-40 % over most of Europe, increasing to 50 %-60 % in the northern and eastern parts of the EDT domain.Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are - 0.24 and -0.22 mu g m(-3) yr(-1) for PM10 and PM2.5, which are somewhat weaker than the observed trends of - 0.35 and -0.40 mu g m(-3) yr(-1) respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are -1.7 % yr(-1) and -2.0 % yr(-1) from the model ensemble and -2.1 % yr(-1) and -2.9 % yr(-1) from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries.The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located.The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in SO42- concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of NH4+ and NO3- to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appear to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties (including the implications of not accounting for forest fires and natural mineral dust by some of the models) and the effect of inter-annual meteorological variability on the trend analysis.Peer reviewe

Assessment of the sensitivity of model responses to urban emission changes in support of emission reduction strategies

© 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The sensitivity of air quality model responses to modifications in input data (e.g. emissions, meteorology and boundary conditions) or model configurations is recognized as an important issue for air quality modelling applications in support of air quality plans. In the framework of FAIRMODE (Forum of Air Quality Modelling in Europe, https://fairmode.jrc.ec.europa.eu/) a dedicated air quality modelling exercise has been designed to address this issue. The main goal was to evaluate the magnitude and variability of air quality model responses when studying emission scenarios/projections by assessing the changes of model output in response to emission changes. This work is based on several air quality models that are used to support model users and developers, and, consequently, policy makers. We present the FAIRMODE exercise and the participating models, and provide an analysis of the variability of O3 and PM concentrations due to emission reduction scenarios. The key novel feature, in comparison with other exercises, is that emission reduction strategies in the present work are applied and evaluated at urban scale over a large number of cities using new indicators such as the absolute potential, the relative potential and the absolute potency. The results show that there is a larger variability of concentration changes between models, when the emission reduction scenarios are applied, than for their respective baseline absolute concentrations. For ozone, the variability between models of absolute baseline concentrations is below 10%, while the variability of concentration changes (when emissions are similarly perturbed) exceeds, in some instances 100% or higher during episodes. Combined emission reductions are usually more efficient than the sum of single precursor emission reductions both for O3 and PM. In particular for ozone, model responses, in terms of linearity and additivity, show a clear impact of non-linear chemistry processes. This analysis gives an insight into the impact of model’ sensitivity to emission reductions that may be considered when designing air quality plans and paves the way of more in-depth analysis to disentangle the role of emissions from model formulation for present and future air quality assessments.Peer reviewe

Air pollution trends in the EMEP region between 1990 and 2012

The present report synthesises the main features of the evolution over the 1990-2012 time period of the concentration and deposition of air pollutants relevant in the context of the Convention on Long-range Transboundary Air Pollution: (i) ozone, (ii) sulfur and nitrogen compounds and particulate matter, (iii) heavy metals and persistent organic pollutants. It is based on observations gathered in State Parties to the Convention within the EMEP monitoring network of regional background stations, as well as relevant modelling initiatives. Joint Report of: EMEP Task Force on Measurements and Modelling (TFMM), Chemical Co-ordinating Centre (CCC), Meteorological Synthesizing Centre-East (MSC-E), Meteorological Synthesizing Centre-West (MSC-W)

EuroDelta phase 3: an intercomparison of 7 european chemistry-transport models against observations from 4 EMEP measurement campaigns

In the frame of the UNECE Task Force on Measurement and Modelling (TFMM) under the Convention on Long-Range Transboundary Air Pollution (CLRTAP), the EuroDelta project (phase 1) was initiated in 2004 with a validation study of models against observational data. In phase 2 of the project the focus was on the impact of sectorwise emission reductions on the quality of air in Europe. The third phase of EuroDelta builds upon the methodology of the earlier phases. The objective of this phase is to analyse the behaviour of models on 4 EMEP intensive 1-month measurement campaigns which took place in 2009, 2008, 2007 and 2006. In particular we focus on the behaviour of the EMEP model, which is the official model of the CLRTAP Convention and involved in the EU air quality policy making process. The results of this model intercomparison are presented in terms of model performances for regulatory pollutants and also for Particulate Matter (PM) components and their precursors. To better assess the ability of models to simulate the physical and chemical processes, the results are analyzed on hourly and daily bases. The meteorology is also assessed. The 7 chemistry-transport models (EMEP, CHIMERE, LOTOS, RCGC, CAMX, MINNI, CMAQ) were run over the 4 campaigns and analyzed using the DeltaTool, a Tool for validation and benchmarking developed at the JRC-Ispra in the frame of FAIRMODE. Apart from the model-observation comparisons for the 4 campaigns, we will shortly discuss near-future EuroDelta activities on the retrospective analysis, and on trend analysis

Multi-model assessment of PM trends in europe during two decades (1990-2010)

The model trend analysis for PM10 and PM2.5, performed within the Eurodelta-Trends experiment, covers 21 year, from 1990 through 2010, with particular focus on the period 2001-2010 for which appropriate amount of PM observations is available. Eight chemical transport models (CTM) participated in the multi-modal trend analysis: EMEP/MSC-W, CHIMERE, LOTOS-EUROS, MINNI, MATCH, WRF-Chem, CMAQ and Polyphemus (out of which six models performed trend runs for the 21-year period). The average modelled trends are somewhat smaller than the observed, though the models identify significant PM trends at more sites in the period 2001-2010. There are considerable difference in the PM trends between the regions/countries and in different seasons. Investigation of the changes in PM chemical composition during the investigated period shows that the models differ in terms of relative contribution of the individual PM components to the PM trends. For the 2001-2010 period, the effcct of inter-annual meteorological variability appears more important relative to emission changes. Finally, we look at PM trends/changes during the 1990-2010 period

Overview of EURODELTA-TRENDS, the air quality Hindcast modelling exercise

A multi-model exercise has been set up by the Task Force on Measurement and Modelling of the Convention on Long-Range Transboundary of Air Pollution in order to assess the evolution of air quality in Europe since the early 1990s. The main science and policy question addressed by the exercise is to assess the efficiency of emission mitigation measures in improving the air quality at the continental scale. It is also expected that EURODELTA-TRENDS will better quantify (i) the capability of models (and underlying emission inventories) in simulating the long term evolution of air quality, (ii) the importance of intercontinental transport of air pollution through the boundary conditions of the regional models, (iii) the role of interannual meteorological variability. In order to cover a range of uncertainty, in addition to the model being used in support to the Convention (EMEP/MSC-W), six chemistry transport models participated to the exercise: Chimere, CMAQ, LOTOS-EUROS, MINNI, Polyphemus and WRF-CHEM. The modelling experiment is organised in three tiers: (i) a reference for the years 1990, 2000 and 2010, including also sensitivity simulations devoted to emission changes, (ii) six sensitivity simulations for boundary condition changes, (iii) full modelling of the complete 21-yr time series for 1990 to 2010. An overview of the experiment will be given as well as key results in terms of (i) trend modelling benchmarking and (ii) attribution of the main factors underlying the evolution over the past 20 years of particulate matter, ozone, and also acidifying and eutrophying pollution in Europe

Biogenic Emissions in the Mediterranean Area. An Overview of BEMA-Phase II (1996-97).

Abstract not availableJRC.(EI)-Environment Institut

Eurodelta multi-model simulated and observed particulate matter trends in Europe in the period of 1990–2010

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty. The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) µg m−3 (or between 10 % and 30 %) across most of Europe (by 0.5–2 µg m−3 in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %–40 % over most of Europe, increasing to 50 %–60 % in the northern and eastern parts of the EDT domain. Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are −0.24 and −0.22 µg m−3 yr−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 µg m−3 yr−1 respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 % yr−1 and −2.0 % yr−1 from the model ensemble and −2.1 % yr−1 and −2.9 % yr−1 from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries. The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located. The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in concentrations playing an overall dominant role. Also, we see..