Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt

Emissions and possible environmental implication of engineered nanomaterials (ENMs) in the atmosphere

In spite of the still increasing number of engineered nanomaterial (ENM) applications, large knowledge gaps exist with respect to their environmental fate, especially after release into air. This review aims to summarize the current knowledge of emissions and behavior of airborne engineered nanomaterials. The whole ENM lifecycle is considered from the perspective of possible releases into the atmosphere. Although in general, emissions during use phase and end-of-life seem to play a minor role compared to entry into soil and water, accidental and continuous emissions into air can occur especially during production and some use cases such as spray application. Implications of ENMs on the atmosphere as e.g., photo-catalytic properties or the production of reactive oxygen species are reviewed as well as the influence of physical processes and chemical reactions on the ENMs. Experimental studies and different modeling approaches regarding atmospheric transformation and removal are summarized. Some information exists especially for ENMs, but many issues can only be addressed by using data from ultrafine particles as a substitute and research on the specific implications of ENMs in the atmosphere is still needed

Impact of emissions of airborne TiO2 ENM on atmospheric NO2 concentrations

Titanium dioxide is one of the most produced engineered nanomaterials (ENMs) worldwide. Its high photocatalytic activity is key to many applications. Like any other ENM, TiO2 may be released into the atmosphere during nearly any phase of its lifecycle, where it may interact with atmospheric gases. It is well known and widely exploited that TiO2 photocatalytically reduces NO2 in the presence of UV light, however, the effect of accidentally released TiO2 ENMs on ambient NOx concentrations is widely unknown. We here present a comprehensive study on experimental laboratory investigations on the reaction rates of NO2 in the presence of TiO2 ENM (Evonik P25) under UV irradiation. The study is carried out in a dedicated test rig, where defined concentrations of TiO2 ENMs and NO2 are exposed to UV light. Both the UV light intensity and exposure time are adjustable. In a parallel study, the emission rates of engineered metal oxide nanomaterials from industrial facilities have been experimentally determined in field measurements and are used as surrogates for the TiO2 concentrations used in our lab-experiments. Experimental data on both the emission rates, as well as the chemical reaction rates, are used along with emission inventory data as input parameters for long range modeling of TiO2 and NOx concentrations across Europe using LOTOS-EUROS (see Figure 1) to better understand the dispersion of engineered nanomaterials and their impact on atmospheric chemistry. The poster will present results of the laboratory experiments and the field measurements and how these data are used in the model. First modeling results will be shown and it will be discussed how modeling can help improve the understanding of the presence and effects of engineered nanomaterials in the atmosphere

Trends of inorganic and organic aerosols and precursor gases in Europe: insights from the EURODELTA multi-model experiment over the 1990–2010 period

In the framework of the EURODELTA-Trends (EDT) modeling experiment, several chemical transport models (CTMs) were applied for the 1990–2010 period to investigate air quality changes in Europe as well as the capability of the models to reproduce observed long-term air quality trends. Five CTMs have provided modeled air quality data for 21 continuous years in Europe using emission scenarios prepared by the International Institute for Applied Systems Analysis/Greenhouse Gas – Air Pollution Interactions and Synergies (IIASA/GAINS) and corresponding year-by-year meteorology derived from ERA-Interim global reanalysis. For this study, long-term observations of particle sulfate (SO2−4 ), total nitrate (TNO3), total ammonium (TNHx) as well as sulfur dioxide (SO2) and nitrogen dioxide (NO2) for multiple sites in Europe were used to evaluate the model results. The trend analysis was performed for the full 21 years (referred to as PT) but also for two 11-year subperiods: 1990–2000 (referred to as P1) and 2000–2010 (referred to as P2). The experiment revealed that the models were able to reproduce the faster decline in observed SO2 concentrations during the first decade, i.e., 1990–2000, with a 64 %–76 % mean relative reduction in SO2 concentrations indicated by the EDT experiment (range of all the models) versus an 82 % mean relative reduction in observed concentrations. During the second decade (P2), the models estimated a mean relative reduction in SO2 concentrations of about 34 %–54 %, which was also in line with that observed (47 %). Comparisons of observed and modeled NO2 trends revealed a mean relative decrease of 25 % and between 19 % and 23 % (range of all the models) during the P1 period, and 12 % and between 22 % and 26 % (range of all the models) during the P2 period, respectively. Comparisons of observed and modeled trends in SO2−4 concentrations during the P1 period indicated that the models were able to reproduce the observed trends at most of the sites, with a 42 %–54 % mean relative reduction indicated by the EDT experiment (range of all models) versus a 57 % mean relative reduction in observed concentrations and with good performance also during the P2 and PT periods, even though all the models overpredicted the number of statistically significant decreasing trends during the P2 period. Moreover, especially during the P1 period, both modeled and observational data indicated smaller reductions in SO2−4 concentrations compared with their gas-phase precursor (i.e., SO2), which could be mainly attributed to increased oxidant levels and pH-dependent cloud chemistry. An analysis of the trends in TNO3 concentrations indicated a 28 %–39 % and 29 % mean relative reduction in TNO3 concentrations for the full period for model data (range of all the models) and observations, respectively. Further analysis of the trends in modeled HNO3 and particle nitrate (NO−3 ) concentrations revealed that the relative reduction in HNO3 was larger than that for NO−3 during the P1 period, which was mainly attributed to an increased availability of “free ammonia”. By contrast, trends in modeled HNO3 and NO−3 concentrations were more comparable during the P2 period. Also, trends of TNHx concentrations were, in general, underpredicted by all models, with worse performance for the P1 period than for P2. Trends in modeled anthropogenic and biogenic secondary organic aerosol (ASOA and BSOA) concentrations together with the trends in available emissions of biogenic volatile organic compounds (BVOCs) were also investigated. A strong decrease in ASOA was indicated by all the models, following the reduction in anthropogenic non-methane VOC (NMVOC) precursors. Biogenic emission data..

Modelling ultrafine particle number concentrations at address resolution in Denmark from 1979-2018 – Part 1: Regional and urban scale modelling and evaluation

The integrated model system DEHM/UBM/AirGIS, developed at Aarhus University, Department of Environmental Science, has been extended with the dynamic aerosol module M7 to account for particle number concentrations of particles with diameters below 1 μm in the atmosphere. The aim of this development is to quantify the spatial and temporal distribution of particle number concentration across Denmark and evaluate the results with available measurements. This article presents model results for particle number concentrations from the regional scale model DEHM and the urban scale model UBM, for comparison with measurements of particle number concentrations from European and Danish measurement stations. The deterministic modelling of particle number concentration has been vitiated by the lack of consistency between emission inventories, and the evaluation of the models is challenged by the lack of consistent long-term measurements data. The performance evaluation of the DEHM and UBM models shows that both models overestimate the level of the particle number concentrations at all stations, however, the results for the correlation coefficients are 0.86 for DEHM and in the range from 0.86 to 0.87, for UBM, for annual mean particle number concentrations at Danish measurement stations. We conclude that the inclusion of particle number concentration in DEHM and UBM shows some capability of reproducing observed patterns, when comparing the results of the models with available measurements, but that there is also room for improvement, especially with respect to the emission inventories and preprocessing of emissions and to the treatment of volatile organic compounds based on natural emissions during summer time

Long-term health impact assessment of total PM2.5 in Europe during the 1990-2015 period

International audience• PM 2.5 concentrations over Europe were used to perform a health impact assessment during the 1990-2015 period. • Population weighted PM 2.5 concentrations were predicted to have declined by 0.8 µg m −3 y −1 on average. • The number of premature deaths due to exposure to PM 2.5 was predicted to have declined during the 1990-2015 period. • The variability in the predicted number of premature deaths was higher in the 1990s compared to the 2000s

Eurodelta-Trends, a Multi-Model Experiment of Air Quality Hindcast in Europe over 1990-2010. Experiment Design and Key Findings

The Eurodelta-Trends multi-model chemistry-transport experiment has been designed to better understand the evolution of air pollution and its drivers for the period 1990-2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional scale air quality. The experiment is designed in three tiers with increasing degree of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000 and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions and (iii) meteorology complements it. The most demanding tier consists in two complete time series from 1990 to 2010, simulated using either time varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and six models have completed the 21-year trend simulations. The modelling results are publicly available for further use by the scientific community. We assess the skill of the models in capturing observed air pollution trends for the 1990-2010 time period. The average particulate matter relative trends are well captured by the models, even if they display the usual lower bias in reproducing absolute levels. Ozone trends are also well reproduced, yet slightly overestimated in the 1990s. The attribution study emphasizes the efficiency of mitigation measures in reducing air pollution over Europe, although a strong impact of long range transport is pointed out for ozone trends. Meteorological variability is also an important factor in some regions of Europe. The results of the first health and ecosystem impact studies impacts building upon a regional scale multi-model ensemble over a 20yr time period will also be presented

Trends of inorganic and organic aerosols and precursor gases in Europe : insights from the EURODELTA multi-model experiment over the 1990-2010 period

International audienceIn the framework of the EURODELTA-Trends (EDT) modeling experiment, several chemical transport models (CTMs) were applied for the 1990-2010 period to investigate air quality changes in Europe as well as the capability of the models to reproduce observed long-term air quality trends. Five CTMs have provided modeled air quality data for 21 continuous years in Europe using emission scenarios prepared by the International Institute for Applied Systems Analysis/Greenhouse Gas-Air Pollution Interactions and Synergies (IIASA/GAINS) and corresponding year-by-year meteorology derived from ERA-Interim global reanaly-sis. For this study, long-term observations of particle sulfate (SO 2− 4), total nitrate (TNO 3), total ammonium (TNH x) as well as sulfur dioxide (SO 2) and nitrogen dioxide (NO 2) for multiple sites in Europe were used to evaluate the model results. The trend analysis was performed for the full 21 years Published by Copernicus Publications on behalf of the European Geosciences Union. 4924 G. Ciarelli et al.: Trends of inorganic and organic aerosols and precursor gases in Europe (referred to as PT) but also for two 11-year subperiods: 1990-2000 (referred to as P1) and 2000-2010 (referred to as P2). The experiment revealed that the models were able to reproduce the faster decline in observed SO 2 concentrations during the first decade, i.e., 1990-2000, with a 64 %-76 % mean relative reduction in SO 2 concentrations indicated by the EDT experiment (range of all the models) versus an 82 % mean relative reduction in observed concentrations. During the second decade (P2), the models estimated a mean relative reduction in SO 2 concentrations of about 34 %-54 %, which was also in line with that observed (47 %). Comparisons of observed and modeled NO 2 trends revealed a mean relative decrease of 25 % and between 19 % and 23 % (range of all the models) during the P1 period, and 12 % and between 22 % and 26 % (range of all the models) during the P2 period, respectively. Comparisons of observed and modeled trends in SO 2− 4 concentrations during the P1 period indicated that the models were able to reproduce the observed trends at most of the sites, with a 42 %-54 % mean relative reduction indicated by the EDT experiment (range of all models) versus a 57 % mean relative reduction in observed concentrations and with good performance also during the P2 and PT periods , even though all the models overpredicted the number of statistically significant decreasing trends during the P2 period. Moreover, especially during the P1 period, both mod-eled and observational data indicated smaller reductions in SO 2− 4 concentrations compared with their gas-phase precursor (i.e., SO 2), which could be mainly attributed to increased oxidant levels and pH-dependent cloud chemistry. An analysis of the trends in TNO 3 concentrations indicated a 28 %-39 % and 29 % mean relative reduction in TNO 3 concentrations for the full period for model data (range of all the models) and observations, respectively. Further analysis of the trends in modeled HNO 3 and particle nitrate (NO − 3) concentrations revealed that the relative reduction in HNO 3 was larger than that for NO − 3 during the P1 period, which was mainly attributed to an increased availability of "free ammonia". By contrast, trends in modeled HNO 3 and NO − 3 concentrations were more comparable during the P2 period. Also, trends of TNH x concentrations were, in general, underpredicted by all models, with worse performance for the P1 period than for P2. Trends in modeled anthropogenic and biogenic secondary organic aerosol (ASOA and BSOA) concentrations together with the trends in available emissions of biogenic volatile organic compounds (BVOCs) were also investigated. A strong decrease in ASOA was indicated by all the models, following the reduction in anthropogenic non-methane VOC (NMVOC) precursors. Biogenic emission data provided by the modeling teams indicated a few areas with statistically significant increase in isoprene emissions and monoterpene emissions during the 1990-2010 period over Fennoscan-dia and eastern European regions (i.e., around 14 %-27 %), which was mainly attributed to the increase of surface temperature. However, the modeled BSOA concentrations did not linearly follow the increase in biogenic emissions. Finally , a comprehensive evaluation against positive matrix factorization (PMF) data, available during the second period (P2) at various European sites, revealed a systematic underestimation of the modeled SOA fractions of a factor of 3 to 11, on average, most likely because of missing SOA precursors and formation pathways, with reduced biases for the models that accounted for chemical aging of semi-volatile SOA components in the atmosphere

Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2

Date of Acceptance: 12/12/2014 Copyright The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/)Air pollution simulations critically depend on the quality of the underlying meteorology. In phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII-2), thirteen modeling groups from Europe and four groups from North America operating eight different regional coupled chemistry and meteorology models participated in a coordinated model evaluation exercise. Each group simulated the year 2010 for a domain covering either Europe or North America or both. Here were present an operational analysis of model performance with respect to key meteorological variables relevant for atmospheric chemistry processes and air quality. These parameters include temperature and wind speed at the surface and in the vertical profile, incoming solar radiation at the ground, precipitation, and planetary boundary layer heights. A similar analysis was performed during AQMEII phase 1 (Vautard etal., 2012) for offline air quality models not directly coupled to the meteorological model core as the model systems investigated here. Similar to phase 1, we found significant overpredictions of 10-m wind speeds by most models, more pronounced during night than during daytime. The seasonal evolution of temperature was well captured with monthly mean biases below 2K over all domains. Solar incoming radiation, precipitation and PBL heights, on the other hand, showed significant spread between models and observations suggesting that major challenges still remain in the simulation of meteorological parameters relevant for air quality and for chemistry-climate interactions at the regional scale.Peer reviewedFinal Published versio