Impact of Grid Resolution on Aerosol Predictions: A Case Study over Italy

Mircea, Mihaela; Grigoraș, Georgiana; D’Isidoro, Massimo; Righini, Gaia; Adani, Mario; Briganti, Gino; Ciancarella, Luisella; Cappelletti, Andrea; Calori, G.; Cionni, Irene; Cremona, Giuseppe; Finardi, S.; Larsen, B.; Pace, Giandomenico; Perrino, Cinzia; Piersanti, Antonio; Silibello, Camillo; Vitali, Lina; Zanini, Gabriele

doi:10.4209/aaqr.2015.02.0058

Cited by 35 publications

(16 citation statements)

References 18 publications

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“…Eight state-of-the-art air quality CTMs delivered their results for the EDT experiments: CHIMERE (Mailler et al, 2017;Menut et al, 2013), CMAQ (Byun and Schere, 2006), EMEP MSC-W (Simpson et al, 2012), LOTOS-EUROS (Manders et al, 2017;Schaap et al, 2008), MATCH (Andersson et al, 2015(Andersson et al, , 2007Robertson et al, 1999), MINNI (Mircea, 2016), Polyphemus (Mallet et al, 2007;Sartelet et al, 2012) and WRF-Chem (Grell et al, 2005;Mar et al, 2016). Given the large computational demand of the simulations, only five modeling teams were able to deliver 21 years of continuous air modeled data: CHIMERE, EMEP MSC-W, LOTOS-EUROS, MATCH and MINNI, the results of which are used in this study.…”

Section: Description Of the Participating Modelsmentioning

confidence: 99%

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

Ciarelli¹,

Theobald²,

Vivanco³

et al. 2019

Preprint

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Abstract. 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 twenty-one continuous years in Europe using emission scenarios prepared by IIASA/GAINS and corresponding year-by-year meteorology derived from ERA-interim global reanalysis. For this study, long-term observations of particle sulfate (SO42−), total nitrate (TNO3), total ammonium (TNHx) as well as sulfur dioxide (SO2) and nitrogen dioxide (NO2) for multiple sites in Europe were used to validate the model results. The trends analysis was performed for the full twenty-one years (referred to as PT), but also for two 11-year sub-periods: 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 19–23 % (range of all the models) during the P1 period, and 12 % and between 22–26 % (range of all the models) during the P2 period, respectively. Comparisons of observed and modeled trends in SO42− 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 performances also during the P2 and PT periods. Moreover, especially during the P1 period, both modeled and observational data indicated smaller reductions in SO42− concentrations compared with its 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 (NO3−) concentrations revealed that the relative reduction in HNO3 was larger than that for NO3− during the P1 period, which was mainly attributed to an increased availability of “free-ammonia”. By contrast, trends in modeled HNO3 and NO3− concentrations were more comparable during the P2 period. Also, trends of TNHx concentrations were, in general, under-predicted by all models, with worst 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 NMVOCs precursors. Biogenic emission data provided by the modeling teams indicated a few areas with statistically significant increase in isoprene emission and monoterpene emissions during the 1990–2010 period over Fennoscandia 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 under-estimation of the modeled SOA fractions of between 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.

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Section: Description Of the Participating Modelsmentioning

confidence: 99%

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

Ciarelli¹,

Theobald²,

Vivanco³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…A set of state-of-the-art air-quality models participating in the EDT exercise is used here: LOTOS-EUROS (Schaap et al, 2008;Manders et al, 2017), EMEP/MSC-W (Simpson et al, 2012), CHIMERE (Mailler et al, 2017), MATCH (Robertson et al, 1999) and MINNI (Mircea et al, 2016 Colette et al, 2017a for further details). For instance, the boundary conditions were defined from a climatology of observational data for most of the experiments of the EDT exercise (including the data used here).…”

Section: Chemistry Transport Models (Ctms)mentioning

confidence: 99%

“…ME, NI, or FR) where MLRs are able to describe more than 80 % of the variance in CTMs and observations. This could be attributed to the major role of meteorology in summer influencing local photochemistry processes of ozone production, while in spring long-range transport plays a stronger role (Monks, 2000;Tarasova et al, 2007). As it includes the bias, the RMSE reveals more differences among the MLRs when compared to each other (e.g.…”

Section: Mlr Performancementioning

confidence: 99%

A multi-model comparison of meteorological drivers of surface ozone over Europe

et al. 2018

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Abstract. The implementation of European emission abatement strategies has led to a significant reduction in the emissions of ozone precursors during the last decade. Ground-level ozone is also influenced by meteorological factors such as temperature, which exhibit interannual variability and are expected to change in the future. The impacts of climate change on air quality are usually investigated through air-quality models that simulate interactions between emissions, meteorology and chemistry. Within a multi-model assessment, this study aims to better understand how air-quality models represent the relationship between meteorological variables and surface ozone concentrations over Europe. A multiple linear regression (MLR) approach is applied to observed and modelled time series across 10 European regions in springtime and summertime for the period of 2000–2010 for both models and observations. Overall, the air-quality models are in better agreement with observations in summertime than in springtime and particularly in certain regions, such as France, central Europe or eastern Europe, where local meteorological variables show a strong influence on surface ozone concentrations. Larger discrepancies are found for the southern regions, such as the Balkans, the Iberian Peninsula and the Mediterranean basin, especially in springtime. We show that the air-quality models do not properly reproduce the sensitivity of surface ozone to some of the main meteorological drivers, such as maximum temperature, relative humidity and surface solar radiation. Specifically, all air-quality models show more limitations in capturing the strength of the ozone–relative-humidity relationship detected in the observed time series in most of the regions, for both seasons. Here, we speculate that dry-deposition schemes in the air-quality models might play an essential role in capturing this relationship. We further quantify the relationship between ozone and maximum temperature (mo3−T, climate penalty) in observations and air-quality models. In summertime, most of the air-quality models are able to reproduce the observed climate penalty reasonably well in certain regions such as France, central Europe and northern Italy. However, larger discrepancies are found in springtime, where air-quality models tend to overestimate the magnitude of the observed climate penalty.

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“…The model was validated for both meteorological parameters and pollutant concentration. For further details on the emission inventories, domains, input data, and model set-up, see [24,54]. In the context of the present paper the pollutant concentrations simulated with the AMS-MINNI model provide continuous, well-spaced and representative air concentrations that are not available from measurements.…”

Section: Air Pollutant Concentrationmentioning

confidence: 99%

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

et al. 2017

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This study is the follow up of the URBAN-MAES pilot implemented in the framework of the EnRoute project. The study aims at mapping and assessing the process of particulate matter (PM 10 ) and tropospheric ozone (O 3 ) removal by various forest and shrub ecosystems. Different policy levels and environmental contexts were considered, namely the Metropolitan city of Rome and, at a wider level, the Latium region. The approach involves characterization of the main land cover and ecosystems using Sentinel-2 images, enabling a detailed assessment of Ecosystem Service (ES), and monetary valuation based on externality values. The results showed spatial variations in the pattern of PM 10 and O 3 removal inside the Municipality and in the more rural Latium hinterland, reflecting the spatial dynamics of the two pollutants. Evergreen species displayed higher PM 10 removal efficiency, whereas deciduous species showed higher O 3 absorption in both rural and urban areas. The overall pollution removal accounted for 5123 and 19,074 Mg of PM 10 and O 3 , respectively, with a relative monetary benefit of 161 and 149 Million Euro for PM 10 and O 3 , respectively. Our results provide spatially explicit evidence that may assist policymakers in land-oriented decisions towards improving Green Infrastructure and maximizing ES provision at different governance levels.

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Impact of Grid Resolution on Aerosol Predictions: A Case Study over Italy

Cited by 35 publications

References 18 publications

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

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

A multi-model comparison of meteorological drivers of surface ozone over Europe

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

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