High resolution air quality simulation over Europe with the chemistry transport model CHIMERE

Abstract. A high resolution air quality simulation (0.125° × 0.0625° horizontal resolution) performed over Europe for the year 2009 has been evaluated using both rural and urban background stations available over most of the domain. Using seasonal and yearly mean statistical indicators such as the correlation index, the fractional bias and the root mean squared error; we interpret objectively the performance of the simulation. Positive outcomes are: a very good reproduction of the daily variability at UB sites for O3 (R =0.73) as well as for NO2 (R =0.61); a very low bias calculated at UB stations for PM2.5 (FB = −6.4%) and PM10 concentrations (FB = −20.1%). Conversely, main weaknesses in model performance include: the underestimation of the NO2 daily maxima at UB site (FB = −53.6%); an overall underestimation of PM10 and PM2.5 concentrations observed over Eastern European countries (e.g. Poland); the overestimation of sulphates concentrations at spring time (FB = 53.7%); finally, over the year, total nitrate and ammonia concentrations are better reproduced than nitrate and ammonium aerosol phase compounds. Obtained results suggest that, in order to improve the model performances, efforts should focus on the improvement of the emission inventory quality for Eastern Europeans countries and the improvement of a specific parameterisation in the model to better account for the urban effect on meteorology and air pollutants concentrations.

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Air quality forecasts at kilometer scale grid over Spanish complex terrains

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-2293-2014 ◽

2014 ◽

Vol 7 (2) ◽

pp. 2293-2334 ◽

Cited By ~ 2

Author(s):

M. T. Pay ◽

F. Martínez ◽

M. Guevara ◽

J. M. Baldasano

Keyword(s):

Air Quality ◽

High Resolution ◽

High Performance ◽

Current Model ◽

Model Performance ◽

Correlation Coefficients ◽

Horizontal Resolution ◽

Urban Morphology ◽

Expected Improvement ◽

Computing Platforms

Abstract. CALIOPE-AQFS represents the current state-of-the-art in air quality forecasting systems running at high resolution over high performance computing platforms. It provides 48 h forecast of main pollutants over Spain at 4 km horizontal resolution, and over the most populated areas with complex terrains in Spain (Barcelona, Madrid and Andalucia domains) at 1 km. Increased horizontal resolution from 4 km to 1 km over the aforementioned domains leads to finer texture and more realistic concentration maps, justified by the increase of NO2/O3 spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High resolution emissions using the bottom-up HERMESv2.0 model are essential to improve the model performance when increasing resolution at urban scale, but it is not sufficient. Decreasing grid spacing does not reveal the expected improvement on hourly statistics, decreasing NO2 bias only in ~ 2 μg m−3 and increasing O3 bias in ~ 1 μg m−3. The grid effect is less pronounced for PM10 because part of its mass consists of secondary aerosols which are less affected by a decreasing grid size in contrast to the locally emitted primary components. The resolution increase has the highest impact over Barcelona, where air flow is mainly controlled by mesoscale phenomena and a lower PBL. Despite the merits and potential uses of the 1 km simulation, the limitations of current model formulations do not allow confirming their expected superiority close to highly urbanized areas and large sources. Future work should combine high grid resolution with techniques that decrease subgrid variability and models that consider urban morphology and thermal parameters.

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Air quality forecasts on a kilometer-scale grid over complex Spanish terrains

Geoscientific Model Development ◽

10.5194/gmd-7-1979-2014 ◽

2014 ◽

Vol 7 (5) ◽

pp. 1979-1999 ◽

Cited By ~ 11

Author(s):

M. T. Pay ◽

F. Martínez ◽

M. Guevara ◽

J. M. Baldasano

Keyword(s):

Air Quality ◽

High Resolution ◽

Current Model ◽

Model Performance ◽

Horizontal Resolution ◽

Urban Morphology ◽

Expected Improvement ◽

Stochastic Field ◽

Field Methods ◽

Air Quality Forecast

Abstract. The CALIOPE Air Quality Forecast System (CALIOPE-AQFS) represents the current state of the art in air quality forecasting systems of high-resolution running on high-performance computing platforms. It provides a 48 h forecast of NO2, O3, SO2, PM10, PM2.5, CO, and C6H6 at a 4 km horizontal resolution over all of Spain, and at a 1 km horizontal resolution over the most populated areas in Spain with complex terrains (the Barcelona (BCN), Madrid (MAD) and Andalusia (AND) domains). Increased horizontal resolution from 4 to 1 km over the aforementioned domains leads to finer textures and more realistic concentration maps, which is justified by the increase in NO2/O3 spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High-resolution emissions using the bottom-up HERMESv2.0 model are essential for improving model performance when increasing resolution on an urban scale, but it is still insufficient. Decreasing grid spacing does not reveal the expected improvement in hourly statistics, i.e., decreasing NO2 bias by only ~ 2 μg m−3 and increasing O3 bias by ~ 1 μg m−3. The grid effect is less pronounced for PM10, because part of its mass consists of secondary aerosols, which are less affected than the locally emitted primary components by a decreasing grid size. The resolution increase has the highest impact over Barcelona, where air flow is controlled mainly by mesoscale phenomena and a lower planetary boundary layer (PBL). Despite the merits and potential uses of the 1-km simulation, the limitations of current model formulations do not allow confirmation of their expected superiority close to highly urbanized areas and large emissions sources. Future work should combine high grid resolutions with techniques that decrease subgrid variability (e.g., stochastic field methods), and also include models that consider urban morphology and thermal parameters.

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Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽

10.3390/atmos12010091 ◽

2021 ◽

Vol 12 (1) ◽

pp. 91

Author(s):

Santiago Lopez-Restrepo ◽

Andres Yarce ◽

Nicolás Pinel ◽

O.L. Quintero ◽

Arjo Segers ◽

...

Keyword(s):

Air Quality ◽

Data Assimilation ◽

Transport Model ◽

Cost Model ◽

Low Cost ◽

Model Performance ◽

Monitoring Network ◽

Correlation Factor ◽

Chemical Transport Model ◽

High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

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Modeled based analysis of fish farm emissions impact on the fjord biogeochemistry

10.5194/egusphere-egu2020-19794 ◽

2020 ◽

Author(s):

Evgeniy Yakushev ◽

Anfisa Berezina

Keyword(s):

Organic Matter ◽

Transport Model ◽

Model Performance ◽

Oxygen Depletion ◽

Horizontal Resolution ◽

Fish Farm ◽

Transformation Model ◽

Model Data ◽

Sulfur Reduction ◽

Satisfactory Model

To investigate the impacts of fish farm emissions, we coupled the biogeochemical C-N-P-Si-O-S-Mn-Fe transformation model BROM with a 2-Dimensional Benthic-Pelagic transport model (2DBP), considering vertical and horizontal transport in the water and upper 5 cm&#160; sediments along a 10000 m transect centered on a fish farm. The 2DBP model had 25 m horizontal resolution and was forced by hydrophysical model data for the Hardangerfjord in western Norway. The model predicted significant impacts on seafloor biogeochemistry up to 500 meters from the fish farm (e.g., increased organic matter in sediments, oxygen depletion in water and sediments, denitrification, metal and sulfur reduction) as well as detectable decreases in oxygen and increases in ammonia, phosphate and organic matter in the water near to the fish farm cages. The model results are compared with field data from the Hardangerfjord in August 2016 and indicated satisfactory model performance.

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HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR. Description, model performance, data handling and validation

10.5194/gmd-2019-350 ◽

2020 ◽

Cited By ~ 11

Author(s):

Rein Haarsma ◽

Mario Acosta ◽

Rena Bakhshi ◽

Pierre-Antoine Bretonnière Bretonnière ◽

Louis-Philippe Caron ◽

...

Keyword(s):

High Resolution ◽

Data Storage ◽

Climate Model ◽

Southern Oscillation ◽

Model Performance ◽

Warming Trend ◽

Horizontal Resolution ◽

Performance Data ◽

Coupled Climate Model ◽

Historical Simulation

Abstract. A new global high-resolution coupled climate model, EC-Earth3P-HR has been developed by the EC-Earth consortium, with a resolution of approximately 40 km for the atmosphere and 0.25 degree for the ocean, alongside with a standard resolution version of the model, EC-Earth3P (80 km atmosphere, 1.0 degree ocean). The model forcing and simulations follow the HighResMIP protocol. According to this protocol all simulations are made with both high and standard resolutions. The model has been optimized with respect to scalability, performance, data-storage and post-processing. In accordance with the HighResMIP protocol no specific tuning for the high resolution version has been applied. Increasing horizontal resolution does not result in a general reduction of biases and overall improvement of the variability, and deteriorating impacts can be detected for specific regions and phenomena such as some Euro-Atlantic weather regimes, whereas others such as El Niño-Southern Oscillation show a clear improvement in their spatial structure. The omission of specific tuning might be responsible for this. The shortness of the spin-up, as prescribed by the HighResMIP protocol, prevented the model to reach equilibrium. The trend in the control and historical simulations, however, appeared to be similar, resulting in a warming trend, obtained by subtracting the control from the historical simulation, close to the observational one.

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Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-4319-2013 ◽

2013 ◽

Vol 13 (8) ◽

pp. 4319-4337 ◽

Cited By ~ 27

Author(s):

È. Lecœur ◽

C. Seigneur

Keyword(s):

Air Quality ◽

Wind Speed ◽

Transport Model ◽

Model Simulation ◽

Model Performance ◽

Monitoring And Evaluation ◽

The Other ◽

Chemical Transport Model ◽

Performance Goal ◽

Dynamic Evaluation

Abstract. A 9 yr air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP). The spatial distribution of PM2.5 over Europe shows high concentrations over northern Italy (36 μg m−3) and some areas of Eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM2.5 composition differs among regions. The operational evaluation shows satisfactory model performance for ozone (O3). PM2.5, PM10, and sulfate (SO4=) meet the performance goal of Boylan and Russell (2006). Nitrate (NO3−) and ammonium (NH4+) are overestimated, although NH4+ meets the performance criterion. The correlation coefficients between simulated and observed data are 63% for O3, 57% for PM10, 59% for PM2.5, 57% for SO4=, 42% for NO3−, and 58% for NH4+. The comparison with other recent 1 yr model simulations shows that all models overestimate nitrate. The performance of PM2.5, sulfate, and ammonium is comparable to that of the other models. The dynamic evaluation shows that the response of PM2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM2.5 and its components (except for sea salt, which shows a positive correlation), which tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM2.5 and its components are better reproduced by the model than the effects of temperature. This is mainly due to the fact that temperature has different effects on the PM2.5 components, unlike precipitation and wind speed, which impact most of the PM2.5 components in the same way. These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM2.5 and therefore are suitable to investigate the effects of climate change on particulate air quality, although uncertainties remain concerning semivolatile PM2.5 components.

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Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-475-2013 ◽

2013 ◽

Vol 13 (1) ◽

pp. 475-526

Author(s):

È. Lecœur ◽

C. Seigneur

Keyword(s):

Air Quality ◽

Wind Speed ◽

Transport Model ◽

Model Simulation ◽

Model Performance ◽

The Other ◽

Performance Criteria ◽

Chemical Transport Model ◽

Performance Goal ◽

Dynamic Evaluation

Abstract. A nine-year air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP). The spatial distribution of PM2.5 over Europe shows high concentrations over northern Italy (36 μg m−3) and some areas of eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM2.5 composition differs among regions. The operational evaluation shows satisfactory model performance for ozone (O3). PM2.5, PM10, and sulfate (SO42−) meet the performance goal of Boylan and Russell (2006). Nitrate (NO3−) and ammonium (NH4+) are overestimated, although NH4+ meets the performance criteria. The correlation coefficients between simulated and observed data are 63% for O3, 57% for PM10, 59% for PM2.5, 57% for SO42−, 42% for NO3−, and 58% for NH4+. The comparison with other recent one-year model simulations shows that all models overestimate nitrate. The performance of PM2.5, sulfate, and ammonium is comparable to that of the other models. The dynamic evaluation shows that the response of PM2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM2.5 and its components (except for sea salt, which shows a positive correlation), that tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM2.5 and its components are better reproduced by the model than the effects of temperature. This is mainly due to the fact that temperature has different effects on the PM2.5 components, unlike precipitation and wind speed which impact most of the PM2.5 components in the same way. These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM2.5 and, therefore, are suitable to investigate the effects of climate change on particulate air quality.

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Downscaling of air pollutants in Europe using uEMEP_v6

10.5194/gmd-2021-198 ◽

2021 ◽

Author(s):

Qing Mu ◽

Bruce Rolstad Denby ◽

Eivind Grøtting Wærsted ◽

Hilde Fagerli

Keyword(s):

Air Quality ◽

High Resolution ◽

Spatial Correlation ◽

Transport Model ◽

Chemical Transport Model ◽

Proxy Data ◽

Linear Processes ◽

Frequency Distributions ◽

Non Linear ◽

Pm2.5 And Pm10

Abstract. The air quality downscaling model uEMEP and its combination with the EMEP MSC-W chemical transport model are used here to achieve high-resolution air quality modeling at street level in Europe. By using publicly available proxy data, this uEMEP/EMEP modelling system is applied to calculate annual mean NO2, PM2.5, PM10 and O3 concentrations for all of Europe down to 100 m resolution and is validated against all available Airbase monitoring stations in Europe at 25 m resolution. Downscaling is carried out on annual mean concentrations, requiring special attention to non-linear processes, such as NO2 chemistry, where frequency distributions are applied to better represent the non-linear NO2 chemistry. The downscaling shows significant improvement in NO2 concentrations where spatial correlation has been doubled for most countries and bias reduced from −46 % to −18 % for all stations in Europe. The downscaling of PM2.5 and PM10 does not show improvement in spatial correlation but does reduce the overall bias in the European calculations from −21 % to −11 % and from −39 % to −30 % for PM2.5 and PM10 respectively. There is improved spatial correlation in most countries after downscaling of O3, and a reduced positive bias of O3 concentrations from +16 % to +11 %. Sensitivity tests in Norway show that improvements in the emission and emission proxy data used for the downscaling can significantly improve both the NO2 and PM results. The downscaling development opens the way for improved exposure estimates, improved assessment of emissions as well as detailed calculations of source contributions to exceedances in a consistent way for all of Europe at high resolution.

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Evaluation of NO2, O3, PM10, and PM2.5 in the city of Buenos Aires, Argentina using WRF-Chem model

10.5194/egusphere-egu21-1514 ◽

2021 ◽

Author(s):

Ana Isabel Lopez-Noreña ◽

Lucas Berná ◽

María Florencia Tames ◽

Emmanuel Millán ◽

Enrique Puliafito ◽

...

Keyword(s):

Air Quality ◽

High Resolution ◽

Buenos Aires ◽

Model Performance ◽

Performance Criteria ◽

Quality Analysis ◽

Modeling Tools ◽

Pm10 And Pm2.5 ◽

The Mean ◽

The Impact

The online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem v4.0), was applied to evaluate the impact of using different anthropogenic emissions inventories on regional air quality in Argentina. For this purpose, we couple the Argentinian high-resolution emissions inventory (GEAA-AHRI) and the Emissions Database for Global Atmospheric Research &#8211; Hemispheric Transport of Air Pollution (EDGAR-HTAP) and introduce them into the model, with a local optimized configuration considering 3 nested domains with a horizontal grid size of 20 x 20 km, 4 x 4 km, and 1.3 x 1.3 km and the MOZART chemical scheme. The model output for NO2, PM10, PM2.5, and O3 concentrations over the innermost domain was compared against the existing surface and satellite-derived observations for the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. We found an overall good model performance for all simulations, and large discrepancies between the emission inventories, obtaining an improved urban-scale spatio-temporal representation when the high resolution GEAA-AHRI dataset is considered. Our results show that the daytime concentrations of air pollutants are strongly influenced by the shape and shift of the hourly emissions profile before sunrise and after sunset, especially for NO2 where the inclusion of the temporal profile decreased the mean bias by ~80%. Performance criteria for modeled PM10 and PM2.5 were in general satisfied, despite having an average underestimation of observations. When compared to NO2 tropospheric columns derived from TROPOMI, The general magnitude and spatial pattern of the NO2 tropospheric column is in agreement with the mean TROPOMI columns during the modeled period, obtaining correlation coefficients higher than 0.6 for all simulations. Our results highlight the benefits of using a time-dependent and high-resolution local inventory for addressing the background air quality in AMBA. The implementation and validation of local emissions and static fields with high spatial and temporal resolution carried out in this work, establishes a benchmark for forthcoming studies in other regions of South America where different modeling tools for air quality analysis are currently being used to complement the usually sparse and discontinuous air quality networks.

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Development of a high-resolution air quality forecasting system, based on WRF-Chem model, for the greater area of Thessaloniki, Greece

10.5194/egusphere-egu2020-21296 ◽

2020 ◽

Author(s):

Irene Zyrichidou ◽

Stavros Solomos ◽

Stylianos Kotsopoulos ◽

Panagiota Syropoulou ◽

Evangelos Kosmidis

Keyword(s):

Air Quality ◽

High Resolution ◽

Regional Scale ◽

Surface Wind ◽

Model Performance ◽

Urban Pollution ◽

Atmospheric Conditions ◽

Pollution Levels ◽

Implementation Period ◽

Simulated Surface

Air pollution models play an important role in science because of their capability to give a description of the air quality problem including an analysis of factors and causes (emission sources, meteorological processes, and physical and chemical changes). Real-time forecast of urban air quality is highly important to the public as advanced information for both air quality and safety assessment.&#160;This study presents the development of a regional scale high-resolution modeling system for simulating air quality and forecasting changes in urban pollution levels. The air quality system based on the state-of-the-art Weather Research and Forecasting model coupled with chemistry (WRF-Chem)&#160;has been applied over the greater area of Thessaloniki, Greece. The model performance, in terms of simulated surface major air pollutants&#8217; concentrations, is evaluated using ground-based measurements during the operational implementation period in winter-spring 2020. Our study highlights the importance of resolving local scale atmospheric conditions such as surface wind flow and boundary layer properties for describing the pollutants&#8217; concentrations and the importance of constraining emissions over the study area.&#160;

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