Simulation of European air quality by WRF–CMAQ models using AQMEII-2 infrastructure

Syrakov, Dimiter; Prodanova, Maria; Georgieva, Emilia; Etropolska, Iglika; Slavov, Kiril

doi:10.1016/j.cam.2015.01.032

Cited by 27 publications

(17 citation statements)

References 26 publications

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“…CMAQ and CAMx photochemical models have been used with various objectives like the behaviour of plume rise, aerosols property and prediction of pollutant concentration. In most of the cases, CMAQ underestimates as compared to observation for AOD, ozone, PM 2.5 and PM 10 concentration while overprediction for O 3 (Hogrefe et al, 2014;Syrakov et al, 2015). AERMOD has been compared with ADMS-Urban and CALPUFF and results show AERMOD has lower as well as higher correlations than these models with various case studies.…”

Section: Resultsmentioning

confidence: 93%

“…The results of WRF-CMAQ were underestimated for AOD, ozone, PM 2.5 and PM 10 concentration (Hogrefe et al, 2014). Again, WRF-CMAQ was applied to European region for prediction of O 3 and other pollutants (Syrakov et al, 2015). Modelling results showed that model is over-predicting for O 3 and underpredicting for other pollutants compared to observed data.…”

Section: Comparison Of Wrf-cmaq Studymentioning

confidence: 92%

“…These 2010-2006 PM 2.5 decreases result in simulated increases of summer mean clear-sky shortwave radiation between 5 and 10 W m -2 . The application of WRF-CMAQ was repeated to the European domain for the year 2010 under the programme AQMEII-2 (Syrakov et al, 2015). The domain size of WRF-CMAQ model system was 5000 × 5000 km 2 with a horizontal resolution of 25 km.…”

Section: Application Of Wrf With Cmaqmentioning

confidence: 99%

See 2 more Smart Citations

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Kumar

Patil

Dikshit

et al. 2017

Aerosol Air Qual. Res.

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Meteorology plays a crucial role in air quality. The presence of uncertainties of a significant nature in the meteorological profile used during air quality model simulation has the potential to affect negatively the results of the simulations. This paper describes a most recent version of the meteorological model called Weather Research and Forecasting (WRF) model and its importance in air quality. The performance of WRF depends upon the intended application and parameterization scheme of physics options. WRF model is also applied to investigate the simulation results with various land surface models (LSMs) and Planetary Boundary Layer (PBL) parameterizations and various set of microphysics options. It predicts various meteorological spatial parameters like mixing layer height, temperature, humidity, rain fall, cloud cover and wind. The WRF results are integrated with air quality model (AQM) and the AQM depends upon the performance of WRF. It has been applied for evaluation of national pollution control policy, behaviour of plume rise, property of aerosols, prediction of Ozone, SO 2 , NO x , PM 10 , PM 2.5 etc. using AQM for various sources. The effect of topography and different seasons on the concentration of pollutants in the atmosphere has also been studied using AQM. AQM AERMOD has also been reviewed with various other AQM models such as ADMS-Urban and CALPUFF. AERMOD has been used for different time scales, health risk assessment, evaluation of various control strategies, Environmental Impact Assessment (EIA) studies and emission factor estimation. This paper presents the importance of meteorological model to AQM as well as many applications of AQM to demonstrate various scientific questions and policies.

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Section: Resultsmentioning

confidence: 93%

Section: Comparison Of Wrf-cmaq Studymentioning

confidence: 92%

Section: Application Of Wrf With Cmaqmentioning

confidence: 99%

See 1 more Smart Citation

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Kumar

Patil

Dikshit

et al. 2017

Aerosol Air Qual. Res.

View full text Add to dashboard Cite

show abstract

“…While high-resolution regional models (e.g. Liora et al, 2016;Syrakov et al, 2016;Galmarini et al, 2017;Hong et al, 2017) and more complex downscaling methodologies (e.g. Milionis and Davies, 1994;Kumar and Goyal, 2016) than the one used here might, in theory, yield better results (Thunis et al, 2016), computational constraints make their application to climate timescales and continent-wide studies challenging.…”

Section: Introductionmentioning

confidence: 99%

“…Deterministic models, such as chemistry transport models and high-resolution regional air quality models, compute pollutant concentrations as explicit functions of meteorological parameters, chemical transformation processes and source characteristics, and can consequently be computationally expensive (e.g. Liora et al, 2016;Syrakov et al, 2016;Hong et al, 2017). Statistical models are instead based on the relationship between observed small-scale variables (predictands) and large-scale fields from a numerical model (predictors), and are generally computationally inexpensive (Wilby et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

The impact of future atmospheric circulation changes over the Euro-Atlantic sector on urban PM<sub>2.5</sub> concentrations

Messori

Wees

Pausata

et al. 2018

Tellus B: Chemical and Physical Meteorology

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Air quality management is strongly driven by legislative aspects related to the exceedance of air quality limit values. Here, we use the Norwegian Climate Centre's Earth System Model to assess the impact of a future scenario of maximum feasible aerosol emission abatement and increasing greenhouse gases (RCP4.5) on urban PM 2.5 concentrations in Europe. Daily PM 2.5 concentrations are assessed using a novel downscaling method which allows us to compute exceedances of current and planned air quality thresholds. For the latter, we assume that future ambitious emission reductions are likely to be accompanied by stricter air quality thresholds. The changes in PM 2.5 concentrations are discussed in the context of the large-scale atmospheric changes observed relative to the present-day climate. Our results show a more positive North Atlantic Oscillation mean state in the future, combined with a large eastward shift of both North Atlantic sea-level pressure centres of action. This is associated with more frequent mid-latitude blocking and a northward shift of the jet stream. These changes favour higher than expected anthropogenic urban PM 2.5 concentrations in Southern Europe, while they have the opposite effect on the northern half of the continent. In the future scenario, PM concentrations in substantial parts of Southern Europe are found to exceed the World Health Organisation Air Quality Guideline daily limit of 25 lg/m 3 on 25 to over 50 days per year, and annual guidelines of 10 mg/m 3 on more than 80% of the 30 years analysed in our study. We conclude that alterations in atmospheric circulation in the future, induced by stringent maximum feasible air pollution mitigation as well as GHG emissions, will negatively influence the effectiveness of these emission abatements over large parts of Europe. This has important implications for future air quality policies.

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Estimation of precipitation and air temperature over western Canada using a regional climate model

Kuo

Gan

2018

Intl Journal of Climatology

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The Mackenzie River basin (MRB), which covers a geographic region from central Alberta of Canada to the coast of Arctic Ocean, has an area of approximately 1.8 × 106 km2. In this study, the regional climate of MRB, in particular the precipitation and air temperature from the late spring to the fall (May–October), was simulated using a regional climate model Weather Research and Forecasting (WRF). In the open water season of May–October, Mackenzie River provides a critical corridor for Canada's Arctic transportation network. With nine sets of physical parameterizations of WRF selected, we simulated the climate of MRB over representative dry, normal, and wet years to identify the best setting prior to performing the 27‐year simulation for 1979–2005. The major physical parameterizations considered were shortwave (Dudhia, CAM, and RRTMG) and longwave radiation scheme (RRTM, CAM, and RRTMG), microphysics scheme (WRF Double‐Moment 6‐class, WRF Single‐Moment 5‐class, Stony Brook University, and Morrison double‐moment), and cumulus parameterization (Kain–Fritsch, Betts–Miller–Janjic, Tiedtke, and New Simplified Arakawa–Schubert). The simulation for MRB by each set of parameterizations of WRF is assessed using root‐mean‐square error (RMSE), absolute error percentage, and bias maps. After a detailed fine tuning process, and from verifying the 1979–2005 long‐term simulations of WRF, WRF generally simulated realistic air temperature and precipitable water over MRB, but precipitation is over‐simulated, especially at Canadian Rockies.

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Simulation of European air quality by WRF–CMAQ models using AQMEII-2 infrastructure

Cited by 27 publications

References 26 publications

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

The impact of future atmospheric circulation changes over the Euro-Atlantic sector on urban PM<sub>2.5</sub> concentrations

Estimation of precipitation and air temperature over western Canada using a regional climate model

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