Simulation of aerosols and gas-phase species over Europe with the POLYPHEMUS system: Part I-Model-to-data comparison for 2001

TLDR: A preliminary validation study of the Polyphemus system applied over Europe for 2001 of the aerosol model, a sectional model that describes the temporal evolution of the size/composition distribution of atmospheric particles containing a mix of black carbon, mineral dust, inorganic species, and primary and secondary organics.

About: This article is published in Atmospheric Environment.The article was published on 2007-09-01 and is currently open access. It has received 126 citations till now. The article focuses on the topics: Polyphemus & Aerosol.

Figures

Fig. 1. Locations of the stations for the EMEP (left panel), the BD

Fig. 2. Yearly mean diurnal cycle of hourly ozone averaged over all

Table 3 Statistics obtained with POLYPHEMUS over Europe in 2001 for aerosols: number of stations used to compute the statistics, observed mean ðmgm 3Þ, modeled mean ðmgm 3Þ, RMSE ðmgm 3Þ, correlation (%), MFB (%), MFE (%)

Fig. 5. MFE at each of the EMEP stations for PM2:5, sulfate, nitrate and ammonium. The dashed lines represent the model performance goal of 50% and the model performance criterion of 75%.

Fig. 8. Time series of daily concentrations of O3, NO2, NH3 and SO2 at the EMEP stations.

Fig. 9. Time series of daily concentrations of sulfate, ammonium and nitrate at the EMEP stations.

Frequently asked questions

Q1. What have the authors contributed in "Simulation of aerosols and gas-phase species over europe with the polyphemus system: part i - model-to-data comparison for 2001" ?

This paper aims at presenting a validation of multi-pollutants over Europe with a focus on aerosols. The authors present in this paper a preliminary validation study of the POLYPHEMUS system applied over Europe for 2001. It is a sectional model that describes the temporal evolution of the size/composition distribution of atmospheric particles containing a mix of black carbon, mineral dust, inorganic species, and primary and secondary organics. In addition to a brief model description, the authors present an overview of the model validation. 

Q2. What are the processes that are not considered in the simulations?

Some processes such as the oligomerization in the particulate phase, the formation of organics in the aqueous phase (Pun et al., 2006b), the formation of organosulfates (Surratt et al., 2007) and organonitrates are not considered. 

Q3. Why is the deposition of NH3 near sources underestimated?

Because emissions are assumed to be instantaneously mixed throughout the first mixing layer, and because gradients from surfacic NH3 emission maybe very strong, the deposition of NH3 close to sources is underestimated. 

Q4. What is the effect of nitrate on aerosols in summer?

The heterogeneous formation of nitrate on dust particles (e.g. Dentener et al., 1996; Hodzic et al., 2006ba) tends to decrease the HNO3 concentrations and to increase nitrate concentrations of coarse aerosols in summer. 

Q5. What is the main reason for the observational error?

the observational error may be large due to artifacts in the measurement methods (we refer for instance to Schaap et al., 2004a for a deeper understanding; a key process is evaporation of the samples, for example). 

Q6. What are the different types of background stations in AirBase?

In AirBase, although traffic and industrial stations have been excluded, stations labeled as background may be representative of urban or suburban background stations. 

Q7. What is the effect of ion dissociation on the soluble gaseous species?

During below-cloud scavenging, equilibrium concentrations of soluble gaseous species can be significantly affected by the ion dissociation during dissolution in water. 

Q8. What is the percentage of organics at the EMEP stations?

At the EMEP stations, the simulated primary and secondary organic aerosols represent only about 6% of the total aerosol mass, whereas Putaud et al. (2004) estimates the percentage of organics between 16 to 22%. 

Q9. What are the key statistical indicators for ozone?

The key statistical indicators are the correlation coefficient (%) and the root mean square error (RMSE) (mgm 3) (given in Appendix). 

Q10. How much of the dust is simulated at the EMEP stations?

at the EMEP stations, the simulated dust represents about 25% of the total aerosol mass, whereas Putaud et al. (2004) estimates the percentage of dust between 9% and 19%. 

Q11. What is the reason for the underestimation of PM10?

Another reason of the underestimation of PM10 may lie in Saharan dust episodes, which may contribute to daily PM10 levels by as much as 20mgm 3 (Gobbi et al., 2007). 

Q12. What is the percentage of sodium in sea salt?

Although based on the composition of sea water (Seinfeld and Pandis, 1998), sea salt is made of only 30.61% of sodium, the percentage of sodium is taken as 39.33% here. 

Q13. What is the main reason for the underestimation of sulfate in winter?

As emphasized by Bessagnet et al. (2004), sulfur aqueous chemistry, which is predominant in winter, is very difficult to simulate, because it is very sensitive to pH.