Evaluation of European air quality modelled by CAMx including the volatility basis set scheme

Abstract

Abstract. Four periods of EMEP (European Monitoring and Evaluation Programme) intensive measurement campaigns (June 2006, January 2007, September–October 2008 and February–March 2009) were modelled using the regional air quality model CAMx with VBS (volatility basis set) approach for the first time in Europe within the framework of the EURODELTA-III model intercomparison exercise. More detailed analysis and sensitivity tests were performed for the period of February–March 2009 and June 2006 to investigate the uncertainties in emissions as well as to improve the modelling of organic aerosol (OA). Model performance for selected gas phase species and PM2.5 was evaluated using the European air quality database AirBase. Sulfur dioxide (SO2) and ozone (O3) were found to be overestimated for all the four periods, with O3 having the largest mean bias during June 2006 and January–February 2007 periods (8.9 pbb and 12.3 ppb mean biases respectively). In contrast, nitrogen dioxide (NO2) and carbon monoxide (CO) were found to be underestimated for all the four periods. CAMx reproduced both total concentrations and monthly variations of PM2.5 for all the four periods with average biases ranging from −2.1 to 1.0 µg m−3. Comparisons with AMS (aerosol mass spectrometer) measurements at different sites in Europe during February–March 2009 showed that in general the model overpredicts the inorganic aerosol fraction and underpredicts the organic one, such that the good agreement for PM2.5 is partly due to compensation of errors. The effect of the choice of VBS scheme on OA was investigated as well. Two sensitivity tests with volatility distributions based on previous chamber and ambient measurements data were performed. For February–March 2009 the chamber case reduced the total OA concentrations by about 42 % on average. In contrast, a test based on ambient measurement data increased OA concentrations by about 42 % for the same period bringing model and observations into better agreement. Comparison with the AMS data at the rural Swiss site Payerne in June 2006 shows no significant improvement in modelled OA concentration. Further sensitivity tests with increased biogenic and anthropogenic emissions suggest that OA in Payerne was affected by changes in emissions from residential heating during the February–March 2009 whereas it was more sensitive to biogenic precursors in June 2006.

Modelling winter organic aerosol at the European scale with CAMx: evaluation and source apportionment with a VBS parameterization based on novel wood burning smog chamber experiments

“…The new emission inventory was used in two CTMs (EMEP and PMCAMx) and it improved the model performance for the total OA (Denier van der . Ciarelli et al (2016) showed that allowing for evaporation of primary organic particles as available in the European emission inventories degraded the model performance for the total OA mass (further underpredicting OA, but the POA to SOA ratio was in better agreement with measurements). In the same study, on the other hand, model performance improved when a volatility distribution which implicitly accounts for missing semivolatile material (increasing POA emissions by a factor of 3) was deployed.…”

“…The modelling method and input data were the same as those used in the EURODELTA III (ED III) project, described in detail in Ciarelli et al (2016). The model domain covers Europe with a horizontal resolution of 0.25 • × 0.25 • .…”

“…More information regarding the anthropogenic emission inventories is available in Bessagnet et al (2014Bessagnet et al ( , 2016 and Ciarelli et al (2016). Hourly emissions of biogenic VOCs, such as monoterpenes, isoprene, sesquiterpenes, xylene and toluene, were calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1; Guenther et al, 2012) for each grid cell in the model domain.…”

“…A few models also include intermediate-volatility organic compounds (IVOCs) with a C * of 10 3 -10 6 µg m −3 and semivolatile organic compounds (SVOCs) with a C * of 0.1-10 3 µg m −3 co-emitted with POA (Bergström et al, 2012;Ciarelli et al, 2016;Denier van der Gon et al, 2015;Fountoukis et al, 2014;Tsimpidi et al, 2010;Woody et al, 2016). In these applications, the volatility distributions of POA and IVOC emissions are based on the study of Robinson et al (2007), where the IVOC mass is assumed to be 1.5 times the total organic mass available in the semivolatile range.…”

“…Most of the CTMs today account for SOA formation from biogenic and anthropogenic high-volatility precursors such as terpenes, isoprene, xylene and toluene which have a saturation concentration (C * ) higher than 10 6 µg m −3 (Aksoyoglu et al, 2011;Ciarelli et al, 2016). A few models also include intermediate-volatility organic compounds (IVOCs) with a C * of 10 3 -10 6 µg m −3 and semivolatile organic compounds (SVOCs) with a C * of 0.1-10 3 µg m −3 co-emitted with POA (Bergström et al, 2012;Ciarelli et al, 2016;Denier van der Gon et al, 2015;Fountoukis et al, 2014;Tsimpidi et al, 2010;Woody et al, 2016).…”