A model for European Biogenic Volatile Organic Compound emissions: Software development and first validation

Poupkou, A.; Giannaros, Theodore M.; Markakis, K.; Kioutsioukis, Ioannis; Curci, Gabriele; Melas, Dimitrios; Zerefos, C. S.

doi:10.1016/j.envsoft.2010.05.004

Cited by 75 publications

(44 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the climatological simulations, the biomass burning emissions and biogenic VOC emissions exhibit a strong seasonal cycle with higher emissions in the summer and lower emissions in the winter. Biogenic emissions approach zero during the winter with summer emission rates nearly two orders of magnitude higher than winter, consistent with other emissions studies in Europe (Poupkou et al, 2010;Steinbrecher et al, 2009). …”

Section: Emissions Inventoriessupporting

confidence: 90%

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

et al. 2012

View full text Add to dashboard Cite

Abstract. The RegCM-CHEM4 is a new online climatechemistry model based on the International Centre for Theoretical Physics (ICTP) regional climate model (RegCM4). Tropospheric gas-phase chemistry is integrated into the climate model using the condensed version of the Carbon Bond Mechanism (CBM-Z; Zaveri and Peters, 1999) with a fast solver based on radical balances. We evaluate the model over continental Europe for two different time scales: (1) an event-based analysis of the ozone episode associated with the heat wave of August 2003 and (2) a climatological analysis of a six-year simulation (2000)(2001)(2002)(2003)(2004)(2005). For the episode analysis, model simulations show good agreement with European Monitoring and Evaluation Programme (EMEP) observations of hourly ozone over different regions in Europe and capture ozone concentrations during and after the summer 2003 heat wave event. For long-term climate simulations, the model captures the seasonal cycle of ozone concentrations with some over prediction of ozone concentrations in non-heat wave summers. Overall, the ozone and ozone precursor evaluation shows the feasibility of using RegCM-CHEM4 for decadal-length simulations of chemistry-climate interactions.

show abstract

Section: Emissions Inventoriessupporting

confidence: 90%

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

et al. 2012

View full text Add to dashboard Cite

show abstract

“…Both models overestimate the observed data, and MEGAN results have a larger difference in this station. Nevertheless, the results are in agreement with Poupkou et al (2010) concluding an average level of uncertainty within a factor of 4 for isoprene estimations in Europe. In addition, it should also be emphasized that the relatively coarse spatial resolution applied in DEHM in these simulations is not able to well represent the high spatio-temporal variation in the isoprene concentrations.…”

Section: Evaluation Of Isoprene Concentrationssupporting

confidence: 90%

“…A number of studies have compared the isoprene models before incorporating the modules into CTMs on both global (Arneth et al, 2011) and regional (Wiedinmyer et al, 2008;Lam et al, 2011;Poupkou et al, 2010) scales. Arneth et al (2011) found agreement in the spatial distribution, interannual variability and total emissions as simulated by the three global isoprene emission models of MEGAN, LPJ-GUESS and BVOCEM.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of two isoprene emission models for use in a long-range air pollution model

et al. 2012

View full text Add to dashboard Cite

Abstract. Knowledge about isoprene emissions and concentration distribution is important for chemistry transport models (CTMs), because isoprene acts as a precursor for tropospheric ozone and subsequently affects the atmospheric concentrations of many other atmospheric compounds. Isoprene has a short lifetime, and hence it is very difficult to evaluate its emission estimates against measurements. For this reason, we coupled two isoprene emission models with the Danish Eulerian Hemispheric Model (DEHM), and evaluated the simulated background ozone concentrations based on different models for isoprene emissions. In this research, results of using the two global biogenic emission models; GEIA (Global Emissions Inventory Activity) and MEGAN (the global Model of Emissions of Gases and Aerosols from Nature) are compared and evaluated. The total annual emissions of isoprene for the year 2006 estimated by using MEGAN is 592 Tg yr −1 for an extended area of the Northern Hemisphere, which is 21 % higher than that estimated by using GEIA. The overall feature of the emissions from the two models is quite similar, but differences are found mainly in Africa's savannah and in the southern part of North America. Differences in spatial distribution of emission factors are found to be a key source of these discrepancies. In spite of the short life-time of isoprene, a direct evaluation of isoprene concentrations using the two biogenic emission models in DEHM has been made against available measurements in Europe. Results show an agreement between two models simulations and the measurements in general and that the CTM is able to simulate isoprene concentrations. Additionally, investigation of ozone concentrations resulting from the two biogenic emission models show that isoprene simulated by MEGAN strongly affects the ozone production in the African savannah; the effect is up to 10 % more than that obtained using GEIA. In contrast, the impact of using GEIA is higher in the Amazon region with more than 8 % higher ozone concentrations compared to that of using MEGAN. Comparing the ozone concentrations obtained by DEHM using the two different isoprene models with measurements from Europe and North America, show an agreement on the hourly, mean daily and daily maximum values. However, the average of ozone daily maximum value simulated by using MEGAN is slightly closer to the measured value for the average of all measuring sites in Europe.

show abstract

“…Particulate matter emissions from natural sources (windblown dust and sea salt aerosol) and biogenic volatile organic compounds from vegetation are estimated using the Natural Emission MOdel NEMO version 1 (Markakis et al, 2009;Poupkou et al, 2010;Markakis, 2010) driven by the WRF meteorology. The Model for the Spatial and Temporal Distribution of Emissions (MOSESS) (Markakis et al, 2013) was applied for the calculation of spatially and temporally disaggregated and chemically speciated anthropogenic emission data of the following pollutants: CO, NO x , SO 2 , NH 3 , NMVOC, PM 10 and PM 2.5 .…”

Section: The Comprehensive Air Quality Model With Extensions (Camx)mentioning

confidence: 99%

Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data

et al. 2017

Self Cite

View full text Add to dashboard Cite

Abstract. In this study we present an evaluation of the Comprehensive Air Quality Model with extensions (CAMx) for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the PM 2.5 and PM 2.5−10 concentration profiles retrieved by the Lidar-Radiometer Inversion Code (LIRIC). The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere. The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the PM 2.5 particles. The mean centers of mass values are also close, with a mean bias of 0.57 km. On the opposite side, there are larger differences for the PM 2.5−10 mode, both in the boundary layer and in the free troposphere. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol sources that are not properly included in the model's emission inventory and in the boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model in conjunction with satellite fire pixel data from MODerate-resolution Imaging Spectroradiometer (MODIS) Terra and Aqua global monthly fire location product MCD14ML. By removing those cases the correlation coefficient improves from 0.69 to 0.87 for the PM 2.5 integrated mass in the boundary layer and from 0.72 to 0.89 in the free troposphere. The PM 2.5 center of mass fractional bias also decreases to 0.38 km. Concerning the analysis of the desert dust component, the simulations from the Dust Regional Atmospheric Model (BSC-DREAM8b) were deployed. When only the Saharan dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a mean bias of −29.1 % for the integrated mass in the free troposphere and a correlation of 0.57 for the center of mass. CAMx, on the other hand, underestimates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported Saharan dust cases. We conclude that the performance of CAMx appears to be best for the PM 2.5 particles, both in the boundary layer and in the free troposphere. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance, especially for the PM 2.5−10 particles.

show abstract

A model for European Biogenic Volatile Organic Compound emissions: Software development and first validation

Cited by 75 publications

References 40 publications

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

Evaluation of two isoprene emission models for use in a long-range air pollution model

Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data

Contact Info

Product

Resources

About