Journals / Atmospheric Pollution Research / 2016 / Cilt: 7 - Sayı: 6

Influence of boundary conditions and anthropogenic emission inventories on simulated O3 and PM2.5 concentrations over Lebanon

Pages
971–979
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The observedconcentration is 20.7 mg m3, while the modeled concentrations are 20.7 and 20.1 mg m3 respectively

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study investigates the influence of boundary conditions and anthropogenic emission inventories onthe simulated O3 and PM2.5 concentrations over a middle-eastern country e Lebanon.
📊
Key Findings & Data:The Polyphemuschemical transport model (CTM) is used over Lebanon to simulate O3 and PM2.5 concentrations.
💡
Conclusion & Impact:The observedconcentration is 20.7 mg m3, while the modeled concentrations are 20.7 and 20.1 mg m3 respectively
🔬Design:Modeling & Simulation
📍Scope:2011 Verileri
⚙️Variables:Domain Parameters

Özet

This study investigates the influence of boundary conditions and anthropogenic emission inventories onthe simulated O3 and PM2.5 concentrations over a middle-eastern country e Lebanon. The Polyphemuschemical transport model (CTM) is used over Lebanon to simulate O3 and PM2.5 concentrations. Comparisonsto measurements at a sub-urban site of Beirut between 2 and 13 July 2011 show that O3 islargely over-estimated when concentrations from a large-scale model are used as boundary conditions,as used in Waked et al. (2013). A global anthropogenic emission inventory (EDGAR-HTAP) is used withPolyphemus, in order to provide anthropogenic emissions for the Middle-East domain. Over Lebanon,sensitivity to emissions and to boundary conditions have been investigated. The comparison of EDGARHTAPto Waked et al. (2012) over Lebanon highlights high discrepancies between the inventories both interms of emission estimates and spatial distribution. However, when studying the sensitivity toboundary conditions, O3 is well modeled when a Middle-East domain and the Lebanon domain arenested and thus achieves better statistics. The observed concentration is 48.8 mg m3 and the respectiveconcentrations for the simulation using MOZART4 and the one using the Polyphemus/Middle-East are154.8 and 65.1 mg m3. As for PM2.5 which is less sensitive to regional transport than O3, the influence ofthe boundary conditions on the PM2.5 concentrations at the site of comparison is low. The observedconcentration is 20.7 mg m3, while the modeled concentrations are 20.7 and 20.1 mg m3 respectively

🔖

Cite This Article

ABDALLAH, C., SARTELET, K., AFİF, C. (2016). Influence of boundary conditions and anthropogenic emission inventories on simulated O3 and PM2.5 concentrations over Lebanon. Atmospheric Pollution Research, Cilt: 7 - Sayı: 6, 971–979. https://ajindex.com/articles/351420

References (4)

  1. Afif, C., Chelala, C., Borbon, A., Abboud, M., Adjizian-G erard, J., Farah, W., Jambert, C., Zaarour, R., Badaro Saliba, N., Perros, P., Rizk, T., 2008. SO2 in Beirut: air quality implication and effects of local emissions and long-range transport. Air Qual. Atmos. Health 1, 167e178. Afif, C., Dutot, A., Jambert, C., Abboud, M., Adjizian-Gerard, J., Farah, W., Perros, P., Rizk, T., 2009. Statistical approach for the characterization of NO2 concentrations in Beirut. Air Qual. Atmos. Health 2, 57e67. Airbase, 2009. http://acm.eionet.europa.eu/databases/airbase accessed in 2013.
  2. Boylan, J.W., Russell, A.G., 2006. PM and light extinction model performance metrics, goals, and criteria for three-dimensional air quality models. Atmos. Environ. 40, 4946e4959. Bretherton, C.S., Park, S., 2009. A new moist turbulence parameterization in the community atmosphere model. J. Clim. 22, 3422e3448. Center for International Earth Science Information Network - CIESIN - Columbia University, United Nations Food and Agriculture Programme - FAO, Centro Internacional de Agricultura Tropical - CIAT, 2005.
  3. Gridded Population of the World, Version 3 (GPWv3): Population Count Grid, Future Estimates. Couvidat, F., Debry, E., Sartelet, K., Seigneur, C., 2012. A hydrophilic/hydrophobic organic (H2O) aerosol model: development, evaluation and sensitivity analysis. J. Geophys. Res. Atmos. 117. Debry, E., Fahey, K., Sartelet, K., Sportisse, B., Tombette, M., 2007. Technical note: a new SIze REsolved aerosol model (SIREAM). Atmos. Chem. Phys. 7, 1537e1547. EMEP, 2009. http://www.emep.int accessed in 2013.
  4. Emmons, L.K., Walters, S., Hess, P.G., Lamarque, J.-F., Pfister, G.G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D., Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C., Baughcum, S.L., Kloster, S., 2010. Description and evaluation of the model for ozone and related chemical Tracers, version 4 (MOZART-4). Geosci. Model Dev. 3, 43e67. EU, 2008. Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on Ambient Air Quality and Cleaner Air for Europe. Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P.I., Geron, C., 2006. Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature). Atmos. Chem. Phys. 6, 3181e3210. Janssens-Maenhout, G., Dentener, F., van Aardenne, J., Monni, S., Pagliari, V., Orlandini, L., Klimont, Z., Kurokawa, J., Akimoto, H., Ohara, T., Wankmüller, R., Battye