Simulations of Emissions, Air Quality, and Climate Contribution in Southeast Asia for March and December
Air pollution is a major concern over Southeast Asia, especially in March when biomass burning and anthropogenic emissions both contribute significantly to air quality in terms of gases and aerosols. This work explores the sensitivity of air quality in terms of ozone in Southeast Asia from future emissions and climate. Simulations with the Nested Regional Climate Model coupled with Chemistry (NRCM-Chem) with 60 and 12 km grid sizes were performed for March and December during 2030–2034 and present day (2005–2009). The NRCM-Chem model employs initial and boundary conditions from the Community Climate System Version 3 (CCSM3) for meteorological variables and Community Atmospheric Model with Chemistry (CAM-Chem) for chemical species. The emission inventories include anthropogenic, biogenic, and biomass burning emissions. The future anthropogenic emissions are the RCP4.5 scenario from CAM-Chem emissions, while biomass burning emissions are the same in both present-day and 2030–2034 simulations. Three simulations were conducted for: (1) present day (2005–2009), (2) future day using the RCP4.5 climate scenario and present anthropogenic emission, and (3) future day using the RCP4.5 climate scenario and future anthropogenic emission. We find, by comparing the NRCM-Chem results with the CAM-Chem results (at a coarser grid spacing of ~200 km), that the two model results have a similar spatial pattern in the present day over Southeast Asia, and they agree fairly well compared to ground-based observations from Pollution Control Department in Thailand. Model results indicate that climate change alone increases ozone concentrations by about 30% in Southeast Asia, while the combination of climate and emission changes in the future increase ozone by another 10% compared to the simulation with only future climate change.
KeywordsOzone Southeast Asia CAM-Chem model
The study was partially supported by NSF CHEM award 1049058. We are thankful for the Thai Pollution Control Department (PCD) and Thai Meteorological Department (TMD) providing their air quality (O3, CO, and NO2) and meteorological (temperature and precipitation) observation data. We also acknowledge the Global Modelling and Assimilation Office (GMAO) and the GES DISC for the dissemination of MERRA and Tropical Rainfall Measuring Mission (TRMM) data. We acknowledge Associate Professor Dr. Jiemjai Kreasuwun from Chiang Mai University for kindly suggestion and Jean-Francois Lamarque for his assistance with CAM-Chem. NCAR is operated by the University Corporation for Atmospheric Research (UCAR) under sponsorship of the National Science Foundation.
- Carslaw KS, Gordon H, Hamilton DS, Johnson JS, Regayre LA, Yoshioka M, Pringle KJ (2017) Aerosols in the pre-industrial atmosphere. Curr Climate Change Rep 3(1):1–15Google Scholar
- Emmons LK, Walters S, Hess PG, Lamarque J-F, Pfister GG, Fillmore D, Granier C, Guenther A, Kinnison D, Laepple T, Orlando J, Tie X, Tyndall G, Wiedinmyer C, Baughcum SL, Kloster S (2010) Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4). Geosci Model Dev 3(1):43–67Google Scholar
- Fast JD, Gustafson WI, Easter RC, Zaveri RA, Barnard JC, Chapman EG, Grell GA, Peckham SE (2006) Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model. J Geophys Res 111(D21305). https://doi:10.1029/2005JD006721Google Scholar
- Hogrefe CB, Lynn K, Civerolo J-Y, Ku J, Rosenthal C, Rosenzweig R, Goldberg S, Gaffin K, Kinney PL (2004) Simulating changes in regional air pollution over the eastern United States due to changes in global and regional climate and emissions. J Geophys Res 109(D22). https://doi.org/10.1029/2004JD004690
- Huffman GJ, Bolvin DT (2012) TRMM and other data precipitation data set document. ftp://precip.gsfc.nasa.gov/pub/trmmdocs/3B42_3B43_doc.pdf
- Iacono MJ, Delamere JS, Mlawer EJ, Shephard MW, Clough SA, Collins WD (2008) Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res 113(D13). https://doi.org/10.1029/2008jD009944
- Intergovernmental Panel on Climate Change (2000) Emission Scenarios, edited by N. Nakicenovic and R. Swart, pp. 570, Cambridge Univ. Press, UKGoogle Scholar
- Lu Z, Street DG (2012) The Southeast Asia Composition, Cloud, Climate Coupling Regional Study Emission Inventory. http://www.cgrer.uiowa.edu/SEAC4RS/emission.html
- Nolte C, Gilliland A, Hogrefe C (2008) Linking Global and Regional Models to Simulate U.S. Air Quality in the Year 2050. In: Borrego C, Miranda AI (eds) Air pollution modeling and its application XIX. NATO Science for Peace and Security Series Series C: Environmental Security, vol 6. Springer, Dordrecht, pp 559–567Google Scholar
- Pfister GG, Walters S, Lamarque J-F, Fast J, Barth MC, Wong J, Done J, Holland G, Bruyere CL (2014) Projections of future summertime ozone over the U.S. J Geophys Res 119:5559–5582Google Scholar
- Skamarock WC, Klemp JB, Duhia J, Gill DO, Barker DM, Duda MG, Huang X-Y, Wang W, Powers JG (2008) A description of the advanced research WRF version 3, NCAR Technical noteGoogle Scholar
- Wiedinmyer C, Akagi SK, Yokelson RJ, Emmons LK, Al-Saadi JA, Orlando JJ, Soja AJ (2011) The Fire INventory from NCAR (FINN) – a high resolution global model to estimate the emissions from open burning. Geosci Model Dev 4:625–641. https://doi:10.5194/gmd-4-625-2011Google Scholar