European Geosciences Union, Atmospheric Chemistry and Physics, 6(14), p. 2735-2756, 2014
European Geosciences Union, Atmospheric Chemistry and Physics Discussions, 6(13), p. 16775-16830
DOI: 10.5194/acpd-13-16775-2013
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Accurate estimates of emissions from natural sources are needed for reliable predictions of ozone and fine particulate matter (PM 2.5 ) using air quality models. In this study, the large-scale atmospheric chemistry transport model, DEHM (the Danish Eulerian Hemispheric Model) is further developed, evaluated and applied to study and quantify the contributions of natural emissions of VOCs, NO x , NH 3 , SO 2 , CH 4 , PM, CO and sea salt to the concentration of ozone and formation of PM 2.5 for the year 2006. Natural source categories adopted in the recent model are vegetation, lightning, soils, wild animals and oceans. In this study, the model has been further developed to include more Biogenic Volatile Organic Compounds (BVOCs) and to implement a scheme for secondary organic aerosols as well as an updated description of sea-salt emissions. Our simulations indicate that in the Northern Hemisphere the contribution from natural emissions to the average annual ozone mixing ratios over land is between 4–30 ppbV. Among the natural emissions, BVOCs are found to be the most significant contributors to ozone formation in 2006, enhancing the average ozone mixing ratio by about 11% over the land areas of the Northern Hemisphere. The relative contribution of all the natural emissions to ozone is found to be highest in the northern part of South America by about 42%. Similarly, the highest contribution of all the natural sources to total fine particles over land is found to be in South America by about 74% and sea-salt aerosols demonstrated to play the most important role. However, over the rest of the regions in the model domain the largest contribution from the natural sources to PM 2.5 in the specific year 2006 is due to wildfires. The contribution from natural emissions to the mean PM 2.5 concentration over the land areas in the model domain is about 34%.