Modeling the Effects of Biogenic NO X Emissions on the South African Highveld and Waterberg Regions

Abstract

The Highveld and Waterberg regions in South Africa contain extensive coal fields and therefore have a high concentration of coal-fired power stations. Previous studies assessed the impact of atmospheric deposition of S- and N-containing species from anthropogenic sources in the region but did not include the effect of biogenic emissions. This study models biogenic NO_X soil emissions for the regions and includes them in an atmospheric dispersion model to study the effects of biogenic emission on nitrogen deposition rates. Simulated sulfur deposition rates for the Highveld area are also reported on. Anthropogenic and biogenic sulfur and nitrogen emission sources were inventoried for the Highveld and Waterberg regions. Using previous work by Yienger and Levy, biogenic soil NO_X emissions were quantified by constructing models for both areas using land use data, rainfall data, and atmospheric ground level temperatures from CALMET data. A CALPUFF dispersion model was used to predict deposition rates for S- and N-containing species with and without biogenic NO_x emissions to determine the impact of biogenic emissions for the Highveld. As rainfall is highly variable in the region, meteorological data representative of high, average, and low rainfall years was used to determine the effect of rainfall on deposition rates for the various species. The biogenic NO_x made up 3.96, 4.14, and 3.34% of total released NO_x for 2001 (average rainfall), 2003 (low rainfall), and 2010 (high rainfall), respectively. Dry nitrogen deposition rates were affected most by the biogenic component, adding from 1.7 to 6.2% at various receptor locations. Wet deposition rates were affected very little (0.13 to 0.75%). Effect on total nitrogen deposition rates ranged from 0.32 to 1.77%. Biogenic emissions for the Waterberg area, being more arid, were calculated to be only 2.3% of total NO_x emissions for the area and accordingly have little effect on deposition rates.

from #ORL-AlexandrosSfakianakis via ola Kala on Inoreader http://ift.tt/2w1y2vl