ABSTRACT Visibility degradation has become one of the major problems of public concern in Kaohsiung City as well as in most of the urban areas of Taiwan in recent years due to the increasing severity of smog. This study investigated the different aspects of atmospheric visibility degradation problems in metro Kaohsiung. First of all, both the long-term and short-term variation trends of atmospheric visibility were interpreted by analyzing the past data of prevailing visibility. Secondly, the correlation of atmospheric visibility with its major causative factors (i.e. meteorological and pollutant parameters) was established. Thirdly, the relationship between visibility degradation and aerosol mass/composition was derived by using multiple linear regression techniques based on in-situ field measurements of ambient aerosols and light extinction coefficient. Finally, the effective strategies for improving the visual air quality of metro Kaohsiung were proposed based on the results of the receptor-oriented modeling. In metro Kaohsiung, the seasonal variation of atmospheric visibility from the highest to the lowest were found to be in the sequence of summer, spring, autumn and winter, with mean values of 9.1, 8.2, 5.4, and 3.4 km, respectively. A diurnal variation of visibility was observed and showed that the visibility was generally lower in the morning and higher in the afternoon. A mass light scattering efficiency of 3.6 m2 g-1 for PM2.5 and a much lower value (0.3 m2 g-1) for PM2.5-10 indicated that the visible light was mainly scattered by the fine aerosol particles. The derived multiple linear regression model of light scattering coefficient yielded the mass scattering efficiencies of 4.6 m2 g-1 for (NH4)2SO4, 6.7 m2 g-1 for NH4NO3, 3.3 m2 g-1 for total carbon, and 3.2 m2 g-1 for PM2.5-remainder with an R2 of 0.97. On average, the percentage contributions of the visibility-degrading species to the light scattering coefficient were 29% for sulfates, 28% for nitrates, 22% for total carbon, and 21% for PM2.5-remainder, respectively. Furthermore, the major component of light extinction coefficient (bext) was the scattering of light by particles (75% of bext), followed by the absorption of light by particles (20%), while the remaining 5% of bext was attributed to gases. An empirical regression model of visibility based on sulfates, nitrates, PM2.5-remainder, and relative humidity was developed. The results showed that the variation of sulfate in PM2.5 aerosols was most sensitive to visibility change among the parameters. In terms of visibility degradation sources, source apportionment results indicated that the major contributors to fine particles were motor vehicle exhaust and secondary aerosols, which contributed more than half of the visibility degradation in metro Kaohsiung. Meanwhile, the second largest contributor was secondary aerosols containing ammonium sulfate and ammonium nitrate. Additionally, the contribution of soil dust increased markedly from normally only 4% to 25%, owing to an impact of continental dust storm from Mainland China. The results strongly indicated that soil dust blown from the desert areas of Northern China could be transported across the Yellow Sea and the East China Sea and evidently deposited in metro Kaohsiung. Results of the correlation analysis between atmospheric visibility and emission sources revealed a similarity between the source contribution pattern for visibility impairment and the source apportionment of fine particles. It showed ammonium sulfate contributed approximately 46% of the logarithm of atmospheric visibility, while the ¡§remainders¡¨, ammonium nitrate, and elemental carbons contributed about 20%, 17%, and 17%, respectively. Accordingly, this study concluded that the most effective strategy for improving atmospheric visibility in metro Kaohsiung was to prevent the formation of secondary fine particles containing ammonium sulfate and ammonium nitrate.

Faculty of Science School of Geography And Archaeology and Enviromental Studies 9905693x Nicola@crg.bpb.wits.ac.za / The Cape Town brown haze is a brown-coloured smog that is present over the Cape Town atmosphere during the winter months due to the accumulation of gaseous and particulate pollutants. The main aim of this research was to evaluate the impact of atmospheric pollutants to visibility impairment by the brown haze through visibility modelling of major pollution sources around the City of Cape Town. The screening model, VISCREEN, the Plume Visibility model, PLUVUE II and the CALPUFF Modelling System were employed to model the visual impact of emissions from the major sources. Two point sources, Caltex Oil Refinery and Consol Glass, and three area sources, Cape Town Central Business District (CBD), Cape Town International Airport and the townships of Khayelitsha and Mitchell’s Plain were identified as the major sources. An initial screening analysis indicated that emissions from the two industrial sources would be visible and would result in a yellow-brown discolouration of the atmosphere. Detailed modelling using PLUVUE II identified the area sources of Cape Town CBD and the townships to be the significant contributors to visibility impairment over Cape Town. Plume perceptibility is primarily dependant upon particulate emissions while NOx emissions influence the colouration of the atmosphere. CALPUFF was employed to assess the distribution of NOx, SO2 and PM10 concentrations over the area and the associated visibility impairment on a nonhaze (13 August 2003) and haze day (22 August 2003). Pollutant concentrations were considerably reduced on the non-haze day compared to the haze day. The Cape Town CBD was an important source of all the major pollutants with the townships contributing significantly to the aerosol loading over Cape Town. Pollutant concentrations are particularly elevated during the late evening and early morning periods, particularly between 7 am and 8 am. Visibility impairment is greatest on the haze day, particularly over the central Cape Town region and the townships. The greatest reduction in visibility is experienced between midnight and 9 am which corresponds with the periods of elevated atmospheric pollutant concentrations.