Mudassar Hassan Arsalan

Spatio-temporal patterns of road traffic noise pollution in Karachi, Pakistan

We studied the spatial and temporal patterns of noise exposure due to road traffic in Karachi City, Pakistan, and found that levels of noise were generally higher during mornings and evenings because of the commuting pattern of Karachi residents. This study found the average value of noise levels to be over 66 dB, which could cause serious annoyance according to the World Health Organization (WHO) outdoor noise guidelines. Maximum peak noise was over 101 dB, which is close to 110 dB, the level that can cause possible hearing impairment according to the WHO guidelines. We found that noise pollution is not an environmental problem reserved for developed countries, but occurs in developing countries as well. For this reason, steps might be required to reduce noise levels caused by road traffic.

Who is the bigger culprit? Studying impacts of traffic and land use on noise levels in CBD area of Karachi, Pakistan

The trend of urbanization has attracted increased attention towards urban areas around the world. Central business districts (CBDs) serve as the core of commercial activities of urban areas and are often associated with high-density population. Noise pollution in urban areas, especially CBDs, is considered as an important issue for planners and policy makers especially with regard to human health. Noise prediction models for CBD area of Karachi, Pakistan, have been developed in this study using land use and traffic parameters. These models show that traffic and built-up space (especially residential land use) contribute positively and vacant space contributes negatively to the noise levels. However, it was found that traffic volume has higher impact, than land use, in terms of on noise levels in CBD area. The models of this research are anticipated to be used for planning of urban CBD areas in other cities where noise levels do not meet international health standards. In addition, they would be useful in calculating the rate of traffic volume associated with residential land use.