Bachelor of Chemical Engineering Technology (Hons) in (Environment)

Abstract

Due to natural events such as tsunami and earthquake, the decomposition of heavy metals has been increase where humans are exposed to a serious disease which it might comes from air, plants and water. The objectives of this study are to determine the concentration of Cu, Mg, Pb and Fe in water, soils, and plants along Malacca River, to record heavy metal data and identify possible hot-spots of elevated concentrations of heavy metal using GIS approaches. There were 10 sampling points that were divided into 4 zones; Zone A, B, C and D which are rural area, housing area, industrial area and tourist area respectively. The levels of Cu, Mg, Pb and Fe were measured using Atomic Absorption Spectroscopy. Heavy metals in water were found very high at Zone C. Among all heavy metal, the level of Fe was the highest due to there were industrial activities that contribute to the presence of heavy metal in water. In conjunction with that, soils at Zone C also high concentration in heavy metal which level of Fe was the highest. Since the heavy metals were high at Zone C, it can conclude that heavy metal in soil was a bit higher than water. Soils acts as reservoir for all contaminant and dead organic matter descending from the ecosystem. However, the accumulation of heavy metal in plants depends on the plant species, types of soil and environment and agricultural practice (Alloway, 1990). Tripathi et al. (1997) reported that concentration of Fe, Cu and Mg were high since they were an essential element in plant nutrition. On the other hand, Pb was the least abundant heavy metals in plants. Generally, the root of plant accumulated higher levels of metals compared to leaves because of the activities of the root itself. By the application of GIS, other users can analyze the concentration of heavy metal along Malacca River by the data that has been plotted. In addition, other users also can share information to others. Besides, the data can be use to relate with the data population on that area.