Abstract
The Hsinchu Science Industry Park (Hsinchu SIP) located in northern part of Taiwan constitutes of more than 400 companies distributed in 700 hectare of land. With annual turnover of 20 billion US$ reported in 2001, it has significant contribution in growth of Taiwan economy. Increased industrial growth subsequently increased usage of water. The wastewater released from the industries is processed in the wastewater treatment plant and released into the Koaya stream along with the municipal wastewater from southern part of Hsinchu city. Thus, analysis of wastewater from different industries, treatment plants and after it is released in the Koaya stream is important. Total of 434 water samples were analyzed including 148 samples for 16 heavy metal by ICP-MS, 88 samples for 7 phthalates and 17 non-ionic surfactants by LC-MS, and 198 samples for 6 anionic species. Conventional analysis like pH, conductivity, BOD, COD, SS, ammonia nitrogen, total Phosphate and E. Coli bacteria cluster were carried out to investigate normal ground water quality. Samples were collected from wastewater treatment plant both inlet and outlet, 24 different factories, 5 different rain-drain in the SIP area, and 5 different sample site of the SIP wastewater receiving rivers. The processing efficiency of the wastewater treatment plant was evaluated through comparison of inlet and outlet water. Wastewater effluents from different industries were analyzed and compared to investigate presence of characteristic species. By selecting suitable sampling sites from the SIP wastewater and city municipal area water released in Koaya stream, the water contaminating species were traces back to its source i.e. either to SIP or city wastewater. Factor analysis, a powerful technique for data mining was used for confirming the results and probing relationship between different analyses strategies used in this work. In addition to chemical analysis, biological toxicity test of industrial wastewater was also conducted using microorganism as basic platform.