To the central content area

FY97 “Taichung County Water Pollution Control Program on Pollution Source Monitoring, Pollution Inspection Enhancement, and River Patrolling”

Absrtact
This project, under contract between April 8th and December 31st of 2008, has carried out all the tasks according to plan. The project team performed the following: ˙ Non-registered effluent pipes: Identified 36 hidden or by-pass effluent pipes were identified after thorough investigations inside and around 33 factories, including manufacturing area and wastewater treatment works of these factories. Of these effluent pipes, 29 have completed improvement. Include scientific instrument use part of checking among them, total discover and seize 11 place 13 hidden effluent pipes, by-pass pipes or non-registered pipes and is it improve to finish. ˙ Effluent water quality: Collected and analyzed 707 samplings among the factories. 707 samples were in compliance with effluence standards. The 49 that did not comply were in compliance after follow-up investigations. ˙ Registered major water pollution sources: Evaluated 8 wastewater treatment plants and their follow-up improvements. ˙ Pollution prevention and solid waste collection along river sides: Conducted 9 rounds of inspection along the river basins of Wu-Hsi, Da-Ja Hsi, and Da-An Hsi. Discovered 41 random garbage dumps with an estimated weight around 189.5 metric tons. Cleared and removed 151.7 metric tons. ˙ Edcuaction on water pollution regulations: Conducted five sessions of education on water pollution regulations ˙ Promotion of public participation in river protection: Organized 22 teams with 572 persons to take part in protecting river from pollution; conducted 1progress-review workshops, 1 sessions on river cleaning, and 1 session of observation-learning-study activity on ecology. The project has completed 100% of the tasks under contract.
Keyword
Auditing and sampling, hidden effluent pipes, by-pass pipes, scientific instrument, non-registered pipes, education and training, observation-learning-study on ecology
Open
top