Northeastern Section - 50th Annual Meeting (23–25 March 2015)

Paper No. 3
Presentation Time: 8:00 AM-12:00 PM

BIOREMEDIATION OF SULFUR IN MINING WATER


JUGAN, Ashleigh1, ISOMÄKI, Ritva2 and KEISKI, Riitta2, (1)Department of Biodiversity, Earth, and Environmental Science, Drexel University, 3141 Chestnut Street, Philadelphia, MA 19104, (2)Department of Process and Environmental Engineering, University of Oulu Finland, Oulu, MA 90014, aaj57@drexel.edu

Acid mine drainage (AMD) is a serious water pollution problem throughout the world. It is caused by poor maintenance of closed and abandoned mines. When sulfide in newly exposed rock comes into contact with water and oxygen, an oxidation reaction takes place producing sulfates, low pH water, and dissolved metals in the water. This process is further accelerated by sulfur oxidizing bacteria. These pollutants reduce the diversity in the aquatic environment and make it unsuitable for human consumption. With increased interest in maximizing retention of resources (metals) from mining and heightened awareness of the pollution caused by AMD, there has been increased interest in finding the most efficient and cost-effective method of remediating AMD waters. The most successful method so far for treating AMD affected water is an active biological system that employs sulfate-reducing bacteria (SRB) to reduce the sulfate, precipitate the metals as usable sulfides, and neutralize the pH. This method still has many limitations such as having a temperature and pH that lowers the efficiency of the bacteria or kills them. The company Paques has installed systems such as the Sulfateqä to treat AMD and recover metals in several mines. However, as each SRB phyla requires different optimal conditions to operate at the maximum efficiency and each AMD water body is different, more research is needed to better understand how to optimize metal precipitation and water purification. This analytical literature review will be the basis of experiments to determine optimal conditions for the SRB and can be used to optimize the efficiency of current and future bioreactors.