Institute: Connecticut
Year Established: 2014 Start Date: 2014-03-01 End Date: 2015-02-15
Total Federal Funds: $12,821 Total Non-Federal Funds: $24,828
Principal Investigators: Bin Zhu, Timothy Vadas
Project Summary: With the increases in human activities and human population, aquatic ecosystems in the United States are facing various threats and contaminations. According to the EPA and CT DEEP, heavy metals have become one of a suite of common causes of stream impairment in the State of Connecticut and nationwide. In the nation, with respect to stream miles affected, heavy metals are ranked 7th most important causes for impaired water (with 72,000 miles). The metal contaminants include iron, aluminum, copper (Cu), or zinc (Zn). In the State of Connecticut, many listed impairments are for recreational use due to E. coli, but of the impairments for habitat there are 11 instances of Cu or Zn impairment in established total maximum daily loads (TMDLs), which represents over half of the habitat designated use impairments. Elevated concentrations of heavy metals, particularly for Cu and Zn in urban streams usually come from stormwater runoff non-point sources and municipal wastewater point sources. The two types of sources differ in the forms of heavy metals, makeup of organic matter, and the contaminant load size, which will likely affect the heavy metal biouptake and transfer in the stream food webs. Understanding the dynamics of heavy metals in impaired streams is critical to maintain or restore urban stream ecosystem health. Two junior researchers at the University of Hartford and the University of Connecticut are proposing a collaborative interdisciplinary project (biology and environmental engineering) to conduct investigations in the natural streams as well as experiments in the laboratory to study how water from different sources (i.e., wastewater from point sources and stormwater from nonpoint sources) affects the biouptake and transfer of heavy metals in the food webs. Specifically, our objectives are: 1) to study the biouptake and transfer of Cu and Zn in macroinvertebrates in urban streams exposed to two different conditions: one with impacts from increased water column concentrations during stormflow and the other with wastewater effluent release of metals; and 2) to investigate how Cu and Zn are transferred in the food webs, i.e. from stormflow and wastewater effluent impacted streamwater to periphyton (algae) and to benthic invertebrate grazers (e.g., mayflies) by setting up laboratory experiments. To achieve our first goal, we will select 10 streams with stormwater runoff and 10 streams with wastewater in Connecticut. Stream reaches are selected based on wadeable streams that are impacted directly by municipal wastewater effluent discharges or were listed as an impaired water body by CT DEEP. Water and benthic invertebrate communities will be sampled in the upstream and downstream of the wastewater treatment plants as well as in the baseflow and stormwater runoff. The makeup and concentrations of heavy metals will be measured to estimate the heavy metal biouptake and transfer across the food chain. To achieve our second goal, we will set up a factorial experimental design to include five different water sources (A. stream water without wastewater effluent or stormwater, B. wastewater effluent, C. stream water during stormflow without wastewater effluent with 1-day exposure time for organisms (to simulate weak storm events), D. stream water during stormflow without wastewater effluent with 3-day exposure time, and E. stream water during stormflow without wastewater effluent with 5-day exposure time), four testing periods (3 days, 7 days, 10 days, and 14 days to measure the rates of biouptake), and four replicates for each combination. The results being collected in this study will help identify conditions that can implicate which source as a driving force for the biouptake of heavy metals and urban stream impairment. Understanding the role of specific sources will help target mitigation strategies for developing or implementing TMDLs.