Potential Relationship Between Septic Tank Density and Nitrogen and Phosphorus Concentrations in Lake Water in Volusia County FL

1 POTENTIAL RELATIONSHIP BETWEEN SEPTIC TANK DENSITY AND NITROGEN AND PHOSPHORUS CONCENTRATIONS IN LAKE WATER IN VOLUSIA COUNTY FL A PAPER SUBMITTED FOR COMPLETION OF SENIOR RESEARCH FOR THE COLLEGE OF ARTS AND SCIENCES STETSON UNIVERSITY BY JORDAN MADIO IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF BACHELOR OF SCIENCE ENVIRONMENTAL SCIENCE ADVISORS Dr. J. Anthony Abbott, Ph.D. Dr. Kirsten Work, Ph.D. MAY 2016 i Table of Contents Table of Figures ..................................................................................................................... ii Tables ................................................................................................................................. iii Acknowledgments ................................................................................................................ iv Abstract ............................................................................................................................... v Introduction and Literature Review ....................................................................................... 1 Study Area ............................................................................................................................ 2 Methodology ......................................................................................................................... 3 GIS ...............................................................................................................................................3 Sampling Procedures.....................................................................................................................4 Results ................................................................................................................................. 6 Discussion ............................................................................................................................. 9 Works Cited......................................................................................................................... 11 ii 1. 1 1 Table of Figures Figure 1. Anova Single Factor: TP/μg/L …………………………………………………………………………………....6 Figure 2. Linear Regression: TP/μg/L…………………………………………………………………….……………...….7 Figure 3. Anova Single Factor: TN ppm………………………………………………………………………………….….8 Figure 4. Linear Regression: TN ppm……………………………………………………...…………………………………9 iii Tables Table 1. Sample Sites……………………………………………………………………………..9 Table 2. Tukey Multiple Comparison Test……………………………………………………14 iv 1. 1 1 Acknowledgments I formerly acknowledge my advisors for assisting me with my research. Dr. Abbott worked with me throughout the research process, and together we were able to refine my research interests into a practical project. Dr. Kirsten Work provided me with invaluable assistance with performing the lab work required for my water samples, and guidance for the statistical analyses of my data. I thank the Colleges of Arts and Sciences for funding the costs for sampling equipment. Finally, I thank my peers in the Environmental Science Department for providing critical feedback of my work. v 1. 1 1 Abstract The Indian River Lagoon (IRL) has suffered a decline in ecosystem function from nutrient and coliform pollution from septic tanks. Both the IRL and the study area for this research are karst landscapes. The porous limestone and sandy soils found in karst geology promote leaching of nutrients into aquifers. This study aims to identify the relationship septic tank density has on nutrient, Nitrogen and Phosphorous concentrations within Blue and South Talmadge Lakes in Volusia County Fl. Sites that contain higher concentration of septic tank densities should exhibit increased levels of nutrient pollution. Four sites were ascertained with varying septic tank densities. Water samples tested for Phosphate and Nitrogen in Ammonia form. There was strong positive correlation between septic density and increase on both total phosphate and nitrogen (R2>0.8). There was a statistically significant difference between total nitrogen concentrations from the sample site with the highest septic density from all other sample sites (p<0.05). The hypothesis was supported which suggests septic tank densities can be used to determine sites that will benefit strongest from the implementation of best management practices to reduce pollution into aquatic ecosystems, especially for systems that are limited by Nitrogen. 1 Introduction and Literature Review Nutrient pollution degrades aquatic ecosystems, and is a wide spread ecological concern throughout the world. Often the areas at risk of nutrient pollution are critical estuarine systems which provide many ecosystem services which benefit both humans and the biotic inhabitants found in these estuaries; nutrient enrichment can offset the ecological function of the system resulting most commonly from eutrophic conditions (Deegan 2002). When nutrients, Nitrogen and Phosphorus, concentrations exceed levels at which aquatic vegetation can uptake they become accessible to algae. Rapid algal growth causes blooming events which reduces available light, from increased turbidity, causing a reduction or inhibition of photosynthesis by vegetation causing stress or mortality of vegetation (Burkholder “et. al”). As vegetation and algae die microorganisms decompose this organic material, and in the process can consume mass quantities of oxygen. Anoxic conditions caused from the microorganism result in mortalities of fish and invertebrates (Deegan 2002). Anthropogenic sources of nutrient pollution from storm water runoff, fertilizers, and sewage are frequently tied to the acceleration of eutrophic algal bloom events (Anderson, “et. al.” 2002). Sewage derived N signatures have been traced to macroalgae in the Indian River Lagoon (Lapointe, “et. al.” 2015). These sewage derived N signatures could be the result from the 19 wastewater treatment facilities or from numerous septic tanks located in the IRL basin (Barile 2004). Nitrogen loading from septic tanks into surficial groundwater was found to be significant with N concentrations 50 to a 100 times greater than adjacent surficial groundwater without septic tank inputs (Reay 2004). Phosphorus concentrations in groundwater near septic tanks in St. George Island, FL. has been shown to be elevated 2-7 times above natural P concentrations (Corbett, “et. al.” 2002). Nutrients from septic tank drain fields are prone to rapid leaching when 2 1. 1 1 the drain field overlays karst geology, which contains surficial sandy sediments; positively charged N particles do not bind to sandy sediments preventing proper sequestering of septic tank N pollutants ( Harden, “et. al” 2008). Volusia County consists of karst geology. Its surficial aquifer is composed of sands and clays (Rutledge 1985) which makes aquatic systems found within this county potentially prone to septic derived nutrient enrichment. There is an inherent concern with pollution of aquifers and surficial groundwater caused by septic tanks, in particular in areas with karst geology. There is a consensus amongst scientists that septic tanks do pollute groundwater, but there is less research that attempts to understand the potential relationship between septic polluted groundwater and its potential effect on aquatic nutrient enrichment of lakes and estuaries from seepage. This research focuses on addressing this gap in literature, by studying the effect of varying near shore septic tank densities and their potential effect on nutrient enrichment in lake water in Volusia County. I hypothesized that sites containing higher concentration of septic tank densities should exhibit increased levels of nutrient pollution. Study Area There are over 300,000 septic tank systems in the IRL basin mostly found in Volusia and Brevard counties (Lapointe “et. al.” 2015). The lakes that were chosen for this research were Blue Lake and South Talmadge Lake in septic rich Volusia County. Both lakes were 58 acres with similar benthic topography. This was important in order to minimize effects from potential dilution of nutrients that would have occurred if one of the sample lakes was of larger size. An observable gradient in near shore septic tanks coupled with the karst underlying geology supported the use of these sites for my research. 3 1. 1 1 Methodology GIS Shapefiles for septic tanks and Hydrology were obtained through the St. Johns River Water Management District. Blue and South Talmadge Lakes were separated from the hydrology shapefile. Using area statistics for each lake feature established that Blue Lake is 58.66 acres, and South Talmadge Lake is 58.14 acres. Two sampling sites were chosen from each lake and were georeferenced. A buffer of 300 meters was assigned to each selection site to establish individual septic tank densities for each sampling location. Site one had 19 septic tanks, site two had zero septic tanks, site three had five septic tanks, and site four had 0 septic tanks. Site one and site four were near shore and sites two and three were located within the center of Blue and South Talmadge Lakes. Sample Sites Sample Site GPS Coordinates 1. Blue Lake 29 1.986’ N 81 16.303’ W 2. Blue Lake 29 1.944’ N 81 16.135’ W 3. South Talmadge 29 2.363’ N 81 15.911’ W 4. South Talmadge 29 2.452’ N 81 16.047’ W Table 1. 4 1. 1 1 Sampling Procedures Samples from each site were taken by boat at one meter depths, using a Van Dorn Bottle, over the course of three weeks during the month of March. Samples were placed in a cooler until they were brought back to the lab for testing. There was a sample size of three (=3) for total phosphate (TP) and a sample size of five (=5) for total Nitrogen derived from Ammonia (TN) for each of the four treatment groups. Lab work errors for TP testing from the first two samples were omitted causing a reduction in sample size. Lab Procedures The L Ascorbic Acid method was used for determining TP in each of the four treatment groups. Reagents were made; 70mL concentrated H2SO4 diluted to 500mL with distilled water (DW); 1.3715g of Potassium antimonyl tartrate solution (K(SbO)C4H4O6*½H2O) dissolved in 400 ml of DW and then diluted in 500 ml of DW; Ammonium molybdate solution from dilution of 20 grams of(NH4)6Mo7O24 into 500 mL of DW; 1.76g of concentrated ascorbic acid dissolved in 100 mL of DW to form 0.1M of Ascorbic Acid. The combined reagent was prepared by adding 50mL sulfuric acid, 5mL Potassium antimonyl tartrate solution, 15mL Ammonium molybdate solution, and 30mL ascorbic acid. The reagent was mixed and was allowed to settle. Stock P solutions were then made. 50mL of 1.25μg P stock was diluted into 50 mL of DW, forming 0.61μg stock. Then 50 mL 0.61μg stock was diluted with 50 mL of DW to form 0.31μg stock. 10 mL of 0.31μg was diluted into 90mL of DW to form 0.31μg P. This last process was repeated two more times to form 0.031μg and 0.0031μg stock solutions. 8mL of the combined reagent was then added to 50 mL to each of the three stock solutions, and to DW. The spectrophotometer was set to 880nm to measure the absorbance. The DW with the combined reagent was used to zero the spectrophotometer. Measurements for absorbance for each of three stock solutions were recorded for each sampling session. 8mL of the 5 1. 1 1 combined reagent was then added to 50mL of each of the four treatment group water samples. The absorbance for each sample was recorded. Tests to obtain TN were performed using an Ammonia sampling kit, K-1510/R-1501: 0-1 & 1-10 ppm N, from Chemetrics. 25mL from each of the four treatment groups was added to the snap cup provided in the kit. 2 drops of A-1500 Stabilizer solution were added to the cup. An ampoule was placed in the sample cup and the tip was broken off to mix contents from ampoule with sample cup contents. After a minute, the ampoule was placed in the low range comparator. The color of the ampoule contents provided the concentration of N in ppm. Statistical Methods Absorbance readings from the stock solutions were graphed along the Y axis and the known concentrations of P, from the stock solutions, were graphed along the X axis. A trend line, R2, and equation was added to the graph. The equation was then applied to the absorbance readings, Y value, from each of the four treatment groups to solve for x, the TP concentration in μg/mL. The P concentrations were converted to μg/L. An Anova Single Factor statistical test was then administered. To show potential correlation between septic tank density and TP a linear regression analysis was administered. An Anova Single Factor Statistical Test was administered to the N readings from each treatment group. A Tukey Multiple Comparison Test was applied to test individual treatment group statistical significance (treatment groups: 1-2, 1-3, 1-4, 2-3, 2-4, 3-4). A linear regression analysis was also applied to show potential correlation between septic tank density and TN concentration. 6 1. 1 1 Results There was a mean TP for sample site 1 (S1) of 27.66 g/L, sample site 2 (S2) of 20.99 g/L, sample site 3 (S3) of 18.71 g/L, and sample site 4 (S4) of 18.10 g/L. Results from an Anova Single Factor Statistical Test indicate that there was no statistically significant difference between mean TP g/L of TP for the four treatment groups, -value 0.35, though S1 had the highest mean TP concentration. Anova Single Factor: TP/μg/L Figure 1. Mean TP, g/L, is shown on the Y axis, and the sample site is shown along the X axis. Error bars are the Standard Deviation. S1 has a septic density of 19/300 m2, S2 of 0/300 m2, S3 of 5/ 300 m2, and S4 of 0/m2. The results based on septic tank density and not individual sampling sites show a positive correlation between TP g/L increase with septic tanks, R2= 0.9056. There were statistically significant results for the correlation between septic tank density and the increase in TP g/L, -value 0.0063. There was a mean TP concentration of 27.66 g/L for a septic density of 19/ 300 m2, 19.27 g/L for septic density of 0/ 300 m2, and 18.71 g/L for a septic density of 5/ 300 m2. 0 5 10 15 20 25 30 35 40 1 2 3 4 Mean TP μg/L Sample Site 7 1. 1 1 Linear Regression: TP/μg/L Figure 2. TP g/L is shown along the Y axis, and septic tank density is shown along the X axis. S2 and S4 TP readings were combined since both sites had a septic tank density of 0/300 m2. There was a mean TN concentration of 0.74 ppm for S1, 0.54 ppm for S2, 0.52 for S3, and 0.54 ppm for S4. An Anova Single Factor Statistical test identified that there was a statistically significant difference between one of the means from the four treatment groups, -value 0.001493. A Tukey Multiple Comparison Statistical Test was administered to identify the specific treatment group that differed from the other means. The results showed that S1 was the statistically different treatment group, and contained the highest concentration of TN ppm (.74 ppm) when compared to all treatment groups. y = 0.4847x + 18.003 R² = 0.9056 0 5 10 15 20 25 30 0 5 10 15 20 TP μg/L Septic Tanks/300 m² 8 1. 1 1 Anova Single Factor: TN ppm Figure 3. TN ppm is shown along the X axis, and sampling sites is shown along the Y axis. Error bars are the Standard Deviation. S1 has a septic density of 19/300 m2, S2 of 0/300 m2, S3 of 5/ 300 m2, and S4 of 0/m2. Tukey Multiple Comparison Test Site Comparison difference SE q critical value P-value S1S-2 -0.2 0.036056 -5.547 3.977 P<0.05 S1-S3 0.22 0.036056 6.101702 3.977 P<0.05 S1-S4 0.2 0.036056 5.547002 3.977 P<0.05 S2-S3 0.02 0.036056 0.547002 3.977 P >0.05 S3-S4 -0.02 0.036056 0.5547 3.977 P>0.05 S2-S4 0 0.036056 0 3.977 P>0.05 Table 2. The Tukey Multiple Comparison Test for TN (ppm) concentrations. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 3 4 TN ppm Sample Site 9 1. 1 1 A linear regression analysis was administered to septic density and TN concentration readings. The results based on septic tank density and not individual sampling sites show a positive correlation and statistically significant result for TN ppm increase and septic tank density/ 300 m2 increase, R2=0.87818 and -value= 0.0029. Linear Regression: TN ppm Figure 4. TN ppm is shown along the Y-axis, and septic tank density per 300 m2 is shown along the X-axis. S4 TP readings were combined since both sites had a septic tank density of 0/300 m2. Discussion The results for TN support the hypothesis; sampling sites that contain higher concentration of septic tank densities should exhibit increased levels of nutrient pollution. S1 had the highest septic tank density of the four-treatment groups and exhibited statistically significant difference in mean TN, -value<0.05, when compared to all other treatment groups. There was also a positive correlation between septic tank density and increase in TN concentrations, R2=0.87818. These results for TN are congruent with the findings of previous research that indicated N enrichment from septic tanks for the Indian River Lagoon is an y = 0.0108x + 0.52 R² = 0.8782 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 2 4 6 8 10 12 14 16 18 20 TN ppm Septic Tanks/ 300m² 10 1. 1 1 overlooked non point source of pollution (Lapointe et. Al. 2015). However there was a not a statistically significant difference between mean TP from all four treatment groups, but there was a positive correlation between septic density and TP increase: R2= 0.9056. Influence between septic tank derived nutrient aquatic pollution needs further study, but the results do indicate that a difference was found between a near shore sampling site (S1) with a septic density of 19/300 m2 and from a near shore site with a septic density of 0/ 300 m2. The results of this study support the use of additional research to better understand the relationship between septic tanks and lake pollution. This study was constrained by time, and would have benefited from a sampling scale between three and six months, and increased sampling sites with varying septic tank densities. During the sampling period the water table for the lakes were low, this could have reduced potential septic tank pollution from reduced pressure on the surficial groundwater. The results of my research provide tangible evidence of nutrient enrichment, in both Blue Lake and South Talmadge Lake, that would support efforts in local policy change advocating the removal of septic tanks surrounding these water bodies to effectively reduce anthropogenic nutrient enrichment. 11 1. 1 1 Works Cited Anderson, M., Donald, M. Glibert Patricia, and M. J. Burkholder. 2002. Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences. Estuaries 24:704-726. Barile, P. J. 2004. Evidence of Anthropogenic Nitrogen Enrichment of the Littoral Waters of East Central Florida. Journal of Coastal Research1237. Burkholder, J. M., D. A. Tomasko, and B. W. Touchette. 2007. Seagrasses and eutrophication. Journal of experimental marine biology and ecology 350:46-72. Deegan, A. L. 2002. Lessons learned: The effects of nutrient enrichment on the support of nekton by seagrass and salt marsh ecosystems. Estuaries 25:727-742. Harden, H. S., E. Roeder, M. Hooks, and J. P. Chanton. 2008. Evaluation of onsite sewage treatment and disposal systems in shallow karst terrain. Water research 42:2585-2597. Lapointe, B. E., L. W. Herren, D., Debortoli,D., and M. A. Vogel. 2015. Evidence of sewage-driven eutrophication and harmful algal blooms in Florida's Indian River Lagoon. Harmful Algae 43: 82-102. Reay, G. W. 2004. Septic Tank Impacts on Ground Water Quality and Nearshore Sediment Nutrient Flux. ground water 42:1079-1089. Reide Corbett, D., K. Dillon, W. Burnett, and G. Schaefer. 2002. The spatial variability of nitrogen and phosphorus concentration in a sand aquifer influenced by onsite sewage treatment and disposal systems: a case study on St. George Island, Florida. Environmental Pollution 117:337-345. Rutledge, T. A. 1985. Ground-Water Hydrology of Volusia County, Florida, With Emphasis on Occurance and Movement of Brackish Water. USGS Water Resources Investigations, Report Number, 84-4206.