Nitrogen removal from domestic wastewater using the marshland upwelling system

e c o l o g i c a l e n g i n e e r i n g 2 7 ( 2 0 0 6 ) 22–36

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Nitrogen removal from domestic wastewater using the marshland upwelling system Jeremy Fontenot, Dorin Boldor 1 , Kelly A. Rusch ∗ Institute for Ecological Infrastructure Engineering, Louisiana State University, 100 ELAB, Baton Rouge, LA 70803, USA

a r t i c l e

i n f o

a b s t r a c t

Article history:

Malfunctioning or nonexistent wastewater treatment systems are one of the primary causes

Received 13 June 2003

of water quality degradation in coastal areas. The marshland upwelling system (MUS)

Received in revised form 20

was developed as a low-cost, low-maintenance on-site treatment alternative for coastal

September 2005

dwellings, in which wastewater is injected into the saline subsoil and pushed toward the

Accepted 26 September 2005

surface by buoyancy forces. Four injection regimes, characterized by flow rate (L/min), duration (min), and frequency (h), were evaluated for a MUS located in Moss Point, Mississippi, from June 2001 to June 2002 to determine the system’s ability to remove nitrogen from

Keywords:

wastewaters generated from recreational facilities. Nitrogen data were collected from a

Nitrogen

cluster of monitoring wells surrounding the injection well. The injection regime of 2.8 L/min

Marshland upwelling system

(30 min/3 h) resulted in the best removal efficiency. Total kjeldahl nitrogen (TKN) and total

Wetlands

ammonia nitrogen (TAN) were reduced from an influent average of 168 and 160 to 2.4 and

Decentralized wastewater

1.5 mg-N/L, respectively. Vector distance-based removal coefficients were estimated to be

treatment

0.88 and 0.84 m−1 for TKN and TAN, respectively. Subsequently, 3.2 and 3.1 vector meters were required to reduce TKN and TAN to 10 mg-N/L. The probabilities of the system effluent to exceed 10 mg-N/L were estimated to be 3% for TKN and 0% for TAN, respectively. Benchscale laboratory studies indicated the potential for further treatment in the upper zone of the MUS system due to increases in redox potential caused by the Juncus roemerianus’ rhizosphere, which provided a nitrification zone. © 2005 Elsevier B.V. All rights reserved.

1.

Introduction

Numerous natural resources and recreational opportunities provided by wetlands, estuaries, and coastal water bodies have resulted in a population explosion in these areas; the human population living in coastal areas in the United States is expected to exceed 165 million people by 2010 (NOAA, 1998). A corresponding increase in the number of coastal dwellings is expected to result in greater coastal pollution due to improperly treated wastewater (NOAA, 1998). Limited-use systems, mechanical plants, and septic systems are the traditional decentralized methods employed to treat domestic wastew-

∗

ater (Ache and Wenger, 1999; USEPA, 2002). Under ideal conditions, these traditional treatment alternatives work well. However, coastal areas provide unique challenges to their implementation due to the location and sporadic usage of the dwellings. Mechanical treatment plants may not be a viable option for a community, partially due to their high capital cost. Limiteduse systems, which require maintenance and a constant supply of chlorine, are often rendered ineffective due to improper or no maintenance (Ache and Wenger, 1999). Septic systems present problems because camps are often built directly above water or in locations with a high water table, resulting in an

Corresponding author. Tel.: +1 225 578 8528; fax: +1 225 578 8662. E-mail addresses: [email protected] (D. Boldor), [email protected] (K.A. Rusch). 1 Tel.: +1 225 578 7762; fax: +1 225 578 8662. 0925-8574/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.ecoleng.2005.09.013

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Fig. 1 – Cross-sectional view of a marshland upwelling system (MUS). The arrows indicate the expected direction of the wastewater flow upon injection into the subsurface soil matrix.

ineffective absorption field (USEPA, 2002). In addition, these traditional on-site wastewater treatment systems do not focus on nutrient removal, an issue that has been recognized as having a detrimental impact on aquatic ecosystems (Delaune and Jugsujinda, 2003; de-Bashan and Bashan, 2004) and one that is coming under scrutiny with EPA’s National Nutrient Criteria (USEPA, 2001). Natural and constructed wetlands have been shown to remove nutrients from a variety of wastewater sources (Aguirre et al., 2005; Breen, 1990; Hench et al., 2003; Jenssen et al., 2005; Jin et al., 2002; Kadlec and Knight, 1996; Luederitz et al., 2001; Obarska-Pempkowiak and Gajewska, 2003; Tanner et al., 2002). Wetland macrophytes uptake and microorganisms metabolize organic and inorganic pollutants commonly found in wastewater, and the sand/silt/clay matrix of wetland soils adsorbs and filters nutrients and bacteria, respectively (Gopal, 1999; Hench et al., 2003; Lakatos et al., 1997; Lau and Chu, 2000; Luederitz et al., 2001; Sakadevan and Bavor, 1999). However, the traditional natural and constructed wetland designs may be neither an effective nor a viable option for the treatment of domestic wastewater in coastal areas due to the minimal land elevation, lack of upland boundaries, and high water tables. The marshland upwelling system (MUS) was developed at Louisiana State University as an on-site wastewater treatment alternative for coastal dwellings (Richardson and Rusch, 2005; Richardson et al., 2004; Stremlau, 1994; Watson and Rusch, 2001; Watson, 2000). The system consists of a collection/distribution tank, an injection pump, timer, injection well, one monitoring well, and the subsurface soil matrix (Fig. 1). The native soil characteristics and background salinity influence the selection of the injection well depth. The collection/distribution tank (retention time of less than 1 day) receives gray and black water from the dwelling, which is then intermittently injected below ground surface (bgs) to a specified depth. Intermittent injection facilitates pressure dissipation, thus minimizing the potential for hydraulic channelization. Advective forces during the active pumping phase transport the wastewater radially away from the point of injec-

tion. During the resting phase, buoyancy forces resulting from the density gradient between the native, saline groundwater, and the fresh wastewater move the wastewater vertically upwards. These forces decrease as the wastewater migrates upwards toward the surface, resulting in a more lateral dispersion of the wastewater plume. Natural groundwater flow may impart a bias in plume movement in one direction. However, most coastal areas have minimal hydraulic gradients; thus, plume development tends to be approximately symmetrical. During plume movement, the MUS takes advantage of the physical and biochemical unit operations and processes naturally occurring in the sand/silt/clay matrix to remove the bacteria, organic matter, and nutrients from the wastewater. The overall operational and treatment efficiency is dependent on a number of factors including hydraulic, organic, solids, nutrient, and bacteria loadings and injection regimes. To date, the treatment efficiency of the MUS has been quantified for bacteria (Richardson and Rusch, 2005; Watson, 2000; Watson and Rusch, 2001, 2002) and phosphorus (Evans, 2005). The present research focuses on quantifying the nitrogen removal capabilities of the MUS. The objectives of this study were to: (1) evaluate the nitrogen removal/retention capabilities of the MUS containing sandy, loamy soils; (2) determine the operational hydraulic, nitrogen, organic, and solids loading rates for meeting an effluent nitrogen limit of 10 mgN/L; and (3) determine whether wetland macrophytes could beneficially influence the near surface soils for nitrification. Objectives one and two were addressed via field studies, while objective three was accomplished through a laboratory study.

2.

Methodology

2.1.

Study site

The study site was located within the Grand Bay National Estuarine Research reserve (NERR), Mississippi (Fig. 2). The Grand Bay NERR covers 75 km2 and is a part of the Mississippi Sound

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Fig. 2 – The research site was located in the grand Bay National Estuarine Research Reserve (NERR), Moss Point, Mississippi.

estuary. The watershed is home to approximately 50–60 residents, mostly residing along Bayou Cumbest, classified as the most impaired shellfish harvesting water body in the state of Mississippi (MDEQ, 1996). A number of the septic systems used for wastewater treatment by these residents were found by a Mississippi Department of Health survey (MSU, 2000) to be operating ineffectively. The system was installed within a saline marsh vegetated with the wetland macrophyte Juncus roemerianus (needlegrass rush). The marsh was identified as having high salinity with mean subsurface concentrations of approximately 31 ppt. A soil characterization was performed on soil corings taken at 0.3 m increments. The fractions of sand, silt, and clay in the soil matrix (Table 1) were determined by conducting sieve (ASTM C117, C136) and hydrometer analyses (ASTM D422). The organic carbon content (ASTM D2974) was also measured for the soil surface and at the injection depth (ASTM, 1995;

Bardet, 1997). Several distinctive layers were identified within the soil matrix of the system. The upper 1.2 m was a dark, highly organic soil with characteristics analogous to that of the Scatlake series of soil found along the Gulf coast of the United States. Scatlake soils are semifluid mineral soils, which are generalized as poorly draining due mostly to the slope of the surrounding region (USDA, 1984). A noticeable trend was identified with the high sand and silt percentage being replaced by sand as soil layers became progressively deeper. Also, a noticeable high clay layer was identified between the 1.2–2.4 m depths, which may act as an aquitard.

2.2.

Experimental MUS

The experimental MUS treated wastewater (black and gray) from a public restroom and two private camps (Fig. 3). The primary camp was generally occupied throughout the year.

Table 1 – Selected properties of the field soil at various depths Property Sand Silt Clay Mean grain size diameter (d50 ) Uniformity coefficient (d60 /d10 ) Fraction of organic content (foc ) USDA classification N/A: not analyzed. a b

Excludes plant matter. Unable to calculate d10 values.

Units % % % mm %

Depth interval (m) 0–1.2a 44 44 12 0.10 –b 9.0 ± 0.5 Loam

1.2–2.4 37 40 23 0.04 –b N/A Loam

2.4–3.0 62 23 15 0.10 –b N/A Sandy loam

3.0–3.8 86 9 5 0.16 1.08 0.5 ± 0.1 Loamy sand

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Fig. 3 – The MUS-treated wastewater from a public restroom (PR), primary camp (1), and camp (2).

Camp 2 was very seldom used, and the public restroom was used mostly during the spring and summer months. The wastewater from the public restroom and the primary camp was collected in a 208-L polyethylene collection tank buried 0.3 m bgs and anchored with a 508 kg concrete collar to prevent floatation as a result of the high water table (Fig. 3). A submersible 373 W grinder pump with a float switch transferred the wastewater to a 1325-L polyethylene collection/distribution tank located behind Camp 2 while a 186 W low flow, high pressure progressive cavity pump controlled by a programmable timer and float switch injected the wastewater into the marsh at a depth of 3.8 m. A water meter and pressure transducer, placed on the injection line, monitored wastewater injection volume and pressure, respectively. A slow, steady rise in pressure over time would indicate potential system clogging, while a sudden drop in pressure during an injection cycle would indicate hydraulic channelization. The injection well was comprised of an open-ended 1.9 cm diameter PVC pipe enclosed in a 5.1 cm diameter PVC pipe casing (Fontenot, 2003). A pressure relief valve and a by-pass line were placed on the injection line to divert wastewater away from the site in case of system clogging. Twenty-one groups of monitoring wells at depths of 1.5, 2.3, and 3.0 m surrounded the injection well concentrically to allow dimensional monitoring of the site (Fig. 4). To avoid issues of potential surface contamination, no monitoring well was shallower than 1.5 m. The monitoring wells were similar in design to the injection well except for a 0.3 m section of well screen containing 0.25 mm slits placed on the end of the inner pipe. The subsurface environment was characterized for pH, salinity, temperature, and nitrogen following system construction to provide data on background conditions (Table 2).

Fig. 4 – The experimental MUS consists of one injection well (
) and 38 monitoring wells at depths of 1.5 m (), 2.3 m (), and 3.0 m (䊉). Each grid square is equal to 0.61 m × 0.61 m.

2.3.

Experimental design and operation

2.3.1.

Field study

A suite of four studies was executed to investigate the impact of the injection regime (flow rate, duration of injection, injection frequency) on nitrogen removal (Table 3). The injection regime governs the hydraulic/solids/organic/nutrient loading rates of the system and is therefore a critical operational parameter for the MUS. Determination of the optimum injection regime allows the MUS to achieve maximum system loading, while effectively removing nitrogen from wastewater without hydraulic difficulties. A biweekly sampling protocol was established during which samples were collected from the influent, bayou (background conditions), and selected monitoring wells. Samples were collected in 1-L polyethylene bottles and in whirlpack bags (bacteria), immediately placed on ice, and transported to the Civil and Environmental Engineering Water Quality Lab at Louisiana State University for analysis. Influent samples were analyzed for total suspended solids (TSS), volatile suspended solids (VSS), fecal coliforms, and filtered (<1.2 ␮m) and unfiltered carbonaceous biochemical oxygen demand (CBOD5 ), total kjeldahl nitrogen (TKN), ammonia nitrogen (TAN), nitrate

Table 2 – A summary of the native groundwater conditions at field site Property

Salinity pH Temperature TKN TAN NO2 NO3

Units

ppt ◦ C mg-N/L mg-N/L mg-N/L mg-N/L

n

32 28 27 24 26 24 26

Surface water

17.1 ± 7.3 7.5 ± 0.4 24.1 ± 6.8 0.1 ± 1.3 0.09 ± 0.1 0.004 ± 0.01 BDL

n: Number of samples; BDL: below detection limit.

Subsurface water (m) n

1.5

2.3

3.0

15 14 14 1 3 3 3

31.7 ± 3.4 6.5 ± 0.2 21.8 ± 2.7 0.9 0.3 ± 0.1 0.02 ± 0.004 BDL

30.3 ± 3.7 6.6 ± 0.1 22.1 ± 2.6 0.9 0.6 ± 0.3 0.01 ± 0.003 BDL

30.9 ± 3.6 6.8 ± 0.3 22.9 ± 2.7 0.6 0.6 ± 0.1 0.006 ± 0.003 BDL

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Table 3 – Injection flow rates and frequencies employed at the field site Study period (mm/dd/yy) 06/21/01–09/17/01 09/17/01–11/05/01 11/05/01–04/02/02 04/02/02–06/17/02 a

Elapsed time (day)

Injection flow rate (L/min)

Injection frequency

Volume of WW injected (L)

88 49 147 78

1.9 5.5 2.8 2.8

30 min/3 h 30 min/3 h 30 min/3 h 15 min/h

13213 8942 41851 12207

Theoretical hydraulic loading rate (L/day)a 456 1320 672 1008

Assumes an adequate volume of wastewater is present in holding tank to trigger injection.

(NO3 − –N), nitrite (NO2 − –N), total phosphorus (TP), and orthophosphate (PO4 –P). The bayou and monitoring well samples were analyzed for TKN, TAN, NO3 − –N, and NO2 − –N. All analyses were performed in accordance with Standard Methods (APHA, 1998). In situ parameters (salinity, pH, temperature) were measured for all samples, and dissolved oxygen (DO) concentration was also measured for the influent and the bayou. Redox potential was measured using copper/platinum sensors constructed according to Patrick et al. (1996) and placed in 1 cm PVC pipe alongside the monitoring wells in the same casing. The redox potential measurements, corrected to Eh (Patrick et al., 1996), were recorded at various locations within and outside of the plume to determine the impact of the wastewater on the subsurface environment.

2.4.

Table 4 – Synthetic wastewater recipe for laboratory studies Constituent Dextrose Glutamic acid Na2 ·EDTA FeCl3 ·6H2 O CuSO4 ·5H2 O ZnSO4 ·7H2 O CoCl2 ·6H2 O MnCl2 ·4H2 O Na2 MoO4 ·2H2 O Sodium phosphate Ammonium chloride

Measured concentration (mg/L) 38.6 CBOD5 0.3 0.2 (0.04 mg/L Fe) 7 × 10−4 (0.18 ␮g/L Cu) 0.001 (0.35 ␮g/L Zn) 7 × 10−4 (2.5 ␮g/L Co) 0.01 (0.004 mg/L Mn) 4 × 10−4 (0.18 ␮g/L Mo) 0.5 PO4 P 2.1 NH4 N

Note: Concentrations based on values observed in 1.5 m monitoring wells.

Laboratory study

Turriciano (2005) determined the maximum sorption capacity of the system’s soils to be 1667, 1250, and 1000 mg/kg for soils with pore water salinities of 0, 5, and 10 ppt, respectively. Thus, it can be assumed that the majority of ammonium within the reduced zones of the MUS is removed/retained by adsorption to the soil matrix. However, the rhizosphere provides an excellent area for the attachment and growth of beneficial microorganisms to the root structure of the wetland macrophytes and for the transfer of oxygen from the root structure to the surrounding soils (Chappell and Goulder, 1994; Gumbricht, 1993). This enriched oxygen zone could provide additional ammonium treatment via nitrification. Since the shallowest monitoring wells were 1.5 m deep, no field data were available to determine the additional nitrogen treatment within the rhizosphere. Subsequently, laboratory studies were performed to gain a better understanding of the influence wetland macrophytes could have on redox potential and thus on the nitrogen removal process in the upper zone of the MUS. Two replicated treatments were investigated: planted (J. roemerianus) and unplanted soil columns. Each polyethylene column (124 L; 50 cm diameter, 63 cm height; Fig. 5) contained 3 cm of coarse gravel and 2 cm of 20–40 mesh sand to distribute the wastewater. The columns were filled with soil from the field site, resulting in a media volume of 114 L. The media were saturated with 10 ppt synthetic saltwater (Instant Ocean® ) to reflect the near surface conditions at the field site. Sampling/redox ports were placed at depths of 7 (root zone), 27, and 47 cm to allow data and sample collection from various treatment zones within the soil matrix. A solenoid valve was placed on the 7 cm sampling port to allow simulation of high

and low tides. Synthetic wastewater (Table 4) was injected in the bottom of each of the tanks using a variable-flow peristaltic pump at a flow rate of 3.0 mL/min (30 min/3 h). The system was acclimated for 1.5 months prior to the start of the study, which ran from 13 March to 23 July 2002. Samples were collected twice a week from all sampling ports and analyzed for pH, temperature, salinity, and redox potential. Once a week, samples were analyzed for TAN, NO2 –N, and NO3 –N.

2.5.

Data analyses

The mean hydraulic loading rate for each study was calculated based on the wastewater volume injected between two consecutive sampling events and averaged over the number of sampling events in the study. Solids, organic, and nutrient loading rates were similarly calculated for each individual study. Means and standard deviations were determined for the influent (field) parameters for the entire study period. Mean and standard error values for in situ and nitrogen parameters were calculated with respect to depth and vector distance (VD) for each injection scheme of the field study. A nitrogen effluent limit of 10 mg-N/L was used when calculating TKN and TAN removal efficiencies. Removal was calculated based on the data from the 1.5 monitoring wells and the influent measurements. Visual comparisons of the nitrogen concentrations prior to system operation and following the last study were constructed using three-dimensional mesh plots. A first-order decay analysis was performed to describe the relationship between mean TKN and TAN concentrations and vector distance for each study. This relationship was used to estimate removal rate constants, travel distances to reduce concentrations below 10 mg-N/L, and surface concentrations. The mean

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Fig. 5 – Laboratory studies were performed to investigate whether the macrophyte Juncus roemerianus would positively influence the redox potential in the rhizosphere of the MUS. Two replicated treatments were used: unplanted and planted.

TKN and TAN data were also fit to the Weibull probability density function to allow predictions of exceeding the 10 mgN/L limit at the surface of the marsh. The 5.5 L/min injection regime was performed in an effort to establish an upper flow-rate limit for the MUS. The elevated flow rates generated hydraulic channels in the subsurface, impairing the efficiency of the system. The channelization disappeared when the flow rate was decreased to normal operating ranges. The data collected for the 5.5 L/min study are not considered representative of normal operations, thus, they was not included in the first-order decay analysis. For the laboratory study, the means and the standard deviations of in situ and nitrogen parameters were calculated for each sample depth. The data were statistically analyzed using t-test and ANOVA (˛ = 0.05) to investigate whether differences

existed between the treatments. All data analyses, for both field and laboratory study, were performed in Microsoft Excel 2000, Sigma Plot 8.0, and SAS 6.12.

3.

Results

3.1.

Field study — overall analysis

The influent wastewater was characterized as high strength with respect to nutrients and fecal coliforms, and medium strength with respect to CBOD5 and TSS (Table 5). The unfiltered TKN and TAN ranged from 12 to 272 and from 8 to 252 mg-N/L, respectively. This wide variation of concentrations is typical of sporadically used coastal dwellings and

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Table 5 – Influent wastewater parameters at field site Standard methoda procedure

Parameter

Units

Unfiltered n

Fecal coliform CBOD5 TSS VSS TKN TAN NO2 − –N NO3 − –N TP PO4 –P

c

9222 D 5210 B 2500 D 2540 E 4500-Norg B 4500-NH3 D 4500-NO2 − B 4500-NO3 − B 4500-P E 4500-P B

col/100 mL mg/L mg/L mg/L mg-N/L mg-N/L mg-N/L mg-N/L mg-P/L mg-P/L

23 21 31 28 22 21 26 13 15 17

Results 7.2 × 105 ± 2.1 × 106 274 ± 34.2 273 ± 62.4 147 ± 29.0 136 ± 70.64 112 ± 63.8 NA BDL 16.7 ± 9.6 12.7 ± 7.2

Filtered (<1.2 ␮m) n NA 25 NA NA 22 21 26 13 16 15

Typical wastewaterb

Results NA 214 ± 13.7 NA NA 107 ± 69.0 103 ± 59.4 0.1 ± 0.3 BDL 14.7 ± 8.9 13.5 ± 6.6

103 –108 10–350 120–400 95–315 8–25 12–45 0 0 4–12 3–8

NA: not analysed; BDL: below detection limit. a b c

APHA (1998). Metcalf & Eddy Inc. (2003). Geometric mean ± standard deviation.

presents complexities in assessing system operation. Eightytwo percent of the unfiltered influent nitrogen existed as ammonia, while the filtered TAN:TKN ratio increased to 96%. Subsequently, the majority of the nitrogen load (soluble ammonium) was immediately available to the subsurface, with a small additional, delayed load from the mineralization of organic nitrogen to ammonium. The filtered:unfiltered ratios for TKN and TAN were 0.79 and 0.92, respectively. Thus, attempts to remove as many solids as possible prior to injection would reduce the ammonia-nitrogen load only slightly. The small amount of nitrite and mean dissolved oxygen concentration of 1.2 mg/L suggests that a low level of nitrification may have been taking place in the collection/distribution tank. The total volume of wastewater injected over the entire study period (6/21/01–6/17/02) was 76,213 L (Table 3), resulting in 443 (to the 2.3 m monitoring wells) and 110 (to the 1.5 m monitoring wells) pore volume exchanges for the inner (radial distance −1.4 m) and outer (radial distance −7 m) wells, respectively. These calculations assumed a cylindrical plume and porosities of 0.37 and 0.20 for sand and clay, respectively. The assumption of a cylindrical plume provided conservative (low) estimates of the pore volumes exchanges when compared to a rhodamine tracer study performed at the same site (Richardson et al., 2004). However, the estimates more than indicate that dilution did not play a substantial role in nitrogen reduction observed in the MUS. A total of 194 samples were analyzed for NO2 –N over the study period. The average concentrations for the 1.5 and 2.3 m depth samples were 0.01 and 0.02 mg-N/L, respectively, representing no change from the influent concentration. There was no NO3 –N detected in any of the 280 samples analyzed throughout the study. Thus, no additional data analyses were performed on these parameters. A total of 238 monitoring well samples were analyzed for TKN. Eighty-two of these (34%) yielded TKN concentrations above the 10 mg-N/L limit. However, only four (6%) of the 1.5 m samples (total of 68 samples) had a concentration above 10 mg-N/L, with the highest concentration being 13.8 mg-N/L. The mean TKN concentration at the 1.5 m samples was 2.4 mgN/L for the entire study, resulting in a TKN removal efficiency of 98% in the MUS. The highest TKN concentrations recorded

throughout the study (58 ± 5 mg-N/L) were in the inner circle of 3.0 m monitoring wells (A, B, C, and D in Fig. 3; VD = 1.4 m). In the middle circle of 3.0 m monitoring wells (I, J, K, and L in Fig. 3; VD = 2.6 m), the concentrations, still elevated, were only half of those in the inner circle. By the end of the study, the outer 3.0 m monitoring wells (R, S, and U; VD = 6.9 m) had TKN concentrations ranging from 1.0 to 2.0, while the outer 1.5 m wells (R, S, and U; VD = 7.3 m) had concentration levels of approximately 1.0–1.5, providing evidence that the plume moved laterally as well as vertically. The mean TAN concentration in the 1.5 m well samples was 1.5 mg-N/L resulting in a removal efficiency of 98.6%. Only 88 (37%) of the 286 samples exceeded the limit of 10 mg-N/L, with only three samples in the 1.5 m wells above this limit. The highest concentrations were recorded for the 3.0 m wells of the inner circle (61 ± 6 mg-N/L). The middle circle of 3.0 m depth monitoring wells was the other location where high TAN concentrations were recorded (also half of those in the inner circle). By the end of the study, the outer 3.0 m monitoring wells (R, S, and U; VD = 6.9 m) had TAN concentrations approximately the same as TKN, while the outer 1.5 m wells (R, S, and U; VD = 7.3 m) had concentration levels of <1.0 mg-N/L, providing evidence that the plume moved laterally as well as vertically (Fig. 6). The background redox potential measurements were substantially higher than those measured within the plume, reflecting the reducing nature of the wastewater (Table 6). Both the background and plume measurements showed an increase in redox potential with decreasing subsurface depth, providing evidence that nitrification may be possible in the upper subsurface zones.

3.2. Field study — removal as a function of flow regime Due to varying field conditions (i.e. influent concentration, temperature, pH, tidal pattern, injection pressure, and salinity), the direct comparison of nitrogen removal as a function of varying flow regimes is statistically difficult. Focht (1974) and Wood et al. (1999) also noted the difficulty in assessing nitrogen removal with a fluctuation in temperature and pH.

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Fig. 6 – Surface plots of TAN before and after the field study illustrate the movement of the wastewater plume at 1.5 m depth (top), 2.3 m depth (middle), and 3.0 m depth (bottom).

Table 6 – Depth-dependent redox potential within and outside the plume at the field site Depth (m) 3.0 2.3 1.5

Redox potential within plume (mV) −144 ± 9.3 (13) −75 ± 12 (13) −60 ± 20 (12)

Number of sampling events represented in parentheses.

Background redox potential (mV) −30 ± 4.3 (13) 1.0 ± 15 (13) 46 ± 5.0 (13)

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Table 7 – Depth and injection regime-dependent salinity, pH, and temperature for the field study Sampling location

1.9 (L/min) (30 min/3 h)

2.8 (L/min) (30 min/3 h)

5.5 (L/min) (30 min/3 h)

2.8 (L/min) (15 min/h)

Salinity (ppt) 3.0 m Wells 2.3 m Wells 1.5 m Wells Surface water

11.9 21.2 21.9 10.9

± ± ± ±

4.5 (9) 3.8 (9) 3.3 (9) 1.5 (9)

13.2 24.8 27.2 22.0

± ± ± ±

1.0 (11) 0.8 (11) 0.5 (11) 7.2 (15)

10.8 ± 2.0 (3) 21.4 ± 3.6 (3) 24.3 ± 5.9 (3) 24.1 ± 2.1 (2)

12.7 21.2 23.5 14.0

± ± ± ±

4.9 (4) 2.6 (4) 3.5 (4) 3.8 (4)

pH 3.0 m Wells 2.3 m Wells 1.5 m Wells Surface water Influent

6.7 6.4 6.3 7.1 7.6

± ± ± ± ±

0.3 (6) 0.1 (6) 0.2 (6) 0.2 (6) 0.1 (4)

6.8 6.7 6.5 7.6 8.0

± ± ± ± ±

0.1 (11) 0.1 (11) 0.1 (11) 0.4 (15) 0.6 (14)

7.0 (2) 6.7 (2) 6.4 (2) 7.6 ± 0.01 (2) 8.1 ± 0.04 (2)

6.8 6.8 6.5 7.4 7.3

± ± ± ± ±

0.1 (4) 0.1 (4) 0.1 (4) 0.1 (4) 0.2 (4)

Temperature (◦ C) 3.0 m Wells 2.3 m Wells 1.5 m Wells Surface water Influent

24.1 24.9 25.1 30.6 27.1

± ± ± ± ±

0.8 (6) 0.9 (6) 0.8 (6) 1.4 (6) 0.3 (3)

19.9 18.9 18.6 17.7 18.4

± ± ± ± ±

1.0 (11) 1.0 (11) 0.8 (11) 6.0 (15) 5.9 (14)

23.3 ± 1.1 (2) 23.4 ± 1.7 (2) 23.5 ± 1.2 (2) 25.2 ± 1.1 (2) 19.0 ± 2.3 (2)

20.4 20.8 20.6 24.8 24.3

± ± ± ± ±

1.2 (4) 1.4 (4) 1.6 (4) 1.0 (4) 1.5 (4)

Number of sampling events represented in parentheses.

Table 8 – A comparison of the temperature, pH, and salinity between the field studies Flow rate and frequency

Temperature (◦ C)

pH

Salinity (ppt)

24.5 ± 1.10 23.6 ± 1.54 19.0 ± 2.40 21.3 ± 1.81

6.46 ± 0.35 6.65 ± 0.36 a 6.71 ± 0.34 a 6.64 ± 0.30 a

18 ± 7.7 a 20 ± 8.7 ab 21 ± 8.2 b 20 ± 7.4 b

1.9 (L/min)–(30 min/3 h) 5.5 (L/min)–(30 min/3 h) 2.8 (L/min)–(30 min/3 h) 2.8 (L/min)–(15 min/h)

Values with similar letters are not significantly different at ˛ = 0.05.

However, general patterns and trends are evident and will be presented. The in situ parameters measured over each of the study periods are summarized by injection regime and depth (Table 7) and injection regime (Table 8). Salinity decreased with depth and showed no real correlation to surface water salinity. With the exception of the 1.9 L/min study, no significant differences were observed between the studies. However, the mean salinities from all four studies were significantly

(p < 0.05) lower than the background salinity prior to system operation, indicating that the natural groundwater flow had minimal influence on the wastewater plume. The mean pH values for the four studies varied by only 0.25 unit even though the first study was significantly different than the last three studies. Given the small deviation between studies, it is safe to assume that the wastewater had little impact on the subsurface pH. As expected, the mean temperatures were significantly different for the four studies. Also, during the sum-

Table 9 – Depth injection regime-dependent TKN and TAN concentrations for field study Sampling location

1.9 (L/min) (30 min/3 h)

Mean TKN concentration (mg-N/L) Influent 48 3.0 m Wells 22 2.3 m Wells 4.8 1.5 m Wells 2.4 Surface water 0.6

± ± ± ± ±

2.8 (L/min) (30 min/3 h)

5.5 (L/min) (30 min/3 h)

2.8 (L/min) (15 min/h)

13.2 (5) 33 (5) 7.2 (5) 1.8 (5) 0.3 (4)

168 33 12 2.4 0.3

± ± ± ± ±

68.2 (10) 6.7 (11) 1.6 (11) 0.8 (10) 0.03 (9)

87 ± 21 (3) 26 (2) 5.8 (2) 6.6 (1) 0.2 (1)

177 37 16 1.8 0.6

± ± ± ± ±

62.1 (6) 19 (4) 18 (4) 1.0 (4) 0.2 (4)

Mean TAN concentration (mg-N/L) Influent 42 ± 16.2 (3) 3.0 m Wells 23 ± 25 (3) 2.3 m Wells 6.0 ± 8.3 (3) 1.5 m Wells 2.2 ± 1.9 (3) Surface water 0.2 (2)

160 28 8.7 1.5 0.04

± ± ± ± ±

62.9 (10) 6.4 (11) 1.4 (11) 0.3 (11) 0.01 (11)

81 ± 14 (3) 32 (2) 4.2 ± 1.8 (2) 3.3 (1) 0.08 (1)

131 32 10 2.3 0.1

± ± ± ± ±

34.2 (5) 12 (5) 7.7 (5) 1.8 (5) 0.1 (5)

Number of sampling events is represented in parentheses; Note: samples sizes <3 have no standard deviation.

31

e c o l o g i c a l e n g i n e e r i n g 2 7 ( 2 0 0 6 ) 22–36

Table 10 – Summary of a first-order decay analysis performed to estimate removal rate constants, predicted surface concentration, and predicted travel distance Injection flow rate (L/min)

First-order rate constant (/m)

Predicted surface concentration (mg-N/L)

Predicted travel distance (m)c

Probability to exceed 10 mg-N/L at the surface (%)

TKN 1.9 2.8a 2.8b

0.77 0.88 0.89

2.7 6.1 5.9

2.1 3.2 3.2

0 3 5

TAN 1.9 2.8a 2.8b

0.63 0.84 0.85

4.1 5.6 5.2

2.4 3.1 3.1

0 0 5

a b c

Injection frequency of 30 min/3 h. Injection frequency of 15 min/h. Required to meet effluent limit of 10 mg-N/L.

mer months—1.9 L/min (30 min/3 h) and 2.8 L/min (15 min/h) studies—the temperatures in wells were lower than those at the surface, with the opposite being true for the winter months. Over the duration of the study, at least an order of magnitude decrease in TKN and TAN concentrations from the influent to the 2.3 m monitoring wells was observed for each injection regime tested (Table 9). Further reductions of TKN and TAN were observed as the wastewater traveled to the 1.5 m monitoring wells, and this reduction is expected to continue as the plume moves toward the surface. A first-order decay analysis was performed to estimate the TKN and TAN removal rate constants for each study (Figs. 7 and 8; Table 10). As the data indicate, the TKN and TAN removal rate constants for the

1.9 L/min study were substantially lower than the constants for the other two studies. The two 2.8 L/min studies showed no differences in the estimated influent and removal rate constants. The estimated removal rate constants were used to calculate predicted surface concentrations and travel distances required to reduce nitrogen concentrations below the 10 mg-N/L limit (Table 10). These calculations assumed that a droplet of wastewater traveled vertically upwards from the point of injection in a liquid medium. Thus, no consideration was given to porosity and tortuosity, resulting in very conservative estimates. For each injection scheme evaluated, the predicted surface concentration was well below the 10 mg-N/L limit, and the required vector distances to achieve nitrogen removal to 10 mg-N/L was less than the injection well depth

Table 11 – Daily (mean ± S.D.) hydraulic, organic, TKN, TAN, and solids loading rates for field site Injection flow rate (L/min)

Hydraulic (L/day)

Organic (g/day)

TKN (g/day)

TAN (g/day)

Solids loading rate TSS (g/day)

202 ± 124 376 ± 403 188 ± 67

1.9 2.8a 2.8b a b

35 ± 12.8 105 ± 127 90 ± 40

5.9 ± 7.33 47 ± 74 29 ± 7.6

3.0 ± 3.29 40 ± 41 24 ± 8.8

13 ± 4.1 121 ± 28 29 ± 57

VSS (g/day) 10 ± 2.2 102 ± 23 24 ± 5.1

Injection frequency of 30 min/3 h. Injection frequency of 15 min/h.

Table 12 – A summary of the in situ parameters in the unplanted and planted columns Column

Depth (cm)

Salinity (ppt)

Eh (mV)

pH

Temperature (◦ C)

Unplanted

Surface 7 27 47

20.4 16.8 12.1 10.4

± ± ± ±

1.6 (19) 0.5 (73) 0.4 (78) 0.4 (81)

1.7 −32 −62 −49

± ± ± ±

15.7 (51) 17 (25) 6.8 (25) 7.8 (24)

8.0 ± 0.1 (15) 7.5 ± 0.04 (65) 7.2 ± 0.03 (69) 7.3 ± 0.03 (71)

23.5 ± 0.7 (18) 24.4 ± 0.2 (73) 24.6 ± 0.2 (79) 24.7 ± 0.2 (83)

Planted

Surface 7 27 47

20.8 17.5 12.4 10.4

± ± ± ±

3.8 (6) 0.6 (75) 0.6 (82) 0.4 (84)

102 161 4.7 −9.0

± ± ± ±

17.2 (48) 22.4 (25) 24 (25) 21 (25)

8.1 ± 0.3 (3) 7.5 ± 0.05 (65) 7.3 ± 0.03 (73) 7.3 ± 0.02 (74)

20.7 ± 0.1 (2) 24.8 ± 0.2 (77) 24.8 ± 0.2 (84) 24.8 ± 0.2 (86)

Influent

–

7.8 ± 0.6 (35)

25.5 ± 0.3 (86)

Note: Sample size is noted in parenthesis.

8.4 ± 0.5 (33)

–

32

e c o l o g i c a l e n g i n e e r i n g 2 7 ( 2 0 0 6 ) 22–36

Fig. 7 – TKN removal with respect to vector distance from the point of injection was analyzed using a first-order decay injection well at flow rates of (a) 1.9 L/min (30 min/3 h), (b) 2.8 L/min (30 min/3 h), and (c) 2.8 L/min (15 min/h).

of 3.8 m in all cases. The probabilities of exceeding the effluent limit at the surface of the marsh were <5% in all cases (Table 10). The hydraulic, organic, TKN, TAN, TSS, and VSS loading rates (mass per day) were calculated for each injection regime (Table 11). Traditional loading rates (i.e., volumetric or surface loading) could not be calculated since there are no physical boundaries to the MUS. The loading rates exhibit large standard deviations due to the sporadic usage of most coastal dwellings. No statistical differences were observed between

Fig. 8 – TAN removal with respect to vector distance from the injection well at flow rates of (a) 1.9 L/min (30 min/3 h), (b) 2.8 L/min (30 min/3 h), and (c) 2.8 L/min (15 min/h).

treatments for each of the loadings; however, the large variations make it very difficult to practically compare the impact of loading on nitrogen removal.

3.3.

Laboratory study

The laboratory study was performed to investigate whether the marsh vegetation could potentially influence nitrification in the rhizosphere. While the mean salinities of the planted and unplanted columns decreased with depth, there were no significant differences between the treatments (p = 0.71,

e c o l o g i c a l e n g i n e e r i n g 2 7 ( 2 0 0 6 ) 22–36

33

The TAN concentrations profiles (Fig. 9) show an initial increase from the point of injection as depth decreases in both the planted and control columns, followed by a decrease. The initial increase was attributed to breakdown of organic content in both planted and control columns. The higher rate of increase in the planted versus the control column may be attributed to the additional decay of plant material (Matheson et al., 2002). Overall first-order removal rate constants were calculated using mass balances for both the control (0.002/day) and planted columns (0.003/day). However, in the upper 7 cm of soil, the removal rate constants were 0.1 and 0.06/day for the planted and control columns, respectively. Therefore, the macrophyte plants had an important impact on the removal of nitrogen in the upper zones of the columns (49% reduction) when compared to the control columns (29% reduction). The impact of macrophyte roots on the nitrification process is evident from the drastic increase (98% for planted columns) in the NO2 –N concentration between the 27 and 7 cm depth sampling points (Fig. 9). The mean NO2 –N concentration (0.5 mg-N/L) in the planted columns was significantly greater (p = 0.0001) than in the control columns (0.01 mg-N/L). The NO3 –N was below the detection limit (of 0.002 mg-N/L) for both treatments throughout the study.

4.

Fig. 9 – (a) Redox potential, (b) TAN, and (c) NO2 − –N in the planted vs. control columns. Each data point represents the mean concentration at its respective depth.

Table 12). The pH of the treatments decreased with an increase in depth, and no significant differences between the planted and unplanted columns were observed (p = 0.87). The temperatures of the planted and unplanted columns were rather constant with depth, with a statistical difference observed only at the surface (p = 0.09), which can be attributed to shading provided by the plants. The redox potential at the 7 cm depth (rhizosphere) of the planted column was significantly greater (p = 0.0001) than the redox potential of the unplanted column at the same depth (Fig. 9), indicating the potential influence of the root structure of the J. roemerianus.

Discussion

Overall, the MUS responded extremely well to the high loads imparted on the system. The nitrogen concentrations were four to six times higher than seen in municipal wastewater. This increased strength can be attributed to the fact that most of the wastewater generated is black water. Many coastal dwellings collect rainwater for general camp usage, thus, water is used sparingly. The strength of the wastewater at the Moss Point field site is similar that that observed for other MUS systems (Evans, 2005; Watson and Rusch, 2002). TKN and TAN removal in the MUS was proportional with the vector distance, similar to removal in vertical flow wetlands (Von Felde and Kunst, 1997). While the effluent concentrations of 2.4 and 1.5 mg-N/L for TKN and TAN, respectively, were slightly higher than the 1.0 mg-N/L effluent recorded for vertical flow wetlands (Cooper et al., 1997; Luederitz et al., 2001; Von Felde and Kunst, 1997), the MUS influent concentrations were an order of magnitude higher. Additionally, the MUS effluent values are taken at the 1.5 m monitoring well depth. Thus, additional treatment capability is available prior to the water reaching the surface of the marsh. Both the TKN and TAN removal efficiencies are favorably comparable to the vertical flow wetland studied by Von Felde and Kunst (1997). While the calculation of removal efficiency provides valuable insight into overall system function, the estimation of removal rate constants provides much needed design and operational criteria for global system implementation. Removal rate constants were calculated using a first-order decay analysis. It is understood by the researchers that a first-order decay analysis may present a simplistic view of the actual removal/retention taking place within the subsurface soil matrix. However, the first-order analysis has proved adequate with the data collected to date. As expected, the TKN removal constants are slightly higher than those for

34

e c o l o g i c a l e n g i n e e r i n g 2 7 ( 2 0 0 6 ) 22–36

TAN. The majority of this difference can be explained by the higher amount of particulate matter associated with TKN. It is hypothesized that within the first one to 2 m of travel, the majority of the particulate matter is removed from the wastewater via filtration. Thus, TKN would exhibit a quicker reduction in concentration than TAN, which was present in the influent in mostly the soluble form. All of the removal rate constants were significant (p < 0.0001 for the 2.8 L/min studies), however, those calculated for the 1.9 L/min study exhibited the most variability (p < 0.0059). It can be seen from Figs. 7 and 8 that the majority of the variability in the 1.9 L/min study centered on the wells located 1.7 m (vector distance) from the point of injection. It is hypothesized that during the first study, the soil matrix had not developed a biofilm to aid in the removal/retention process. In contrast, both of the 2.8 L/min studies yielded estimated influent concentrations and removal rate constants that were virtually the same, suggesting that the 0.84–0.85 and 0.88–0.89/m, for TAN and TKN, respectively, represent steady state system operation. Both 2.8 L/min studies yielded the virtually same results. However, the 2.8 L/min (30 min/3 h) study had greater loading rates (Table 11), resulting in a TAN removal efficiency of 99% versus 98% for the 2.8 L/min (30 min/3 h) study. From a design perspective, the 2.8 L/min (15 min/h) flow regime provides for 33% more hydraulic loading capacity. Subsequently, given the similarities on system response, the 2.8 L/min (15 min/h) flow regime would be recommended for future MUS implementation. The actual surface (1.5 m monitoring wells) for TKN and TAN were substantially lower than that predicted by the firstorder regression analysis, demonstrating the conservativeness of the estimates. The predicted surface concentrations were based on the assumption the wastewater travels straight up. However, as the salinity gradient decreases, the wastewater begins to travel more laterally, increasing the distance required to reach the surface, and thus the treatment capacity. Richardson et al. (2004) demonstrated that background salinity had a significant impact on pore water velocity in the area surrounding the point of injection, with diminishing effects as the wastewater moved upwards, allowing for more lateral dispersion. While these estimates are overly conservative, they provide guidance for determining injection well depth for future MUS installations. The data indicate that the current 3.8 m injection depth is adequate for systems with loam to sandy loamy soils and high natural background salinities and treating nitrogen. It must be kept in mind that the selection of injection well depth will be dependent on the required travel distance of the critical parameter of interest. Different parameters within the same wastewater may require differing injection well depths. Thus, the design will be based on the parameter requiring the deepest subsurface injection. Once injected, the retention/removal of the nitrogen is mainly through filtration of the particulate fraction (delayed load) of the soluble (instantaneous load) component. Within the first meter of travel, the majority of removal is due to filtration of the particulate matter, which decays and mineralizes over time releasing additional ammonium to the pore water. Thus, efforts should be made to retain as many solids in the collection/distribution tank as possible where the load can either be removed periodically or better regulated. The largest

sink of the ammonium, however, is through adsorption to the native soils. Quantifying ammonium adsorption capacities of wetland soils can provide insight into the nitrogen removal capabilities of MUS. However, any quantification of sorptive properties must be considered in light of other factors, including the total cation concentrations within the soil, the ionic strength of the wastewater and the groundwater, as well as the cation exchange capacity of the soil. Turriciano (2005) investigated the impact of salinity on the ammonium adsorptive capacities of the Moss Point soil. The maximum adsorption capacity decreased with increasing pore water salinity. This provides an indication that as the wastewater plume becomes established and the pore water salinity drops, the amount of ammonium that can be adsorbed by a unit mass of wetland soil increases substantially. Therefore, the longer the system operates, the more effective it becomes in retaining ammonium. Turriciano’s studies did not investigate desorption, thus, the data must be considered as a rough estimate of the adsorption capacity. The time to saturation will vary with varying soil bulk density, the nitrogen-loading rate, and the number of times the ion exchange sites have adsorbed/released ammonium (Demir et al., 2002). For example, a MUS soil volume and bulk density of 100 m3 and 1.59 g/cm3 , respectively, and a nitrogen-loading rate of 22 g-N/day results in saturation times of 5.5-greater than 8 years for pore water salinities of 0–10 ppt. Following saturation, a portion of the ammonium will be released back to the pore water and be transported further from the point of injection until it is readsorbed. A small fraction of the nitrogen is will be temporarily removed via uptake by heterotrophic microorganisms stabilizing the injected organic matter. However, since this only a temporary storage, it is not considered a removal mechanism. Although nitrification is unlikely to occur in the deeper soils of the MUS (Eh = −144, −75, −60 for 3.0, 2.3, and 1.5 m depths, respectively), it still may be responsible for some of the ammonium removal in the upper region of the subsurface (Eh = 1–46 mV between 2.3 and 1.5 m depth) if the wastewater plume moves into this region. While it was not possible to determine whether nitrification took place in the upper zone of the subsurface environment of the MUS due to the potential for surface contamination, the laboratory studies did provide valuable insight, which can be extrapolated to the field site. While a large portion of the ammonium was probably removed through adsorption for both laboratory treatments, the sharp increase in redox and nitrite within the upper 7 cm of the column strongly suggests that nitrification was taking place. The impact of wetland macrophytes such as J. roemerianus on oxygen concentration and redox conditions in the upper soil matrix has been previously documented in literature, with estimations of oxygen release between 0.5 and 5.2 g/m2 /day (Brix, 1997). At dissolved oxygen levels of 0.5 mg/L (similar with those observed in the MUS), the growth rate of ammonium oxidizers become elevated, whereas the NO2 − oxidizers are unaffected (Hanaki et al., 1990). While low dissolved oxygen levels inhibit the oxidation rate per unit biomass of ammonium oxidizers, it is compensated for by the increased growth rate (Hanaki et al., 1990). The results from the laboratory study illustrate the potential for continued treatment

ecological engineering

of nitrogen as the wastewater moves upward, past the 1.5 m monitoring wells.

5.

Conclusions

The effective removal/retention of nitrogen from domestic wastewater by the MUS has been demonstrated through field studies conducted in Moss Point, MS. No indications of hydraulic failure or system clogging were observed during the entire study period. The overall removal efficiencies for TKN and TAN were 98 and 98.6%, respectively, resulting in effluent (taken as the 1.5 m deep monitoring well) concentrations of <2.3 mg-N/L for both parameters. The injection regime of 2.8 L/min (30 min/3 h) yielded the most effective treatment and resulted in estimated removal rate constants of 0.88/m (TKN) and 0.84 m−1 (TAN). These constants can be used to aid in the design of future MUS systems designed for nitrogen removal. The removal of other parameters of interest, such as bacteria/viruses, organic matter, and phosphorus, must be considered before determining an appropriate overall injection depth. Laboratory studies demonstrated that the rhizosphere of the MUS can support nitrification, thereby providing additional treatment capacity.

Acknowledgements The authors would like to acknowledge The Cooperative Institute for Coastal and Estuarine and Environmental Technology (CICEET) for funding this research. Additionally, the authors would like to thank Sarah Jones, Rob Watson, and Stephen Richardson for their help, support, and guidance. Finally, thanks to Aubrey Lipham and Carl Anderson for their endless analytical help on this project.

references

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