The aim was to compare the impact of different design (aggregate size) and operational (contact time, empty time and chemical oxygen demand (COD) loading) variables on the long-term and seasonal performance of vertical-flow constructed wetland filters operated in tidal flow mode before and after a one-off spill of diesel. Ten different vertical-flow wetland systems were planted with Phragmites australis (Cav.) Trin. ex Steud. (common reed). Approximately 130 g of diesel fuel was poured into four wetland filters. Before the spill, compliance with secondary wastewater treatment standards was achieved by all wetlands regarding ammonia-nitrogen (NH4-N), nitrate-nitrogen (NO3-N) and suspended solids (SS), and non-compliance was recorded for biochemical oxygen demand and ortho-phosphate-phosphorus (PO4-P). Higher COD inflow concentrations had a significantly positive impact on the treatment performance for COD, PO4-P and SS. The wetland with the largest aggregate size had the lowest mean NO3-N outflow concentration. However, the results were similar regardless of aggregate size and resting time for most variables. Clear seasonal outflow concentration trends were recorded for COD, NH4-N and NO3-N. No filter clogging was observed. The removal efficiencies dropped for those filters impacted by the diesel spill. The wetlands system shows a good performance regarding total petroleum hydrocarbon (TPH) removal.

INTRODUCTION

Owing to their green nature, low or zero energy input, low-operation and maintenance costs, and sustainable credentials (Scholz 2006, 2010; Vymazal 2010; Dong et al. 2011), constructed wetlands are considered an alternative and efficient tool, and they are a reliable option used for wastewater purification. Wetlands treating industrial and domestic wastewater are sometimes subject to permanent or one-off hydrocarbon contamination, which result in changing the structure, function and ecosystem service values of wetlands (Ying et al. 2013). The inflow wastewater characteristics and the physical state of the hydrocarbon impact on the efficiency and hydraulic properties of wetlands (Imfeld et al. 2009; De Biase et al. 2011). Some diesel components are water-insoluble, entering and gradually disturbing the water quality of the wetland system (Al-Baldawi et al. 2013, 2014). These hydrocarbons are generally more toxic to plants and contain higher concentrations of light hydrocarbon components (Lin & Mendelssohn 2009).

Diesel is one of the predominant energy sources that is used in various aspects of human life to maintain economic and social development. During exploration and transportation phases, spills of these hydrocarbons have increased remarkably. Hydrocarbons mixed with wastewater pose a dangerous impact to ecosystems such as groundwater (De Biase et al. 2011). Therefore, it is important to find an effective, green and economic method to treat and control diesel contaminants such as constructed wetlands. Vertical-flow constructed wetland systems could be chosen to accomplish this purpose. However, there is a lack of information about the optimum design and operational variables of vertical-flow constructed wetlands to treat diesel.

The aim of this study is, therefore, to assess the performances of different wetland filters in treating domestic wastewater, with and without one-off spills of diesel contamination, with the following objectives: (a) to evaluate the diesel and other water quality parameter removal efficiencies of different wetland filters; (b) to assess the annual and seasonal variability in water quality parameter removal by vertical-flow constructed wetlands located in a greenhouse (before and after adding diesel); and (c) to qualitatively study the seasonal variability of other effluent variables including NH4-N, NO3-N and PO4-P.

METHODS AND MATERIALS

Constructed wetlands setup and operation

The vertical-flow constructed wetland systems are located within a greenhouse on the roof of the Newton Building of The University of Salford, Greater Manchester, UK. They were operated between 27 June 2011 and 10 June 2014. Table 1 indicates an overview of the statistical experimental setup used to test the impact of four variables (Sani et al. 2013).

Table 1

Comparison of the experimental vertical-flow wetland setup

  Design and/or operational variable
 
Wetland filters Aggregate diameter (mm) Contact time (h) Resting time (h) Chemical oxygen demand (mg/L) 
Filters 1 and 2 20 72 48 139.3 
Filters 3 and 4 10 72 48 139.3 
Filters 5 and 6 10 72 48 283.1 
Filter 7 10 36 48 139.3 
Filter 8 10 36 24 139.3 
Control A 10 72 48 2.1 
Control B 10 72 48 2.1 
  Design and/or operational variable
 
Wetland filters Aggregate diameter (mm) Contact time (h) Resting time (h) Chemical oxygen demand (mg/L) 
Filters 1 and 2 20 72 48 139.3 
Filters 3 and 4 10 72 48 139.3 
Filters 5 and 6 10 72 48 283.1 
Filter 7 10 36 48 139.3 
Filter 8 10 36 24 139.3 
Control A 10 72 48 2.1 
Control B 10 72 48 2.1 

Note: Annually treated approximate volumes of wastewater Filters 1–6, 470 L/a; Filter 7, 624 L/a; Filter 8, 858 L/a. Filters 2, 4 and 6 are replicates for the most common operational scenarios. The controls receive tap water. On 26 September 2013, 130 g of diesel was added to Filters 1, 3 and 5 and Control A.

A comparison of Filters 1 and 2 with Filters 3 and 4 allows for the assessment of the influence of different aggregate diameters. The impact of different loading rates can be studied if Filters 3 and 4 are compared to Filters 5 and 6. The contact time is different between Filters 3 and 4 compared to Filter 7. A variation of resting time is the difference between Filters 7 and 8. The setup includes two filters (Controls A and B) that are essentially controls receiving clean de-chlorinated water.

Chemical oxygen demand (COD) was used as the criterion to differentiate between low and high loads (Table 1). An inflow target COD of about 283 mg/L (usually between 122 and 620 mg/L) was set for wetlands with a high loading rate (Filters 5 and 6). The remaining Filters 1, 2, 3, 4, 7 and 8 received wastewater diluted with de-chlorinated tap water. The target inflow COD for these filters was approximately 139 mg/L (usually between 43 and 350 mg/L).

All wetland filters received 6.5 L of inflow (domestic wastewater) during the feeding mode, which was different between several filters (Table 1). To simulate a one-off diesel spill, 130 g (equivalent to an inflow concentration of 20 g/L) of diesel fuel (100% pure; no additives) were poured into Filters 1, 3 and 5, and into Control A on 26 September 2013 (Table 1). The fuel was obtained from a petrol station operated by Tesco Extra (Salford, UK).

Water quality analysis

The water quality analysis was carried out according to APHA (2005) unless otherwise stated. A DR 2800 spectrophotometer (Hach Lange, Düsseldorf, Germany) was used for analysis of COD, NH4-N, NO3-N, PO4-P and suspended solids (SS). Turbidity was measured with a Turbicheck Turbidity Meter (Lovibond Water Testing, Tintometer Group, Amesbury, UK). The pH was measured with a sensION + Benchtop Multi-Parameter Meter (Hach Lange, Düsseldorf, Germany).

The 5-day biochemical oxygen demand (BOD) was determined for all water samples with the OxiTop IS 12-6 system, a manometric measurement device supplied by the Wissenschaftlich–Technische Werkstätten (WTW; Weilheim, Germany). Nitrification was suppressed by adding 0.05 mL of 5 g/L N-allylthiourea solution (WTW chemical solution No. NTH600) per 50 mL of sample water.

Hydrocarbon analysis

Total petroleum hydrocarbons (TPHs) were determined by gas chromatography and flame ionization by Exova Health Sciences (Hillington Park, Glasgow, UK) according to their own accredited ‘TPH in Waters (with Aliphatic/Aromatic Splitting) Method’ (Exova Health Sciences 2014). To assess the natural volatilization process in the wetland filters, 500 mL of pure diesel were poured into an open round container of 10 cm diameter, and kept in the greenhouse to mimic the natural volatilization process. Another container with 500 mL diesel was kept in a laboratory fume cupboard for comparison.

Data analysis

Microsoft Excel (www.microsoft.com) was used for data analysis unless stated otherwise. The non-parametric Mann–Whitney U test was computed using Matlab (www.mathworks.co.uk). The research complied with good laboratory practice and UK standards.

RESULTS AND DISCUSSION

Water quality analysis

For the pre-hydrocarbon period, the COD removal efficiency was acceptable for all filters, and there is no significant difference in COD removal for Filters 1–6, with COD removal efficiencies of around 60–68%. The COD removal efficiency generally improved as the microorganisms responsible for biodegradation acclimatized (Scholz 2006, 2010; De Biase et al. 2011). Filters 7 and 8 showed lower performance in terms of COD removal (57% and 56%, respectively), when compared with other filters. This could be attributed to a high contact time that resulted in the provision of more time for treatment processes to remove pollutants (Prochaskaa et al. 2007). Filter 8 showed the lowest performance in COD removal, which could be attributed to the high frequency of loading (less resting time), which results in the accumulation of contaminants in the system.

For the post-hydrocarbon period, the results for COD removal efficiencies for filters with hydrocarbon (Filters 1, 3 and 5, and Control A) showed remarkable drops (23–45%) compared with those in the pre-hydrocarbon period. Diesel spills resulted in a sharp decline of the removal efficiency because diesel contributes artificially to the COD of the inflow water. Hydrocarbons such as diesel are associated with high COD values. Note that the calculated removal efficiencies do not take account of the additional COD associated with the diesel spill. Therefore, removal rates for filters subjected to diesel spills are, strictly speaking, flawed. However, this would also be the case for accidental spills that often go unnoticed in real plant operations. Drops in such filter performances are frequently considered as ‘natural fluctuations’ (data noise).

In addition, there is an increase in the nutrient removal efficiencies with time. This could indicate the maturity of a wetlands system. The results showed similar removal efficiencies for both nutrient effluents (NH4-N and PO4-P). The treatment efficiencies for Filters 5 and 6 were less than those of the other filters (particularly regarding NH4-N and PO4-P removal efficiencies). These wetland filters received concentrated wastewater (without dilution) containing high amounts of nutrients (treatment efficiency decreased with increasing nutrient loading) compared with others filters (that received fewer nutrients because the inflow wastewater was diluted with tap water). These trends were similar for both periods. However, in the post-hydrocarbon period, the filters with hydrocarbon showed a slight increase in nutrient treatment efficiencies compared with filters without hydrocarbon.

The removal efficiency of SS for both periods is relatively high, ranging from 83–97%. It has been suggested that the filter biomass improves with time (matured) and that the biodegradation rate is high (De Biase et al. 2011). However, filters with hydrocarbon contamination showed elevated SS concentrations compared to those without hydrocarbons. Depending on the stage of biodegradation over time, initially dying contaminated biomass, and later on, degraded diesel, contributed to elevated SS and turbidity values within the filters. The BOD removal efficiencies generally improved over time. Nitrate-nitrogen removal was higher for those filters treating hydrocarbons.

Table 2 shows the mean seasonal comparison of the outflow water quality for all filters. The table documents the results of investigation into the relationship between various variables and hydrocarbon removal in constructed wetlands by assessing the roles played by seasonal changes. Note that data for summer 2013 were excluded, since the data for summer 2014 were also not included. The inflow water quality data show relatively high variability with season.

Table 2

Comparison of seasonal inflow and outflow water quality parameters (value and sample number in brackets, and standard deviation) and air temperature (26 June 2012–10 June 2014) measured in mg/L

Parameter Autumn 2012a Winter 2012/2013b Spring 2013c Autumn 2013d Winter 2013/2014e Spring 2014f 
Inflow 
 Chemical oxygen demand 261.0(14) ± 96.75 230.3(11) ± 91.94 186.0(2) ± 2.83 352.5(2) ± 10.61 200.7(3) ± 73.22 245.3(8) ± 68.93 
 Biochemical oxygen demand 108.6(12) ± 12.44 118.0(16) ± 67.76 221.2(15) ± 33.50 167.1(14) ± 110.00 104.3(12) ± 72.56 105.8 (12) ± 87.23 
 Ammonia-nitrogen 65.0(14) ± 13.5 46.0(12) ± 21.99 69.4(2) ± 4.81 32.2(3) ± 28.10 41.4(5) ± 25.04 23.0(7) ± 12.35 
 Nitrate-nitrogen 6.7(14) ± 4.00 12.0(9) ± 6.51 5.2(2) ± 5.61 0.8(2) ± 0.12 5.7(5) ± 5.48 1.6(10) ± 1.27 
 Ortho-phosphate-phosphorus 18.71(9) ± 10.52 7.18(11) ± 2.43 17.81(2) ± 15.68 14.85(2) ± 4.31 16.37(4) ± 5.04 13.62(7) ± 8.40 
 Suspended solids 125.7(14) ± 77.28 158.5(17) ± 100.83 379.9(18) ± 206.44 166.6(14) ± 102.83 147.5(14) ± 138.50 122.6(16) ± 56.94 
Filter 1(outflow) 
 Chemical oxygen demand 57.1(14) ± 12.63 64.5(11) ± 7.21 82.5(2) ± 48.79 240.5(2) ± 149.20 72.0(6) ± 27.60 65.6(5) ± 4.79 
 Biochemical oxygen demand 42.7(13) ± 19.58 23.0(16) ± 17.29 54.2(16) ± 24.73 28.3(15) ± 19.85 18.3(14) ± 13.08 26.3(12) ± 19.33 
 Ammonia-nitrogen 9.4(14) ± 11.51 11.8(11) ± 7.56 25.1(2) ± 4.60 14.9(3) ± 12.27 4.5(5) ± 2.95 2.7(5) ± 5.90 
 Nitrate-nitrogen 1.2(14) ± 1.85 4.0(10) ± 3.45 0.7(2) ± 0.19 0.4(2) ± 0.13 0.5(5) ± 0.29 0.42(7) ± 0.25 
 Ortho-phosphate-phosphorus 2.46(10) ± 0.70 2.46(11) ± 0.74 5.41(2) ± 0.89 6.93(2) ± 5.48 1.92(4) ± 0.59 2.99(5) ± 0.84 
 Suspended solids 4.5(14) ± 2.42 4.2(17) ± 3.18 12.1(17) ± 11.48 12.9(14) ± 9.25 14.7(15) ± 15.23 5.8(15) ± 3.63 
Filter 2 (outflow) 
 Chemical oxygen demand 57.1(14) ± 12.63 64.5(11) ± 7.21 82.5(2) ± 48.79 86.4(2) ± 9.69 24.9(2) ± 0.57 19.8(5) ± 4.42 
 Biochemical oxygen demand 42.7(13) ± 19.58 23.0(16) ± 17.29 54.2(16) ± 24.73 18.3(15) ± 10.53 9.4(12) ± 5.09 12.7(12) ± 5.87 
 Ammonia-nitrogen 9.4(14) ± 11.51 11.8(11) ± 7.56 25.1(2) ± 4.60 12.0(3) ± 9.71 3.9(5) ± 2.00 3.2(4) ± 5.90 
 Nitrate-nitrogen 1.2(14) ± 1.85 4.0(10) ± 3.45 0.7(2) ± 0.19 3.6(2) ± 4.75 2.9(5) ± 3.23 2.8(6) ± 2.51 
 Ortho-phosphate-phosphorus 2.46(10) ± 0.70 2.46(11) ± 0.74 5.41(2) ± 0.89 4.10(2) ± 5.48 3.08(4) ± 1.46 2.44(5) ± 0.54 
 Suspended solids 4.5(14) ± 2.42 4.2(17) ± 3.18 12.1(17) ± 11.48 6.1(14) ± 7.67 9.6(15) ± 15.95 5.5(15) ± 4.24 
Filter 3 (outflow) 
 Chemical oxygen demand 51.6(14) ± 15.22 59.4(11) ± 6.32 69.2(2) ± 14.50 181.7(3) ± 133.41 83.1(5) ± 36.09 72.5(5) ± 8.25 
 Biochemical oxygen demand 35.6(13) ± 18.09 19.4(16) ± 14.84 54.4(16) ± 37.35 33.6(14) ± 26.26 22.3 (12) ± 11.28 17.9(14) ± 7.74 
 Ammonia-nitrogen 7.0(14) ± 9.66 8.2(11) ± 5.78 20.0(2) ± 5.59 9.9(3) ± 6.23 2.9(5) ± 1.97 1.73(5) ± 1.25 
 Nitrate-nitrogen 2.0(14) ± 2.55 5.1(10) ± 3.27 3.0(2) ± 2.43 0.37(2) ± 0.06 0.42(5) ± 0.38 0.42(7) ± 0.32 
 Ortho-phosphate-phosphorus 2.26(10) ± 0.71 2.23(11) ± 0.44 2.49(2) ± 0.09 6.65(2) ± 4.03 1.79(4) ± 0.84 2.25(5) ± 0.66 
 Suspended solids 4.3(14) ± 2.55 3.7(17) ± 3.03 5.9(17) ± 5.24 12.3(14) ± 9.15 16.0(15) ± 14.39 7.6(15) ± 3.81 
Filter 4 (outflow) 
 Chemical oxygen demand 51.6(14) ± 15.22 59.4(11) ± 6.32 69.2(2) ± 14.50 81.4(2) ± 13.01 81.6(2) ± 5.09 13.59(5) ± 6.41 
 Biochemical oxygen demand 35.6(13) ± 18.09 19.4(16) ± 14.84 54.4(16) ± 37.35 18.9(14) ± 12.95 8.0(11) ± 3.10 8.8(13) ± 6.81 
 Ammonia-nitrogen 7.0(14) ± 9.66 8.2(11) ± 5.78 20.0(2) ± 5.59 8.9(3) ± 7.60 3.5(5) ± 1.75 1.89(4) ± 2.06 
 Nitrate-nitrogen 2.0(14) ± 2.55 5.1(10) ± 3.27 3.0(2) ± 2.43 4.3(2) ± 5.73 3.2(5) ± 4.57 1.2(6) ± 2.28 
 Ortho-phosphate-phosphorus 2.26(10) ± 0.71 2.23(11) ± 0.44 2.49(2) ± 0.09 3.76(2) ± 1.51 3.36(4) ± 1.56 2.13(5) ± 0.31 
 Suspended solids 4.3(14) ± 2.55 3.7(17) ± 3.03 5.9(17) ± 5.24 8.1(14) ± 11.39 9.2(15) ± 16.33 5.4(15) ± 4.03 
Filter 5 (outflow) 
 Chemical oxygen demand 77.8(14) ± 19.23 80.1(11) ± 12.11 108.4(2) ± 17.89 356.0(2) ± 0.00 112.2(6) ± 19.24 65.7(5) ± 10.86 
 Biochemical oxygen demand 49.0(12) ± 27.69 26.5(15) ± 14.92 76.4(16) ± 52.09 37.9(14) ± 18.90 19.5(11) ± 7.55 14.6(14) ± 10.83 
 Ammonia-nitrogen 21.5 (14) ± 24.75 22.88(11) ± 12.95 46.20(2) ± 1.27 26.87(3) ± 29.99 8.12(5) ± 2.39 10.45(5) ± 2.30 
 Nitrate-nitrogen 5.9 (14) ± 7.25 7.1 (10) ± 4.55 6.9(2) ± 7.82 0.7 (2) ± 0.00 1.0(5) ± 0.67 1.4(7) ± 1.10 
 Ortho-phosphate-phosphorus 4.10(9) ± 1.47 3.62(11) ± 1.59 3.67(2) ± 1.46 10.65(2) ± 4.18 3.01(4) ± 1.45 2.42(5) ± 0.79 
 Suspended solids 5.2(14) ± 3.30 4.7(17) ± 3.99 9.6(17) ± 9.73 19.2(15) ± 17.13 14.8(15) ± 15.27 6.5(15) ± 4.64 
Filter 6 (outflow) 
 Chemical oxygen demand 77.8(14) ± 19.23 80.1(11) ± 12.11 108.4(2) ± 17.89 107.6(2) ± 44.48 29.5(2) ± 2.40 19.2(5) ± 12.02 
 Biochemical oxygen demand 49.0(12) ± 27.69 26.5(15) ± 14.92 76.4(16) ± 52.09 27.6(15) ± 14.15 8.7(11) ± 4.76 11.7(14) ± 11.26 
 Ammonia-nitrogen 21.5 (14) ± 24.75 22.88(11) ± 12.95 46.20(2) ± 1.27 23.0(3) ± 27.21 11.7 (5) ± 5.16 3.2(4) ± 3.53 
 Nitrate-nitrogen 5.9 (14) ± 7.25 7.1 (10) ± 4.55 6.9(2) ± 7.82 9.3(2) ± 12.20 2.2(5) ± 1.47 5.5(6) ± 3.73 
 Ortho-phosphate-phosphorus 4.10(9) ± 1.47 3.62(11) ± 1.59 3.67(2) ± 1.46 8.12(2) ± 7.62 3.07(4) ± 1.22 2.75(5) ± 0.45 
 Suspended solids 5.2(14) ± 3.30 4.7(17) ± 3.99 9.6(17) ± 9.73 10.0(15) ± 8.91 7.8(15) ± 13.36 7.1(15) ± 5.76 
Filter 7 (outflow) 
 Chemical oxygen demand 52.4(14) ± 13.55 62.6(8) ± 11.27 64.2(2) ± 5.66 82.5(2) ± 33.30 19.4(2) ± 3.11 19.9(4) ± 4.90 
 Biochemical oxygen demand 40.4(14) ± 18.13 19.4(16) ± 12.37 28.1(16) ± 20.40 18.1(17) ± 13.24 10.1(16) ± 5.95 12.7(12) ± 12.67 
 Ammonia-nitrogen 7.8(17) ± 8.28 7.0(11) ± 4.25 12.8(2) ± 6.70 7.3(3) ± 11.61 1.4(5) ± 1.74 5.1(7) ± 6.98 
 Nitrate-nitrogen 4.3(16) ± 3.50 6.3(10) ± 3.40 15.8(2) ± 2.47 2.5(2) ± 2.97 4.2(5) ± 4.03 3.1(8) ± 2.54 
 Ortho-phosphate-phosphorus 2.89(11) ± 0.69 2.71(11) ± 0.42 2.73(2) ± 0.20 5.26(2) ± 3.58 2.86(4) ± 1.21 2.05(4) ± 0.25 
 Suspended solids 6.3(15) ± 4.15 4.8(17) ± 3.60 5.6(19) ± 9.35 5.2(14) ± 5.78 1.0(19) ± 1.87 1.56(16) ± 2.31 
Filter 8 (outflow) 
 Chemical oxygen demand 60.0(15) ± 12.72 62.7(2) ± 12.06 75.0(2) ± 4.60 174.4(3) ± 162.06 18.85(2) ± 0.78 40.0(3) ± 22.67 
 Biochemical oxygen demand 39.6(11) ± 21.03 17.8(18) ± 12.27 26.9(18) ± 18.72 19.6(20) ± 9.75 9.8(17) ± 6.24 13.7(15) ± 5.23 
 Ammonia-nitrogen 9.4(17) ± 8.55 8.6(10) ± 6.90 23.1(2) ± 8.91 6.5(3) ± 9.41 1.2(5) ± 1.53 1.6(4) ± 0.68 
 Nitrate-nitrogen 4.9(15) ± 5.06 5.4(10) ± 3.88 9.0(2) ± 6.41 5.6(2) ± 7.25 3.1(5) ± 4.37 3.1(6) ± 1.96 
 Ortho-phosphate-phosphorus 3.08(11) ± 0.79 2.72(9) ± 0.53 2.83(2) ± 1.63 4.74(2) ± 3.99 3.32(4) ± 1.77 2.47(3) ± 0.61 
 Suspended solids 5.0(18) ± 2.77 4.8(22) ± 3.07 7.9(23) ± 11.37 4.5(19) ± 4.64 1.1(22) ± 1.62 3.9(17) ± 5.81 
Air temperature (inside) 11.7 9.0 17.9 14.9 10.7 19.7 
Air temperature (outside) 10.0 7.0 14.3 12.7 8.8 16.3 
Parameter Autumn 2012a Winter 2012/2013b Spring 2013c Autumn 2013d Winter 2013/2014e Spring 2014f 
Inflow 
 Chemical oxygen demand 261.0(14) ± 96.75 230.3(11) ± 91.94 186.0(2) ± 2.83 352.5(2) ± 10.61 200.7(3) ± 73.22 245.3(8) ± 68.93 
 Biochemical oxygen demand 108.6(12) ± 12.44 118.0(16) ± 67.76 221.2(15) ± 33.50 167.1(14) ± 110.00 104.3(12) ± 72.56 105.8 (12) ± 87.23 
 Ammonia-nitrogen 65.0(14) ± 13.5 46.0(12) ± 21.99 69.4(2) ± 4.81 32.2(3) ± 28.10 41.4(5) ± 25.04 23.0(7) ± 12.35 
 Nitrate-nitrogen 6.7(14) ± 4.00 12.0(9) ± 6.51 5.2(2) ± 5.61 0.8(2) ± 0.12 5.7(5) ± 5.48 1.6(10) ± 1.27 
 Ortho-phosphate-phosphorus 18.71(9) ± 10.52 7.18(11) ± 2.43 17.81(2) ± 15.68 14.85(2) ± 4.31 16.37(4) ± 5.04 13.62(7) ± 8.40 
 Suspended solids 125.7(14) ± 77.28 158.5(17) ± 100.83 379.9(18) ± 206.44 166.6(14) ± 102.83 147.5(14) ± 138.50 122.6(16) ± 56.94 
Filter 1(outflow) 
 Chemical oxygen demand 57.1(14) ± 12.63 64.5(11) ± 7.21 82.5(2) ± 48.79 240.5(2) ± 149.20 72.0(6) ± 27.60 65.6(5) ± 4.79 
 Biochemical oxygen demand 42.7(13) ± 19.58 23.0(16) ± 17.29 54.2(16) ± 24.73 28.3(15) ± 19.85 18.3(14) ± 13.08 26.3(12) ± 19.33 
 Ammonia-nitrogen 9.4(14) ± 11.51 11.8(11) ± 7.56 25.1(2) ± 4.60 14.9(3) ± 12.27 4.5(5) ± 2.95 2.7(5) ± 5.90 
 Nitrate-nitrogen 1.2(14) ± 1.85 4.0(10) ± 3.45 0.7(2) ± 0.19 0.4(2) ± 0.13 0.5(5) ± 0.29 0.42(7) ± 0.25 
 Ortho-phosphate-phosphorus 2.46(10) ± 0.70 2.46(11) ± 0.74 5.41(2) ± 0.89 6.93(2) ± 5.48 1.92(4) ± 0.59 2.99(5) ± 0.84 
 Suspended solids 4.5(14) ± 2.42 4.2(17) ± 3.18 12.1(17) ± 11.48 12.9(14) ± 9.25 14.7(15) ± 15.23 5.8(15) ± 3.63 
Filter 2 (outflow) 
 Chemical oxygen demand 57.1(14) ± 12.63 64.5(11) ± 7.21 82.5(2) ± 48.79 86.4(2) ± 9.69 24.9(2) ± 0.57 19.8(5) ± 4.42 
 Biochemical oxygen demand 42.7(13) ± 19.58 23.0(16) ± 17.29 54.2(16) ± 24.73 18.3(15) ± 10.53 9.4(12) ± 5.09 12.7(12) ± 5.87 
 Ammonia-nitrogen 9.4(14) ± 11.51 11.8(11) ± 7.56 25.1(2) ± 4.60 12.0(3) ± 9.71 3.9(5) ± 2.00 3.2(4) ± 5.90 
 Nitrate-nitrogen 1.2(14) ± 1.85 4.0(10) ± 3.45 0.7(2) ± 0.19 3.6(2) ± 4.75 2.9(5) ± 3.23 2.8(6) ± 2.51 
 Ortho-phosphate-phosphorus 2.46(10) ± 0.70 2.46(11) ± 0.74 5.41(2) ± 0.89 4.10(2) ± 5.48 3.08(4) ± 1.46 2.44(5) ± 0.54 
 Suspended solids 4.5(14) ± 2.42 4.2(17) ± 3.18 12.1(17) ± 11.48 6.1(14) ± 7.67 9.6(15) ± 15.95 5.5(15) ± 4.24 
Filter 3 (outflow) 
 Chemical oxygen demand 51.6(14) ± 15.22 59.4(11) ± 6.32 69.2(2) ± 14.50 181.7(3) ± 133.41 83.1(5) ± 36.09 72.5(5) ± 8.25 
 Biochemical oxygen demand 35.6(13) ± 18.09 19.4(16) ± 14.84 54.4(16) ± 37.35 33.6(14) ± 26.26 22.3 (12) ± 11.28 17.9(14) ± 7.74 
 Ammonia-nitrogen 7.0(14) ± 9.66 8.2(11) ± 5.78 20.0(2) ± 5.59 9.9(3) ± 6.23 2.9(5) ± 1.97 1.73(5) ± 1.25 
 Nitrate-nitrogen 2.0(14) ± 2.55 5.1(10) ± 3.27 3.0(2) ± 2.43 0.37(2) ± 0.06 0.42(5) ± 0.38 0.42(7) ± 0.32 
 Ortho-phosphate-phosphorus 2.26(10) ± 0.71 2.23(11) ± 0.44 2.49(2) ± 0.09 6.65(2) ± 4.03 1.79(4) ± 0.84 2.25(5) ± 0.66 
 Suspended solids 4.3(14) ± 2.55 3.7(17) ± 3.03 5.9(17) ± 5.24 12.3(14) ± 9.15 16.0(15) ± 14.39 7.6(15) ± 3.81 
Filter 4 (outflow) 
 Chemical oxygen demand 51.6(14) ± 15.22 59.4(11) ± 6.32 69.2(2) ± 14.50 81.4(2) ± 13.01 81.6(2) ± 5.09 13.59(5) ± 6.41 
 Biochemical oxygen demand 35.6(13) ± 18.09 19.4(16) ± 14.84 54.4(16) ± 37.35 18.9(14) ± 12.95 8.0(11) ± 3.10 8.8(13) ± 6.81 
 Ammonia-nitrogen 7.0(14) ± 9.66 8.2(11) ± 5.78 20.0(2) ± 5.59 8.9(3) ± 7.60 3.5(5) ± 1.75 1.89(4) ± 2.06 
 Nitrate-nitrogen 2.0(14) ± 2.55 5.1(10) ± 3.27 3.0(2) ± 2.43 4.3(2) ± 5.73 3.2(5) ± 4.57 1.2(6) ± 2.28 
 Ortho-phosphate-phosphorus 2.26(10) ± 0.71 2.23(11) ± 0.44 2.49(2) ± 0.09 3.76(2) ± 1.51 3.36(4) ± 1.56 2.13(5) ± 0.31 
 Suspended solids 4.3(14) ± 2.55 3.7(17) ± 3.03 5.9(17) ± 5.24 8.1(14) ± 11.39 9.2(15) ± 16.33 5.4(15) ± 4.03 
Filter 5 (outflow) 
 Chemical oxygen demand 77.8(14) ± 19.23 80.1(11) ± 12.11 108.4(2) ± 17.89 356.0(2) ± 0.00 112.2(6) ± 19.24 65.7(5) ± 10.86 
 Biochemical oxygen demand 49.0(12) ± 27.69 26.5(15) ± 14.92 76.4(16) ± 52.09 37.9(14) ± 18.90 19.5(11) ± 7.55 14.6(14) ± 10.83 
 Ammonia-nitrogen 21.5 (14) ± 24.75 22.88(11) ± 12.95 46.20(2) ± 1.27 26.87(3) ± 29.99 8.12(5) ± 2.39 10.45(5) ± 2.30 
 Nitrate-nitrogen 5.9 (14) ± 7.25 7.1 (10) ± 4.55 6.9(2) ± 7.82 0.7 (2) ± 0.00 1.0(5) ± 0.67 1.4(7) ± 1.10 
 Ortho-phosphate-phosphorus 4.10(9) ± 1.47 3.62(11) ± 1.59 3.67(2) ± 1.46 10.65(2) ± 4.18 3.01(4) ± 1.45 2.42(5) ± 0.79 
 Suspended solids 5.2(14) ± 3.30 4.7(17) ± 3.99 9.6(17) ± 9.73 19.2(15) ± 17.13 14.8(15) ± 15.27 6.5(15) ± 4.64 
Filter 6 (outflow) 
 Chemical oxygen demand 77.8(14) ± 19.23 80.1(11) ± 12.11 108.4(2) ± 17.89 107.6(2) ± 44.48 29.5(2) ± 2.40 19.2(5) ± 12.02 
 Biochemical oxygen demand 49.0(12) ± 27.69 26.5(15) ± 14.92 76.4(16) ± 52.09 27.6(15) ± 14.15 8.7(11) ± 4.76 11.7(14) ± 11.26 
 Ammonia-nitrogen 21.5 (14) ± 24.75 22.88(11) ± 12.95 46.20(2) ± 1.27 23.0(3) ± 27.21 11.7 (5) ± 5.16 3.2(4) ± 3.53 
 Nitrate-nitrogen 5.9 (14) ± 7.25 7.1 (10) ± 4.55 6.9(2) ± 7.82 9.3(2) ± 12.20 2.2(5) ± 1.47 5.5(6) ± 3.73 
 Ortho-phosphate-phosphorus 4.10(9) ± 1.47 3.62(11) ± 1.59 3.67(2) ± 1.46 8.12(2) ± 7.62 3.07(4) ± 1.22 2.75(5) ± 0.45 
 Suspended solids 5.2(14) ± 3.30 4.7(17) ± 3.99 9.6(17) ± 9.73 10.0(15) ± 8.91 7.8(15) ± 13.36 7.1(15) ± 5.76 
Filter 7 (outflow) 
 Chemical oxygen demand 52.4(14) ± 13.55 62.6(8) ± 11.27 64.2(2) ± 5.66 82.5(2) ± 33.30 19.4(2) ± 3.11 19.9(4) ± 4.90 
 Biochemical oxygen demand 40.4(14) ± 18.13 19.4(16) ± 12.37 28.1(16) ± 20.40 18.1(17) ± 13.24 10.1(16) ± 5.95 12.7(12) ± 12.67 
 Ammonia-nitrogen 7.8(17) ± 8.28 7.0(11) ± 4.25 12.8(2) ± 6.70 7.3(3) ± 11.61 1.4(5) ± 1.74 5.1(7) ± 6.98 
 Nitrate-nitrogen 4.3(16) ± 3.50 6.3(10) ± 3.40 15.8(2) ± 2.47 2.5(2) ± 2.97 4.2(5) ± 4.03 3.1(8) ± 2.54 
 Ortho-phosphate-phosphorus 2.89(11) ± 0.69 2.71(11) ± 0.42 2.73(2) ± 0.20 5.26(2) ± 3.58 2.86(4) ± 1.21 2.05(4) ± 0.25 
 Suspended solids 6.3(15) ± 4.15 4.8(17) ± 3.60 5.6(19) ± 9.35 5.2(14) ± 5.78 1.0(19) ± 1.87 1.56(16) ± 2.31 
Filter 8 (outflow) 
 Chemical oxygen demand 60.0(15) ± 12.72 62.7(2) ± 12.06 75.0(2) ± 4.60 174.4(3) ± 162.06 18.85(2) ± 0.78 40.0(3) ± 22.67 
 Biochemical oxygen demand 39.6(11) ± 21.03 17.8(18) ± 12.27 26.9(18) ± 18.72 19.6(20) ± 9.75 9.8(17) ± 6.24 13.7(15) ± 5.23 
 Ammonia-nitrogen 9.4(17) ± 8.55 8.6(10) ± 6.90 23.1(2) ± 8.91 6.5(3) ± 9.41 1.2(5) ± 1.53 1.6(4) ± 0.68 
 Nitrate-nitrogen 4.9(15) ± 5.06 5.4(10) ± 3.88 9.0(2) ± 6.41 5.6(2) ± 7.25 3.1(5) ± 4.37 3.1(6) ± 1.96 
 Ortho-phosphate-phosphorus 3.08(11) ± 0.79 2.72(9) ± 0.53 2.83(2) ± 1.63 4.74(2) ± 3.99 3.32(4) ± 1.77 2.47(3) ± 0.61 
 Suspended solids 5.0(18) ± 2.77 4.8(22) ± 3.07 7.9(23) ± 11.37 4.5(19) ± 4.64 1.1(22) ± 1.62 3.9(17) ± 5.81 
Air temperature (inside) 11.7 9.0 17.9 14.9 10.7 19.7 
Air temperature (outside) 10.0 7.0 14.3 12.7 8.8 16.3 

a22 September 2012–20 December 2012.

b21 December 2012–19 March 2013.

c20 March 2013–20 June 2013.

d22 September 2013–20 December 2013 (diesel poured on 26 September 2013).

e21 December 2013–19 March 2014.

f20 March 2014–20 June 2014 (data collection stopped on 10 June 2014).

For the whole period of the experiment, all filters (except for filters with diesel contamination) showed high removal efficiencies for the major water quality parameters COD, BOD, NH4-N and SS. This could be as a result of well-established microbial populations, vegetation and favourable operating conditions achieved over time. Furthermore, some variables, such as BOD, COD and SS, have shown seasonal variations that could be due to temperature fluctuations and the activity of microorganisms (Scholz 2010; Sani et al. 2013). Moreover, the results showed a low water quality performance during the winter. It is uncertain whether the poor winter performances were due to low temperatures alone or the combined effect of operating conditions and other variables.

Some water quality variables did not show seasonal variability, especially in winter (Table 2). This suggests that soil microbes may still have the capacity to decompose organic matter in winter, and that low temperatures enhance aerobic metabolism through the increase of dissolved oxygen saturation.

A typical standard set by environment agencies for NH4-N removal concerning secondary wastewater treatment is 20 mg/L (Royal Commission on Sewage Disposal 1915). However, NH4-N concentrations for Filters 5 and 6 (subject to a higher loading rate) were frequently above this threshold.

Table 3 presents the non-parametric Mann–Whitney U test findings. There is a significant difference in performance for all filters related to SS, while there is no difference regarding nutrients. The period after the hydrocarbon spill showed a difference in COD because the degrading hydrocarbons contributed to an increase in the strength of the wastewater.

Table 3

Overview of the statistically significant differences between p-values regarding outflow water quality variables (mg/L) of different wetland filters using the non-parametric Mann–Whitney U test

Parameter Hydrocarbon influencea Hydrocarbon influenceb Hydrocarbon influencec 
Chemical oxygen demand 0.021 0.016 0.016 
Biochemical oxygen demand 0.005 0.000 0.104 
Ammonia-nitrogen 0.806 0.712 0.689 
Nitrate-nitrogen 0.014 0.091 0.170 
Ortho-phosphate-phosphorus 0.940 0.496 1.000 
Suspended solids 0.001 0.000 0.016 
Parameter Hydrocarbon influenced Hydrocarbon influencee Hydrocarbon influencef 
Chemical oxygen demand 0.084 0.001 0.084 
Biochemical oxygen demand 0.004 0.027 0.000 
Ammonia-nitrogen 0.396 0.572 0.551 
Nitrate-nitrogen 0.320 0.003 0.004 
Ortho-phosphate-phosphorus 0.984 0.871 0.416 
Suspended solids 0.003 0.000 0.000 
Parameter Hydrocarbon influencea Hydrocarbon influenceb Hydrocarbon influencec 
Chemical oxygen demand 0.021 0.016 0.016 
Biochemical oxygen demand 0.005 0.000 0.104 
Ammonia-nitrogen 0.806 0.712 0.689 
Nitrate-nitrogen 0.014 0.091 0.170 
Ortho-phosphate-phosphorus 0.940 0.496 1.000 
Suspended solids 0.001 0.000 0.016 
Parameter Hydrocarbon influenced Hydrocarbon influencee Hydrocarbon influencef 
Chemical oxygen demand 0.084 0.001 0.084 
Biochemical oxygen demand 0.004 0.027 0.000 
Ammonia-nitrogen 0.396 0.572 0.551 
Nitrate-nitrogen 0.320 0.003 0.004 
Ortho-phosphate-phosphorus 0.984 0.871 0.416 
Suspended solids 0.003 0.000 0.000 

A P-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed. Filters are statistically significantly different only if the P-value < 0.05 for the corresponding water quality parameter.

aComparison between Filters 1 and 2.

bComparison between Filters 3 and 4.

cComparison between Filters 5 and 6.

dComparison between Filter 1 before and after hydrocarbon.

eComparison between Filter 3 before and after hydrocarbon.

fComparison between Filter 5 before and after hydrocarbon.

gNot applicable.

Figure 1(a) and 1(b) show the temporal variations for NO3-N for the filters with and without hydrocarbon contamination, respectively, for the whole experiment period. The traditional UK standard for NO3-N removal from secondary wastewater is 50 mg/L (Royal Commission on Sewage Disposal 1915). In comparison, the NO3-N values in this experiment were relatively low and variable, and no clear trends among filters were observed. Although the NO3-N concentration in the inflow was relatively low, the outflow concentrations were rather high for most filters. It follows that these filters can be considered as sources for NO3-N. The results indicate high nitrate-nitrogen values at the beginning of winter and low values in summer. Biodegradation is considered to be responsible for a high proportion of the nutrient removal in the wetland system (De Biase et al. 2011). The NO3-N values were lower for filters contaminated with hydrocarbon compared to those without hydrocarbon. The addition of carbon (via diesel) stimulated the removal of nitrogen, which is required by microorganisms to degrade hydrocarbons.

Figure 1

Temporal variations of NO3-N for the effluent of filters (a) with and (b) without diesel contamination. The diesel fuel was poured into these filters on 26 September 2013. MAL–maximum allowable limit.

Figure 1

Temporal variations of NO3-N for the effluent of filters (a) with and (b) without diesel contamination. The diesel fuel was poured into these filters on 26 September 2013. MAL–maximum allowable limit.

Degradation removal of TPH

Table 4 provides an overview of the hydrocarbon results indicating removal efficiencies for each hydrocarbon component. Background concentrations of diesel species in the raw wastewater were low. However, findings are based only on one-off samples. The results showed a good performance regarding all hydrocarbon removal efficiencies (about 6 months after the diesel spill). The seasonal reductions in COD (a crude substitute for hydrocarbon) after the diesel spill indicate rather rapid hydrocarbon degradation (Table 2). It is suggested that the high removal efficiencies in the effluents from all filters are consistent with the increased availability of oxygen in these areas and its subsequent decrease in concentration with depth.

Table 4

Overview of the hydrocarbon analysis (concentration and hydrocarbon removal efficiency in brackets) for 10 March 2014. Filters 1, 3, 5 and Control A were contaminated with diesel. The detection limit was 10 μg/L

Analyte (μg/L) Filter 1 Filter 3 Filter 5 Filter 6 Filter 7 Filter 8 Control A Inflow Diesel 
Aliphatic >EC8–10 <1* (99.5) <1* (99.5) <1* (99.5) (94.6) (94.6) 99 (46.5) <1* (99.5) 185 19,465 
Aliphatic >EC10–12 <1* (98.7) <1* (98.7) <1* (98.7) <10 (86.8) <10 (86.8) <1* (98.7) 73 (3.9) 76 1,180,882 
Aliphatic >EC12–16 28 (−75.0) 14 (12.5) <1* (93.8) <10 (37.5) <10 (37.5) <1* (93.8) 124 (−675.0) 16 273,642 
Aliphatic >EC16–35 72 (−132) 55 (−77) 14 (54.8) <10 (67.7) <10 (67.7) <1* (96.8) 70 (−125.8) 31 246,575 
Total aliphatics EC5–44 100 (67.6) 69 (77.7) 14 (95.5) <10 (96.8) <10 (96.8) 99 (68.0) 267 (13.6) 309 2,330,883 
Aromatic >EC8–10 <1* (94.7) <1* (94.7) <1* (94.7) <10 (47.4) <10 (47.4) 17 (10.5) <1* (94.7) 19 572 
Aromatic >EC10–12 <1* (98.1) <1* (98.1) <1* (98.1) <10 (81.5) <10 (81.5) <1* (98.1) 41 (24.1) 54 3,296 
Aromatic >EC12–16 <1* (99.5) <1* (99.5) <1* (99.5) <10 (95.3) <10 (95.3) <1* (99.5) 37 (82.8) 215 8,672 
Aromatic >EC16–21 <1* (99.4) <1* (99.4) <1* (99.4) <10 (93.6) <10 (93.6) <1* (99.4) <1* (99.4) 157 6,672 
Aromatic >E21–35 <1* (96.3) <1* (96.3) <1* (96.3) <10 (63.0) <10 (63.0) <1* (96.3) <1* (96.3) 27 7,866 
Total aromatics <1* (99.8) <1* (99.8) <1* (99.8) <10 (97.9) <10 (97.9) 17 (96.4) 79 (83.3) 473 456,114 
Total TPH 100 (87.2) 69 (91.2) 14 (98.2) <10 (98.7) <10 (98.7) 116 (85.2) 346 (55.8) 782 2,786,997 
Analyte (μg/L) Filter 1 Filter 3 Filter 5 Filter 6 Filter 7 Filter 8 Control A Inflow Diesel 
Aliphatic >EC8–10 <1* (99.5) <1* (99.5) <1* (99.5) (94.6) (94.6) 99 (46.5) <1* (99.5) 185 19,465 
Aliphatic >EC10–12 <1* (98.7) <1* (98.7) <1* (98.7) <10 (86.8) <10 (86.8) <1* (98.7) 73 (3.9) 76 1,180,882 
Aliphatic >EC12–16 28 (−75.0) 14 (12.5) <1* (93.8) <10 (37.5) <10 (37.5) <1* (93.8) 124 (−675.0) 16 273,642 
Aliphatic >EC16–35 72 (−132) 55 (−77) 14 (54.8) <10 (67.7) <10 (67.7) <1* (96.8) 70 (−125.8) 31 246,575 
Total aliphatics EC5–44 100 (67.6) 69 (77.7) 14 (95.5) <10 (96.8) <10 (96.8) 99 (68.0) 267 (13.6) 309 2,330,883 
Aromatic >EC8–10 <1* (94.7) <1* (94.7) <1* (94.7) <10 (47.4) <10 (47.4) 17 (10.5) <1* (94.7) 19 572 
Aromatic >EC10–12 <1* (98.1) <1* (98.1) <1* (98.1) <10 (81.5) <10 (81.5) <1* (98.1) 41 (24.1) 54 3,296 
Aromatic >EC12–16 <1* (99.5) <1* (99.5) <1* (99.5) <10 (95.3) <10 (95.3) <1* (99.5) 37 (82.8) 215 8,672 
Aromatic >EC16–21 <1* (99.4) <1* (99.4) <1* (99.4) <10 (93.6) <10 (93.6) <1* (99.4) <1* (99.4) 157 6,672 
Aromatic >E21–35 <1* (96.3) <1* (96.3) <1* (96.3) <10 (63.0) <10 (63.0) <1* (96.3) <1* (96.3) 27 7,866 
Total aromatics <1* (99.8) <1* (99.8) <1* (99.8) <10 (97.9) <10 (97.9) 17 (96.4) 79 (83.3) 473 456,114 
Total TPH 100 (87.2) 69 (91.2) 14 (98.2) <10 (98.7) <10 (98.7) 116 (85.2) 346 (55.8) 782 2,786,997 

Figures indicated by * were returned as less than the detection limit.

EC–equivalent carbon number index; TPH–total petroleum hydrocarbon.

Phragmites australis plants may also assist in enhancing the removal efficiencies in all filters due to their ability to transport oxygen from the atmosphere to the rhizosphere (Omari et al. 2003; Al Mahruki et al. 2006) and to derive organic carbon, which act as an electron donor in the removal process (Chen et al. 2012). The presence of diesel may encourage the reed to absorb the contaminants as a material required to synthesize enzymes (Wang et al. 2011). This assessment can be justified by the presence of sufficient nutrients and the regular presence of aerobic conditions (stimulating and speeding-up biodegradation and volatilization (De Biase et al. 2011)) within the filter (i.e., tidal flow mode), and also by P. australis enriching the substrate with oxygen via its root zone.

The biodegradation processes of diesel spills in Filters 1, 3 and 5 reduced the availability of nutrients to microorganisms and P. australis. However, as biodegradation of diesel progressed, it can be assumed that small amounts of remaining hydrocarbon actually promote the growth of some microorganism species, which increases the degradation rate.

The removal efficiencies of both total aliphatics and total aromatics (i.e., all hydrocarbon fractions; C8–C35) are shown in Table 4. In comparison, all wetlands without hydrocarbon contamination (Filters 2, 4 and Control B) had very high removal efficiencies for all hydrocarbon fractions (>96%, data not shown). Based on the evaporation experiments, about 30% of the diesel had evaporated after 34 days. No further evaporation was noticed on visual inspection thereafter.

The results showed a high removal efficiency for benzene, toluene, ethylbenzene and xylene-volatile aromatic compounds and methyl tertiary butyl ether (>96%). It is suggested that volatilization and phyto-volatilization are the main removal mechanisms during the first few days of diesel application (Imfeld et al. 2009). Thereafter, hydrocarbon contaminants are likely to migrate further into the cover layer, which increases the efficiency of this layer as a diffusive bioreactive barrier. De Biase et al. (2011) showed that hydrocarbons are still subject to biodegradation even after entering the gas phase. In the cover layer, the development of an equilibrium between the gas phase and the residual water phase allows the contaminants to re-enter the water phase, where they can be biodegraded by the microbial community. The total volatile petroleum hydrocarbon compounds were virtually completely removed from all filters. For TPH, the results showed very low concentration values for all filters.

After the diesel has been drawn into the filter beds during water exchange, volatilization is considerably reduced and phyto-remediation is considered to increase oil attenuation by P. australis taking in small molecular hydrocarbons. The passive aeration of the aggregates to increase biodegradation provides root exudates for microbial co-metabolization of oil components and other molecules (Lin & Mendelssohn 2009). Co-metabolism by microorganisms in the context of this study can be defined as the simultaneous degradation of two compounds, in which the degradation of the second compound (root exudates) depends on the presence of the first compound (diesel).

Control A, which lacks mature biomass, showed the highest TPH concentration value of 346 μg/L compared with those for other filters. Moreover, P. australis had a delayed and reduced growth during the post-hydrocarbon period. This can be explained by diesel toxicity to microorganisms, which formed a weak biofilm due to the absence of sufficient nutrients in the tap water. Although Filter 8 lacked diesel contamination, the TPH concentration was 116 μg/L. This can be explained by the elevated loading rate (Table 1) for this filter, resulting in the accumulation of hydrocarbon originating from the petroleum background concentration in wastewater.

CONCLUSIONS AND RECOMMENDATIONS

All wetland systems had relatively high removal efficiencies for the main water quality parameters regardless of filter setup before the diesel spill, which impeded plant development and led to poor water quality (except for NO3-N used partly for the biodegradation of diesel). The filter with the highest COD loading rate but no diesel contamination performed best in terms of COD and BOD removal. Filters contaminated by diesel performed worse in terms of COD and BOD, but considerably better regarding NO3-N removal.

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