Diurnal cycles of variation of physical–chemical parameters in waste stabilization ponds

Ecological Engineering 18 (2002) 287– 291

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Diurnal cycles of variation of physical–chemical parameters in waste stabilization ponds S. Kayombo a,*, T.S.A. Mbwette a, A.W. Mayo a, J.H.Y. Katima a, S.E. Jørgensen b b

a Faculty of Engineering,, Uni6ersity of Dar es Salaam, P.O. Box 35131 Dar es Salaam, Tanzania The Royal Danish School of Pharmacy, Department of General Chemistry, En6ironmental Section, Uni6ersitetsparken 2, DK-2100 Copenhagen, Denmark

Received 1 April 1999; received in revised form 2 May 2000; accepted 5 June 2001

Abstract Diurnal fluctuations of pH, dissolved oxygen (DO), water, air temperature and sunlight intensity were investigated in the waste stabilization ponds at the University of Dar es Salaam. The variation of these parameters followed the diurnal pattern of light intensity. The rate of oxygen production based on first order linear regression analysis was between 0.02 and 0.36 mg/l per h with high production rate being observed in secondary facultative ponds. The rate of utilization of dissolved oxygen (total respiration) during the night by the microbial population in the pond ranged between 0.016 and 0.435 mg/l per h. The average rate of increase of pH during the day was 0.0006– 0.243 units of pH per h, and the rate of decrease was 0.0003–0.101 units of pH per h. The ponds receiving low organic loading showed high diurnal variation of physical–chemical parameters. The relationship between average hourly DO and pH followed a polynomial trend with the coefficient of regression (R 2) ranging from 0.76 to 0.82. It may be concluded that the diurnal variation of the parameters in the WSPs is due to hourly and daily variation of light intensity. © 2002 Elsevier Science B.V. All rights reserved. Keywords: Algal biomass; Diurnal cycle; Oxygen production and utilization rate; Primary facultative pond; Secondary facultative pond; Maturation ponds

1. Introduction The treatment occurring in waste stabilization pond (WSP) results from the complex symbiosis of bacteria and algae species which results in an * Corresponding author. Fax: + 255-51-410-0029/514. E-mail address: [email protected] (S. Kayombo).

ecological pattern different from that of these organisms grown in pure culture. Periodic change of pH, temperature, and light intensity controls the abundance and activity of specific groups of micro-organisms in the multi-species microbial communities characteristic of facultative ponds (Wilderer et al., 1991; Murakani et al., 1992; Humenik and Hanna, 1971; Varma and Nepal,

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1972). The retention time and sewage strength (including characteristics) also have influence upon symbiotic activities for bacteria and algae in the pond. Utilization of natural light as an energy source implies a system that is subject to environmental changes and well defined operating zone created by the light– dark cycle (Guterman et al., 1990). The diurnal pH change in the ponds is usually followed by net algal uptake of CO2 during the daylight via photosynthesis and the increase of CO2 during the night due to total bacteria and algae respiration. Increase of pH up to 11 is not uncommon in WSPs, with the highest pH levels commonly being reached during the late afternoon. The objective of the work reported in this paper was to use the data collected from the field ponds to determine the manner in which the physical– chemical parameters influence each other and hence to compute the rates of DO production and utilization, which are useful for operation of WSP.

2. Materials and methods The data determined from the University of Dar es Salaam pond system was used to establish the pattern of diurnal variation of physical– chemical parameters. The pond system comprises a primary facultative pond (PFP), two secondary facultative ponds (SFP1 and SFP11) working in parallel and the two series of maturation ponds (MP1, MP11, MP2, and MP22) working in parallel with another set (Fig. 1). The mean monthly temperature varies between 23 and 28 °C. The ponds are used to treat domestic wastewater from the University of Dar es Salaam main campus, which has a population of 5000. The depth of PFP was 1.92, 1.7 m for SFPs, 1.6 m for MPs.

2.1. Determination of physical–chemical parameters A datalogger model R10 (Campbell Scientific Inc., Logan, UT) provided with a probes for pH, water temperature, depth of flow and dissolved

Fig. 1. The layout of the waste stabilization ponds at the University of Dar es Salaam. PFP is primary facultative pond, SFP is secondary facultative pond and MP is maturation pond F1 to F6 are the flow measurement points, S1 to S11 are the sampling points. The data logger was located at S3, S5, S6, S7, S8, S9, and S10.

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oxygen was used for data collection. It had accessories for measuring air temperature, sunlight intensity and rainfall intensity. After calibration the probes were set at the outlet of each pond at the depth of 30 cm from the water surface and data were recorded at an interval of 15 min for 24 h. Flow measurements were determined hourly at a frequency of three times a week at each location using a V-notches weir.

2.2. Determination of chemical and biological parameters Samples were analyzed for total chemical oxygen demand (TCOD), soluble chemical oxygen demand (SCOD) based on the Standard Method (APHA, AWWA, WEF, 1992). Free carbon dioxide was obtained by titrating a sample against 0.02 M NaOH (APHA, AWWA, WEF, 1992). The total biomass was measured as total volatile solids while the algae biomass was determined as volatile suspended solids following the Standard Method (APHA, AWWA, WEF, 1992). The heterotrophic bacteria biomass was obtained as a difference between total and algal biomass and was based on the assumption that the water column contains algae and heterotrophic bacteria only.

3. Results and discussion

3.1. Hydraulic, organic and surface loading to pond systems The average daily flow rate to the PFP for the period of 135 days of data collection was 489.69 m3/day, and the average daily outflow (MP2 and MP22) was 462.76 m3/day as shown in Table 1. The overall average calculated evaporation rate was 1.53 mm/day. The daily average composition of sewage and effluent along the pond system is shown in Table 1. The surface loading to PFP was 694 kg COD/ha day (467 kg BOD5/ha day). The surface loading as well as the organic loading was found to decrease along the pond series as in Table 1. The rate of COD removal was 66% for PFP, 68% for SFP1, 71% for MP1 to MP2. The

Fig. 2. Average daily hourly variation of pH, DO, and water temperature in SFP1.

overall performance of the pond system based on the final effluent quality was 71%. Minimum performance of PFP was attributed to high organic and surface loading applied to the pond. The average COD due to algal biomass based on unfiltered and filtered COD was ranging between 0.42 and 0.58 mg COD/mg dry weight of algal biomass. Tschortner (1967) found that the COD due to algae was 1 mg COD/mg dry weight of algae.

3.2. A6erage daily 6ariation of physical–chemical parameters The average hourly light intensity increased exponentially during the day and was zero during the night, with equal distribution of 12 h light and dark. The daily variations of physical–chemical parameters determined from the pond systems are presented in Table 1. The average change in pH, temperature and dissolved oxygen (DpH, DT, and DDO), shown in Table 1 signifies the difference between average maximum and minimum values. The measured parameters in each pond were high during the day and minimum during the night showing the dependence on sun light intensity. Fig. 2 shows the pattern of average hourly variation of pH and DO in the PFP. Similar pattern of average hourly variation were observed from each pond. The relationship between DO and pH was found by regression analysis in order to determine how the concentration of DO may be used to predict the pH of water in the ponds. The regression coefficient (R 2) was found to range from 0.69 to 0.77 as shown in Eqs. (1)–(4).

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Pond/parameter

Raw sewage PFP system PFP effluent SFP1 system SFP1 effluent SFP11 system MP1 effluent MP1 system MP11 MP2 effluent MP2 system MP22

Depth (m)

Inflow (m3/day)

Outflow (m3/day)

1.92

489.69

434.77

1.7

249.42

249.42

1.7

245.21

245.21

TCOD Range

Average

120–973 104–416 100–280 136–448 112–384

612 9187 274966 299.05 206 953 319974 51.27 193 940

59–320 1.6 1.6

249.42 245.21

249.42 245.21

1.2 1.2

249.42 245.22

204.56 258.20

65–640

AB is algal biomass and TB is total biomass.

Organic load (kgCOD/m3 day)

Surface load (kgCOD/ha day)

pH

695.96

6.3–8.3

208.49

Water temperature (°C)

DO (mg/l)

DpH Range

Average

DT

Range

7.39 0.47

2.1

27.5–29.8

28.7 90.5

2.34

3.2–13.2

3.79 0.01

10.4

5.5–8.0

7.490.6

2.5

20.9–28.1

23.8 9 1.9

7.09

0.9–7.7

3.29 1.6

16.0

7.2–11.3

7.8 90.9

4.1

27.9–30.9

29.8 9 0.9

2.9

0.9–7.9

3.49 0.6

7.1

Range

Average

Average

DDO

177 9 67 35.57

155.81

8.4–9.8 7.6–8.9

9.090.5 8.129 0.4

1.4 1.3

20.7–29.9 24.3–25.9

24.4 9 2.5 24.8 9 0.5

9.29 1.66

0.1–9.7 3.9–30.3

5.992.9 11.398.4

9.7 26.4

30.25

155.81

6.6–9.2 6.9–11.7

8.690.7 7.7 9 1.1

2.6 4.8

21.6–28.4 24.2–27.1

23.8 9 1.6 25.9 9 0.8

6.78 2.93

0.8–11.5 3.2–9.7

6.29 0.8 6.49 1.7

10.7 6.5

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S. Kayombo et al. / Ecological Engineering 18 (2002) 287–291

Table 1 Daily average of chemical and biological parameters

S. Kayombo et al. / Ecological Engineering 18 (2002) 287–291

pH 7.0978e 0.0147(DO) pH 7.3043e

0.0169(DO)

pH 8.2974e 0.0103(DO) pH 7.7516e

0.0122(DO)

R 2 =0.69 for PFP 2

(1)

R =0.70 for SFP1

(2)

R 2 =0.75 for MP1

(3)

2

R =0.77 for MP22

(4)

Eqs. (1)–(4) signify that pH may be estimated when the concentration of DO is known. The first order kinetics was used to compute the rate of increase and decrease of DO. This was done by assuming that increase of DO occurs during the day. Other statistical regression analysis for day and night changes yielded low regression coefficients. The average rate of DO production based on linear regression analysis was 0.002, 0.356, 0.317, 0.102, 0.299 and 0.134 mg/l h, for PFP, SFP1, SFP11, MP1, MP2 and MP22 respectively. The rate of DO utilization in the series of the ponds was 0.016, 0.435, 0.190, 0.270 and 0.216 mg/l h. The rate of increase and decrease of pH in the ponds followed the same pattern as that of DO (Fig. 2). The rate of increase of the pH during the day based on linear regression analysis was 0.006, 0.204, 0.243, 0.185, 0.186, and 0.262 pH units/h, for the PFP, SFP1, SFP11, MP1, MP2 and MP22 respectively. However, the rate of decrease of pH at late evening to early morning was 0.0003, 0.035, 0.059, 0.086, 0.075 and 0.037 pH units/h. There was a direct relationship between DO increase and pH during the day in which DO production in the ponds was followed by increase in pH probably due to increase in hydroxyl ions. The variation of DO and dissolved carbon dioxide indicated an alternating process, that during the day the DO concentration was high and the reverse occurs at night.

4. Conclusions The hourly variation of pH, temperature and DO appear to follow the pattern of the diurnal cyclic nature of sunlight intensity on the processes in the pond. The pH levels in the pond system may be used as performance indicator in the following manner: (1) pH above 8 is produced by

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photosynthetic rate that demands more CO2 than quantities replaced by respiration and decomposition; (2) pH level below 8 indicates failure of photosynthesis to utilize completely CO2 produced, and thus indicates presence of high concentration of CO2, At pH above 8 ammonia concentration becomes high and thus affecting the photosynthesis activity as is toxic to algae (Mara et al., 1992). The pond which received high organic loading has relatively low diurnal variations as was observed in primary facultative pond. Carbon dioxide in the pond may limit algae activities when the rate of oxidation of organic matter is preceded by high uptake of carbon dioxide by algae. It appears that this phenomenon will occur when the pH in water is high (more than 8). The average daily change of these parameters constitutes an average processes disturbance in the pond system. The computed values on the rate of change in pH are useful for determining the operating pH in the pond system.

References APHA, AWWA, WEF, 1992. Standard methods for the examination of water and wastewater, 18th ed. American Public Health Association, Washington DC. Guterman, H., Vanshak, A., Ben-Yaakov, S., 1990. A macromodel for outdoor algal mass production. Biotechnol. Bioeng. 35, 809 – 819. Humenik, L.E., Hanna, G.P., 1971. Algal-bacterial symbiosis for removal and conservation of wastewater nutrients. J. Water Pollut. Control Federation 43 (4), 580 – 593. Mara, D.D., Alabaster, G.P., Pearson, H.W., Mills, S.W., 1992. Waste stabilization ponds. A design manual for Eastern Africa. Lagoon Technology International, Leeds, pp. 27 – 29. Murakani, K., Inomari, Y., Sudo, R., Kurihara, Y., 1992. Effect of temperature on prosperity and decay of genetically engineered micro-organisms in a microcosm system. Water Sci. Technol. 26 (9 – 11), 2165 – 2165. Tschortner, U.S., 1967. The Determination of Chlorophyll a in Algae and its Application in South African Oxidation Ponds, Water Research, vol. 1, pp. 785 – 793. Varma, M.M., Nepal, J.K., 1972. Kinetics of soluble substrate assimilation. J. Water Pollut. Control Federation 44 (12), 2316 – 2324. Wilderer, P.A., Rubio, M.A., Davids, L., 1991. Impact of the addition of pure cultures on the performance of mixed culture reactors. Water Res. 25 (11), 1307 – 1313.