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Secondary settling tank temperature
The formation of concentration and thermal density currents in secondary settling tanks are created by SS concentration and temperature differences (De Clercq et al., 2003). These temperature differences are as small as 0.2°C. Taebi-Harandy and Schroeder (2000) experimentally confirmed these small temperature differences, as well as related settleability changes. The MLSS inflow from the reactor, the MLSS in the settling tank, the return activated sludge (RAS), the clarified effluent from the tank, as well as the top surface effluent layer, all exhibit different temperatures that can be related to Ta (Tadesse et al., 2004). Density currents cause short-circuiting (Kim et al., 2003) as MLSS inflow moves over dead space (when warmer and lighter) or under dead space (when colder and heavier) inside a secondary settling tank.
Denitrification in a secondary settling tank is regulated by the NO3 – / NO2 – concentration and the sludge residence time (Azimi and Horan, 1991). There is furthermore a correlation between temperature and the denitrification rate, as the buoyancy of gas bubbles increases by 15% for a MLSS temperature increase of 10°C (Ekama et al., 1997). Sarioglu and Horan (1996) determined that the gas bubble size is dependent on temperature. At lower temperatures (<15°C), the small gas bubbles result in a critical nitrogen concentration (rising sludge) of 13 to 16.5 mgN/ℓ that decreases to about 8 to 13 mgN/ℓ at higher temperatures. Settled MLSS stability is therefore temperature dependent. Solar radiation (Schutte, 2006) and changing wind patterns (Van Der Walt, 1998) create diurnal temperature changes in secondary settling tanks. Kim et al. (2006) modelled the effect of these diurnal temperature fluctuations on MLSS settling flow patterns. A positive heat flux is created by daytime solar radiation once Ta is about 2°C warmer than the tank MLSS influent. This temperature increase results in density currents and cascading flow patterns. Conversely, a negative heat flux is created by nighttime and winter surface cooling once Ta is 2°C cooler than the tank MLSS influent. This temperature decrease results in buoyant flow, a surface current and significant shortcircuiting. Jokela and Immonen (2002) studied the impact of the lower winter water temperatures (3 to 12°C) on activated sludge clarification in a chemical-industry wastewater treatment plant. They observed sludge settling deterioration and ultimate sludge carry-over during variable and lower temperatures. These results confirm the general hypothesis of the direct link between MLSS settleability and temperature.
The temperature dependent MLSS settling process in a secondary settling tank is simulated by manual batch MLSS settling tests. For these tests, the temperature impact on MLSS samples in containers will vary according to procedures and equipment used.
Batch MLSS settling tests and temperature variations
Batch MLSS settling tests should preferably be carried out on-site as soon as possible after a MLSS sample is collected (Ho et al., 2006). The immediate testing of MLSS samples ensures the sample is fresh (Ekama, 1988). Wilén (1999) recommends that Ts is as close as possible to Tr during settling tests, as storage (specifically at 4°C) results in a reduction in microbial activity and a larger tendency of the MLSS to deflocculate. Neither Ts nor Ta is as a rule regulated or monitored during batch MLSS settling tests. Research reports mention occasionally that a settling test is performed at a laboratory or room temperature (Chaigon et al., 2002). Constant room temperatures are in such cases assumed, if not specified (Grijspeerdt and Verstraete, 1997; Hercules et al., 2002). Most research reports disregard the requirement to create uniform temperature conditions throughout the MLSS settling container content. Tchobanoglous et al. (2003) caution against Ts variations inside large settling columns. For this reason, Clements (1976) insulates settling columns with polystyrene to minimise changes to Ts. Simon et al. (2005) specifies a maximum 2°C difference between Ts and Ta to minimise the effects of convection on samples during MLSS settling. These references appear to be the only reports in the available literature to address the control of Ts inside settling containers. Different types and sizes of containers are used for batch MLSS settling tests. Tchobanoglous et al. (2003) describe these containers as 1 or 2 ℓ graduated cylinders or 2 ℓ settlometers (usually wider than 2 ℓ graduated cylinders), as well as larger settling columns. These columns vary in size, from 1.8 m (Bye and Dold, 1999) to 3 m (Clements, 1976) tall. The basic 30-minute batch MLSS settling test in such a container is the short term simulation of reactor MLSS settleability. The reactor MLSS settles subsequently in a downstream secondary settling tank.
1 INTRODUCTION
1.1 Background
1.2 Experimental work
1.3 Project scope
1.4 Conclusions
2 LITERATURE REVIEW
2.1 Background
2.2 Principles and monitoring of MLSS settling
2.3 Operational plant temperature conditions
2.4 Batch MLSS settling tests and temperature variations
2.5 On-line MLSS settling tests and temperature variations
2.6 Summary
2.7 Conclusions
2.8 Research aims
3 THEORETICAL FRAMEWORK
3.1 Background
3.2 Materials and methods
3.3 Results and discussion
3.4 Summary
3.5 Conclusions
4 TEMPERATURE OBSERVATIONS
4.1 Background
4.2 Materials and methods
4.3 Results and discussion
4.4 Summary
4.5 Conclusions
5 BATCH MLSS SETTLING EVALUATION
5.1 Background
5.2 Materials and methods
5.3 Results and discussion
5.4 Summary
5.5 Conclusions
6 ON-LINE MLSS SETTLING EVALUATION
6.1 Background
6.2 Materials and methods
6.3 Results and discussion
6.4 Summary
6.5 Conclusions
7 SUMMARY OF RESULTS
8 CONCLUSIONS
9 RESEARCH CONTRIBUTION
10 REFERENCES
11 APPENDICES
11.1 Appendix A: Tr measurements: surface and bubble aeration plant data
11.2 Appendix B: Raw sewage plant inflow diurnal temperature variation
11.3 Appendix C: MLSS concentration meter reading Ts-based variations
11.4 Appendix D: Batch MLSS settling data
11.5 Appendix E: On-line meter data
11.6 Appendix F: Photograph of MLSS settling meter
11.7 Appendix G: Settleability factors summary
Appendix H: Summary of regression model variable results
