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Particle Size Distribution to Assess the Performance of Trickling Filters
PARTICLE SIZE DISTRIBUTION TO ASSESS THE PERFORMANCE OF TRICKLING FILTERS R. Marquet1, N. Muhammad2, K. Vairavamoorthy3 and A. Wheatley2 1
Asset Management Team, Severn Trent Water, Birmingham, UK. Department of Civil Engineering, Loughborough University, Loughborough, UK. 3 UNESCO-IHE Institute of Water Education, Delft, The Netherlands. 2
Abstract: Particle size distributions by laser scatter analysis were compared with other solids settlement performance indicators from trickling filters. Field and laboratory pilot plant data indicated smaller less flocculated solids from trickling filters than activated sludge or rotating biological contractors (RBC). Analysis of utility company treatment plants indicated settlement characteristics were linked to less consistent performance from the trickling filters compared to activated sludge. Experiments with synthetic sewage also demonstrated a link between fine influent solids and performance. The research found no simple association between residual COD to BOD ratio and type of bioreactor. Neither was it possible to establish a link between flow rate and solids characteristics in the effluents but more complex analysis including ambient temperature, flow and recycle rates was suggested. Keywords: particle size distribution; wastewater characteristics; COD to BOD; settlement; suspended solids and turbidity.
INTRODUCTION
Correspondence to: Professor A. Wheatley, Department of Civil Engineering, Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK. E-mail: A.D.Wheatley@ lboro.ac.uk
DOI: 10.1205/psep.05194 0957–5820/07/ $30.00 þ 0.00 Process Safety and Environmental Protection Trans IChemE, Part B, January 2007 # 2007 Institution of Chemical Engineers
Trickling filters are the most common treatment process for small and medium sized wastewater treatment processes in the UK. Trickling filters produce less sludge and use less energy than the alternatives and are attractive for smaller and medium sized works. The effluent quality from trickling filters however lacks sufficient consistency to meet the current standards and flies and smells have also reduced their popularity. Settlement of solids that are periodically washed out of the filter (Zahid and Ganczarczyk, 1990) have always been a particular issue at small works where tanks are subjected to greater diurnal and seasonal variations and desludging is performed less frequently. Earlier studies on humus settlement tanks at typical flow velocities of 1–2 m h21 have shown complete removal of particles greater than 100 mm (Herold and Muller, 1987; Steinmann, 1989). Schubert and Gunthert (2001), compared the particle distribution of the influent and effluent from humus tanks and found that particles greater than 100 mm in diameter, were completely removed but there was almost no change in the number of particles with diameters less than 30 mm. Particle distribution results expressed by number showed
that 98% of the particles shed from trickling filters were smaller than 100 mm and 90% had diameters less than 30 mm (Alon and Adin, 1994). Particle distribution analysis by volume on the other hand indicated about 40% of the solid mass was in particles less than 100 mm. In practice humus tanks typically remove more than 70% of suspended solids indicating 10% improvement by flocculation compared to theory. The particles in the effluent from trickling filters could include influent solids, partially degraded or changed influent solids and debris from endogenous grazing activity. Typically and at the lower filtration rates, the majority of large solids in trickling filter effluents are most likely to be degrading biofilms and humus solids (CIWEM, 2000). It is also understood that the periodic sloughing of biofilm by grazing activity and increases in temperature are a source of transient load on settling tanks. It has also been suggested that older biomass such as humus in trickling filters and residual solids contribute to the recalcitrant or hard COD in biologically treated effluents (e.g., Boero et al., 1991). Therefore more information on the nature and size of the humus solids could contribute to improving the performance of trickling filters and the design of tertiary treatment which will be needed where nutrient removal is required.
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Table 1. Operating conditions of the example treatment plants in ML21day. Dry weather flow Trickling filter plant nitrifying and tertiary treatment Activated sludge nitrification/ denitrification Rotating biological contractor
Peak flow to full treatment
6
17
21
60.5
Not measured estimated 500 population
Table 2. Pilot-scale trickling filter specifications and operating conditions. Filter depth (m) Diameter (m) Medium Hydraulic loading (m3 m23 d21) Organic loading (g BOD m23 d21) Recirculation (%)
1.8 0.9 50 mm blast furnace slag 0.5 82 + 24 0
METHODS To corroborate the advantages of activated sludge for the retention of particulates and in achieving the COD standard set in the Urban Waste Water Treatment Directive, all the sewage works of one of the UK’s major water utilities were surveyed. The utility has 540 trickling filter plants and 225 activated sludge plants. Not all the works were sampled regularly and to obtain more confidence in the results only those works with more than 50 data sets over at least 12 months (to account for the seasonality) were incorporated in the analysis (10 works). Three specific works were selected with no significant industrial load as examples of the most common types of bioreactor for more detailed study (Table 1). Composite daily samples were analysed for suspended solids, turbidity, particle size distribution, COD, BOD and TOC (APHA et al., 1998). Particle size distribution (PSD) was carried out using a Malvern Mastersizerw. Laboratory based pilot scale studies with a trickling filter and a controllable synthetic sewage, were carried out to investigate the influence of soluble and insoluble BOD on performance and the generation of solids and hard COD. The pilot trickling filter was made from a 2.5 m tall glass-fibre cylinder; the main characteristics of its design and operation are given in Table 2. These characteristics correspond to those of a standard UK single pass low-rate trickling filter (CIWEM, 2000). Details of the composition of the synthetic sewage which was pulse fed by timer 5 s in 65 s (equivalent to 1 rpm) to simulate the rotating distributor are given in Table 3. More details of the methodology and results are also given in Marquet (1999).
Figure 1. Final effluent COD to BOD (a) percolating filters, (b) activated sludge of all works with more than 12 months data.
RESULTS AND ANALYSIS Figure 1 shows the COD and BOD values of the surveyed works. Linear correlation was used to compare COD to BOD ratios of the influents and effluents for trickling filters and activated sludge. The data confirms that the spread of measured effluent BOD and COD values are greater for the trickling filter than the activated sludge process. The COD to BOD ratios and the minimum COD values are very similar showing that trickling filters can achieve good quality effluents without increasing the proportion of refractory COD but not with the same consistency as activated sludge (Table 4). Comparing this with the more intensive monitoring of the three bioreactor types (Tables 5 –7), indicates that the performance differences could be caused by smaller residual solids. The unsettled median (d50) particle size for the trickling filter was 82 mm compared to 143 mm for the activated sludge plant and 171 mm for the RBC. The trickling filter effluent also has the highest turbidity, a reflection of smaller particle sizes and suspended solids. The bottom row of each of these tables gives the 5% trimmed mean (using all measure data) to remove outlying data. The results for the settled samples follow the pattern but are less pronounced (Table 8). Apart from spring sloughing it was assumed that humus tanks would also be effected by hydraulic load. The results do not show a simple link between hydraulic load and particle size although there are possibilities in the case of the trickling filter that the higher flow rates flush out more solids stored or retained within the bed. This requires further research, particularly the role of sloughing and antecedent rainfall but the RBC data may be interpreted as supportive of this idea
Table 4. Summary of treatment efficiencies and COD: BOD ratios of selected works with large numbers of samples. Table 3. Synthetic waste (values mg L21).
Glucose Soluble starch Insoluble starch %sol BOD SS .1 m NTU
Stream 1
Stream 2
Stream 3
100 100 0 55 152 55
100 0 100 20 222 51
200 0 75 74 175 56
Number Mean Mean of samples Mean Median %R COD %R BOD Sewage Trickling filter plants Activated sludge Final effluent Trickling filter Activated Sludge
630 1371 372 1054
3:1 4:1
3:1 3:1
90.4 89.6
97.4 97.5
11 : 1 10 : 1 16 : 1 14 : 1
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
PARTICLE SIZE DISTRIBUTION TO ASSESS THE PERFORMANCE OF TRICKLING FILTERS Table 5. Biofilter works. Month
Flow ML week21
d10
d50
d90
NTU
SS
Nov Dec Feb March
21 44 37 42
12.93 20.11 24.34 23.88
75.02 82.59 86.75 85.61
471.98 289.94 294.35 258.46
20.27 48.03 30.20 34.40
27.67 71.33 50.50 48.25
Tri.mean
19.37 82.16 331.07 33.18 48.54
Average of two samples per month.
Table 6. A/S works. Month
Flow ML week21
Oct Nov Dec Feb March
85 92 91 82 80
Tri.mean
d10
d50
d90
NTU
SS
47.94 308.41 748.80 30.89 206.03 642.54 18.82 61.35 140.85 21.11 64.35 137.65 21.82 65.64 136.75
— — — — —
3502.25 3428.00 3444.00 3451.00 3542.00
28.16 142.46 396.03
—
3476.59
Average of two samples per month.
Table 7. RBC works. Month
Rain mm month21
d10
d50
d90
NTU
SS
Nov Dec Feb March
20 45 36 31
11.09 15.28 4.09 5.97
88.67 125.95 346.57 271.53
440.72 633.51 661.72 463.155
8.11 6.62 7.36 9.26
12.00 11.50 12.00 15.75
10.31
170.50
552.92
7.71
12.69
Tri.mean
Average of two samples per month.
where the constant rotation may generate more shear and continual flushing of smaller solids rather than a periodic discharge. The RBC generates the largest and widest range of particle sizes but also the least solids and this merits further investigation. Baggaley (2004) reported on effluent quality differences (SS and BOD) between similar RBCs but operated at different rotational speeds. There were no differences in performance; smaller particle sizes might have been anticipated at the higher speed but counteracted by better flocculating or mixing at the higher speed but the differences were too small to measure. Work has been reported on improvements to trickling filter performance by the introduction of an additional aerated flocculation stage. Parker et al. (1993)
Table 8. Summary bioreactors (settled effluent).
AS Filter RBC—humus tank samples too variable because of rising sludge
d10
d50
d90
NTU
SS
16.9 10.6
57.6 52.0
152.9 145.2
9.5 12.7
19.0 21.7
Data based on one sample per month (4 month study).
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published data on 28 US plants where improved consistency in final effluent suspended solids was achieved from either the introduction of separate flocculators and/or the introduction of baffles to humus tanks to improve flocculation. The laboratory results with synthetic sewage feed experiments (Table 9), confirm the link between particle load and trickling filter performance (Sarner and Markland, 1984). Removal efficiency of the soluble component of BOD is less varied and better than that for BODt that includes the particulate fraction of BOD. BOD removal performance was best with Stream 3 (Table 9) which had a high proportion of soluble BOD. High particulate loads have a negative impact on the performance of the trickling filters. Previous work using PSD techniques (Sarner, 1986) has already indicated that highly turbid influents with high particulate concentrations, typical of some recycled sludge liquors, are inhibitory to biological treatment (Sarner and Markland, 1984). The adsorption of organic particles within and on the biofilm surface was reported to prevent the removal of dissolved organics. This effect on performance was worse if both temperature and concentration of dissolved organics were high, indicating competition for adsorption sites. Sarner explained the inhibitory influence of adsorbed organic particles as being caused by a local oxygen shortage inside the biofilm. Bouwer (1987) modelled the kinetics of the removal of particulate BOD and demonstrated that the slow rate of particulate hydrolysis would also reduce biofilm activity. Adsorbed particles may also be inert or recalcitrant and therefore present a barrier to molecular diffusion in the boundary layer. Inert particles may also encourage detachment and sloughing by reducing activity. Both these ideas need further experimental research. The soluble waste stream generates the largest particle sizes inferring that these solids are well coagulated by bioadsorbtion. Distribution analysis by volume shows that trickling filtration causes a shift in the volume/mass distribution towards larger particle diameters (due to adsorption, flocculation and grazing fauna). Both mean and median diameters were increased as the proportion of solubles increased (Table 10). The results show complete disappearance of particles larger than 100 mm as predicted by Schubert and Gunthert (2001). The mean particle size distributions were from the field study, about 80 mm before settlement and 40 –50 mm after (Tables 5 and 8). The settled particle sizes were similar to the influents and with a synthetic feed it was possible to characterise the type of particles using size exclusion chromatography (Marquet, 1999). Preliminary indications were that pass through of un-captured feed particles and partially degraded materials were an important component of the higher solids in the effluent. The result suggests that particle load and condition of the biofilm are important influences on capture and flocculation and therefore to overall trickling filter performance. Mean hydraulic residence time distributions in standard trickling filters are about 45 min compared to 15 h in nitrifying activated sludge. Figure 2 and also Table 10 analyse the particle size distribution for the three synthetic streams. All the data show the anticipated skew pattern: the influent has a smaller wider range of particle sizes i.e., a flat peak; in the unsettled effluents there is a shift to a range of larger particle sizes; and then in the final effluent there is a shift back to smaller particle sizes (but much sharper peak of particle size). The results also suggest the value of particle volume analysis since the
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
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MARQUET et al. Table 9. Performance trickling filter %R. Stream 1typical BOD total BOD filtered COD SS
sewage
Stream 2low
86 90 73 61
solubility
75 85 58 70
Stream 3high
solubility
94 95 84 82
Table 10. PSD analysis (microns). Stream 1typical
Feed Unsettled Settled by volume Settled by number
Stream 2low
sol
Stream 3high
sol
Mean
Median
Mean
Median
Mean
Median
45.1 + 19.3 116.5 + 14.9 47.2 + 6.1 0.6
27.9 + 15.0 85.1 + 11.4 40.0 + 7.7 0.4
41.3 + 8.5 115.5 + 12.1 52.8 + 6.2 0.3
30.0 + 5.6 87.7 + 8.6 47.0 + 5.5 0.2
36.3 + 12.9 131.9 + 19.1 52.2 + 4.6 0.2
23.5 + 8.3 162 + 31.3 53.3 + 0.5 0.1
Stream 1 represents an average sewage with a 50% particulate BOD, Stream 2 a high particulate sewage and Stream 3 a highly soluble sewage.
numbers of smaller particles (Figure 3) are not representative of effluent quality which was very good (Table 9). Particle size analysis by numbers therefore needs to exclude the smallest sizes below 1 mm the pore size for suspended solids
Figure 2. (a) Average PSD by volume—Stream 1 typical sewage, (b) average PSD by volume—Stream 2 low solubility feed and (c) average PSD by volume—Stream 3 high solubility feed.
analysis. The results do however provide indications of potential to cause blockage in microfiltration membranes and potential vehicles for refractory COD. The graphs (Figures 2 and 3) show that by volume the supra-colloidal fractions (i.e., the consent boundary for SS determinants) could contribute to over 80% of the effluent solid mass and that performance would be very sensitive to
Figure 3. (a) Particulate fractionation by number—Streams 1-2-3 and (b) particulate fractionation by volume—Streams 1-2-3.
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
PARTICLE SIZE DISTRIBUTION TO ASSESS THE PERFORMANCE OF TRICKLING FILTERS removal of these particle sizes i.e., better flocculation or tertiary treatment would significantly improve the consistency of effluent quality. Similar patterns were observed from the full scale trickling filter survey data. The mean particle diameter (and median diameter and SD) of settled wastewater increased through treatment by trickling filtration, and then decreased again after secondary settlement to reach a median value of around 50 mm. It is suggested that better flocculation both primary or humus tanks would improve trickling filter performance.
. The data indicated the performance of trickling filters were sensitive to the volume of particles in the 1– 50 mm size (i.e., the consent settlement boundaries). . The performance of trickling filters was also linked to the proportion of colloidal solids in the feed indicating the importance of mixing and bio flocculation to final effluent quality. . COD: BOD ratios of the effluents from activated sludge and trickling filters were quite similar and did not reflect the smaller solids from trickling filters.
DISCUSSION The data presented supports the view that trickling filters are less consistent at removing suspended solids than activated sludge. Comparisons of particle sizes from activated sludge, RBCs and trickling filters has shown this to be due to poorer flocculation of small particles. This corroborates previous research which has shown improvements in performance of trickling filters by chemical coagulants, (Odegaard, 2000) enhanced coagulation by flocculators and baffles (Parker et al., 1993) and tertiary treatment (CIWEM, 2000). As would be anticipated there were correlations between particle size distribution, measured by volume, with suspended solids and turbidity but not by simple number because of the bias from large numbers of very small particles. The results have also confirmed theory and previous work (Schubert and Gunthert, 2001) that particles larger than 50 mm are removed easily by standard settlement tank designs. Unlike some earlier work (Odegaard, 2000) there was no simple link between hydraulic load and settlement performance. This is thought to be due to complex secondary hydraulic behaviour in trickling filters and settlement tanks. Improvements in performance of trickling filters from increased hydraulic load from recycle (CIWEM, 2000) are well known. Further work on the effects of the intermittent pulses from the distributors would be interesting. It proved impossible to get good settled samples from the very small works because of gassing and flotation. The data also supports suggestions made by Mels et al. (1999), Odegaard (2000) and others that the sustainability of sewage treatment could be improved by better flocculation of the ,50 mm particles during primary settlement. Increasing the fine solids load on the trickling filter also led to a deterioration in performance.
CONCLUSIONS . Final effluent quality from trickling filters was not as good as that from activated sludge and RBC because of higher proportion of smaller (1–50 mm) and therefore less settleable solids. . No link to hydraulic transients could be found, suggesting particle size is linked to tank design. Changes to settlement tank design to improve flocculation such as baffled diffuser drums and gentle mixing could achieve better performance from single pass filters. More extensive monitoring was recommended to include more seasonal trends.
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REFERENCES Alon, G. and Adin, A., 1994, Mathematical modelling of particle size distribution in secondary effluent filtration, Water Environ Res, 66: 836– 841. APHA (American Public Health Association), AWWA (American Water Works Association) and WEF (Waste and Environment Federation), 1998, Standard Methods for the Examination of Water and Wastewater, 20th edition (Washington, DC, USA). Baggaley, E., 2004, The impact of speed of rotation on the treatment capacity of rotating biological contractors, paper presented at CIWEM East/West Midlands Seminar, 24th February 2004. Boero, J.J., Eckenfelder, W.W.J. and Bowers, A.R., 1991, Soluble microbial product formation in biological treatment systems, Wat Science and Technology, 23(4–6): 1067– 1076. Bouwer, E.J., 1987, Theoretical investigation of particle deposition in biofilm systems, Water Res, 21(12): 1489–1498. Chartered Institute of Water and Environmental Management (CIWEM) 2000, CIWEM Handbooks of UK Wastewater Practice, Biological Filtration and Other Fixed Film Processes (CIWEM John Street, London, UK). Herold, M. and Muller, H., 1987, Floc sedimentation velocity and particle shape (German), Chem Technol, 39(5): 203–204. Marquet, R., 1999, Low rate trickling filter effluent characterisation and cross flow filtration. Doctoral thesis, Loughborough University and Institute National Polytechnique de Toulouse. Mels, A.R., Van Nieuwenhuijzen, A.F., Vander Graaf, J.H.J.M., De Koning, J., Klapwijk, A. and Rulkens, W.H., 1999, Sustainability criteria is a tool in the development of new sewage treatment methods, Wat Science Technology, 39(5): 243–250. Odegaard, H., 2000, Advanced compact wastewater treatment based on coagulation and moving bed biofilmprocesses, Wat Science Technology, 42(12). Parker, D.S., Brischke, K.V. and Matasci, R.N., 1993, Upgrading biological filter effluents using TF/SC process, J Institution Water and Environmental Management, 7(1): 90–100. Pike, E.B., 1978, The design of percolating filters and rotary biological contactors, including details of international practice, WRc Technical Report TR 93, Medmenham-Stevenage. Sarner, E. and Markland, S., 1984, Influence of particulate organics on the removal of dissolved organics in fixed-film biological reactors, Water Sci Technol, 17: 15–26. Sarner, E., 1986, Removal of particulate and dissolved organics in aerobic fixed-film biological processes, J Water Pollut Control Fed, 58(2): 165–172. Schubert, W. and Gunthert, W., 2001, Particle size distribution in effluent of trickling filters and in humus tanks, Wat Res, 35(16): 3993–3997. Steinmann, G., 1989, Sedimentation and coagulation processes in final settling tanks from trickling filters with suggestions for dimensioning (German), Reports from Water Quality and Waste Management No. 88, Technical University, Munich. Zahid, W. and Ganczarczyk, J., 1990, Suspended solids in biological filter effluents, Water Res, 24(2): 215–220. The manuscript was received 10 August 2005 and accepted for publication after revision 4 May 2006.
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
Asset Management Team, Severn Trent Water, Birmingham, UK. Department of Civil Engineering, Loughborough University, Loughborough, UK. 3 UNESCO-IHE Institute of Water Education, Delft, The Netherlands. 2
Abstract: Particle size distributions by laser scatter analysis were compared with other solids settlement performance indicators from trickling filters. Field and laboratory pilot plant data indicated smaller less flocculated solids from trickling filters than activated sludge or rotating biological contractors (RBC). Analysis of utility company treatment plants indicated settlement characteristics were linked to less consistent performance from the trickling filters compared to activated sludge. Experiments with synthetic sewage also demonstrated a link between fine influent solids and performance. The research found no simple association between residual COD to BOD ratio and type of bioreactor. Neither was it possible to establish a link between flow rate and solids characteristics in the effluents but more complex analysis including ambient temperature, flow and recycle rates was suggested. Keywords: particle size distribution; wastewater characteristics; COD to BOD; settlement; suspended solids and turbidity.
INTRODUCTION
Correspondence to: Professor A. Wheatley, Department of Civil Engineering, Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK. E-mail: A.D.Wheatley@ lboro.ac.uk
DOI: 10.1205/psep.05194 0957–5820/07/ $30.00 þ 0.00 Process Safety and Environmental Protection Trans IChemE, Part B, January 2007 # 2007 Institution of Chemical Engineers
Trickling filters are the most common treatment process for small and medium sized wastewater treatment processes in the UK. Trickling filters produce less sludge and use less energy than the alternatives and are attractive for smaller and medium sized works. The effluent quality from trickling filters however lacks sufficient consistency to meet the current standards and flies and smells have also reduced their popularity. Settlement of solids that are periodically washed out of the filter (Zahid and Ganczarczyk, 1990) have always been a particular issue at small works where tanks are subjected to greater diurnal and seasonal variations and desludging is performed less frequently. Earlier studies on humus settlement tanks at typical flow velocities of 1–2 m h21 have shown complete removal of particles greater than 100 mm (Herold and Muller, 1987; Steinmann, 1989). Schubert and Gunthert (2001), compared the particle distribution of the influent and effluent from humus tanks and found that particles greater than 100 mm in diameter, were completely removed but there was almost no change in the number of particles with diameters less than 30 mm. Particle distribution results expressed by number showed
that 98% of the particles shed from trickling filters were smaller than 100 mm and 90% had diameters less than 30 mm (Alon and Adin, 1994). Particle distribution analysis by volume on the other hand indicated about 40% of the solid mass was in particles less than 100 mm. In practice humus tanks typically remove more than 70% of suspended solids indicating 10% improvement by flocculation compared to theory. The particles in the effluent from trickling filters could include influent solids, partially degraded or changed influent solids and debris from endogenous grazing activity. Typically and at the lower filtration rates, the majority of large solids in trickling filter effluents are most likely to be degrading biofilms and humus solids (CIWEM, 2000). It is also understood that the periodic sloughing of biofilm by grazing activity and increases in temperature are a source of transient load on settling tanks. It has also been suggested that older biomass such as humus in trickling filters and residual solids contribute to the recalcitrant or hard COD in biologically treated effluents (e.g., Boero et al., 1991). Therefore more information on the nature and size of the humus solids could contribute to improving the performance of trickling filters and the design of tertiary treatment which will be needed where nutrient removal is required.
99
Vol 85 (B1) 99–103
100
MARQUET et al.
Table 1. Operating conditions of the example treatment plants in ML21day. Dry weather flow Trickling filter plant nitrifying and tertiary treatment Activated sludge nitrification/ denitrification Rotating biological contractor
Peak flow to full treatment
6
17
21
60.5
Not measured estimated 500 population
Table 2. Pilot-scale trickling filter specifications and operating conditions. Filter depth (m) Diameter (m) Medium Hydraulic loading (m3 m23 d21) Organic loading (g BOD m23 d21) Recirculation (%)
1.8 0.9 50 mm blast furnace slag 0.5 82 + 24 0
METHODS To corroborate the advantages of activated sludge for the retention of particulates and in achieving the COD standard set in the Urban Waste Water Treatment Directive, all the sewage works of one of the UK’s major water utilities were surveyed. The utility has 540 trickling filter plants and 225 activated sludge plants. Not all the works were sampled regularly and to obtain more confidence in the results only those works with more than 50 data sets over at least 12 months (to account for the seasonality) were incorporated in the analysis (10 works). Three specific works were selected with no significant industrial load as examples of the most common types of bioreactor for more detailed study (Table 1). Composite daily samples were analysed for suspended solids, turbidity, particle size distribution, COD, BOD and TOC (APHA et al., 1998). Particle size distribution (PSD) was carried out using a Malvern Mastersizerw. Laboratory based pilot scale studies with a trickling filter and a controllable synthetic sewage, were carried out to investigate the influence of soluble and insoluble BOD on performance and the generation of solids and hard COD. The pilot trickling filter was made from a 2.5 m tall glass-fibre cylinder; the main characteristics of its design and operation are given in Table 2. These characteristics correspond to those of a standard UK single pass low-rate trickling filter (CIWEM, 2000). Details of the composition of the synthetic sewage which was pulse fed by timer 5 s in 65 s (equivalent to 1 rpm) to simulate the rotating distributor are given in Table 3. More details of the methodology and results are also given in Marquet (1999).
Figure 1. Final effluent COD to BOD (a) percolating filters, (b) activated sludge of all works with more than 12 months data.
RESULTS AND ANALYSIS Figure 1 shows the COD and BOD values of the surveyed works. Linear correlation was used to compare COD to BOD ratios of the influents and effluents for trickling filters and activated sludge. The data confirms that the spread of measured effluent BOD and COD values are greater for the trickling filter than the activated sludge process. The COD to BOD ratios and the minimum COD values are very similar showing that trickling filters can achieve good quality effluents without increasing the proportion of refractory COD but not with the same consistency as activated sludge (Table 4). Comparing this with the more intensive monitoring of the three bioreactor types (Tables 5 –7), indicates that the performance differences could be caused by smaller residual solids. The unsettled median (d50) particle size for the trickling filter was 82 mm compared to 143 mm for the activated sludge plant and 171 mm for the RBC. The trickling filter effluent also has the highest turbidity, a reflection of smaller particle sizes and suspended solids. The bottom row of each of these tables gives the 5% trimmed mean (using all measure data) to remove outlying data. The results for the settled samples follow the pattern but are less pronounced (Table 8). Apart from spring sloughing it was assumed that humus tanks would also be effected by hydraulic load. The results do not show a simple link between hydraulic load and particle size although there are possibilities in the case of the trickling filter that the higher flow rates flush out more solids stored or retained within the bed. This requires further research, particularly the role of sloughing and antecedent rainfall but the RBC data may be interpreted as supportive of this idea
Table 4. Summary of treatment efficiencies and COD: BOD ratios of selected works with large numbers of samples. Table 3. Synthetic waste (values mg L21).
Glucose Soluble starch Insoluble starch %sol BOD SS .1 m NTU
Stream 1
Stream 2
Stream 3
100 100 0 55 152 55
100 0 100 20 222 51
200 0 75 74 175 56
Number Mean Mean of samples Mean Median %R COD %R BOD Sewage Trickling filter plants Activated sludge Final effluent Trickling filter Activated Sludge
630 1371 372 1054
3:1 4:1
3:1 3:1
90.4 89.6
97.4 97.5
11 : 1 10 : 1 16 : 1 14 : 1
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
PARTICLE SIZE DISTRIBUTION TO ASSESS THE PERFORMANCE OF TRICKLING FILTERS Table 5. Biofilter works. Month
Flow ML week21
d10
d50
d90
NTU
SS
Nov Dec Feb March
21 44 37 42
12.93 20.11 24.34 23.88
75.02 82.59 86.75 85.61
471.98 289.94 294.35 258.46
20.27 48.03 30.20 34.40
27.67 71.33 50.50 48.25
Tri.mean
19.37 82.16 331.07 33.18 48.54
Average of two samples per month.
Table 6. A/S works. Month
Flow ML week21
Oct Nov Dec Feb March
85 92 91 82 80
Tri.mean
d10
d50
d90
NTU
SS
47.94 308.41 748.80 30.89 206.03 642.54 18.82 61.35 140.85 21.11 64.35 137.65 21.82 65.64 136.75
— — — — —
3502.25 3428.00 3444.00 3451.00 3542.00
28.16 142.46 396.03
—
3476.59
Average of two samples per month.
Table 7. RBC works. Month
Rain mm month21
d10
d50
d90
NTU
SS
Nov Dec Feb March
20 45 36 31
11.09 15.28 4.09 5.97
88.67 125.95 346.57 271.53
440.72 633.51 661.72 463.155
8.11 6.62 7.36 9.26
12.00 11.50 12.00 15.75
10.31
170.50
552.92
7.71
12.69
Tri.mean
Average of two samples per month.
where the constant rotation may generate more shear and continual flushing of smaller solids rather than a periodic discharge. The RBC generates the largest and widest range of particle sizes but also the least solids and this merits further investigation. Baggaley (2004) reported on effluent quality differences (SS and BOD) between similar RBCs but operated at different rotational speeds. There were no differences in performance; smaller particle sizes might have been anticipated at the higher speed but counteracted by better flocculating or mixing at the higher speed but the differences were too small to measure. Work has been reported on improvements to trickling filter performance by the introduction of an additional aerated flocculation stage. Parker et al. (1993)
Table 8. Summary bioreactors (settled effluent).
AS Filter RBC—humus tank samples too variable because of rising sludge
d10
d50
d90
NTU
SS
16.9 10.6
57.6 52.0
152.9 145.2
9.5 12.7
19.0 21.7
Data based on one sample per month (4 month study).
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published data on 28 US plants where improved consistency in final effluent suspended solids was achieved from either the introduction of separate flocculators and/or the introduction of baffles to humus tanks to improve flocculation. The laboratory results with synthetic sewage feed experiments (Table 9), confirm the link between particle load and trickling filter performance (Sarner and Markland, 1984). Removal efficiency of the soluble component of BOD is less varied and better than that for BODt that includes the particulate fraction of BOD. BOD removal performance was best with Stream 3 (Table 9) which had a high proportion of soluble BOD. High particulate loads have a negative impact on the performance of the trickling filters. Previous work using PSD techniques (Sarner, 1986) has already indicated that highly turbid influents with high particulate concentrations, typical of some recycled sludge liquors, are inhibitory to biological treatment (Sarner and Markland, 1984). The adsorption of organic particles within and on the biofilm surface was reported to prevent the removal of dissolved organics. This effect on performance was worse if both temperature and concentration of dissolved organics were high, indicating competition for adsorption sites. Sarner explained the inhibitory influence of adsorbed organic particles as being caused by a local oxygen shortage inside the biofilm. Bouwer (1987) modelled the kinetics of the removal of particulate BOD and demonstrated that the slow rate of particulate hydrolysis would also reduce biofilm activity. Adsorbed particles may also be inert or recalcitrant and therefore present a barrier to molecular diffusion in the boundary layer. Inert particles may also encourage detachment and sloughing by reducing activity. Both these ideas need further experimental research. The soluble waste stream generates the largest particle sizes inferring that these solids are well coagulated by bioadsorbtion. Distribution analysis by volume shows that trickling filtration causes a shift in the volume/mass distribution towards larger particle diameters (due to adsorption, flocculation and grazing fauna). Both mean and median diameters were increased as the proportion of solubles increased (Table 10). The results show complete disappearance of particles larger than 100 mm as predicted by Schubert and Gunthert (2001). The mean particle size distributions were from the field study, about 80 mm before settlement and 40 –50 mm after (Tables 5 and 8). The settled particle sizes were similar to the influents and with a synthetic feed it was possible to characterise the type of particles using size exclusion chromatography (Marquet, 1999). Preliminary indications were that pass through of un-captured feed particles and partially degraded materials were an important component of the higher solids in the effluent. The result suggests that particle load and condition of the biofilm are important influences on capture and flocculation and therefore to overall trickling filter performance. Mean hydraulic residence time distributions in standard trickling filters are about 45 min compared to 15 h in nitrifying activated sludge. Figure 2 and also Table 10 analyse the particle size distribution for the three synthetic streams. All the data show the anticipated skew pattern: the influent has a smaller wider range of particle sizes i.e., a flat peak; in the unsettled effluents there is a shift to a range of larger particle sizes; and then in the final effluent there is a shift back to smaller particle sizes (but much sharper peak of particle size). The results also suggest the value of particle volume analysis since the
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
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MARQUET et al. Table 9. Performance trickling filter %R. Stream 1typical BOD total BOD filtered COD SS
sewage
Stream 2low
86 90 73 61
solubility
75 85 58 70
Stream 3high
solubility
94 95 84 82
Table 10. PSD analysis (microns). Stream 1typical
Feed Unsettled Settled by volume Settled by number
Stream 2low
sol
Stream 3high
sol
Mean
Median
Mean
Median
Mean
Median
45.1 + 19.3 116.5 + 14.9 47.2 + 6.1 0.6
27.9 + 15.0 85.1 + 11.4 40.0 + 7.7 0.4
41.3 + 8.5 115.5 + 12.1 52.8 + 6.2 0.3
30.0 + 5.6 87.7 + 8.6 47.0 + 5.5 0.2
36.3 + 12.9 131.9 + 19.1 52.2 + 4.6 0.2
23.5 + 8.3 162 + 31.3 53.3 + 0.5 0.1
Stream 1 represents an average sewage with a 50% particulate BOD, Stream 2 a high particulate sewage and Stream 3 a highly soluble sewage.
numbers of smaller particles (Figure 3) are not representative of effluent quality which was very good (Table 9). Particle size analysis by numbers therefore needs to exclude the smallest sizes below 1 mm the pore size for suspended solids
Figure 2. (a) Average PSD by volume—Stream 1 typical sewage, (b) average PSD by volume—Stream 2 low solubility feed and (c) average PSD by volume—Stream 3 high solubility feed.
analysis. The results do however provide indications of potential to cause blockage in microfiltration membranes and potential vehicles for refractory COD. The graphs (Figures 2 and 3) show that by volume the supra-colloidal fractions (i.e., the consent boundary for SS determinants) could contribute to over 80% of the effluent solid mass and that performance would be very sensitive to
Figure 3. (a) Particulate fractionation by number—Streams 1-2-3 and (b) particulate fractionation by volume—Streams 1-2-3.
Trans IChemE, Part B, Process Safety and Environmental Protection, 2007, 85(B1): 99– 103
PARTICLE SIZE DISTRIBUTION TO ASSESS THE PERFORMANCE OF TRICKLING FILTERS removal of these particle sizes i.e., better flocculation or tertiary treatment would significantly improve the consistency of effluent quality. Similar patterns were observed from the full scale trickling filter survey data. The mean particle diameter (and median diameter and SD) of settled wastewater increased through treatment by trickling filtration, and then decreased again after secondary settlement to reach a median value of around 50 mm. It is suggested that better flocculation both primary or humus tanks would improve trickling filter performance.
. The data indicated the performance of trickling filters were sensitive to the volume of particles in the 1– 50 mm size (i.e., the consent settlement boundaries). . The performance of trickling filters was also linked to the proportion of colloidal solids in the feed indicating the importance of mixing and bio flocculation to final effluent quality. . COD: BOD ratios of the effluents from activated sludge and trickling filters were quite similar and did not reflect the smaller solids from trickling filters.
DISCUSSION The data presented supports the view that trickling filters are less consistent at removing suspended solids than activated sludge. Comparisons of particle sizes from activated sludge, RBCs and trickling filters has shown this to be due to poorer flocculation of small particles. This corroborates previous research which has shown improvements in performance of trickling filters by chemical coagulants, (Odegaard, 2000) enhanced coagulation by flocculators and baffles (Parker et al., 1993) and tertiary treatment (CIWEM, 2000). As would be anticipated there were correlations between particle size distribution, measured by volume, with suspended solids and turbidity but not by simple number because of the bias from large numbers of very small particles. The results have also confirmed theory and previous work (Schubert and Gunthert, 2001) that particles larger than 50 mm are removed easily by standard settlement tank designs. Unlike some earlier work (Odegaard, 2000) there was no simple link between hydraulic load and settlement performance. This is thought to be due to complex secondary hydraulic behaviour in trickling filters and settlement tanks. Improvements in performance of trickling filters from increased hydraulic load from recycle (CIWEM, 2000) are well known. Further work on the effects of the intermittent pulses from the distributors would be interesting. It proved impossible to get good settled samples from the very small works because of gassing and flotation. The data also supports suggestions made by Mels et al. (1999), Odegaard (2000) and others that the sustainability of sewage treatment could be improved by better flocculation of the ,50 mm particles during primary settlement. Increasing the fine solids load on the trickling filter also led to a deterioration in performance.
CONCLUSIONS . Final effluent quality from trickling filters was not as good as that from activated sludge and RBC because of higher proportion of smaller (1–50 mm) and therefore less settleable solids. . No link to hydraulic transients could be found, suggesting particle size is linked to tank design. Changes to settlement tank design to improve flocculation such as baffled diffuser drums and gentle mixing could achieve better performance from single pass filters. More extensive monitoring was recommended to include more seasonal trends.
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REFERENCES Alon, G. and Adin, A., 1994, Mathematical modelling of particle size distribution in secondary effluent filtration, Water Environ Res, 66: 836– 841. APHA (American Public Health Association), AWWA (American Water Works Association) and WEF (Waste and Environment Federation), 1998, Standard Methods for the Examination of Water and Wastewater, 20th edition (Washington, DC, USA). Baggaley, E., 2004, The impact of speed of rotation on the treatment capacity of rotating biological contractors, paper presented at CIWEM East/West Midlands Seminar, 24th February 2004. Boero, J.J., Eckenfelder, W.W.J. and Bowers, A.R., 1991, Soluble microbial product formation in biological treatment systems, Wat Science and Technology, 23(4–6): 1067– 1076. Bouwer, E.J., 1987, Theoretical investigation of particle deposition in biofilm systems, Water Res, 21(12): 1489–1498. Chartered Institute of Water and Environmental Management (CIWEM) 2000, CIWEM Handbooks of UK Wastewater Practice, Biological Filtration and Other Fixed Film Processes (CIWEM John Street, London, UK). Herold, M. and Muller, H., 1987, Floc sedimentation velocity and particle shape (German), Chem Technol, 39(5): 203–204. Marquet, R., 1999, Low rate trickling filter effluent characterisation and cross flow filtration. Doctoral thesis, Loughborough University and Institute National Polytechnique de Toulouse. Mels, A.R., Van Nieuwenhuijzen, A.F., Vander Graaf, J.H.J.M., De Koning, J., Klapwijk, A. and Rulkens, W.H., 1999, Sustainability criteria is a tool in the development of new sewage treatment methods, Wat Science Technology, 39(5): 243–250. Odegaard, H., 2000, Advanced compact wastewater treatment based on coagulation and moving bed biofilmprocesses, Wat Science Technology, 42(12). Parker, D.S., Brischke, K.V. and Matasci, R.N., 1993, Upgrading biological filter effluents using TF/SC process, J Institution Water and Environmental Management, 7(1): 90–100. Pike, E.B., 1978, The design of percolating filters and rotary biological contactors, including details of international practice, WRc Technical Report TR 93, Medmenham-Stevenage. Sarner, E. and Markland, S., 1984, Influence of particulate organics on the removal of dissolved organics in fixed-film biological reactors, Water Sci Technol, 17: 15–26. Sarner, E., 1986, Removal of particulate and dissolved organics in aerobic fixed-film biological processes, J Water Pollut Control Fed, 58(2): 165–172. Schubert, W. and Gunthert, W., 2001, Particle size distribution in effluent of trickling filters and in humus tanks, Wat Res, 35(16): 3993–3997. Steinmann, G., 1989, Sedimentation and coagulation processes in final settling tanks from trickling filters with suggestions for dimensioning (German), Reports from Water Quality and Waste Management No. 88, Technical University, Munich. Zahid, W. and Ganczarczyk, J., 1990, Suspended solids in biological filter effluents, Water Res, 24(2): 215–220. The manuscript was received 10 August 2005 and accepted for publication after revision 4 May 2006.
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