Performance Evaluation of Modified Rapid Gravity Filter by Using Sand and Crushed Overburnt Brick Separated by Geotextile

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This study aimed to access the effectiveness of using novel filter media composed of crushed overburnt brick and sand separated by geotextile in rapid gravity filtration. The experiment was conducted with four rapid gravity filters by maintaining the constant influent and effluent discharge of 2.5 m 3 /m 2 /h. The experiment was repeated seven times with varied influent turbidites by resuming the filtration process after backwashing with the backwash velocity of 21 m 3 /m 2 /h, when terminal head loss exhausted 155 cm. Turbidity removal efficiency of RGF with novel media was observed to be improved by 2.07% as compared to conventional sand filter. Further, improvement in UFRV was by 49.89%, backwash water consumption was by 58.32%, backwash time was by 3.68%. The filter run length was reached up to about 1.5 times more than that of conventional sand filter. This study suggests that, substituting sand media with innovative media, which has a filter media thickness of 75% compared to sand media, can perform effectively. Additionally, it was observed that novel media with a filter media thickness of 50% as compared to sand media can efficiently operate when influent turbidity is below 100 NTU. Conventional Filter Crushed Overburnt Brick Filtration Modified Rapid Gravity Filter Turbidity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction Water is regarded as one of the most vital natural resources on the planet. The availability of safe drinking water reflects a community's economic, social, and cultural well-being. Global urbanization has posed new issues to the availability and delivery of drinkable water. According to ADB reports, people living in urban areas are at daily danger of different diseases, health risks, and associated economic burdens, which disproportionately affect Kathmandu Valley's poor and vulnerable population due to insufficient water availability [1]. Natural sources or a variety of human activities can contaminate groundwater gathered and stored in subterranean water reservoirs [2]. Turbidity is a substantial impurity that may be present in water, and the general population can utilize it to decide whether or not to accept the water after visualization without more thought. Water turbidity is caused primarily by the presence of suspended particles, colloidal particles, inorganic debris, plankton, and other microscopic creatures [3]. Turbid water can also serve as a breeding ground for dangerous algae and other microbes that create toxins that are detrimental to humans and animals. To handle water turbidity issues, the filtering process stands out as an efficient and cost-effective method of water treatment. Filtration is the fundamental process on removal of suspended and colloidal particles present in water that drains through a porous medium (Garcia-Avila et al., 2020). Slow Sand Filters (SSF) was primitive water treatment system developed in England in 19th century. SSF has some limitations and is not recommended for water treatment with turbidity greater than 5 NTU [4]. To overcome the frequent clogging in slow sand filtration, rapid gravity filters (RGF) with coarse sand as filter media were developed, which draws more water than that of SSF [5]. The development of filter media, that have ability to withdraw more water is critical in water treatment. Study shows that, RGF with dual filter media is capable of producing 10% more water having same quality standard of single bed with longer filtration cycles [6]. Filtration system having consequent reduction in cost along with improved filtration efficiency are under research to replace the traditional sand. In RGF's, sand and anthracite are the traditionally used filter media materials. Due to hardness, porosity and readily availability of overburnt bricks (about 13% of the produced brick from brick factory [7]), research on overburnt brick could state an alternative filter media material in filtration process. Facilitation of bed stability, longer filter run time, slow clogging and more water production in a cycle are the key characteristics of filter media materials for efficient filtration. Application of porous, heavy and tightly confined media bed can achieve such characteristics. The integration of essential qualities found in overburnt brick as porous material, sand as heavy material, and geotextile as layer separator to create dual-layered filtering media might potentially result a highly effective water treatment system. As combined media bed, crushed overburnt brick facilitates adsorption and trapping of tiny particles at upper layer, traditional sand may help to keep the flow steady during the filtration process and the use of a geotextile layer within filter media helps to prevent filter media clogging [8], bed stability and avoid in mixing of filter media materials during backwashing process as well. The growing need for efficient and sustainable water treatment systems has given rise to researchers to explore alternative materials for use in filtration processes. As COB is not a regular construction material, it is considered only a waste material from brick factory. Due to its impressive properties on filtration, utilization of COB in filtration process states a novel filter media and it will be also a proper utilization of factory waste materials. Besides, study of COB and its combination with sand by providing geotextile as layer separator for bed stability is rare. This study aimed to assessed the performance of dual layered filter media consisting of COB and sand separated by geotextile in terms of turbidity removal, head loss development, filter run length, UFRV and back wash water consumption under varied influent turbidity. Materials and Methodology Four rapid gravity filter columns made of fiber glass were used in the experiment. The filter column using sand as filter media was labelled as a Conventional Rapid Gravity Filter (CRGF), while the other three with dual-layered media were labelled as Modified Rapid Gravity Filters (MRGF). The conceptual framework of this study is presented in Fig. 2.1 . 3.1 Material Collection and Preparation of Filter Media 3.1.1 Base materials The machine crushed gravel collected from the stockpile of the IOE Pulchowk campus laboratory was manually sorted and cleaned of clay, dirt, vegetable, and organic matter. The cleaned gravel was then sieved through different sieve sizes, and then packed into separate sacks, ensuring its proper storage for later use. 3.1.2 Filter media River sand collected from Heavy lab of Pulchowk campus as well as overburnt bricks collected from brick factory and then crushed manually in same lab were sieved separately through the series of sieves and mixed to get uniformity coefficient of 1.60 and effective size (d 10 ) of 0.50 mm. Loss on ignition test was determined as 0.25% while it was 0.35% for COB, were less than 0.7 as prescribed by (IS:8419 (part I)). Acid solubility test was also conducted and percentage loss in weight for sand was determined as 1.99% and that for COB was determined as 0.89%, which were remained less than 5% [9]. During preparation, porosity and density tests were also conducted in the laboratory by using the standard method prescribed by (IS 1528 (Part 15): 2007). The tests showed that, COB was 6.4% more porous than that of sand, but the density of sand surpassed that of COB by a significant margin of 439.23 kg/m 3 . 3.1.3 Geotextile Geotextile with a nonwoven structure and a pore size of 0.2 mm was acquired from a hardware shop. It was carefully cut, trimmed, and arranged to match the internal dimensions of the filter column, ensuring a perfect fit and optimal functionality. 3.2 Model Setup Four filter columns were fashioned, each possessing internal dimensions measuring 150 mm × 150 mm. The filter columns were marked with a series of marks at every 10 cm from bottom to top. These filter columns were subsequently designated with distinct names, correlating to the specific thickness of their filter media, as depicted in Table 3.1 . Table 3.1 Designation of filter columns Code Name Description Reference CRGF Filter column with sand media having thickness of 60 cm. As per design MRGF M A Filter column with 30 cm sand and 30 cm COB. [10] M B Filter column with 22.5 cm sand and 22.5 cm COB. [10] M C Filter column with 15 cm sand and 15 cm COB. [10] The four filter columns were specifically established in the water supply department of TU, IOE. Each filter column was comprised of six ports. Three of them were placed 5 cm above the bottom of the filter columns for the purpose of outlet, piezometer connection, and backwashing operation, while the remaining three were placed at specific heights for piezometer connection, backwash water effluent, and overflow drainage whilst maintaining the bed expansion 20 cm and standing depth of water level at 110 cm above the filter media. A comprehensive summary of the ports is mentioned in the Fig. 3.1 . 3.3 Operation of Filter Model The filter columns were operated intermittently under constant discharge and variable water head conditions by using the artificially prepared turbid water by maintaining the equal influent as well as effluent discharges of 2.5 m 3 /m 2 /h and initial water level above the top of the filter media was precisely maintained at 110 cm. Samples from influent and effluent ports were collected hourly in 250 ml bottles and turgidities were measured by using Digital Turbidity Meter (Model no. 988, AE-MAX company). When terminal head loss reached up to 155 cm, the backwashing operation was initiated by using clear water stored in 1000 liter tank with a consistent discharge rate of 21 m 3 /m 2 /h and available head 5 m at inlet portal. The backwashing operation was halted once the clarity of the backwashed effluent was determined to be satisfactory. Once the backwashing operation was completed, filters were resumed by applying water with higher influent turbidity. Result and Discussion Seven filter runs were performed for influent turbidity values 0–25, 25–50, 50–100, 100–150, 150–200, 200–250, and 250–300 NTU. With comparative analysis of four filter columns, performance of Modified Rapid Gravity Filters was evaluated and compared with Conventional Rapid Gravity Filter. The results of the filter runs were discussed and presented graphically. The summary of filter runs for CRGF, M A and M B were as depicted in Table 4.1 , Table 4.2 , Table 4.3 . Table 4.1 Summary of filter runs for CRGF Run cycle Turbidity Range (NTU) Average Influent Turbidity (NTU) Average Effluent Turbidity (NTU) Run Time (Hrs.). UFRV (m 3 /m 2 ) Head loss gained Backwashing Time (Mins) % Water Consumption 1 0–25 10.34 0.76 136 389 1.50 17 1.53 2 25–50 31.73 1.90 76 212 1.40 21 3.47 3 50–100 72.13 3.55 38 109 1.39 22 7.06 4 100–150 111.88 4.96 24 63 1.38 24 13.33 5 150–200 169.29 7.07 15.5 46 1.37 27 20.54 6 200–250 220.93 8.70 14 40 1.37 30 26.25 7 250–300 277.00 9.88 10 29 1.39 28 33.79 Table 4.2 Summary of filter runs for M A Run Cycle Turbidity Range (NTU) Average Influent Turbidity (NTU) Average Effluent Turbidity (NTU) Run Time (Hrs.) UFRV (m 3 /m 2 ) Head loss gained Backwashing Time (Mins) % Water Consumption 1 0–25 10.34 0.51 175 583 1.50 16 0.96 2 25–50 31.73 1.28 108 309 1.43 19 2.15 3 50–100 72.13 2.30 54 154 1.39 19 4.32 4 100–150 111.88 2.79 36 103 1.39 23 7.82 5 150–200 169.29 3.86 26 75 1.38 25 11.67 6 200–250 220.93 4.40 20 58 1.39 32 19.31 7 250–300 277.00 5.17 17 49 1.39 29 20.71 Table 4.3 Summary of filter runs for M B Run Cycle Turbidity Range (NTU) Average Influent Turbidity (NTU) Average Effluent Turbidity (NTU) Run Time (Hrs.) UFRV (m 3 /m 2 ) Head loss gained Backwashing Time (Mins) % Water Consumption 1 0–25 10.34 0.63 154 440 1.50 15 1.19 2 25–50 31.73 1.64 90 257 1.42 17 2.32 3 50–100 72.13 3.21 44 125 1.39 18 5.04 4 100–150 111.88 4.38 30 86 1.38 21 8.55 5 150–200 169.29 6.35 19 54 1.37 24 15.56 6 200–250 220.93 6.91 15 43 1.38 26 21.16 7 250–300 277.00 8.50 12 34 1.39 28 28.82 4.1 Influent and Effluent Turbidity with Filter Run Time The influent and effluent turbidity of synthetic turbid water resulted from third, fourth and sixth filter runs are presented in Fig. 4.1: During the filter runs, all the filter models showed effluent turbidity values below 5 NTU for influent turbidity value up to 100 NTU as prescribed by (Nepal Gazette, 2022). CRGF, M A and M B showed effluent turbidity value below 5 NTU for influent turbidity up to 150 NTU. However, M A showed effluent turbidity value below 5 NTU for influent turbidity up to 250 NTU. Above 250 NTU all filters were unable to produce effluent turbidity below 5 NTU. During the seven filter run cycles, M A consistently outperformed the other models in terms of turbidity removal. This superior performance can be attributed to several factors such as, the enhanced surface area that trapped tiny particles, the extended contact time for particles within the filter media, and the improved depth filtration resulting from the increased porosity of the filter medium. 4.2 Head Loss Development During Filtration Process Throughout the seven cycles of filter run, a stringent criterion was set for the allowable terminal head loss, which was determined to be 155 cm. The minimum initial head loss was 4.7 cm for filter columns, M A , M B and M C and that for CRGF was 5.3 cm in first filter run while, maximum initial head loss was 18.2 cm for CRGF, in fifth filter run, 17.4 cm for M A , 17.8 cm for M B in fifth filter run and that for M C was 17.8 cm in fourth filter run as shown in Figure (4.2). With the escalating influent turbidity, the progression of head loss exhibited rapidity across all filter columns. Amongst the entirety of filter columns, the minimum rate of head loss growth was observed in M A , while M C displayed a higher rate of head loss. The swift development of head loss in all filter columns can be attributed to the increased influent turbidity, which is indicative of surface sealing within the filter media. The increased suspended particle load on identical cross-sectional area of filter media from initial cycle to last cycle was also a main reason on rapid head loss development. Additionally, the intermittent filter operation resulted in a consistent daily decline in head pressure. 4.3 Filter Run Time and its Correlation with Increase in Influent Turbidity The filter run length is contingent upon the unique characteristics of the raw water being treated. In Fig. 4.3 , the filter run times for various influent turbidity values were displayed for all filter columns. As the influent turbidity increases, the filter run time decreases, primarily due to the escalated presence of suspended solids. Throughout the seven cycles of filter run, with the increases in influent turbidity length of cycles were decreased. During every filter run cycle, the maximum filter run time was observed for M A , while the minimum filter run time was recorded for filter column M C . Additionally, the filter run time for M B was consistently longer than that of CRGF for each cycle of runs. The filter run time for CRGF and M C remains almost the same for all influent turbidity values. However, upon attaining an average influent turbidity level of 180 NTU, the filter run time for CRGF, M B , and M C becomes approximately equal, although M B showed a slightly higher run time. The longer duration of filtration in MRGF's, in comparison to CRGF, suggests that there is a lower density of COB particles packed within the filtering material. This leads to greater porosity in the media, an expanded surface area allowing more interaction between media grains and suspended particles, and so on. 4.4 Effect of Porosity of Filter Media in Filtration Process From the experiment, it was found that the porosity of COB was 6.4% higher than that of sand media. Experimentally, the filter run time for MRGF's was consistently higher than that of CRGF for every influent turbidity range with exceptional case of M C . Theoretical analysis revealed that the initial head loss development for CRGF was 58.5 cm, whereas for MRGF's, it was 38.5 cm. This indicates that the head loss development for CRGF was greater than that of MRGF's. Additionally, the filter run length for MRGF's was longer than that of CRGF, attributed to the higher porosity of the COB as well as extra porosity imparted by geotextile used between the layers. 4.5 Analysis of Turbidity Removal Under Varying Influent Turbidity Levels Throughout the seven cycles of filter run, M C was lower efficient and M A was most efficient. CRGF was more efficient than M C but less efficient than M B . Filter M A was relatively most efficient in the influent turbidity range of 25–50 NTU and was less efficient in the influent turbidity range of 200–250 NTU. The comparison of four filter models in the influent turbidity removal is presented in Fig. 4.4 . The comparative study shows that the MRGF was more efficient for turbidity removal even in reduction of thickness up to 75% than that of CRGF. The achievement of higher efficiency for the MRGF columns over CRGF columns was due to higher porosity of COB that enable to trap the suspended particles in top portion of the filter media and extra porosity imparted by geotextile used as layer separator. The graph showed that, turbidity removal efficiency was in increasing trend on increasing influent turbidity for all filter columns. Referring to the Fig. 4.7 , the equations of trend line and R 2 values for CRGF, M A , M B and M C were as follow: or, y = 2.3034x + 12.294 [R² = 0.9721] (4.1) or, y = 5.8495x + 14.327 [R² = 0.9891] (4.2) or, y = 2.7933x + 13.816 [R² = 0.9805] (4.3) or, y = 1.0583x + 10.246 [R² = 0.9868] (4.4) The regression coefficient (R 2 ) for M A was highest among all. It showed that, the data obtained for M A was more consistent than that from other columns. This observation implies that the filter bed remained stable in its operation, likely due to better confinement provided by the geotextile and the higher specific gravity of the sand used. 4.6 Unit Filter Run Volume (UFRV) with Increased Influent Turbidity Level With the increase in influent turbidity, Unit Filtration Run Volume (UFRV) of CRGF and MRGD's was found to be decreased throughout the cycles. The UFRV value for M A was found to be higher among all filters for all cycles. Throughout the cycles of filter run, maximum UFRV value for M A was 583 m 3 /m 2 , that for M B was 440 m 3 /m 2 , that for CRGF was 389 m 3 /m 2 and that for M C was 386 m 3 /m 2 . CRGF and M C were showed same pattern of UFRV throughout the cycles. Similarly, minimum UFRV value for M A was 49 m 3 /m 2 , that for M B was 34 m 3 /m 2 , that for CRGF was 29 m 3 /m 2 and that for M C was 26 m 3 /m 2 . The graph between UFRV and avg. influent turbidity is depicted in Fig. 4.5 . On average, the UFRV for M A was higher by 63.29 m 3 /m 2 , for M B was higher by 21.57 m 3 /m 2 and that for M C was lower by 3.14 m 3 /m 2 as compared to that of filter CRGF. The higher values of UFRV for M A and M B compared to CRGF were due to the increased surface area within the filter media due to porosity. 4.7 Backwash Time with Increased Influent Turbidity Backwashing was commenced with a backwash velocity of 21 m 3 /m 2/ hr when the terminal head loss was attained at 155 cm. Backwashing time was determined by observing the relative clarity of the backwash effluent. The backwash time for different influent turbidity levels is shown in Fig. 4.6 . Backwashing time for CRGF was more than M A , M B and M C except from sixth cycle of filter run. After sixth filter run, backwashing time for CRGF was less than that of M A , but more than that of M B and M C . Throughout the cycles, the maximum backwash time for CRGF was 30 minutes, after completion of sixth cycle and the minimum backwash time for CRGF was 17 minutes at the end of first cycle. However, the maximum backwash time for M A was 32 minutes, after completion of sixth cycle and the minimum backwash time for M A was 16 minutes at the end of first cycle. The maximum backwash time for M B was 28 minutes after completion of seventh cycle and the minimum backwash time for M B was 15 minutes at the end of first cycle. The maximum backwash time for M C was 23 minutes, after completion of sixth cycle and the minimum backwash time for M C was 12 minutes at the end of first cycle. Throughout the cycles, the shortest duration for backwashing was occurred with M C , taking an average of 19.43 minutes. This was because the depth of filter media being washed at once was smaller, resulting in a quicker process. On the other hand, the longest backwashing time was observed with CRGF, averaging 24.14 minutes. This was attributed to the larger depth of filter media to be cleaned and the presence of densely packed sand grains, which led to a more time-consuming backwashing process. 4.8 Filter Run Time with Increased Depth for MRGF's The graph showing filter run time with increased depth for MRGF's is presented in Fig. 4.7 . Throughout the cycles, the average filter run time for M A was 62.29 Hrs., that for M B was 52 Hrs. and it was 43.29 Hrs. for M C . With the increases in depth of filter media in MRGF's, the filter run time was also in increasing trend. Equation of the trend line is: or, y = 0.6333x + 24.027 Eq. (4.5) As the regression coefficient (R 2 ) value is nearly equal to one. This showed that, filter run time was consistently increasing with the increase in depth of filter media. 4.9 Removal Efficiency with Increased Depth for MRGF's The graph showing turbidity removal efficiency with increased depth of MRGF's is presented in Fig. 4.8 . Throughout the cycles, the average turbidity removal efficiency for M A was 96.99%, that for M B was 95.66% and it was 92.66% for M C . With the increases in depth of filter media in MRGF's, the filter run time was also in increasing trend. The equation of the trend line is: or, y = 0.0637x + 94.005 Eq. (4.6) As the regression coefficient (R 2 ) value is nearly equal to one. This showed that, turbidity removal efficiency was consistently increasing with the increase in depth of filter media. 4.10 UFRV with Increased Depth for MRGF's The graph showing UFRV with increased depth of MRGF's is presented in Fig. 4.9 . Throughout the cycles, the average UFRV for M A was 190.10 m 2 /m 2 , that for M B was 148.40 m 3 /m 2 and it was 123.70 m 3 /m 2 for M C . With the increases in depth of filter media in MRGF's, the UFRV was also in increasing trend. The equation of the trend line was as below: or, y = 3.3402x (4.7) As the regression coefficient (R 2 ) value is equal to 0.991. This showed that, UFRV of MRGF was increasing with the increase in depth of filter media. This showed that, by increasing the depth of filter media in MRGF, more water can withdraw during filtration process. Conclusion Current water difficulties necessitate the replacement of slow sand filters and the modification of rapid gravity filters with novel filter materials. This study aimed to access the effectiveness of using novel filter media composed of crushed overburnt brick and sand separated by geotextile in rapid gravity filtration. Numerous innovative materials, including pumice, sandstone, quartzite, and glass, have been experimented with in the rapid filtration process, yielding more favourable outcomes. Furthermore, research comparing the efficiency of rapid gravity filters in single layer media to that with dual layered media is uncommon. The aim of this study is to introduce novel filter media by combining the COB and sand separated by geotextile. During the execution of the entire experiment, the effect due to temperature, pH, and biological features of water were not considered. The effects of brick particle solubility, filter media loss, and intermittent operation of filter models were also not explored. During the filtration process, the increased surface area as well as depth of filter media due to high porosity imparted by COB and geotextile leading to turbidity removal of 97.87% for M A and 96.78% for M B , were greater than that of CRGF at 96.43%. The geotextile as a barrier between sand and COB and high porosity of COB stops entering of particles in to low lying sand layer, leading to longer filter run length and less head loss development during running for both M A and M B as compared to CRGF. As the filter run length extended, the UFRV of M A reached 190.14 m 3 /m 2 /h, while for M B it was 148.43 m 3 /m 2 /h, both surpassing to that of CRGF at 126.86 m 3 /m 2 /h. Finally, sand media can be replaced by novel media having filter media thickness 75% to that of sand media operating under similar conditions. Further, novel media with filter media thickness 50% to that of sand media under similar condition can be operated efficiently below influent turbidity of 100 NTU. Recommendations The outcomes generated by MRGF may undergo alterations when filters are operated in different environmental conditions. The execution of this experiment was hindered by limitations in terms of both time and resources. While the experiment was in progress, certain crucial parameters that warrant further investigation came to our attention. Exploring the impact of the formation of a dirty layer on overall filtration efficiency is imperative and should be subject to more extensive research. Additionally, it is worth delving deeper into how changes in water temperature during backwashing affect the expansion of the filter bed. The removal of metals such as iron and manganese from MRGF is achievable. If coagulants can be effectively applied within the filter bed, there is potential for enhancing filtration efficiency. Expanding the scope of this research to encompass the entire wastewater treatment process would be a notably superior approach. Declarations Author Contribution Er. yubaraj acharya is designated as correspondence author for this research article, who involved at every aspect of the research and preparation of manuscript, figures, and tables all complete. Similarly, Er. Arun parasad parajuli was involved as instructor/supervisor and final reviewer of the prepared manuscript from the start of day to this time. We both participated to perform our best from our side as per our assigned duty. References P. Udmale, H. Ishidaira, B. R. Thapa, and N. M. Shakya, “The status of domestic water demand: Supply deficit in the Kathmandu Valley, Nepal,” Water (Switzerland) , vol. 8, no. 5, pp. 1–9, 2016, doi: 10.3390/w8050196. N. Kresic, “Groundwater Contamination,” Hydrogeol. Groundw. Model. , pp. 425–468, 2020, doi: 10.1201/9781420004991-9. J. U. Grobbelaar, “Turbidity,” Encycl. Inl. Waters , pp. 699–704, Jan. 2009, doi: 10.1016/B978-012370626-3.00075-2. K. Abdiyev et al. , “Review of Slow Sand Filtration for Raw Water Treatment with Potential Application in Less-Developed Countries,” Water (Switzerland) , vol. 15, no. 11, 2023, doi: 10.3390/w15112007. K. J. 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Perera, “Burnt Clay Bricks as an Alternative Filter Media for Pebble Matrix Filters (PMF),” Eng. J. Inst. Eng. Sri Lanka , vol. 49, no. 3, p. 1, 2016, doi: 10.4038/engineer.v49i3.7071. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3881049","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268959293,"identity":"dabe105f-f6d5-4321-985a-c37837324d5d","order_by":0,"name":"Yubaraj Acharya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABXElEQVRIie3RP2vCQBzG8V84ODtcmo4JVnwLJ9JA0eLQN3IhkC4igkuHDheEuNjOigXfgi6h44UDJ7tbEkpLwalCuwgOLU1EEYJ1LjTfIQ8kfMg/gKysPxguvol4qkSLjyg5o3T47rK+h2jgsHicU4NvSVccJgav03hklYoNAZ0dJlSIs/HqQRIqiJlv3jwXUX8RfKzqkTXkKAgJRI00CbgTqtMrYiSkN2mV3EHDNm79uTUS2K4QmLfSRMIkVLwKOU4IwUxxB3UTVF9aI0jOgLR4ikwU72nlIQJr8s1qbn9qKl8xGXJtuY8YXYRnqndJThKiesxye8REyV24IHgf0XSMQ9VziNHGrUr/jtlut2HnC/68PJK4fH5PZfpdsK4t4wer1rRcexw2l+xi3HkMPhd+VBh22q+z92uZ/mK70BFdb4mTZMTmN1FgvxLIvaynCFuy6QDJysrK+h/9ANT6eAWfITZ/AAAAAElFTkSuQmCC","orcid":"","institution":"Tribhuvan University","correspondingAuthor":true,"prefix":"","firstName":"Yubaraj","middleName":"","lastName":"Acharya","suffix":""},{"id":268959294,"identity":"4b00712f-0e0b-43ff-866a-735b2dc8f2a4","order_by":1,"name":"Arun Prasad Parajuli","email":"","orcid":"","institution":"Tribhuvan University","correspondingAuthor":false,"prefix":"","firstName":"Arun","middleName":"Prasad","lastName":"Parajuli","suffix":""}],"badges":[],"createdAt":"2024-01-20 08:29:57","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3881049/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3881049/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50152847,"identity":"4ee1f17a-74c3-4524-8bfe-14a482196c4f","added_by":"auto","created_at":"2024-01-25 10:38:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":247302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2.1: Conceptual framework of study\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/23f0cf3588f0009d352a2168.png"},{"id":50153382,"identity":"1876e449-b6ad-4643-8c5f-c6ccb39ce100","added_by":"auto","created_at":"2024-01-25 10:46:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19101,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3.1: Ports location details (all dimensions in cm)\u003c/p\u003e","description":"","filename":"22.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/f7ddba1f945e642e4ba27ddd.png"},{"id":50152841,"identity":"fae5b95b-b397-4796-a5f8-8e336d37ee98","added_by":"auto","created_at":"2024-01-25 10:38:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":83153,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.1: Turbidity vs. Filter run time\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/8d46b12b6cb23b382fc44d71.png"},{"id":50152843,"identity":"66f170dd-94e7-4513-b1ea-83a7985ee6a9","added_by":"auto","created_at":"2024-01-25 10:38:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":125817,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.2: Head loss vs. filter run time\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/6890788e357289c587416211.png"},{"id":50153384,"identity":"d6e9fbc9-77af-4f7e-ad54-62a736e29621","added_by":"auto","created_at":"2024-01-25 10:46:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":31304,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.3: Filter run time vs. avg. influent turbidity\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/a29e73452a4e6d3da1cc74ff.png"},{"id":50152849,"identity":"438bc965-0f20-4952-bb77-5ecc17a413eb","added_by":"auto","created_at":"2024-01-25 10:38:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":42613,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.4: Influent/effluent vs. avg. influent turbidity\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/c40c1f0b055d919f2fe96c05.png"},{"id":50153381,"identity":"267bf474-2e33-4aa4-ae99-b18e2d81aef2","added_by":"auto","created_at":"2024-01-25 10:46:35","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":26884,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.5: UFRV vs. influent turbidity\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/64f3f2fcfcfc1a7177543009.png"},{"id":50152845,"identity":"bf61c51b-bec3-4d45-adc3-74a9a47c43ef","added_by":"auto","created_at":"2024-01-25 10:38:35","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":26709,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.6: Backwash time vs. avg. influent turbidity\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/a2debb6dde1b8f8df65b4be8.png"},{"id":50152851,"identity":"b97079ea-5b62-4a4c-bce8-d8b7734297bd","added_by":"auto","created_at":"2024-01-25 10:38:35","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":15186,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.7: Filter run time vs. depth of filter\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/fe9f8a704639ada5c26e5e12.png"},{"id":50153639,"identity":"36653980-eb1b-4041-b52a-3eead580f8d2","added_by":"auto","created_at":"2024-01-25 10:54:35","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":19203,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.8: Avg. removal efficiency vs. depth\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/db621df5e81f8d20bea63abd.png"},{"id":50153383,"identity":"ed6d89aa-461e-4491-a8e6-d08114c743fa","added_by":"auto","created_at":"2024-01-25 10:46:35","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":18272,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.9: UFRV vs. depth\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/37492000b4c2db163cc0e139.png"},{"id":62351483,"identity":"4f87f469-9c90-4bfa-ad10-f0d8b5ea13e4","added_by":"auto","created_at":"2024-08-13 08:14:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1325431,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3881049/v1/0e19c8bd-e36f-43cb-823b-88fe14868b8e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Performance Evaluation of Modified Rapid Gravity Filter by Using Sand and Crushed Overburnt Brick Separated by Geotextile","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWater is regarded as one of the most vital natural resources on the planet. The availability of safe drinking water reflects a community's economic, social, and cultural well-being. Global urbanization has posed new issues to the availability and delivery of drinkable water. According to ADB reports, people living in urban areas are at daily danger of different diseases, health risks, and associated economic burdens, which disproportionately affect Kathmandu Valley's poor and vulnerable population due to insufficient water availability [1]. Natural sources or a variety of human activities can contaminate groundwater gathered and stored in subterranean water reservoirs [2].\u003c/p\u003e \u003cp\u003eTurbidity is a substantial impurity that may be present in water, and the general population can utilize it to decide whether or not to accept the water after visualization without more thought. Water turbidity is caused primarily by the presence of suspended particles, colloidal particles, inorganic debris, plankton, and other microscopic creatures [3]. Turbid water can also serve as a breeding ground for dangerous algae and other microbes that create toxins that are detrimental to humans and animals. To handle water turbidity issues, the filtering process stands out as an efficient and cost-effective method of water treatment. Filtration is the fundamental process on removal of suspended and colloidal particles present in water that drains through a porous medium (Garcia-Avila et al., 2020). Slow Sand Filters (SSF) was primitive water treatment system developed in England in 19th century. SSF has some limitations and is not recommended for water treatment with turbidity greater than 5 NTU [4]. To overcome the frequent clogging in slow sand filtration, rapid gravity filters (RGF) with coarse sand as filter media were developed, which draws more water than that of SSF [5]. The development of filter media, that have ability to withdraw more water is critical in water treatment. Study shows that, RGF with dual filter media is capable of producing 10% more water having same quality standard of single bed with longer filtration cycles [6]. Filtration system having consequent reduction in cost along with improved filtration efficiency are under research to replace the traditional sand.\u003c/p\u003e \u003cp\u003eIn RGF's, sand and anthracite are the traditionally used filter media materials. Due to hardness, porosity and readily availability of overburnt bricks (about 13% of the produced brick from brick factory [7]), research on overburnt brick could state an alternative filter media material in filtration process. Facilitation of bed stability, longer filter run time, slow clogging and more water production in a cycle are the key characteristics of filter media materials for efficient filtration. Application of porous, heavy and tightly confined media bed can achieve such characteristics. The integration of essential qualities found in overburnt brick as porous material, sand as heavy material, and geotextile as layer separator to create dual-layered filtering media might potentially result a highly effective water treatment system.\u003c/p\u003e \u003cp\u003eAs combined media bed, crushed overburnt brick facilitates adsorption and trapping of tiny particles at upper layer, traditional sand may help to keep the flow steady during the filtration process and the use of a geotextile layer within filter media helps to prevent filter media clogging [8], bed stability and avoid in mixing of filter media materials during backwashing process as well. The growing need for efficient and sustainable water treatment systems has given rise to researchers to explore alternative materials for use in filtration processes. As COB is not a regular construction material, it is considered only a waste material from brick factory. Due to its impressive properties on filtration, utilization of COB in filtration process states a novel filter media and it will be also a proper utilization of factory waste materials. Besides, study of COB and its combination with sand by providing geotextile as layer separator for bed stability is rare. This study aimed to assessed the performance of dual layered filter media consisting of COB and sand separated by geotextile in terms of turbidity removal, head loss development, filter run length, UFRV and back wash water consumption under varied influent turbidity.\u003c/p\u003e"},{"header":"Materials and Methodology","content":"\u003cp\u003eFour rapid gravity filter columns made of fiber glass were used in the experiment. The filter column using sand as filter media was labelled as a Conventional Rapid Gravity Filter (CRGF), while the other three with dual-layered media were labelled as Modified Rapid Gravity Filters (MRGF). The conceptual framework of this study is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Material Collection and Preparation of Filter Media\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Base materials\u003c/h2\u003e \u003cp\u003eThe machine crushed\u003c/p\u003e \u003cp\u003egravel collected from the stockpile of the IOE Pulchowk campus laboratory was manually sorted and cleaned of clay, dirt, vegetable, and organic matter. The cleaned gravel was then sieved through different sieve sizes, and then packed into separate sacks, ensuring its proper storage for later use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Filter media\u003c/h2\u003e \u003cp\u003eRiver sand collected from Heavy lab of Pulchowk campus as well as overburnt bricks collected from brick factory and then crushed manually in same lab were sieved separately through the series of sieves and mixed to get uniformity coefficient of 1.60 and effective size (d\u003csub\u003e10\u003c/sub\u003e) of 0.50 mm. Loss on ignition test was determined as 0.25% while it was 0.35% for COB, were less than 0.7 as prescribed by (IS:8419 (part I)). Acid solubility test was also conducted and percentage loss in weight for sand was determined as 1.99% and that for COB was determined as 0.89%, which were remained less than 5% [9]. During preparation, porosity and density tests were also conducted in the laboratory by using the standard method prescribed by (IS 1528 (Part 15): 2007). The tests showed that, COB was 6.4% more porous than that of sand, but the density of sand surpassed that of COB by a significant margin of 439.23 kg/m\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Geotextile\u003c/h2\u003e \u003cp\u003eGeotextile with a nonwoven structure and a pore size of 0.2 mm was acquired from a hardware shop. It was carefully cut, trimmed, and arranged to match the internal dimensions of the filter column, ensuring a perfect fit and optimal functionality.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Model Setup\u003c/h2\u003e \u003cp\u003eFour filter columns were fashioned, each possessing internal dimensions measuring 150 mm \u0026times; 150 mm. The filter columns were marked with a series of marks at every 10 cm from bottom to top. These filter columns were subsequently designated with distinct names, correlating to the specific thickness of their filter media, as depicted in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3.1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDesignation of filter columns\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCode Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCRGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFilter column with sand media having thickness of 60 cm.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAs per design\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMRGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003csub\u003eA\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFilter column with 30 cm sand and 30 cm COB.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[10]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFilter column with 22.5 cm sand and 22.5 cm COB.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[10]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003csub\u003eC\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFilter column with 15 cm sand and 15 cm COB.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[10]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe four filter columns were specifically established in the water supply department of TU, IOE. Each filter column was comprised of six ports. Three of them were placed 5 cm above the bottom of the filter columns for the purpose of outlet, piezometer connection, and backwashing operation, while the remaining three were placed at specific heights for piezometer connection, backwash water effluent, and overflow drainage whilst maintaining the bed expansion 20 cm and standing depth of water level at 110 cm above the filter media. A comprehensive summary of the ports is mentioned in the Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Operation of Filter Model\u003c/h2\u003e \u003cp\u003eThe filter columns were operated intermittently under constant discharge and variable water head conditions by using the artificially prepared turbid water by maintaining the equal influent as well as effluent discharges of 2.5 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h and initial water level above the top of the filter media was precisely maintained at 110 cm. Samples from influent and effluent ports were collected hourly in 250 ml bottles and turgidities were measured by using Digital Turbidity Meter (Model no. 988, AE-MAX company). When terminal head loss reached up to 155 cm, the backwashing operation was initiated by using clear water stored in 1000 liter tank with a consistent discharge rate of 21 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h and available head 5 m at inlet portal. The backwashing operation was halted once the clarity of the backwashed effluent was determined to be satisfactory. Once the backwashing operation was completed, filters were resumed by applying water with higher influent turbidity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result and Discussion","content":"\u003cp\u003eSeven filter runs were performed for influent turbidity values 0\u0026ndash;25, 25\u0026ndash;50, 50\u0026ndash;100, 100\u0026ndash;150, 150\u0026ndash;200, 200\u0026ndash;250, and 250\u0026ndash;300 NTU. With comparative analysis of four filter columns, performance of Modified Rapid Gravity Filters was evaluated and compared with Conventional Rapid Gravity Filter. The results of the filter runs were discussed and presented graphically. The summary of filter runs for CRGF, M\u003csub\u003eA\u003c/sub\u003e and M\u003csub\u003eB\u003c/sub\u003e were as depicted in Table \u003cspan\u003e4.1\u003c/span\u003e, Table \u003cspan\u003e4.2\u003c/span\u003e, Table \u003cspan\u003e4.3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4.1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSummary of filter runs for CRGF\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRun cycle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTurbidity Range (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAverage Influent Turbidity (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAverage Effluent Turbidity (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRun Time (Hrs.).\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUFRV\u003c/p\u003e\n \u003cp\u003e(m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHead loss gained\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBackwashing\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (Mins)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e% Water Consumption\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026ndash;100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u0026ndash;200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u0026ndash;250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e220.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u0026ndash;300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e277.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4.2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSummary of filter runs for M\u003csub\u003eA\u003c/sub\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRun Cycle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTurbidity Range (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAverage Influent Turbidity (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAverage Effluent Turbidity (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRun Time (Hrs.)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUFRV\u003c/p\u003e\n \u003cp\u003e(m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHead loss gained\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBackwashing\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (Mins)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e% Water Consumption\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026ndash;100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u0026ndash;200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u0026ndash;250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e220.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u0026ndash;300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e277.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4.3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSummary of filter runs for M\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRun Cycle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTurbidity Range (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAverage Influent Turbidity (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAverage Effluent Turbidity (NTU)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRun Time (Hrs.)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUFRV\u003c/p\u003e\n \u003cp\u003e(m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHead loss gained\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBackwashing\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (Mins)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e% Water Consumption\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026ndash;100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u0026ndash;200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u0026ndash;250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e220.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u0026ndash;300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e277.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e4.1 Influent and Effluent Turbidity with Filter Run Time\u003c/h2\u003e\n \u003cp\u003eThe influent and effluent turbidity of synthetic turbid water resulted from third, fourth and sixth filter runs are presented in Fig. 4.1:\u003c/p\u003e\n \u003cdiv\u003eDuring the filter runs, all the filter models showed effluent turbidity values below 5 NTU for influent turbidity value up to 100 NTU as prescribed by (Nepal Gazette, 2022). CRGF, M\u003csub\u003eA\u003c/sub\u003e and M\u003csub\u003eB\u003c/sub\u003e showed effluent turbidity value below 5 NTU for influent turbidity up to 150 NTU. However, M\u003csub\u003eA\u003c/sub\u003e showed effluent turbidity value below 5 NTU for influent turbidity up to 250 NTU. Above 250 NTU all filters were unable to produce effluent turbidity below 5 NTU. During the seven filter run cycles, M\u003csub\u003eA\u003c/sub\u003e consistently outperformed the other models in terms of turbidity removal. This superior performance can be attributed to several factors such as, the enhanced surface area that trapped tiny particles, the extended contact time for particles within the filter media, and the improved depth filtration resulting from the increased porosity of the filter medium.\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e4.2 Head Loss Development During Filtration Process\u003c/h2\u003e\n \u003cp\u003eThroughout the seven cycles of filter run, a stringent criterion was set for the allowable terminal head loss, which was determined to be 155 cm. The minimum initial head loss was 4.7 cm for filter columns, M\u003csub\u003eA\u003c/sub\u003e, M\u003csub\u003eB\u003c/sub\u003e and M\u003csub\u003eC\u003c/sub\u003e and that for CRGF was 5.3 cm in first filter run while, maximum initial head loss was 18.2 cm for CRGF, in fifth filter run, 17.4 cm for M\u003csub\u003eA\u003c/sub\u003e, 17.8 cm for M\u003csub\u003eB\u003c/sub\u003e in fifth filter run and that for M\u003csub\u003eC\u003c/sub\u003e was 17.8 cm in fourth filter run as shown in Figure (4.2).\u003c/p\u003e\u003cspan\u003e\u0026nbsp;\u003c/span\u003eWith the escalating influent turbidity, the progression of head loss exhibited rapidity across all filter columns. Amongst the entirety of filter columns, the minimum rate of head loss growth was observed in M\u003csub\u003eA\u003c/sub\u003e, while M\u003csub\u003eC\u003c/sub\u003e displayed a higher rate of head loss. The swift development of head loss in all filter columns can be attributed to the increased influent turbidity, which is indicative of surface sealing within the filter media. The increased suspended particle load on identical cross-sectional area of filter media from initial cycle to last cycle was also a main reason on rapid head loss development. Additionally, the intermittent filter operation resulted in a consistent daily decline in head pressure.\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e4.3 Filter Run Time and its Correlation with Increase in Influent Turbidity\u003c/h2\u003e\n \u003cp\u003eThe filter run length is contingent upon the unique characteristics of the raw water being treated. In Fig. \u003cspan\u003e4.3\u003c/span\u003e, the filter run times for various influent turbidity values were displayed for all filter columns. As the influent turbidity increases, the filter run time decreases, primarily due to the escalated presence of suspended solids. Throughout the seven cycles of filter run, with the increases in influent turbidity length of cycles were decreased.\u003c/p\u003e\n \u003cp\u003eDuring every filter run cycle, the maximum filter run time was observed for M\u003csub\u003eA\u003c/sub\u003e, while the minimum filter run time was recorded for filter column M\u003csub\u003eC\u003c/sub\u003e. Additionally, the filter run time for M\u003csub\u003eB\u003c/sub\u003e was consistently longer than that of CRGF for each cycle of runs. The filter run time for CRGF and M\u003csub\u003eC\u003c/sub\u003e remains almost the same for all influent turbidity values. However, upon attaining an average influent turbidity level of 180 NTU, the filter run time for CRGF, M\u003csub\u003eB\u003c/sub\u003e, and M\u003csub\u003eC\u003c/sub\u003e becomes approximately equal, although M\u003csub\u003eB\u003c/sub\u003e showed a slightly higher run time. The longer duration of filtration in MRGF\u0026apos;s, in comparison to CRGF, suggests that there is a lower density of COB particles packed within the filtering material. This leads to greater porosity in the media, an expanded surface area allowing more interaction between media grains and suspended particles, and so on.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003e4.4 Effect of Porosity of Filter Media in Filtration Process\u003c/h2\u003e\n \u003cp\u003eFrom the experiment, it was found that the porosity of COB was 6.4% higher than that of sand media. Experimentally, the filter run time for MRGF\u0026apos;s was consistently higher than that of CRGF for every influent turbidity range with exceptional case of M\u003csub\u003eC\u003c/sub\u003e. Theoretical analysis revealed that the initial head loss development for CRGF was 58.5 cm, whereas for MRGF\u0026apos;s, it was 38.5 cm. This indicates that the head loss development for CRGF was greater than that of MRGF\u0026apos;s. Additionally, the filter run length for MRGF\u0026apos;s was longer than that of CRGF, attributed to the higher porosity of the COB as well as extra porosity imparted by geotextile used between the layers.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003e4.5 Analysis of Turbidity Removal Under Varying Influent Turbidity Levels\u003c/h2\u003e\n \u003cp\u003eThroughout the seven cycles of filter run, M\u003csub\u003eC\u003c/sub\u003e was lower efficient and M\u003csub\u003eA\u003c/sub\u003e was most efficient. CRGF was more efficient than M\u003csub\u003eC\u003c/sub\u003e but less efficient than M\u003csub\u003eB\u003c/sub\u003e. Filter M\u003csub\u003eA\u003c/sub\u003e was relatively most efficient in the influent turbidity range of 25\u0026ndash;50 NTU and was less efficient in the influent turbidity range of 200\u0026ndash;250 NTU. The comparison of four filter models in the influent turbidity removal is presented in Fig. \u003cspan\u003e4.4\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThe comparative study shows that the MRGF was more efficient for turbidity removal even in reduction of thickness up to 75% than that of CRGF. The achievement of higher efficiency for the MRGF columns over CRGF columns was due to higher porosity of COB that enable to trap the suspended particles in top portion of the filter media and extra porosity imparted by geotextile used as layer separator. The graph showed that, turbidity removal efficiency was in increasing trend on increasing influent turbidity for all filter columns. Referring to the Fig. \u003cspan\u003e4.7\u003c/span\u003e, the equations of trend line and R\u003csup\u003e2\u003c/sup\u003e values for CRGF, M\u003csub\u003eA\u003c/sub\u003e, M\u003csub\u003eB\u003c/sub\u003e and M\u003csub\u003eC\u003c/sub\u003e were as follow:\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;2.3034x\u0026thinsp;+\u0026thinsp;12.294 [R\u0026sup2; = 0.9721] (4.1)\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;5.8495x\u0026thinsp;+\u0026thinsp;14.327 [R\u0026sup2; = 0.9891] (4.2)\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;2.7933x\u0026thinsp;+\u0026thinsp;13.816 [R\u0026sup2; = 0.9805] (4.3)\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;1.0583x\u0026thinsp;+\u0026thinsp;10.246 [R\u0026sup2; = 0.9868] (4.4)\u003c/p\u003e\n \u003cp\u003eThe regression coefficient (R\u003csup\u003e2\u003c/sup\u003e) for M\u003csub\u003eA\u003c/sub\u003e was highest among all. It showed that, the data obtained for M\u003csub\u003eA\u003c/sub\u003e was more consistent than that from other columns. This observation implies that the filter bed remained stable in its operation, likely due to better confinement provided by the geotextile and the higher specific gravity of the sand used.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003e4.6 Unit Filter Run Volume (UFRV) with Increased Influent Turbidity Level\u003c/h2\u003e\n \u003cp\u003eWith the increase in influent turbidity, Unit Filtration Run Volume (UFRV) of CRGF and MRGD\u0026apos;s was found to be decreased throughout the cycles. The UFRV value for M\u003csub\u003eA\u003c/sub\u003e was found to be higher among all filters for all cycles. Throughout the cycles of filter run, maximum UFRV value for M\u003csub\u003eA\u003c/sub\u003e was 583 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e, that for M\u003csub\u003eB\u003c/sub\u003e was 440 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e, that for CRGF was 389 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e and that for M\u003csub\u003eC\u003c/sub\u003e was 386 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e. CRGF and M\u003csub\u003eC\u003c/sub\u003e were showed same pattern of UFRV throughout the cycles. Similarly, minimum UFRV value for M\u003csub\u003eA\u003c/sub\u003e was 49 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e, that for M\u003csub\u003eB\u003c/sub\u003e was 34 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e, that for CRGF was 29 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e and that for M\u003csub\u003eC\u003c/sub\u003e was 26 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e. The graph between UFRV and avg. influent turbidity is depicted in Fig. \u003cspan\u003e4.5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eOn average, the UFRV for M\u003csub\u003eA\u003c/sub\u003e was higher by 63.29 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e, for M\u003csub\u003eB\u003c/sub\u003e was higher by 21.57 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e and that for M\u003csub\u003eC\u003c/sub\u003e was lower by 3.14 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e as compared to that of filter CRGF. The higher values of UFRV for M\u003csub\u003eA\u003c/sub\u003e and M\u003csub\u003eB\u003c/sub\u003e compared to CRGF were due to the increased surface area within the filter media due to porosity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003e4.7 Backwash Time with Increased Influent Turbidity\u003c/h2\u003e\n \u003cp\u003eBackwashing was commenced with a backwash velocity of 21 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2/\u003c/sup\u003ehr when the terminal head loss was attained at 155 cm. Backwashing time was determined by observing the relative clarity of the backwash effluent. The backwash time for different influent turbidity levels is shown in Fig. \u003cspan\u003e4.6\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eBackwashing time for CRGF was more than M\u003csub\u003eA\u003c/sub\u003e, M\u003csub\u003eB\u003c/sub\u003e and M\u003csub\u003eC\u003c/sub\u003e except from sixth cycle of filter run. After sixth filter run, backwashing time for CRGF was less than that of M\u003csub\u003eA\u003c/sub\u003e, but more than that of M\u003csub\u003eB\u003c/sub\u003e and M\u003csub\u003eC\u003c/sub\u003e. Throughout the cycles, the maximum backwash time for CRGF was 30 minutes, after completion of sixth cycle and the minimum backwash time for CRGF was 17 minutes at the end of first cycle. However, the maximum backwash time for M\u003csub\u003eA\u003c/sub\u003e was 32 minutes, after completion of sixth cycle and the minimum backwash time for M\u003csub\u003eA\u003c/sub\u003e was 16 minutes at the end of first cycle. The maximum backwash time for M\u003csub\u003eB\u003c/sub\u003e was 28 minutes after completion of seventh cycle and the minimum backwash time for M\u003csub\u003eB\u003c/sub\u003e was 15 minutes at the end of first cycle. The maximum backwash time for M\u003csub\u003eC\u003c/sub\u003e was 23 minutes, after completion of sixth cycle and the minimum backwash time for M\u003csub\u003eC\u003c/sub\u003e was 12 minutes at the end of first cycle. Throughout the cycles, the shortest duration for backwashing was occurred with M\u003csub\u003eC\u003c/sub\u003e, taking an average of 19.43 minutes. This was because the depth of filter media being washed at once was smaller, resulting in a quicker process. On the other hand, the longest backwashing time was observed with CRGF, averaging 24.14 minutes. This was attributed to the larger depth of filter media to be cleaned and the presence of densely packed sand grains, which led to a more time-consuming backwashing process.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003e4.8 Filter Run Time with Increased Depth for MRGF\u0026apos;s\u003c/h2\u003e\n \u003cp\u003eThe graph showing filter run time with increased depth for MRGF\u0026apos;s is presented in Fig. \u003cspan\u003e4.7\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThroughout the cycles, the average filter run time for M\u003csub\u003eA\u003c/sub\u003e was 62.29 Hrs., that for M\u003csub\u003eB\u003c/sub\u003e was 52 Hrs. and it was 43.29 Hrs. for M\u003csub\u003eC\u003c/sub\u003e. With the increases in depth of filter media in MRGF\u0026apos;s, the filter run time was also in increasing trend. Equation of the trend line is:\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;0.6333x\u0026thinsp;+\u0026thinsp;24.027 Eq.\u0026nbsp;(4.5)\u003c/p\u003e\n \u003cp\u003eAs the regression coefficient (R\u003csup\u003e2\u003c/sup\u003e) value is nearly equal to one. This showed that, filter run time was consistently increasing with the increase in depth of filter media.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \u003ch2\u003e4.9 Removal Efficiency with Increased Depth for MRGF\u0026apos;s\u003c/h2\u003e\n \u003cp\u003eThe graph showing turbidity removal efficiency with increased depth of MRGF\u0026apos;s is presented in Fig. \u003cspan\u003e4.8\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThroughout the cycles, the average turbidity removal efficiency for M\u003csub\u003eA\u003c/sub\u003e was 96.99%, that for M\u003csub\u003eB\u003c/sub\u003e was 95.66% and it was 92.66% for M\u003csub\u003eC\u003c/sub\u003e. With the increases in depth of filter media in MRGF\u0026apos;s, the filter run time was also in increasing trend. The equation of the trend line is:\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;0.0637x\u0026thinsp;+\u0026thinsp;94.005 Eq.\u0026nbsp;(4.6)\u003c/p\u003e\n \u003cp\u003eAs the regression coefficient (R\u003csup\u003e2\u003c/sup\u003e) value is nearly equal to one. This showed that, turbidity removal efficiency was consistently increasing with the increase in depth of filter media.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\"\u003e\n \u003ch2\u003e4.10 UFRV with Increased Depth for MRGF\u0026apos;s\u003c/h2\u003e\n \u003cp\u003eThe graph showing UFRV with increased depth of MRGF\u0026apos;s is presented in Fig. \u003cspan\u003e4.9\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThroughout the cycles, the average UFRV for M\u003csub\u003eA\u003c/sub\u003e was 190.10 m\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e, that for M\u003csub\u003eB\u003c/sub\u003e was 148.40 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e and it was 123.70 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e for M\u003csub\u003eC\u003c/sub\u003e. With the increases in depth of filter media in MRGF\u0026apos;s, the UFRV was also in increasing trend. The equation of the trend line was as below:\u003c/p\u003e\n \u003cp\u003eor, y\u0026thinsp;=\u0026thinsp;3.3402x (4.7)\u003c/p\u003e\n \u003cp\u003eAs the regression coefficient (R\u003csup\u003e2\u003c/sup\u003e) value is equal to 0.991. This showed that, UFRV of MRGF was increasing with the increase in depth of filter media. This showed that, by increasing the depth of filter media in MRGF, more water can withdraw during filtration process.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCurrent water difficulties necessitate the replacement of slow sand filters and the modification of rapid gravity filters with novel filter materials. This study aimed to access the effectiveness of using novel filter media composed of crushed overburnt brick and sand separated by geotextile in rapid gravity filtration. Numerous innovative materials, including pumice, sandstone, quartzite, and glass, have been experimented with in the rapid filtration process, yielding more favourable outcomes. Furthermore, research comparing the efficiency of rapid gravity filters in single layer media to that with dual layered media is uncommon. The aim of this study is to introduce novel filter media by combining the COB and sand separated by geotextile. During the execution of the entire experiment, the effect due to temperature, pH, and biological features of water were not considered. The effects of brick particle solubility, filter media loss, and intermittent operation of filter models were also not explored. During the filtration process, the increased surface area as well as depth of filter media due to high porosity imparted by COB and geotextile leading to turbidity removal of 97.87% for M\u003csub\u003eA\u003c/sub\u003e and 96.78% for M\u003csub\u003eB\u003c/sub\u003e, were greater than that of CRGF at 96.43%. The geotextile as a barrier between sand and COB and high porosity of COB stops entering of particles in to low lying sand layer, leading to longer filter run length and less head loss development during running for both M\u003csub\u003eA\u003c/sub\u003e and M\u003csub\u003eB\u003c/sub\u003e as compared to CRGF. As the filter run length extended, the UFRV of M\u003csub\u003eA\u003c/sub\u003e reached 190.14 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h, while for M\u003csub\u003eB\u003c/sub\u003e it was 148.43 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h, both surpassing to that of CRGF at 126.86 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h. Finally, sand media can be replaced by novel media having filter media thickness 75% to that of sand media operating under similar conditions. Further, novel media with filter media thickness 50% to that of sand media under similar condition can be operated efficiently below influent turbidity of 100 NTU.\u003c/p\u003e"},{"header":"Recommendations","content":"\u003cp\u003eThe outcomes generated by MRGF may undergo alterations when filters are operated in different environmental conditions. The execution of this experiment was hindered by limitations in terms of both time and resources. While the experiment was in progress, certain crucial parameters that warrant further investigation came to our attention. Exploring the impact of the formation of a dirty layer on overall filtration efficiency is imperative and should be subject to more extensive research. Additionally, it is worth delving deeper into how changes in water temperature during backwashing affect the expansion of the filter bed. The removal of metals such as iron and manganese from MRGF is achievable. If coagulants can be effectively applied within the filter bed, there is potential for enhancing filtration efficiency. Expanding the scope of this research to encompass the entire wastewater treatment process would be a notably superior approach.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eEr. yubaraj acharya is designated as correspondence author for this research article, who involved at every aspect of the research and preparation of manuscript, figures, and tables all complete. Similarly, Er. Arun parasad parajuli was involved as instructor/supervisor and final reviewer of the prepared manuscript from the start of day to this time. We both participated to perform our best from our side as per our assigned duty.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eP. Udmale, H. Ishidaira, B. R. Thapa, and N. M. Shakya, \u0026ldquo;The status of domestic water demand: Supply deficit in the Kathmandu Valley, Nepal,\u0026rdquo; \u003cem\u003eWater (Switzerland)\u003c/em\u003e, vol. 8, no. 5, pp. 1\u0026ndash;9, 2016, doi: 10.3390/w8050196.\u003c/li\u003e\n\u003cli\u003eN. Kresic, \u0026ldquo;Groundwater Contamination,\u0026rdquo; \u003cem\u003eHydrogeol. Groundw. Model.\u003c/em\u003e, pp. 425\u0026ndash;468, 2020, doi: 10.1201/9781420004991-9.\u003c/li\u003e\n\u003cli\u003eJ. U. Grobbelaar, \u0026ldquo;Turbidity,\u0026rdquo; \u003cem\u003eEncycl. Inl. Waters\u003c/em\u003e, pp. 699\u0026ndash;704, Jan. 2009, doi: 10.1016/B978-012370626-3.00075-2.\u003c/li\u003e\n\u003cli\u003eK. Abdiyev \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Review of Slow Sand Filtration for Raw Water Treatment with Potential Application in Less-Developed Countries,\u0026rdquo; \u003cem\u003eWater (Switzerland)\u003c/em\u003e, vol. 15, no. 11, 2023, doi: 10.3390/w15112007.\u003c/li\u003e\n\u003cli\u003eK. J. Ives, \u0026ldquo;Rapid filtration,\u0026rdquo; \u003cem\u003eWater Res.\u003c/em\u003e, vol. 4, no. 3, pp. 201\u0026ndash;223, 1970, doi: 10.1016/0043-1354(70)90068-0.\u003c/li\u003e\n\u003cli\u003eA. Zouboulis, G. Traskas, and P. Samaras, \u0026ldquo;Comparison of single and dual media filtration in a full-scale drinking water treatment plant,\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e, vol. 213, no. 1\u0026ndash;3, pp. 334\u0026ndash;342, Jul. 2007, doi: 10.1016/j.desal.2006.02.102.\u003c/li\u003e\n\u003cli\u003eA. R. Mazumder, A. Kabir, and N. Yazdani, \u0026ldquo;Performance of Overburnt Distorted Bricks as Aggregates in Pavement Works,\u0026rdquo; \u003cem\u003eJ. Mater. Civ. Eng.\u003c/em\u003e, vol. 18, no. 6, pp. 777\u0026ndash;785, 2006, doi: 10.1061/(asce)0899-1561(2006)18:6(777).\u003c/li\u003e\n\u003cli\u003eN. Fitriani \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Performance of geotextile-based slow sand filter media in removing total coli for drinking water treatment using system dynamics modelling,\u0026rdquo; \u003cem\u003eHeliyon\u003c/em\u003e, vol. 6, no. 9, p. e04967, 2020, doi: 10.1016/j.heliyon.2020.e04967.\u003c/li\u003e\n\u003cli\u003eR. Schneider and M. Furton, \u0026ldquo;Sand Source and Testing Methods - Research Report,\u0026rdquo; pp. 1\u0026ndash;16, 2013.\u003c/li\u003e\n\u003cli\u003eC. P. G. Jayalath, N. S. Miguntanna, and H. A. K. C. Perera, \u0026ldquo;Burnt Clay Bricks as an Alternative Filter Media for Pebble Matrix Filters (PMF),\u0026rdquo; \u003cem\u003eEng. J. Inst. Eng. Sri Lanka\u003c/em\u003e, vol. 49, no. 3, p. 1, 2016, doi: 10.4038/engineer.v49i3.7071.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Conventional Filter, Crushed Overburnt Brick, Filtration, Modified Rapid Gravity Filter, Turbidity","lastPublishedDoi":"10.21203/rs.3.rs-3881049/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3881049/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe effectiveness of slow sand filters in accomplishing future water demand is becoming less, along with that, improvement in filtration efficiency of rapid gravity filter is under research. This study aimed to access the effectiveness of using novel filter media composed of crushed overburnt brick and sand separated by geotextile in rapid gravity filtration. The experiment was conducted with four rapid gravity filters by maintaining the constant influent and effluent discharge of 2.5 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h. The experiment was repeated seven times with varied influent turbidites by resuming the filtration process after backwashing with the backwash velocity of 21 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e/h, when terminal head loss exhausted 155 cm. Turbidity removal efficiency of RGF with novel media was observed to be improved by 2.07% as compared to conventional sand filter. Further, improvement in UFRV was by 49.89%, backwash water consumption was by 58.32%, backwash time was by 3.68%. The filter run length was reached up to about 1.5 times more than that of conventional sand filter. This study suggests that, substituting sand media with innovative media, which has a filter media thickness of 75% compared to sand media, can perform effectively. Additionally, it was observed that novel media with a filter media thickness of 50% as compared to sand media can efficiently operate when influent turbidity is below 100 NTU.\u003c/p\u003e","manuscriptTitle":"Performance Evaluation of Modified Rapid Gravity Filter by Using Sand and Crushed Overburnt Brick Separated by Geotextile","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-25 10:38:30","doi":"10.21203/rs.3.rs-3881049/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5b477a02-df57-466d-a346-44e61f74209b","owner":[],"postedDate":"January 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-13T08:06:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-25 10:38:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3881049","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3881049","identity":"rs-3881049","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}