EM and MM Biological Treatment Raby 1 B iological Treatment of Monteverde Gray Water using Effective Microorganisms and Mountain Microorganisms Sierra Raby Department of Environmental Science, Policy, and Management University of California, Berkeley EAP Tropical B iology and Conservation Program , Fall 2017 15 December 2017 ABSTRACT As in many rural or less structurally developed areas, homeowners and businesses in Monteverde, Costa Rica filter grey water through grease trap s or biojardineras or release it directly into their yards. This study evaluates the efficacy of two concentrations of Effective Microorganisms (EM) and Mountain Microorganisms (MM) in improving local grey water. These solutions contain biologically beneficial bacteria, yeast, and fungi. I collected g rey water from six residential and commercial sources , treated each source with EM and MM in different concentrations , and gathered water quality metrics from each group for seven days. The metrics included surface cover, sedimentation, layering, smel l, percent Total Dissol ved Solids ( %TDS ) , D issolved Oxygen ( %DO ) , and pH. After seven days, all treated containers had more surface cover than the control containers. All treatment groups reduced %TDS significantly more than the control group. Percent dissolved oxygen for all treatments decreased compared to the control, and continued decreasing until day seven, indicating that the microbes remained active until the last day of measurements . Both EM and MM solutions have a low pH, which may ex plain the higher acidity in treatment groups than control groups. EM concentrate performed best in the categories of sedimentation and smell . Therefore, addition of similar ratios of EM would best enhance grey water system efficacy and pleasantness , impro ving the quality of life of those who use them. Tratamiento BiolÃ³gico de Aguas Grises en Monteverde usando Microorganismos Efectivos y Microorganismos de Monta Ã± a RESUMEN Al igual que en muchas Ã¡reas rural es o menos desarrolladas estructuralmente , los propietarios de casas y negocios en Monteverde, Costa Rica filtra n sus agua s gris es a travÃ©s de trampas de grasa o biojardineras o la liberan directamente en sus patio s. Este estudio evalÃºa la eficacia de dos concentrados de Microorganismos Efectivos (EM) y Microorganismos de Monta Ã± a (MM) en la mejora del agua gris local. Estas soluciones contienen bacteria, levadura , y hongos beneficios. Recog Ã agua s gris es de seis fuente s residenciales y comerciales , trat Ã© cada fuente con EM o MM en diferentes concentraciones y med Ã cierto s parÃ¡metros de calidad del agua de cada grupo durante siete dÃas. Los parÃ¡metros incluyen cobertura de la superficie, sedimentaciÃ³n, estratificaciÃ³n, olor, porcentaje de sÃ³lidos totales disueltos (%TDS ), ox Ãgeno di suelto (%DO) y pH. DespuÃ©s de siete dÃas, todos los recipientes tratados tenÃan mÃ¡s cobertura de super ficie que los contenedores del control. Todos los tratamientos redujeron %TDS significativamente mÃ¡s que el grupo control. El porcentaje de oxÃgeno disuel to para todos los
EM and MM Biological Treatment Raby 2 tratamientos disminuy Ã³ en comparaciÃ³n con el control hasta el Ãº ltimo dÃa, lo que indica que los microorganismos todavÃa estaban activos el Ãºltimo dÃa de mediciones . Las soluciones EM y MM tienen un pH bajo, lo cual pudo haber causado que los tratamientos fuera n mÃ¡s Ã¡cidos que el control . El concentrado EM se obtuvo los mejores resultados en las categorÃas de sedimentaciÃ³n y olor. Por lo tanto, la adiciÃ³n de proporciones similares de EM mejorarÃa la eficacia de sistema de aguas gris es , mejo rando la calidad de vida de quienes lo aplican . Grey w ater from businesses and houses includes wastew ater from showers, sinks, and laundry systems , but does not include toilet water or water from animal enclosures . It contains contaminants and nutrients that can disrupt the balance of ecosystems and threaten the safety of waterways for human use. Contaminants include heavy metals that poison many aquatic species, while disruptions of nutrient balance (usually an excess of nitrogen and phosphorus) in aqua tic ecosystems can facilitate excessive growth of some aquatic weed and algal species (Sheffield , 1968). Natural processes deal with waste material in an efficient way. Biological treatment and bioremediation employ microorganisms to degrade or transform pollutants, while phytoremediation uses plants for the same purpose. Both methods offer environmentally sustainable and economically viable methods of cleaning water and soil. Other methods, such as chemical treatments, often harm the environment or prove expensive (Wenzel, 2009). Effective microorganisms (EM) may help to improve grey water quality via bioremediation. EM include fungi, bacteria, and yeasts grown from a simple mix of a commercially produced mother culture or whey (the source of the microbes ) and molasses (a food source) (Zakaria et al., 2010 ) . T hey are primarily used to fertilize crops or improve soil and water q uality (Park et al., 2016). Microbes in EM enhance water quality by fixing nitrogen, decomposing organic wastes, reducing pathogen co unt, breaking down toxins, and/or recycling and solubilizing nutrients . Dr. Teruo Higa introduced EM to improve agricultural sustainability in Japan in 1980 , and it has since improved many aspects of sanitation and organic farming . In comparison, mountain m icroorganisms (a type of EM) come from natural systems ( with microbes sourced from leaf litter instead of whey) , but will also cultivate in a mix of rice flour, molasses, leaf litter, brown charcoal, and water. Mountain microorganisms most common ly serve as compost accelerators (Campo Martinez et al., 2016). In Monteverde, Costa Rica, and other similarly developed areas, many homeowners and businesses run their gray water through biojardineras or grease trap s, which separate the grease and sediment layers ( producing cleaner water ), or release the water directly into their yards . A few already add EM to their tanks. EM may be able to aid the sanitation of these tanks by breaking down grease layers, increasing sedimentation, reduci ng smell, and decreasing percent Total Dissolved Solids , or TDS , which includes organic matter and inorganic matter (most notably salts ) . Decreasing TDS increases water quality because high levels of TDS cause some organisms to uptake harmful chemicals (Ch apman and McPherson , 2015). EM also influences Dissolved Oxygen (DO), which affects waterways because water with higher %DO supports greater biodiversity and positively influences biogeochemical element cycling (Huang et al, 2017). This study evaluate d the efficacy of EM and MM biological treatment of grey water in Monteverde . To acc omplish this, I tested the ef ficacy of concentrated and diluted EM and MM in
EM and MM Biological Treatment Raby 3 improving the quality of water from four household grey water sources and two commer cial kitchen grey water sources . The study tracked changes in the water through the metrics of surface coverage (grease or colony formation), sedimentation, smell, and total dissolved solids. I assumed that most noteworthy changes in water metrics would occur within a one week evaluation period due to depletion of resources by the microbes . The efficacy of these methods is directly applicable to Monteverde residents and businesses as it may allow them to improve their own water filtering and sanitation systems. Improve d gray water systems would also release less contaminants into streams, mitigating pollution related harm to ecosystem function s such as oxygen cycling. MATERIALS AND METHODS To compare the efficacy of EM and MM, I studied gray water from households and commercial buildings in Monteverde and Cerro Plano in Puntarenas Province, Costa Rica. I collect ed 3 L samples of water from four household grey water sources and two comme rcial grey water sources in Monteverde . I separate d 200 mL samples into cups at the Instituto Monteverde, then added 5 mL of two concentrations of EM and MM (concentrate and 10x dilution) , for a total volume of 205 mL in each cup. Concentrate solutions consisted of EM to water ratios of 1:40 , while dilution cup ratios were 1:409. E ach gro up of treatment and source had three replicates. Additionally, two control cups per source received 5 mL of distilled water in place of EM mix (Table 1 and Figures 1 and 2 ) . Table 1. Treatments and grey water source groups. Source 1 Source 2 Source 3 S our c e 4 Source 5 Source 6 EM Concentrate 3 cups 3 cups 3 cups 3 cups 3 cups 3 cups EM Dilution 3 cups 3 cups 3 cups 3 cups 3 cups 3 cups MM Concentrate 3 cups 3 cups 3 cups 3 cups 3 cups 3 cups MM Dilution 3 cups 3 cups 3 cups 3 cups 3 cups 3 cups Control 2 cups 2 cups 2 cups 2 cups 2 cups 2 cups My ratio of EM to gray water (1:40) was much higher than that recommended by commercial EM producers (such as one part EM per 1,000 parts grey water per month ( www.teraganix.com , 2017)) because the EM in this experiment (made locally by Justin Welch) was likely much less concentrated than industrially produced EM . Additionally, Monteverde residents and companies typically use ratios that are similar to mine in th eir grease trap s ( J. Welch , pers. comm. ) . The cups had limited access to oxygen or sunlight (removal of cup covers once daily to record water metrics inevitably introduced oxygen ) because this mimicked the waste water environments likely to benefit from EM (most notably grease trap s).
EM and MM Biological Treatment Raby 4 Figur es 1 and 2: Experimental setup in the Fox Maple Room at the Instituto Monteverde.
EM and MM Biological Treatment Raby 5 After setting up the experiment, I recorded the metrics of percent water surface coverage , sedimentation surface area, sediment layering , smell, total dissolved solids (%TDS) , dissolved oxygen (%DO) , and pH . I found %TDS , %DO , and pH values using a YSI Water Sampling Device. I tested the changes in water metrics in the cups once daily for seve n days (22 November 2017 28 November 2017) . I visually approximated percent surface coverage (grease, colonies, or other material) , sedimentation surface area, and layer formation of each cup . I defined a layer as sedimentation that covered 100% of the cup bottom and was at least 2 mm thick. A significant decrease in grease and %TDS , and increase in sedimentation/layering in comparison to the control cups would indicate that the EM had success fu lly facilitated removal of contaminants from the waste water. The extent to which EM can improve smell will help establish its worth as a water treatment, as people are more willing to adopt changes which increase the pleasantness of their grey water sys tems . I measure d smell using a personalized index with four levels: (1) unbearable (prompted gag reflex) , (2) unpleasant, (3) undetectable /neutral , and (4) pleasant. I ran an ANOVA to evaluate the significance of the percent change in %TDS from day one t o day seven within each treatment group. To evaluate whether surface coverage and sediment ation developed significantly from day one to day seven , I evaluated changes in these metrics with a paired t test. RESULTS EM concentrate produced the best smell and highest sedimentation. All EM and MM treatments had signif icantly lower %TDS than the control, but the control had the lowest surface coverage. Percent DO and pH were not constructive metrics due to microbial use of DO and the high acidity of EM and MM solutions . Surface Coverage Almost all source/treatment groups showed increases in surface cover from day one to day seven, although this increase varied in uniformity and in tensity by source and treatment. T he control groups sh owed the least increase , and EM concentrate groups ended with the highest combined surface cover ( Figure 3 ). This surface cover represented both grease and colony formation, as by day seven , 10 out of 30 groups contained visible white surface colonies. The control surface cover did not yield a significant difference from day one to day seven, but all four treatment groups produced highly significant differences . (Table 2 ).
EM and MM Biological Treatment Raby 6 Figure 3 . Differences in percent surface cover from day 1 to day 7 for all treatments a. Control . b. EM Concentrate .c. EM Dilution . d. MM Concentrate . e. MM Dilution . 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Surface Coverage a Control Day 1 Control Day 7 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Surface Coverage b EM Concentrate Day 1 EM Concentrate Day 7 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Surface Coverage c EM Dilution Day 1 EM Dilution Day 7 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Surface Coverage d MM Concentrate Day 1 MM Concentrate Day 7 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Surface Coverage e MM Dilution Day One MM Dilution Day 7
EM and MM Biological Treatment Raby 7 In Figure 3, Grey bars represent percentages on day one, while black bars represent percentages on day seven. On average, each group increased in surface cover by day seven. Table 2 . Treatment, t value, and p value for s ignificance of surface c over change per treatment from day one to day seven .The change in surface cover in control groups w as not significant. Sedimentation and Layering Similarly to surface coverage, sedimentation increased in most (25 of 30) groups. Control groups produced the least sedimentation, followed by MM dilution groups. EM concentrate showed the greatest and most consistent sedimentation (followed by MM concentrate) , and also l ed to the most layer formation ( Figure 4 ) . All treatments and control cups accumulated significant amounts of se diment by day seven as compared to day one (Table 3 ). 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Sedimentation Surface Area a Control Sedimentation Day 1 Control Sedimentation Day 7 -20 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Sedimentation Surface Area b EM Sedimentation Day 1 EM Sedimentation Day 7 Treatment t 17 p EM Concentrate 4.23 < 0.0001 EM Dilution 5.24 < 0.0001 MM Concentrate 4.43 0.0004 MM Dilution 3.82 0.0014
EM and MM Biological Treatment Raby 8 Figure 4. Differences in sedimentation surface area for each treatment from day 1 to day 7 for all treatments . a. Control . b. EM Concentrate .c. EM Dilution . d. MM Concentrate . e. MM Dilution . Grey bars represent percentages on day one, while black bars represent percentages on day seven . Sedimentation that formed a layer (> 2 mm) is represented as 110% sedimentation. On average, each group increased in sedimentation by day seven. Table 3 . Treatment, t value, and p value for s ignificance of sedimentation change per group from day one to day seven . Changes in all groups were significant. Treatment t 17 p Control 4.78 0.0006 EM Concentrate 8.61 < 0.0001 EM Dilution 3.64 0.0020 MM Concentrate 2.40 0.0279 MM Dilution 3.76 0.0016 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Sedimentation Surface Area c EM Sedimentation Day 1 EM Sedimentation Day 7 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Sedimentation Surface Area d MM Sedimentation Day 1 MM Sedimentation Day 7 0 20 40 60 80 100 120 Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Percent Sediment Surface Area e MM Sedimentation Day 1 MM Sedimentation Day 7
EM and MM Biological Treatment Raby 9 Smell For most sources, groups with EM concentrate ranked highest on the index for the most days , followed by MM concentrate. Control ranked lowest on the most days ( Figure 5 ) . 1 1.5 2 2.5 3 3.5 4 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Smell Index a Control EM1 EM2 MM1 MM2 1 1.5 2 2.5 3 3.5 4 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Smell Index b Control EM1 EM2 MM1 MM2 1 1.5 2 2.5 3 3.5 4 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Smell Index c Control EM1 EM2 MM1 MM2 1 1.5 2 2.5 3 3.5 4 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Smell Index d Control EM1 EM2 MM1 MM2
EM and MM Biological Treatment Raby 10 Figure 5. G raphs of source smell over time. a. Source 1 b. Source 2 c. Source 3 d. Source 4 e. Source 5. f .Source 6. The y axis values are f rom a personalized smell index : (1) unbearable (prompted gag reflex), (2) unpleasant, (3) undetectable/neutral, and (4) pleasant. Total Dissolved Solids All four treatments prompted a significant reduction in %TDS compared to the control. Differences between treatment groups were not significant. Figure 6 . Average percent decrease from day one to day seven in %TDS by treatment or control group . Different letters ( a and b ) denote significant differences (Figure 17, F (4, 79) = 5.6, p < .0005) . pH The changes in pH over time were not significant . Values ranged from 4.5 6, with the control group having the highest average reading and the MM concentrate group typically producing the lowest reading . EM concentrate solutions changed the most, moving from 5.5 to 4.5. 1 1.5 2 2.5 3 3.5 4 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Smell Index e Control EM1 EM2 MM1 MM2 1 1.5 2 2.5 3 3.5 4 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Smell Index f Control EM1 EM2 MM1 MM2 a b b b b -0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 Average Percent Change in %TDS Control EM Concentrate EM Dilution MM Concentrate MM Dilution
EM and MM Biological Treatment Raby 11 Figure 7 . Average pH of control and treatment group s over time. Each value is an average of pH values for a given day within a treatment or control group containing grey water from each source. Percent Dissolved Oxygen Average %DO decreased gradually in each treatment group. MM dilution groups decreased the most, falling an average of 17%, while the control group decreased the least, falling five percent . The control group also maintained the highest %DO for five of seven days. Figure 8 . Average %DO of all grey water sources in a treatment group over time. Each value is an average of %DO v alues for a given day within a treatment or control group containing water from each grey water source. 4 4.5 5 5.5 6 6.5 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 pH Day Control EM Concentrate EM Dilution MM Concentrate MM Dilution 60 65 70 75 80 85 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Percent Dissolved Oxygen Day Control EM Concentrate EM Dilution MM Concentrate MM Dilution
EM and MM Biological Treatment Raby 12 DISCUSSION Surface Coverage Surface cover increased in the vast majority of study groups, decreasing in only 6.6%, or two of 30 source/treatment groups , which I did not predict . Control groups showed the least increase (Figure 3 ). Some surface m aterial was grease, although 10 out of 30 groups eventually showed visible evidence of bacterial colony formation. Microbes in EM (around 80 species) effectively break down organic matter (Zakaria et al., 2010). Therefore, s l ight increases in treatment group surface cover (compared to control groups) likely stem more from microbial growth than gre ase accumulation, and do not represent a substantial drawback to adding EM and MM in grey water systems. Future studies could classify surface microbes in similar systems or analyze the chemical makeup of surfac e accumulate in order to determine what perce nt is attributable to grease. Error in data collection for this metric may have stemmed from surface accumulate remaining on the YSI probe during its removal, causing artificial decrease in surface cover. I visually estimated the surface cover, which may have caused additional error. Although my visual approximation was not quantitative in absolute terms and may have introduced some systematic error, I believe that the relative scale is useful. Sedimentation and Layering Sedimentation increased in 25 of 30 groups after seven days, with control groups producing the least average sedimentation and E M producing the most (Fig ure 4 ). All treatments and the control accumulated significantly higher averages of sediment after seven days (Table 3 ). EM encourages sed imentation due to lactic acid bacteria (including Lactobacillus plantarum , Lactobacillus casei and Streptoccus lactis ) , which secrete organic acids and other antioxidants. These substances aid in solid liquid separation (Zakaria et al., 2010). Additionally, EM influence s the cycling of nitrogen and phosphorus, which contribute significant mass to sediment (Wididana). As in surface cover evaluation , visual approximation of sedimentation and layering may have caused slight error. Smell Groups with EM concentrate ranked highest (best smelling) on the smell index for the most days as compared to other treatment s for a given grey water source. MM concentrate ranked second best, and control groups smelled the worst ( Figure 5 ) . Odor reduction was one of original purposes ( management of odors caused by ammonia, hydrogen sulfide, and methane ) (Zakaria et al., 2010). However, both EM and MM contain molasses, which smells sweet, and may have contributed to better sme lling solutions more than microbes did. Therefore, the dilution treatment groups likely smelled worse than the concentration treatment groups partly because they contained less molasses. Likewise, absence of molasses in the control groups may have caused t heir less pleasant smell.
EM and MM Biological Treatment Raby 13 Total Dissolved Solids All four treatment groups lowered %TDS significantly, as compared to the control group, although none of the treatment groups differed significantly from each other (Figure 6 ). Decreasing TDS increases water quality because high levels of TDS cause some organisms to uptake harmful chemicals (Chapman and McPherson, 2015). EM is especially effective at reducing dissolved nitrogen and phosphorus content ( reducing %TDS and increasing water quality), possibly due to microbial uptake of these elements (Okuda and Higa). Some EM microbe species can even detoxify and/or precipitate metals (Monica et al., 2010). MM may have performed equally well as EM under this metric because MM microbes are selected largely for their ability to decompose organic matter (making them better suited for agricultural purposes such as compost acceleration ) (Castellano et al., 2015) . Furthermore , MM also fix nitrogen (Garnett, 2015), and therefore help lower levels of ammonium, nit rates and nitrites in water (Campo Martinez et al., 2014). pH The pH measurements did not exhibit significant variation over time (Figure 7 ) . In most natural systems, n eutral pH correlates with higher water quality and better ecosystem function (Mosley et al., 2014). However, due to the acidity of the EM solutions, changes in pH do not accurately reflect EM efficacy. Concentrate EM mixtures have low pH values (around 3.5 4 (Zakaria et al., 2010)), so the initial acidification caused by addition of EM may have caused low pH for the remainder of the experiment. EM can still prove effective in initially basic systems by lowering pH to more neutral conditions (Okuda and Higa). Percent Dissolved Oxygen Average %DO decreased gradually in each treatment group (Figure 8 ) . Percent DO did not serve as a quality metric of EM efficacy, as microbial metabolisms uptake oxygen , so EM would reduce %DO in a shor t term closed environment (Park, et al., 2016 ). Instead, DO flux monitored the relative activity of the EM over time, and suggested that the microbes wer e active until the last day. Conclusion As the EM concentrate treatment group lowered %TDS and scored highest in the sedimentation and smell metrics , I would recommend addition of similar ratios of EM to grease trap s, biojardineras and other grey water filtration systems. EM has the potential to improve grey water sedimentation, smell, and %TDS in these systems, making them more sanitary and pleasant and improving the quality of life of those who use them. ACKNOWLEDGEMENTS I w ould firstly like to thank Sof Ã a Arce Flores for her constant support and excellent mentorship. She was there to help from my initial proposal submission through the final data analysis and presentation . Frank Joyce also offered thoughtful input on my proposal. Justin Welch provided the EM and MM (from his own local stocks) and contributed essential knowledge on water metrics and experimental design. Andr Ã© s Camacho generously offered his time to drive myself and other students to Life Monteverde farm. Instituto Monteverde allowed me to set up my experiment in the Fox Maple Room . Brianne Nguyen offered thoughtful and
EM and MM Biological Treatment Raby 14 thorough critiques on the initial version of this paper. I am also grateful to the following groups , which allowed me to collect grey water from their properties: Eladio Cruz Leiton, Familia Ledezma Brenes, Sof Ã a Arce Flores and Justin Welch, Katy VanDusen, Instituto Monteverde, and EstaciÃ³n BiolÃ³gica Monteverde . LITERATURE CITED Campo Martinez, ADP. , Acosta Sanchez, RL., Moralez Velasco, S., and Prado, FA., 2014. Evaluation of Mountain Microorganisms (MM) in the Production of C hard on the Plateau of Popayan. BiotecnologÃa en el Sector Agropecuario y Agroindustrial 12: 79 87. Castellano, K., Nikolaki, V., Picchione, K., Sullivan, K., 2015. Evaluating Impacts of Costa Worcester Polytechnic Institute. Chapman, PM. and McPherson, CA., 2015. Development of a Total Dissolved Solids (TDS) Chronic Effec ts Benchmark for a Northern Canadian Lake. Integrated Environmental Assessment and Management 12: 371 379. Garnett, IFI., 2015. Protection and Sustainable Use of the Selva Maya Regional Programme. Deutsche Gesellschaft fur, Santa Elena, Perten, Guatemala. Monica S . , Karthik L . , Mythili S . , Sathiavelu A ., 2011. Formulation of Effective Microbial Consortia and its Application for Sewage Treatment. J ournal of Microbial and Biochemical Technology 3: 51 55. Mosley, L., Zammit, B., Jolley, AM., Barnett, L., Fitzpatrick, R., 2014. Monitoring and assessment of surface water acidification following rewetting of oxidized acid sulfate soils. Environmental Monitoring and Assessment 186: 1 18. Huang, J., Yin, H., Chapra, SC., Zhou, Q., 2017. Modelling Dissolved Oxyg en Depression in an Urban River in China. Water 9: 1 19. Okuda, A., and Higa, T. Purification of Waste Water with Effective Microorganisms and its Utilization in Agriculture. University of Ryukyus, Okinawa, Japan. Park, GS. , Khan, AR., Kwak, Y., Hong, SJ. , Jung, BK., Ullah, I., Kim, JG., Shin, JH., 2016. An Improved Effective Microorganism (em) Soil Ball making Method for Water Quality Restoration. Environmental science and pollution research international 23: 1100 1107. Sheffield, CW., 1968. Water Hyacin th for Nutrient Removal, Orlando, Florida: Orange County Water Conservation Department. Wang , Z., Zhang Z . , Zhang J . , Zhang Y . , Liu H . , Yan S. , 2012. Large scale utilization of water hyacinth for nutrient removal in Lake Dianchi in China: The effects on the water quality, macrozoobenthos and zooplankton . Chemosphere 89: 1255 1261. Wenzel, WW. Rhizosphere processes and management in plant assisted bioremediation (phytoremediation) of soils . Plant and Soil 321: 385 408. Wididana, GN. Preliminary Experiment of EM Technology on Waste Water Treatment . Indonesian Kyusei Nature Farming Society , Indonesia.
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