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Journal articles on the topic 'Biochemical oxygen demand'

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Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Morris, K., K. Catterall, H. Zhao, N. Pasco, and R. John. "Ferricyanide mediated biochemical oxygen demand–development of a rapid biochemical oxygen demand assay." Analytica Chimica Acta 442, no. 1 (August 2001): 129–39. http://dx.doi.org/10.1016/s0003-2670(01)01133-3.

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2

Pasco, N., K. Baronian, C. Jeffries, and J. Hay. "Biochemical mediator demand - a novel rapid alternative for measuring biochemical oxygen demand." Applied Microbiology and Biotechnology 53, no. 5 (May 15, 2000): 613–18. http://dx.doi.org/10.1007/s002530051666.

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3

Schreiber, J. D., and E. E. Neumaier. "Biochemical Oxygen Demand of Agricultural Runoff." Journal of Environmental Quality 16, no. 1 (January 1987): 6–10. http://dx.doi.org/10.2134/jeq1987.00472425001600010002x.

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4

Yang, Z., H. Suzuki, S. Sasaki, and I. Karube. "Disposable sensor for biochemical oxygen demand." Applied Microbiology and Biotechnology 46, no. 1 (August 20, 1996): 10–14. http://dx.doi.org/10.1007/s002530050776.

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5

Adrian, Donald Dean, Emerald M. Roider, and Thomas G. Sanders. "Oxygen Sag Models for Multiorder Biochemical Oxygen Demand Reactions." Journal of Environmental Engineering 130, no. 7 (July 2004): 784–91. http://dx.doi.org/10.1061/(asce)0733-9372(2004)130:7(784).

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6

Bristow, J. L. "Biochemical Oxygen Demand by a Simplified Procedure." Water Science and Technology 21, no. 2 (February 1, 1989): 177–82. http://dx.doi.org/10.2166/wst.1989.0046.

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Comparative tests made in 1979 and 1980 have shown that the Klein & Gibbs mathematical calculation of BOD5 can give equivalent results to those obtained using the APHA Standard Method 16th Edition Section 507. This method corrects for dilution water blank and seed. It can give just as consistent results as the “Standard Method”. Both methods can be inaccurate when interfering substances are present. Aging of dilution water and aeration of samples with less than 5 mg/L DO have improved the consistency of the results. Halving of the incubation volume has had no effect on the accuracy of results.

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7

ZHAO, Limin, Jianbo JIA, and Changyu LIU. "Application of Rapid Biochemical Oxygen Demand Biosensor." Acta Agronomica Sinica 29, no. 7 (2012): 819. http://dx.doi.org/10.3724/sp.j.1095.2012.00493.

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8

Nakamura, Hideaki, Yuta Abe, Rui Koizumi, Kyota Suzuki, Yotaro Mogi, Takumi Hirayama, and Isao Karube. "A chemiluminescence biochemical oxygen demand measuring method." Analytica Chimica Acta 602, no. 1 (October 2007): 94–100. http://dx.doi.org/10.1016/j.aca.2007.08.050.

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9

Wu, Hui Xiu, Cui Ling Jiang, and Zhong Du. "Long-Term Trends of Water Quality in Upstream of Daling River in China." Advanced Materials Research 599 (November 2012): 673–77. http://dx.doi.org/10.4028/www.scientific.net/amr.599.673.

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Long-term trends and spatial patterns of water quality at 5 stations in the upstream of the Daling River basin of North China were examined for 5 parameters—pH, suspended sediment (SS), dissolved oxygen (DO), permanganate demand (CODMn) and biochemical oxygen demand (BOD5). Analysis determined the trends of parameters of each station between 1987 and 2007. The variations in permanganate demand and biochemical oxygen demand showed increasing trends and the variations in dissolved oxygen were decrease in 1990s. Multi-year average values of permanganate demand and dissolved oxygen in Chaoyang station and Jianping station were 2.8 mg/L, 37.6 mg/L and 9.6 mg/L, 6.1 mg/L, respectively. The parameter characteristics of water quality in flood and dry season showed significant heterogeneity at main stream and tributary. Correlations between parameters were analyzed using a regression analysis method. The correlations of each parameter determined there were linear negative correlation between dissolved oxygen and permanganate demand, dissolved oxygen and biochemical oxygen demand at Habaqi station, Dachengzi station and Chaoyang station. The permanganate demand and biochemical oxygen demand was significant positive correlation in 3 stations.

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10

Zhu, Jun-Jie, Lulu Kang, and Paul R. Anderson. "Predicting influent biochemical oxygen demand: Balancing energy demand and risk management." Water Research 128 (January 2018): 304–13. http://dx.doi.org/10.1016/j.watres.2017.10.053.

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11

Kamarudin, Mohd Khairul Amri, Noorjima Abd Wahab, Siti Nor Aisyah Md Bati, Mohd Ekhwab Toriman, Ahman Shakir Mohd Saudi, Roslan Umar, and Sunardi. "Seasonal Variation on Dissolved Oxygen, Biochemical Oxygen Demand and Chemical Oxygen Demand in Terengganu River Basin, Malaysia." Journal of Environmental Science and Management 23, no. 2 (December 31, 2020): 1–7. http://dx.doi.org/10.47125/jesam/2020_2/01.

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The rise in human population densities and the pace of development had intensified the depletion of the water quality. This study aimed to analyze the concentration of dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD) during wet season and dry season at Terengganu River in 2016. A total of 29 monitoring stations in the study area were selected and three water quality parameters were analyzed using descriptive statistics and the correlation matrix methods. The DO ranged from 2.11 to 8.07 mg L-1, COD from 2.24 to 39 mg L-1 and BOD from 0.67 to 6.52 mg L-1 for the wet season while in dry season, DO ranged from 2.30 to 6.05 mg L-1, COD from 1.9 to 20.48 mg L-1 and BOD from 0.04 to 13.99 mg L-1. Spearman’s correlation test shows there was a weak correlation between DO and COD during wet season, while in the dry season, there was a weak correlation between DO-COD and DO-BOD. This study also found out that urbanization and anthropogenic activities in the area can gave the more impact towards seasons and water quality deterioration in Terengganu River, Malaysia.

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12

TANAKA, Yoshiaki. "Control of biochemical sediment oxygen demand by toxicants." Japan journal of water pollution research 8, no. 12 (1985): 826–33. http://dx.doi.org/10.2965/jswe1978.8.826.

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13

Safarov, A. M., R. M. Khatmullina, V. I. Safarova, A. R. Mukhamatdinova, V. Z. Latypova, G. F. Shaidulina, and A. A. Kovbota. "Effect of Transition Elements on Biochemical Oxygen Demand." Journal of Analytical Chemistry 73, no. 8 (July 31, 2018): 771–76. http://dx.doi.org/10.1134/s1061934818080087.

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14

Vigiak, Olga, Bruna Grizzetti, Angel Udias-Moinelo, Michela Zanni, Chiara Dorati, Fayçal Bouraoui, and Alberto Pistocchi. "Predicting biochemical oxygen demand in European freshwater bodies." Science of The Total Environment 666 (May 2019): 1089–105. http://dx.doi.org/10.1016/j.scitotenv.2019.02.252.

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15

Fulazzaky, Mohamad Ali. "Measurement of biochemical oxygen demand of the leachates." Environmental Monitoring and Assessment 185, no. 6 (September 23, 2012): 4721–34. http://dx.doi.org/10.1007/s10661-012-2899-z.

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16

Praet, E., V. Reuter, T. Gaillard, and J. L. Vasel. "Bioreactors and biomembranes for biochemical oxygen demand estimation." TrAC Trends in Analytical Chemistry 14, no. 7 (August 1995): 371–78. http://dx.doi.org/10.1016/0165-9936(95)97066-a.

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17

Mason, Ian G., Robert I. McLachlan, and Daniel T. Gérard. "A double exponential model for biochemical oxygen demand." Bioresource Technology 97, no. 2 (January 2006): 273–82. http://dx.doi.org/10.1016/j.biortech.2005.02.042.

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18

Udeigwe, Theophilus K., and Jim J. Wang. "Biochemical Oxygen Demand Relationships in Typical Agricultural Effluents." Water, Air, & Soil Pollution 213, no. 1-4 (March 17, 2010): 237–49. http://dx.doi.org/10.1007/s11270-010-0381-5.

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19

Jung, Jongtai, Sam Sofer, and Fayaz Lakhwala. "Towards an on-line biochemical oxygen demand analyser." Biotechnology Techniques 9, no. 4 (April 1995): 289–94. http://dx.doi.org/10.1007/bf00151577.

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20

Burn, Donald H., and Edward A. McBean. "Linear stochastic optimization applied to biochemical oxygen demand – dissolved oxygen modelling." Canadian Journal of Civil Engineering 13, no. 2 (April 1, 1986): 249–54. http://dx.doi.org/10.1139/l86-033.

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A methodology for reflecting stochastic considerations in an optimization model is presented. The technique, which uses chance-constrained programming, is applied to a water quality management problem wherein concern is with the interaction between biochemical oxygen demand (BOD) and the dissolved oxygen (DO) concentration in a river. The uncertainty in the problem is considered to be embodied in transfer coefficients for which a lognormal distribution is derived from moment estimates provided by first-order uncertainty analysis. The appropriateness of the lognormal distribution is confirmed by results from a simulation modelling exercise. Key words: water quality, optimization, uncertainty, mathematical modelling.

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21

Chafia, Laouar, Ayadi Abdelhamid, and Hafdallah Abdelhak. "Optimal Control of a Partially Known Coupled System of BOD and DO." International Journal of Analysis and Applications 19, no. 6 (November 25, 2021): 984–96. http://dx.doi.org/10.28924/2291-8639-19-2021-984.

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The work presented in this paper is concerned with the organic pollution problem and water quality valuation. Biochemical oxygen demand has been used to evaluate the quality of water. If organic matter is present the dissolved oxygen is consumed. This article considers an optimal control problem of coupled system with missing initial conditions, which presents the relation between the biochemical oxygen demand and the dissolved oxygen. The main objective is to control the concentration of dissolved oxygen using the information given in the biochemical oxygen demand equation. The main tool used to characterize the optimal control of the investigate system under the Pareto control formulation.

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22

AMARASINGHE, H. ANUSHA UDENI, HD GUNAWARDENA, and YN AMARAMALI JAYATUNGA. "CORRELATION BETWEEN BIOCHEMICAL OXYGEN DEMAND (BOD) AND CHEMICAL OXYGEN DEMAND (COD) FOR DIFFERENT INDUSTRIAL WASTE WATERS." Journal of the National Science Foundation of Sri Lanka 21, no. 2 (December 29, 1993): 259. http://dx.doi.org/10.4038/jnsfsr.v21i2.8110.

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23

Singh, Urvasini, Vandana Sharma, Shruti Bhandari, Jayashri Vajpai, and Sunita Kumbhat. "Absorbance Based Model for Determination of Biochemical Oxygen Demand." British Journal of Applied Science & Technology 4, no. 31 (January 10, 2014): 4408–19. http://dx.doi.org/10.9734/bjast/2014/12372.

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24

Logan, Bruce E., and Rabindranath Patnaik. "A gas chromatographic-based headspace biochemical oxygen demand test." Water Environment Research 69, no. 2 (March 1997): 206–14. http://dx.doi.org/10.2175/106143097x125362.

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25

Ghosh, Sourav, Monit Paul, Anusree Raha, Prosenjit Mukherjee, Anindya Bagchi, and Abhik Si. "Statistical evaluation of biochemical oxygen demand of river water." Advance Pharmaceutical Journal 3, no. 4 (November 2018): 118–20. http://dx.doi.org/10.31024/apj.2018.3.4.2.

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26

Jouanneau, S., L. Recoules, M. J. Durand, A. Boukabache, V. Picot, Y. Primault, A. Lakel, M. Sengelin, B. Barillon, and G. Thouand. "Methods for assessing biochemical oxygen demand (BOD): A review." Water Research 49 (February 2014): 62–82. http://dx.doi.org/10.1016/j.watres.2013.10.066.

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27

Mittal, S. K., and R. K. Ratra. "Toxic effect of metal ions on biochemical oxygen demand." Water Research 34, no. 1 (January 2000): 147–52. http://dx.doi.org/10.1016/s0043-1354(99)00104-9.

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28

Chee, Gab-Joo, Yoko Nomura, and Isao Karube. "Biosensor for the estimation of low biochemical oxygen demand." Analytica Chimica Acta 379, no. 1-2 (January 1999): 185–91. http://dx.doi.org/10.1016/s0003-2670(98)00680-1.

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29

Kim, Mal-Nam, and Hee-Sun Kwon. "Biochemical oxygen demand sensor using Serratia marcescens LSY 4." Biosensors and Bioelectronics 14, no. 1 (January 1999): 1–7. http://dx.doi.org/10.1016/s0956-5663(98)00107-9.

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30

Al-Homoud, Amer, Miki Hondzo, and Timothy LaPara. "Fluid Dynamics Impact on Bacterial Physiology: Biochemical Oxygen Demand." Journal of Environmental Engineering 133, no. 2 (February 2007): 226–36. http://dx.doi.org/10.1061/(asce)0733-9372(2007)133:2(226).

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31

Borys, Alexander, John M. Hake, and Donald M. D. Gabb. "EVALUATION OF AN ONLINE BIOCHEMICAL OXYGEN DEMAND ANALYZER FOR OXYGEN PRODUCTION CONTROL." Proceedings of the Water Environment Federation 2002, no. 16 (January 1, 2002): 378–96. http://dx.doi.org/10.2175/193864702784247233.

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32

Tan, T. C., F. Li, K. G. Neoh, and Y. K. Lee. "Microbial membrane-modified dissolved oxygen probe for rapid biochemical oxygen demand measurement." Sensors and Actuators B: Chemical 8, no. 2 (May 1992): 167–72. http://dx.doi.org/10.1016/0925-4005(92)80175-w.

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33

Mamedov, B. A. "Evaluation of Oxygen Sag Equation for Second-Order Biochemical Oxygen Demand Decay." Journal of Environmental Engineering 132, no. 12 (December 2006): 1606–8. http://dx.doi.org/10.1061/(asce)0733-9372(2006)132:12(1606).

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34

Khorsandi, Hassan, Rahimeh Alizadeh, Horiyeh Tosinejad, and Hadi Porghaffar. "Analysis of nitrogenous and algal oxygen demand in effluent from a system of aerated lagoons followed by polishing pond." Water Science and Technology 70, no. 1 (April 22, 2014): 95–101. http://dx.doi.org/10.2166/wst.2014.194.

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In this descriptive-analytical study, nitrogenous and algal oxygen demand were assessed for effluent from a system of facultative partially mixed lagoons followed by the polishing pond using 120 grab samples over 1 year. Filtered and non-filtered samples of polishing pond effluent were tested in the presence and absence of a nitrification inhibitor. Effective factors, including 5-day biochemical and chemical oxygen demand (BOD and COD), total suspended solids (TSS), dissolved oxygen, chlorophyll A, and temperature, were measured using standard methods for water and wastewater tests. The results were analyzed using repeated measures analysis of variance with SPSS version 16. Findings show that the annual mean of the total 5-day BOD in the effluent from the polishing pond consisted of 44.92% as the algal carbonaceous biochemical oxygen demand (CBOD), 43.61% as the nitrogenous biochemical oxygen demand (NBOD), and 11.47% as the soluble CBOD. According to this study, the annual mean ratios of algal COD and 5-day algal CBOD to TSS were 0.8 and 0.37, respectively. As the results demonstrate, undertaking quality evaluation of the final effluent from the lagoons without considering nitrogenous and algal oxygen demand would undermine effluent quality assessment and interpretation of the performance of the wastewater treatment plant.

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35

Norizan, A. N., Z. Z. Abdul Rahm, and F. M. Nurul. "Specialization of Biochemical Oxygen Demand for Surface Water and Wastewater." Journal of Applied Sciences 11, no. 13 (June 15, 2011): 2460–63. http://dx.doi.org/10.3923/jas.2011.2460.2463.

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36

Hayashi, Ryuzo. "Continuous measurement of Biochemical Oxygen Demand by microbial BODs biosensor." JAPAN TAPPI JOURNAL 58, no. 10 (2004): 1345–49. http://dx.doi.org/10.2524/jtappij.58.1345.

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37

Liu, Ling, Lu Bai, Dengbin Yu, Junfeng Zhai, and Shaojun Dong. "Biochemical oxygen demand measurement by mediator method in flow system." Talanta 138 (June 2015): 36–39. http://dx.doi.org/10.1016/j.talanta.2015.02.001.

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38

Kashem, Md Abul, Masayasu Suzuki, Kazuki Kimoto, and Yasunori Iribe. "An optical biochemical oxygen demand biosensor chip for environmental monitoring." Sensors and Actuators B: Chemical 221 (December 2015): 1594–600. http://dx.doi.org/10.1016/j.snb.2015.07.119.

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39

Liu, Jing, Lovisa Björnsson, and Bo Mattiasson. "Immobilised activated sludge based biosensor for biochemical oxygen demand measurement." Biosensors and Bioelectronics 14, no. 12 (February 2000): 883–93. http://dx.doi.org/10.1016/s0956-5663(99)00064-0.

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40

Boyd, Claude E., and Amit Gross. "Biochemical Oxygen Demand in Channel Catfish Ictalurus punctatus Pond Waters." Journal of the World Aquaculture Society 30, no. 3 (September 1999): 349–56. http://dx.doi.org/10.1111/j.1749-7345.1999.tb00685.x.

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41

Rodríguez, Manuel Gil. "Calculus of the biochemical oxygen demand of effluents with xenobiotics." Journal of Environmental Science and Health, Part A 34, no. 4 (May 1999): 879–97. http://dx.doi.org/10.1080/10934529909376871.

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42

Ahmed, A. A. Masrur. "Prediction of dissolved oxygen in Surma River by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks (ANNs)." Journal of King Saud University - Engineering Sciences 29, no. 2 (April 2017): 151–58. http://dx.doi.org/10.1016/j.jksues.2014.05.001.

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43

Ladislav, Kolář, Ledvina Rostislav, Kužel Stanislav, and Štindl František Klimeš and Pavel. "Soil Organic Matter and its Stability in Aerobic and Anaerobic Conditions." Soil and Water Research 1, No. 2 (January 7, 2013): 57–64. http://dx.doi.org/10.17221/6506-swr.

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In eight samples of organic and organomineral surface horizons we studied the stability of soil organic matter in aerobic and anaerobic conditions expressed by the rate constant of its biochemical oxidation, total biochemical oxygen demand, substrate production of methane and degradability in anaerobic conditions. In the eight very different samples no relationship was found between aerobic and anaerobic stability of their organic matter; nor was the expected relationship between total biochemical oxygen demand and “active carbon” Chws proved. Methods of determination are described.

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44

Y.W., Oon, Law P.L., Ting S.N., and Tang F.E. "A 3-Stage Treatment System For Domestic Wastewater: Part II. Performance Evaluation." Journal of Civil Engineering, Science and Technology 4, no. 1 (March 1, 2013): 26–33. http://dx.doi.org/10.33736/jcest.105.2013.

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A 3-stage micro-scale wastewater treatment system that consisted of 1) a spiral-framed human hair-based filter, 2) a plastic medium mixed flow biotower, and 3) a free surface water wetland system filled with Pistia Stratiotes (water lettuce) operating in series was recently developed and performance tests were conducted. Performance tests were carried out to determine the efficiencies of the system for removal of physically emulsified and free oils, organic matters such as biochemical oxygen demand, ammoniacal-nitrogen, suspended solids,and nutrients such as nitrogen, phosphorous, and potassium from semi-synthetic wastewaters. From this study, it was found that the human hair-based filter could retain approximately 73.5% of physically emulsified oils, while the mixed flow biotower was capable of reducing approximately 35.0% biochemical oxygen demand, 57.4% ammoniacal-nitrogen, 51.8% nitrogen, 13.4% phosphorus, 21.8% potassium, and 21.9% reduction in turbidity. The Pistia Stratiotes-based free surface water wetland was found to remove approximately 24.1% biochemical oxygen demand, 30.6% ammoniacal-nitrogen, 38.0% nitrogen, 41.5% phosphorus, 46.7% potassium and 31.7% reduction in turbidity. When the mixed flow biotower and free surface water wetland system were to operate in series, the combined removal efficiencies were approximately 59.2% for biochemical oxygen demand, 87.9% for ammoniacal-nitrogen, 90.6% for nitrogen, 54.9% for phosphorus, 68.5% for potassium, and 59.0% reduction in turbidity. Experimental data also showed that daily uptake rates (mg/kg-day) of organics and nutrients by per kilogram of Pistia Stratiotes were approximately 1,731 mg for biochemical oxygen demand, 1,015 mg for ammoniacal-nitrogen, 1,206 mg for nitrogen, 1,468 mg for phosphorus, and 5,431 mg for potassium.

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45

Orhon, D., Ö. Karahan-Gül, S. l. Sözen, and N. Artan. "Scientific basis for the design of small activated sludge systems." Water Science and Technology 48, no. 11-12 (December 1, 2004): 15–22. http://dx.doi.org/10.2166/wst.2004.0793.

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The study presents an evaluation of the oxygen requirement and sludge production, modeled in terms of fundamental processes reflecting different biochemical transformations in activated sludge systems. Modern modeling concepts define substrate utilization and endogenous decay as major processes requiring final electron acceptors. Substrate and sludge components may be defined in terms of different parameters. Chemical oxygen demand (COD) and biochemical oxygen demand (BOD5) are the traditional substrate parameters. COD also serves to define biomass along with volatile suspended solids (VSS) parameter. Estimation of oxygen requirement and sludge production for aerobic activated sludge systems covering basic biochemical processes are defined for different substrate and sludge parameters, considering that each calculation is associated with a different stoichiometry on the basis of a selected parameter set. The German regulations are examined and the biochemical bases of the coefficients in the regulatory expressions are set in terms of fundamental model constants.

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46

Edori, E. S., O. S. Edori, and I. B. Nwoke. "Degradability and Organic Strength of Gross Organic Pollutants In Surface Water of Mini Whuo Stream Obio/Akpor, Rivers State, Nigeria." Journal of Physical Science and Environmental Studies 8, no. 2 (December 25, 2022): 15–20. http://dx.doi.org/10.36630/jpses_22004.

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Water samples were collected from Mini Whou Stream and analyzed for gross organic pollutants and the results was used to evaluate the organic strength of the Stream. The gross organic pollutants studied were dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD). Dissolved oxygen within the months studied ranged from 5.45±0.15-5.58±0.14mg/L, which were lower than the WHO value for drinking water. Biochemical oxygen demand within the months studied ranged from 36.25±4.47-36.55±3.88mg/L, which was higher than the recommended level for drinking water by WHO. Chemical oxygen within the months studied ranged from 51.82±3.25 – 52.57 mg/L which was above the WHO acceptable level. The organic strength (BOD/COD) of the surface water during the months ranged from 0.69–0.70. The results recorded revealed that the stream was polluted with gross organic pollutants and is therefore not fit for human consumption. The values recorded for organic strength indicated that microbial breakdown of organic matter was very active, which showed that the water of the stream was contaminated with organic pollutants. This should therefore discourage input of organic matter from diffuse sources into the stream. Keywords: Biological oxygen demand, chemical oxygen demand, dissolved oxygen, gross organic pollutants, organic strength

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47

Hasadsri, S., and M. Maleewong. "Finite Element Method for Dissolved Oxygen and Biochemical Oxygen Demand in an Open Channel." Procedia Environmental Sciences 13 (2012): 1019–29. http://dx.doi.org/10.1016/j.proenv.2012.01.095.

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48

Choi, Dong-Ho, Jin-A. Beom, Min-Hyuk Jeung, Woo-Jung Choi, Young-Gu Her, and Kwang-Sik Yoon. "Characteristics of biochemical oxygen demand and chemical oxygen demand export from paddy fields during rainfall and non-rainfall periods." Paddy and Water Environment 17, no. 2 (April 2019): 165–75. http://dx.doi.org/10.1007/s10333-019-00708-3.

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49

Adeniji, Ayodeji Oluwole, Iyabo Oluremi Olabanji, and Ayodele Emmanuel Oluyemi. "Physicochemical Parameters Of Effluents From A Lubricating Oil Company And Metal Analysis Of The Sediment Of The Receiving Stream In Osogbo Osun State, Nigeria." JOURNAL OF ADVANCES IN CHEMISTRY 15, no. 1 (March 12, 2018): 6087–98. http://dx.doi.org/10.24297/jac.v15i1.7100.

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Effluent and its receiving sediment samples were collected on seasonal basis, comprising of three months (August to October, 2014) in the wet season and three months (December 2014 to February 2015) in the dry season. Five sampling points around the lubricating oil company were marked for the study. Physicochemical parameters of the effluent samples such as pH, temperature, conductivity, total dissolve solids were determined in situ. Dissolved oxygen and biochemical oxygen demand were determined by WinklerÂ´s method. Digestion of the sediments was carried out by acid dissolution. The heavy metals (Mn, Ni, Co, Cd and Pb) level was determined using Flame Atomic Absorption Spectrophotometer. The results revealed that the physicochemical parameters ranged between (27.40 to 29.860C) for temperature, pH (6.89 to 7.88), electrical conductivity (92.27 to 292.84Âµs/cm), total dissolve solids, dissolved oxygen (2.58 to 7.01mg/L), biochemical oxygen demand (5.00 to 14.00mg/L) for the sampling periods. The overall total metal was in similar order: Mn > Ni > Co > Cd > Pb for both seasons. Most of the results were within the recommended limit required except for the levels of biochemical oxygen demand which exceeded the recommended value of 10mg/L in dry season by WHO, (2006). Statistically, no significant difference at p â‰¤ 0.05 between the parameters obtained in both seasons. The study concluded that the effluents discharged from the lubricating oil company in osogbo was polluted based on the results of biochemical oxygen demand and the Cd concentrations in the sediment samples.

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Ayala Daza, Rudy Roxana, Palmir Ponte Viera, and Jhonny Valverde Flores. "Reduction of organic and biological pollutants from affluents of the Ancón wastewater treatment plant using microanobubbles of air and graphene [Reducción de contaminantes orgánicos y biológicos de afluentes de la planta de tratamiento de aguas residuales de Ancón utilizando micronanoburbujas de aire y grafeno]." Journal of Nanotechnology 4, no. 1 (December 23, 2020): 1. http://dx.doi.org/10.32829/nanoj.v4i1.198.

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Abstract:

The objective of this research was to reduce the organic and biological load of tributaries of the Ancón Wastewater Treatment Plant using microanobubbles of air and graphene. A preliminary sample of the affluent (3L) was taken, which had an initial concentration of Biochemical Oxygen Demand (BOD5) of 410 mg/L, Chemical Oxygen Demand (COD) of 483 mg/L, Thermotolerant Coliforms of 44,000 NMP/100mL and turbidity of 63.33 NTU. The experimental part was carried out with 03 samples of 20 liters with 03 repetitions with a treatment time of 20, 40 and 60 minutes applying air nanobubbles and 6, 12 and 18 grams of graphene respectively. The results of the treated samples were: 87 mg/L representing 78.8% reduction in Biochemical Oxygen Demand (BOD5), 114 mg/L representing 76.4% reduction in Chemical Oxygen Demand (COD), 2,900 NMP/100mL that represents 93.41% reduction of Thermotolerant Coliforms and 12.4 NTU that represents 80.11% reduction of turbidity.

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