Biological Oxygen Demand Concentrations Research Articles

Assessing environmental awareness activism to river decay and recurring pollution using parallel multiple mediator model

ABSTRACT The decay of rivers coupled with its escalated pollution is a concern worldwide. The present study intends to assess the agony of the riverine people due to the contamination of the Churni River and the transformation of their grievance into environmental activism at individual and community levels for rejuvenating the river and for a secured livelihood. The study observed an enriched concentration of biological oxygen demand, nitrate, and phosphate and a reduced concentration of dissolved oxygen during 2011–2020 due to the release of untreated industrial wastewater, sewage from urban areas, and agricultural runoff into the river. A systematic investigation reveals pollution-induced socio-psychological trauma and community awareness leading to the active involvement of the people in the environmental awareness movement, which was mediated by self-efficacy, self-responsibility, self-identity, and community value. A parallel multiple mediator model was employed, which included 29 parameters for exploring the key-mediated factors for the environmental movement. The model-based results identified that self-responsibility and community-value for upper stretch villages and self-efficacy and community-value for the lower stretch villages are significant mediators of environmental activism. A canonical component analysis predicted socio-demographic factors (e.g. age, dependency ratio female-male ratio, etc.) as intrinsically linked to environmental activism. This study is significant because it reveals how pollution and river degradation affect riverine people. It also clarifies how local grievances turned into environmental activism as a result of the documented socio-psychological trauma and growing community awareness. This study would thus play a pivotal role in understanding the human-nature complex to better planning and river restoration.

Modification and Performance of a Rotating Biological Contactor for the Rectification of Synthetic Auramine O dye Wastewater

The disposal of domestic and industrial wastewater into the drainage/atmosphere without treatment is a major source of pollution that endangers the health of the population and needs to be controlled. Despite long been used as a secondary treatment strategy for wastewater, conventional rotating biological contactor (RBC) suffers from the drawbacks of limited surface area for the growth of biofilms. There are persistent problems of less oxygenation capacity, and inefficient mixing resulting in inadequate mass transfer. To address these issues conventional RBC has been modified in the present study by replacing a bank of discs using a rotating drum. The use of a rotating drum in RBC enhanced the biofilm attachment surface area up to 2.29 m2 (?108.2% higher than conventional RBC), thereby improving the working performance. To prevent the dissolved oxygen as a limiting factor, four small aerators were placed as supplement aeration system in the wastewater collection tank of modified RBC. To prevent the influence of atmospheric temperature on biological process, a blast-proof aquarium glass heater was placed in the tank. For experimental work, a 700 ppm pretreated synthetic solution of Auramine-O dye as wastewater was utilized. A constant level of percentage variation in biological oxygen demand (BOD) removal efficiency was observed after 15 days of the experiment. After day-15, the MLSS concentration increased to 2960 mg/L, and the BOD concentration reduced to 12.85 mg/L, resulting in a reduction of 89.86% in BOD, indicating the meeting of effluent discharge standards.

Investigation of Deoxygenation Rate Determination in Cikakembang River, West Java, Indonesia

Cikakembang River, a tributary of Citarum River, is situated in the densely populated Majalaya District, renowned for textile production. Direct discharges of domestic and industrial pollutants into the river contribute to substantial pollution, making it crucial to manage pollution levels. This implies that controlling pollution is crucial, as it significantly impacts the condition of Citarum River, already infamous as one of the world most polluted rivers. A key indicator for assessing river water quality is Biological Oxygen Demand (BOD), representing the oxygen required for microorganism-mediated decomposition. This parameter is influenced by deoxygenation rate, denoted as kd. Therefore, this study aimed to analyze the most suitable kd value for Cikakembang River using various empirical methods, including Simple, Fujimoto, Sawyer, Thomas, Fair, and Hydroscience. The result showed that Thomas method provided the most accurate prediction for BOD concentration of the river. In rainy season, Root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) values were 0.542, 0.035, and 0.981, respectively, and in dry season, the values were 0.117, 0.009, and 0.999. Additionally, kd value effectively simulated the river water quality using HEC-RAS, yielding satisfactory results. RMSE, MAPE, and R2 values for BOD concentration were 3.551, 0.162, and 0.331 in rainy season and 1.071, 0.100, and 0.812 in dry season. Finally, the modeling result showed that Cikakembang River did not meet the Class 2 Water Quality Standard during both rainy and dry seasons. This finding is critical, as it underscores the severity of the pollution problem in the river and the urgent need for comprehensive and effective management strategies to improve its water quality.

Impact of Lockdown on the Surface Water Quality in Kelani River, Sri Lanka

The COVID-19 lockdown has been regarded as a catalyst for the restoration of natural water bodies worldwide. Therefore, this study aims to investigate the impacts of the lockdown on the water quality of the Kelani River, Sri Lanka. The water quality downstream of the Kelani River Basin was greatly improved during the lockdown season, The concentration of biological oxygen demand (BOD) decreased downstream by ~46% during the lockdown, while that in the middle and upstream reduced by 7.1% and 5.0%, respectively. The concentration of chemical oxygen demand (COD) was diminished by around 65%, 52%, and 43% in downstream, middle stream, and upstream, respectively, in the lockdown season. However, in post-lockdown season, upstream showed the highest spatial variation in nitrate concentration, which may be due to excessive use of fertilizers in that region. Many industries temporarily shut down or scaled back operations during the lockdown, which allowed for a large reduction in the discharge of pollutants, particularly in the river’s downstream region. The river’s water quality showed a significant improvement as a result of temporarily suspending human activities.

Chemical substances present in discharge water generated by laundry industry: Analytical monitoring

To our knowledge, precise data concerning the pollution in terms of qualitative and quantitative fluctuations in discharge water from the laundry sector have seldom been reported. This study investigated the chemical composition of the discharge water from a laundry industry. Over 160 chemical substances and 15 standard water parameters were monitored. The results showed that the discharge water presented both inorganic and organic polycontamination with a high degree of qualitative and quantitative variability. However, of all monitored substances, only five metals (Al, Cu, Fe, Sr, and Zn), five minerals (P, Ca, K, Na, and S), and alkylphenols were systematically present and quantifiable. For a daily average water flow of 129 m3, the released metal flux was 356 g/d. Substances, such as trichloromethane, brominated diphenyl ether (BDE) 47, and fluorides, were occasionally found and quantified. Other substances, such as chlorophenols, organo-tins, and pesticides were never identified. All the samples had quantifiable levels in the chemical oxygen demand (COD), biological oxygen demand (BOD), and hydrocarbons. Only the concentrations of Zn (8.3 g/d), Cu (21.4 g/d), and BOD (57.4 g/d) were close to or above the regulatory values: 74.0 g/d for Zn, 9.0 g/d for Cu, and 57.0 kg/d for BOD. The data obtained from this study are useful to the choice of additional treatments for the reduction of pollutant fluxes.

DynQual v1.0: a high-resolution global surface water quality model

Abstract. Maintaining good surface water quality is crucial to protect ecosystem health and for safeguarding human water use activities. However, our quantitative understanding of surface water quality is mostly predicated upon observations at monitoring stations that are highly limited in space and fragmented across time. Physical models based upon pollutant emissions and subsequent routing through the hydrological network provide opportunities to overcome these shortcomings. To this end, we have developed the dynamical surface water quality model (DynQual) for simulating water temperature (Tw) and concentrations of total dissolved solids (TDS), biological oxygen demand (BOD) and fecal coliform (FC) with a daily time step and at 5 arcmin (∼ 10 km) spatial resolution. Here, we describe the main components of this new global surface water quality model and evaluate model performance against in situ water quality observations. Furthermore, we describe both the spatial patterns and temporal trends in TDS, BOD and FC concentrations for the period 1980–2019, and we also attribute the dominant contributing sectors to surface water pollution. Modelled output indicates that multi-pollutant hotspots are especially prevalent across northern India and eastern China but that surface water quality issues exist across all world regions. Trends towards water quality deterioration have been most profound in the developing world, particularly sub-Saharan Africa and South Asia. The model code is available open source (https://doi.org/10.5281/zenodo.7932317, Jones et al., 2023), and we provide global datasets of simulated hydrology, Tw, TDS, BOD and FC at 5 arcmin resolution with a monthly time step (https://doi.org/10.5281/zenodo.7139222, Jones et al., 2022b). These data have the potential to inform assessments in a broad range of fields, including ecological, human health and water scarcity studies.

STORET (Storage and Retrieval) method for analysis and identification of water pollutants in the Upper Citarum Watershed, West Java, Indonesia

Water pollution in the Citarum watershed is currently an urgent problem to control. Water pollution usually occurs due to the large number of pollutants entering the water bodies, such as from household, agricultural, industrial, livestock, and land use wastes. This study was conducted in the Citarum upstream watershed and divided into five locations: Situ Cisanti, Cikawao, Koyod, Rancamanyar, and Nanjung. This study aimed to analyze and identify the pollution level in the Citarum upstream watershed based on the BOD (biological oxygen demand), TDS (total dissolved solids), chloride, zinc, total detergent, nitrate, nitrite, lead, mercury, and phenol concentrations. These parameter data were then compared to the Indonesian government regulation for river water quality standards No. 22/2021 and the STORET (Storage and Retrieval) method, based on the United States Environmental Protection Agency (US EPA). Water sampling from each location was carried out in different seasons. The STORET value in the rainy season was categorized as slightly polluted with the value of -10, then became -34 in the dry season as heavily polluted. Therefore, water pollution management is necessary to sustain the water resources by controlling the domestic waste and fertilizer application in agriculture and livestock culture.

Analysis of the Load Carrying Capacity of BOD and COD Pollutants in The Krukut River

Krukut River is one of the rivers that has an important role to support the activities of the residents of Jakarta City. Krukut River has a length of 44.3 km. In 2015 the Krukut River was the target of a master plan for improving river water quality in Jakarta by Regional Environmental Management Agency (BPLHD) DKI Jakarta but in fact there was a decline in river water quality due to increasing population growth so that monitoring activities are needed. The purpose of the study is to identify the polluting sources of the Krukut River, analyze the water quality of the river, determine the pollutant load. The research parameters used are Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Sampling in the Krukut River was carried out using the grab sampling method in September, October, November 2021 divided into 9 segments consisting of 9 non-point sources and 5 point sources. Non-point sources of pollutants are obtained from domestic waste dominated by residential areas, as well as food stalls, point source of pollutants are obtained from drainage channels, Mampang River, Ciliwung River, Cideng Channel and Krendang River. Pollutant load carrying capacity for BOD and COD concentrations in the Krukut River were respectively 292.896-622.592 kg/day and 2440.8-13521.6 kg/day. The pollutant load for BOD and COD concentrations in the Krukut River were respectively 2601.3-13792.2 kg/day and 3139.1-16542.6 kg/day.

Statistical indicators to evaluate the performance of electrocoagulation with membrane bioreactor (EC-MBR) for treatment of organic matters in domestic wastewater

An electrocoagulation with membrane bioreactor technique (EC-MBR) was developed to treat domestic wastewater and prevent membrane fouling. To support the new design, experiments were conducted on a few levels. The structure and distribution of organic matter removal utilizing the membrane are investigated using a laboratory-scale (EC-MBR) treatment of domestic wastewater. The study's goals were to assess the removal efficiency of organic matter (biological oxygen demand (BOD) and chemical oxygen demand (COD) in Al-Hawraa's wastewater, as well as its links to statistical indicators. It was chosen to sample and evaluate effluent from domestic wastewater using EC-MBR with operating temperature (25 0C), pH (7-8), DO (4-6) mg/L, beginning and final concentrations of BOD (184-6 mg/L), and COD (489-20 mg/L) using biological and electrochemical treatment procedures. According to the results, the organic matter removal efficiency may be calculated using the multilinear regression (MLR) and neural network (NN) models in the SPSS modeler. In addition, the results showed that the entire reactor had good BOD and COD maximum removal efficiencies of 96.7% and 95.9%, respectively. Finally, the highest accuracy of the MLR algorithm for COD and BOD is 99.6 for both, whereas the maximum accuracy of the NN algorithm for COD and BOD is 99.2 % and 99.1%, respectively. To choose the best algorithm for analysis and modeling the outcomes, a comparative study has been achieved to compare the results of two algorithms that used in this study. Therefore, for this study MLR algorithm was chosen.

Irrigation suitability, health risk assessment and source apportionment of heavy metals in surface water used for irrigation near marble industry in Malakand, Pakistan.

Water is a vital, finite resource whose quantity and quality are deteriorating as the world population increases. The current study aims to investigate the concentration of heavy metals (HM) in surface water for irrigation purposes with associated human health risks and pollution sources near the marble industry in Malakand, Pakistan. Twenty-seven water samples were randomly collected and analyzed for HM concentration by inductively coupled plasma‒optical emission spectrometry (ICP‒OES). pH, electrical conductivity (EC), total dissolved solids (TDS), biological oxygen demand (BOD), and chemical oxygen demand (COD) were measured using standard methods of American Public Health Association (APHA). Irrigation suitability was assessed using specific water quality parameters. The associated health risks from ingestion and dermal exposure to heavy metals were calculated by USEPA health risk indices. Pollution sources and spatial distribution mapping were studied using compositional data analysis (CoDa) and the application of a geographic information system (GIS) to understand the changing behavior of heavy metals in surface waters. The concentrations of BOD (89%), COD (89%), Al (89%), Ca (89%), Cr (56%), Cu (78%), Fe (56%), K (34%) Mg (23%), Mn (56%), Na (89%), Ni (56%), P (89%), and Zn (11%) exceeded the safety limits of National Environmental Quality standards (NEQs) of Pakistan. The results of Kelly's ratio (KR) classified surface water as unsuitable for irrigation. The average daily doses (ADD, mg/kg/day) for Al, Cu, Cr, Fe, Mn, Ni, and Zn were higher in children than in adults. The hazard index (HI) for children and adults was above the threshold (HI > 1), indicating a significant risk of non-carcinogenic toxicity. The carcinogenic risk values for Cr and Ni were above the USEPA limit (1 × 10-6 to 1 × 10-4), suggesting a potential carcinogenic risk for the target population. Principal component analysis (PCA), biplot (CLR), and the CoDa-dendrogram allowed for the identification of elemental associations, and their potential source was anthropogenic rather than natural in origin. Regular monitoring and phytoremediation strategies are proposed to safeguard crops and human health.

Adsorptive removal of organic pollutants from milk-processing industry effluents through chitosan-titanium dioxide nanoadsorbent-coated sand.

Milk-processing industry effluent (MPIE) poses severe problems for aquatic and environmental systems, especially in the South Asian region. Therefore, its treatment is of great interest. This study deals with the investigation of chitosan titanium dioxide nanoadsorbent (CTiO2) coated onto sand particles via calcination that are used to remove the emerging pollutants. The adsorptive properties of these developed adsorbents are compared with those of the nascent sand without coating as well as with the chitosan titanium dioxide nanoadsorbent coated sand (CTiO2-CS). Batch adsorption experiments were performed to investigate the percent reduction efficiency (%RE) of organic pollutants in terms of biological oxygen demand (BOD) and chemical oxygen demand (COD) from synthetic and real effluents. The maximum %RE of BOD (96.76) and COD (98.91) was achieved at 1.5M dose of CTiO2-CS, 120min of contact time, pH 6.5, an initial BOD concentration of 900mg/L, and an agitation speed of 400rpm. Similarly, the %RE of COD was found to be 86.75 for synthetic effluent and 90.97 for real effluent at initial COD concentrations of 8000mg/L. Pseudo-second-order and Langmuir models are found to be the best fits for BOD and COD adsorption. The diffusion model suggests that surface adsorption as well as intraparticle diffusion contribute to the actual adsorption process. Regeneration experiments were performed for four cycles, and CTiO2-CS was found to be the most regenerable adsorbent material. The performance of the adsorbent was compared with previous studies, and it was found to have excellent adsorption capacity. As a result, the developed filter bed could be used as a promising superadsorbent for the removal of organic load in MPIE.

Penerapan Metode Activated Sludge dalam Pengolahan Limbah Cair Industri Tahu Beru

The tofu industry in its production process uses ± 25 liters of water per 1 kg of soybean raw material. Soybean used as raw material for tofu contains protein, carbohydrates, fat, and other nutritional ingredients so that the resulting liquid waste contains high organic matter that has the potential to pollute the environment with a value of Biological Oxygen Demand (BOD) of 467 mg/L and Chemical Oxygen Demand (COD) of 668.2 mg/L. Efforts to control water pollution can be overcome by processing biotechnology using an activated sludge system. This study aims to analyze the effectiveness of polluted water sediment as the main ingredient of activated sludge in reducing levels of Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) and to determine the growth rate of microorganisms in the acclimatization process. This research was carried out on 4 different composition variations in batches under aerobic conditions using an aerator and a pump as a stirrer. The results showed that the composition of the sludge in treatment IV, namely the composition of the sludge consisting of (60% Waste, 40% Nutrients, and cultured RPH sludge) was the best composition at 60 hours of aeration with the effectiveness of removing BOD concentration of 90.10% and COD concentration. amounted to 87.41% or achieved a reduction value of 46.21 mg/L of BOD concentration and 84.14 mg/L of COD concentration with a specific biomass growth rate of 0.054 day-1.

Biological Oxygen Demand (BOD) Simulation in Sunter River Using Non Orthogonal Water Quality Model Transport

Water pollution problem in Jakarta has been going on for a long time. The existence of some rivers that are not directly connected to upstream in the tidal area can speed up the occurrence of water pollution and slow the circulation of polluted waste that affects water quality in river-estuary. Since 2010 after Kanal Banjir Timur (KBT) operated, Sunter River streamflow was divided by KBT, changes flow rate and water quality pattern. The study area is the main channel of the Sunter River which has 17 km lengths includes Duren Sawit, Pulo Gadung, Kelapa Gading, Plumpang, Rawa Badak and Tanjung Priok Area where the average water load is 624 mg/L. The simulation is divided into 2 scenarios with a flowrate configuration of 5 m3/s and 100 m3/s (with a raining condition of 1 hour). MuQuald3D, a three-dimensional water quality model, has been employed in this research. The merit of this model is that it can accurately predict water pollution load within the surface layer and the bottom layer and can be shown in contour profile which is effective and efficient guidance to solve the water quality problems along Sunter river-estuary. The model results show the effect of salinity will gradually reduce BOD concentration, and the existence of permanent construction around estuary (breakwater, port) changes pollutant distribution to the West and East area and increases the time of decomposition in waters, especially in low flowrate conditions.

Land-Use Impact on Water Quality of the Opak Sub-Watershed, Yogyakarta, Indonesia

The integrated monitoring system of water quality is eminently reliant on water quality trend data. This study aims to obtain water quality patterns related to land-use change over a periodic observation in the Opak sub-watershed, Indonesia, both from a seasonal and spatial point of view. Landsat image data from 2013 to 2020 and water quality data comprising 25 parameters were compiled and analyzed. This study observed that land use remarkably correlated to water quality, especially the building area representing the dense population and various anthropogenic activities, to pollute the water sources. Three types of pollutant sources were identified using principal component analysis (PCA), including domestic, industrial, and agricultural activities, which all influenced the variance in river water quality. The use of spatiotemporal-based and multivariate analysis was to interpret water quality trend data, which can help the stakeholders to monitor pollution and take control in the Opak sub-watershed. The results investigated 17 out of 25 water quality parameters, which showed an increasing trend from upstream to downstream during the observation time. The concentration of biological oxygen demand over five days (BOD5), chemical oxygen demand (COD), nitrite, sulfide, phenol, phosphate, oil and grease, lead, Escherichia coli (E. coli), and total coli, surpassed the water quality standard through spatial analysis.

Prediction of leachate quantity and quality from a landfill site by the long short-term memory model

The long short-term memory (LSTM) model was first applied in this study for the prediction of the leachate quantity and quality at a real landfill site. In our LSTM model, in the learning phase from July 2003 to March 2018, three input data items consisting of the daily precipitation (DP), the daily average temperature (DAT), and the accumulated amount of landfilled waste presented the quantity of leachate generated with high accuracy. The DAT was important for the landfill site, particularly in a snow area because it contributes to the leachate generated during the spring thaw with low precipitation. In the testing phase from April 2018 to March 2019, our LSTM model predicted the leachate generated with a mean absolute percentage error (MAPE) of 26.2%. The concentrations of biological oxygen demand, chemical oxygen demand, total nitrogen, calcium ion and chloride ion in leachate were presented in the learning phase by six input data items: DP, DAT, and the daily amount of landfilled waste (incineration residue, incombustible waste, business waste, and combustible waste) with high R2 values. In the testing phase, the quality of leachate was predicted with the MAPE between 11.8% and 30.2%. Another year data from April 2019 to March 2020 was used to verify accuracy of our model with no overfitting. This study showed the possibility of applying the LSTM model to future predictions of leachate quantity and quality from landfill sites with an acceptable error for daily operation.

Treatment of poultry slaughterhouse wastewater using electrocoagulation: a review

AbstractPoultry slaughterhouses are generally large consumers of fresh water, which is exhausted as wastewater characterized by a high concentration of biological oxygen demand (BOD), chemical oxygen demand COD, and fats, oil, and grease (FOG). Cost-effective methods are required for the treatment of poultry slaughterhouse wastewater, with the aim of attaining a high quality effluent that can be reused in industrial processes to promote sustainability. As compared to conventional treatment methods, electrocoagulation is an efficient and low-cost system. Electrocoagulation is environmentally friendly, treating wastewater without the need of chemicals, thus limiting secondary pollution. The metal anodes initiate electrochemical reactions for coagulation and flocculation. Its distinct advantages include compact installation and simple operation. This paper offers a comprehensive review of recent literature that has been dedicated to utilizing electrocoagulation for poultry slaughterhouse wastewater treatment. This paper also examines aspects such as theory, potential applications, current applications, as well as economical assessment of the technique.

Adsorptive removal of dairy industrial pollutants by chitosan zinc –oxide nanoadsorbent- A comparitive study of artificial neural network and quadratic Box-Behnken design

Aim: To investigate the effect of operational parameters on the adsorption of biological oxygen demand (BOD) and chemical oxygen demand (COD) on to Chitosan zinc oxide (CZnO) nanoadsorbent using cost-effective and eco-friendly nanoadsorbent based effluent treatment processes. Methodology: CZnO nanoadsorbent particle was synthesized using chemical precipitation method. The nano size <100 nm was achieved using high-speed cryo all mill, followed by the characterization using high-end instruments such as scanning electron microscope with elemental detection sensor (SEM-EDS), atomic force microscope (AFM), X-ray diffractometer (XRD) and Fourier transform inform infrared spectroscopy (FT-IR). Modeling and optimization of operational parameters were done with the artificial neural network (ANN) and Box-BehnkenDesign (BBD) statistical tools. Results: Optimized treatment combination for adsorption of BOD and COD were found at initial BOD and COD concentration of 100 and 200 mg l−1, pH of 7.0 and 2.0, adsorbent dosage of 1.25 mg l−1, contact time of 100 and 60 min. In these conditionsthe desirability values of 0.988 and 0.950 were found for BOD and COD adsorption. The maximum per cent reduction of BOD and COD by using CZnO nanoadsorbent was found to be 96.71 and 87.56. Two models such as Quadratic Box-Behnken and ANN were compared in term of sum of square errors (SSE), root mean square error (RMSE) and correlation coefficient (R2) values. Interpretation: The results obtained revel the well trained ANN model found to be more accurate in prediction of BOD and COD adsorption process parameters compared to BBD model.

Assessment of Water Quality Target Attainment and Influencing Factors Using the Multivariate Log-Linear Model in the Nakdong River Basin, Republic of Korea

Because identifying the factors affecting water quality is challenging, water quality assessment of an individual component based on the arithmetic mean method cannot adequately support management policies. Therefore, in this study, we assessed the water quality target attainment at 24 sites in the Nakdong River Basin by applying multivariate log-linear models to identify factors influencing water quality, including flow and season. The temporal and seasonal water quality trend and flow were also analyzed using the calculated model coefficients. Specifically, weekly data on biological oxygen demand (BOD), total phosphorous (TP), and flow during 2013–2018 were used to investigate the 2018 water quality target attainment level for this river. The significance and suitability of the models were analyzed using the F-test, root mean squared error (RMSE), mean absolute percent error (MAPE), and adjusted R2 values. All 24 models applied in this study showed statistical significance and suitability for the prediction of BOD and TP concentrations. Moreover, flow was identified as the main factor affecting water quality and had a predominant effect on BOD and TP concentrations in tributaries and the main stream, respectively. Furthermore, among the 24 sites, BOD and TP targets were evidently attained at 18 and 17 sites, respectively.

Application of effective microorganisms technology on dairy wastewater treatment for irrigation purposes

Due to the massive amounts of freshwater consumed in dairy industries, as a result, thousands of liters of wastewater were produced as one liter of milk produces 10 liters of wastewater which represents a major threat to the surrounding environment and aquatic life. The application of a promising technology called “effective microorganism (EM)” was the key solution due to its low operating cost, low technology, and eco-friendly condition. Three different effective microorganisms were used, such as Bacillus bacteria (EM1), Staphylococcus bacteria (EM2), and EM stoste + Molasses (EM3). EM1 and EM2 were isolated from the dairy wastewater by using streaking for isolation on an agar plate process, while EM3 was prepared by mixing 12 % EM stoste, 6% molasses, and 82% distilled water. A laboratory pilot consists of aeration and final settling tanks, both tanks followed by an activated carbon filter. Four trials were performed, the first trial was without any EM, the second trial was adding EM1 with a dose of 50 ml to the aeration tank, the third trial was EM2 with a dose of 50 ml to the aeration tank, finally adding EM3 with a dose of 30 ml to the aeration tank. Results showed that using Bacillus bacteria (EM1) was the most effective trial as it was effective in reducing TSS (total suspended solids), BOD (biological oxygen demand), COD (chemical oxygen demand), TN (total nitrogen), and TP (total phosphorous) concentrations by removal efficiency of 93%, 96.2%, 95.9%, 94%, and 64%, respectively which were below the limitations of the Egyptian code for reuse for irrigation purposes.

Distribution of DO (Dissolved Oxygen) and BOD (Biological Oxygen Demand) in the Waters of Karimunjawa National Park using Two-Dimensional Model Approach

Massive mangrove conversion into intensive pond farming has become environmental problem in Kemujan Island and Karimunjawa Island which affect the water quality. This research aimed to examine the dispersion of DO and BOD related to the current pattern in the seas west of Kemujan Island and Karimunjawa Island by using two-dimensional modelling simulations. Quantitative and descriptive methods were used to provide interpretation and analysis of the modelling simulation results. Modelling simulations were conducted in September 2019. The validation results show that the model and the field measurements has a very good. The results show that the current characteristics are dominated by tidal current, which moves westward with an average magnitude of 0.078 m/s. Furthermore, divergence, convergence and turbulence are also identified. Based on the simulation results, the prediction of DO and BOD concentrations fluctuate in Lagoon Mrican. During spring tide, the DO concentration changes from 7.95 - 8.1 mg/L into 8.55 - >9.45 mg/L and during neap tide, it changes from 8.55 - 8.7 mg/L into 9.15 - >9.45 mg/L. On the other hand, the BOD concentration increases from 0 - 0.08 mg/L to 0.88 - 0.96 mg/L during spring tide and neap tide.