<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">OJAppS</journal-id><journal-title-group><journal-title>Open Journal of Applied Sciences</journal-title></journal-title-group><issn pub-type="epub">2165-3917</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ojapps.2023.138116</article-id><article-id pub-id-type="publisher-id">OJAppS-127428</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject><subject> Chemistry&amp;Materials Science</subject><subject> Computer Science&amp;Communications</subject><subject> Engineering</subject><subject> Physics&amp;Mathematics</subject></subj-group></article-categories><title-group><article-title>
 
 
  Systematic Biological Upgrade of a Urea Fertilizer Effluent Treatment Plant Using GPS
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Isyaku</surname><given-names>Ahmad</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Joseph</surname><given-names>T. Akintola</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Regina</surname><given-names>J. Patinvoh</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wilson</surname><given-names>F. Ekpotu</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Martins</surname><given-names>C. Obialor</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Philemon</surname><given-names>Chukwuebuka Udom</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib></contrib-group><aff id="aff5"><addr-line>Department of Chemical Engineering, Federal University of Owerri, Owerri, Nigeria</addr-line></aff><aff id="aff1"><addr-line>Process (Urea) Department, Dangote Fertiliser Limited, Lagos, Nigeria</addr-line></aff><aff id="aff4"><addr-line>Department of Chemical &amp;amp; Petroleum Engineering, University of Uyo, Akwa Ibom, Nigeria</addr-line></aff><aff id="aff2"><addr-line>Department of Research &amp;amp; Development, Vitapur Nigeria Limited, Lagos, Nigeria</addr-line></aff><aff id="aff3"><addr-line>Department of Chemical Engineering, Faculty of Engineering, Lagos State University, Lagos, Nigeria</addr-line></aff><pub-date pub-type="epub"><day>04</day><month>07</month><year>2023</year></pub-date><volume>13</volume><issue>08</issue><fpage>1457</fpage><lpage>1477</lpage><history><date date-type="received"><day>8,</day>	<month>June</month>	<year>2023</year></date><date date-type="rev-recd"><day>28,</day>	<month>August</month>	<year>2023</year>	</date><date date-type="accepted"><day>31,</day>	<month>August</month>	<year>2023</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  The use of modeling and simulation has developed into a critical tool for the sustainable management of wastewater, especially when it comes to replicating the complex biochemical procedures required for fertilizer effluent treatment, which calls for a significant amount of wastewater-related data. The bio
  logical improvement of a urea fertilizer effluent via GPS* simulation was carried out in this work using a methodical process. Using established analytical techni
  ques, temperature, total suspended solids (TSS), biochemical oxygen 
  demand (BOD), total phosphorus (T/
  
  ), chemical oxygen demand (COD), total nitrogen (TN), total nitrate (NO<sub>3</sub>), electric conductivity (EC), turbidity, 
  residual chlorine, urea, NH<sub>3</sub>, and heavy metals (Cu, Cd, Cr, Pb, Ni, and Fe) were assessed. The research revealed that the measured values from the fertilizer factory outfall effluent had high concentrations of all the physicochemical water quality indicators, with the exception of TSS, PO<sub>4</sub><sup>-</sup>
  , SO<sub>4</sub><sup>-</sup>
  , and NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;. These concentrations are higher compared to the authorized limits or suggested values by the Federal Environmental Protection Agency (FEPA). To improve the therapy biologically, however, a modeling and simulation program (GPS-X, version 8.0) was used with the physicochemical information gathered from the studied sample. The results of the treated water simulation showed that the concentrations of BOD<sub>5</sub> and COD had been significantly reduced by 35% and 44%, respectively. Additionally, it was discovered that total phosphorus (TP), nitrate (N), and total nitrogen (TN) were all within the permitted FEPA limit. The results revealed good treatment performance of the wastewater with increasing concentration of acetic acid and sodium hydroxide. Hence, the results of this research work identify the need for proper treatment of fertilizer industry effluents prior to their release into the environment.
 
</p></abstract><kwd-group><kwd>Fertilizer Wastewater Effluent</kwd><kwd> Discharge Basin</kwd><kwd> Outfall Basin</kwd><kwd> Physiochemical Analysis</kwd><kwd> GPS*</kwd><kwd> Modelling &amp; Simulation</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The dangers of dumping hazardous chemicals, solid waste, heavy metals, and industrial effluent into rivers, lakes, and streams to aquatic life and ultimately to humans cannot be understated. With the advent of industrialization, many chemical firms have expanded and adapted to inadequate waste management procedures; typically, effluents wind up being diverted directly into the environment. Hence, this has adverse effect on the health of people, and the entire marine.</p><p>The quality of the water standard and the environment suffer severely if the residence time for microbial activity is insufficient to break down the contaminants and protects the habitats from deterioration [<xref ref-type="bibr" rid="scirp.127428-ref1">1</xref>] . In developing countries, particularly in African countries like Nigeria, a sizable portion of the rural population drinks water that they personally obtained from those sources. These water sources are exposed to pollutants from industrial activity because the industrial effluents are either not treated at all or only partially treated, making the water from those natural sources unsafe to drink. Because chemicals and pollutants are absorbed by aquatic species and then by humans, leading to a variety of health concerns, industrial effluent treatment becomes vital [<xref ref-type="bibr" rid="scirp.127428-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.127428-ref2">2</xref>] .</p><p>Water contaminants that pose risks to people and the environment if discharged to surface and ground waters without effective treatments are what wastewater treatment processes aim to remove or reduce [<xref ref-type="bibr" rid="scirp.127428-ref3">3</xref>] . While industrialized nations continue to work on creating new technologies or setting up more effective treatment processes in WWTPs to fulfill the rising demand for water, the poorer nations are still struggling to put in place the necessary infrastructure for treatment. Even if the harm caused by a lack of such infrastructure is clear, public concern is still restricted as a result of a lack of public education programs on environmental issues as well as the impact of crises and political unrest in these nations [<xref ref-type="bibr" rid="scirp.127428-ref4">4</xref>] .</p><p>In order of increasing degree of treatment, teams of preliminary, primary, secondary, and tertiary wastewater treatment stages are frequently used to describe the amount of water treatment. Activated sludge, contact stabilization, trickling filters, aerated lagoons, total oxidation, and waste stabilization ponds are also used in the secondary treatment process, which is the most important step in the sewage treatment process [<xref ref-type="bibr" rid="scirp.127428-ref5">5</xref>] . To remove particles, raw materials, and nutrients from effluent, physical and biological techniques are frequently combined in wastewater treatment. The treatment of wastewater from manufacturing companies has been a challenge in the past; in the fertilizer industry, the anoxic process is the most frequently used biological process analog due to its ability to denitrify [<xref ref-type="bibr" rid="scirp.127428-ref3">3</xref>] .</p><p>While biological treatment is frequently used to remove nitrates from wastewater used in the production of nitrogenous fertilizers, ion exchange can be utilized to remove ammonia and nitrates. However, it was advised to eliminate nitrogenous fertilizer effluents utilizing physical, chemical, and biological methods [<xref ref-type="bibr" rid="scirp.127428-ref6">6</xref>] . It is common knowledge that biological wastewater treatment requires the least amount of energy. It is the most eco-friendly method and doesn’t require any xenobiotics. The characteristics of an effluent treatment system can be thoroughly understood using a mathematical model, lowering risk and operating costs.</p><p>Agriculture’s support system unquestionably includes the industrial facilities that produce a wide range of fertilizer products [<xref ref-type="bibr" rid="scirp.127428-ref7">7</xref>] . On the other hand, by emitting gaseous, liquid, and solid pollutants, these businesses are also among the biggest offenders of environmental pollution. The main contaminants in effluents discharged by the fertilizer, pharmaceutical, tanning, and dyeing industries are toxic anions, organic and inorganic chemicals, dissolved gases, pesticides, and heavy metals [<xref ref-type="bibr" rid="scirp.127428-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.127428-ref9">9</xref>] . To ensure effective treatment before disposal, liquid effluents must be regularly and accurately characterized [<xref ref-type="bibr" rid="scirp.127428-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.127428-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.127428-ref12">12</xref>] .</p><p>A “simulation” is a simple depiction of a chemical reaction that captures its operational circumstances throughout time. Simulation is frequently used in conjunction with scientific modeling of chemical systems to comprehend how a certain chemical system behaves or functions [<xref ref-type="bibr" rid="scirp.127428-ref13">13</xref>] . GPS*, a modular, versatile computer application, is used to construct and simulate wastewater treatment plants for both commercial and municipal uses. When constructing a new development or replicating an existing one, GPS* improves the design and operational efficiency of the process facility. This research’s sole goal is to update fertilizer wastewater treatment facilities using GPS. GPS* is developed and distributed by Hydromantis Environmental Software Solutions, Inc., and is recognized for its accuracy, reliability, and user-friendly interface [<xref ref-type="bibr" rid="scirp.127428-ref14">14</xref>] . The key features of GPS* are process modeling, user-friendly interface, flexibility, simulation capabilities, data management, sensitivity analysis, reporting and visualization. Users can simulate the behavior of wastewater treatment plants under different operating conditions and scenarios, enabling them to optimize performance and identify potential issues. Hence, GPS* is a leading software tool in the field of wastewater treatment process modeling and simulation [<xref ref-type="bibr" rid="scirp.127428-ref14">14</xref>] . Its extensive features, accuracy, and user-friendly interface make it an indispensable asset for engineers, researchers, and operators working in the wastewater treatment industry. This research’s sole goal is to upgrade Urea fertilizer wastewater using GPS*.</p><p>Solids, organic matter, and nutrients are removed from wastewater via physical and biological processes in traditional wastewater treatment methods. Preliminary, primary, secondary, and tertiary or advanced wastewater treatment methods are general terminology used to represent various degrees of treatment, in sequence of increasing treatment [<xref ref-type="bibr" rid="scirp.127428-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.127428-ref15">15</xref>] . The secondary treatment procedure, which involves biological treatment methods using a variety of microorganisms in a controlled environment, is the main treatment method used in traditional sewage treatment methods. Activated sludge, total oxidation, contact stabilization, aerated lagoons, waste stabilization ponds, trickling filters, and anaerobic treatment are among the aerobic and anaerobic biological processes utilized for secondary treatment methods. In comparison to other biological processes, the activated sludge process is the most commonly used since its facility design is well known and it has specified operation characteristics [<xref ref-type="bibr" rid="scirp.127428-ref16">16</xref>] .</p><p>The purpose of this study is to biologically treat the effluents produced by various fertilizer plant operations, with the goal of reducing the following: Chemical Oxygen Demand (COD), Electric Conductivity (EC), Biochemical Oxygen Demand (BOD), Sulphates, Total Dissolved Solids (TDS), Turbidity, Total Phosphorus (T/ PO 4 − ), Residual Chlorine, Nitrate (NO<sub>3</sub>), Total Nitrogen (TN), Total Suspend Prospects related to this research include water recovery and reuse, economic savings (chemical, waste minimization), better management, and operator training. The biological treatment of fertilizer plant wastewater was evaluated in the study using the GPS*. The results of this study are anticipated to assist the pertinent companies and authorities in using biological treatment techniques for effluents and reduce the amount of hazardous waste released into the environment.</p></sec><sec id="s2"><title>2. Materials and Methods</title><sec id="s2_1"><title>2.1. Collection of Samples</title><p>The wastewater from a fertilizer company was sampled in Epe, Lagos State, in southwest Nigeria. Two closed basins containing fertilizer wastewater at various concentrations were chosen for the collection of effluent samples. In addition to the outfall basin (Sample 2) because of the potential effects on aquatic life once it entered the lagoon, samples were also taken from the final discharge basin (Sample 1) because it comprises effluent from both the equalization basin and cooling tower blowdown. There is a fishing settlement along its banks.</p></sec><sec id="s2_2"><title>2.2. Analysis and Calculations</title><p>The analytical procedures used to determine these parameters have been modified from Theoretical Aspects of Laboratory Analysis in 1992, Guidelines and Criteria for Water Quality Management in Ontario in 1967, the Laboratory Manual on Soil and Plant Analysis in 1995, and A.O.A.C. (Association of Analytical Chemists, Official Methods of Analysis, 1990). The wastewater quality characteristics of these effluents were measured, including temperature, total suspended solids (TSS), urea, total nitrogen, NH<sub>3</sub>, electric conductivity, color, nitrate, total dissolved solids (TDS), turbidity, residual chlorine, total phosphorus, sulphates, pH, and heavy metals.</p><sec id="s2_2_1"><title>2.2.1. Physicochemical Analysis of Effluents</title><p>As soon as the samples arrived, the pH was measured using a JENWAY 3020 pH meter using 100 ml of each sample. Total chloride was also measured using potentiometric titration. In order to prevent certain cations from being lost by absorption or ionic exchange with the walls of plastic containers as a result of storage effect, an additional 1.5 litres of each sample were collected in two distinct clean bottles and acidified with nitric acid to a pH below 2.0.</p><p>To analyze the other physicochemical parameters, the remaining samples were kept in the refrigerator overnight at a temperature of about 4˚C. A mercury thermometer was dipped into each homogeneously mixed sample at each sampling location and left there for roughly two minutes to record the temperature. The mercury thermometer was cleaned in a buffer solution with a pH of 7 prior to reuse. The electrical conductivity of the samples was measured using a digital bench-top conductivity meter (JENWAY 4010 conductivity meter). The relationship between Total Dissolved Solids (TDS) and Electric Conductivity, however, is 2.2:1. To calculate the TDS measurement in mg/L, the electric conductivity value was divided by 2.2.</p><p>The spectrophotometric approach was used to calculate urea levels. P-dimethyl amino benzaldehyde (DMAB) and urea react to form a yellow complex in a Sulphuric acid medium. According to Obire, Ogan, and Okigbo (2008), the strength of the complex is closely correlated with the amount of urea contained in the sample. The organic nitrogen approach was used to calculate the amount of ammonia present in the effluent. Using a turbimetric method, the samples’ sulphate (SO<sub>4</sub>) content was measured. The total phosphate in the samples was determined using a spectrophotometric method based on sample digestion. A standard approach was used to analyze the sample color. Brucine reagent B was used to quantify the samples’ nitrite (NO<sub>3</sub>) level using spectrophotometry [<xref ref-type="bibr" rid="scirp.127428-ref7">7</xref>] .</p><p>Titration was used to determine the chemical oxygen demand (COD), and then potassium permanganate was used as an oxidizing agent. The Winkler test was first used to gauge how much dissolved oxygen was present in the water samples. Iodometric titrations were used to calculate the BOD<sub>5</sub> of the effluent samples using the dilution method. MnSO<sub>4</sub> solution was used as the nutrient solution, and then the alkali-iodide reagent, sodium thiosulfate (Na<sub>2</sub>SO<sub>3</sub>), and sulfuric acid titration were used.</p><p>The metal concentration was measured using a Buck Scientific model 230 atomic absorption spectrometer with an air-acetylene flame and a wavelength range of 190 to 900 nm. Using calibration curves at specific wavelengths of 228.8 nm, 224.8 nm, 217 nm, 373 nm, 231.6 nm, and 522 nm, respectively, the concentrations of cadmium (Cd), copper (Cu), lead (Pb), nickel (Ni), chromium (Cr), and iron (Fe) were calculated.</p></sec><sec id="s2_2_2"><title>2.2.2. BOD<sub>5</sub> Calculations</title><p>To determine the value of the BOD<sub>5</sub> in mg/l the following formula was used:</p><p>BOD 5   mg / l = ( InitialDO − FinalDO ) &#215; 300 samplevolume ( ml ) (1)</p><p>Where DO is dissolved oxygen.</p></sec><sec id="s2_2_3"><title>2.2.3. Final Discharge Basin (Sample 1)</title><p>D 1fd = 13.5   ml + 13.0   ml + 14.0   ml 3 = 13.5   ml (2)</p><p>D 2fd = 8.0   ml + 7.8   ml + 7.9   ml 3 = 7.9   ml (3)</p><p>BOD 5fd = ( 13.5 − 7.9 ) &#215; 250 15 = 13.5   ml (4)</p></sec><sec id="s2_2_4"><title>2.2.4. Outfall Effluent (Sample 2)</title><p>D 1oe = 12.9   ml + 12.9   ml + 12.9   ml 3 = 12.9   ml (5)</p><p>D 2oe = 7.3   ml + 7.3   ml + 7.4   ml 3 = 7.4   ml (6)</p><p>BOD 5oe = ( 12.9 − 7.4 ) &#215; 250 15 = 91   ml (7)</p></sec><sec id="s2_2_5"><title>2.2.5. COD Calculations</title><p>COD   mg / l = ( A − B ) &#215; m &#215; 800 volumeofsample (8)</p><p>A = Titre volume of blank. B = Titre volume of sample. M = molarity of titer.</p></sec><sec id="s2_2_6"><title>2.2.6. Final Discharge Basin (Sample 1)</title><p>Titre value of blank = 22.1 ml; Titre value of sample = 21.5 ml.</p><p>COD = ( 22.1 − 21.5 ) &#215; 0.5 &#215; 800 12 = 100   mg / l</p></sec><sec id="s2_2_7"><title>2.2.7. Outfall Effluent (Sample 2)</title><p>Titre value of blank = 22.1 ml; Titre value of sample = 21.7 ml.</p><p>COD = ( 22.1 − 21.7 ) &#215; 0.25 &#215; 800 12 = 116.7   mg / l</p><p>Using an atomic absorption spectrometer with an air-acetylene flame and a wavelength range of 190 to 900 nm, Buck Scientific’s model 230 was used to measure the metal concentration. Cadmium (Cd), Copper (Cu), Lead (Pb), Nickel (Ni), Chromium (Cr), and Iron (Fe) concentrations were determined using calibration curves at particular wavelengths of 228.8 nm, 224.8 nm, 217 nm, 373 nm, 231.6 nm, and 522 nm, respectively.</p></sec></sec><sec id="s2_3"><title>2.3. Simulation</title><p>The biological treatment of fertilizer effluent made it possible to install and use GPS*, version 8.0, a modelling and simulation program developed by Hydromantis Environmental Software Solutions Inc., the most advanced tool currently accessible for the mathematical optimization, modelling, and management of wastewater treatment plants [<xref ref-type="bibr" rid="scirp.127428-ref17">17</xref>] .</p><p>The software was started, and the process water treatment library (proc water lib) option was selected. After finding the process table, a plant layout was made utilizing its icons. On the drawing board, every element of the process model was moved, arranged, and labelled. The process table was especially used to build all of the flow connections between the components of the process model. After adjusting the flow connections, stream labels were chosen using the labels button on the main toolbar. Following that, all process model object flow lines were given new names and labels.</p><sec id="s2_3_1"><title>2.3.1. Selection of Object Model and Mathematical Analysis</title><p>The primary unit processes and control points are the sole fundamental objects chosen to be modelled in our plant. The layout’s numerous objects weren’t given mathematical models. Therefore, several equations were established by the GPS* as one of the most crucial qualities to define the dynamic behavior of the process model objects. The models of the process elements that were utilized to construct the treatment scheme were examined, and decisions were taken for each element as indicated in <xref ref-type="table" rid="table1">Table 1</xref>.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Process model utilization for each equipment</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >S/N</th><th align="center" valign="middle" >Process Model Objects</th><th align="center" valign="middle" >Available Model (s)</th><th align="center" valign="middle" >Selected Model</th></tr></thead><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >Wastewater Influent point</td><td align="center" valign="middle" >states, tsstoc</td><td align="center" valign="middle" >Tsstoc</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >Anoxic Tank 1 &amp; 2</td><td align="center" valign="middle" >pw2</td><td align="center" valign="middle" >pw2</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Aeration Tank 1 &amp; 2</td><td align="center" valign="middle" >pw2</td><td align="center" valign="middle" >pw2</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >Air Blower</td><td align="center" valign="middle" >Interchange</td><td align="center" valign="middle" >Interchange</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >Clarifier</td><td align="center" valign="middle" >empiric, point, simple1d, tss-sor-slr</td><td align="center" valign="middle" >Empiric</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >Sludge Buffer Sump</td><td align="center" valign="middle" >pw2</td><td align="center" valign="middle" >pw2</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >Sludge Thickener</td><td align="center" valign="middle" >empiric, simple1d</td><td align="center" valign="middle" >Empiric</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >Sludge Centrifuge</td><td align="center" valign="middle" >asce, point, simple1d, press</td><td align="center" valign="middle" >Empiric</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >Solutions from Side Filter &amp; Oil Sludge</td><td align="center" valign="middle" >Interchange</td><td align="center" valign="middle" >Interchange</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >Sludge Disposer</td><td align="center" valign="middle" >Default</td><td align="center" valign="middle" >Default</td></tr><tr><td align="center" valign="middle" >11</td><td align="center" valign="middle" >Outfall Effluent point</td><td align="center" valign="middle" >Default</td><td align="center" valign="middle" >Default</td></tr><tr><td align="center" valign="middle" >12</td><td align="center" valign="middle" >Acetic Acid Doser</td><td align="center" valign="middle" >Codfeed</td><td align="center" valign="middle" >Codfeed</td></tr><tr><td align="center" valign="middle" >13</td><td align="center" valign="middle" >Sodium Hydroxide Doser</td><td align="center" valign="middle" >Alkalifeed</td><td align="center" valign="middle" >Alkalifeed</td></tr><tr><td align="center" valign="middle" >14</td><td align="center" valign="middle" >Sodium Hypochlorite Doser</td><td align="center" valign="middle" >Watchem</td><td align="center" valign="middle" >Watchem</td></tr><tr><td align="center" valign="middle" >15</td><td align="center" valign="middle" >Polymer Doser</td><td align="center" valign="middle" >Metaladd</td><td align="center" valign="middle" >Metaladd</td></tr><tr><td align="center" valign="middle" >16</td><td align="center" valign="middle" >Ferric Chloride Doser</td><td align="center" valign="middle" >Metaladd</td><td align="center" valign="middle" >Metaladd</td></tr></tbody></table></table-wrap><p>The created layout was saved as “Fertilizer Effluent Biological Treatment GPS* Modelling Layout” using the file browser, which was chosen from the file menu.</p><p>Empiric Model was selected due to the following advantages;</p><p>&#183; It’s easily the most-used solids separation model for thickening and dewatering.</p><p>&#183; It’s easy to use and calibrate.</p><p>&#183; No differentiation between different types of particulate COD.</p><p>&#183; It is not predictive at very low/high concentrations due to the constant removal rate. One exception to the generic empiric model in the primary clarifier:</p><p>Efficiency ( % ) = ( T det A + B ) &#215; T det 100 (9)</p><p>where, T<sub>det</sub> = Detention time (h). A&amp;B = Solids removal parameters [<xref ref-type="bibr" rid="scirp.127428-ref17">17</xref>] .</p><p>The data from sample 1 (the effluent sample), which were received following the laboratory analysis, were used to characterize the influent on the influent advisor by selecting influent characterization from the influent composition menu. The information for all chosen process model objects, such as initial conditions, input variables, flow, output variables, source data, etc., was also chosen and filled using menus and sub-menus based on information obtained from the Biological Treatment and Sludge Handling Package design manual and data sheet used in the fertilizer plant. The model’s construction process is depicted in <xref ref-type="fig" rid="fig1">Figure 1</xref> [<xref ref-type="bibr" rid="scirp.127428-ref17">17</xref>] .</p><p>The values of the variables used to describe the GPS-X Modelling Layout for the characterization of the wastewater influent and characterization of process model objects are presented in <xref ref-type="table" rid="table2">Table 2</xref> and <xref ref-type="table" rid="table3">Table 3</xref>, respectively.</p></sec><sec id="s2_3_2"><title>2.3.2. Modelling and Simulation Procedure</title><p>To transition from modelling mode to simulation mode, click the Simulation button in the upper-right corner of the main window. This started the compilation and linking processes and produced an executable model. Upon completion, the simulation environment was available and the building model window vanished. The simulation proceeded in a steady state when the start button on the tool bar was pressed. Values were output in tabular form in the output section after completion. A rapid display screen allowed users to evaluate the simulation results, simulation parameters, and mass flows for each unit process in the layout [<xref ref-type="bibr" rid="scirp.127428-ref17">17</xref>] .</p><p>1) Creating Input Controls</p><p>To investigate the effects of changes in the influent flow rates on the plant effluent qualities, the saved built layout was opened via file menu, new input controls were created. The flow rate setup was selected on the acetic acid and sodium hydroxide dosage object thereby accessing their parameters. The flow rate variables for both were moved from the flow rate setup to the empty input control space directly above the layout. The input control properties were changed</p><p>on the control toolbar to 45 L/hr, 60 L/hr, 75 L/hr, and 90 L/hr for acid dose and 9 m<sup>3</sup>/hr, 12 m<sup>3</sup>/hr, 15 m<sup>3</sup>/hr, and 18 m<sup>3</sup>/hr for alkali dose. Simulations were then run in accordance with the changes, the results of which were generated, and the impact on the treated water quality was examined. Additionally, the cost summary, energy usage summary, mass balance diagram, and Sankey diagram were generated by clicking on additional output displays on the output tool bar, as illustrated in Figures 2-5, respectively.</p></sec></sec></sec><sec id="s3"><title>3. Results and Discussion</title><sec id="s3_1"><title>3.1. Effluent Characterization</title><p>The collected fertilizer effluent samples were evaluated in reference to temperature,</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Simulation data sample for the characterization of wastewater influent</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >Unit</th><th align="center" valign="middle" >Default</th><th align="center" valign="middle" >Value</th></tr></thead><tr><td align="center" valign="middle" >[winf] pH</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >7.0</td><td align="center" valign="middle" >11.48</td></tr><tr><td align="center" valign="middle" >[winf] total BOD</td><td align="center" valign="middle" >g/m<sup>3</sup></td><td align="center" valign="middle" >87.0</td><td align="center" valign="middle" >93.3</td></tr><tr><td align="center" valign="middle" >[winf] turbidity</td><td align="center" valign="middle" >NTU</td><td align="center" valign="middle" >78.0</td><td align="center" valign="middle" >108.0</td></tr><tr><td align="center" valign="middle" >[winf] total nitrogen</td><td align="center" valign="middle" >mgN/L</td><td align="center" valign="middle" >43.0</td><td align="center" valign="middle" >112.9</td></tr><tr><td align="center" valign="middle" >[winf] fraction inert soluble organic nitrogen</td><td align="center" valign="middle" >gN/gCOD</td><td align="center" valign="middle" >0.05</td><td align="center" valign="middle" >0.24</td></tr><tr><td align="center" valign="middle" >[winf] fraction inert soluble organic phosphorus</td><td align="center" valign="middle" >gP/gCOD</td><td align="center" valign="middle" >0.01</td><td align="center" valign="middle" >0.0167</td></tr><tr><td align="center" valign="middle" >[winf] nitrate</td><td align="center" valign="middle" >gNO<sub>3</sub>-N/m<sup>3</sup></td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >2.3</td></tr><tr><td align="center" valign="middle" >[winf] sulfatesulfur</td><td align="center" valign="middle" >gSO<sub>4</sub>-S/m<sup>3</sup></td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >50.311</td></tr><tr><td align="center" valign="middle" >[winf] chloride</td><td align="center" valign="middle" >gCl/m<sup>3</sup></td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >8.6</td></tr><tr><td align="center" valign="middle" >[winf] copper</td><td align="center" valign="middle" >gCu/m<sup>3</sup></td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >6.0</td></tr><tr><td align="center" valign="middle" >[winf] other cations</td><td align="center" valign="middle" >eq/m<sup>3</sup></td><td align="center" valign="middle" >3.0</td><td align="center" valign="middle" >42.0</td></tr><tr><td align="center" valign="middle" >[winf] ammonia nitrogen</td><td align="center" valign="middle" >gNH<sup>4</sup>-N/m<sup>3</sup></td><td align="center" valign="middle" >25.0</td><td align="center" valign="middle" >5.6</td></tr><tr><td align="center" valign="middle" >[winf] unit price of water</td><td align="center" valign="middle" >$/m<sup>3</sup></td><td align="center" valign="middle" >2.0</td><td align="center" valign="middle" >6.5</td></tr><tr><td align="center" valign="middle" >[winf] influent flow</td><td align="center" valign="middle" >m<sup>3</sup>/hr</td><td align="center" valign="middle" >83.3333</td><td align="center" valign="middle" >45.0</td></tr></tbody></table></table-wrap><p>Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Dissolved Solids (TDS), Electric Conductivity (EC), Sulphates, Turbidity, Total Phosphorus (T/ PO 4 − ), Residual Chlorine, Nitrate (NO<sub>3</sub>), Total Nitrogen (TN), Total Suspended Solids (TSS), Colour, pH, Urea, NH<sub>3</sub> and heavy metals (Cu, Cd, Cr, Pb, Ni and Fe). Results are shown in figures that compare the outfall effluent of the urea fertilizer business to Federal Environmental Protection Agency (FEPA) criteria from 1991.</p><p>Sample 1’s color was a pale shade of blackish white, while sample 2 was found to be colorless. The fertilizer factory outfall effluent (sample 2) recorded high concentrations for all the water quality physicochemical parameters, and these concentrations are higher than the FEPA (1991) standard, with the exception of TSS, PO 4 − , SO 4 − , and NO 3 − . Temperature and pH were determined from sample 2 analysis to be 41˚C and 9.7, respectively. Because it has an impact on aquatic life, the outfall effluent temperature is a crucial variable. An abrupt change in temperature may lead to a high mortality rate for aquatic species [<xref ref-type="bibr" rid="scirp.127428-ref1">1</xref>] . In rivers, streams, and canals, high pH wastewater has the potential to reduce the solubility and toxicity of pollutants, which could have an impact on aquatic life (Umer et al., 2017) [<xref ref-type="bibr" rid="scirp.127428-ref7">7</xref>] . High pH wastewater can also promote the solubility of many important elements, such as Selenium (Se), in place of Mn, Cd, Al, B, Hg, and Cd. Additionally, high urea and NH<sub>3</sub> concentrations of the process condensates from the urea plant, ammonia plants, and from the sanitary sewage system following organic matter decomposition are connected with high pH values of the</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Simulation value for variables used in characterization of process model objects</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Process Model Objects</th><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >Unit</th><th align="center" valign="middle" >Value</th><th align="center" valign="middle" >Process Model Objects</th><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >Unit</th><th align="center" valign="middle" >Value</th></tr></thead><tr><td align="center" valign="middle" >Anoxic Tank-1</td><td align="center" valign="middle" >Maximum Volume Tank Depth Pumped Flow Initial Reactor Volume Start with Full Tank</td><td align="center" valign="middle" >m<sup>3</sup> m m<sup>3</sup>/hr m<sup>3</sup></td><td align="center" valign="middle" >307.2 6.0 170.0 270.0 Off</td><td align="center" valign="middle" >Air Blower</td><td align="center" valign="middle" >Solids Capture Rate Flowrate</td><td align="center" valign="middle" >% Nm<sup>3</sup>/hr</td><td align="center" valign="middle" >95.0 650</td></tr><tr><td align="center" valign="middle" >Aeration Tank-1</td><td align="center" valign="middle" >Tank Depth Maximum Volume Pumped Flow</td><td align="center" valign="middle" >M m<sup>3</sup> m<sup>3</sup>/hr</td><td align="center" valign="middle" >6.0 328.0 70.0</td><td align="center" valign="middle" >Clarifier</td><td align="center" valign="middle" >Surface Area Depth Pumped Flow Sludge Disposal Cost</td><td align="center" valign="middle" >m<sup>2</sup> m m<sup>3</sup>/hr $/m<sup>3</sup></td><td align="center" valign="middle" >44.8 3.5 70.0 553.6</td></tr><tr><td align="center" valign="middle" >CH<sub>3</sub>COOH Dosing</td><td align="center" valign="middle" >Chemical Purity Cost of Chemical Flowrate</td><td align="center" valign="middle" >% $/kg L/hr</td><td align="center" valign="middle" >45.0 1.03 31.0</td><td align="center" valign="middle" >Polymer Dosing</td><td align="center" valign="middle" >Use Local Temperature Local Liquid Temp. Chemical Type Chem. Dosage, in Mass Chemical Purity Cost of Chemical</td><td align="center" valign="middle" >C Kg/hr % $/ kg</td><td align="center" valign="middle" >On 21.0 PAC-Al<sub>2</sub>(OH)n cl(6n) 450.0 0.2 2.0</td></tr><tr><td align="center" valign="middle" >NaOH Dosing</td><td align="center" valign="middle" >Use Local Temperature Local Liquid Temp. Chemical Purity Cost of Chemical Flowrate</td><td align="center" valign="middle" >C % $/KG L/hr</td><td align="center" valign="middle" >On 21.0 50.0 0.42 6.0</td><td align="center" valign="middle" >Sludge Buffer Sump</td><td align="center" valign="middle" >Maximum Volume Tank Depth Pumped Flow Initial Reactor Volume Start with Full Tank</td><td align="center" valign="middle" >m<sup>3</sup> m m<sup>3</sup>/hr m3</td><td align="center" valign="middle" >230.0 6.0 70.0 192.0 Off</td></tr><tr><td align="center" valign="middle" >Anoxic Tank-2</td><td align="center" valign="middle" >Maximum Volume Tank Depth Initial Reactor Volume Start with Full Tank</td><td align="center" valign="middle" >m<sup>3</sup> m m<sup>3</sup></td><td align="center" valign="middle" >153.6 6.0 140.0 0ff</td><td align="center" valign="middle" >Sludge Thickener</td><td align="center" valign="middle" >Surface Area Depth Pumped Flow Sludge Disposal Cost</td><td align="center" valign="middle" >m<sup>3</sup> m m<sup>3</sup>/hr $/m<sup>3</sup></td><td align="center" valign="middle" >18.5 3.5 19.0 553.6</td></tr><tr><td align="center" valign="middle" >Aeration Tank-2</td><td align="center" valign="middle" >Tank Depth Maximum Volume Pumped Flow</td><td align="center" valign="middle" >M m<sup>3</sup> m<sup>3</sup>/hr</td><td align="center" valign="middle" >6.0 140.0 170.0</td><td align="center" valign="middle" >Sludge Centrifuge</td><td align="center" valign="middle" >Pumped Flow Sludge Disposal Cost</td><td align="center" valign="middle" >m<sup>3</sup>/hr $/m<sup>3</sup></td><td align="center" valign="middle" >1.75 553.5</td></tr><tr><td align="center" valign="middle" >FeCl<sub>3</sub> Dosing</td><td align="center" valign="middle" >Chem. Dosage, in Mass Chemical Purity Cost of Chemical</td><td align="center" valign="middle" >Kg/hr % $/kg</td><td align="center" valign="middle" >7197 40 0.26</td><td align="center" valign="middle" >NaOCl Dosing</td><td align="center" valign="middle" >Use Local Temperature Local Liquid Temp. Chemical Type Chemical Purity Cost of Chemical Flowrate</td><td align="center" valign="middle" >C % $/kg L/hr</td><td align="center" valign="middle" >On 22.0 Sodium Hypochlorite 10.0 0.16 10.0</td></tr><tr><td align="center" valign="middle" >Treated Wastewater</td><td align="center" valign="middle" >Maximum TDS Max. Total Hardness</td><td align="center" valign="middle" >mg/L mg/L</td><td align="center" valign="middle" >30.0 120.0</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Sludge Disposal</td><td align="center" valign="middle" >Sludge Disposal Cost</td><td align="center" valign="middle" >$/tonne</td><td align="center" valign="middle" >55.36</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >System</td><td align="center" valign="middle" >Ratio of Soluble BOD to soluble COD Liquid Temperature Blower Inlet Air Temp.</td><td align="center" valign="middle" >% C C</td><td align="center" valign="middle" >93.3 43.0 32.0</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>outfall effluent. The pH of natural waters is a crucial quality indicator [<xref ref-type="bibr" rid="scirp.127428-ref1">1</xref>] . Salts are present in the samples, as determined by the measurements of EC and TDS. The EC and TDS values of the outfall effluent were measured to be 5848 S/cm and 2658.18 mg/l, respectively. These values are higher than the FEPA standard of less than 1000 μS/cm and 2000 mg/l in reported in the [<xref ref-type="bibr" rid="scirp.127428-ref7">7</xref>] , indicating their propensity to increase the salinity level of water bodies, which can have detrimental ecological effects on aquatic biota. High solubility compounds in aquatic environments may also slow down the rate of sunlight penetration into aquatic microsystems, which would otherwise have been a key factor in the emergence of photosynthetic organisms [<xref ref-type="bibr" rid="scirp.127428-ref7">7</xref>] . However, a high concentration of conducting particles in the effluent from production processes and chemical spills may be to blame for the small rise in EC and TDS [<xref ref-type="bibr" rid="scirp.127428-ref1">1</xref>] . The outfall effluent’s turbidity was estimated to be 267 NTU, exceeding the FEPA requirement of 100 NTU. High turbidity can affect aquatic life, raise the expense of treating drinking water, and have a negative effect on tourism and recreation, greater turbidity of wastewater correlated with greater conductivity, and vice versa.</p><p><xref ref-type="fig" rid="fig6">Figure 6</xref>(a) and <xref ref-type="fig" rid="fig6">Figure 6</xref>(b) shows that the outlet effluent’s concentrations of urea, ammonia, phosphates, sulfates, nitrates, and total nitrogen were 219 mg/l, 20 mg/l, 0.358 mg/l, 26.80 mg/l, 1.70 mg/l, and 2.80 mg/l, respectively. The results of the current analysis show that the effluent quality of fertilizers is poor and that inorganic elements are present in considerable concentrations. The levels of urea, ammonia, and T/N are over the FEPA’s acceptable limits of 100 mg/l, 0 - 5 mg/l, and 0.6 mg/l, respectively. The lagoon’s water quality has greatly decreased as a result of this. High quantities of (NH<sub>2</sub>)<sub>2</sub>CO and NH<sub>3</sub> in process condensates from the urea plant and the ammonia plant, which were improperly hydrolyzed or stripped, are linked to the high values. Excretory materials from the sanitary sewage system and seal leakage from ammonia pumps may both cause a high level of NH<sub>3</sub> to appear in the outfall effluent. (Obire, Ogan, &amp; Okigbo, 2008) stated that high concentrations of (NH<sub>2</sub>)<sub>2</sub>CO and NH<sub>3</sub>may have an effect on available trace metals that brings about detrimental or beneficial effect and also cause eutrophication issues on water. These activities include urea synthesis, housekeeping activity, and granulation section cleaning that dispose/discharge urea granules into open drains. When nitrogen is released into the environment above the necessary level, it may have undesirable consequences on the environment’s ecology and human health [<xref ref-type="bibr" rid="scirp.127428-ref18">18</xref>] . In order to maintain oxidation (degradation) of the available nutrients and support the typical spectrum of aquatic life, the available dissolved oxygen (DO) must be used [<xref ref-type="bibr" rid="scirp.127428-ref1">1</xref>] .</p><p>The calculated biological and chemical oxygen demands were 91.7 mg/l and 116.7 mg/l, respectively. <xref ref-type="fig" rid="fig6">Figure 6</xref>(c) demonstrates that despite the normally low amounts, both samples have BOD and COD levels that are greater than the FEPA’s recommended limits of 30 mg/l for each.</p><p>According to Umer et al. (2017), high BOD and COD of effluent samples indicate that organic and inorganic matter is present in the fertilizer effluent</p><p>sample in high concentration, suggesting the possibility that the sample could enhance algal blooms and destabilize aquatic systems due to the high amount of nutrients present. The rate at which oxygen is used up in the stream increases with BOD. Similar to low dissolved oxygen levels, too much BOD stresses aquatic life, suffocates it, and ultimately kills it.</p><p>According to <xref ref-type="fig" rid="fig6">Figure 6</xref>(d), the amounts of Cd, Cr, Cu, Fe, Pb, and Ni in the fertilizer outfall effluent sample were 1.7 mg/l, 5.1 mg/l, 4.6 mg/l, 2.0 mg/l, 9.2 mg/l, and 4.7 mg/l, respectively. Except for the Fe concentration, which was not as high as observed in other detected heavy metals, the results of all heavy metals detected show concentrations exceeding the FEPA recommended values of the release of heavy metals into the environment. This suggests that the fertilizer plant’s piping system is sufficiently protected from corroding by chemical and biological actions. Metal and non-metal ion concentrations in aquatic environments have been shown to impact the metabolism of higher creatures and bacteria in seawater. These ions, particularly cations, are hazardous to aquatic life at varying levels. This can be caused by the impact of soluble elements in the effluent generated by the overall functioning of the fertilizer plant. Lead is a toxic metal that can harm the liver and kidneys. Chromium in its hexavalent form is extremely toxic because it has the ability to cross cell membranes and interact with genetic materials after being reduced to trivalent form, which is what causes its mutagenic and toxic effects. As a result, the effluent from the fertilizer outfall can be deemed inappropriate for environmental release (Umer et al., 2017). When applied to the soil, high iron concentrations in wastewater can cause soil acidity and lower the amount of molybdenum and phosphorus that is readily available. When copper concentrations rise slightly over those needed as a micronutrient, they become hazardous, especially to marine invertebrate larvae [<xref ref-type="bibr" rid="scirp.127428-ref19">19</xref>] .</p></sec><sec id="s3_2"><title>3.2. GPS* Modelling and Simulation Result</title><p>The model layout was built due to what is obtainable from <xref ref-type="fig" rid="fig1">Figure 1</xref>, the process model objects were calibrated as per the data extracted from the Biological Treatment and Sludge Handling Package design manual and data sheet used in the fertilizer plant, and the influent was characterized using the physicochemical parameters got from the analyzed influent sample. From the process simulation of the wastewater treatment, the analysis of results revealing the chemical analysis of the effluents is shown in <xref ref-type="table" rid="table4">Table 4</xref>. Hence, the treated water simulation results clearly showed high reduction in BOD and COD concentration by 36% and 54.5% respectively, total nitrogen (TN), Nitrate-N and total phosphorus (TP) were also seen to be within the permissible FEPA standard as can be seen in <xref ref-type="table" rid="table4">Table 4</xref>. Acetic acid and sodium hydroxide flow rates were used as the output variables to investigate the effects of changes in the influent flow rates on the plant effluent qualities. On increasing the acetic acid dosage at 45 L/hr, 60 L/hr, 75 L/hr and 90 L/hr into anoxic tank-1 and keeping sodium hydroxide flow at 6 m<sup>3</sup>/hr, some changes in the treated water simulation results were observed.</p><p>As the acid flow rate increases and more simulations are run, a continuous concentration decrease was seen in the TSS, BOD, COD, Volatile Suspended</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Treated wastewater simulation results. Source: (GPS*, version 8.0)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >Unit</th><th align="center" valign="middle" >Value</th></tr></thead><tr><td align="center" valign="middle" >Flow</td><td align="center" valign="middle" >m<sup>3</sup>/d</td><td align="center" valign="middle" >2400</td></tr><tr><td align="center" valign="middle" >TSS</td><td align="center" valign="middle" >mg/L</td><td align="center" valign="middle" >3570</td></tr><tr><td align="center" valign="middle" >VSS</td><td align="center" valign="middle" >mg/L</td><td align="center" valign="middle" >1.166</td></tr><tr><td align="center" valign="middle" >cBOD<sub>5</sub></td><td align="center" valign="middle" >mg/L</td><td align="center" valign="middle" >33.37</td></tr><tr><td align="center" valign="middle" >COD</td><td align="center" valign="middle" >mg/L</td><td align="center" valign="middle" >63.64</td></tr><tr><td align="center" valign="middle" >Ammonia N</td><td align="center" valign="middle" >mgN/L</td><td align="center" valign="middle" >3.342</td></tr><tr><td align="center" valign="middle" >Nitrite N</td><td align="center" valign="middle" >mgN/L</td><td align="center" valign="middle" >2.233</td></tr><tr><td align="center" valign="middle" >Nitrate N</td><td align="center" valign="middle" >mgN/L</td><td align="center" valign="middle" >2.029</td></tr><tr><td align="center" valign="middle" >TKN</td><td align="center" valign="middle" >mgN/L</td><td align="center" valign="middle" >81.67</td></tr><tr><td align="center" valign="middle" >TN</td><td align="center" valign="middle" >mgN/L</td><td align="center" valign="middle" >85.93</td></tr><tr><td align="center" valign="middle" >Soluble PO<sub>4</sub>-P</td><td align="center" valign="middle" >mgP/L</td><td align="center" valign="middle" >1.964e−10</td></tr><tr><td align="center" valign="middle" >TP</td><td align="center" valign="middle" >mgP/L</td><td align="center" valign="middle" >0.576</td></tr><tr><td align="center" valign="middle" >Total Alkalinity</td><td align="center" valign="middle" >mgCaCO<sub>3</sub>/L</td><td align="center" valign="middle" >62,590</td></tr><tr><td align="center" valign="middle" >pH</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >14.0</td></tr><tr><td align="center" valign="middle" >DO</td><td align="center" valign="middle" >mgO<sub>2</sub>/L</td><td align="center" valign="middle" >0.0</td></tr></tbody></table></table-wrap><p>Solids (VSS), Ammonia-N, Total Kjeldahl Nitrogen (TKN), Nitrate-N and Total Phosphorus in the treated water simulation results as shown in <xref ref-type="table" rid="table5">Table 5</xref> below. Hence, this indicates a proportional relationship with acid flow rate and the waste-water treatment performance.</p><p>Similarly, on increasing the sodium hydroxide dosage at 9 m<sup>3</sup>/hr, 12 m<sup>3</sup>/hr, 15 m<sup>3</sup>/hr and 18 m<sup>3</sup>/hr into the aeration tank-1 and keeping acetic acid flow at 31 L/hr, some changes on the treated water simulation results were observed. As the sodium hydroxide flow rate increases and more simulations are run, even though, continuous concentration decrease was observed in total alkalinity but, a continuous concentration decrease was sighted in the TSS, BOD, COD, Volatile Suspended Solids (VSS), Ammonia-N, Total Kjeldahl Nitrogen (TKN), Nitrate-N and Total Phosphorus in the treated water simulation results as shown in <xref ref-type="table" rid="table6">Table 6</xref>.</p><p>Also, on increasing both sodium hydroxide dosage at 9 m<sup>3</sup>/hr, 12 m<sup>3</sup>/hr, 15 m<sup>3</sup>/hr and 18 m<sup>3</sup>/hr into the aeration tank-1 and acetic acid flow at 45 l/hr, 60 l/hr, 75 l/hr and 90 l/hr into anoxic tank-1, some changes on the treated water simulation results were observed. As the flow rate of both chemicals increases with corresponding values and more simulations are run, even though, continuous concentration decrease was sighted in total alkalinity and Nitrate-N but, a continuous concentration decrease was observed in the TSS, BOD, COD, Volatile Suspended Solids (VSS), Ammonia-N, Total Kjeldahl Nitrogen (TKN) and Total Phosphorus in the treated water simulation results as shown in <xref ref-type="table" rid="table7">Table 7</xref>.</p><p>However, no significant change was observed in all the three scenarios as</p><table-wrap id="table5" ><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> Treated water simulation results with increasing acetic acid dose at 6 m<sup>3</sup>/hr dose of sodium hydroxide</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Acetic Acid Flow (L/hr)</th><th align="center" valign="middle" >31.0</th><th align="center" valign="middle" >45.0</th><th align="center" valign="middle" >60.0</th><th align="center" valign="middle" >75.0</th><th align="center" valign="middle" >90.0</th></tr></thead><tr><td align="center" valign="middle" >pH</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td></tr><tr><td align="center" valign="middle" >Total Alkali (mgCaCO<sub>3</sub>/L)</td><td align="center" valign="middle" >62,590</td><td align="center" valign="middle" >64,490</td><td align="center" valign="middle" >62,980</td><td align="center" valign="middle" >63,150</td><td align="center" valign="middle" >63,100</td></tr><tr><td align="center" valign="middle" >TSS (mg/L)</td><td align="center" valign="middle" >3570</td><td align="center" valign="middle" >3560</td><td align="center" valign="middle" >3995</td><td align="center" valign="middle" >3990</td><td align="center" valign="middle" >3988</td></tr><tr><td align="center" valign="middle" >cBOD<sub>5</sub> (mg/L)</td><td align="center" valign="middle" >33.37</td><td align="center" valign="middle" >33.36</td><td align="center" valign="middle" >33.35</td><td align="center" valign="middle" >33.34</td><td align="center" valign="middle" >33.33</td></tr><tr><td align="center" valign="middle" >VSS (mg/L)</td><td align="center" valign="middle" >1.166</td><td align="center" valign="middle" >1.162</td><td align="center" valign="middle" >1.161</td><td align="center" valign="middle" >1.161</td><td align="center" valign="middle" >1.160</td></tr><tr><td align="center" valign="middle" >COD (mg/L)</td><td align="center" valign="middle" >63.64</td><td align="center" valign="middle" >63.62</td><td align="center" valign="middle" >63.60</td><td align="center" valign="middle" >63.58</td><td align="center" valign="middle" >63.56</td></tr><tr><td align="center" valign="middle" >DO (mgO<sub>2</sub>/L)</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td></tr><tr><td align="center" valign="middle" >Ammonia-N (mgN/L)</td><td align="center" valign="middle" >3.342</td><td align="center" valign="middle" >4.936</td><td align="center" valign="middle" >4.934</td><td align="center" valign="middle" >4.933</td><td align="center" valign="middle" >4.932</td></tr><tr><td align="center" valign="middle" >TKN (mgN/L)</td><td align="center" valign="middle" >81.67</td><td align="center" valign="middle" >83.23</td><td align="center" valign="middle" >83.20</td><td align="center" valign="middle" >83.18</td><td align="center" valign="middle" >83.16</td></tr><tr><td align="center" valign="middle" >Nitrite-N ( NO 2 − ) (mgN/L)</td><td align="center" valign="middle" >2.233</td><td align="center" valign="middle" >5.23 &#215; 10<sup>−10 </sup></td><td align="center" valign="middle" >1.10 &#215; 10<sup>−10 </sup></td><td align="center" valign="middle" >1.01 &#215; 10<sup>−10 </sup></td><td align="center" valign="middle" >1.10 &#215; 10<sup>−10 </sup></td></tr><tr><td align="center" valign="middle" >TN (mgN/L)</td><td align="center" valign="middle" >85.93</td><td align="center" valign="middle" >85.26</td><td align="center" valign="middle" >85.23</td><td align="center" valign="middle" >85.21</td><td align="center" valign="middle" >85.18</td></tr><tr><td align="center" valign="middle" >TP (mgP/L)</td><td align="center" valign="middle" >0.5760</td><td align="center" valign="middle" >0.5757</td><td align="center" valign="middle" >85.5755</td><td align="center" valign="middle" >0.5753</td><td align="center" valign="middle" >0.5751</td></tr><tr><td align="center" valign="middle" >Nitrate-N ( NO 3 − ) (mgN/L)</td><td align="center" valign="middle" >2.029</td><td align="center" valign="middle" >2.027</td><td align="center" valign="middle" >2.027</td><td align="center" valign="middle" >2.026</td><td align="center" valign="middle" >2.025</td></tr><tr><td align="center" valign="middle" >Soluble PO<sub>4</sub>-P (mgP/L)_</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td></tr></tbody></table></table-wrap><table-wrap id="table6" ><label><xref ref-type="table" rid="table6">Table 6</xref></label><caption><title> Treated water simulation results with increasing sodium hydroxide dose at 31 L/hr dose of acetic acid</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sodium Hydroxide Flow (m<sup>3</sup>/hr)</th><th align="center" valign="middle" >6.0</th><th align="center" valign="middle" >9.0</th><th align="center" valign="middle" >12.0</th><th align="center" valign="middle" >15.0</th><th align="center" valign="middle" >18.0</th></tr></thead><tr><td align="center" valign="middle" >P<sup>H</sup></td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td></tr><tr><td align="center" valign="middle" >Total Alkali (mgCaCO<sub>3</sub>/L)</td><td align="center" valign="middle" >62,590</td><td align="center" valign="middle" >87,080</td><td align="center" valign="middle" >108,700</td><td align="center" valign="middle" >127,900</td><td align="center" valign="middle" >145,400</td></tr><tr><td align="center" valign="middle" >TSS (mg/L)</td><td align="center" valign="middle" >3570</td><td align="center" valign="middle" >4207</td><td align="center" valign="middle" >3895</td><td align="center" valign="middle" >3627</td><td align="center" valign="middle" >3393</td></tr><tr><td align="center" valign="middle" >cBOD<sub>5</sub> (mg/L)</td><td align="center" valign="middle" >33.37</td><td align="center" valign="middle" >31.50</td><td align="center" valign="middle" >29.83</td><td align="center" valign="middle" >28.32</td><td align="center" valign="middle" >26.96</td></tr><tr><td align="center" valign="middle" >VSS (mg/L)</td><td align="center" valign="middle" >1.166</td><td align="center" valign="middle" >1.046</td><td align="center" valign="middle" >0.9513</td><td align="center" valign="middle" >0.872</td><td align="center" valign="middle" >0.8049</td></tr><tr><td align="center" valign="middle" >COD (mg/L)</td><td align="center" valign="middle" >63.64</td><td align="center" valign="middle" >60.02</td><td align="center" valign="middle" >56.79</td><td align="center" valign="middle" >53.90</td><td align="center" valign="middle" >51.30</td></tr><tr><td align="center" valign="middle" >DO (mgO<sub>2</sub>/L)</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td></tr><tr><td align="center" valign="middle" >Ammonia-N (mgN/L)</td><td align="center" valign="middle" >3.342</td><td align="center" valign="middle" >4.663</td><td align="center" valign="middle" >4.418</td><td align="center" valign="middle" >4.197</td><td align="center" valign="middle" >3.997</td></tr><tr><td align="center" valign="middle" >TKN (mgN/L)</td><td align="center" valign="middle" >81.67</td><td align="center" valign="middle" >78.62</td><td align="center" valign="middle" >74.48</td><td align="center" valign="middle" >72.48</td><td align="center" valign="middle" >67.39</td></tr><tr><td align="center" valign="middle" >Nitrite-N ( NO 2 − ) (mgN/L)</td><td align="center" valign="middle" >2.233</td><td align="center" valign="middle" >1.01 &#215; 10<sup>−10 </sup></td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >1.42 &#215; 10<sup>−10</sup></td></tr><tr><td align="center" valign="middle" >TN (mgN/L)</td><td align="center" valign="middle" >85.93</td><td align="center" valign="middle" >80.54</td><td align="center" valign="middle" >76.30</td><td align="center" valign="middle" >72.48</td><td align="center" valign="middle" >69.03</td></tr><tr><td align="center" valign="middle" >TP (mgP/L)</td><td align="center" valign="middle" >0.576</td><td align="center" valign="middle" >0.532</td><td align="center" valign="middle" >0.505</td><td align="center" valign="middle" >0.476</td><td align="center" valign="middle" >0.451</td></tr><tr><td align="center" valign="middle" >Nitrate-N ( NO 3 − ) (mgN/L)</td><td align="center" valign="middle" >2.029</td><td align="center" valign="middle" >1.915</td><td align="center" valign="middle" >1.815</td><td align="center" valign="middle" >1.724</td><td align="center" valign="middle" >1.642</td></tr><tr><td align="center" valign="middle" >Soluble PO<sub>4</sub>-P (mgP/L)_</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td></tr></tbody></table></table-wrap><p>regard Dissolve oxygen (DO), soluble PO<sub>4</sub>-P and P<sup>H</sup>, this could be owing to the fact that limited parameters were used in characterizing the influent causing most required parameters to run on default. Another factor may be that the acid dosage flow rate is not sufficient enough to bring down the P<sup>H</sup> and alkalinity concentration of the treated water.</p><table-wrap id="table7" ><label><xref ref-type="table" rid="table7">Table 7</xref></label><caption><title> Treated water simulation results with increasing both sodium hydroxide and acetic acid dose</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Acetic Acid Flow (L/hr)</th><th align="center" valign="middle" >31.0</th><th align="center" valign="middle" >45.0</th><th align="center" valign="middle" >60.0</th><th align="center" valign="middle" >75.0</th><th align="center" valign="middle" >90.0</th></tr></thead><tr><td align="center" valign="middle" >Sodium Hydroxide Flow (m<sup>3</sup>/hr)</td><td align="center" valign="middle" >6.0</td><td align="center" valign="middle" >9.0</td><td align="center" valign="middle" >12.0</td><td align="center" valign="middle" >15.0</td><td align="center" valign="middle" >18.0</td></tr><tr><td align="center" valign="middle" >P<sup>H</sup></td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td><td align="center" valign="middle" >14.0</td></tr><tr><td align="center" valign="middle" >Total Alkali (mgCaCO<sub>3</sub>/L)</td><td align="center" valign="middle" >62,590</td><td align="center" valign="middle" >87,740</td><td align="center" valign="middle" >110,200</td><td align="center" valign="middle" >127,800</td><td align="center" valign="middle" >145,400</td></tr><tr><td align="center" valign="middle" >TSS (mg/L)</td><td align="center" valign="middle" >3570</td><td align="center" valign="middle" >4205</td><td align="center" valign="middle" >3892</td><td align="center" valign="middle" >3315</td><td align="center" valign="middle" >3389</td></tr><tr><td align="center" valign="middle" >cBOD<sub>5</sub> (mg/L)</td><td align="center" valign="middle" >33.37</td><td align="center" valign="middle" >31.49</td><td align="center" valign="middle" >29.81</td><td align="center" valign="middle" >28.30</td><td align="center" valign="middle" >26.94</td></tr><tr><td align="center" valign="middle" >VSS (mg/L)</td><td align="center" valign="middle" >1.166</td><td align="center" valign="middle" >1.046</td><td align="center" valign="middle" >0.9504</td><td align="center" valign="middle" >0.8709</td><td align="center" valign="middle" >0.8037</td></tr><tr><td align="center" valign="middle" >COD (mg/L)</td><td align="center" valign="middle" >63.64</td><td align="center" valign="middle" >60.00</td><td align="center" valign="middle" >56.76</td><td align="center" valign="middle" >53.86</td><td align="center" valign="middle" >51.25</td></tr><tr><td align="center" valign="middle" >DO (mgO<sub>2</sub>/L)</td><td align="center" valign="middle" >0.00</td><td align="center" valign="middle" >0.00</td><td align="center" valign="middle" >0.00</td><td align="center" valign="middle" >4.07</td><td align="center" valign="middle" >0.00</td></tr><tr><td align="center" valign="middle" >Ammonia-N (mgN/L)</td><td align="center" valign="middle" >3.342</td><td align="center" valign="middle" >4.662</td><td align="center" valign="middle" >4.416</td><td align="center" valign="middle" >4.194</td><td align="center" valign="middle" >3.994</td></tr><tr><td align="center" valign="middle" >TKN (mgN/L)</td><td align="center" valign="middle" >81.67</td><td align="center" valign="middle" >78.60</td><td align="center" valign="middle" >74.45</td><td align="center" valign="middle" >70.71</td><td align="center" valign="middle" >67.33</td></tr><tr><td align="center" valign="middle" >Nitrite-N ( NO 2 − ) (mgN/L)</td><td align="center" valign="middle" >2.233</td><td align="center" valign="middle" >1.04 &#215; 10<sup>−10 </sup></td><td align="center" valign="middle" >3.34 &#215; 10<sup>−10</sup></td><td align="center" valign="middle" >4.16 &#215; 10<sup>−10</sup></td><td align="center" valign="middle" >1.04 &#215; 10<sup>−10</sup></td></tr><tr><td align="center" valign="middle" >TN (mgN/L)</td><td align="center" valign="middle" >85.93</td><td align="center" valign="middle" >80.52</td><td align="center" valign="middle" >76.26</td><td align="center" valign="middle" >72.43</td><td align="center" valign="middle" >68.97</td></tr><tr><td align="center" valign="middle" >TP (mgP/L)</td><td align="center" valign="middle" >0.576</td><td align="center" valign="middle" >1.915</td><td align="center" valign="middle" >1.814</td><td align="center" valign="middle" >1.723</td><td align="center" valign="middle" >1.640</td></tr><tr><td align="center" valign="middle" >Nitrate-N ( NO 3 − ) (mgN/L)</td><td align="center" valign="middle" >2.233</td><td align="center" valign="middle" >1.915</td><td align="center" valign="middle" >1.814</td><td align="center" valign="middle" >1.723</td><td align="center" valign="middle" >1.640</td></tr><tr><td align="center" valign="middle" >Soluble PO<sub>4</sub>-P (mgP/L)_</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td><td align="center" valign="middle" >0.0</td></tr></tbody></table></table-wrap></sec></sec><sec id="s4"><title>4. Conclusion</title><p>The physicochemical characterization of influent and outfall effluent samples collected from a urea fertilizer plant was conducted and the parameters measured from outfall effluent were compared with Federal Environmental Protection Agency (FEPA) standard. While TSS, PO 4 − , SO 4 − and NO<sub>3</sub> values were found within the permissible limits, the pH, temperature, COD, BOD, TDS, EC, Turbidity, Residual Chlorine, TN, Colour, Urea, NH<sub>3</sub> and heavy metals ions (Cu, Cd, Cr, Pb, Ni and Fe) recorded concentration values higher than recommended standards. Results showed that a proper treatment of fertilizer industries effluents is required prior to discharge into the environment. However, using modelling and simulation software (GPS-X, version 8.0), a biological treatment upgrade of the physicochemical parameters obtained from the analyzed influent sample was performed. The treated water simulation results clearly showed a high reduction in cBOD<sub>5</sub> and COD concentration by 35% and 44% respectively. A continuous concentration decrease was also observed in the TSS, Volatile Suspended Solids (VSS), Ammonia-N, Total Kjeldahl Nitrogen (TKN), Nitrate-N and Total Phosphorus on increasing the acetic acid and sodium hydroxide dosage and running more simulations. Results showed that a proper treatment of fertilizer industries effluents is required prior to discharge into the environment.</p></sec><sec id="s5"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s6"><title>Cite this paper</title><p>Ahmad, I., Akintola, J.T., Patinvoh, R.J., Ekpotu, W.F., Obialor, M.C. and Udom, P.C. (2023) Systematic Biological Upgrade of a Urea Fertilizer Effluent Treatment Plant Using GPS. Open Journal of Applied Sciences, 13, 1457-1477. https://doi.org/10.4236/ojapps.2023.138116</p></sec></body><back><ref-list><title>References</title><ref id="scirp.127428-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Obire, O., Ogan, A. and Okigbo, R.N. (2008) Impact of Fertilizer Plant Effluent on Water Quality. International Journal of Environmental, Science and Technology, 5, 107-118. https://doi.org/10.1007/BF03326003</mixed-citation></ref><ref id="scirp.127428-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Leakovi&amp;#263;, S., Mijatovi&amp;#263;, I., Cerjan-Stefanovi&amp;#263;, S. and Hod&amp;#382;i&amp;#263;, E. (2000) Nitrogen Removal from Fertilizer Wastewater by Ion Exchange. Water Research, 34, 185-190. https://doi.org/10.1016/S0043-1354(99)00122-0</mixed-citation></ref><ref id="scirp.127428-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Singh, R., Andaluri, G. and Pandey, V.C. (2022) Cities’ Water Pollution—Challenges and Controls. Algae and Aquatic Macrophytes in Cities, Bioremediation, Biomass, Biofuels and Bioproducts, 3-22. https://doi.org/10.1016/B978-0-12-824270-4.00015-8</mixed-citation></ref><ref id="scirp.127428-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Mallik, A., Arefin, A. and Shahadat, M.M.Z. (2018) Design and Feasibility Analysis of a Low-Cost Water Treatment Plant for Rural Regions of Bangladesh. AIMS Agriculture and Food, 3, 181-204. https://doi.org/10.3934/agrfood.2018.3.181</mixed-citation></ref><ref id="scirp.127428-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Jasim, N.A. and Aziz, H.A. (2020) The Design of Wastewater Treatment Plant (WWTP) with GPSX Modelling. Cogent Engineering, 7, Article: 1723782. https://doi.org/10.1080/23311916.2020.1723782</mixed-citation></ref><ref id="scirp.127428-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Bhandari, V.M., Sorokhaibam, L.G. and Ranade, V.V. (2016) Industrial Wastewater Treatment for Fertilizer Industry—A Case Study. Desalination and Water Treatment, 57, 27934-27944. https://doi.org/10.1080/19443994.2016.1186399</mixed-citation></ref><ref id="scirp.127428-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Umer, Y., Shahid, I., Asif, S., Munawar, I., Arif, N. and Sajida, N. (2017) Fertilizer Industrial Effluents: Physicochemical Characterization and Water Quality Parameters Evaluation. Acta Ecologica Sinica, 37, 236-239. https://doi.org/10.1016/j.chnaes.2017.02.002</mixed-citation></ref><ref id="scirp.127428-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Namasivayam, C., Sangeetha, D. and Gunasekaran, R. (2007) Removal of Anions, Heavy Metals, Organics and Dyes from Water by Adsorption onto a New Activated Carbon from Jatropha Husk, an Agro-Industrial Solid Waste. Process Safety and Environmental Protection, 85, 181-184. https://doi.org/10.1205/psep05002</mixed-citation></ref><ref id="scirp.127428-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Babarinde, A. and Onyiaocha, G.O. (2016) Equilibrium Sorption of Divalent Metal Ions onto Groundnut (Arachis hypogaea) Shell: Kinetics, Isotherm and Thermodynamics. Chemistry International, 2, 37-46.</mixed-citation></ref><ref id="scirp.127428-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Qureshi, K., Ahmad, M., Bhatti, I., Iqbal, M. and Khan, A. (2015) Cytotoxicity Reduction of Wastewater Treated by Advanced Oxidation Process. Chemistry International, 1, 53-59.</mixed-citation></ref><ref id="scirp.127428-ref11"><label>11</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Ukpaka</surname><given-names> C. </given-names></name>,<etal>et al</etal>. (<year>2016</year>)<article-title>Development of Model for Bioremediation of Crude Oil Using Moringa Extract</article-title><source> Chemistry International</source><volume> 2</volume>,<fpage> 19</fpage>-<lpage>28</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.127428-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Engida, A.M. and Chandravanshi, B.S. (2017) Assessment of Heavy Metals in Tobacco of Cigarettes Commonly Sold in Ethiopia. Chemistry International, 3, 213-219.</mixed-citation></ref><ref id="scirp.127428-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Odunlami, M.O., Akintola, J.T., Amodu, O.S., Sodeinde, O.A., Ezeka, F.C., Gbadamosi, A.S. and Omoigui, B.O. (2022) Process Simulation of the Synthesis of Acetone from Isopropyl Alcohol. Nigerian Research Journal of Engineering and Environmental Sciences, 7, 363-368.</mixed-citation></ref><ref id="scirp.127428-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Hydromantis Environmental Software Solutions, Inc. (2021) GPS-X: Advanced Wastewater Treatment Process Modeling and Simulation Software.https://www.hydromantis.com/</mixed-citation></ref><ref id="scirp.127428-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Janssen, P.M., Meinema, K. and van der Roest, H.F. (2002) Biological Phosphorus Removal: Manual for Design and Operation. IWA Publishing, London.</mixed-citation></ref><ref id="scirp.127428-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Culp, R.L., Clup, G.L. and Wesner, G.M. (1978) Handbook of Advanced Wastewater Treatment. 2nd Edition, Van Nostrand Reinhold Co., Kentucky.</mixed-citation></ref><ref id="scirp.127428-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Marlin, T.E. (1995) Process Control: Designing Processes and Control Systems for Dynamic Performance. McGraw-Hill, London.</mixed-citation></ref><ref id="scirp.127428-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Okereke, J.N., Ogidi, O.I. and Obasi, K.O. (2016) Environmental and Health Impact of Industrial Wastewater Effluents in Nigeria—A Review. International Journal of Advanced Research Biological Sciences, 3, 55-67.</mixed-citation></ref><ref id="scirp.127428-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Abagale, F.K., Sarpong, D.A., Ojediran, J.O., Osei-Agyemang, R., Shuaibu, A.G. and Birteeb, P.T. (2013) Heavy Metals Concentration in Wastewater from Car Washing Bays Used for Agriculture in the Tamale Metropolis, Ghana. International Journal of Current Research, 5, 1571-1576.</mixed-citation></ref></ref-list></back></article>