Pollution Parameters Research Articles

Treatment of organic compounds resulting from oil refineries under solar light and reuse it for industrial purpose

This paper was aimed to examine the removal of oil from water by photocatalytic advance oxidation under solar light. A pH of 11 has shown a higher oil removal efficiency. Oil remove efficiency levels at pH 11 have been found 75% within 230 minutes’ oily water effluent, studies have shown that Langmuir isotherm has been the best-fit one of the isotherms for the removal of oil. Data have shown a higher adsorptive capacity. Also we have studied another parameter like (catalyst concentration, initial oil concentration and pH). While the treatment of waste-water is dependent upon a great level of quality for the processed industrial water, the nature of wastes that are added throughout the utilization, and the treatment degree that has been received by the waste-water. Then, the data of the waste-water quality that has been measured routinely and it was reported at the plants of the waste-water treatments are mainly for disposal of the treated effluent or the necessities of the discharge in terms of the gross pollution parameters.

ENVIRONMENTAL MANAGEMENT AS A TOOL FOR PROVIDING RESILIENCE OF THE SEA PORT

Abstract. It is proved the importance of environmental management to ensure sustainable development of the port. Based on the study of academic literature, the factors of external and internal environment that determine the need for the development of environmental management are identified. A generalized model of the environmental management system is proposed and the need to introduce a rational management system at all levels of port management is emphasized. It is emphasized that the problem of developing a system of ecological and economic model of management and decision making requires the use of theory and methods of modern information technology, as well as methods of adaptive and intelligent management of port processes in real time based on a set of technological and economic and environmental criteria. It is offered the general principle of formation of the combined criteria of management on all levels of hierarchy according to decomposition of management system structure of a production function and at the account of both economic and ecological parameters. A system-wide generalized technological, economic and environmental criterion for management and decision-making has been developed, which includes both qualitative and quantitative characteristics of services and environmental parameters of pollutants. For all technological and transport processes the local control criteria corresponding to the general system criterion on observations of technological and ecological parameters are received. Variants of criteria of operative management of operational function of port are developed. It is emphasized that the specific choice of quality criteria is determined by many factors, such as the specifics of the problem, the nature and complexity of the object, the simplicity and feasibility of the proposed algorithms. Relevant principles are given for the selection of the appropriate criterion. The concept of ecological management of port’s operational function is formulated. Keywords: environmental management, environmental criteria, seaport, management system, management principles. JEL Classification M11 Formulas: 29; fig.: 2; tabl.: 0; bibl.: 24.

COLLABORATIVE AIR QUALITY MAPPING OF DIFFERENT METROPOLITAN CITIES OF INDIA

Abstract. Environmental pollution has become extremely serious as a result of today's technological advancements all over the world. One of the most important environmental and public health risks is air pollution. The exponential growth of population, vehicular density on highways, urbanization, and other factors are rising air pollution in cities, necessitating techniques for monitoring and forecasting air quality or determining its health consequences. Various experiments are being conducted on city air quality and its distribution through the built climate. The amount of emissions in the air varies according to the time of day as depicted it is merely high in morning time between 9 to 10 am and between 5 to 6 pm in all cities. These collected data are also characterized as peak hour, average hour, and off-peak hour. It also varies geographically and during special occasions. Since computing and showcasing of air pollution levels require terrain data, air quality data from the open sources i.e. CPCB (central pollution control board, India), and air pollution prediction models. Acculumating the data of the air pollution parameter from the open sources of cities based on typically very crowded, averagely crowded, and thinly crowded areas across the city and then mapping it on ArcGIS. The data monitoring has been done for the whole year merely main emphasizes has been done on the three seasons autumn, winter, and summer (January, May, and August). Also, in winter the value of having pollutants is high due to winter inversion and in the morning also the value is higher, and in monsoon, due to precipitation, it decreases. The dispersion model help in considering the wind speed and direction, the computed data from each source location reaching out to the monitoring sensing station from the comparatively adding to the value of pollutant. With the help of questionnaires, computed out to the result that people residing or having the workplace near to the busy crossing are more promising to have the health-related issue like chocking, respiratory diseases. Men are merely more affected by this between the age of 37 to 63 years.

Implementation of an Environmental Pollution Monitoring System for Industrial Facilities

Air pollution is one of the most significant problems affecting the quality of life and the health of the rising urban population of industrial societies. A common industrial pollutant resulting from the incomplete burning of natural gas and any other material containing carbon is carbon monoxide and other hazardous substances. Real time environmental data monitoring has significant role in industries and also in everyday life. This study presents air pollution monitoring system using a gas sensor and a microcontroller. It also sends SMS to those who are likely overexposed to these pollutants. The system comprised of nodes/pairs of sensors and attendant microcontroller which are used to measure pollutant parameters at any particular point of interest. The data is read on a (Personal Computer) PC through a USB connection. The microcontroller-based system provides a tool for real time monitoring of carbon monoxide and Liquefied Petroleum Gases at any location deployed. This monitoring device can deliver real-time measurements of air quality. The system was deployed at an industrial location and it performed reliably.

Treatment of Organic Compounds Resulting from Oil Refineries under Solar Light and Reuse it for Industrial Purpose

This paper was aimed to examine the removal of oil from water by photocatalytic advance oxidation under solar light. A pH of 11 has shown a higher oil removal efficiency. Oil remove efficiency levels at pH 11 have been found 75% within 230 minutes’ oily water effluent, studies have shown that Langmuir isotherm has been the best-fit one of the isotherms for the removal of oil. Data have shown a higher adsorptive capacity. Also we have studied another parameter like (catalyst concentration, initial oil concentration and pH). While the treatment of waste-water is dependent upon a great level of quality for the processed industrial water, the nature of wastes that are added throughout the utilization, and the treatment degree that has been received by the waste-water. Then, the data of the waste-water quality that has been measured rou-tinely and it was reported at the plants of the waste-water treatments are mainly for disposal of the treated effluent or the necessities of the discharge in terms of the gross pollution parameters.

Effect of Different Pollution Parameters and Chemical Components of PM2.5 on Health of Residents of Xinxiang City, China.

The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM2.5) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April–May), 19 (July–August), 27 (September–October), 28 (December–January) of PM2.5 were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM2.5 were analyzed via ion chromatography and inductively coupled plasma–mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM2.5 concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017–2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM2.5 concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM2.5 to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO3−) and sulfate (SO42−) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM2.5 in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM2.5 has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM2.5 rises by 10 μg·m−3, hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741–11.264) and 0.068% (95% CI, 0.067–0.069). GAM model analysis predicted the maximum effect of PM2.5 exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM2.5 on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM2.5 has the greatest effect on HGB. The maximum cumulative effect of PM2.5 on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM2.5 increases significantly and has a significant correlation with some blood routine indicators.

Treatment of young and stabilized landfill leachate by integrated sequencing batch reactor (SBR) and reverse osmosis (RO) process

In this paper, the performance and effectiveness of combined sequencing batch reactor (SBR) and reverse osmosis (RO), as well as differences in treating young and matured landfill leachate, was investigated. Samples of young and stabilized leachate were collected from a municipal landfill in north-eastern Poland. The general pollution parameters, organic and inorganic indicators were determined in raw leachate and after each step of leachate treatment. The performance characteristics of the reverse osmosis system were made based on permeate flux, electroconductivity removal rate, concentration factor and removal rate. The use of biological pre-treatment had a good efficiency (>98% for both leachate) in ammonia nitrogen removal. The SBR treatment effectiveness for BOD (64%), Fe (29%), Cl− (0.2%) and Total Organic Carbon (-5.3%) was lower for young leachate compared to a stabilized. Pretreated leachate was directed to a RO system which was characterized by better operational parameters during the filtration of stabilized leachate: the average permeate flux was higher by 3.3 L/m2⋅s⋅10−6 and the filtration time was shorter by 110 min compared to the young leachate. The main reason of membrane clogging during young leachate filtration was a higher content of organic matter and its neutralization by Ca2+ and N-NH4+ presented in leachate, causing clogging of negatively charged RO membrane. Another reason could be complex formation between iron and natural organic matter that may precipitate on the membrane surface or inside the pores. This study has shown a high removal efficiency (over 80%) of the integrated SBR-RO method for all analyzed parameters.

Study of the impact of metal and organic pollution on benthic macrofauna using multivariate analyses in coastal wetland of Reghaïa, Algeria.

In this study, we studied the impact of pollution, metallic, organic, and environmental parameters, on benthic macroinvertebrates of the Reghaïa wetland and coastal zone, which is a nature reserve located in northern Algeria and is one of the last heritage sites on the central coast of the country. To do this, multivariate methods are used. The results of the multivariate analyses clearly show the impact of metal and organic pollution on the macroinvertebrates of this wetland which is really striking; this pollution has destroyed and upset the biodiversity of the benthic macrofauna and it has led to the disappearance of several taxa. This pollution has drained this wetland of the taxonomic richness of benthic macroinvertebrates, the only taxa that have resisted are the Diptera such as Psychodidae, Ceratopogonidae, and Syrphidae.

Spatial-Temporal Analysis of Air Pollutant Concentrations in Relation to Land Use and School Environment

Excessive exposure schoolchildren to air pollution can lead to long-lasting health problems, allergies and respiratory disease. It is well known that the major factors contributing to increase of air pollution are motor vehicles and industries. Thus, it is important to analyze the spatial temporal air pollutant concentrations and its relation with school location as the location of schools and its surrounding can increase their exposure. In this study, six schools in Johor were selected and the land use surrounding the schools were updated using ArcGIS. The Inverse Distance Weighting (IDW) interpolation technique was used to identify which schools’ area in Johor has a higher range of air pollutant concentration. There are four air pollution parameters obtained from the Department of Environment (DOE) which are PM2.5, CO, O3 and SO2. Hourly air pollutant concentration reading was obtained from the DOE in order to analyze air pollutant concentration during school period. The results obtained from the IDW technique showed that Sekolah Menengah Pasir Gudang (2) located in Pasir Gudang, Malaysia has reached a very unhealthy and hazardous level as compared to other schools in Johor. On the other hand, Sekolah Menengah Kebangsaan Tanjung Pengelih, Pengerang, Malaysia showed good to unhealthy range as compared to other schools in Johor. The spatial autocorrelation tool was used to analyze the relationship between the air pollution concentration and the school’s location in Johor. The results showed that the Moran’s Indices is positive showing a strong relationship that is clustering. It can be stated that there is a relationship between air pollutant concentrations with the school locations.

Relationship Between Air Pollution and the Concentration of Nitric Oxide in the Exhaled Air (FeNO) in 8-9-Year-Old School Children in Krakow.

The consequences of air pollution pose one of the most serious threats to human health, and especially impact children from large agglomerations. The measurement of nitric oxide concentration in exhaled air (FeNO) is a valuable biomarker in detecting and monitoring airway inflammation. However, only a few studies have assessed the relationship between FeNO and the level of air pollution. The study aims to estimate the concentration of FeNO in the population of children aged 8–9 attending the third grade of public primary schools in Krakow, as well as to determine the relationship between FeNO concentration and dust and gaseous air pollutants. The research included 4580 children aged 8–9 years who had two FeNO measurements in the winter–autumn and spring–summer periods. The degree of air pollution was obtained from the Regional Inspectorate of Environmental Protection in Krakow. The concentration of pollutants was obtained from three measurement stations located in different parts of the city. The FeNO results were related to air pollution parameters. The study showed weak but significant relationships between FeNO and air pollution parameters. The most significant positive correlations were found for CO8h (r = 0.1491, p < 0.001), C6H6 (r = 0.1420, p < 0.001), PM10 (r = 0.1054, p < 0.001) and PM2.5 (r = 0.1112, p < 0.001). We suggest that particulate and gaseous air pollutants impact FeNO concentration in children aged 8–9 years. More research is needed to assess the impact of air pollution on FeNO concentration in children. The results of such studies could help to explain the increase in the number of allergic and respiratory diseases seen in children in recent decades.

A Proposal for Architectural Framework Using Internet of Things with Fog Computing for an Air Quality Monitoring System

Air Monitoring becomes a systematic approach for sensitivity and finding out the circumstances of the atmosphere. The major concern of air quality monitoring is to measure the concentration of pollution and other important parameter related to the contamination and provides information in real-time to make decisions at right time to cure lives and save the environment. This paper proposes an Architectural Framework for the air quality monitoring system based on Internet-of-Things (IoT) and via Fog computing techniques with novel methods to obtain real-time and accurate measurements of conventional air quality monitoring. IoT-based real-time air pollution monitoring system is projected to at any location and stores the measured value of various pollutants over a web server with the Internet. It can facilitate the process and filter data near the end of the IoT nodes in a concurrent manner and improve the Latency issue with the quality of services.

WITHDRAWN: Ecofriendly enhancement of engine performance using biofuel palm stearin

Biodiesel is the best solution since it is a dependable and sustainable source of energy. Palm-stearin oil is a significant biodiesel source with a low environmental impact. Dual fueling is an effective method for improving engine performance while lowering emissions. With this context and foresight, propane was mixed with air at different liters per minute (lpm) to boost the emission and performance operation of a diesel engine using Palm-stearin Biodiesel as the primary fuel (PSBD). The study looked at performance parameters like BSFC and BTE, as well as pollution parameters like HC, CO, NOx, and Smoke, which were calculated under various conditions with different intake propane rates with PSBD and compared to diesel. The addition of propane at 6 lpm reduced HC by 0.04 g/kW-hr, CO by 0.5 g/kW-hr, and smoke emissions by 0.4 BSU at all BPs compared to neat PSBD with a higher NO of 0.9 g/kW-hr. The inclusion of propane also improved performance trends, such as a 0.06 kg/kW-h drop in BSFC and a 0.7 percent rise in BTE for PSBD. The addition of propane with PSBD at 6 lpm improves CI ignition trends.

Phytoremediation of dairy wastewater using Azolla pinnata: Application of image processing technique for leaflet growth simulation

The present study assessed the phytoremediation efficiency of water fern (Azolla pinnata R.Br.) in the treatment of dairy wastewater (DWW). Batch mode experimentation was done using different dilutions (0 to 100%) of DWW transplanted with five healthy leaflets of A. pinnata. Besides this, the A. pinnata growth was captured using camera vision-based image recognition and further modeled using logistic and modified Gompertz models. The findings showed that after 14 days of phytoremediation experiments, the maximum significant (p < 0.05) reduction efficiency of selected pollutant parameters of DWW i.e. pH (9.41%), electrical conductivity (61.42%), total dissolved solids (71.56%), total Kjeldahl's nitrogen (73.25%), and total phosphorus (65.37%) observed using 75% DWW dilution. Moreover, the periodically taken surface images were useful to recognize the position and number of leaflets which further helped to simulate A. pinnata growth patterns. The maximum number of leaflets (n = 20), fresh biomass (16.18 ± 0.42 g), dry biomass (1.47 ± 0.04 g), and chlorophyll content (3.14 ± 0.03 mg/g fwt.) was also observed using 75% DWW treatment, respectively. The logistic model was found more robust as compared to modified Gompertz to predict leaflet production (y) as revealed from model validation results i.e. coefficient of determination (R2 > 0.9533) and minimum difference between experimental and model-predicted results. Thus, the combined application of phytoremediation and image processing techniques can be used to monitor and maximize plant growth performance.

Coupling of quantile regression into boosted regression trees (BRT) technique in forecasting emission model of PM10 concentration

Air pollution is currently becoming a significant global environmental issue. The sources of air pollution in Malaysia are mobile or stationary. Motor vehicles are one of the mobile sources. Stationary sources originated from emissions caused by urban development, quarrying and power plants and petrochemical. The most noticeable contaminant in the Peninsular of Malaysia is the particulate matter (PM10), the highest contributor of Air Pollution Index (API) compared to other pollution parameters. The aim of this study is to determine the best loss function between quantile regression (QR) and ordinary least squares (OLS) using boosted regression tree (BRT) for the prediction of PM10 concentration in Alor Setar, Klang and Kota Bharu, Malaysia. Model comparison statistics using coefficient of determination (R2), prediction accuracy (PA), index of agreement (IA), normalized absolute error (NAE) and root mean square error (RMSE) show that QR is slightly better than OLS with the performance of R2 (0.60–0.73), PA (0.78–0.85), IA (0.86–0.92), NAE (0.15–0.17) and RMSE (9.52–22.15) for next-day predictions in BRT model.

Environmental and Air Pollution Factors Affecting Allergic Eye Disease in Children and Adolescents in India.

The aim of this study was to describe the correlation between the meteorological and air pollution parameters with the temporal pattern of presentation of recent onset allergic eye disease (AED). This cross-sectional hospital-based study included new patients (≤21 years of age) presenting between January 2016 and August 2018 from the district of Hyderabad with a clinical diagnosis of AED and an acute exacerbation of recent onset of symptoms of less than 3 months duration. Correlation analysis was performed with the local environmental rainfall, temperature, humidity, windspeed, and air pollution. Of the 25,354 new patients hailing from the district of Hyderabad, 2494 (9.84%) patients were diagnosed with AED, of which 1062 (4.19%) patients had recent onset of symptoms. The mean monthly prevalence in this cohort was 4.13%, and the month of May (6.09%) showed the highest levels. The environmental parameters of humidity (r2 = 0.83/p = < 0.0001) and rainfall (r2 = 0.41/p = 0.0232) showed significant negative correlation, while temperature (r2 = 0.43/p = 0.0206) and ground-level ozone (r2 = 0.41/p = 0.0005) showed significant positive correlation with the temporal pattern of AED in the population. An increase in rainfall and humidity was associated with a lower prevalence, and an increase of temperature and ground-level ozone was associated with a higher prevalence of AED cases during the year among children and adolescents.

Effect of meteorological factors and Air Quality Index on the COVID-19 epidemiological characteristics: an ecological study among 210 countries.

The survival of COVID-19 in different environments may be affected by a variety of weather, pollution, and seasonal parameters. Therefore, the present study aims to conduct an ecological investigation on COVID-19 average growth rate of daily cases and deaths influenced by environmental factors (temperature, humidity, and air pollution) using a sample size of adjusted cumulative incidence of daily cases and deaths based on five 60-day periods. Research data was gathered on official websites, including information on COVID-19, meteorological data, and air pollution indicators from December 31, 2019, to October 12, 2020, from 210 countries. Spearman correlation and generalized additive model (GAM) were used to analyze the data. During the observed period, the COVID-19 average growth rate of daily cases (r = −0.08, P =0.151) and deaths (r= −0.09, P = 0.207) were not correlated with humidity. Also, there was a negative relationship between the COVID-19 average growth rate of new cases and deaths with the Air Quality Index (AQI) and wind (new cases and wind: r=−0.25, P= 0.04). Furthermore, the data related to the first and second 60 day of the adjusted cumulative incidence of COVID-19 daily cases and deaths were not associated with humidity and Air Quality Index (AQI). The result of GAM showed the effect of AQI on the average growth rate of COVID-19 new cases and deaths. This study provides evidence for a positive relationship between COVID-19 daily cases, deaths, and AQI.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-021-14322-6.

Legal Contemplation Regarding Healthcare and Covid-19

Public healthcare and disease prevention is the utmost concerns of the governments around the world. The quality, accountability and accessibility of health infrastructure along with medicines are desired so that the people use these resources at the time of medical emergency. Good health is measured when the mortality rate, malnutrition, huger, pollution and other parameters are low and does not impact upon the individual’s life. The communicable and non-communicable diseases put harmful effect on the health and life the people and COVID-19 which is a pandemic spread all over the world through transmission. The World Health Organisation issued various guidelines for safety and security but it’s a medical emergency like situation and governments of the countries already framed rule and regulations for the prevention/ protection and eliminate the transmission of disease through lockdown. There are number of legal provisions at international and national level for health and medicare as well as implementation of government mandates for protection from corona virus.

Effects of air pollution in Spatio-temporal modeling of asthma-prone areas using a machine learning model

Industrialization and increasing urbanization have led to increased air pollution, which has a devastating effect on public health and asthma. This study aimed to model the spatial-temporal of asthma in Tehran, Iran using a machine learning model. Initially, a spatial database was created consisting of 872 locations of asthma children and six air pollution parameters, including carbon monoxide (CO), particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) in four-seasons (spring, summer, autumn, and winter). Spatial-temporal modeling and mapping of asthma-prone areas were performed using a random forest (RF) model. For Spatio-temporal modeling and assessment, 70% and 30% of the dataset were used, respectively. The Spearman correlation and RF model findings showed that during different seasons, the PM2.5 parameter had the most important effect on asthma occurrence in Tehran. The assessment of the Spatio-temporal modeling of asthma using the receiver operating characteristic (ROC)-area under the curve (AUC) showed an accuracy of 0.823, 0.821, 0.83, and 0.827, respectively for spring, summer, autumn, and winter. According to the results, asthma occurs more often in autumn than in other seasons.

Treatment of mustard tuber wastewater (MTWW) using a pilot-scale packed cage rotating biological contactor system: process modeling and optimization.

The water quality range for wastewater treatment projects in the food processing industry changes constantly. To fully understand the threshold for pollutant removal with the lowest possible energy consumption, the relationship between pollutant removal and wastewater treatment conditions was established using response surface methodology (RSM). The optimum conditions for total COD, TN, and NH3-N removal from saline mustard tuber wastewater (MTWW) with a packed cage rotating biological contactor (RBC) system were investigated by experiments based on a Box-Behnken design (BBD). The independent variables were organic load (ORL), rotational disk velocity (RDV), and immersion rate (IR). Parameters of COD, TN, and NH3-N removal efficiency were selected as responses. The optimal conditions for the best COD, TN, and NH3-N removal efficiency with the lowest energy consumption were found to be at an ORL of 26.71 kg/day, a RDV of 1.62 rpm (7.62 m/s), and an IR of 46%. After the optimization, the energy cost was evaluated by coupling energy performance indicators with organic pollution efficiencies to be the highest class of performance. This research demonstrates that the suggested models have a good predicting and fitting ability in interrelations between the pollutant removal and process parameters of the packed cage RBC system treating saline MTWW.

A kinetic model for electrocoagulation and its application for the electrochemical removal of phosphate ions from brewery wastewater

A kinetic model based on electrochemical principles, elementary reactions and phase equilibrium was constructed to describe electrocoagulation. The approach was successfully illustrated for the removal of phosphate ions and other pollutant parameters from a brewery effluent. The kinetic results were obtained from a factorial design of experiments at optimal conditions for removal of phosphate and COD. Al3+ from the electrolysis of zero-valent aluminum reacted with phosphate at a rate constant of ~8.16 × 107 L mol−1 s−1 to form aluminum phosphate. Hexose sugars adsorbed on aluminum phosphate at a rate constant of ~5.34 × 102 L mol−1 s−1 were removed by flotation at the same rate of COD. The concentration of soluble aluminum was dependent on multiple reactions involving aluminum species and on the equilibrium between soluble and solid aluminum species. Turbidity was associated with the formation of aluminum phosphate and its removal by flotation at a rate constant of ~1.49 × 10−3 s−1.