To date, experimental and epidemiological evidence of endocrine disrupting compounds (EDCs) adversely affecting human and animal populations has been widely debated. Notably, human health risk assessment is required for risk mitigation. The lack of human health risk assessment and management may thus unreliably regulate the quality of water resources and efficiency of treatment processes. Therefore, drinking water supply systems (DWSSs) may be still unwarranted in assuring safe access to potable drinking water. Drinking water supply, such as tap water, is an additional and crucial route of human exposure to the health risks associated with EDCs. A holistic system, incorporating continuous research in DWSS monitoring and management using multi-barrier approach, is proposed as a preventive measure to reduce human exposure to the risks associated with EDCs through drinking water consumption. The occurrence of EDCs in DWSSs and corresponding human health risk implications are analyzed using the Needs, Approaches, Benefits, and Challenges (NABC) method. Therefore, this review may act as a supportive tool in protecting human health and environmental quality from EDCs, which is essential for decision-making regarding environmental monitoring and management purposes. Subsequently, the public could have sustainable access to safer and more reliable drinking water.
The prolonged persistence of toxic arsenic (As) in environment is due to its non-biodegradable characteristic. Meanwhile, several studies have reported higher concentrations of As in Langat River. However, it is the first study in Langat River Basin, Malaysia, that As concentrations in drinking water supply chain were determined simultaneously to predict the health risks of As ingestion. Water samples collected in 2015 from the four stages of drinking water supply chain were analysed for As concentration by inductively coupled plasma mass spectrometry. Determined As concentrations along with the time series data (2004-2015) were significantly within the maximum limit 0.01 mg/L of drinking water quality standard set by World Health Organization. The predicted As concentration by auto-regression moving average was 3.45E-03 mg/L in 2020 at 95% level based on time series data including climatic control variables. Long-term As ingestion via household filtration water at Langat Basin showed no potential lifetime cancer risk (LCR) 9.7E-06 (t = 6.68; p = 3.37E-08) as well as non-carcinogenic hazard quotient (HQ) 4.8E-02 (t = 6.68; p = 3.37E-08) risk at 95% level. However, the changing landscape, ex-mining ponds and extensive use of pesticides for palm oil plantation at Langat Basin are considered as the major sources of increased As concentration in Langat River. Therefore, a two-layer water filtration system at Langat Basin should be introduced to accelerate the achievement of sustainable development goal of getting safe drinking water supply.
Monitoring the groundwater chemical composition and identifying the presence of pollutants is an integral part of any comprehensive groundwater management strategy. The present study was conducted in a part of West Tripura, northeast India, to investigate the presence and sources of trace metals in groundwater and the risk to human health due to direct ingestion of groundwater. Samples were collected from 68 locations twice a year from 2016 to 2018. Mixed Ca-Mg-HCO3, Ca-Cl and Ca-Mg-Cl were the main groundwater types. Hydrogeochemical methods showed groundwater mineralization due to (1) carbonate dissolution, (2) silicate weathering, (3) cation exchange processes and (4) anthropogenic sources. Occurrence of faecal coliforms increased in groundwater after monsoons. Nitrate and microbial contamination from wastewater infiltration were apparent. Iron, manganese, lead, cadmium and arsenic were above the drinking water limits prescribed by the Bureau of Indian Standards. Water quality index indicated 1.5% had poor, 8.7% had marginal, 16.2% had fair, 66.2% had good and 7.4% had excellent water quality. Correlation and principal component analysis reiterated the sources of major ions and trace metals identified from hydrogeochemical methods. Human exposure assessment suggests health risk due to high iron in groundwater. The presence of unsafe levels of trace metals in groundwater requires proper treatment measures before domestic use.
Active pharmaceutical ingredients (APIs) are typical endocrine disruptors found in common pharmaceuticals and personal care products, which are frequently detected in aquatic environments, especially surface water treated for drinking. However, current treatment technologies are inefficient for removing emerging endocrine disruptors, leading to the potential contamination of tap water. This study employed an optimized analytical method comprising solid-phase extraction and liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) to detect APIs in tap water in Putrajaya, Malaysia. Several therapeutic classes of pharmaceuticals and personal care products, including anti-inflammatory drugs (dexamethasone and diclofenac), antibiotics (sulfamethoxazole and triclosan), antiepileptics (primidone), antibacterial agents (ciprofloxacin), beta-blockers (propranolol), psychoactive stimulants (caffeine), and antiparasitic drugs (diazinon), were detected in the range of water pollutants. Diclofenac accounted for the highest concentration (21.39 ng/L), followed by triclosan and ciprofloxacin (9.74 ng/L and 8.69 ng/L, respectively). Caffeine was observed in all field samples with the highest distribution at 35.32%. Caffeine and triclosan exhibited significantly different distributions in household tap water (p water; however, the estimated risk was negligible (risk quotient water quality monitoring indicators for water resource conservation and water supply safety related to emerging organic contaminants; thus, API detection is important for safeguarding the environment and human health.
With the advancement of technologies and growth of the economy, it is inevitable that more complex processes are deployed, producing more heterogeneous wastewater that comes from biomedical, biochemical and various biotechnological industries. While the conventional way of wastewater treatment could effectively reduce the chemical oxygen demand, pH and turbidity of wastewater, trace pollutants, specifically the endocrine disruptor compounds (EDCs) that exist in µg L-1 or ng L-1 have further hardened the detection and removal of these biochemical pollutants. Even in small amounts, EDC could interfere human's hormone, causing severe implications on human body. Hence, this review elucidates the recent insights regarding the effectiveness of an advanced 2D material based on titanium carbide (Ti3C2Tx), also known as MXene, in detecting and removing EDCs. MXene's highly tunable feature also allows its surface chemistry to be adjusted by adding chemicals with different functional groups to adsorb different kinds of EDCs for biochemical pollution mitigation. At the same time, the incorporation of MXene into sample matrices also further eases the analysis of trace pollutants down to ng L-1 levels, thereby making way for a more cleaner and comprehensive wastewater treatment. In that sense, this review also highlights the progress in synthesizing MXene from the conventional method to the more modern approaches, together with their respective key parameters. To further understand and attest to the efficacy of MXene, the limitations and current gaps of this potential agent are also accentuated, targeting to seek resolutions for a more sustainable application.
Landfills are sources of groundwater and soil pollution due to the production of leachate and its migration through refuse. This study was conducted in order to determine the extent of groundwater and soil pollution within and around the landfill of Seri Petaling located in the State of Selangor, Malaysia. The condition of nearby surface water was also determined. An electrical resistivity imaging survey was used to investigate the leachate production within the landfill. Groundwater geochemistry was carried out and chemical analysis of water samples was conducted upstream and downstream of the landfill. Surface water was also analyzed in order to determine its quality. Soil chemical analysis was performed on soil samples taken from different locations within and around the landfill in the vadose zone (unsaturated zone) and below the water table (in the soil saturated zone). The resistivity image along line L-L1 indicated the presence of large zones of decomposed waste bodies saturated with highly conducting leachate. Analysis of trace elements indicated their presence in very low concentrations and did not reflect any sign of heavy metal pollution of ground and surface water or of soil. Major ions represented by Na, K, and Cl were found in anomalous concentrations in the groundwater of the downstream bore hole, where they are 99.1%, 99.2%, and 99.4%, respectively, higher compared to the upstream bore hole. Electrical conductivity (EC) was also found in anomalous concentration downstream. Ca and Mg ions represent the water hardness (which is comparatively high downstream). There is a general trend of pollution towards the downstream area. Sulfates (SO4) and nitrates (NO3) are found in the area in low concentrations, even below the WHO standards for drinking water, but are significantly higher in the surface water compared to the groundwater. Phosphate (PO4) and nitrite (NO2), although present in low levels, are significantly higher at the downstream. There is no significant difference in the amount of fluoride (F) in the different locations. In the soil vadose zone, heavy metals were found to be in their typical normal ranges and within the background concentrations. Soil exchangeable bases were significantly higher in the soil saturated zone compared to the vadose zone, and no significant difference was obtained in the levels of inorganic pollutants. With the exception of Cd, the concentration ranges of all trace elements (Cu, Zn, Cr, Pb, and Ni) of Seri Petaling landfill soils were below the upper limits of baseline concentrations published from different sources.
We sampled extensively (29 stations) at the Klang estuarine system over a 3-day scientific expedition. We measured physical and chemical variables (temperature, salinity, dissolved oxygen, total suspended solids, dissolved inorganic nutrients) and related them to the spatial distribution of phototrophic picoplankton (Ppico). Multivariate analysis of variance of the physicochemical variables showed the heterogeneity of the Klang estuarine system where the stations at each transect were significantly different (Rao's F₁₈, ₃₆ = 8.401, p < 0.001). Correlation analyses also showed that variables related to Ppico abundance and growth were mutually exclusive. Distribution of Ppico was best explained by the physical mixing between freshwater and seawater whereas Ppico growth was correlated with temperature.
Water from 15 sampling stations in Tasik Chini (Chini Lake), Peninsular Malaysia were sampled for 12 months from September 2004 until August 2005 and analyzed for 11 metals including iron (Fe), aluminum (Al), manganese (Mn), barium (Ba), zinc (Zn), lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), chromium (Cr) and cobalt (Co). Results showed that the mean (min-max) metal concentrations (in micrograms per liter) in Tasik Chini waters for the 12 months sampling based on 15 sampling stations (in descending order) for Fe, Al, Mn, Ba, Zn, Pb, Cu and Cd were 794.84 (309.33-1609.07), 194.53 (62.37-665.93), 29.16 (16.68-79.85), 22.07 (15.64-29.71), 5.12 (2.224-6.553), 2.36 (1.165-4.240), 0.832 (0.362-1.443) and 0.421 (0.254-0.696) respectively. Concentration for three metals i.e. Ni, Cr and Co were too low and not detected by the graphite furnace Atomic Absorption Spectrophotometry (AAS). Comparison with various water quality standards showed that the mean metals concentration in surface water of Tasik Chini were low and within the range of natural background except for Fe and Al. In general, metal concentrations in Tasik Chini water varied temporally and spatially. The main factors influencing these metal concentrations in the water were the raining season and mining activities. Stations located at Tanjung Jerangking and Melai areas were the most effected due to those factors.
The city of Dhaka has been ranked repeatedly as the most polluted, the most populous, and the most unbearable city in the world. More than 19.5 million inhabitants live in Dhaka, and the population growth rate of urban areas in Bangladesh is almost double that of rural areas. Rapid urbanization is one of the leading contributors to water pollution in Dhaka and could prevent the country from achieving sustainable development. Therefore, this study estimates respondents' willingness to pay (WTP) to improve water pollution management systems and identifies factors that influence WTP in Dhaka. This study employed the contingent valuation method (CVM) to estimate WTP of the respondents. Data were collected using a structured questionnaire with CVM questions, which was distributed to households in the study areas. The results revealed that 67% of the respondents are willing to pay for an improved water pollution management system, while 31.8% of households are unwilling to pay. The study also found that socio-economic factors (e.g., income and education) and perception significantly influence WTP. Therefore, this paper will provide directives for policymakers in developing an effective policy framework, as well as sensitize all stakeholders to the management of water pollution in Dhaka. The study suggests that social institutions, financial institutions, banks, non-government organizations (NGOs), insurance companies, and the government could provide effective outreach programs for water pollution management as part of their social responsibility.
The analysis of total organic carbon (TOC) by the American Public Health Association (APHA) closed-tube reflux colorimetric method requires potassium dichromate (K2Cr2O7), silver sulfate (AgSO4), and mercury (HgSO4) sulfate in addition to large volumes of both reagents and samples. The method relies on the release of oxygen from dichromate on heating which is consumed by carbon associated with organic compounds. The method risks environmental pollution by discharging large amounts of chromium (VI) and silver and mercury sulfates. The present method used potassium monochromate (K2CrO4) to generate the K2Cr2O7 on demand in the first phase. In addition, miniaturizing the procedure to semi microanalysis decreased the consumption of reagents and samples. In the second phase, mercury sulfate was eliminated as part of the digestion mixture through the introduction of sodium bismuthate (NaBiO3) for the removal of chlorides from the sample. The modified method, the potassium monochromate closed-tube colorimetry with sodium bismuthate chloride removal (KMCC-Bi), generates the potassium dichromate on demand and eliminates mercury sulfate. The semi microanalysis procedure leads to a 60% reduction in sample volume and ≈ 33.33 and 60% reduction in monochromate and silver sulfate consumption respectively. The LOD and LOQ were 10.17 and 33.90 mg L-1 for APHA, and 4.95 and 16.95 mg L-1 for KMCC-Bi. Recovery was between 83 to 98% APHA and 92 to 104% KMCC-Bi, while the RSD (%) ranged between 0.8 to 5.0% APHA and 0.00 to 0.62% KMCC-Bi. The method was applied for the UV-Vis spectrometry determination of COD in water and wastewater. Statistics was done by MINITAB 17 or MS Excel 2016. ᅟ Graphical abstract.
Groundwater hazard assessments involve many activities dealing with the impacts of pollution on groundwater, such as human health studies and environment modelling. Nitrate contamination is considered a hazard to human health, environment and ecosystem. In groundwater management, the hazard should be assessed before any action can be taken, particularly for groundwater pollution and water quality. Thus, pollution due to the presence of nitrate poses considerable hazard to drinking water, and excessive nutrient loads deteriorate the ecosystem. The parametric IPNOA model is one of the well-known methods used for evaluating nitrate content. However, it cannot predict the effect of soil and land use/land cover (LULC) types on calculations relying on parametric well samples. Therefore, in this study, the parametric model was trained and integrated with the multivariate data-driven model with different levels of information to assess groundwater nitrate contamination in Saladin, Iraq. The IPNOA model was developed with 185 different well samples and contributing parameters. Then, the IPNOA model was integrated with the logistic regression (LR) model to predict the nitrate contamination levels. Geographic information system techniques were also used to assess the spatial prediction of nitrate contamination. High-resolution SPOT-5 satellite images with 5 m spatial resolution were processed by object-based image analysis and support vector machine algorithm to extract LULC. Mapping of potential areas of nitrate contamination was examined using receiver operating characteristic assessment. Results indicated that the optimised LR-IPNOA model was more accurate in determining and analysing the nitrate hazard concentration than the standalone IPNOA model. This method can be easily replicated in other areas that have similar climatic condition. Therefore, stakeholders in planning and environmental decision makers could benefit immensely from the proposed method of this research, which can be potentially used for a sustainable management of urban, industrialised and agricultural sectors.
Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall's coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall's coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network.
In the last few decades, environmental contaminants (ECs) have been introduced into the environment at an alarming rate. There is a risk to human health and aquatic ecosystems from trace levels of emerging contaminants, including hospital wastewater (HPWW), cosmetics, personal care products, endocrine system disruptors, and their transformation products. Despite the fact that these pollutants have been introduced or detected relatively recently, information about their characteristics, actions, and impacts is limited, as are the technologies to eliminate them efficiently. A wastewater recycling system is capable of providing irrigation water for crops and municipal sewage treatment, so removing ECs before wastewater reuse is essential. Water treatment processes containing advanced ions of biotic origin and ECs of biotic origin are highly recommended for contaminants. This study introduces the fundamentals of the treatment of tertiary wastewater, including membranes, filtration, UV (ultraviolet) irradiation, ozonation, chlorination, advanced oxidation processes, activated carbon (AC), and algae. Next, a detailed description of recent developments and innovations in each component of the emerging contaminant removal process is provided.
Mining activities in the Chini Lake catchment area have been extensive for several years, contributing to acid mine drainage (AMD) events with high concentrations of iron (Fe) and other heavy metals impacting the surface water. However, during the restriction period due to the COVID-19 outbreak, anthropogenic activities have been suspended, which clearly shows a good opportunity for a better environment. Therefore, we aimed to analyze the variation of AMD-associated water pollution in three main zones of the Chini Lake catchment area using Sentinel-2 data for the periods pre-movement control order (MCO), during MCO, and post-MCO from 2019 to 2021. These three zones were chosen due to their proximity to mining areas: zone 1 in the northeastern part, zone 2 in the southeastern part, and zone 3 in the southern part of the Chini Lake area. The acid mine water index (AMWI) was a specific index used to estimate acid mine water. The AMWI values from Sentinel-2 images exhibited that the mean AMWI values in all zones during the MCO period decreased by 14% compared with the pre-MCO period. The spatiotemporal analysis found that the highest polluted zones were recorded in zone 1, followed by zone 3 and zone 2. As compared with during the MCO period, the maximum percentage of increment during post-MCO in all zones was up to 25%. The loosened restriction policy has resulted in more AMD flowing into surface water and increased pollution in Chini Lake. As a whole, our outputs revealed that Sentinel-2 data had a major potential for assessing the AMD-associated pollution of water.
Most studies of metals exposure focus on the heavy metals. There are many other metals (the transition, alkali and alkaline earth metals in particular) in common use in electronics, defense industries, emitted via combustion and which are naturally present in the environment, that have received limited attention in terms of human exposure. We analysed samples of whole blood (172), urine (173) and drinking water (172) for antimony, beryllium, bismuth, cesium, gallium, rubidium, silver, strontium, thallium, thorium and vanadium using ICPMS. In general most metals concentrations were low and below the analytical limit of detection with some high concentrations observed. Few factors examined in regression models were shown to influence biological metals concentrations and explained little of the variation. Further study is required to establish the source of metals exposures at the high end of the ranges of concentrations measured and the potential for any adverse health impacts in children.
Metals are micropollutants that cannot be degraded by microorganisms and are infiltrated into various environmental media, including both freshwater and marine water. Metals from polluted water are absorbed by many aquatic species, especially fish. Fish is a staple food in the diets of many regions in the world; hence, both the type and concentration of metals accumulated and transferred from contaminated water sources to fish must be determined and assessed. In this study, the heavy metal concentration was determined and assessed in fish collected from freshwater sources via published literature and Estimated Daily Intake (EDI), Target hazard quotient (THQ), and Carcinogenic Risk (CR) analyses, aiming to examine the metal pollution in freshwater fish. The fish was used as a bioindicator, and Geographic information system (GIS) was sued to map the polluted regions. The results confirmed that Pb was detected in fish sampled at 28 locations, Cr at 24 locations, Cu and Zn at 30 locations, with values Pb detected ranging from 0.0016 mg kg-1 to 44.3 mg kg-1, Cr detected ranging from 0.07 mg kg-1 to 27 mg kg-1, Cu detected ranging from 0.031 mg kg-1 to 35.54 mg kg-1, and Zn detected ranging from 0.242 mg kg-1 to 103.2 mg kg-1. The strongest positive associations were discovered between Cu-Zn (r = 0.74, p
Microplastics (MPs) occurrence in farmed aquatic organisms has already been the prime priority of researchers due to the food security concerns for human consumption. A number of commercially important aquaculture systems have already been investigated for MPs pollution but the mud crab (Scylla sp.) aquaculture system has not been investigated yet even though it is a highly demanded commercial species globally. This study reported the MPs pollution in the mud crab (Scylla sp.) aquaculture system for the first time. Three different stations of the selected aquafarm were sampled for water and sediment samples and MPs particles in the samples were isolated by the gravimetric analysis (0.9% w/v NaCl solution). MP abundance was visualized under a microscope along with their size, shape, and color. A subset of the isolated MPs was analyzed by scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FTIR) for the surface and chemical characterization respectively. The average MPs concentration was 47.5 ± 11.875 particles/g in sediment and 127.92 ± 14.99 particles/100 L in the water sample. Fibrous-shaped (72.17%) and transparent-colored (59.37%) MPs were dominant in all the collected samples. However, smaller MPs (>0.05-0.5 mm) were more common in the water samples (47.69%) and the larger (>1-5 mm) MPs were in the sediment samples (47.83%). SEM analysis found cracks and roughness on the surface of the MPs and nylon, polyethylene, polypropylene, and polystyrene MPs were identified by FTIR analysis. PLI value showed hazard level I in water and level II in sediment. The existence of deleterious MPs particles in the mud crab aquaculture system was well evident. The other commercial mud crab aquafarms must therefore be thoroughly investigated in order to include farmed mud crabs as an environmentally vulnerable food security concern.
This study aims to determine the concentrations of surfactants in the surface microlayer (SML), subsurface water (SSW) and fine mode aerosol (diameter size Water-soluble ions, for the determination of fine mode aerosol sources, were determined using ion chromatography (IC) for anions (SO42-, NO3-, Cl- and F-) and cations (Na+, K+, Ca2+ and Mg2+). Principal component analysis (PCA), combined with multiple linear regression (MLR), was used to identify the possible sources of surfactants in fine aerosol. The results showed the concentrations of surfactants as MBAS and DBAS in the SML ranged between 0.23 ± 0.03 and 0.35 ± 0.01 μmol L-1 and between 0.21 ± 0.02 and 0.29 ± 0.01 μmol L-1, respectively. The enrichment factors (Efs) ratios between MBAS and DBAS in the SML and SSW ranged between 1.04 ± 0.01 and 1.32 ± 0.04, respectively. The station that is located near to tourism and industrial activities recorded the highest concentrations of surfactants in SML and SSW. The concentrations of surfactants in fine aerosol ranged between 62.29 and 106.57 pmol m-3. The three possible sources of fine aerosol during the northeast monsoon were aged sea spray/biomass burning (which accounted for 69% of the atmospheric aerosol), nitrate/mineral dust (23%) and sulphate/fresh sea salt (8%). During the southwest monsoon, the three main sources of atmospheric aerosol were biomass burning (71%), secondary inorganic aerosol (23%) and sea spray (6%). This study suggests anthropogenic sources are main contributors to the concentrations of surfactants in SML, SSW and fine aerosols.
Surface and ground water resources are highly sensitive aquatic systems to contaminants due to their accessibility to multiple-point and non-point sources of pollutions. Determination of water quality variables using mathematical models instead of laboratory experiments can have venerable significance in term of the environmental prospective. In this research, application of a new developed hybrid response surface method (HRSM) which is a modified model of the existing response surface model (RSM) is proposed for the first time to predict biochemical oxygen demand (BOD) and dissolved oxygen (DO) in Euphrates River, Iraq. The model was constructed using various physical and chemical variables including water temperature (T), turbidity, power of hydrogen (pH), electrical conductivity (EC), alkalinity, calcium (Ca), chemical oxygen demand (COD), sulfate (SO4), total dissolved solids (TDS), and total suspended solids (TSS) as input attributes. The monthly water quality sampling data for the period 2004-2013 was considered for structuring the input-output pattern required for the development of the models. An advance analysis was conducted to comprehend the correlation between the predictors and predictand. The prediction performances of HRSM were compared with that of support vector regression (SVR) model which is one of the most predominate applied machine learning approaches of the state-of-the-art for water quality prediction. The results indicated a very optimistic modeling accuracy of the proposed HRSM model to predict BOD and DO. Furthermore, the results showed a robust alternative mathematical model for determining water quality particularly in a data scarce region like Iraq.
Despite being a key Malaysian economic contributor, the oil palm industry generates a large quantity of environmental pollutant known as palm oil mill effluent (POME). Therefore, the need to remediate POME has drawn a mounting interest among environmental scientists. This study has pioneered the application of Meyerozyma guilliermondii with accession number (MH 374161) that was isolated indigenously in accessing its potential to degrade POME. This strain was able to treat POME in shake flask experiments under aerobic condition by utilising POME as a sole source of carbon. However, it has also been shown that the addition of suitable carbon and nitrogen sources has significantly improved the degradation potential of M. guilliermondii. The remediation of POME using this strain resulted in a substantial reduction of chemical oxygen demand (COD) of 72%, total nitrogen of 49.2% removal, ammonical nitrogen of 45.1% removal, total organic carbon of 46.6% removal, phosphate of 60.6% removal, and 92.4% removal of oil and grease after 7 days of treatment period. The strain also exhibited an extracellular lipase activity which promotes better wastewater treatment. Additionally, Fourier transform infrared spectroscopy (FTIR) and gas chromatography-mass spectrometry (GC-MS) analyses have specifically shown that M. guilliermondii strain can degrade hydrocarbons, fatty acids, and phenolic compounds present in the POME. Ultimately, this study has demonstrated that M. guilliermondii which was isolated indigenously exhibits an excellent degrading ability. Therefore, this strain is suitable to be employed in the remediation of POME, contributing to a safe discharge of the effluent into the environment.