Most human activities that use water produced sewage. As urbanization grows, the overall demand for water grows. Correspondingly, the amount of produced sewage and pollution-induced water shortage is continuously increasing worldwide. Ensuring there are sufficient and safe water supplies for everyone is becoming increasingly challenging. Sewage treatment is an essential prerequisite for water reclamation and reuse. Sewage treatment plants' (STPs) performance in terms of economic and environmental perspective is known as a critical indicator for this purpose. Here, the window-based data envelopment analysis model was applied to dynamically assess the relative annual efficiency of STPs under different window widths. A total of five STPs across Malaysia were analyzed during 2015-2019. The labor cost, utility cost, operation cost, chemical consumption cost, and removal rate of pollution, as well as greenhouse gases' (GHGs) emissions, all were integrated to interpret the eco-environmental efficiency. Moreover, the ordinary least square as a supplementary method was used to regress the efficiency drivers. The results indicated the particular window width significantly affects the average of overall efficiencies; however, it shows no influence on the ranking of STP efficiency. The labor cost was determined as the most influential parameter, involving almost 40% of the total cost incurred. Hence, higher efficiency was observed with the larger-scale plants. Meanwhile, the statistical regression analysis illustrates the significance of plant scale, inflow cBOD concentrations, and inflow total phosphorus concentrations at [Formula: see text] on the performance. Lastly, some applicable techniques were suggested in terms of GHG emission mitigation.
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.
Water-based cooling towers and their water supply at two hospitals in Johor were surveyed for the presence Legionella pneumophila. L. pneumophila were grown from 19 (76%) out of 25 collected water samples. One hospital cooling tower was contaminated with L. pneumophila serogroup 1.
This article describes design and application of feed-forward, fully-connected, three-layer perceptron neural network model for computing the water quality index (WQI)(1) for Kinta River (Malaysia). The modeling efforts showed that the optimal network architecture was 23-34-1 and that the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75. The WQI predictions of this model had significant, positive, very high correlation (r=0.977, p<0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values. The approach presented in this article offers useful and powerful alternative to WQI computation and prediction, especially in the case of WQI calculation methods which involve lengthy computations and use of various sub-index formulae for each value, or range of values, of the constituent water quality variables.
Multivariate statistical techniques such as multivariate analysis of variance (MANOVA) and discriminant analysis (DA) were applied for analyzing the data obtained from two rivers in the Penang State of Malaysia for the concentration of heavy metal ions (As, Cr, Cd, Zn, Cu, Pb, and Hg) using a flame atomic absorption spectrometry (F-AAS) for Cr, Cd, Zn, Cu, Pb, As and cold vapor atomic absorption spectrometry (CV-AAS) for Hg. The two locations of interest with 20 sampling points of each location were Kuala Juru (Juru River) and Bukit Tambun (Jejawi River). MANOVA showed a strong significant difference between the two rivers in terms of heavy metal concentrations in water samples. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers. It provided an important data reduction as it used four parameters (Zn, Pb, Cd and Cr) affording 100% correct assignations. Results indicated that the two rivers were different in terms of heavy metals concentrations in water, and the major difference was due to the contribution of Zn. A negative correlation was found between discriminate functions (DF) and Cr and As, whereas positive correlation was exhibited with other heavy metals. Therefore, DA allowed a reduction in the dimensionality of the data set, delineating a few indicator parameters responsible for large variations in heavy metal concentrations. Correlation matrix between the parameters exhibited a strong evidence of mutual dependence of these metals.
Water pollution during festival periods is a major problem in all festival cities across the world. Reliable prediction of water pollution is essential in festival cities for sewer and wastewater management in order to ensure public health and a clean environment. This article aims to model the biological oxygen demand (BOD(5)), and total suspended solids (TSS) parameters in wastewater in the sewer networks of Karbala city center during festival and rainy days using structural equation modeling and multiple linear regression analysis methods. For this purpose, 34 years (1980-2014) of rainfall, temperature and sewer flow data during festival periods in the study area were collected, processed, and employed. The results show that the TSS concentration increases by 26-46 mg/l while BOD(5) concentration rises by 9-19 mg/l for an increase of rainfall by 1 mm during festival periods. It was also found that BOD(5) concentration rises by 4-17 mg/l for each increase of 10,000 population.
Global deterioration of water, soil, and atmosphere by the release of toxic chemicals from the ongoing anthropogenic activities is becoming a serious problem throughout the world. This poses numerous issues relevant to ecosystem and human health that intensify the application challenges of conventional treatment technologies. Therefore, this review sheds the light on the recent progresses in nanotechnology and its vital role to encompass the imperative demand to monitor and treat the emerging hazardous wastes with lower cost, less energy, as well as higher efficiency. Essentially, the key aspects of this account are to briefly outline the advantages of nanotechnology over conventional treatment technologies and to relevantly highlight the treatment applications of some nanomaterials (e.g., carbon-based nanoparticles, antibacterial nanoparticles, and metal oxide nanoparticles) in the following environments: (1) air (treatment of greenhouse gases, volatile organic compounds, and bioaerosols via adsorption, photocatalytic degradation, thermal decomposition, and air filtration processes), (2) soil (application of nanomaterials as amendment agents for phytoremediation processes and utilization of stabilizers to enhance their performance), and (3) water (removal of organic pollutants, heavy metals, pathogens through adsorption, membrane processes, photocatalysis, and disinfection processes).
Field and laboratory studies were conducted to estimate concentration of potential contaminants from landfill in the underlying groundwater, leachate, and surface water. Samples collected in the vicinity of the landfill were analyzed for physiochemical parameters, organic contaminants, and toxic heavy metals. Water quality results obtained were compared from published data and reports. The results indicate serious groundwater and surface water contamination in and around the waste disposal site. Analysis of the organic samples revealed that the site contains polychlorinated biphenyls and other organo-chlorine chemicals, principally chloro-benzenes. Although the amount of PCB concentration discovered was not extreme, their presence indicates a potentially serious environmental threat. Elevated concentrations of lead, copper, nickel, manganese, cadmium, and cobalt at the downgradient indicate that the contamination plume migrated further from the site, and the distribution of metals and metals containing wastes in the site is nonhomogeneous. These results clearly indicate that materials are poorly contained and are at risk of entering the environment. Therefore, full characterization of the dump contents and the integrity of the site are necessary to evaluate the scope of the problem and to identify suitable remediation options.
Sungai Puloh mangrove estuary supports a large diversity of macrobenthic organisms and provides social benefits to the local community. Recently, it became a major recipient of heavy metals originating from industries in the hinterland as a result of industrialization and urbanization. This study was conducted to evaluate mobility and pollution status of heavy metals (Cd, Cu, Ni, Pb, Zn, and Fe) in intertidal surface sediments of this area. Surface sediment samples were collected based on four different anthropogenic sources. Metals concentrations were analyzed using an atomic absorption spectrophotometer (AAS). Results revealed that the mean concentrations were Zn (1023.68 ± 762.93 μg/g), Pb (78.8 ± 49.61 μg/g), Cu (46.89 ± 43.79 μg/g), Ni (35.54 ± 10.75 μg/g), Cd (0.94 ± 0.29 μg/g), and Fe (7.14 ± 0.94%). Most of the mean values of analyzed metals were below both the interim sediment quality guidelines (ISQG-low and ISQG-high), except for Pb concentration (above ISQG-low) and Zn concentration (above ISQG-high), thus suggesting that Pb and Zn may pose some environmental concern. Cadmium, Pb, and Zn concentrations were above the threshold effect level (TEL), indicating seldom adverse effect of these metals on macrobenthic organisms. Pollution load index (PLI) indicated deterioration and other indices revealed the intertidal surface sediment is moderately polluted with Cd, Pb, and Zn. Therefore, this mangrove area requires urgent attention to mitigate further contamination. Finally, this study will contribute to data sources for Malaysia in establishing her own ISQG since it is a baseline study with detailed contamination assessment indices for surface sediment of intertidal mangrove area.
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
A sacred ritual well with continuously discharging of methane gas through its water body was studied for physicochemical and microbiological quality in three seasons and during ritual mass bathing. Most of the physicochemical parameters showed significant seasonal variations (P<0.05) and a sharp fluctuation during mass bathing. Dissolved oxygen (DO) was found negatively correlated with temperature (r=-0.384, P<0.05), biochemical oxygen demand (BOD) (r=-0.58, P<0.001) and ammonia (r=-0.738, P<0.001), while BOD showed positive correlation with chemical oxygen demand (COD) (r=0.762, P<0.001) and ammonia (r=0.83, P<0.001). Simple regression analysis also yielded significant linear relationship in DO vs. temperature (r(2)=0.147, P<0.05), DO vs. ammonia (r(2)=0.544, P<0.001) and BOD vs. DO (r(2)=0.336, P<0.001). A total of eight microbial indicators were studied and found that all of them increased unusually during mass bathing comparing with their respective seasonal values. Total coliforms (TC) were found positively correlated with fecal coliforms (FC) (r=0.971), FC with Escherichia coli (EC) (r=0.952), EC with intestinal enterococci (IE) (r=0.921), fecal streptococci (FS) with IE (r=0.953) and Staphylococcus aureus (SA) with Pseudomonas aeruginosa (PA) (r=0.946), which were significant at P<0.001. Some regression models showed significant linear relationship at P<0.001 with r(2) value of 0.943 for FC vs. TC, 0.907 for EC vs. FC, 0.869 for FS vs. FC, 0.848 for IE vs. EC and 0.909 for IE vs. FS. The overall results found in this study revealed that well water is suitable for bathing purpose but the religious activity considerably worsen its quality.
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.
Thirty snakehead fish, Channa micropeltes (Cuvier, 1831) were collected at Lake Kenyir, Malaysia. Muscle, liver, intestine and kidney tissues were removed from each fish and the intestine was opened to reveal cestodes. In order to assess the concentration of heavy metal in the environment, samples of water in the surface layer and sediment were also collected. Tissues were digested and the concentrations of manganese (Mn), zinc (Zn), copper (Cu), cadmium (Cd) and lead (Pb) were analysed by using inductively-coupled plasma mass-spectrometry (ICP-MS) equipment. The results demonstrated that the cestode Senga parva (Fernando and Furtado, 1964) from fish hosts accumulated some heavy metals to a greater extent than the water and some fish tissues, but less than the sediment. In three (Pb, Zn and Mn) of the five elements measured, cestodes accumulated the highest metal concentrations, and in remaining two (Cu and Cd), the second highest metal accumulation was recorded in the cestodes when compared to host tissues. Therefore, the present study indicated that Senga parva accumulated metals and might have potential as a bioindicator of heavy-metal pollution.
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.
A study to determine the contribution of Giardia cysts and Cryptosporidium oocysts from cattle farms was carried out at the Langat Basin. This study investigated the contribution of cattle farms, located near Sungai Langat and Sungai Semenyih, towards river contamination with these cysts and oocysts. The findings showed that out of 24 samples of water taken from Sungai Semenyih, 4.2% was positive for Giardia cysts with a concentration of 1.3 cysts/L and 20.8% were positive with Cryptosporidium oocysts with a range of 0.7 - 2.7 oocysts/L. At Sungai Langat, from the 43 samples taken, 23.3% were positive for Giardia cysts with a range of 1.5 - 9 cysts/L whereas 11.6% were positive with Cryptosporidium oocysts with a range of 2.5 - 240 oocysts/L. Isolation of cysts and oocysts in bovine faecal materials revealed that 14.6% of faecal samples were positive for Giardia cysts which had a range of 75 - 1.3x104 cysts/g and 25% were positive for Cryptosporidium oocysts with a range of 50 - 3.9x105 oocysts/g. From the cattle wastewater, 98% were positive with oocysts and 6.7% with cysts. The concentrations were between 20 - 3.1x103 oocysts/mL for Cryptosporidium and 4 - 75 cysts/mL for Giardia. Given that the prevalence of Cryptosporidium and Giardia are high amongst the cattle and the positive findings of the (oo)cysts in the river samples, it could be deduced that there is a very high possibility of the cattle farms contaminating the river with Giardia cysts and Cryptosporidium oocysts. Viability study of Cryptosporidium oocysts in the surrounding soil and pond within the cattle farm showed that the viability of Cryptosporidium oocysts decreased with time. It was estimated that it will take 52 days for all the oocysts from both environment to be non-viable. With a viability rate of approximately 2 months in a cattle farm setup, river water contaminated with Cryptosporidium oocysts has a high chance of acting as an agent of transmission. As cattle farms are also inhabited by the owners and their families, this problem may pose a threat to humans (e.g. children) especially if they are dependent on the river water as their source of water for their daily activities.
In recent years, environmental concerns over ultra-trace levels of steroid estrogens concentrations in water samples have increased because of their adverse effects on human and animal life. Special attention to the analytical techniques used to quantify steroid estrogens in water samples is therefore increasingly important. The objective of this review was to present an overview of both instrumental and non-instrumental analytical techniques available for the determination of steroid estrogens in water samples, evidencing their respective potential advantages and limitations using the Need, Approach, Benefit, and Competition (NABC) approach. The analytical techniques highlighted in this review were instrumental and non-instrumental analytical techniques namely gas chromatography mass spectrometry (GC-MS), liquid chromatography mass spectrometry (LC-MS), enzyme-linked immuno sorbent assay (ELISA), radio immuno assay (RIA), yeast estrogen screen (YES) assay, and human breast cancer cell line proliferation (E-screen) assay. The complexity of water samples and their low estrogenic concentrations necessitates the use of highly sensitive instrumental analytical techniques (GC-MS and LC-MS) and non-instrumental analytical techniques (ELISA, RIA, YES assay and E-screen assay) to quantify steroid estrogens. Both instrumental and non-instrumental analytical techniques have their own advantages and limitations. However, the non-instrumental ELISA analytical techniques, thanks to its lower detection limit and simplicity, its rapidity and cost-effectiveness, currently appears to be the most reliable for determining steroid estrogens in water samples.