The spatial and temporal distributions of trace metals in dissolved forms mainly result from anthropogenic and lithogenic contributions. Surface water samples (∼0.5 m) were collected monthly at respective stations from Setiu Wetland. In this study, the behaviour of trace metals in the dissolved phases along the water column from sampling sites in the Setiu Wetland, Malaysia was investigated. In addition, dissolved organic carbon (DOC) and physical parameters such as salinity, temperature, pH and dissolved oxygen (DO) of the surface water were measured in order to evaluate the relationship between trace metals fractionation with different water quality parameters. Size fractionation study of dissolved trace metals using ultrafiltration technique were also carried out and analysed using inductively coupled plasma mass spectrometry (ICP-MS). Correlation of trace metals with other measured parameters was made to furthermore understand the dynamics of trace metals and its fractionated components in this area. The concentration of dissolved trace metals was in the range of 0.001-0.16 μg/L for Cd, 0.12-2.81 μg/L for Cu, 0.01-1.84 μg/L for Pb, 3-17 μg/L for Fe and 1-34 μg/L for Zn, suggesting the input of anthropogenic sources for trace metals such as municipal, industrial, agricultural and domestic discharge. The periodic monitoring and evaluation of trace metals in wetlands and protected tropical areas is highly recommended.
Dye is one of the pollutants found in water bodies because of the increased growth of the textile industry. In this study, Scirpus grossus was planted inside a constructed wetland to treat mixed dye (methylene blue and methyl orange)-containing wastewater under batch and continuous modes. The plants were exposed to various concentrations (0, 50, 75, and 100 mg/L) of mixed dye for 72 days (with hydraulic retention time of 7 days for the continuous system). Biological oxygen demand, chemical oxygen demand, total organic carbon, pH, temperature, ionic content, and plant growth parameters were measured. Results showed that S. grossus can withstand all the tested dye concentrations until the end of the treatment period. Color removal efficiencies of 86, 84, and 75% were obtained in batch mode, whereas 90%, 85%, and 79% were obtained in continuous mode for 50, 75, and 100 mg/L dye concentrations, respectively. Fourier-transform infrared analysis confirmed the transformation of dye compounds after treatment and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy analysis showed that most of the intermediate compounds were not absorbed into plants but adsorbed onto the surface of the root structure.
This study examined the impact of worldwide governance indicators on the sustainability of the bioenergy industry in selected European countries for the period 1996-2018. Applying the Fixed Effect (FE) Model, the results reveal that the bioenergy industry can significantly grow by improving the quality of worldwide governance indicators in European countries, especially in Western European Countries (WEC). Government effectiveness, rule of law, regulatory quality, and voice and accountability are found to be increasing the growth of the bioenergy industry. Precisely, the results further show that the magnitude of the effect of government effectiveness, voice and accountability, and Gross Domestic Product (GDP) on bioenergy output is higher in Western European Countries (WEC) as compared to the Central and Eastern European Countries (CEEC). Also, the findings further elaborate that the significant positive impact of regulatory quality and rule of law on bioenergy output is higher in CEEC countries compared to the WEC countries. The finding implies that the growth of the bioenergy industry in European countries can be effectively increased by improving the practice and quality of worldwide governance indicators. The study recommends for European countries to increase the efficiency of worldwide governance in their bioenergy industry to increase the sustainability of bioenergy production and reduce Dioxide Carbon (CO2) emissions. Policymakers in these countries should also invest more in worldwide governance to increase its effectiveness and transparency in the bioenergy industry. The authorities should equally emphasize the effectiveness and transparency of worldwide governance indicators to attain bioenergy security and lessen the dependence on fossil fuels.
The practice of aquaculture is associated with the generation of a substantial quantity of effluent. Microalgae must effectively assimilate nitrogen and phosphorus from their surrounding environment for growth. This study modeled the algal biomass film, NO3-N concentration, and pH in the membrane bioreactor using the response surface methodology (RSM) and an artificial neural network (ANN). Furthermore, it was suggested that the optimal condition for each parameter be determined. The results of ANN modeling showed that ANN with a structure of 5-3 and employing the transfer functions tansig-logsig demonstrated the highest level of accuracy. This was evidenced by the obtained values of coefficient (R2) = 0.998, R = 0.999, mean squared error (MAE) = 0.0856, and mean square error (MSE) = 0.143. The ANN model, characterized by a 5-5 structure and employing the tansig-logsig transfer function, demonstrates superior accuracy when predicting the concentration of NO3-N and pH. This is evidenced by the high values of R2 (0.996), R (0.998), MAE (0.00162), and MSE (0.0262). The RSM was afterward employed to maximize the performance of algal film biomass, pH levels, and NO3-N concentrations. The optimal conditions for the algal biomass film were a concentration of 2.884 mg/L and a duration of 6.589 days. Similarly, the most favorable conditions for the NO3-N concentration and pH were 2.984 mg/L and 6.787 days, respectively. Therefore, this research uses non-dominated sorting genetic algorithm II (NSGA II) to find the optimal NO3-N concentration, algal biomass film, and pH for product or process quality. The region has the greatest alkaline pH and lowest NO3-N content.
Microplastics (MPs) have become a prevalent environmental concern, exerting detrimental effects on marine and terrestrial ecosystems, as well as human health. Addressing this urgent issue necessitates the implementation of coordinated waste management policies and strategies. In this study, we present a comprehensive review focusing on key results and the underlying mechanisms associated with microplastics. We examine their sources and pathways, elucidate their ecological and human health impacts, and evaluate the current state of waste management policies. By drawing upon recent research and pertinent case studies, we propose a range of practical solutions, encompassing enhanced recycling and waste reduction measures, product redesign, and innovative technological interventions. Moreover, we emphasize the imperative for collaboration and cooperation across sectors and jurisdictions to effectively tackle this pressing environmental challenge. The findings of this study contribute to the broader understanding of microplastics and provide valuable insights for policymakers, researchers, and stakeholders alike.
Mixed culture sludge has been widely used as a microbial consortium for biohydrogen production. Simple thermal treatment of sludge is usually required in order to eliminate any H2-consuming bacteria that would reduce H2 production. In this study, thermal treatment of sludge was carried out at various temperatures. Electron flow model was then applied in order to assess community structure in the sludge upon thermal treatment for biohydrogen production. Results show that the dominant electron sink was acetate (150-217 e- meq/mol glucose). The electron equivalent (e- eq) balances were within 0.8-18% for all experiments. Treatment at 100 °C attained the highest H2 yield of 3.44 mol H2/mol glucose from the stoichiometric reaction. As the treatment temperature increased from 80 to 100 °C, the computed acetyl-CoA and reduced form of ferredoxin (Fdred) concentrations increased from 13.01 to 17.34 e- eq (1.63-2.17 mol) and 1.34 to 4.18 e- eq (0.67-2.09 mol), respectively. The NADH2 balance error varied from 3 to 10% and the term e-(Fd↔NADH2) (m) in the NADH2 balance was NADH2 consumption (m = -1). The H2 production was mainly via the Fd:hydrogenase system and this is supported with a good NADH2 balance. Using the modified Gompertz model, the highest maximum H2 production potential was 1194 mL whereas the maximum rate of H2 production was 357 mL/h recorded at 100 °C of treatment.
Textile wastewater laden with dyes has emerged as a source of water pollution. This possesses a challenge in its effective treatment using a single functional material. In respond to this technological constraint, this work presents multifunctional cotton fabrics (CFs) within a single, streamlined preparation process. This approach utilizes the adherence of Ag NPs (nanoparticles) using Si binder on the surface of CFs, resulting in Ag-coated CFs through a pad dry method. The prepared samples were characterized using scanning electron microscope-energy dispersive X-ray electroscopy (SEM-EDS), thermal gravimetric analysis (TGA), Fourier transformation infrared (FT-IR). It was found that the FT-IR spectra of Ag NPs-coated CFs had peaks appear at 3400, 2900, and 1200 cm-1, implying the stretching vibrations of O-H, C-H, and C-O, respectively. Based on the EDX analysis, the presence of C, O, and Ag related to the coated CFs were detected. After coating the CFs with varying concentrations of Ag NPs (1%, 2% and 3% (w/w)), they were used to remove dyes. Under the same concentration of 10 mg/L and optimized pH 7.5 and 2 h of reaction time, 3% (w/w) Ag-coated CFs exhibited a substantial MB degradation of 98 %, while removing 95% of methyl orange, 85% of rhodamine B, and 96% of Congo red, respectively, following 2 h of Vis exposure. Ag NPs had a strong absorption at 420 nm with 2.51 eV of energy band gap. Under UV irradiation, electrons excited and produced free radicals that promoted dyes photodegradation. The oxidation by-products included p-dihydroxybenzene and succinic acid. Spent Ag-coated CFs attained 98% of regeneration efficiency. The utilization of Ag-coated CFs as a photocatalyst facilitated treated effluents to meet the required discharge standard of lower than 1 mg/L mandated by national legislation. The integration of multifunctional CFs in the treatment system presents a new option for tackling water pollution due to dyes.
This study critically reviews the recent developments and future opportunities pertinent to the conversion of CO2 as a potent greenhouse gas (GHG) to fuels and valuable products. CO2 emissions have reached an alarming level of around 410 ppm and have become the primary driver of global warming and climate change leading to devastating events such as droughts, hurricanes, torrential rains, floods, tornados and wildfires across the world. These events are responsible for thousands of deaths and have adversely affected the economic development of many countries, loss of billions of dollars, across the globe. One of the promising choices to tackle this issue is carbon sequestration by pre- and post-combustion processes and oxyfuel combustion. The captured CO2 can be converted into fuels and valuable products, including methanol, dimethyl ether (DME), and methane (CH4). The efficient use of the sequestered CO2 for the desalinization might be critical in overcoming water scarcity and energy issues in developing countries. Using the sequestered CO2 to produce algae in combination with wastewater, and producing biofuels is among the promising strategies. Many methods, like direct combustion, fermentation, transesterification, pyrolysis, anaerobic digestion (AD), and gasification, can be used for the conversion of algae into biofuel. Direct air capturing (DAC) is another productive technique for absorbing CO2 from the atmosphere and converting it into various useful energy resources like CH4. These methods can effectively tackle the issues of climate change, water security, and energy crises. However, future research is required to make these conversion methods cost-effective and commercially applicable.
This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, G, and the number of textural features, are investigated to determine the best parameter values of the bin images. The parameter values and number of texture features are used to form the GLCM database. The most appropriate features collected from the GLCM are then used as inputs to the multi-layer perceptron (MLP) and the K-nearest neighbor (KNN) classifiers for bin image classification and grading. The classification and grading performance for DB1, DB2 and DB3 features were selected with both MLP and KNN classifiers. The results demonstrated that the KNN classifier, at KNN = 3, d = 1 and maximum G values, performs better than using the MLP classifier with the same database. Based on the results, this method has the potential to be used in solid waste bin level classification and grading to provide a robust solution for solid waste bin level detection, monitoring and management.
In-situ bioremediation of mangrove soil contaminated with polyethylene terephthalate (PET) and polystyrene (PS) microplastics was investigated using indigenous microbial consortium with adequate capacity to degrade the plastics. Eight (8) bacteria were isolated from plastic/microplastic-inundated mangrove soil and screened for the ability to degrade PET and PS microplastics. Optical density at 600 nm and colony forming unit counts were measured to evaluate the growth response of the microbes in the presence of PS and PET microplastics at different times of exposure. Structural and surface changes that occurred post biodegradation on the microplastics were determined through EDS and SEM analysis. The obtained results demonstrated the elongation and disappearance of peaks, suggesting that the microbial consortium could modify both types of microplastics. The overall results of the microplastic degradation showed varied degrees of weight loss after 90 experimental days, with the treated plot recorded 18% weight loss. The augmented soil was increased in the concentrations of Si S, and Fe and decreased in the concentrations of C, O, Na, Mg, Al, Cl, and K after bioremediation.
Most palm oil currently available in global markets is sourced from certified large-scale plantations. Comparatively little is sourced from (typically uncertified) smallholders. We argue that sourcing sustainable palm oil should not be determined by commercial certification alone and that the certification process should be revisited. There are so-far unrecognized benefits of sourcing palm oil from smallholders that should be considered if genuine biodiversity conservation is to be a foundation of 'environmentally sustainable' palm oil production. Despite a lack of certification, smallholder production is often more biodiversity-friendly than certified production from large-scale plantations. Sourcing palm oil from smallholders also alleviates poverty among rural farmers, promoting better conservation outcomes. Yet, certification schemes - the current measure of 'sustainability' - are financially accessible only for large-scale plantations that operate as profit-driven monocultures. Industrial palm oil is expanding rapidly in regions with weak environmental laws and enforcement. This warrants the development of an alternative certification scheme for smallholders. Greater attention should be directed to deforestation-free palm oil production in smallholdings, where production is less likely to cause large scale biodiversity loss. These small-scale farmlands in which palm oil is mixed with other crops should be considered by retailers and consumers who are interested in promoting sustainable palm oil production. Simultaneously, plantation companies should be required to make their existing production landscapes more compatible with enhanced biodiversity conservation.
This study analyzes and compares the results of leachate composition at the semi-aerobic Pulau Burung Landfill Site (PBLS) (unaerated pond and intermittently aerated pond) and the anaerobic Kulim Sanitary Landfill in the northern region of Malaysia. The raw samples were collected and analyzed for twenty parameters. The average values of the parameters such as phenols (1.2, 6.7, and 2.6 mg/L), total nitrogen (448, 1200, and 300 mg/L N-TN), ammonia-N (542, 1568, and 538 mg/L NH(3)-N), nitrite (91, 49, and 52 mg/L NO(2)(-)-N), total phosphorus (21, 17, and 19 mg/L), BOD(5) (83, 243, and 326 mg/L), COD (935, 2345, and 1892 mg/L), BOD(5)/COD (0.096,0.1124,0.205%), pH (8.20, 8.28, and 7.76), turbidity (1546, 180, and 1936 Formazin attenuation units (FAU)), and color (3334, 3347, and 4041 Pt Co) for leachate at the semi-aerobic PBLS (unaerated and intermittently aerated) and the anaerobic Kulim Sanitary Landfill were recorded, respectively. The obtained results were compared with previously published data and data from the Malaysia Environmental Quality Act 1974. The results indicated that Pulau Burung leachate was more stabilized compared with Kulim leachate. Furthermore, the aeration process in PBLS has a considerable effect on reducing the concentration of several pollutants. The studied leachate requires treatment to minimize the pollutants to an acceptable level prior to discharge into water courses.
Malaysia alone produces more than 49 million m3 palm oil mill effluent per year. Biological treated palm oil mill effluent via ponding system often fails to fulfill the regulatory discharge standards. This is due to remaining of non-biodegradable organics in the treated effluent. Thus, the aim of this study was to resolve such issue by using electro persulphate oxidation process, for the first time, as a post treatment of palm oil mill effluent. Central composite design in response surface methodology was used to analyze and optimize the interaction of operational variables (i.e., current density, contact time, initial pH and persulphate dosage) targeted on maximum treatment efficiency. The significance of quadratic model of each response was determined by analysis of variance, where all models indicated sufficient significance with p-value
Palm oil processing is a multi-stage operation which generates large amount of effluent. On average, palm oil mill effluent (POME) may contain up to 51, 000 mg/L COD, 25,000 mg/L BOD, 40,000 TS and 6000 mg/L oil and grease. Due to its potential to cause environmental pollution, palm oil mills are required to treat the effluent prior to discharge. Biological treatments using open ponding system are widely used for POME treatment. Although these processes are capable of reducing the pollutant concentrations, they require long hydraulic retention time and large space, with the effluent frequently failing to satisfy the discharge regulation. Due to more stringent environmental regulations, research interest has recently shifted to the development of polishing technologies for the biologically-treated POME. Various technologies such as advanced oxidation processes, membrane technology, adsorption and coagulation have been investigated. Among these, advanced oxidation processes have shown potentials as polishing technologies for POME. This paper offers an overview on the POME polishing technologies, with particularly emphasis on advanced oxidation processes and their prospects for large scale applications. Although there are some challenges in large scale applications of these technologies, this review offers some perspectives that could help in overcoming these challenges.
The primary objective of this paper is to investigate the isolated impacts of hydroelectricity consumption on the environment in Malaysia as an emerging economy. We use four different measures of environmental degradation including ecological footprint, carbon footprint, water footprint and CO2 emission as target variables, while controlling for GDP, GDP square and urbanization for the period 1971 to 2016. A recently introduced unit root test with breaks is utilized to examine the stationarity of the series and the bounds testing approach to cointegration is used to probe the long run relationships between the variables. VECM Granger causality technique is employed to examine the long-run causal dynamics between the variables. Sensitivity analysis is conducted by further including fossil fuels in the equations. The results show evidence of an inverted U-shaped relationship between environmental degradation and real GDP. Hydroelectricity is found to significantly reduce environmental degradation while urbanization is also not particularly harmful on the environment apart from its effect on air pollution. The VECM Granger causality results show evidence of unidirectional causality running from hydroelectricity and fossil fuels consumption to all measures of environmental degradation and real GDP per capita. There is evidence of feedback hypothesis between real GDP to all environmental degradation indices. The inclusion of fossil fuel did not change the behavior of hydroelectricity on the environment but fossil fuels significantly increase water footprint.
Heavy metals (HMs) such as Lead (Pb) have played a vital role in increasing the sediments of the Australian bay's ecosystem. Several meteorological parameters (i.e., minimum, maximum and average temperature (Tmin, Tmax and TavgoC), rainfall (Rn mm) and their interactions with the other batch HMs, are hypothesized to have high impact for the decision-making strategies to minimize the impacts of Pb. Three feature selection (FS) algorithms namely the Boruta method, genetic algorithm (GA) and extreme gradient boosting (XGBoost) were investigated to select the highly important predictors for Pb concentration in the coastal bay sediments of Australia. These FS algorithms were statistically evaluated using principal component analysis (PCA) Biplot along with the correlation metrics describing the statistical characteristics that exist in the input and output parameter space of the models. To ensure a high accuracy attained by the applied predictive artificial intelligence (AI) models i.e., XGBoost, support vector machine (SVM) and random forest (RF), an auto-hyper-parameter tuning process using a Grid-search approach was also implemented. Cu, Ni, Ce, and Fe were selected by all the three applied FS algorithms whereas the Tavg and Rn inputs remained the essential parameters identified by GA and Boruta. The order of the FS outcome was XGBoost > GA > Boruta based on the applied statistical examination and the PCA Biplot results and the order of applied AI predictive models was XGBoost-SVM > GA-SVM > Boruta-SVM, where the SVM model remained at the top performance among the other statistical metrics. Based on the Taylor diagram for model evaluation, the RF model was reflected only marginally different so overall, the proposed integrative AI model provided an evidence a robust and reliable predictive technique used for coastal sediment Pb prediction.
A continuous increase in the amount of greenhouse gases (GHGs) is causing serious threats to the environment and life on the earth, and CO2 is one of the major candidates. Reducing the excess CO2 by converting into industrial products could be beneficial for the environment and also boost up industrial growth. In particular, the conversion of CO2 into methanol is very beneficial as it is cheaper to produce from biomass, less inflammable, and advantageous to many industries. Application of various plants, algae, and microbial enzymes to recycle the CO2 and using these enzymes separately along with CO2-phillic materials and chemicals can be a sustainable solution to reduce the global carbon footprint. Materials such as MOFs, porphyrins, and nanomaterials are also used widely for CO2 absorption and conversion into methanol. Thus, a combination of enzymes and materials which convert the CO2 into methanol could energize the CO2 utilization. The CO2 to methanol conversion utilizes carbon better than the conventional syngas and the reaction yields fewer by-products. The methanol produced can further be utilized as a clean-burning fuel, in pharmaceuticals, automobiles and as a general solvent in various industries etc. This makes methanol an ideal fuel in comparison to the conventional petroleum-based ones and it is advantageous for a safer and cleaner environment. In this review article, various aspects of the circular economy with the present scenario of environmental crisis will also be considered for large-scale sustainable biorefinery of methanol production from atmospheric CO2.
Microalgae technology, if managed properly, has promising roles in solving food-water-energy nexus. The Achilles' heel is, however, to lower the costs associated with cultivation and harvesting. As a favorable technique, application of membrane process is strongly limited by membrane fouling. This study evaluates performance of nylon 6,6 nanofiber membrane (NFM) to a conventional polyvinylidene fluoride phase inverted membrane (PVDF PIM) for filtration of Chlorella vulgaris. Results show that nylon 6,6 NFM is superhydrophilic, has higher size of pore opening (0.22 vs 0.18 μm) and higher surface pore density (23 vs 18 pores/μm2) leading to higher permeance (1018 vs 493 L/m2hbar) and better fouling resistant. Such advantages help to outperform the filterability of PVDF PIM by showing much higher steady-state permeance (286 vs 120 L/m2hbar), with comparable biomass retention. In addition, unlike for PVDF PIM, imposing longer relaxation cycles further enhances the performance of the NFM (i.e., 178 L/m2hbar for 0.5 min and 236 L/m2hbar for 5 min). Overall findings confirm the advantages of nylon 6,6 NFM over the PVDF PIM. Such advantages can help to reduce required membrane area and specific aeration demand by enabling higher flux and lowering aeration rate. Nevertheless, developments of nylon 6,6 NFM material with respect to its intrinsic properties, mechanical strength and operational conditions of the panel can still be explored to enhance its competitiveness as a promising fouling resistant membrane material for microalgae filtration.
Considering the chemical properties of batik effluents, an efficient and economical treatment process was established to treat batik wastewater containing not only high levels of Si and chemical oxygen demand (COD), but also toxic heavy metals. After mixing the effluents obtained from the boiling and soaking steps in the batik process, acidification using concentrated hydrochloric acid (conc. HCl) was conducted to polymerize the silicate under acidic conditions. Consequently, sludge was produced and floated. XRD and FT-IR analyses showed that wax molecules were coordinated by hydrogen bonding with silica (SiO2). The acidification process removed ∼78-95% of COD and ∼45-50% of Si, depending on the pH. In the next stage, magnesium oxide (MgO) was applied to remove heavy metals completely and almost 90% of the Si in the liquid phase. During this step, about 70% of COD was removed in the hydrogel that arose as a consequence of the crosslinking characteristics of the formed nano-composite, such as magnesium silicate or montmorillonite. The hydrogel was composed mainly of waxes with polymeric properties. Then, the remaining Si (∼300 mg/L) in the wastewater combined with the effluents from the rinsing steps was further treated using 50 mg/L MgO. As a final step, palm-shell activated carbon (PSAC) was used to remove the remaining COD to
Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM.