A combination of persulfate and hydrogen peroxide (S2O8(2-)/H2O2) was used to oxidizelandfill leachate. The reaction was performed under varying S2O8(2-)/H2O2 ratio (g/g), S2O8(2-)/H2O2 dosages (g/g), pH, and reaction time (minutes), so as to determine the optimum operational conditions. Results indicated that under optimum operational conditions (i.e. 120 min of oxidation using a S2O8(2-)/H2O2 ratio of 1 g/1.47 g at a persulfate and hydrogen peroxide dosage of 5.88 g/50 ml and8.63 g/50 ml respectively, at pH 11) removal of 81% COD and 83% NH3-N was achieved. In addition, the biodegradability (BOD5/COD ratio) of the leachate was improved from 0.09 to 0.17. The results obtained from the combined use of (S2O8(2-)/H2O2) were compared with those obtained with sodium persulfate only, hydrogen peroxide only and sodium persulfate followed by hydrogen peroxide. The combined method (S2O8(2-)/H2O2) achieved higher removal efficiencies for COD and NH3-N compared with the other methods using a single oxidizing agent. Additionally, the study has proved that the combination of S2O8(2-)/H2O2 is more efficient than the sequential use of sodium persulfate followed by hydrogen peroxide in advanced oxidation processes aiming at treatingstabilizedlandfill leachate.
Photocatalytic degradation is among the promising technology for removal of various dyes and organic contaminants from environment owing to its excellent catalytic activity, low energy utilization, and low cost. As one of potential photocatalysts, Fe2O3 has emerged as an important material for degradation of numerous dyes and organic contaminants caused by its tolerable band gap, wide harvesting of visible light, good stability and recyclability. The present review thoroughly summarized the classification, synthesis route of Fe2O3 with different morphologies, and several modifications of Fe2O3 for improved photocatalytic performance. These include the incorporation with supporting materials, formation of heterojunction with other semiconductor photocatalysts, as well as the fabrication of Z-scheme. Explicitly, the other photocatalytic applications of Fe2O3, including for removal of heavy metals, reduction of CO2, evolution of H2, and N2 fixation are also deliberately discussed to further highlight the huge potential of this catalyst. Moreover, the prospects and future challenges are also comprised to expose the unscrutinized criteria of Fe2O3 photocatalyst. This review aims to contribute a knowledge transfer for providing more information on the potential of Fe2O3 photocatalyst. In the meantime, it might give an idea for utilization of this photocatalyst in other environmental remediation application.
This study assessed the environmental impacts of the formulation of graphene oxide (GO)/multi-walled carbon nanotubes (MWCNTs) conductive membranes and of the process operating parameters of electrically-enhanced palm oil mill effluent (POME) filtration. Two different analyses approaches were employed, cradle-to-gate approach for conductive membrane production and gate-to-gate approach for the POME filtration process. The parameters in conductive-membrane formulation (e.g. the weight ratio of carbon nanomaterials, and concentration of GO/MWCNT nanohybrids) and process operating parameters (e.g. electric field strength and electricity operating mode) were investigated. The findings herein are twofold. Firstly, for the fabrication of GO/MWCNT conductive membranes, the best weight ratio of GO:MWCNTs was found to be 1:9, given its superior membrane electrical conductivity with lower environmental impacts by 8.51% compared to pristine MWCNTs. The most suitable concentration of carbon nanomaterials was found to be 5 wt%, given its lowest impacts on resource depletion, human health, and ecosystems. Secondly, for the electrically-enhanced POME filtration, the optimum process operating parameters were found to be the application of an electric field of 300 V/cm in the continuous mode, given its lower environmental impacts (22.99%-89.30%) secondary to its requirement of the least electricity to produce permeate. The present study has established not only the optimized conditions in membrane formulation but also the operating parameters of electrically-enhanced filtration; such findings enable the use of cleaner production and sustainable approach to minimize fouling for industrial applications, whilst maintaining excellent efficiency.
Energy is widely used in industry for heating and cooling, with natural gas (NG) being the largest primary energy source in Malaysia, closely followed by coal. Renewable energy, such as biogas upgrading to biomethane, could cut the use of fossil fuels by supplementing NG usage due to their similar physicochemical and thermochemical characteristics. Biogas production plants in Malaysia are more commonly seen in waste-to-energy scenarios, with the technology anaerobic digestion, and their deployment is supported via feed-in tariffs (FiT) for power generation. Other potential applications such as the conversion of biogas into biomethane, injection into the natural gas grid or transportation through a virtual pipeline may still need further technical development. This paper presents spatial techno economic optimisation modelling using BeWhere to determine decentralised biomethane production plants using feedstock from multiple sources of biogas, including palm oil mill effluent (POME), food waste, cattle manure and chicken manure. This model considered potential configurations and sizes of the biomethane plants, the transportation of biomethane using a virtual pipeline (at 250 psig) and demand in one of the states in Malaysia, namely Johor. It was found that two to four biomethane plants with capacities ranging between 125 and 700 m3/h were located in densely populated areas or heavier industrial consumers when the carbon tax was implemented at 167.71 EUR/tCO2 (800 MYR/tCO2). Sensitivity analysis suggested that biomethane production increases with the increasing country renewable energy share target to beyond 2080 MW. It is recommended that specific policy regulations and Feed-in Tariff (FiT) mechanisms are used to expand the biomethane market share in the country.
The main problem of landfill leachate is its diverse composition comprising many persistent organic pollutants which must be removed before being discharge into the environment. This study investigated the treatment of raw landfill leachate using electrocoagulation process. An electrocoagulation system was designed with iron as both the anode and cathode. The effects of inter-electrode distance, initial pH and electrolyte concentration on colour and COD removals were investigated. All these factors were found to have significant effects on the colour removal. On the other hand, electrolyte concentration was the most significant parameter affecting the COD removal. Numerical optimization was also conducted to obtain the optimum process performance. Under optimum conditions (initial pH: 7.73, inter-electrode distance: 1.16 cm, and electrolyte concentration (NaCl): 2.00 g/L), the process could remove up to 82.7% colour and 45.1% COD. The process can be applied as a pre-treatment for raw leachates before applying other appropriate treatment technologies.
The sustainable management of natural resources requires the consideration of multiple stakeholders' perspectives and knowledge claims, in order to inform complex and possibly contentious decision-making dilemmas. Hence, a better understanding of why people in particular contexts do manage natural resources in a particular way is needed. Focusing on mangroves, highly productive tropical intertidal forests, this study's first aim is to map the diversity of subjective viewpoints among a range of stakeholders on the management of Matang Mangrove Forest in peninsular Malaysia. Secondly, this study aims to feed the reflection on the possible consequences of the diversity of perspectives for the future management of mangroves in Malaysia and beyond. The use of the semi-quantitative Q methodology allowed us to identify three main discourses on mangrove management: i. the optimization discourse, stressing the need to improve the current overall satisfactory management regime; ii. the 'change for the better' discourse, which focuses on increasingly participatory management and on ecotourism; and iii. the conservative 'business as usual' discourse. The existence of common points of connection between the discourses and their respective supporters provides opportunities for modifications of mangrove management regimes. Acknowledging this diversity of viewpoints, reflecting how different stakeholders see and talk about mangrove management, highlights the need to develop pro-active and resilient natural resource management approaches.
This research investigates the impact of geopolitical risk, institutional governance and green finance on environmental outcomes, specifically focusing on carbon emissions and ecological footprint. Utilizing the dynamic CS-ARDL method and aggregated mean group analysis on a panel dataset covering 21 nations from 2000 to 2021, our findings reveal that heightened geopolitical risk leads to both short and long run increases in carbon emissions and the ecological footprint. Our study finds both a direct as well as indirect connection between governance, green finance and environmental outcomes in both the short and long run, highlighting the nuanced impact of governance on the formulation of environmental policies and regulatory frameworks. The results emphasize the need for targeted strategies, including focused investments and incentives for sustainable finance, particularly in conflict-affected regions. Furthermore, our research underscores the enduring impact of historical events, such as wars, on contemporary environmental indicators, emphasizing the importance of proactive conflict prevention measures. Our research suggests that policymakers should adopt comprehensive strategies that prioritize emission reduction during short-run spikes in geopolitical risk while maintaining a steadfast commitment to long-run sustainability.
Forest growth models are useful tools for investigating the long-term impacts of logging. In this paper, the results of the rain forest growth model FORMIND were assessed by a multicriteria decision analysis. The main processes covered by FORMIND include tree growth, mortality, regeneration and competition. Tree growth is calculated based on a carbon balance approach. Trees compete for light and space; dying large trees fall down and create gaps in the forest. Sixty-four different logging scenarios for an initially undisturbed forest stand at Deramakot (Malaysia) were simulated. The scenarios differ regarding the logging cycle, logging method, cutting limit and logging intensity. We characterise the impacts with four criteria describing the yield, canopy opening and changes in species composition. Multicriteria decision analysis was used for the first time to evaluate the scenarios and identify the efficient ones. Our results plainly show that reduced-impact logging scenarios are more 'efficient' than the others, since in these scenarios forest damage is minimised without significantly reducing yield. Nevertheless, there is a trade-off between yield and achieving a desired ecological state of logged forest; the ecological state of the logged forests can only be improved by reducing yields and enlarging the logging cycles. Our study also demonstrates that high cutting limits or low logging intensities cannot compensate for the high level of damage caused by conventional logging techniques.
Palm oil sludge (POS) is an organic waste generated from the palm oil industry. POS causes environmental pollution if it is improperly disposed. In this study, the potential of activated POS biochar, as an adsorbent for the removal of SO2 gas was tested. POS biochar was physically activated using CO2 gas. The effects of activation preparation variables i.e. activation temperature (300-700 °C), activation time (30-150 min) and CO2 flow rate (100-500 ml/min) were investigated using design expert version 8.0.7.1 software. Central Composite Design (CCD) was used to develop a quadratic model to correlate the operating variables with the activated biochar adsorption capacity. Analysis of variance (ANOVA) was performed to identify the significant factors on the experimental design response. The optimum preparation conditions of activated POS biochar were found to be at activation temperature of 442 °C, activation time of 63 min and CO2 flow rate of 397 ml/min. The maximum adsorption capacity at the optimum conditions was recorded as 16.65 mg/g. The adsorption capacity increased significantly after the activation process. Characteristics of the activated POS biochar proposed that SO2 was physically adsorbed. Furthermore, it was found that the adsorption capacity can be further enhanced by increasing the reaction temperature to 100 °C or with 15% of relative humidity in the inlet gas. The prepared adsorbents can be regenerated by thermal treatment.
In this study two deep eutectic solvents (DESs) were prepared using ethylene glycol (EG) and two different ammonium-based salts. The potential of these DESs as novel agents for CNTs functionalization was examined by performing a comprehensive characterization study to identify the changes developing after the functionalization process. The impact of DESs was obvious by increasing the surface area of CNTs to reach 197.8 (m2/g), and by adding new functional groups to CNTs surface without causing any damage to the unique structure of CNTs. Moreover, CNTs functionalized with DESs were applied as new adsorbents for the removal of methyl orange (MO) from water. The adsorption conditions were optimized using RSM-CCD experimental design. The kinetics and the equilibrium adsorption data were analyzed using different kinetic and isotherm models. According to the regression results, adsorption kinetics data were well described by pseudo-second order model, whereas adsorption isotherm data were best represented by Langmuir isotherm model. The highest recorded maximum adsorption capacity (qmax) value was found to be 310.2 mg/g.
Poor performance of wet scrubbers in rubber processing plants due to breakthrough of specific volatile organic compounds (VOCs) causes odour impact events. The performance of wet scrubbers in the rubber drying process to remove VOCs was investigated in order to determine the responsible odorants. VOC emissions originating at the inlet and outlet of wet scrubbers were quantified using gas chromatography-mass spectrometry/olfactometry (GC-MS/O). Critical VOCs were identified alongside seasonal and daily variations of those VOCs. Altogether, 80 VOCs were detected in rubber emissions with 16 classified as critical VOCs based on their chemical concentration, high odour activity value (OAV) and unpleasant odour. Volatile fatty acids (VFAs) were the dominant VOCs with seasonal variations affecting emission composition. Results demonstrated the ineffectiveness of the wet scrubbers to mitigate odorous VOCs whereas the removal of some VOCs could be improved based on their polarity and solubility. It was found that there is a correlation between the wet scrubber performance and VFAs concentration in the emissions. The findings demonstrated that combining quantitative and sensory analyses improved accuracy in identifying odorous VOCs, which can cause odour annoyance from rubber processing. A VOC identification framework was proposed using both analyses approaches.
Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986-2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.
Microbial fuel cells (MFCs) are considered as promising technology to achieve simultaneous wastewater treatment and electricity generation. However, operational and technological developments are still required to make it as a sustainable technology. In the present study, response surface methodology (RSM) was used to evaluate the effects of substrate concentration, co-culture composition, pH and time on the performance of co-culture (Klebsiella variicola and Pseudomonas aeruginosa) inoculated double chamber MFC. From the statistical analysis, it can be seen that the performance of MFC was not influenced by the interaction between the initial COD and time, pH and time, pH and initial COD, time and initial COD. However, the interaction between the inoculum composition and time, pH and the inoculum composition, initial COD and inoculum composition significantly influenced the performance of MFC. Based on the RSM results, best performance (power density and COD removal efficiency) was obtained when the inoculum composition, initial COD, pH and time were about 1:1, 26.690 mg/L, 7.21 and 15.50 days, respectively. The predictions from the model were in close agreement with the experimental results suggesting that the proposed model could adequately represent the actual relationships between the independent variables generating electricity and the COD removal efficiency.
Mesoporous activated carbon was prepared using a hydrochar derived from coconut shell waste through hydrothermal carbonization and NaOH chemical activation process (COSHTC). Three sets of activated carbons were obtained with different hydrochar:NaOH impregnation ratios (1:1, 1:2, and 1:3). Among these ratios, 1:3 (COSHTC3) exhibited the optimum adsorption for methylene blue (MB). COSHTC3 adsorbed MB with an initial concentration of 25-250 mg/L at pH 3-11 and 30 °C. The adsorption isotherm of MB on COSHTC3 demonstrated that Langmuir isotherm could be better applied at a maximum monolayer adsorption capacity of 200.01 mg/g at 30 °C. The data was well fitted to the pseudo-second-order (PSO) kinetic model. These results show that the COSHTC3 prepared from low-cost agricultural waste (coconut shell) with average pore diameter 28.6 Å and surface area 876.14 m(2)/g acts as a better adsorbent for removal of cationic dyes and could pave the way for more low-cost adsorbents for dye removal.
Studies on sustainable management of waste from electrical and electronic equipment (or e-waste) have gained increasing attention from researchers around the world in recent years, with investigations into various aspects of e-waste management were investigated. Studies on e-waste generation by previous papers have been reviewed to provide an overview of the current research progress and recommendations for future research. The relevant existing studies were collected from various databases. Using content analysis, three main aspects of the existing studies were evaluated: the distribution and trends of the publications, the scope and boundaries of the studies, and the current research practices and research applications. Although there was a significant increasing trend of the amount of research on the evaluation of e-waste generation, however, the number of publications based on the countries of origin was still small. Another limitation was found related to the differences in the selection of research subjects and the level of analysis resulted in variations in the scopes and boundaries of the existing studies. Various other research areas were investigated further based on their research findings, but the analysis of various methodological aspects was complicated due to the increasing number of newly developed methodologies and the lack of comprehensive and up-to-date reviews on this research area. Additionally, there was also a need to evaluate emerging and/or older technology, which led electrical appliances to be overlooked. We found that comprehensive and up-to-date reviews of the methodological aspects of e-waste generation are still lacking. Based on the research gaps and limitations discussed, recommendations for future research were made.
Pilot-scale constructed wetlands planted with Scirpus grossus, were used to investigate the effects of applying a three-rhizobacterial consortium (Bacillus cereus strain NII, Bacillus subtilis strain NII and Brevibacterium sp. strain NII) on the growth of S. grossus and also on the accumulation of iron (Fe) and aluminium (Al) in S. grossus. The experiment includes constructed wetlands with the addition of 2% of the consortium rhizobacteria and without the consortium rhizobacteria addition (acting as control). During each sampling day (0, 5, 10, 15, 20, 25, 30, 42, 72 and 102), plant height, concentration of Fe and Al and sand microbial community were investigated. The results for the constructed wetland with the addition of consortium rhizobacteria showed the growth of S. grossus increased significantly at 26% and 29% for plant height and dry weight, respectively. While the accumulation of Fe and Al in S. grossus were enhanced about 48% and 19% respectively. To conclude, the addition of the rhizobacteria consortium has enhanced both the growth of S. grossus and the metal accumulation. These results suggesting that rhizobacteria has good potential to restore Fe and Al contaminated water in general and particularly for mining wastewater.
Oleochemicals industry effluence mainly contains a high chemical oxygen demand (COD) in a range of 6000-20,000 ppm. An effective biological wastewater treatment process must be carried out before wastewater is discharged into the environment. In this study, a submerged bed biofilm reactor (SBBR) was adapted to the biological oleochemical wastewater treatment plant observed in the present study. The effect of wastewater flow rate (100-300 mL/min), Cosmoball® percentage in the SBBR system (25-75%), and percentage of activated sludge (0-50%) were investigated in terms of COD reduction. The Box-Behnken design was used for response surface methodology (RSM) and to create a set of 18 experimental runs, which was needed for optimising the biological oleochemical wastewater treatment. A quadratic polynomial model with estimated coefficients was developed to describe COD reduction patterns. The analysis of variance (ANOVA) shows that the wastewater flow rate was the most effective factor in reducing COD, followed by activated sludge percentage and Cosmoball® carrier percentage. Under the optimum conditions (i.e., a wastewater flow rate of 103.25 mL/min a Cosmoball® carrier percentage of 71.94%, and an activated sludge percentage of 40.50%) a COD reduction of 98% was achieved. Thus, under optimum conditions, as suggested by the BBD, SBBR systems can be used as a viable means of biological wastewater treatment in the oleochemicals industry.
Landfill has become an underlying source of surface and groundwater pollution if not efficiently managed, due to the risk of leachate infiltration into to land and aquifers. The generated leachate is considered a serious environmental threat for the public health, because of the toxic and recalcitrant nature of its constituents. Thus, it must be collected and appropriately treated before being discharged into the environment. At present, there is no single unit process available for proper leachate treatment as conventional wastewater treatment processes cannot achieve a satisfactory level for degrading toxic substances present. Therefore, there is a growing interest in examination of different leachate treatment processes for maximum operational flexibility. Based on leachate characteristics, discharge requirements, technical possibilities, regulatory requirements and financial considerations, several techniques have been applied for its degradation, presenting varying degrees of efficiency. Therefore, this article presents a comprehensive review of existing research articles on the pros and cons of various leachate degradation methods. In line with environmental sustainability, the article stressed on the application and efficiency of sequencing batch reactor (SBR) system treating landfill leachate due to its operational flexibility, resistance to shock loads and high biomass retention. Contributions of integrated leachate treatment technologies with SBR were also discussed. The article further analyzed the effect of different adopted materials, processes, strategies and configurations on leachate treatment. Environmental and operational parameters that affect SBR system were critically discussed. It is believed that information contained in this review will increase readers fundamental knowledge, guide future researchers and be incorporated into future works on experimentally-based SBR studies for leachate treatment.
Suitable extraction technique and the least cost while reducing the environmental impact is the primary concern in timber transportation planning in undulate topography. Two types of extraction machines with unique characteristics to be applied in timber harvest area in Malaysia is combined for timber harvesting with the aim each machine will extract timber suitable to their ability. A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. The result shows the log fisher (1351 timbers) as a preferable extraction technique with total cost of RM 86,551.73 than the crawler tractor (206 timbers); the timber extraction route is 2630 m for the log fisher and 9860 m for the crawler tractor with total cost of RM 10,453.03. The model finds a suitable timber extraction technique and estimates the extraction costs. Further studies are required to compare the BA with other optimization methods for better results.
The concentration of soluble salts in surface water and rivers such as sodium, sulfate, chloride, magnesium ions, etc., plays an important role in the water salinity. Therefore, accurate determination of the distribution pattern of these ions can improve better management of drinking water resources and human health. The main goal of this research is to establish two novel wavelet-complementary intelligence paradigms so-called wavelet least square support vector machine coupled with improved simulated annealing (W-LSSVM-ISA) and the wavelet extended Kalman filter integrated with artificial neural network (W-EKF- ANN) for accurate forecasting of the monthly), magnesium (Mg+2), and sulfate (SO4-2) indices at Maroon River, in Southwest of Iran. The monthly River flow (Q), electrical conductivity (EC), Mg+2, and SO4-2 data recorded at Tange-Takab station for the period 1980-2016. Some preprocessing procedures consisting of specifying the number of lag times and decomposition of the existing original signals into multi-resolution sub-series using three mother wavelets were performed to develop predictive models. In addition, the best subset regression analysis was designed to separately assess the best selective combinations for Mg+2 and SO4-2. The statistical metrics and authoritative validation approaches showed that both complementary paradigms yielded promising accuracy compared with standalone artificial intelligence (AI) models. Furthermore, the results demonstrated that W-LSSVM-ISA-C1 (correlation coefficient (R) = 0.9521, root mean square error (RMSE) = 0.2637 mg/l, and Kling-Gupta efficiency (KGE) = 0.9361) and W-LSSVM-ISA-C4 (R = 0.9673, RMSE = 0.5534 mg/l and KGE = 0.9437), using Dmey mother that outperformed the W-EKF-ANN for predicting Mg+2 and SO4-2, respectively.