This work presents the synthesis of the novel silica-cyanopropyl functionalized magnetic graphene oxide (MGO/SiO2-CN) hybrid nanomaterial derived by sol-gel method as a cheap efficient magnetic sorbent for the removal of extremely hazardous lead ions from aqueous media. The integration of the magnetic property, the carbon substrate, and the nitrile (-C ≡ N) containing organic grafted silica matrix promoted the adsorption capability against lead ions along with its simple synthesis recovery and low cost. The prepared nanocomposite was comprehensively characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. Adsorption of lead was found to be pH dependent because of the charged nature of both analyte and adsorbent surface. Adsorption experiments were conducted under the optimum conditions, and the obtained experimental data from atomic absorption spectroscopy were analyzed using the popular isothermal models namely Langmuir, Freundlich, and Dubinin-Radushkevich isotherms as well as kinetically studied and evaluated for adsorption standard free energy (E). The experimental results have demonstrated the enhanced adsorption capability of the proposed sorbent nanocomposite for lead ion removal with the maximum adsorption capacity of 111.11 mg/g at pH 5.0. The proposed mechanism of lead adsorption was mainly attributed to the complexation of lead positive ions with the grafted -C ≡ N bond. The synergistic effect of the combination of three components (i.e., the magnetic graphene oxide matrix, the triple bond containing organic moiety, and the inorganic porous silica framework) excelled the adsorption capability and proved to be a good candidate as adsorbent for the removal of lead ions.
The focus of this work is to investigate the emission characteristics of a stationary diesel engine while utilizing an emulsion fuel from a novel preparation process. The emulsion preparation was performed in real time without using any surfactant. Instead of mechanically breaking the water down into droplets, the water is delivered thermally, by changing its phase from gas to liquid. Steam is used in this proposed process, where it will be converted into suspended water droplets once it meets colder diesel. The product is called steam-generated water-in-diesel emulsion fuel (S/D). The method is expected to reduce the moving components of a previous surfactant-less system; therefore, reducing costs and increasing the system reliability. The emission characteristics of S/D were compared with EURO 2 diesel (D2), and a conventional emulsion denoted as E10. E10 was prepared using 10% water (volumetric) and SPAN80 as a surfactant. The emission characterizations were carried out based on the exhaust gas of a single cylinder naturally aspirated CI engine fueled with D2, S/D, and E10. Compared to D2, both emulsions significantly reduced the emissions of nitrogen oxides (NOx) (E10 max ↓58.0%, S/D max ↓40.0%) and particulate matter (PM) (E10 max ↓20.0%, S/D max ↓57.0%).
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.
Occupational exposure to pesticide mixtures comprising active substance(s) and/or co-formulant(s) with known/possible endocrine-disrupting activity was assessed using long-term activity records for 50 professional operators representing arable and orchard cropping systems in Greece, Lithuania, and the UK. Exposure was estimated using the harmonised Agricultural Operator Exposure Model, and risk was quantified as a point of departure index (PODI) using the lowest no observed (adverse) effect level. Use of substances with known/possible endocrine activity was common, with 43 of the 50 operators applying at least one such active substance on more than 50% of spray days; at maximum, one UK operator sprayed five such active substances and 10 such co-formulants in a single day. At 95th percentile, total exposure was largest in the UK orchard system (0.041 × 10-2 mg kg bw-1 day-1) whereas risk was largest in the Greek cropping systems (PODI 0.053 × 10-1). All five cropping systems had instances indicating potential for risk when expressed at a daily resolution (maximum PODI 1.2-10.7). Toxicological data are sparse for co-formulants, so combined risk from complex mixtures of active substances and co-formulants may be larger in reality.
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model's accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model-which applies two hidden layers-achieved the best performance, then followed by ANN-MLP1 model-which applies one hidden layer and three inputs-while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.
In this work, a sunlight-sensitive photocatalyst of nanocubic-like titanium dioxide (TiO2) and N-doped graphene quantum dots (N-GQDs) is developed through a simple hydrothermal and physical mixing method. The successful amalgamation composite photocatalyst characteristics were comprehensively scrutinized through various physical and chemical analyses. A complete removal of bisphenol A (BPA) is attained by a synthesized composite after 30 min of sunlight irradiation as compared to pure TiO2. This clearly proved the unique contribution of N-GQDs that enhanced the ability of light harvesting especially under visible light and near-infrared region. This superior characteristic enables it to maximize the absorbance in the entire solar spectrum. However, the increase of N-GQDs weight percentage has created massive oxygen vacancies that suppress the generation of active radicals. This resulted in a longer duration for a complete removal of BPA as compared to lower weight percentage of N-GQDs. Hence, this finding can offer a new insight in developing effective sunlight-sensitive photocatalysts for various complex organic pollutants degradation.
Microalgal biomass produced from the phycoremediation of wastewater represents an important protein source, lipids, and natural antioxidants and bioproducts. Therefore, the microalgal biomass and their derived compounds are used in animal and aquaculture feed as well as human nutrition and health products. Many microalgal species have shown promising potential for many bioproducts. However, significant processes to find the optimum quality and quantity of microalgal biomass are still required especially when it is used as a replacement for aquaculture feed. The limitations lie in the selection of microalgal species and their production. The present review discusses the potential generation of bioproducts from microalgal biomass resulting from the phycoremediation of wet market wastewater. The consortium approach in wastewater treatment and the comparison between biomass production and available common feeds for aquaculture were reviewed.
This article projects the social cost of carbon (SCC) and other related consequences of climate change by using Malaysia's intended nationally determined contribution (INDC) and climate vision 2040 (CV2040) by 2050. It compares the projections derived from the Dynamic Integrated Model of the Climate and Economy (DICME) based on the respective INDC and CV2040 scenario. The results reveal that industrial emissions would incur a substantial increase every 5 years under the scenario CV2040, while Malaysia would experience lower industrial emissions in the coming years under the scenario INDC. Emission intensity in Malaysia will be 0.61 and 0.59 tons/capita in 2030 for scenario CV2040 and scenario INDC respectively. Malaysia would face climate damage of MYR456 billion and MYR 49 billion by 2050 under CV2040 and INDC scenario respectively. However, climate damage could be much lower if the INDC regime were adopted, as this scenario would decrease climatic impacts over time. The estimated SSC per ton of CO2 varies between MYR74 and MYR97 for scenario CV2040 and MYR44 and MYR62 for scenario INDC in 2030 and 2050 respectively. Considering different aspects, including industrial emissions, damage cost, and social cost of carbon, INDC is the best policy compared to CV2040. Thus, Malaysia could achieve its emissions reduction target by implementing INDC by 2050.
Protein hydrolysates and bioactive peptides from various protein sources have demonstrated their effectiveness for the prevention of illness and the improvement of symptoms from several diseases. In particular, the use of microalgae to generate bioactive peptides has received a growing interest because of their potential to be cultivated on non-arable land and high nutritional value. However, scant research is available on the toxicity of peptide-based preparations. The present study aims to evaluate the toxicity of microalgal protein hydrolysates (MPH) from one marine species of microalgae (Bellerochea malleus) to determine the feasibility of their use for functional food applications. Results showed that the oral administration of MPH at three doses (D1, 100 mg kg-1 BW; D2, 400 mg kg-1 BW; and D3, 2000 mg kg-1 BW) to male Wistar rats did not induce any adverse effects or mortality up to13 days of treatment. Data analysis of relative organ weights and biochemical and hematological parameters did not show any significant differences between control and treated groups at the three doses investigated. Data from histopathological observations did not reveal any signs of major toxicity at the doses D1 and D2. However, mild signs of inflammation and necrosis were observed in the kidney of rats fed MPH at D3. All together, these results reveal the overall safety of MPH and provide new evidence for advocating their use for functional food or nutraceutical applications.
The aim of this paper is to augment the existing literature on convergence of CO2 emissions, by adding carbon footprint per capita and ecological footprint per capita to the convergence debate. We use the residual augmented least squares regression to examine the stochastic convergence of the environmental indices in 27 OECD countries. Furthermore, in contrast to the previous studies which mainly used the conventional beta-convergence approach to examine conditional convergence, we use a beta-convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma-convergence of the environmental indices is also examined. The results suggest that conditional convergence exists in 12 countries for CO2 emissions per capita, 15 countries for carbon footprint per capita and also 13 countries for ecological footprint per capita. There is evidence for sigma-convergence for all the three indicators. The policy implications of the results are discussed in the body of the paper.
Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.
In this article, we have examined the hypothesis of convergence of renewable energy consumption in 27 OECD countries. However, instead of relying on classical techniques, which are based on the dichotomy between stationarity I(0) and nonstationarity I(1), we consider a more flexible approach based on fractional integration. We employ both parametric and semiparametric techniques. Using parametric methods, evidence of convergence is found in the cases of Mexico, Switzerland and Sweden along with the USA, Portugal, the Czech Republic, South Korea and Spain, and employing semiparametric approaches, we found evidence of convergence in all these eight countries along with Australia, France, Japan, Greece, Italy and Poland. For the remaining 13 countries, even though the orders of integration of the series are smaller than one in all cases except Germany, the confidence intervals are so wide that we cannot reject the hypothesis of unit roots thus not finding support for the hypothesis of convergence.
In this study, we analyzed hydroxylated polychlorinated biphenyls (OH-PCBs) in urine of both PCB transport workers and PCB researchers. A method to monitor OH-PCB in urine was developed. Urine was solid-phase extracted with 0.1% ammonia/ methanol (v/v) and glucuronic acid/sulfate conjugates and then decomposed using β-glucuronidase/arylsulfatase. After alkaline digestion/derivatization, the concentration of OH-PCBs was determined by HRGC/HRMS-SIM. In the first sampling campaign, the worker's OH-PCB levels increased several fold after the PCB waste transportation work, indicating exposure to PCBs. The concentration of OH-PCBs in PCB transport workers' urine (0.55~11 μg/g creatinine (Cre)) was higher than in PCB researchers' urine (
Several treatment technologies are available for the treatment of palm oil mill wastes. Vermicomposting is widely recognized as efficient, eco-friendly methods for converting organic waste materials to valuable products. This study evaluates the effect of different vermicompost extracts obtained from palm oil mill effluent (POME) and palm-pressed fiber (PPF) mixtures on the germination, growth, relative toxicity, and photosynthetic pigments of mung beans (Vigna radiata) plant. POME contains valuable nutrients and can be used as a liquid fertilizer for fertigation. Mung bean seeds were sown in petri dishes irrigated with different dilutions of vermicomposted POME-PPF extracts, namely 50, 60, and 70% at varying dilutions. Results showed that at lower dilutions, the vermicompost extracts showed favorable effects on seed germination, seedling growth, and total chlorophyll content in mung bean seedlings, but at higher dilutions, they showed inhibitory effects. The carotenoid contents also decreased with increased dilutions of POME-PPF. This study recommends that the extracts could serve as a good source of fertilizer for the germination and growth enhancement of mung bean seedlings at the recommended dilutions.
The process parameters of microwave hydrothermal carbonization (MHTC) have significant effect on yield of hydrochar. This study discusses the effect of process parameters on hydrochar yield produced from MHTC of rice husk. Results revealed that, over the ranges tested, a lower temperature, lower reaction time, lower biomass to water ratio, and higher particle size produce more hydrochar. Maximum hydrochar yield of 62.8% was obtained at 1000 W, 220 °C, and 5 min. The higher heating value (HHV) was improved significantly from 6.80 MJ/kg of rice husk to 16.10 MJ/kg of hydrochar. Elemental analysis results showed that the carbon content increased and oxygen content decreased in hydrochar from 25.9 to 47.2% and 68.5 to 47.0%, respectively, improving the energy and combustion properties. SEM analysis exhibited modification in structure of rice husk and improvement in porosity after MHTC, which was further confirmed from BET surface analysis. The BET surface area increased from 25.0656 m2/g (rice husk) to 92.6832 m2/g (hydrochar). Thermal stability of hydrochar was improved from 340 °C for rice husk to 370 °C for hydrochar.
Biodiesels have gained much popularity because they are cleaner alternative fuels and they can be used directly in diesel engines without modifications. In this paper, a brief review of the key studies pertaining to the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends, exhaust aftertreatment systems, and low-temperature combustion technology is presented. In general, most biodiesel blends result in a significant decrease in carbon monoxide and total unburned hydrocarbon emissions. There is also a decrease in carbon monoxide, nitrogen oxide, and total unburned hydrocarbon emissions while the engine performance increases for diesel engines fueled with biodiesels blended with nano-additives. The development of automotive technologies, such as exhaust gas recirculation systems and low-temperature combustion technology, also improves the thermal efficiency of diesel engines and reduces nitrogen oxide and particulate matter emissions.
This work describes the development of supported zeolite-Y membranes, prepared using the hydrothermal method, for the removal of nickel from an aqueous solution. Alumina hollow fibers prepared using the phase inversion and sintering technique were used as an inert support. The supported zeolite-Y membranes were characterized using the field emission scanning electron microscope (FESEM), X-ray diffraction (XRD), and the water permeation and rejection test. The performance of the supported zeolite-Y membranes for heavy metal removal using batch adsorption and filtration test was studied using the atomic absorption spectroscopy (AAS). The adsorption study shows that the removal of nickel was pH-dependent but affected by the presence of α-alumina. The seeded zeolite-Y membrane gave the highest adsorption capacity which was 126.2 mg g-1. This enabled the membrane to remove 63% of nickel ions from the aqueous solution within 180 min of contact time. The adsorption mechanism of nickel onto the zeolite-Y membrane was best fitted to the Freundlich isotherm. The kinetic study concluded that the adsorption was best fitted to pseudo-second-order model with higher correlation coefficient (R2 = 0.9996). The filtration study proved that the zeolite-Y membrane enabled to reduce the concentration of heavy metal at parts per billion level.
The feasibility of biomass-based activated carbons has received a huge attention due to their excellent characteristics such as inexpensiveness, good adsorption behaviour and potential to reduce a strong dependency towards non-renewable precursors. Therefore, in this research work, eco-friendly activated carbon from palm kernel shell that has been produced from one-stage physical activation by using the Box-Behnken design of Response Surface Methodology is highlighted. The effect of three input parameters-temperature, dwell time and gas flow rate-towards product yield and carbon dioxide (CO2) uptake at room temperature and atmospheric pressure are studied. Model accuracy has been evaluated through the ANOVA analysis and lack-of-fit test. Accordingly, the optimum condition in synthesising the activated carbon with adequate CO2 adsorption capacity of 2.13 mmol/g and product yield of 25.15 wt% is found at a temperature of 850 °C, holding time of 60 min and CO2 flow rate of 450 cm3/min. The synthesised activated carbon has been characterised by diverse analytical instruments including thermogravimetric analyser, scanning electron microscope, as well as N2 adsorption-desorption isotherm. The characterisation analysis indicates that the synthesised activated carbon has higher textural characteristics and porosity, together with better thermal stability and carbon content as compared to pristine palm kernel shell. Activated carbon production via one-step activation approach is economical since its carbon yield is within the industrial target, whereas CO2 uptake is comparable to the synthesised activated carbon from conventional dual-stage activation, commercial activated carbon and other published data from literature.
A Gram-negative, arsenite-resistant psychrotolerant bacterial strain, Yersinia sp. strain SOM-12D3, was isolated from a biofilm sample collected from a lake at Svalbard in the Arctic area. To our knowledge, this is the first study on the ability of acid-treated and untreated, non-living biomass of strain SOM-12D3 to absorb arsenic. We conducted batch experiments at pH 7, with an initial As(III) concentration of 6.5 ppm, at 30 °C with 80 min of contact time. The Langmuir isotherm model fitted the equilibrium data better than Freundlich, and the sorption kinetics of As(III) biosorption followed the pseudo-second-order rate equation well for both types of non-living biomass. The highest biosorption capacity of the acid-treated biomass obtained by the Langmuir model was 159 mg/g. Further, a high recovery efficiency of 96% for As(III) was achieved using 0.1 M HCl within four cycles, which indicated high adsorption/desorption. Fourier transformed infrared (FTIR) demonstrated the involvement of hydroxyl, amide, and amine groups in As(III) biosorption. Field emission scanning electron microscopy-energy dispersive analysis (FESEM-EDAX) indicated the different morphological changes occurring in the cell after acid treatment and arsenic biosorption. Our results highlight the potential of using acid-treated non-living biomass of the psychrotolerant bacterium, Yersinia sp. Strain SOM-12D3 as a new biosorbent to remove As(III) from contaminated waters.
The present work analyzes the effect of antioxidants on engine combustion performance of a multi-cylinder diesel engine fueled with PB30 and PB50 (30 and 50 vol.% palm biodiesel (PB)). Four antioxidants namely N,N'-diphenyl-1,4-phenylenediamine (DPPD), N-phenyl-1,4-phenylenediamine (NPPD), 2(3)-tert-Butyl-4-methoxyphenol (BHA), and 2-tert-butylbenzene-1,4-diol (TBHQ) were added at concentrations of 1000 and 2000 ppm to PB30 and PB50. TBHQ showed the highest activity in increasing oxidation stability in both PB30 and PB50 followed by BHA, DPPD, and NPPD respectively, without any negative effect on physical properties. Compared to diesel fuel, PB blends showed 4.61-6.45% lower brake power (BP), 5.90-8.69% higher brake specific fuel consumption (BSFC), 9.64-11.43% higher maximum in cylinder pressure, and 7.76-12.51% higher NO emissions. Carbon monoxide (CO), hydrocarbon (HC), and smoke opacity were reduced by 36.78-43.56%, 44.12-58.21%, and 42.59-63.94%, respectively, than diesel fuel. The start of combustion angles (SOC) of PB blends was - 13.2 to - 15.6 °CA BTDC, but the combustion delays were 5.4-7.8 °CA short compared to diesel fuel which were - 10 °CA BTDC and 11°CA respectively. Antioxidant fuels of PB showed higher BP (1.81-5.32%), CO (8.41-24.60%), and HC (13.51-37.35%) with lower BSFC (1.67-7.68%), NO (4.32-11.53%), maximum in cylinder pressure (2.33-4.91%) and peak heat release rates (HRR) (3.25-11.41%) than baseline fuel of PB. Similar SOC of - 13 to - 14 °CA BTDC was observed for PB blended fuels and antioxidants. It can be concluded that antioxidants' addition is effective in increasing the oxidation stability and in controlling the NOx emissions of palm biodiesel fuelled diesel engine.