This paper describes the synthesis of graphene-based activated carbon from carbonaceous rice straw fly ash in an electrical furnace and the subsequent potassium hydroxide extraction. The produced graphene has a proper morphological structure; flakes and a rough surface can be observed. The average size of the graphene was defined as up to 2000 nm and clarification was provided by high-resolution microscopes (FESEM and FETEM). Crystallinity was confirmed by surface area electron diffraction. The chemical bonding from the graphene was clearly observed, with -C=C- and O-H stretching at peaks of 1644 cm-1 and 3435 cm-1, respectively. Impurities in the graphene were found using X-ray photoelectron spectroscopy and energy dispersive X-ray spectroscopy. The measured size, according to zeta-potential analysis, was 8722.2 ± 25 nm, and the average polydispersity index was 0.576. The stability of the mass reduction was analyzed by a thermogravimetric at 100 °C, with a final reduction of ~ 11%.
Solvent flow reactor system was introduced into the extraction system to increase the system efficiency and enhance the extraction yield by adding fresh solvent during the extraction processes. The liquefaction experiment was carried out at various flow-rates (1, 3 and 5 ml/min), reaction times (30, 45 and 60 min) and reaction temperatures (300ºC, 350ºC, 400ºC, 420ºC and 450ºC) with tetralin as solvent. Despite the ability of adding fresh solvent into the extraction process, the conversion of oil+gas was still considered to be low as there was ~25% of coal extracts left to be converted into low molecular weight compounds. One possible option to increase the oil yield is by applying catalyst that will further break up the coal extracts into small molecular weight compounds. In this study, a second reactor was introduced consisting of catalyst (NiSiO2) assuming that the catalyst would interact more effectively with coal extracts rather than the coal itself. In the
absence of catalyst, the oil yield was 55%. By introducing the Ni catalyst, the oil yield increased by 15%. Further analysis of GCMS showed that the oil from catalytic liquefaction gave out more low molecular weight compounds in comparison to the un-catalytic liquefaction oil.
Malaysia is the world’s top manufacturer of examination and surgical natural rubber (NR) gloves, exported mainly to the USA and Europe. The glove manufacturing process yields effluent which must be treated to comply with the stringent regulatory requirements imposed by the Malaysian Department of Environment. To make glove manufacturing an eco-friendly process, efforts are geared towards minimizing and utilizing waste or converting it into raw material for making value-added products. Waste generated from the glove industry is mainly rubber sludge which is obtained from the chemical flocculation stage of the effluent treatment process and consists of mainly rubber, remnants of compounding ingredients and water. R&D work by the Malaysian Rubber Board on waste utilization and resource recovery investigations have revealed many uses for this sludge. This paper briefly outlines only one of the many options available, which is the conversion of the sludge into sludge derived fuel (SDF). Preliminary study has identified three formulations of SDF with calorific values (CV) exceeding 16 000 kJ/kg, matching a good grade coal. This was considered as promising results which warrant explorative work for further increasing the CV of SDF to turn it into a viable fuel substitute in the latex products manufacturing industry and subsequently apply for a Clean Development Mechanism status to generate income.
Current study concerns measurement of radioactivity levels in areas surrounding a 2420 MW thermal power plant fueled predominantly by bituminous coal. The concentrations of (226)Ra, (232)Th and (40)K in onsite bottom-ash were found to be 139 Bq/kg, 108 Bq/kg and 291 Bq/kg, respectively, the levels for these radiolnuclides in soil decreasing with distance from the power plant. At the plant perimeter the respective radionuclide concentrations were 87 Bq/kg, 74 Bq/kg and 297 Bq/kg. In a nearby town, the corresponding concentrations were 104 Bq/kg, 52 Bq/kg and 358 Bq/kg, suggestive of use of TENORM affected soils. The mean radium equivalent activities (Raeq) in soil and ash sample in the town were 205 Bq/kg and 316 Bq/kg, respectively. The Kapar plant ash/slag appears to contain a higher level of TENORM than the world average. The degree of contamination is much higher inside the town where slag has been mixed with topsoil as landfill or as simple domestic waste. For the prevailing levels of exposure and a worst case senario, the predicted committed effective dose due to ingestion and inhalation for intake durations of 1- and 30 years would be 4.2 μSv and 220 μSv, respectively.
This study was designed to determine the particle size distribution and develop road dust index combining source and transport factors involving road dust for dust pollution quantification in Rawang. Principal component analysis (PCA) was applied to identify possible sources of potentially toxic elements and spot major pollution areas in Rawang. The health risks (carcinogenic and noncarcinogenic) to adults and children were assessed using the hazard index and total lifetime cancer Risk, respectively. A total of 75 road dust samples were collected and particle sizes (1000, 500, 250, 160, 125 and 63 µm) were determined. Concentrations of potentially toxic elements (Cu, Cd, Co, Cr, Pb, Ni, Zn and As) in particle size of 63 µm were analyzed. The results demonstrated that the highest grain size of 250 µm has contributed almost more than 25% of atmospheric particulate pollution. The highest potentially toxic element concentration was Pb (593.3 mg/kg), whereas the lowest was Co (5.6 mg/kg). Road dust index output indicated that pollution risk fell into moderate levels in eastern and northern areas of Rawang. Similarly, PCA results revealed that potentially toxic elements (Cu, Cd, Pb, Zn, Ni and Cr) were linked with anthropogenic sources (urbanization process, industrial and commercial growth, urban traffic congestion) in northern and southern parts of Rawang. Cobalt and As concentrations were explained mainly from natural sources. Noncarcinogenic risk by hazard index value more than 1.0 was indicated for adults and children. Similarly, carcinogenic risk by total lifetime cancer risk value also showed carcinogenic risks among adults and children.
Novel heterogeneous catalysts from calcium oxide (CaO)/calcined calcium carbonate (CaCO(3)) loaded onto different palm oil mill boiler ashes were synthesised and used in the transesterification of crude palm oil (CPO) with methanol to yield biodiesel. Catalyst preparation parameters including the type of ash support, the weight percentage of CaO and calcined CaCO(3) loadings, as well as the calcination temperature of CaCO(3) were optimised. The catalyst prepared by loading of 15 wt% calcined CaCO(3) at a fixed temperature of 800°C on fly ash exhibited a maximum oil conversion of 94.48%. Thermogravimetric analysis (TGA) revealed that the CaCO(3) was transformed into CaO at 770°C and interacted well with the ash support, whereas rich CaO, Al(2)O(3) and SiO(2) were identified in the composition using X-ray diffraction (XRD). The fine morphology size (<5 μm) and high surface area (1.719 m(2)/g) of the fly ash-based catalyst rendered it the highest catalytic activity.
The combustion characteristics of Malaysia oil palm biomass (palm kernel shell (PKS), palm mesocarp fibre (PMF) and empty fruit bunches (EFB)), sub-bituminous coal (Mukah Balingian) and coal/biomass blends via thermogravimetric analysis (TGA) were investigated. Six weight ratios of coal/biomass blends were prepared and oxidised under dynamic conditions from temperature 25 to 1100°C at four heating rates. The thermogravimetric analysis demonstrated that the EFB and PKS evolved additional peak besides drying, devolatilisation and char oxidation steps during combustion. Ignition and burn out temperatures of blends were improved in comparison to coal. No interactions were observed between the coal and biomass during combustion. The apparent activation energy during this process was evaluated using iso-conversional model free kinetics which resulted in highest activation energy during combustion of PKS followed by PMF, EFB and MB coal. Blending oil palm biomass with coal reduces the apparent activation energy value.
This study aims to investigate the behaviour of Malaysian sub-bituminous coal (Mukah Balingian), oil palm biomass (empty fruit bunches (EFB), kernel shell (PKS) and mesocarp fibre (PMF)) and their respective blends during pyrolysis using thermogravimetric analysis (TGA). The coal/palm biomass blends were prepared at six different weight ratios and experiments were carried out under dynamic conditions using nitrogen as inert gas at various heating rates to ramp the temperature from 25 degrees C to 900 degrees C. The derivative thermogravimetric (DTG) results show that thermal decomposition of EFB, PMF and PKS exhibit one, two and three distinct evolution profiles, respectively. Apparently, the thermal profiles of the coal/oil palm biomass blends appear to correlate with the percentage of biomass added in the blends, thus, suggesting lack of interaction between the coal and palm biomass. First-order reaction model were used to determine the kinetics parameters for the pyrolysis of coal, palm biomass and their respective blends.
Catalytic steam gasification of palm kernel shell is investigated to optimize operating parameters for hydrogen and syngas production using TGA-MS setup. RSM is used for experimental design and evaluating the effect of temperature, particle size, CaO/biomass ratio, and coal bottom ash wt% on hydrogen and syngas. Hydrogen production appears highly sensitive to all factors, especially temperature and coal bottom ash wt%. In case of syngas, the order of parametric influence is: CaO/biomass>coal bottom ash wt%>temperature>particle size. The significant catalytic effect of coal bottom ash is due to the presence of Fe2O3, MgO, Al2O3, and CaO. A temperature of 692°C, coal bottom ash wt% of 0.07, CaO/biomass of 1.42, and particle size of 0.75mm are the optimum conditions for augmented yield of hydrogen and syngas. The production of hydrogen and syngas is 1.5% higher in the pilot scale gasifier as compared to TGA-MS setup.
Co-pyrolysis of biomass with abundantly available materials could be an economical method for production of bio-fuels. However, elimination of oxygenated compounds poses a considerable challenge. Catalytic co-pyrolysis is another potential technique for upgrading bio-oils for application as liquid fuels in standard engines. This technique promotes the production of high-quality bio-oil through acid catalyzed reduction of oxygenated compounds and mutagenic polyaromatic hydrocarbons. This work aims to review and summarize research progress on co-pyrolysis and catalytic co-pyrolysis, as well as their benefits on enhancement of bio-oils derived from biomass. This review focuses on the potential of plastic wastes and coal materials as co-feed in co-pyrolysis to produce valuable liquid fuel. This paper also proposes future directions for using this technique to obtain high yields of bio-oils.
Waste materials from the agricultural and industries can cause problems to human health and the environment when improperly disposed and managed. Due to rapid development in construction, the demand of cement in concrete has increased dramatically. Therefore, wastes such as rice husk, eggshell, glass, fly ash and many more can be used in construction industry to minimize the environmental impact and producing new material on construction industry. Many studies have been conducted as an effort to find replacement materials to substitute cement in concrete.
Waste materials from the agricultural and industries can cause problems to human health and the environment when improperly disposed and managed. Due to rapid development in construction, the demand of cement in concrete has increased dramatically. Therefore, wastes such as rice husk, eggshell, glass, fly ash and many more can be used in construction industry to minimize the environmental impact and producing new material on construction industry. Many studies have been conducted as an effort to find replacement materials to substitute cement in concrete.
High performance sorbents for flue gas desulfurization can be synthesized by hydration of coal fly ash, calcium sulfate, and calcium oxide. In general, higher desulfurization activity correlates with higher sorbent surface area. Consequently, a major aim in sorbent synthesis is to maximize the sorbent surface area by optimizing the hydration conditions. This work presents an integrated modeling and optimization approach to sorbent synthesis based on statistical experimental design and two artificial intelligence techniques: neural network and genetic algorithm. In the first step of the approach, the main and interactive effects of three hydration variables on sorbent surface area were evaluated using a full factorial design. The hydration variables of interest to this study were hydration time, amount of coal fly ash, and amount of calcium sulfate and the levels investigated were 4-32 h, 5-15 g, and 0-12 g, respectively. In the second step, a neural network was used to model the relationship between the three hydration variables and the sorbent surface area. A genetic algorithm was used in the last step to optimize the input space of the resulting neural network model. According to this integrated modeling and optimization approach, an optimum sorbent surface area of 62.2m(2)g(-1) could be obtained by mixing 13.1g of coal fly ash and 5.5 g of calcium sulfate in a hydration process containing 100ml of water and 5 g of calcium oxide for a fixed hydration time of 10 h.
A novel and economic sequential process consisting of precipitation, adsorption, and oxidation was developed to remediate actual rare-earth (RE) wastewater containing various toxic pollutants, including radioactive species. In the precipitation step, porous air stones (PAS) containing waste oyster shell (WOS), PASWOS, was prepared and used to precipitate most heavy metals with >97% removal efficiencies. The SEM-EDS analysis revealed that PAS plays a key role in preventing the surface coating of precipitants on the surface of WOS and in releasing the dissolved species of WOS successively. For the adsorption step, a polyurethane (PU) impregnated by coal mine drainage sludge (CMDS), PUCMDS, was synthesized and applied to deplete fluoride (F), arsenic (As), uranium (U), and thorium (Th) that remained after precipitation. The continuous-mode sequential process using PAS(WOS), PU(CMDS), and ozone (O3) had 99.9-100% removal efficiencies of heavy metals, 99.3-99.9% of F and As, 95.8-99.4% of U and Th, and 92.4% of COD(Cr) for 100 days. The sequential process can treat RE wastewater economically and effectively without stirred-tank reactors, pH controller, continuous injection of chemicals, and significant sludge generation, as well as the quality of the outlet met the EPA recommended limits.
This study aimed to determine the distribution and potential health risks of polycyclic aromatic hydrocarbons (PAHs) in PM2.5 collected in Kuala Lumpur during different monsoon seasons. The potential sources of PM2.5 were investigated using 16 priority PAHs with additional of biomass tracers namely levoglucosan (LV), mannosan (MN) and galactosan (GL). This study also investigated the cytotoxic potential of the extracted PAHs towards V79-4 cells. A high-volume air sampler (HVS) was used to collect PM2.5 samples for 24 h. PAHs were extracted using dichloromethane (DCM) while biomass tracers were extracted by a mixture of DCM/methanol (3:1) before analysis with gas chromatography-mass spectrometry (GC-MS). The cytotoxicity of the PAHs extract was determined by assessing the cell viability through the reduction of tetrazolium salts (MTT). The results showed that the total mean ± SD concentrations of PAHs during the southwest (SW) and northeast (NE) monsoons were 2.51 ± 0.93 ng m-3 and 1.37 ± 0.09 ng m-3, respectively. Positive matrix factorization (PMF) using PAH and biomass tracer concentrations suggested four potential sources of PM2.5; gasoline emissions (29.1%), natural gas and coal burning (28.3%), biomass burning (22.3%), and diesel and heavy oil combustion (20.3%). Health risk assessment showed insignificant incremental lifetime cancer risk (ILCR) of 2.40E-07 for 70 years of exposure. MTT assay suggested that PAHs extracts collected during SW monsoon have cytotoxic effect towards V79-4 cell at the concentrations of 25 μg mL-1, 50 μg mL-1, 100 μg mL-1 whereas non-cytotoxic effect was observed on the PAHs sample collected during NE monsoon.
The thermochemical processes such as gasification and co-gasification of biomass and coal are promising route for producing hydrogen-rich syngas. However, the process is characterized with complex reactions that pose a tremendous challenge in terms of controlling the process variables. This challenge can be overcome using appropriate machine learning algorithm to model the nonlinear complex relationship between the predictors and the targeted response. Hence, this study aimed to employ various machine learning algorithms such as regression models, support vector machine regression (SVM), gaussian processing regression (GPR), and artificial neural networks (ANN) for modeling hydrogen-rich syngas production by gasification and co-gasification of biomass and coal. A total of 12 machine learning algorithms which comprises the regression models, SVM, GPR, and ANN were configured, trained using 124 datasets. The performances of the algorithms were evaluated using the coefficient of determination (R2), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). In all cases, the ANN algorithms offer superior performances and displayed robust predictions of the hydrogen-rich syngas from the co-gasification processes. The R2 of both the Levenberg-Marquardt- and Bayesian Regularization-trained ANN obtained from the prediction of the hydrogen-rich syngas was found to be within 0.857-0.998 with low prediction errors. The sensitivity analysis to determine the effect of the process parameters on the model output revealed that all the parameters showed a varying level of influence. In most of the processes, the gasification temperature was found to have the most significant influence on the model output.
Abundance of fine particulate-bound 16 priority polycyclic aromatic hydrocarbons (PAHs) was investigated to ascertain its sources and potential carcinogenic health risks in Varanasi, India. The city represents a typical urban settlement of South Asia having particulate exposure manyfold higher than standard with reports of pollution induced mortalities and morbidities. Fine particulates (PM2.5) were monitored from October 2019 to May 2020, with 32% of monitoring days accounting ≥100 μgm-3 of PM2.5 concentration, frequently from November to January (99% of monitoring days). The concentration of 16 priority PAHs varied from 24.1 to 44.6 ngm-3 (mean: 33.1 ± 3.2 ngm-3) without much seasonal deviations. Both low (LMW, 56%) and high molecular weight (HMW, 44%) PAHs were abundant, with Fluoranthene (3.9 ± 0.4ngm-3) and Fluorene (3.5 ± 0.3ngm-3) emerged as most dominating PAHs. Concentration of Benzo(a)pyrene (B(a)P, 0.5 ± 0.1ngm-3) was lower than the national standard as it contributed 13% of total PAHs mass. Diagnostic ratios of PAH isomers indicate predominance of pyrogenic sources including emissions from biomass burning, and both from diesel and petrol-driven vehicles. Source apportionment using receptor model revealed similar observation of major PAHs contribution from biomass burning and fuel combustion (54% of source contribution) followed by coal combustion for residential heating and cooking purposes (44%). Potential toxicity of B[a]P equivalence ranged from 0.003 to 1.365 with cumulative toxicity of 2.13ngm-3. Among the PAH species, dibenzo[h]anthracene contributed maximum toxicity followed by B[a]P, together accounting 86% of PAH induced carcinogenicity. Incremental risk of developing cancer through lifetime exposure (ILCR) of PAHs was higher in children (3.3 × 10-4) with 56% contribution from LMW PAHs, primarily through ingestion and dermal contact. Adults in contrast, were more exposed to inhale airborne PAHs with cumulative ILCR of 2.2 × 10-4. However, ILCR to PM2.5 exposure is probably underestimated considering unaccounted metal abundance thus, require source-specific control measures.
The survey data on potential aquifer was collected at two sites located in Banggi Island (i.e. Laksian Primary School [LPS] and Padang Primary School [PPS]), Malaysia on 25 and 26 April 2013. Both locations are geologically surrounded by various types of lithologies, namely, sandstone, mudstone, siltstone, shale, chert, conglomerate, lignite, tuff, limestone, terrace sand, gravel and coral. The resistivity data consisted of six-line pole-dipole short arrays and were recorded in-situ using SAS 4000 ABEM Lund Imaging System, together with a relay switching unit (Electrode Selector ES 464), six multiconductor cables, steel rod electrodes and jumpers. The data, namely electrode spacing, depth of investigation, subsurface resistivity, type of material and horizontal data coverage were used to assess the characteristics of the potential aquifer. The recorded data were then processed using RES2DINV software to obtain 2-D inversion model of the subsurface. The data were also equipped with six models of inverse resistivity section for both areas. The data obtained can be used by the government and stakeholders for groundwater exploration and extraction in order to provide water supplies for local communities, especially since access to these resources from the surrounding water treatment plants on the island is limited.
Coal combustion by-products (CCPs) (i.e. fly (FA) and bottom (BA) ashes) generated by power plants contain heavy metals. This research presents leaching properties of coal ashes (FA and BA) collected from Jimah coal-fired power station, Port Dickson, Negeri Sembilan using USEPA standard methods namely toxicity characteristic leaching procedure (TCLP), and synthetic precipitation leaching procedure (SPLP). Heavy metals like lead (Pb), zinc (Zn), copper (Cu) and arsenic (As) were quantified using atomic absorption spectrometer (AAS). The leached of heavy metals fluxes were Cu < Zn < Pb < As. As leached the most whilst indicating of possible contamination from As. Overall, the ranges of leached concentration were adhered to permissible limits of hazardous waste criteria for metal (Pb and As) and industrial effluent (Zn and Cu). The presented data has potential reuse as reference for the coal ash concrete mixed design application in construction industries.
Energy has a significant influence on Malaysia's industry. It is used in electricity generation, refineries, gas processing plants and end-user applications such as transportation, residential, agriculture and fishing. These burning fossil fuel activities produce greenhouse gases (GHG) emissions. This article presents the emissions data of fuel used in power plants in Malaysia during the year of 1990 until 2017. The fuel used in power plants is coal and coke, natural gas, diesel oil and residual fuel oil. The energy data used in power plants were gathered from the Malaysia Energy Information Hub, published by the Malaysian Energy Commission. The GHG emissions data were calculated using the emission factors method. The climate impact of different GHGs in terms of CO2-equivalent (CO2-e) was also calculated using global warming potentials. The article also presents population data in Malaysia during the year. A correlation between the fuels, GHG emission and the population is also investigated using statistical analysis. The data presented here may facilitate the Malaysian government to identify the source of the pollutants and undertake a climate change mitigation plan.