Bio: Najib Al-mahbashi is an academic researcher. The author has contributed to research in topics: Adsorption & Fourier transform infrared spectroscopy. The author has an hindex of 3, co-authored 5 publications receiving 32 citations.
TL;DR: In this paper , the effect of varying bed depth and flow rate over time on the removal efficiency of color from batik industrial effluent (BIE) was analyzed, and the results of FTIR showed that some functional groups such as CO and OH were hosted on the surface of the biochar.
Abstract: Batik industrial effluent wastewater (BIE) contains toxic dyes that, if directly channeled into receiving water bodies without proper treatment, could pollute the aquatic ecosystem and, detrimentally, affect the health of people. This study is aimed at assessing the adsorptive efficacy of a novel low-cost sewage-sludge-based biochar (SSB), in removing color from batik industrial effluent (BIE). Sewage-sludge-based biochar (SSB) was synthesized through two stages, the first is raw-material gathering and preparation. The second stage is carbonization, in a muffle furnace, at 700 °C for 60 min. To investigate the changes introduced by the preparation process, the raw sewage sludge (RS) and SSB were characterized by the Brunauer–Emmett–Teller (BET) method, Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy. The surface area of biochar was found to be 117.7 m2/g. The results of FTIR showed that some functional groups, such as CO and OH, were hosted on the surface of the biochar. Continuous fixed-bed column studies were conducted, by using SSB as an adsorbent. A glass column with a diameter of 20 mm was packed with SSB, to depths of 5 cm, 8 cm, and 12 cm. The volumes of BIE passing through the column were 384 mL/d, 864 mL/d, and 1680 mL/d, at a flow rate of 16 mL/h, 36 mL/h, and 70 mL/h, respectively. The initial color concentration in the batik sample was 234 Pt-Co, and the pH was kept in the range of 3–5. The effect of varying bed depth and flow rate over time on the removal efficiency of color was analyzed. It was observed that the breakthrough time differed according to the depth of the bed and changes in the flow rates. The longest time, where breakthrough and exhausting points occurred, was recorded at the highest bed and slowest flowrate. However, the increase in flow rate and decrease in bed depth made the breakthrough curves steeper. The maximum bed capacity of 42.30 mg/g was achieved at a 16 mL/h flowrate and 12 cm bed height. Thomas and Bohart–Adams mathematical models were applied, to analyze the adsorption data and the interaction between the adsorption variables. For both models, the correlation coefficient (R2) was more than 0.9, which signifies that the experimental data are well fitted. Furthermore, the adsorption behavior is best explained by the Thomas model, as it covers the whole range of breakthrough curves.
TL;DR: In this article , the effectiveness of activated carbon in the removal of copper and cadmium from aqueous solutions in column study was evaluated. And the authors demonstrated that using sewage sludge-based activated carbon to remove heavy metals is an alternative, more cost-effective option to reach the objectives of sustainable development.
Abstract: Among the water-polluting substances, heavy metals stand out due to their carcinogenic and toxic effects on the creatures and environment. This study aimed to scrutinize the effectiveness of sewage sludge-based activated carbon in the removal of copper and cadmium from aqueous solutions in column study. Detection of breakthrough curves and related parameters was conducted by varying bed depths (3, 6, and 9 cm). The solution with an initial metal concentration (IMC) of 100 ppm was pumped to the column at a flow rate of 2 mL/min. In the process of copper removal, the breakthrough points for depths 3 cm, 6 cm, and 9 cm were achieved at 10 min, 15 min, and 60 min, respectively, whereas breakthrough points of similar depths in cadmium removal process were achieved at 5 min, 10 min, and 30 min, respectively. Adsorption kinetics were analyzed using the Adams–Bohart, Yoon–Nelson, and Thomas kinetics models. The Adams–Bohart model described only the initial part of breakthrough curves. The Thomas model represented the adsorption process with coefficients of determination (R2) ranging between 0.90–0.95 for cadmium removal and 0.89–0.96 for copper removal, while the coefficients of determination of Yoon–Nelson ranged between 0.89–0.94 for cadmium and 0.95–0.97 for copper. Yoon–Nelson was fitted well with copper removal data, while removal of cadmium data was best described by the Thomas model. This study demonstrated that using sewage sludge-based activated carbon to remove heavy metals is an alternative, more cost-effective option to reach the objectives of sustainable development.
TL;DR: In this paper , DIAION™ CRB05 is used as an adsorbent for removing boron from aqueous solutions, and the results of the study demonstrate the effectiveness of this material and provide insight into optimal conditions for the adsorption process.
Abstract: A significant issue for the ecosystem is the presence of boron in water resources, particularly in produced water. Batch and dynamic experiments were used in this research to extract boron in the form of boric acid from aqueous solutions using boron selective resins, DIAION CRB05. DIAION™ CRB05 is an adsorbent that is effective in extracting boron from aqueous solutions due to its high binding capacity and selectivity for boron ions, and it is also regenerable, making it cost-effective and sustainable. Field Emission Scanning Electron Microscopy (FESEM), X-ray diffraction (XRD), and FTIR analysis for DIAION CRB05 characterization. To increase the adsorption capacity and find the ideal values for predictor variables such as pH, adsorbent dose, time, and boric acid concentration, the Box–Behnken response surface method (RSM) was applied. The dosage was reported to be 2000 mg/L at pH 2 and boron initial concentration of 1115 mg/L with 255 min for the highest removal anticipated from RSM. According to the outcomes of this research, the DIAION CRB05 material enhanced boron removal capability and has superior performance to several currently available adsorbents, which makes it suitable for use as an adsorbent for removing boric acid from aqueous solutions. The outcomes of isotherm and kinetic experiments were fitted using linear methods. The Temkin isotherm and the pseudo-first-order model were found to have good fits after comparison with R2 of 0.998, and 0.997, respectively. The results of the study demonstrate the effectiveness of DIAION™ CRB05 in removing boron from aqueous solutions and provide insight into the optimal conditions for the adsorption process. Thus, the DIAION CRB05 resin was chosen as the ideal choice for recovering boron from an aqueous solution because of its higher sorption capacity and percentage of boron absorbed.
TL;DR: In this article , the authors examined the trends in precipitation products in the Kelani river basin using Artificial Neural Networks (ANNs), precipitation estimation using remotely sensed information using artificial neural networks, PERSIANN-cloud classification system (CCS), and ground observed rain gauge daily rainfall data at nine locations for the analysis.
Abstract: Satellite-based precipitation products, (SbPPs) have piqued the interest of a number of researchers as a reliable replacement for observed rainfall data which often have limited time spans and missing days. The SbPPs possess certain uncertainties, thus, they cannot be directly used without comparing against observed rainfall data prior to use. The Kelani river basin is Sri Lanka’s fourth longest river and the main source of water for almost 5 million people. Therefore, this research study aims to identify the potential of using SbPPs as a different method to measure rain besides using a rain gauge. Furthermore, the aim of the work is to examine the trends in precipitation products in the Kelani river basin. Three SbPPs, precipitation estimation using remotely sensed information using artificial neural networks (PERSIANN), PERSIANN-cloud classification system (CCS), and PERSIANN-climate data record (CDR) and ground observed rain gauge daily rainfall data at nine locations were used for the analysis. Four continuous evaluation indices, namely, root mean square error (RMSE), (percent bias) PBias, correlation coefficient (CC), and Nash‒Sutcliffe efficiency (NSE) were used to determine the accuracy by comparing against observed rainfall data. Four categorical indices including probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and proportional constant (PC) were used to evaluate the rainfall detection capability of SbPPs. Mann‒Kendall test and Sen’s slope estimator were used to identifying whether a trend was present while the magnitudes of these were calculated by Sen’s slope. PERSIANN-CDR performed well by showing better performance in both POD and CSI. When compared to observed rainfall data, the PERSIANN product had the lowest RMSE value, while all products indicated underestimations. The CC and NSE of all three products with observed rainfall data were also low. Mixed results were obtained for the trend analysis as well. The overall results showed that all three products are not a better choice for the chosen study area.
TL;DR: In this article , the economic and environmental impacts of district cooling systems (DCS) that are integrated with renewable energy sources and thermal energy storage (TES) are examined, highlighting the benefits and challenges associated with these systems.
Abstract: This paper examines the economic and environmental impacts of district cooling systems (DCS) that are integrated with renewable energy sources and thermal energy storage (TES). Typically, a DCS offers a highly efficient and environmentally friendly alternative to traditional air conditioning systems, providing cool air to buildings and communities through a centralized system that uses chilled water. However, the integration of renewable energy and thermal energy storage into these systems can further increase their sustainability and efficiency, reducing their dependence on fossil fuels and improving their ability to handle fluctuations in demand. The goal of this paper is to provide a comprehensive review of the current state of the art of renewable energy-driven DCS with TES integrated and to highlight the benefits and challenges associated with these systems. Finally, the findings of this paper offer valuable insights into the potential for renewable energy-powered district cooling systems to contribute to a more sustainable and efficient built environment.
TL;DR: In this paper , a polypyrrole-polyethyleneimine (PPy-PEI) nano-adsorbent was successfully synthesized for the removal of methylene blue (MB) from an aqueous solution.
Abstract: In this work, a polypyrrole-polyethyleneimine (PPy-PEI) nano-adsorbent was successfully synthesized for the removal of methylene blue (MB) from an aqueous solution. Synthetic dyes are among the most prevalent environmental contaminants. A new conducting polymer-based adsorbent called (PPy-PEI) was successfully produced using ammonium persulfate as an oxidant. The PEI hyper-branched polymer with terminal amino groups was added to the PPy adsorbent to provide more effective chelating sites for dyes. An efficient dye removal from an aqueous solution was demonstrated using a batch equilibrium technique that included a polyethyleneimine nano-adsorbent (PPy-PEI). The best adsorption parameters were measured at a 0.35 g dosage of adsorbent at a pH of 6.2 and a contact period of 40 min at room temperature. The produced PPy-PEI nano-adsorbent has an average particle size of 25–60 nm and a BET surface area of 17 m2/g. The results revealed that PPy-PEI nano-composite was synthesized, and adsorption was accomplished in the minimum amount of time. The maximum monolayer power, qmax, for MB was calculated using the isothermal adsorption data, which matched the Langmuir isotherm model, and the kinetic adsorption data, which more closely fitted the Langmuir pseudo-second-order kinetic model. The Langmuir model was used to calculate the maximum monolayer capacity, or qmax, for MB, which was found to be 183.3 mg g−1. The as-prepared PPy-PEI nano-adsorbent totally removes the cationic dyes from the aqueous solution.
TL;DR: In this paper , the performance of the activated sludge bioreactor system (ASBS) for the treatment of pulp and paper industry wastewater (PPIW) was characterized.
Abstract: The pulp and paper industry has been recognized as one of the largest users of water worldwide. Water is used in nearly every step of the manufacturing process. It generates significant amounts of wastewater and leftover sludge, creating several problems for wastewater treatment, discharge, and sludge disposal. Adopting the most effective and economical treatment techniques before discharging wastewater is therefore crucial. Thus, this study aims to evaluate the performance of the activated sludge bioreactor system (ASBS) for the treatment of pulp and paper industry wastewater (PPIW). The PPIW was characterized. During the experiment, the domestic and PPIW wastewater were run at a fixed HRT of 1 day. Subsequently, the ASBS was evaluated by varying the HRT and OLR. The HRT was varied in the range of 3, 2, and 1 day. At a fixed HRT of 2 days, the maximum and minimum COD removal were 88.4 and 63.2%. Throughout the study, the ASBS demonstrated higher treatment efficiency in terms of COD removal. First order, Grau second order, and modified Stover Kincannon biokinetic models were applied for the study. The biokinetic investigation shows that the modified stover kinetic model was more appropriate for the description of the experimental data in terms of microbial growth parameters. Thus, the kinetic coefficients obtained in this study could be used for the bioreactor scale-up. The study has also proven that the biosorbent made from biomass waste can potentially help preserve non-renewable resources and promote zero-waste attainment and principles of a circular bioeconomy.
TL;DR: In this paper , a review was designed to highlight the several waste, plants, and other materials that have been utilized during petroleum sludge or petroleum contaminated site treatment for resource recovery and to ensure environmental safety.
Abstract: Activities in the petroleum industry unavoidably generates huge amount of petroleum sludge that contain hazardous constituents. Numerous treatment techniques are proven to reduce toxicity, sludge volume, and extract petroleum products. Their efficiency is determined by the sludge properties. These treatment technologies can lessen the hazardous elements in sludge and alleviate their negative environmental and human health impacts. However, only a few, can strike a compromise between meeting strict environmental regulations and consuming notable quantity of water, energy, and chemicals. Now, there are no waste-free and cost-effective technologies available for petroleum sludge treatment. Therefore, this review was designed to highlight the several waste, plants, and other materials that have been utilized during petroleum sludge or petroleum contaminated site treatment for resource recovery and to ensure environmental safety. The application of various additives to remediate petroleum sludge contaminated areas has been proven to be a practical and environmentally beneficial alternative. The review found that reusing remediated soils for bioremediation activity on soil contaminated with oil sludge was efficient. The review further revealed that phytoremediation by sowing plants in the soil can remarkably boost microorganism’s growth and TPH elimination rate. Also, in planted treatments using Zea mays L., Secale cereale L., Festuca arundinacea, Onobrychis viciifolia, Vertiver zizanioide, Cajanus cajan, Medicago sativa, Lolium perenne, Ttrifolium pratense etc. the most probable number were significantly higher than in unplanted treatments. It was also discovered that there is a commercial potential for the use of plants as sources of biosurfactant for use in accelerated TPHs degradation. Biosurfactant supplementation in the phytoremediation of metals and petroleum hydrocarbons co-contaminated soil was effective. The review suggests the use of composite materials for petroleum sludge treatment.
TL;DR: In this article , the authors investigated the effectiveness of extended aeration system (EAS) and rice straw activated carbon-extended aeration systems (RAC-EAS), in the treatment of pulp and paper biorefinery effluent (PPBE).
Abstract: This study investigated the effectiveness of extended aeration system (EAS) and rice straw activated carbon-extended aeration system (RAC-EAS) in the treatment of pulp and paper biorefinery effluent (PPBE). RAC-EAS focused on the efficient utilization of lignocellulosic biomass waste (rice straw) as a biosorbent in the treatment process. The experiment was designed by response surface methodology (RSM) and conducted using a bioreactor that operated at 1–3 days hydraulic retention times (HRT) with PPBE concentrations at 20, 60 and 100%. The bioreactor was fed with real PPBE having initial ammonia-N and total phosphorus (TP) concentrations that varied between 11.74 and 59.02 mg/L and 31–161 mg/L, respectively. Findings from the optimized approach by RSM indicated 84.51% and 91.71% ammonia-N and 77.62% and 84.64% total phosphorus reduction in concentration for EAS and RAC-EAS, respectively, with high nitrification rate observed in both bioreactors. Kinetic model optimization indicated that modified stover models was the best suited and were statistically significant (R2 ≥ 0.98) in the analysis of substrate removal rates for ammonia-N and total phosphorus. Maximum nutrients elimination was attained at 60% PPBE and 48 h HRT. Therefore, the model can be utilized in the design and optimization of EAS and RAC-EAS systems and consequently in the prediction of bioreactor behavior.
TL;DR: In this article , the effectiveness of a continuous flow bioreactor system (CFBS) in the treatment of agro-industrial effluent using hybrid waste sludge biochar (HWSB) was investigated.
Abstract: Agro-waste management processes are evolving through the development of novel experimental approaches to understand the mechanisms in reducing their pollution levels efficiently and economically from industrial effluents. Agro-industrial effluent (AIE) from biorefineries that contain high concentrations of COD and color are discharged into the ecosystem. Thus, the AIE from these biorefineries requires treatment prior to discharge. Therefore, the effectiveness of a continuous flow bioreactor system (CFBS) in the treatment of AIE using hybrid waste sludge biochar (HWSB) was investigated. The use of a bioreactor with hydraulic retention time (HRT) of 1–3 days and AIE concentrations of 10–50% was used in experiments based on a statistical design. AIE concentration and HRT were optimized using response surface methodology (RSM) as the process variables. The performance of CFBS was analyzed in terms of COD and color removal. Findings indicated 76.52% and 66.97% reduction in COD and color, respectively. During biokinetic studies, the modified Stover models were found to be perfectly suited for the observed measurements with R2 values 0.9741 attained for COD. Maximum contaminants elimination was attained at 30% AIE and 2-day HRT. Thus, this study proves that the HWSB made from biomass waste can potentially help preserve nonrenewable resources and promote zero-waste attainment and principles of circular economy.