Potential of biomass for bioenergy in Pakistan based on present case and future perspectives

Authors have no conflict of interest and would like to acknowledge the National University of Sciences&Technology (NUST), Pakistan.Peer reviewedPostprin

HPLC-PDA-ESI-MSn profiling of polyphenolics in different parts of Capparis spinosa and Capparis decidua as function of harvesting seasons

HPLC-PDA-ESI-MSn analysis of different parts such as stem bark, shoot, flower, fruit and root of Capparis spinosa (C. spinosa) and Capparis decidua (C. decidua), collected in rainy and dry seasons from the Cholistan desert of Pakistan, depicted the occurrence of a wide array of phenolics with quercetin, apigenin and kaempferol derivatives along with dicaffeoylquinic acid, caffeoylquinic acid and feruloylquinic acid as the main compounds. Kaempferol-3-glucoside (28.02-167.21 μg g-1dw) was found to be the principal component in all tested parts of both species while dicaffeoylquinic acid was detected only in the flowers and roots. The roots exhibited maximum contents of flavonoids and hydroxycinnamic acid derivatives. The harvesting period significantly (p<0.05) affected the concentration of phenolics wherein the samples collected in rainy season offered greater levels of phenolics than their counterpart. The roots and fruits of both species were found to be rich sources of phenolics. The findings of this research suggest the harvesting of the selected wild Capparis species in rainy season to maximize their antioxidant and nutraceutical benefits

An overview of groundwater monitoring through point-to satellite-based techniques

Groundwater supplies approximately half of the total global domestic water demand. It also complements the seasonal and annual variabilities of surface water. Monitoring of groundwater fluctuations is mandatory to envisage the composition of terrestrial water storage. This research provides an overview of traditional techniques and detailed discussion on the modern tools and methods to monitor groundwater fluctuations along with advanced applications. The groundwater monitoring can broadly be classified into three groups. The first one is characterized by the point measurement to measure the groundwater levels using classical instruments and electronic and physical investigation techniques. The second category involves the extensive use of satellite data to ensure robust and cost-effective real-time monitoring to assess the groundwater storage variations. Many satellite data are in use to find groundwater indirectly. However, GRACE satellite data supported with other satellite products, computational tools, GIS techniques, and hydro-climate models have proven the most effective for groundwater resources management. The third category is groundwater numerical modeling, which is a very useful tool to evaluate and project groundwater resources in future. Groundwater numerical modeling also depends upon the point-based groundwater monitoring, so more research to improve point-based detection methods using latest technologies is required, as these still play the baseline role. GRACE and numerical groundwater modeling are suggested to be used conjunctively to assess the groundwater resources more efficiently

Phototrophic Bioremediation of Municipal Tertiary Wastewater Coupling with Lipid Biosynthesis Using <i>Scenedesmus dimorphus</i>: Effect of Nitrogen to Phosphorous Ratio with/without CO₂ Supplementation

Scenedesmus dimorphus was utilized for the tertiary treatment of municipal wastewater in an effort to remove nutrients from secondary treated wastewater. In addition to the concurrent generation of biomass containing lipids for biofuel production. The effect of nitrogen to phosphorous (N:P) ratios (1:1 to 8:1) in culture media without carbon dioxide (CO2) supplementation (air supply alone, Case 1) and with CO2 supplementation (2% CO2 in air, Case 2) was investigated through a series of systematic parametric batch experiments. Case 2 produces greater biomass at all N:P ratios than Case 1. In Case 1, the highest biomass output for a N:P ratio of 8:1 is 567 mg/L at pH 8.4. In Case 2, however, the maximum biomass yield is 733 mg/L when the N:P ratio is 2:1 and the pH is 7.23. Scenedesmus dimorphus is capable of absorbing nitrogen and phosphorous from wastewater in a CO2 environment and at the optimal N:P ratio. In Case 1, total nitrogen removal ranges from 28% to 100% and in Case 2, total nitrogen removal ranges from 60% to 100%, depending on the N:P ratio. For an initial concentration of 13 mg/L, the total phosphorous removal ranges from 37% to 57%, depending on the N:P ratio in both cases. Case 2 yields a maximum lipid content of 29% of the biomass dry weight when the N:P ratio is 1:1. These results suggest the viability of removing nutrients from secondary treated wastewater utilizing microalgae Scenedesmus dimorphus and lipid biosynthesis in the generated biomass

Magnesium Aminoclay-Fe3O4 (MgAC-Fe3O4) Hybrid Composites for Harvesting of Mixed Microalgae

In this paper, we describe the synthesis of magnesium aminoclay-iron oxide (MgAC-Fe3O4) hybrid composites for microalgae-harvesting application. MgAC-templated Fe3O4 nanoparticles (NPs) were synthesized in different ratios of MgAC and Fe3O4 NPs. The uniform distribution of Fe3O4 NPs in the MgAC matrix was confirmed by transmission electron microscopy (TEM). According to obtained X-ray diffraction (XRD) patterns, increased MgAC loading leads to decreased intensity of the composites&rsquo; (311) plane of Fe3O4 NPs. For harvesting of Chlorella sp. KR-1, Scenedesmus obliquus and mixed microalgae (Chlorella sp. KR-1/ Scenedesmus obliquus), the optimal pH was 4.0. At higher pHs, the microalgae-harvesting efficiencies fell. Sample #1, which had the highest MgAC concentration, showed the most stability: the harvesting efficiencies for Chlorella sp. KR-1, Scenedesmus obliquus, and mixed microalgae were reduced only to ~50% at pH = 10.0. The electrostatic interaction between MgAC and the Fe3O4 NPs in the hybrid samples by microalgae, as confirmed by zeta potential measurements, were attributed to the harvesting mechanisms. Moreover, the zeta potentials of the MgAC-Fe3O4 hybrid composites were reduced as pH was increased, thus diminishing the microalgae-harvesting efficiencies

Bioremediation of textile wastewater and successive biodiesel production using microalgae

Microalgal biodiesel has emerged as an environment friendly alternative to the existing fossil fuels. The commercial production of this biodiesel is still challenging due to several technical and economic issues, which span from mass cultivation of microalgae to the biodiesel production. Mass cultivation is the most critical step in terms of water and nutrient requirement. Industrial wastewater such as textile wastewater (TWW) is a cheap source for water, which additionally contains necessary nutrients (phosphate, nitrates, micronutrients etc.) and organic dyes (potential carbon source) for algae cultivation. The application of microalgae for biodiesel production employing single objective strategy is not sustainable. Microalgae can be effectively employed to bioremediate TWW (dyes and nutrients removal) and to produce biodiesel from grown microalgae. This process integration (bioremediation-biodiesel production) can potentially improve biodiesel production and wastewater treatment. However, this process coupling needs to be thoroughly investigated to identify and optimize critical process factors (algal species, cultivation and harvesting methods, bioremediation mechanism etc.). This study has reviewed the status of TWW as potential source of water and nutrients, role of different algal species in the bioremediation of TWW, different cultivation systems, harvesting and biodiesel production methods. This review also suggests future research and development challenges for coupled textile wastewater treatment and microalgal biodiesel production.</p

Recent progress in microalgae-derived biochar for the treatment of textile industry wastewater

Textile industry utilize a massive amount of dyes for coloring. The dye-containing effluent is released into wastewater along with heavy metals that are part of dye structure. The treatment of textile industry wastewater using conventional techniques (coagulation, membrane technique, electrolysis ion exchange, etc.) is uneco-nomical and less efficient (for a low concentration of pollutants). Moreover, most of these techniques produce toxic sludge, making them less environmentally friendly. Algae base industry is growing for food, cosmetics and energy needs. Algae biomass in unique compared to lignocellulosic biomass due to presence of various functional group on its surface and presence of various cations. These two characteristics are unique for biochar as a tool for environmental decontamination. Algae biomass contain functional groups and cations that can be effective for removal of organic contaminants (dyes) and heavy metals. Algae can be micro and macro and both have entirely different biomass composition which will lead to a synthesis of different biochar even under same synthesis process. This study reviews the recent progress in the development of an economically viable and eco-friendly approach for textile industry wastewater using algae biomass-derived absorbents. The strategy employed microalgal biochar to remove organic pollutants (dyes) and heavy metals from textile effluents by biosorption. This article discusses different methods for preparing algal biochar (pyrolysis, hydrothermal carbonization and torrefaction), and the adsorption capacity of biochar for dyes and heavy metals. Work on hydrothermal carbonization and torrefaction of microalgal biomass for biochar is limited. Variation in structural and functional groups changes on biochar compared to original microalgal biomass are profound in contract with lignocellulosic biomass. Existing Challenges, future goals, and the development of these technologies at the pilot level are also discussed.Web of Science306art. no. 13556

Pyrolysis of high-ash sewage sludge: Thermo-kinetic study using TGA and artificial neural networks

Pyrolysis of high-ash sewage sludge (HASS) is a considered as an effective method and a promising way for energy production from solid waste of wastewater treatment facilities. The main purpose of this work is to build knowledge on pyrolysis mechanisms, kinetics, thermos-gravimetric analysis of high-ash (44.6%) sewage sludge using model-free methods & results validation with artificial neural network (ANN). TG-DTG curves at 5,10 and 20 °C/min showed the pyrolysis zone was divided into three zone. In kinetics, E values of models ranges are; Friedman (10.6–306.2 kJ/mol), FWO (45.6–231.7 kJ/mol), KAS (41.4–232.1 kJ/mol) and Popescu (44.1–241.1 kJ/mol) respectively. ΔH and ΔG values predicted by OFW, KAS and Popescu method are in good agreement and ranged from (41–236 kJ/mol) and 53–304 kJ/mol, respectively. Negative value of ΔS showed the non-spontaneity of the process. An artificial neural network (ANN) model of 2 * 5 * 1 architecture was employed to predict the thermal decomposition of high-ash sewage sludge, showed a good agreement between the experimental values and predicted values (R2 ⩾ 0.999) are much closer to 1. Overall, the study reflected the significance of ANN model that could be used as an effective fit model to the thermogravimetric experimental data

Investigation of combustion performance of tannery sewage sludge using thermokinetic analysis and prediction by artificial neural network

The disposal and the management of sewage sludge from tanneries is a challenging issue for the leather industries because of their adverse effect on the environment. In this study the detailed characterization and assessment using kinetic and thermodynamic parameters of the tannery sewage sludge in combustion environment was employed. Isoconversional model-free methods like Ozawa-Flynn-Wall (OFW), Friedman and Kissinger-Akahira-Sunose (KAS) were employed to investigate the kinetics and the thermodynamic parameters in the air environment. Activation energies (Ea) for the Friedman, KAS and OFW were reported. The DTG curves at the heating rate of 5, 10, 20 and 40 °C/min show the diversified conversions in three major stages. The Ea values for the model ranges are Friedman (148.96 kJ/mol-395.23 kJ/mol), KAS (169.65 kJ/mol-383.75 kJ/mol) and OFW (176.44 kJ/mol-377.85 kJ/mol). The average Ea for the Friedman is 226.04 kJ/mol while for KAS and OFW the average Ea is 230.71 kJ/mol and 230.11 kJ/mol. Moreover, the values of ΔH, ΔG, and ΔS were analysed. Furthermore, the frequency distribution by applying the DAEM model is investigated, and there are six pseudo-components involved in the frequency distribution for combustion. For the thermal degradation prediction of the sewage sludge from the tannery, an artificial neural network (ANN) of the MLP-3-7-1 model was used. This model shows that there is good agreement between the experimental and the predicted values. Overall, this study highlights the importance of the ANN for the prediction of combustion behaviour of biomass with more accuracy