• Energy Research

Abstract To reveal the synergistic effect of hydrogen peroxide and ammonia on lignin, four kinds of ball-milled wood lignins, named as UN-L, HP-L, AFEX-L and H-AFEX-L respectively, were isolated from corn stover of untreated, hydrogen peroxide pretreatment alone, ammonia fiber expansion pretreatment alone and combined hydrogen peroxide and ammonia fiber expansion pretreatment. Modern analytical techniques including elemental analysis, gel permeation chromatography (GPC), Fourier transform infrared (FT-IR) spectroscopy and two-dimensional heteronuclear single-quantum coherence nuclear magnetic resonance (2D-HSQC NMR) spectroscopy were applied to analyze the characteristics of the obtained lignins. The results showed that oxidation, ammonolysis were main chemical reaction during H-AFEX pretreatment. The action site of oxidation was S unit, while that of ammonolysis were ferulate and p-coumarate ester bonds. The synergistic effect of hydrogen peroxide and ammonia strengthened ammonolysis effect whereas weakened oxidation effect. Ammonia selectively degraded the ester bond, while hydrogen peroxide selectively degraded the resinol structure. The synergistic effect of hydrogen peroxide and ammonia could not only effectively degrade lignin, but also greatly reduce its PI to obtain homogeneous lignin fragments.

Abstract Anaerobic co-digestion of corn stover (CS) and goose manure (GM) was carried out in the present study at four composition levels. Corn stover was pretreated to enhance its lignocellulosic digestibility. The NaOH pretreatment effect on the chemical composition of the corn stover was also determined and the methane production from all the composition levels was found significant (P

Modern distribution mechanisms within the smart grid paradigm are considered both reliable in nature and interconnected in topology. In this paper, a multiple-criteria-based sustainable planning (MCSP) approach is presented that serves as a future planning tool for interconnected distribution mechanisms and aims to find a feasible solution among conflicting criteria of various genres. The proposed methodology is based on three stages. In the stage 1, a weighted voltage stability index (VSI_W) and loss minimization condition (LMC) based approach aims at optimal asset optimization (sitting and sizing). In this stage, an evaluation of alternatives (solutions) is carried out across four dimensions (technical, economic, environmental, and social) of performance metrics. The assets considered in the evaluations include distributed generation (DG), renewable DGs, i.e., photovoltaic (PV), wind, and distributed static compensator (D-STATCOM) units. In the stage 2, various multicriteria decision-making (MCDM) methodologies are applied to ascertain the best trade-off among the available solutions in terms of techno-cost (economic) (TCPE), environment-o-social (ESPE), and techno-economic-environmental-socio (TEES) performance evaluations (OPE). In the stage 3, the alternatives are evaluated across multiple load growth horizons of 5 years each. The proposed MCSP approach is evaluated across a mesh-configured 33-bus active distribution network (ADN) and an actual NUST (which is a university in Islamabad, Pakistan) microgrid (MG), with various variants of load growth. The numerical findings of the proposed MCSP approach are compared with reported works the literature supports its validity and can serve as an important planning tool for interconnected distribution mechanisms for researchers and planning engineers.

The present study emphasized the co-digestion of the thermal-H2O2 pretreated wheat straw (WS) and chicken manure (CM) with the waste activated sludge at four levels of C/N (35:1, 30:1, 25:1 and 20:1). All C/N compositions were found significant (P<0.05) to enhance methane generation and process stability during the anaerobic co-digestion of WS and CM. The experimental results revealed that the composition having C/N value of 20:1 was proved as optimum treatment with the methane enhancing capability of 85.11%, CODs removal efficiency of 48.55% and 66.83% VS removal as compared with the untreated WS. The other compositions having C/N of 25:1, 30:1 and 35:1 provided 75.85%, 63.04% and 59.96% enhanced methane respectively as compared with the control. Pretreatment of the WS reduced its C/N value up to 65%. Moreover, to optimize the most suitable C/N composition, the process stability of the co-digestion of WS and CM was deeply monitored.

The present study focused on carbon to nitrogen ratio (C/N) and organic loading rate (OLR) optimization of goose manure (GM) and wheat straw (WS). Dealing the anaerobic digestion of poultry manure on industrial scale; the question of optimum C/N (mixing ratio) and OLR (daily feeding concentration) have significant importance still lack in literature. Therefore, Batch and CSTR co-digestion experiments of the GM and WS were carried out at mesophilic condition. The alkali (NaOH) solubilization pretreatment for the WS had greatly enhanced its anaerobic digestibility. The highest methane production was evaluated between the C/N of 20-30 during Batch experimentation while for CSTRs; the second applied OLR of (3g.VS/L.d) was proved as the optimum with maximum methane production capability of 254.65ml/g.VS for reactor B at C/N of 25. The C/N and OLR regression optimization models were developed for their commercial scale usefulness.

In the present study, thermo-chemical pre-treatment was adopted to evaluate methane production potential from corn stover by co-digesting it with anaerobic activated sludge. Three chemicals H2O2, Ca(OH)2 and NaOH were selected with two levels of concentration. All thermo-chemical pre-treatments were found significant (P<0.05) to enhance lignocellulosic digestibility and methane production. The results indicated that the methane yield by H2O2-1, H2O2-2, and NaOH-2 treated corn stover were 293.52, 310.50 and 279.42ml/g.VS which were 57.18%, 66.27% and 49.63% higher than the untreated corn stover respectively. In the previous studies pre-treatment time was reported in days but our method had reduced it to about one hour. H2O2-2 and NaOH-2 treatments remained prominent to increase lignocellulosic degradation vigorously up to 45% and 42% respectively. Process biochemistry during the anaerobic digestion process was taken into consideration to optimize the most feasible thermo-chemical pre-treatment for corn stover.

Abstract Lignocelluloses’ pretreatment is targeted for the improvement of hydrolysis of their carbohydrates, i.e., cellulose and hemicelluloses. Modification of the hardheaded structure of lignocelluloses is a fundamental stair in biofuels and biochemicals production. The high crystalline configurations of cellulose embed with hemicelluloses and lignin, give rise to recalcitrance structure. Second-generation biofuel production processes, using lignocellulosic biomass as a feedstock, is based on a three-stage process, including pretreatment, enzymatic hydrolysis, and fermentation. The pretreatment stage is the most critical, influencing, costly stage. The perfect pretreatment process is designated to provide minimum cellulosic crystallinity with remarkable low lignin content as well as inhibitory compounds through a sustainable economical process. In the present review, advances in lignocellulosic pretreatment technologies for biofuels production are reviewed and critically discussed. The article further discusses the pros and cons of the various pretreatment methodologies as well as addresses the role and impact of different process parameters associated with the pretreatment process.

To study the optimum process conditions for pretreatments and anaerobic codigestion of oil refinery wastewater (ORWW) with chicken manure, L9 (34) Taguchi’s orthogonal array was applied. The biogas production (BGP), biomethane content (BMP), and chemical oxygen demand solubilization (CODS) in stabilization rate were evaluated as the process outputs. The optimum conditions were obtained by using Design Expert software (Version 7.0.0). The results indicated that the optimum conditions could be achieved with 44% ORWW, 36°C temperature, 30 min sonication, and 6% TS in the digester. The optimum BGP, BMP, and CODS removal rates by using the optimum conditions were 294.76 mL/gVS, 151.95 mL/gVS, and 70.22%, respectively, as concluded by the experimental results. In addition, the artificial neural network (ANN) technique was implemented to develop an ANN model for predicting BGP yield and BMP content. The Levenberg-Marquardt algorithm was utilized to train ANN, and the architecture of 9-19-2 for the ANN model was obtained.