Oxy-fuel co-combustion dynamics of phytoremediation biomass and textile dyeing sludge: Gas-to-ash pollution abatement

Estimated electric conductivities of thermal plasma for air-fuel combustion and oxy-fuel combustion with potassium or cesium seeding

A complete model for estimating the electric conductivity of combustion product gases, with added cesium (Cs) or potassium (K) vapor for ionization, is presented. Neutral carrier gases serve as the bulk fluid that carries the seed material, as well as the electrons generated by the partial thermal (equilibrium) ionization of the seed alkali metal. The model accounts for electron-neutral scattering, as well as electron-ion and electron-electron scattering. The model is tested through comparison with published data. The model is aimed at being utilized for the plasma within magnetohydrodynamic (MHD) channels, where direct power extraction from passing electrically conducting plasma gas enables electric power generation. The thermal ionization model is then used to estimate the electric conductivity of seeded combustion gases under complete combustion of three selected fuels, namely: hydrogen (H2), methane (CH4), and carbon (C). For each of these three fuels, two options for the oxidizer were applied, namely: air (21 % molecular oxygen, 79 % molecular nitrogen by mole), and pure oxygen (oxy-combustion). Two types of seeds (with 1 % mole fraction, based on the composition before ionization) were also applied for each of the six combinations of (fuel-oxidizer), leading to a total of 12 different MHD plasma cases. For each of these cases, the electric conductivity was computed for a range of temperatures from 2000 K to 3000 K. The smallest estimated electric conductivity was 0.35 S/m for oxy-hydrogen combustion at 2000 K, with potassium seeding. The largest estimated electric conductivity was 180.30 S/m for oxy-carbon combustion at 3000 K, with cesium seeding. At 2000 K, replacing potassium with cesium causes a gain in the electric conductivity by a multiplicative gain factor of about 3.6 regardless of the fuel and oxidizer. This gain factor declines to between 1.77 and 2.07 at 3000 K. Based on the findings of this research study, the four analyzed factors to increase the electric conductivity of MHD plasma can be listed by their significance (descending order) as (1) type of additive seed type (cesium is better than potassium), (2) temperature (the higher the better), (3) carbon-to-hydrogen ratio of the fuel (the higher the better), and finally (4) the oxidizer type (air is generally better than pure oxygen). The relative size of the two electric conductivity components (due to neutrals scattering and Coulomb scattering) at various plasma conditions are discussed, and a threshold of 10-5 (0.001 %) electrons mole fraction is suggested to safely neglect Coulomb scattering.

Biomass gasification, catalytic technologies and energy integration for production of circular methanol: New horizons for industry decarbonisation

The Intergovernmental Panel on Climate Change (IPCC) recognises the pivotal role of renewable energies in the future energy system and the achievement of the zero-emission target. The implementation of renewables should provide major opportunities and enable a more secure and decentralised energy supply system. Renewable fuels provide long-term solutions for the transport sector, particularly for applications where fuels with high energy density are required. In addition, it helps reducing the carbon footprint of these sectors in the long-term. Information on biomass characteristics feedstock is essential for scaling-up gasification from the laboratory to industrial-scale. This review deals with the transformation biogenic residues into a valuable bioenergy carrier like biomethanol as the liquid sunshine based on the combination of modified mature technologies such as gasification with other innovative solutions such as membranes and microchannel reactors. Tar abatement is a critical process in product gas upgrading since tars compromise downstream processes and equipment, for this, membrane technology for upgrading syngas quality is discussed in this paper. Microchannel reactor technology with the design of state-of-the-art multifunctional catalysts provides a path to develop decentralised biomethanol synthesis from biogenic residues. Finally, the development of a process chain for the production of (i) methanol as an intermediate energy carrier, (ii) electricity and (iii) heat for decentralised applications based on biomass feedstock flexible gasification, gas upgrading and methanol synthesis is analysed.

Multi-index control strategy from cement calcination denitration system: a model predictive control method for combined control of nitrogen oxide and ammonia escape

The cement industry is one of the main sources of NOx emissions, and automated denitration systems enable precise control of NOx emission concentration. With non-linearity, time delay and strong coupling data in cement production process, making it difficult to maintain stable control of the denitration system. However, excessive pursuit of denitration efficiency is often prone to large ammonia escape, causing environmental pollution. A multi-objective prediction model combining time series and a bi-directional long short-term memory network (MT-BiLSTM) is proposed to solve the data problem of the denitration system and achieve simultaneous prediction of NOx emission concentration and ammonia escape value. Based on this model, a model predictive control framework is proposed and a control strategy of denitration system with multi-index model predictive control (MI-MPC) is built based on neural networks. In addition, the differential evolution (DE) algorithm is used for rolling optimization to find the optimal solution and to obtain the best control variable parameters. The control method proposed has significant advantages over the traditional PID (proportional integral derivative) controller, with a 3.84% reduction in overshoot and a 3.04% reduction in regulation time. Experiments prove that the predictive control framework proposed in this paper has better stability and higher accuracy, with practical research significance.

Migration and transformation of phosphorus and toxic metals during sludge incineration with Ca additives

The recycling and utilization of phosphorus resources in sludge is becoming increasingly important. In this study, we compared the conversion of phosphorus and toxic metal passivation effects of different Ca additives under oxygen-rich combustion conditions and elucidated their specific mechanisms of action. The experimental results indicated that four Ca-based additives improved the recovery rate of total phosphorus, and promoted the generation of stable apatite phosphorus (AP). The effect of CaCl2 and CaO was greater than that of Ca(OH)2 and CaSO4. CaCl2 promoted the formation of Ca3(PO4)2 and Ca2P2O7, and CaSO4 improved the conversion of AlPO4 to Ca(H2PO4)2 with increasing temperature. The conversion capacity of CaO on non-apatite inorganic phosphorus to AP was greater than that of Ca(OH)2, and more CaH2P2O7, Ca(PO3)2, and Ca-Al-P minerals were found. Toxic metal percentages decreased after sludge incineration with CaCl2. Compared with CaO and Ca(OH)2, the toxic metal adsorption effect of CaSO4 was more significant. The influence of Ca additives on the conversion of Zn into stable components was as follows: CaCl2 > Ca(OH)2 > CaO > CaSO4. Ca additives reduced the toxic metal contamination level and ecological risk index values, and the order of toxic metal contamination levels was Ni > Zn > Cr > Cu > Mn. The experiment confirmed the conversion of phosphorus and the toxic metal passivation effect of Ca additives during oxy-fuel combustion of sludge, which is beneficial for its resource utilization.

Research on the Combustion Performance of Municipal Solid Waste in Different Sorting Scenarios: Thermokinetics Investigation via TG-DSC-FTIR-MS

Waste sorting is regarded as one of the most important strategies for municipal solid waste (MSW) management. The changes in the combustion parameters after MSW sorting had a significant impact on the actual operation of the boiler. In the present study, the effects of heating rate on combustion characteristics and dynamics of MSW in different sorting scenarios were studied using the thermogravimetry (TG)-differential scanning calorimetry (DSC)-Fourier transform infrared (FTIR)-mass spectrometry (MS) technique. TG-DSC analysis showed that the heat released from MSW combustion at different heating rates ranged from 1394.1 to 4130.1 J/g. According to the TG-DTG curves, the combustibility of 30% sorted MSW was increased by 1.2 times compared to that of the unsorted scenario. In the 30% sorted scenario, the average activation energies were estimated to be 161.24 and 159.93 kJ/mol based on the Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods, respectively. Based on the Coats-Redfern (CR) method, the minimum activation energies for unsorted and 20% sorted scenarios were 148.74 and 135.53 kJ/mol at 523 to 606 K, respectively, while they were 29.42 and 33.22 kJ/mol at 606 to 780 K. XRF analysis showed that the alkali and alkaline earth metal oxides in the ash contributed to a high risk of slagging and scaling. This work can provide a scientific basis for the real situation of MSW incineration.

Valorization of Textile Sludge and Cattle Manure Wastes into Fuel Pellets and the Assessment of Their Combustion Characteristics

The textile wastewater sludge (TWS) treatment and disposal are environmentally challenging due to toxic organics and metals. At the same time, cattle manure (CM), with better combustion performance, i.e., calorific value and uniform burning capability, is still underutilized in many parts of the world. This study evaluated and assessed the TWS and CM blending compatibility to convert them into fuel pellets for the direct combustion option and to stabilize toxic contaminants in TWS. After initial drying, grinding, and particle size control of the raw TWS and CM, both were blended at different ratios. The blended and nonblended TWS and CM samples were converted into pellets and analyzed for proximate and ultimate analyses, namely, moisture content, fixed carbon, CHNO, gross calorific value (GCV), bulk density, ash content, and metals, to evaluate the efficacy for energy applications. Out of three blended ratios, i.e., 75:25 (W/W%; CM/TWS), 50:50, and 25:75, the 75:25 blended pellet composition was found appropriate for fuel application. For the 75:25 blend, the obtained GCV was 12.77 MJ/kg, elemental carbon was 27.5%, volatiles were 41.7%, and residue ash was 42.8% of the total weight. Moreover, the blending ratios of 75:25 and 50:50 revealed that elemental and metal (Fe, Cu, Zn, Ni, Cr, Na, Mg, Mn) concentrations in TWS were stabilized to below threshold limits in the obtained residue ash for safe handling. The explored methods of TWS and CM waste processing, blending, and pelletization proposed a new technique for their sustainable waste valorization into energy sources.

Migration and transformation of trace elements during sewage sludge and coal slime Co-combustion

Co-combustion of sewage sludge (SS) and coal slime (CS) could improve the combustion properties of the two materials, however, high levels of trace elements (TEs) can be released from the two wastes, resulting in secondary pollution. The migration and transformation behavior of As, Cr, Pb, Zn, and Mn during co-combustion is explored in current research. The results showed co-combustion could inhibit the emission of Zn, As, Pb, and Mn, and the effect was more pronounced for Zn, As and Mn. Meanwhile, minerals like kaolinite and gypsum were found to generated in the ash from co-combustion but not solo-combustion. Model experiments demonstrated that kaolinite captured As, Pb and Mn, while gypsum captured Zn, As and Mn but facilitated the emission of Pb and Cr. This well explained the distinct TEs emission characteristics between co-combustion and solo combustion. As the temperature elevated, kaolinite in co-combustion ash decomposed and the generation of gypsum was promoted. In this way, the emission ratios of Zn, As, and Mn initially increased but subsequently decreased between 700 and 1300 °C, whereas Pb and Cr emission ratios increased by twofold within the same temperature range. Leaching characteristics and risk assessment code on co-combustion ashes were also conducted in this study. The results indicated a marginal elevation in the risk associated with trace elements (TEs) following co-combustion, provided that all five TEs remained within the limits of national standards.

Multi-objective prediction for denitration systems in cement: an approach combining process analysis and bi-directional long short-term memory network

Selective Non-Catalytic Reduction (SNCR) can improve the denitration process and reduce NOx emissions by accurizing prediction of NOx concentration and ammonia escape. However, there are inevitable time delays and nonlinearity problems in the prediction of NOx emission. To reduce NOx concentration quickly in SNCR, excessive ammonia spraying often causes a large amount of ammonia to escape, resulting in secondary pollution. Therefore, it is particularly important to monitor ammonia escape. To solve the above problems, this paper proposes a framework by specifically analyzing the cement denitration process and combining a multi-objective time series bi-directional long short-term memory network (MT-BiLSTM). Among them, the model achieves multi-objective prediction of NOx emission concentration and ammonia escape simultaneously. In addition, time series containing delay information are introduced in the input layer to eliminate the influence of delay. Based on the bi-directional LSTM model, the dropout strategy is adopted to improve the generalization of the model and the Adam optimizer is applied to improve the network performance. Besides, through the multi-step prediction of NOx emission at 3 time points, the dynamic nature of the data is preserved, which provides dynamic information support for realizing the automation of denitration system. The prediction performance of the MT-BiLSTM model is experimentally validated, and the results demonstrate that it can reliably predict both NOx and ammonia escape. The model achieves more accurate and reliable results for the prediction of flue gas concentrations compared with other methods such as SVR, DTR and LSTM. Therefore, the MT-BiLSTM model provides a basis for achieving NOx emission reduction and accurate ammonia injection.