Data-driven models applying in household hazardous waste: Amount prediction and classification in Shanghai.

Precisely predicting the amount of household hazardous waste (HHW) and classifying it intelligently is crucial for effective city management. Although data-driven models have the potential to address these problems, there have been few studies utilizing this approach for HHW prediction and classification due to the scarcity of available data. To address this, the current study employed the prophet model to forecast HHW quantities based on the Integration of Two Networks systems in Shanghai. HHW classification was performed using HVGGNet structures, which were based on VGG and transfer learning. To expedite the process of finding the optimal global learning rate, the method of cyclical learning rate was adopted, thus avoiding the need for repeated testing. Results showed that the average rate of HHW generation was 0.1 g/person/day, with the most significant waste categories being fluorescent lamps (30.6 %), paint barrels (26.1 %), medicine (26.2 %), battery (15.8 %), thermometer (0.03 %), and others (1.22 %). Recovering rare earth element (18.85 kg), Cd (3064.10 kg), Hg (15643.43 kg), Zn (14239.07 kg), Ag (11805.81 kg), Ni (4956.64 kg) and Li (1081.45 kg) from HHW can help avoid groundwater pollution, soil contamination and air pollution. HVGGNet-11 demonstrated 90.5 % precision and was deemed most suitable for HHW sorting. Furthermore, the prophet model predicted that HHW in Shanghai would increase from 794.43 t in 2020 to 2049.67 t in 2025.

Agglomeration-influenced transformation of heavy metals in gas-solid phases during simulated sewage sludge co-incineration: Effects of phosphorus and operating temperature.

Phosphorus and operating temperature not only affect the agglomeration behavior but also the transformation and migration of heavy metals. Accordingly, this study examined the effect of temperature and phosphorus in a fluidized bed combustion process to understand the emission and distribution of heavy metals by both experimental and thermodynamic calculations. The experimental results indicated that the sodium-phosphate reactions occur before the sodium-silicate reaction in the solid phase when the ratio of P/Na was 1/2. A low-melting-point sodium phosphate component, such as NaPO3, leads to easier particle agglomeration than Na2O-SiO2. In terms of the emissions of heavy metals, Pb and Cd show a similar trend: both the amount of emission smaller than that without adding phosphorus and the amount of emission share an upward trend with the operating time increased during MSS fluidized bed combustion. However, with the presence of phosphorus, the emission of Cr shows slightly decreased, and then sharply dropped, after that, increasing with operating time increased. Generally speaking, the maximum amount of Pb and Cd emitted was at 900 °C, followed by 800 °C and 700 °C. The higher temperature would promote the volatilization of Pb and Cd to emit. On the other hand, Cr emitted at the beginning tended to increase but later decreases when the temperatures were 700 and 900 °C, which may be due to the emission of Cr being influenced by the different affinities of both Al and Cr, reacting with Na in a fluidized bed incinerator. As for the distribution of heavy metals in the solid phase, a higher concentration of heavy metals was found in both the coarsest and finest particles during the process of agglomeration/defluidization.

Deep learning hybrid predictions for the amount of municipal solid waste: A case study in Shanghai.

It is crucial to precisely estimate the municipal solid waste (MSW) amount for its sustainable management. Owing to learning complicated and abstract features between the factors and target, deep learning has recently emerged as one of the useful tools with potential to predict the MSW amount. Therefore, this study aimed to design an MSW amount predicted system in Shanghai, consisting of Attention (A), one-dimensional convolutional neural network (C), and long short-term memory (L), to investigate the relationship between exogenous series (24 socioeconomics factors and past MSW amount) and target (MSW amount). The role of Attention, 1D-CNN, LSTM played on the MSW predicted amount also have investigated. The results show that attention is crucial for decoding the encoding information, which would improve performance between predicted and known MSW amount (R2 in A-L-C, L-A-C, L-C-A was 89.45%, 90.77%, and 95.31%, respectively.). CNN modules appear to be positioned similarly across the MSW predicted system. Finally, R2 in L-A-C, A-L-C, and A-C-L was 85.44%, 91.61%, and 89.45%, which suggested that LSTM as an intermediary between CNN and Attention modules seems a wise measure to predict the MSW amount based on the correlation efficiency. In addition, some socioeconomic factors including the average number of people in households and budget revenue may be chosen for the decision-making of MSW management in Shanghai city in the future, according to the weight of neurons in fully connected layers by the visual technology.

Influence of different fluidization and gasification parameters on syngas composition and heavy metal retention in a two-stage fluidized bed gasification process.

Herein, we investigated the influence of gasification and fluidization parameters on the H2 content of syngas and the retention of heavy metals (Cu and Pb) in a bed material during a two-stage fluidized bed gasification process. The results indicated that a temperature of 900 °C in both stages resulted in the highest H2 content (32.4 mol%) in syngas. When different equivalence ratios (ERs) were investigated, it was found that the highest H2 content in syngas (25.4 mol%) was achieved at an ER of 0.3. A particle size of 0.46 mm in the fluidized bed led to an increase in the H2 content of syngas. Moreover, increasing the operating gas velocity led to an increase in the H2 content of syngas. The heavy metal concentration in the bed material was the highest at 500 °C. When the influences of different particle sizes and operating gas velocities were compared, it was observed that a particle size of 0.46 mm and gas velocity of 1.5 U/Umf resulted in increased heavy metal concentrations in the bed material, which indicates that the reduction in the particle size and the increase in the operating gas velocity enhanced gasification and improved the retention of heavy metals.

Sequential extraction for heavy metal distribution of bottom ash from fluidized bed co-combusted phosphorus-rich sludge under the agglomeration/defluidization process.

Agglomeration that occurs during municipal sewage sludge (MSS) fluidized bed co-combustion might affect heavy metal distribution and the transformation of bottom ash. A study on the mobility and speciation of heavy metals that accompanies agglomeration behavior and phosphorus addition should be examined during MSS co-combustion. Meanwhile, the aim of this study was to evaluate the total content and speciation of heavy metals during the MSS fluidized bed co-combustion by the chemical sequential extraction procedure (SEP). The risk assessment code (RAC) and individual contamination factor (ICF) are calculated to evaluate the mobility of heavy metals and their environmental risks in agglomerates. Moreover, identification of agglomerates is established by both characterization (scanning electron microscopy/energy-dispersive spectroscopy, X-ray photoelectron spectroscopy) and thermodynamic simulation (HSC chemistry software). The experimental results indicated that P and Na would form the lower melting-point compounds such as NaPO3 and Na2O in the bottom ash, which promoted agglomeration during MSS fluidized bed co-combustion. According to the simulation, Na and P have a stronger affinity than Si and Cr, and this reaction is not only influenced by particle agglomeration, but also by heavy metal distribution during modified MSS co-combustion. Nevertheless, the results of ICFs and RACs obtained from the SEP indicated that for heavy metals trapped in agglomerates, a weaker binding such as physical covering by eutectics might be considered as the dominant reaction compared with chemical binding to form a metal complex.

Experimental investigation of synthetic gas composition in a two-stage fluidized bed gasification process: effect of activated carbon as bed material.

In this study, a two-stage fluidized bed gasifier was used to investigate the effect of the equivalence ratio (ER) and steam/biomass ratio (S/B) on the synthetic gas distribution while activated carbon (AC) was added as the bed material in secondary gasifier (Stage II). The experimental results showed that when the empty bed (without the bed material) was used for the Stage II reaction, the hydrogen (H2) content in the synthetic gas emitted from the Stage II reactor was 2-3 mol% higher than that from the first-stage gasifier (Stage I). It was supposed that using the Stage II reactor prolongs the reaction time and thereby increases the H2 production. Besides, when the AC was added in the Stage II gasifier, the H2 concentration, the total gas yield, and gas heating value reached their maximum (30 mol%) when ER and S/B were 0.3 and 1.5, respectively.

Catalytic upgrading of syngas from fluidized bed air gasification of sawdust.

This study was conducted to investigate the effects of various gasification temperatures in a fluidized bed gasifier on biomass-derived products and to evaluate the efficiency of syngas upgraded by a secondary catalytic reactor. The results indicated that biomass vaporization was clearly affected by gasification temperature, resulting in the obtained products having different composition ratios. Additionally, the hydrogen promotion ratios were found to be strongly dependent on the condensable products, indicating that the products were upgraded via the use of a catalyst in the secondary reactor. If biomass vaporized at suitable gasification temperatures can produce a large amount of condensable products, the products could be effectively upgraded for hydrogen production by the secondary catalytic reactor under very mild conditions (250°C). Overall, the process not only upgraded hydrogen production, but also degraded contaminants; therefore, its implementation should reduce the cost of operation and pollution control in the biomass-to-energy industry.

Evaluating the potential of CNT-supported Co catalyst used for gas pollution removal in the incineration flue gas.

This study investigated the use of Cu/Al(2)O(3), Co/Al(2)O(3), Fe/Al(2)O(3), and Ni/Al(2)O(3) catalysts for the growth of carbon nanotubes (CNTs). These CNTs were used as support for Co catalyst preparation and Co/CNT catalysts were applied to a catalytic reaction to remove BTEX, PAHs, SO(2), NO, and CO simultaneously in a pilot-scale incineration system. The analyzed results of EDS and XRD showed low metal content and good dispersion characteristics of the Al(2)O(3)-supported catalysts by excess-solution impregnation. FESEM analyzed results showed that the CNTs that were synthesized from Co, Fe, and Ni catalysts had a diameter of 20nm, whereas those synthesized from Cu/Al(2)O(3) had a diameter of 50nm. Pilot-scale test results demonstrated that the Co/CNT catalyst effectively removed air pollutants in the catalytic reaction and that there was no obvious deactivation by Pb, water vapor, and coke deposited in the process. The thermal stabilization at 250 degrees C and hydrophobicity properties of CNTs enhanced the application of CNT catalysts in flue gas.

The prospect and development of incinerators for municipal solid waste treatment and characteristics of their pollutants in Taiwan.

Taiwan is a small, densely populated island with unique experiences in the construction and operation of incinerators. In such a small area, Taiwan has built 22 incinerators over a short span of time, combusting large amount of municipal solid waste as much as 23,250 tons per day. This study focuses on the history of construction and development of incinerators in Taiwan as well as the characteristics of pollutants, such as heavy metals (Pb, Cd, and Hg), acid gases (NO x , SO x , CO, and HCl), and dioxins emitted from the incinerators. Furthermore, the study also covers the generation and composition of municipal solid waste (MSW), and the production of energy in Taiwan. According to Taiwan's data on pollutant emissions, the emission level of pollutants is under control and meets the stringent regulations of Taiwan Environmental Protection Administration (TEPA). Researches have shown that using air pollution control devices (APCDs) in the operation of incinerators provides effective measures for air pollutant control in Taiwan. The main advantage of using incinerators is the generation of electricity (waste-to-energy) during the incineration of municipal solid waste, producing energy that can be consumed by the general public and the industry. Taiwan's extensive experience in incinerator construction and operation may serve as an example for developing countries in devising waste treatment technology, energy recovery, and the control of contagious viral diseases.