Increasing generation of municipal solid waste, heterogeneity of waste composition, and complex processes of waste management and recovery have limited the performance of traditional treatment ...approaches. It is urgent to innovate waste management toward smarter and more efficient modes and break up the bottlenecks of the current system. Recently, deep learning has emerged as a powerful method for revealing hidden patterns or deducing correlations for which traditional treatment approaches face limitations or challenges. However, deep learning concepts and practices have not been widely utilized by researches in municipal solid waste management (MSWM). Herein, this research provides a critical review for deep learning and its application in MSWM. The framework and algorithms of a variety of deep learning methods have been compared and assessed. A body of deep learning applications have been reviewed according to their engagement in waste collection, transportation, and final disposal. Application of deep learning in MSWM stays in its infancy and requires great efforts for further development. The challenges and futures opportunities in the application of deep learning in the MSWM have been discussed to highlight the potential of deep learning in this field.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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.
•Data-driven models were adopted to promote the HHW management.•The estimated amount of HHW in Shanghai was 2049.67 t in 2025.•HVGGNet-11 with 90.5 % of precision was most suitable for HHW sorting.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
It is crucial to precisely predict the generation of plastic waste and realize its fine classification in terms of policy demand and environmental benefits. Only a few studies have used the ...date‐driven model to forecast the amount of plastic waste. The benefits of classifying the plastic waste using deep learning have also been only scarcely reported in the literature. Therefore, this study used the Prophet model to estimate the amount of plastic waste from 2005 to 2025. Four types of Visual Geometry Group Networks based on Transfer Learning (TLVGGNet) were performed for classifying the plastic waste. Potentials of saved energy, the reduction of green‐house gases emission (GHG), and air pollutants were also discussed under different scenarios (current recycling system and TLVGGNet system). The results showed that the amount of waste plastic was anticipated to be 26.44 Mt in 2020 and 33.18 Mt in 2025 in China. The method of transfer learning could shorten the training time and improve the performance of the TLVGGNet‐11 model in the test dataset (41.6–68.1%). Moreover, TLVGGNet‐16 was considered to be the most optimum model for plastic waste classification in terms of training time (83.94 s), accuracy (75.5%), precision (76.9%), recall (75.5%), and F1 score (75.1%). The TLVGGNet‐16 system contributes about 12.15–15.97% in terms of electricity‐savings. Compared with the current recycling system, the amount of CO2 emissions saved and reduction in CH4 emissions could be more than 8–10% and 0.4–0.5%, respectively, in the TLVGGNet‐16 system. The saved VOCS and NOX emissions were within the ranges of 34.84–127.22 billion kg and 93.64–414.14 billion kg between 2017 and 2025 using the method of deep learning.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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•Effect of agglomeration on heavy metals behavior has been considered.•Effect of phosphorus on heavy metals in gas-solid phase also discussed.•Emission of heavy metals sharply increased after defluidization started.•Phosphorus reduces the emission concentration of Pb and Cd.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•A two-stage pyrolysis-catalysis reactor was used to convert plastics into hydrogen.•Ni-Ce based catalyst showed great catalytic activity for H2 production.•Ni-Ce@SiO2 catalysts with different shell ...thickness were investigated.•The core-shell catalyst exhibited great stability during 5 times of reuse.
A core-shell type catalyst was applied to convert polyethylene (PE) plastic wastes into hydrogen using a two-stage pyrolysis-catalysis reactor. The effects of catalyst: plastic ratio, reaction temperature, and the suppression of coke formation on catalytic performance were investigated. Ni-Ce bimetallic catalyst was synthesized via modified polyol method, and the silica coating with different Ni:Si molar ratio was prepared with the extension of Stöber method. Different thickness of silica shell was synthesized and tested for hydrogen production from PE waste. The encapsulation of Ni-Ce core by silica shell could effectively inhibit the sintering of nanoparticles under high temperature conditions. The highest amount of hydrogen production was found when the catalyst: plastic weight ratio was 1.0, and the catalytic reaction temperature was 800 °C. The core-shell catalyst also exhibited great ability of coking resistance, showing great catalytic performance within 5 times of reuse.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this study, a core-shell structured catalyst composed of a nickel core coated with a high thermal-stability shell layer was prepared for the decomposition of waste plastics to produce hydrogen. ...Ceria-zirconia mixed metal oxide was used as the coating layer to protect the active phase of the catalyst. The as-prepared catalyst was firstly tested using a methane cracking process to evaluate its stability under high temperature and coking conditions. The special redox characteristics of the Ni@CeO
2
-ZrO
2
core-shell-structured catalyst provide lattice oxygen to oxidize carbon produced during the reaction and extend the life of the catalyst during the coking resistance test. Different pore sizes in the functional shell were prepared by adding a templating agent, and the catalyst was tested for its ability to produce hydrogen from plastic waste. The CeO
2
-ZrO
2
shell promoted the production of active oxygen species and enhanced the dispersion of the Ni cores, which are beneficial attributes for plastic waste decomposition.
A novel core-shell catalyst with high coking resistance ability was applied for hydrogen production from plastic waste.
This study discusses the influence of fluidization and gasification parameters on the hydrogen composition in syngas. For gasification conditions, when Stage 1 and Stage 2 gasifier temperature is ...900 °C, the hydrogen content in syngas is 35.59 mol.% when the activated carbon is used as bed material. For using zeolite as bed material, the hydrogen content is 38.25 mol.%. The hydrogen content is higher than that under other conditions, but if the Steam/Biomass ratio is increased to 0.6, the hydrogen content resulted from zeolite as bed material is the highest 39.38 mol.%. For fluidization parameters, when Stage 2 bed material size is changed to 0.46 mm, no matter the bed material is activated carbon or zeolite, the hydrogen content in syngas is the best among three particle sizes. In terms of operating gas velocity, when gas velocity is 1.5 Umf, the hydrogen content is higher. For fluidization parameters, the two bed materials can increase hydrogen content in syngas effectively in Stage 2 fluidized bed, and their effects are similar to each other. However, considering the fluidization parameters, the hydrogen content in syngas when activated carbon is used as bed material is better than that when the zeolite is used.
•Effects of fluidization and gasification parameters on H2 composition are discussed.•H2 ratio are 35.59 mol.% and 38.25 mol.% as activated carbon and zeolite are used.•As S/B ratio is 0.6, the H2 ratio of zeolite is the highest 39.38 mol.%.•When the gas velocity is 1.5 U/Umf, the H2 ratio is higher than other gas velocities.•For fluidization parameters, the H2 ratio of activated carbon is better than zeolite.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
ZrN thin films were deposited on AISI 304 stainless steel (304SS) by unbalanced magnetron sputtering (UBMS). Afterwards, the specimens were annealed at 1000 °C in vacuum (4 × 10−6 Torr) for a ...duration ranging from 1 to 4 h. The purpose of this study was to investigate the oxidation behavior and corrosion resistance of the vacuum annealed ZrN-coated 304SS prepared by UBMS method. The results of X-ray diffraction indicated that ZrN remained as the major phase in the oxidized thin films even after heat treating at 1000 °C for 4 h in vacuum. The surface grain size of the oxidized film increased with heat treating duration. The oxidized ZrN thin film on 304SS formed two oxide layers, the outer layer on the film surface and the inner layer nearby the film/substrate interface, which could be attributed to the simultaneous diffusion of oxygen from film surface and the edge of film/substrate interface, respectively. The results of potentiodynamic polarization scan showed that the corrosion resistance of the oxidized ZrN-coated 304SS was excellent and increased by at least 100 times relative to that of bare 304SS, based on the decrease of corrosion current density. The oxidized ZrN-coated 304SS also showed excellent durability after 500-hr salt spray test with corrosion area less than 4% for all specimens, and the oxidized ZrN films showed better durability than the as-deposited ZrN film in salt spray test. The results suggested that the electrical conductivity of the film may be a significant factor on Icorr, and the relative corrosion resistance of ZrN and ZrO2 in NaCl solution may also play an important role in salt spray test. The fully oxidized ZrN thin film showed high corrosion resistance and remained intact on 304SS substrate after potentiodynamic polarization scan, which was associated with the enhanced adhesion by the interdiffusion layer due to heat treatment. The adhesive problem of ZrO2 on stainless steel could be solved either with or without ZrN interlayer, if the vacuum annealing could produce a large interdiffusion zone and thereby enhancing the adhesion.
•An anti-corrosion ZrO2 layer was produced by vacuum annealed ZrN thin films at 1000 °C.•Outer and inner oxide layers were observed in vacuum annealed ZrN/304SS specimens.•The oxidized ZrN films show excellent corrosion resistance and durability in salt water.•ZrO2 coatings remains intact on stainless steel due to the broadening interdiffusion zone.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZRSKP
In the incineration process, agglomeration is caused by the combustion of wastes containing adhesion materials such as alkalis and earth alkalis. Alkali oxides not only have a low melting point but ...also can react with Si to form low-melting-point eutectics. Most of the researches focused on the inlet materials, however, the properties of sand bed materials are also playing an important role on defluidization process. A comprehensive analysis of sand compositions on the prediction of defluidization tendency is carried out. Variation of sand properties before and after fluidized bed operation is estimated by XRF characterization, and the effect of particle size distribution is also in consideration. Experimental results indicated that defluidization time decreases with the increasing particle size of all sand sources. Higher temperature promotes agglomeration/defluidization. According to the agglomeration indices calculation, indicator Al + Ca + Mg/(Na + K + Fe) can be used to estimate the defluidization tendency before fluidized bed operation for particle sizes below 770 μm. In contrast, for a particle size of 920 μm, Al + Ca + Mg + Fe /(Na + K) can be utilized to qualitatively characterize the defluidization time. On the other hand, the Support Vector Regression (SVR) model was the best model for predicting the defluidization time (R2 of 93.40% and MSE of 3470). Causal analysis shows particle size, K2O, and Na2O were the top three most important factors that affect the particle agglomeration. The results are helpful to the evaluation of the agglomeration tendency of sand bed materials before using fluidized bed waste incineration agglomeration in terms of qualitative analysis and quantitative analysis.
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•Sand bed compositions have effect on the agglomeration behavior.•Agglomeration indices qualitatively evaluate the defluidization time (DFT).•Machine learning were used to quantitatively predict the DFT.•Support Vector Regression model was the best model for predicting the DFT.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In the present work, a core-shell structured Co/SiO2@HZSM-5 catalyst was prepared for hydrogen production from syngas of plastic waste gasification. The cobalt catalyst was coated with HZSM-5 shell ...through a hydrothermal process, and the Co/SiO2@HZSM-5, with different loadings of HZSM-5 (e.g., 10–30 wt %) exhibited excellent activity and durability for dehydrogenation reactions. The amount of HZSM-5 was found to be an important factor for hydrogen production. Temperature-programmed reduction with H2 and temperature-programmed desorption of ammonia was applied to determine the active site and the acidity of prepared catalyst, respectively. The prepared Co/SiO2@HZSM-5 was tested through reforming of plastic gasification syngas and shown superior hydrogen production ability (∼90%) and stability (over 15 h). The effects of reduction-oxidation behavior on the catalytic performance were also discussed.
•The core-shell catalyst showed superior performance than traditional catalysts.•Mesoporous HZSM-5 shell prevented the active phase core from deactivation.•Co/SiO2@HZSM-5 catalyst was synthesized for hydrogen promotion.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
