Simulating a combined lysis-cryptic and biological nitrogen removal system treating domestic wastewater at low C/N ratios using artificial neural network

Yang, Shan-Shan; Yu, Xin-Lei; Ding, Mengqi; He, Lei; Cao, Guangwen; Zhao, Lei; Yu, Tao; Pang, Ji-Wei; Bai, Shunwen; Ding, Jie; Ren, Nanqi

doi:10.1016/j.watres.2020.116576

Cited by 77 publications

(12 citation statements)

References 51 publications

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“…The Fukui functions (FF) were used to compute the local reactivity descriptors (LRD) of TMP for nucleophilic attacks ( and for electrophilic attacks ( ) [ 30 , 31 ]. The charges values of atom (k) for neutral, cation, and anion species are denoted by , and respectively.…”

Section: Methodsmentioning

confidence: 99%

Experimental and theoretical study for removal of trimethoprim from wastewater using organically modified silica with pyrazole-3-carbaldehyde bridged to copper ions

et al. 2022

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Background Human and veterinary antibiotics are typically discharged as parent chemicals in urine or feces and are known to be released into the environment via wastewater treatment plants (WWTPs). Several research investigations have recently been conducted on the removal and bioremediation of pharmaceutical and personal care products (PPCPs) disposed of in wastewater. Results SiNP-Cu, a chelating matrix, was produced by delaying and slowing 1.5-dimethyl-1H-pyrazole-3-carbaldehyde on silica gel from functionalized with 3-aminopropyltrimethoxysilane. The prepared sorbent material was characterized using several techniques including BET surface area, FT-IR spectroscopy, Scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and nitrogen adsorption–desorption isotherm. The pseudo-second-order model provided the best correlation due to the big match between the experimental and theoretical of different adsorption coefficients. The Langmuir and Freundlich adsorption models were used and the study showed a better match with the Freundlich model with a capacity of removal reached up to 420 mg g−1. The removal capacity was dependent on pH and increased by increasing pH. The removal percentage reached 91;5% at pH = 8. The adsorbent demonstrated a high percentage removal of TMP, reaching more than 94% when increased pH. The sample was simply regenerated by soaking it for a few minutes in 1 N HCl and drying it. The sorbent was repeated five times with no discernible decrease in removal capacity. The thermodynamic study also showed endothermic, increasing randomness and not spontaneous. The free energy was 2.71 kJ/mol at 320 K. The findings of the DFT B3LYP/6–31 + g (d, p) local reactivity descriptors revealed that nitrogen atoms and π-electrons of the benzene and pyrimidine rings in the TMP are responsible for the adsorption process with the SiNP surface. The negative values of the adsorption energies obtained by molecular dynamic simulation indicated the spontaneity of the adsorption process. Conclusion The global reactivity indices prove that TMP is stable and it can be removed from wastewater using SiNP surface. The results of the local reactivity indices concluded that the active centers for the adsorption process are the nitrogen atoms and the π-electrons of the pyrimidine and benzene rings. Furthermore, the positive value of the maximum charge transfer number (ΔN) proves that TMP has a great tendency to donate electrons to SiNP surface during the process of adsorption.

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Section: Methodsmentioning

confidence: 99%

Experimental and theoretical study for removal of trimethoprim from wastewater using organically modified silica with pyrazole-3-carbaldehyde bridged to copper ions

et al. 2022

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“…e production status of agriculture strongly depends on the use of pesticides [1][2][3][4][5][6][7]. Because of the continuously growing population and the progress of modern agriculture, pesticides have played a crucial role in producing high crop yields, preventing diseases and controlling pests [8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

The sorption of Tebuconazole and Linuron from an Aqueous Environment with a Modified Sludge-Based Biochar: Effect, Mechanisms, and Its Persistent Free Radicals Study

Yang

Sun

Liu

et al. 2021

Journal of Chemistry

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In this study, the sludge-based biochar was prepared and utilized as an adsorbent for the removal of two commonly used pesticides in agriculture, namely tebuconazole (Teb) and linuron (Lin) in an aqueous solution. The main contributing factors such as biochar preparation conditions, persistent free radicals as well as contact time, agitation speed, biochar dose, temperature, and pH were investigated. The physicochemical properties were characterized by SEM + EDS, FTIR, BET, EPR, etc. The results showed that the maximum adsorption capacities based on the Langmuir model was 7.8650 mg g−1 for tebuconazole and that based on Freundlich model was 9.0645 mg·g-1 for linuron at 25°C. The pseudo-second-order kinetic equations were all fitted well to the kinetic process of the adsorption of the two pesticides with all R2 ≥ 0.915. The maximum values of tebuconazole adsorption capacity occur at pH = 3. Meanwhile, linuron was not affected by pH. Both Cr6+ (r = −0.793∗∗/ −0.943∗∗) and humic acid (r = −0.798∗∗/ −0.947∗∗) significantly inhibited the adsorption amount of tebuconazole and linuron onto the biochar. Electron spin resonance signals (ESR) indicated that environmentally persistent radicals (EPFRs) are preferentially formed at lower pyrolysis temperatures and lower transition metal concentrations. The g-factors for BC400, BC600, BCF400, and BCF600 were 2.0036, 2.0035, 2.0034, and 2.0033, respectively, indicating that the EPFRs mainly have a carbon-centered structure with adjacent oxygen atoms. In addition, to close to the actual situation, natural water (from YanTai) was collected to simulate pesticide contamination. This study demonstrates that sludge-based biochar can achieve efficient removal of tebuconazole and linuron in aqueous environment in a short period of time with no secondary environmental risk especially on the waste activated sludge.

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“…Machine learning (ML) main areas are supervised learning and unsupervised learning [19,20]. Nevertheless, a third area has been gaining popularity in the last decade: Reinforcement Learning (RL).…”

Section: Reinforcement Learning 21 Originmentioning

confidence: 99%

Steelmaking Process Optimised through a Decision Support System Aided by Self-Learning Machine Learning

et al. 2022

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This paper presents the application of a reinforcement learning (RL) algorithm, concretely Q-Learning, as the core of a decision support system (DSS) for a steelmaking subprocess, the Composition Adjustment by Sealed Argon-bubbling with Oxygen Blowing (CAS-OB) from the SSAB Raahe steel plant. Since many CAS-OB actions are selected based on operator experience, this research aims to develop a DSS to assist the operator in taking the proper decisions during the process, especially less experienced operators. The DSS is intended to supports the operators in real-time during the process to facilitate their work and optimise the process, improving material and energy efficiency, thus increasing the operation’s sustainability. The objective is that the algorithm learns the process based only on raw data from the CAS-OB historical database, and on rewards set according to the objectives. Finally, the DSS was tested and validated by a developer engineer from the CAS-OB steelmaking plant. The results show that the algorithm successfully learns the process, recommending the same actions as those taken by the operator 69.23% of the time. The algorithm also suggests a better option in 30.76% of the remaining cases. Thanks to the DSS, the heat rejection due to wrong composition is reduced by 4%, and temperature accuracy is increased to 83.33%. These improvements resulted in an estimated reduction of 2% in CO2 emissions, 0.5% in energy consumption and 1.5% in costs. Additionally, actions taken based on the operator’s experience are incorporated into the DSS knowledge, facilitating the integration of operators with lower experience in the process.

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Simulating a combined lysis-cryptic and biological nitrogen removal system treating domestic wastewater at low C/N ratios using artificial neural network

Cited by 77 publications

References 51 publications

Experimental and theoretical study for removal of trimethoprim from wastewater using organically modified silica with pyrazole-3-carbaldehyde bridged to copper ions

Experimental and theoretical study for removal of trimethoprim from wastewater using organically modified silica with pyrazole-3-carbaldehyde bridged to copper ions

The sorption of Tebuconazole and Linuron from an Aqueous Environment with a Modified Sludge-Based Biochar: Effect, Mechanisms, and Its Persistent Free Radicals Study

Steelmaking Process Optimised through a Decision Support System Aided by Self-Learning Machine Learning

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