Pub Date : 2025-02-06DOI: 10.1016/j.psep.2025.106866
Yukun Chang , Wenyuan Zhou , Yanhui Chen , Guangshun Ran , Fangyan Cui , Zicong Yang , Hui Song , Jinshu Wang , Hongyi Li
Developing efficient and stable catalysts for methanol oxidation reaction (MOR) is urgent for economic development and energy scarcity. Herein, platinum (Pt) catalyst was planted on carbon nanotubes crosslinked BiOCl ultrathin nanosheets whose (001) facets enriched with oxygen vacancies. It has been found that he oxygen vacancies not only can enhance the electrical conductivity and the adsorption capability, but also can stabilize Pt due to strong metal-support interaction. The catalyst exhibits a mass activity of 2.39 A mgPt−1, four times higher than that of the benchmark PtC. Moreover, its stability has increased by 54 times compared to PtC. Such a superior electrochemical activity is attributed to the enhancement of OH* adsorption dominantly, which is considered as the catalytically active species. Additionally, the density functional theory calculation is employed to explore the methanol oxidation mechanism with assistant of in-situ Raman test. The valuable formic acid may be produced rather than CO2, which is expected to be applied to direct methanol fuel cells while generating additional economic benefits.
{"title":"Oxygen vacancies in ultrathin BiOCl nanosheets induced Pt for enhanced methanol oxidation","authors":"Yukun Chang , Wenyuan Zhou , Yanhui Chen , Guangshun Ran , Fangyan Cui , Zicong Yang , Hui Song , Jinshu Wang , Hongyi Li","doi":"10.1016/j.psep.2025.106866","DOIUrl":"10.1016/j.psep.2025.106866","url":null,"abstract":"<div><div>Developing efficient and stable catalysts for methanol oxidation reaction (MOR) is urgent for economic development and energy scarcity. Herein, platinum (Pt) catalyst was planted on carbon nanotubes crosslinked BiOCl ultrathin nanosheets whose (001) facets enriched with oxygen vacancies. It has been found that he oxygen vacancies not only can enhance the electrical conductivity and the adsorption capability, but also can stabilize Pt due to strong metal-support interaction. The catalyst exhibits a mass activity of 2.39 A mg<sub>Pt</sub><sup>−1</sup>, four times higher than that of the benchmark PtC. Moreover, its stability has increased by 54 times compared to PtC. Such a superior electrochemical activity is attributed to the enhancement of OH* adsorption dominantly, which is considered as the catalytically active species. Additionally, the density functional theory calculation is employed to explore the methanol oxidation mechanism with assistant of in-situ Raman test. The valuable formic acid may be produced rather than CO<sub>2</sub>, which is expected to be applied to direct methanol fuel cells while generating additional economic benefits.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106866"},"PeriodicalIF":6.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-06DOI: 10.1016/j.psep.2025.106863
Ganesh Chembedu, P.V. Manu
The growing population demands more energy from fossil fuels, which are nonrenewable and have environmental risks, thus alternative fuels are in search. This research investigates the impact of novel isopentanol (IP), waste watermelon seed biodiesel (WSB), and turmeric oil (TO) blends in the CI engine at varied levels during preheating and at maximum load for improved performance and emissions. The Response Surface Methodology (RSM) and Adaptive-Network Based Fuzzy Inference Systems (ANFIS) models are developed, and each response is compared, demonstrating that ANFIS models are more accurate than RSM. Adopted multi-criteria decision-making methods (TOPSIS and ARAS) and RSM model for optimization. The TOPSIS and ARAS approaches provided the same optimum parameters for the experiment list, proving their correctness. TOPSIS and ARAS optimum factors are WSB-5 %, IP-5 %, and TO-2000 ppm. TOPSIS/ARAS to diesel results proves, BTE 2.1 %↑, BSEC 3.5 %↓, CO 14.3 %↓, HC 9.8 %↓, CO2 1.4 %↓, NOx 12.1 %↓, and smoke 9 %↓. While RSM optimum factors are WSB-12.5 %, IP-8 %, and TO-2362 ppm, with a combined desirability of 0.967. RSM to diesel results proves, BTE 2.6 %↑, BSEC 4.3 %↓, CO 14.3 %↓, HC 9.8 %↓, CO2 2.7 %↓, NOx 12.3 %↓, and smoke 9.5 %↓. Because of the improved performance and declined emissions, the preheated (WSB12.5IP8TO2362) blend proved to be the best alternative to diesel.
{"title":"Investigation of performance and emissions of a diesel engine fueled with preheated blends of diesel-watermelon seed biodiesel- isopentanol-turmeric oil","authors":"Ganesh Chembedu, P.V. Manu","doi":"10.1016/j.psep.2025.106863","DOIUrl":"10.1016/j.psep.2025.106863","url":null,"abstract":"<div><div>The growing population demands more energy from fossil fuels, which are nonrenewable and have environmental risks, thus alternative fuels are in search. This research investigates the impact of novel isopentanol (IP), waste watermelon seed biodiesel (WSB), and turmeric oil (TO) blends in the CI engine at varied levels during preheating and at maximum load for improved performance and emissions. The Response Surface Methodology (RSM) and Adaptive-Network Based Fuzzy Inference Systems (ANFIS) models are developed, and each response is compared, demonstrating that ANFIS models are more accurate than RSM. Adopted multi-criteria decision-making methods (TOPSIS and ARAS) and RSM model for optimization. The TOPSIS and ARAS approaches provided the same optimum parameters for the experiment list, proving their correctness. TOPSIS and ARAS optimum factors are WSB-5 %, IP-5 %, and TO-2000 ppm. TOPSIS/ARAS to diesel results proves, BTE 2.1 %↑, BSEC 3.5 %↓, CO 14.3 %↓, HC 9.8 %↓, CO<sub>2</sub> 1.4 %<strong>↓,</strong> NOx 12.1 %<strong>↓,</strong> and smoke 9 %↓. While RSM optimum factors are WSB-12.5 %, IP-8 %, and TO-2362 ppm, with a combined desirability of 0.967. RSM to diesel results proves, BTE 2.6 %↑, BSEC 4.3 %↓, CO 14.3 %↓, HC 9.8 %↓, CO<sub>2</sub> 2.7 %<strong>↓,</strong> NOx 12.3 %<strong>↓,</strong> and smoke 9.5 %↓. Because of the improved performance and declined emissions, the preheated (WSB12.5IP8TO2362) blend proved to be the best alternative to diesel.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106863"},"PeriodicalIF":6.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-06DOI: 10.1016/j.psep.2025.106865
Fei Yin , Yingying Li , Tianrui Zhang, Yujun Zhu
Novel Nb-modified FeVO4 (NbaFeVO4) samples were fabricated via utilizing the citric method for employing in selective catalytic reduction NOx with NH3 (NH3-SCR). The NbaFeVO4 catalysts exhibit good NH3-SCR activity compared with FeVO4. In addition, a range of characterization methods was applied to explore the impact of Nb introduction on catalytic activity and tolerance to SO2 and H2O, comprising N2 physical adsorption, XRF, XRD, NH3-TPD, Raman spectroscopy, H2-TPR, XPS, SEM, HR-TEM and DRIFTS. The findings demonstrate that the addition of Nb to FeVO4 can inhibit the crystallization of FeVO4 and lead to improvement in the specific surface area, thereby exposing a greater number of active sites. The introduction of Nb leads to the increase of acid content on NbaFeVO4, and the increase of specific surface area can effectively improve the NH3-SCR activity of the catalyst. Among all NbaFeVO4 catalysts, Nb0.3FeVO4 exhibits the best catalytic activity, and the NO conversion can reach more than 90 % at 210–360 °C, and it also exhibits better resistance to H2O and SO2 than FeVO4. This can be explained the fact that the addition of Nb can increase the ratio of V4+/V on the surface of FeVO4, which can inhibit the ability of the Nb0.3FeVO4 catalyst to absorb SO2 and improve the SO2 resistance of Nb0.3FeVO4. The good water and sulfur resistance of Nb0.3FeVO4 makes it in the face of complex flue gas composition in practical applications. Furthermore, the in-situ DRIFTS was utilized to explore the NH3-SCR reaction mechanism.
{"title":"Enhancing the NH3-SCR denitration activity at low temperature and H2O and SO2 resistance over Nb-modified FeVO4 catalysts","authors":"Fei Yin , Yingying Li , Tianrui Zhang, Yujun Zhu","doi":"10.1016/j.psep.2025.106865","DOIUrl":"10.1016/j.psep.2025.106865","url":null,"abstract":"<div><div>Novel Nb-modified FeVO<sub>4</sub> (Nb<sub>a</sub>FeVO<sub>4</sub>) samples were fabricated via utilizing the citric method for employing in selective catalytic reduction NO<sub>x</sub> with NH<sub>3</sub> (NH<sub>3</sub>-SCR). The Nb<sub>a</sub>FeVO<sub>4</sub> catalysts exhibit good NH<sub>3</sub>-SCR activity compared with FeVO<sub>4</sub>. In addition, a range of characterization methods was applied to explore the impact of Nb introduction on catalytic activity and tolerance to SO<sub>2</sub> and H<sub>2</sub>O, comprising N<sub>2</sub> physical adsorption, XRF, XRD, NH<sub>3</sub>-TPD, Raman spectroscopy, H<sub>2</sub>-TPR, XPS, SEM, HR-TEM and DRIFTS. The findings demonstrate that the addition of Nb to FeVO<sub>4</sub> can inhibit the crystallization of FeVO<sub>4</sub> and lead to improvement in the specific surface area, thereby exposing a greater number of active sites. The introduction of Nb leads to the increase of acid content on Nb<sub>a</sub>FeVO<sub>4</sub>, and the increase of specific surface area can effectively improve the NH<sub>3</sub>-SCR activity of the catalyst. Among all Nb<sub>a</sub>FeVO<sub>4</sub> catalysts, Nb<sub>0.3</sub>FeVO<sub>4</sub> exhibits the best catalytic activity, and the NO conversion can reach more than 90 % at 210–360 °C, and it also exhibits better resistance to H<sub>2</sub>O and SO<sub>2</sub> than FeVO<sub>4</sub>. This can be explained the fact that the addition of Nb can increase the ratio of V<sup>4+</sup>/V on the surface of FeVO<sub>4</sub>, which can inhibit the ability of the Nb<sub>0.3</sub>FeVO<sub>4</sub> catalyst to absorb SO<sub>2</sub> and improve the SO<sub>2</sub> resistance of Nb<sub>0.3</sub>FeVO<sub>4</sub>. The good water and sulfur resistance of Nb<sub>0.3</sub>FeVO<sub>4</sub> makes it in the face of complex flue gas composition in practical applications. Furthermore, the <em>in-situ</em> DRIFTS was utilized to explore the NH<sub>3</sub>-SCR reaction mechanism.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106865"},"PeriodicalIF":6.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-05DOI: 10.1016/j.psep.2025.106819
Adil Sultan , Muhammad Junaid Ali Asif Raja , Chuan-Yu Chang , Chi-Min Shu , Adiqa Kausar Kiani , Muhammad Asif Zahoor Raja
Cholera infectious disease spread through water sanitation containing zooplankton carrying Vibrio Cholerae is a significant global threat, underscoring the urgent need for effective prevention through mathematical simulation regimes. In this study, novel quad-layered deep cascaded feed-forward nonlinear autoregressive exogenous (CFNARX) neural networks optimized with Bayesian regularization (BR) technique are employed to model fractional plankton-assisted cholera propagation (FPCP) system declaring the transmission of Vibrio Cholerae infested on zooplanktons into sanitation system of human society. The fractional differential epidemiological model incorporating density of phytoplankton, density of Vibrio Cholerae infected on zooplankton, number of infected human population with cholerae, number of recovered human population from cholerae, total number of human population and concentration of free-living Vibrio Cholerae exacted by a fractional Adams-Bashforth-Moulton predictor-corrected method across sundry scenarios comprising different fractional order values. The synthetic datasets are partitioned into training and testing sub-sets to model intricate dynamics of FPCP by means of a novel CFNARX-BR computing paradigm. The adept aptitudes of designed neural networks are assessed on diverse FPCP system scenarios using mean squared error (MSE) converging patterns, error-input correlations and error auto-correlation analytics, error regression analysis, time-series response plots, and error histogram studies. The forecasted outcomes of CFNARX-BR paradigm are compared with reference numerical outcomes through comparison charts and absolute error analysis. The minute deviations of CFNARX-BR outcomes reflected by MSE, ranging from 10−11 to 10−12, across all complex FPCP system cases affirming the robustness of the devised intelligent computing schematic. Furthermore, the absolute error analysis reveals minute deviations of the order 10−5 to 10−7, thereby reflecting the adept utilization of an efficient neurocomputing technique to model the fractional ecological-epidemiological differential models.
{"title":"Predictive modeling of fractional plankton-assisted cholera propagation dynamics using Bayesian regularized deep cascaded exogenous neural networks","authors":"Adil Sultan , Muhammad Junaid Ali Asif Raja , Chuan-Yu Chang , Chi-Min Shu , Adiqa Kausar Kiani , Muhammad Asif Zahoor Raja","doi":"10.1016/j.psep.2025.106819","DOIUrl":"10.1016/j.psep.2025.106819","url":null,"abstract":"<div><div>Cholera infectious disease spread through water sanitation containing zooplankton carrying <em>Vibrio Cholerae</em> is a significant global threat, underscoring the urgent need for effective prevention through mathematical simulation regimes. In this study, novel quad-layered deep cascaded feed-forward nonlinear autoregressive exogenous (CFNARX) neural networks optimized with Bayesian regularization (BR) technique are employed to model fractional plankton-assisted cholera propagation (FPCP) system declaring the transmission of <em>Vibrio Cholerae</em> infested on zooplanktons into sanitation system of human society. The fractional differential epidemiological model incorporating density of phytoplankton, density of <em>Vibrio Cholerae</em> infected on zooplankton, number of infected human population with cholerae, number of recovered human population from cholerae, total number of human population and concentration of free-living <em>Vibrio Cholerae</em> exacted by a fractional Adams-Bashforth-Moulton predictor-corrected method across sundry scenarios comprising different fractional order values. The synthetic datasets are partitioned into training and testing sub-sets to model intricate dynamics of FPCP by means of a novel CFNARX-BR computing paradigm. The adept aptitudes of designed neural networks are assessed on diverse FPCP system scenarios using mean squared error (MSE) converging patterns, error-input correlations and error auto-correlation analytics, error regression analysis, time-series response plots, and error histogram studies. The forecasted outcomes of CFNARX-BR paradigm are compared with reference numerical outcomes through comparison charts and absolute error analysis. The minute deviations of CFNARX-BR outcomes reflected by MSE, ranging from 10<sup>−11</sup> to 10<sup>−12</sup>, across all complex FPCP system cases affirming the robustness of the devised intelligent computing schematic. Furthermore, the absolute error analysis reveals minute deviations of the order 10<sup>−5</sup> to 10<sup>−7</sup>, thereby reflecting the adept utilization of an efficient neurocomputing technique to model the fractional ecological-epidemiological differential models.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106819"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-05DOI: 10.1016/j.psep.2025.106869
David B. Olawade , James O. Ijiwade , Oluwaseun Fapohunda , Abimbola O. Ige , David O. Olajoyetan , Ojima Zechariah Wada
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants that resist conventional water treatment methods, raising concerns about their impact on human health and ecosystems. As PFAS contamination becomes increasingly widespread, the need for novel, effective treatment solutions have grown. Predictive modeling offers a promising approach to evaluate PFAS behavior, removal efficiency, and transformation pathways in emerging treatment technologies. This narrative review explores current advancements in predictive models for PFAS remediation, focusing on methods that incorporate PFAS structural characteristics, environmental factors, and treatment type. Three main modeling approaches are discussed: empirical, mechanistic, and machine learning models, each with unique strengths and limitations depending on data availability and treatment conditions. The review also addresses recent developments in advanced treatment systems such as advanced oxidation processes (AOPs), electrochemical treatment, and adsorption, as well as the role of machine learning in optimizing treatment predictions. Key challenges, including data limitations, transformation product toxicity, and model validation, are examined, with recommendations for future research emphasizing data expansion, integration of toxicity predictions, and enhanced model interpretability. By tailoring predictive models to PFAS-specific variables and diverse treatment conditions, researchers can advance sustainable PFAS management practices and guide effective remediation strategies for contaminated sites.
{"title":"Predictive modeling of PFAS behavior and degradation in novel treatment scenarios: A review","authors":"David B. Olawade , James O. Ijiwade , Oluwaseun Fapohunda , Abimbola O. Ige , David O. Olajoyetan , Ojima Zechariah Wada","doi":"10.1016/j.psep.2025.106869","DOIUrl":"10.1016/j.psep.2025.106869","url":null,"abstract":"<div><div>Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants that resist conventional water treatment methods, raising concerns about their impact on human health and ecosystems. As PFAS contamination becomes increasingly widespread, the need for novel, effective treatment solutions have grown. Predictive modeling offers a promising approach to evaluate PFAS behavior, removal efficiency, and transformation pathways in emerging treatment technologies. This narrative review explores current advancements in predictive models for PFAS remediation, focusing on methods that incorporate PFAS structural characteristics, environmental factors, and treatment type. Three main modeling approaches are discussed: empirical, mechanistic, and machine learning models, each with unique strengths and limitations depending on data availability and treatment conditions. The review also addresses recent developments in advanced treatment systems such as advanced oxidation processes (AOPs), electrochemical treatment, and adsorption, as well as the role of machine learning in optimizing treatment predictions. Key challenges, including data limitations, transformation product toxicity, and model validation, are examined, with recommendations for future research emphasizing data expansion, integration of toxicity predictions, and enhanced model interpretability. By tailoring predictive models to PFAS-specific variables and diverse treatment conditions, researchers can advance sustainable PFAS management practices and guide effective remediation strategies for contaminated sites.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106869"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To achieve harmless treatment of sludge, the thermal conversion represented by combustion is considered the most promising treatment technology because it reduces sludge volume and recovers energy. This study develops a process of handling 400 tons of sludge per day by integrating sludge drying and combustion, and accompanied by energy analysis and economic evaluation. The proposed system provides the energy required for the drying process by recovering waste heat from the combustion section, thereby investigating the feasibility of achieving energy self-balance. The impact of variations in carbon and moisture content on the economic performance of the process by adjusting the moisture content of sludge with three different carbon levels has been explored. The findings indicate a strong correlation between achieving energy self-balance in the process and the moisture and carbon content of the sludge. Sludge 1, with a carbon content of 16.99 %, achieves energy self-balance at a moisture content of 60 %, while sludge 2, with a carbon content of 13.82 %, achieves energy self-balance at a moisture content of 50 %. Conversely, sludge 3, which contains a carbon content of 5.49 %, struggled to achieve self-balance even at 50 % moisture content. Despite the potential benefits of high-carbon sludge, the substantial investments required for the dryer and boiler diminish its economic attractiveness. Net present value (NPV) and internal rate of return (IRR) indicate that reducing moisture content and carbon content can enhance the process's economic efficiency. Results indicate that annual operating cost (AOC) predominantly drives economic indicator fluctuations with varying moisture content. In contrast, total capital cost (TCI) and annual depreciation cost (ADC) exert greater influence on economic indicators under changes in carbon content.
{"title":"Process simulation and techno-economic analysis of 400 t/d pilot plant for municipal sewage sludge drying and combustion","authors":"Kaibing Zhang , Aibing Yu , Xinhang He , Yuneng Tang , Zhiao Yu , Yunpeng Yu , Qingwen Wu , Baiqian Dai","doi":"10.1016/j.psep.2025.106833","DOIUrl":"10.1016/j.psep.2025.106833","url":null,"abstract":"<div><div>To achieve harmless treatment of sludge, the thermal conversion represented by combustion is considered the most promising treatment technology because it reduces sludge volume and recovers energy. This study develops a process of handling 400 tons of sludge per day by integrating sludge drying and combustion, and accompanied by energy analysis and economic evaluation. The proposed system provides the energy required for the drying process by recovering waste heat from the combustion section, thereby investigating the feasibility of achieving energy self-balance. The impact of variations in carbon and moisture content on the economic performance of the process by adjusting the moisture content of sludge with three different carbon levels has been explored. The findings indicate a strong correlation between achieving energy self-balance in the process and the moisture and carbon content of the sludge. Sludge 1, with a carbon content of 16.99 %, achieves energy self-balance at a moisture content of 60 %, while sludge 2, with a carbon content of 13.82 %, achieves energy self-balance at a moisture content of 50 %. Conversely, sludge 3, which contains a carbon content of 5.49 %, struggled to achieve self-balance even at 50 % moisture content. Despite the potential benefits of high-carbon sludge, the substantial investments required for the dryer and boiler diminish its economic attractiveness. Net present value (NPV) and internal rate of return (IRR) indicate that reducing moisture content and carbon content can enhance the process's economic efficiency. Results indicate that annual operating cost (AOC) predominantly drives economic indicator fluctuations with varying moisture content. In contrast, total capital cost (TCI) and annual depreciation cost (ADC) exert greater influence on economic indicators under changes in carbon content.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106833"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-05DOI: 10.1016/j.psep.2025.106853
Siqi Liu , Wenqi Bu , Xiangting Hou , Shixu Lu , Chengzhi Zhou , Xiaozhe Song , Qianwen Wang , Shuaishuai Xin , Guocheng Liu , Yanjun Xin , Qinghua Yan
Layered double hydroxides (LDHs) were prepared by co-precipitation method as precursors to obtain mixed metal oxides (LDOs) by high-temperature calcination. Ni1Mn1Fe1-LDO had a large specific surface area and abundant active sites, which was conducive to the generation of active species and the efficient removal of CIP. Based on the optimization of reaction parameters and response surface methodology (RSM), the optimal conditions for the removal of ciprofloxacin (CIP) were determined as follows: 0.2 g/L Ni1Mn1Fe1-LDO, 0.75 mM peroxymonosulfate (PMS), pH = 7, and the degradation rate of 10 mg/L CIP reached 99.82 % at 60 min. In addition, Ni1Mn1Fe1-LDO/PMS showed a certain resistance to the interference of organic compounds and common anions. The surface-bound SO4•– and O2•– played a dominant role in the degradation and mineralization of CIP in the system. The intermediates produced by CIP degradation were analyzed and identified by high performance liquid chromatography-mass spectrometry (HPLC/MS). Through the determination of biological toxicity and total organic carbon (TOC), CIP was effectively decomposed into low toxicity products after degradation by Ni1Mn1Fe1-LDO/PMS system and finally mineralized into carbon dioxide and water molecules. This work aimed to provide a reasonable design for the effective degradation of pollutants by heterogeneous catalysts.
{"title":"Insights into the enhanced removal of ciprofloxacin by Ni1Mn1Fe1-LDO activated peroxymonosulfate: Mechanism and application for antibiotic wastewater","authors":"Siqi Liu , Wenqi Bu , Xiangting Hou , Shixu Lu , Chengzhi Zhou , Xiaozhe Song , Qianwen Wang , Shuaishuai Xin , Guocheng Liu , Yanjun Xin , Qinghua Yan","doi":"10.1016/j.psep.2025.106853","DOIUrl":"10.1016/j.psep.2025.106853","url":null,"abstract":"<div><div>Layered double hydroxides (LDHs) were prepared by co-precipitation method as precursors to obtain mixed metal oxides (LDOs) by high-temperature calcination. Ni<sub>1</sub>Mn<sub>1</sub>Fe<sub>1</sub>-LDO had a large specific surface area and abundant active sites, which was conducive to the generation of active species and the efficient removal of CIP. Based on the optimization of reaction parameters and response surface methodology (RSM), the optimal conditions for the removal of ciprofloxacin (CIP) were determined as follows: 0.2 g/L Ni<sub>1</sub>Mn<sub>1</sub>Fe<sub>1</sub>-LDO, 0.75 mM peroxymonosulfate (PMS), pH = 7, and the degradation rate of 10 mg/L CIP reached 99.82 % at 60 min. In addition, Ni<sub>1</sub>Mn<sub>1</sub>Fe<sub>1</sub>-LDO/PMS showed a certain resistance to the interference of organic compounds and common anions. The surface-bound SO<sub>4</sub><sup>•–</sup> and O<sub>2</sub><sup>•–</sup> played a dominant role in the degradation and mineralization of CIP in the system. The intermediates produced by CIP degradation were analyzed and identified by high performance liquid chromatography-mass spectrometry (HPLC/MS). Through the determination of biological toxicity and total organic carbon (TOC), CIP was effectively decomposed into low toxicity products after degradation by Ni<sub>1</sub>Mn<sub>1</sub>Fe<sub>1</sub>-LDO/PMS system and finally mineralized into carbon dioxide and water molecules. This work aimed to provide a reasonable design for the effective degradation of pollutants by heterogeneous catalysts.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106853"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-05DOI: 10.1016/j.psep.2025.106861
Dandan Liu , Gang Fang , Yuchen Lin , Fan Wang , Zixiu Li , Chunge Dang
The production of polyvinyl chloride (PVC) via the calcium carbide process is one of the most important sources of anthropogenic mercury (Hg) in China. However, detailed information about the quantity and fate of Hg in the PVC production process is unavailable. In this study, the fate and transport of Hg in PVC production was quantified and determined via material flow analysis (MFA). In addition, the content and fate of Hg in deposits on the inner surface of converters and downstream pipelines were quantified. The results indicated that the average Hg output accounted for 89.29 % of annual Hg input and that 10.72 % of the Hg was “missing”. An average 80.77 % of the Hg input was discharged into the waste catalysts, pipeline sediments and waste activated carbon. The waste catalysts, pipeline sediments and waste activated carbon discharged from the PVC production process should be properly disposed as hazardous solid waste.
{"title":"Flow analysis and fate of mercury in Chinese polyvinyl chloride production","authors":"Dandan Liu , Gang Fang , Yuchen Lin , Fan Wang , Zixiu Li , Chunge Dang","doi":"10.1016/j.psep.2025.106861","DOIUrl":"10.1016/j.psep.2025.106861","url":null,"abstract":"<div><div>The production of polyvinyl chloride (PVC) via the calcium carbide process is one of the most important sources of anthropogenic mercury (Hg) in China. However, detailed information about the quantity and fate of Hg in the PVC production process is unavailable. In this study, the fate and transport of Hg in PVC production was quantified and determined via material flow analysis (MFA). In addition, the content and fate of Hg in deposits on the inner surface of converters and downstream pipelines were quantified. The results indicated that the average Hg output accounted for 89.29 % of annual Hg input and that 10.72 % of the Hg was “missing”. An average 80.77 % of the Hg input was discharged into the waste catalysts, pipeline sediments and waste activated carbon. The waste catalysts, pipeline sediments and waste activated carbon discharged from the PVC production process should be properly disposed as hazardous solid waste.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106861"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-05DOI: 10.1016/j.psep.2025.106871
Weiwei Guo , Yang Wang , Le Zhou , Mingwei Jia , Yi Liu
Lack of labeled samples and complexity of unit interactions pose significant challenges for effective anomaly detection in complex industrial processes. This work proposes an unsupervised anomaly detection framework, hierarchical strategy-based global-local graph contrastive learning (HS-GLGCL). First, a process topology graph is constructed based on prior knowledge and then enhanced by the technique of graph augmentation. The graph contrastive learning mechanism enables the model to learn intrinsic information from unlabeled samples. Local topological information is input into the model through structural coefficients to further accurately simulate information transmission between local variables amid complex unit interactions. When global topological information is found inadequately captured, isomorphic similarity is introduced to help the model obtain embeddings that can more accurately describe data distributions. Anomalies are detected and localized by setting a reconstruction error threshold. Additionally, reconstruction dissimilarity represented by Kullback-Leibler divergence is adopted to further confirm the model’s performance superiority and complete a thorough evaluation of the model’s reconstruction performance. The effectiveness of HS-GLGCL is validated in two case studies on data respectively from a sugar factory and a sour water treatment system.
{"title":"Graph contrastive learning of modeling global-local interactions under hierarchical strategy: Application in anomaly detection","authors":"Weiwei Guo , Yang Wang , Le Zhou , Mingwei Jia , Yi Liu","doi":"10.1016/j.psep.2025.106871","DOIUrl":"10.1016/j.psep.2025.106871","url":null,"abstract":"<div><div>Lack of labeled samples and complexity of unit interactions pose significant challenges for effective anomaly detection in complex industrial processes. This work proposes an unsupervised anomaly detection framework, hierarchical strategy-based global-local graph contrastive learning (HS-GLGCL). First, a process topology graph is constructed based on prior knowledge and then enhanced by the technique of graph augmentation. The graph contrastive learning mechanism enables the model to learn intrinsic information from unlabeled samples. Local topological information is input into the model through structural coefficients to further accurately simulate information transmission between local variables amid complex unit interactions. When global topological information is found inadequately captured, isomorphic similarity is introduced to help the model obtain embeddings that can more accurately describe data distributions. Anomalies are detected and localized by setting a reconstruction error threshold. Additionally, reconstruction dissimilarity represented by Kullback-Leibler divergence is adopted to further confirm the model’s performance superiority and complete a thorough evaluation of the model’s reconstruction performance. The effectiveness of HS-GLGCL is validated in two case studies on data respectively from a sugar factory and a sour water treatment system.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106871"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-05DOI: 10.1016/j.psep.2025.106868
Hairong Shen , Jieyi Wang , Mengke Li , Chenquan Ni , Hui Zhong , Zhiguo He
Using peroxymonosulfate (PMS) activation system employing inexpensive solid waste-based catalysts to degrade organic pollutants is a sustainable strategy. In this study, a catalyst derived from copper tailings (CT-BA5) was developed to efficiently activate PMS for aniline aerofloat (AAF) degradation. The micromorphology of copper tailings (CT) was transformed from blocky to porous and loose after the modification, exposing more active sites for PMS activation. The degradation rate constant (kobs) of AAF increased to 23.4 times of CT. The degradation efficiency of AAF by CT-BA5/PMS system was 98.79 % within 10 min. The results of XPS, ESR and DFT calculations demonstrated the important roles of Ca3Fe2Si3O12 and Ov as active sites in the reaction process, which enhanced the electron transfer rate and Fe(II)/Fe(III) valence cycle of the catalyst, thus promoting the generation of reactive oxygen species (ROS). 1O2 was the dominant ROS responsible for AAF degradation and preferentially attacked the P-N bond of AAF. Furthermore, the results of cycling experiments and actual flotation wastewater treatment showed CT-BA5 had excellent reusability and practical applicability. In conclusion, this study provides a solution for the development of solid waste-based environmental remediation materials and waste-to-energy treatment, which is expected to be widely used in practical wastewater treatment.
{"title":"Efficient aniline aerofloat degradation by oxygen vacancies-rich copper tailings/peroxymonosulfate system: Performance evaluation and active sites","authors":"Hairong Shen , Jieyi Wang , Mengke Li , Chenquan Ni , Hui Zhong , Zhiguo He","doi":"10.1016/j.psep.2025.106868","DOIUrl":"10.1016/j.psep.2025.106868","url":null,"abstract":"<div><div>Using peroxymonosulfate (PMS) activation system employing inexpensive solid waste-based catalysts to degrade organic pollutants is a sustainable strategy. In this study, a catalyst derived from copper tailings (CT-BA5) was developed to efficiently activate PMS for aniline aerofloat (AAF) degradation. The micromorphology of copper tailings (CT) was transformed from blocky to porous and loose after the modification, exposing more active sites for PMS activation. The degradation rate constant (<em>k</em><sub><em>obs</em></sub>) of AAF increased to 23.4 times of CT. The degradation efficiency of AAF by CT-BA5/PMS system was 98.79 % within 10 min. The results of XPS, ESR and DFT calculations demonstrated the important roles of Ca<sub>3</sub>Fe<sub>2</sub>Si<sub>3</sub>O<sub>12</sub> and Ov as active sites in the reaction process, which enhanced the electron transfer rate and Fe(II)/Fe(III) valence cycle of the catalyst, thus promoting the generation of reactive oxygen species (ROS). <sup>1</sup>O<sub>2</sub> was the dominant ROS responsible for AAF degradation and preferentially attacked the P-N bond of AAF. Furthermore, the results of cycling experiments and actual flotation wastewater treatment showed CT-BA5 had excellent reusability and practical applicability. In conclusion, this study provides a solution for the development of solid waste-based environmental remediation materials and waste-to-energy treatment, which is expected to be widely used in practical wastewater treatment.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"196 ","pages":"Article 106868"},"PeriodicalIF":6.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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