Pub Date : 2026-02-09DOI: 10.1016/j.psep.2026.108582
Kyung Taek Heo, JunPyo Cho, Insu Lee, Hyeok Won Lee, Won-Dong Cho, Jaeho Jeong, Hwabong Jeong, Dongjun Park, Yunyeong Kim, Jiyoung Park, Kwang young Park, Hee Taek Kim, Seung Kyu Shin, Jung-Oh Ahn
Sterilizing exhaust gases in industrial fermentation, especially those using genetically modified microorganisms, poses significant biosafety challenges that require effective and cost-efficient solutions. This research methodically enhanced a dielectric barrier discharge (DBD) plasma system for treating fermentation exhaust. We developed three iterations: the first was a prototype that proved conceptually viable but exhibited limited flow capacity. The second version improved stability via electrode reconfiguration, although it faced airflow distribution limitations. The final model featured shortened electrodes, vertical alignment, thinner ceramics, and broader fluid pathways, resulting in enhanced discharge uniformity and power efficiency. The optimized system incorporated three modular reactors (90cm × 60cm × 150cm) alongside a condenser and wet scrubber for complete treatment. Testing with Escherichia coli, Corynebacterium glutamicum, and Saccharomyces cerevisiae achieved 100% sterilization efficiency over 8–24h of continuous operation at a flow rate of 3,000L/min, consuming only 0.8kW of power per module. This modular design provides operational flexibility, requires minimal maintenance, and ensures scalability across various fermentation sizes. We present both a viable industrial bioprocessing solution and foundational design guidelines for scaling plasma technologies, thereby enabling the sterilization of genetically modified microorganisms in line with increasingly stringent environmental regulations.
灭菌工业发酵废气，特别是那些使用转基因微生物，提出了重大的生物安全挑战，需要有效和具有成本效益的解决方案。本研究系统地改进了介质阻挡放电等离子体系统处理发酵废气。我们开发了三次迭代：第一次是一个原型，它在概念上是可行的，但显示出有限的流量。第二个版本通过电极重新配置提高了稳定性，尽管它面临气流分布的限制。最终型号的特点是缩短电极、垂直排列、更薄的陶瓷和更宽的流体通道，从而增强了放电均匀性和功率效率。优化后的系统包括三个模块化反应器（90cm × 60cm × 150cm）以及一个冷凝器和湿式洗涤器，用于完整的处理。以大肠杆菌、谷氨酸杆状杆菌、酿酒酵母为实验材料，在3000 l /min的流量下，连续运行8-24h，灭菌率达到100%，每个模块的功耗仅为0.8kW。这种模块化设计提供了操作灵活性，需要最少的维护，并确保了各种发酵规模的可扩展性。我们提出了可行的工业生物处理解决方案和缩放等离子体技术的基本设计指南，从而使转基因微生物的灭菌符合日益严格的环境法规。
{"title":"Dielectric barrier discharge plasma system for sterilizing exhaust gas from microbial fermentation processes","authors":"Kyung Taek Heo, JunPyo Cho, Insu Lee, Hyeok Won Lee, Won-Dong Cho, Jaeho Jeong, Hwabong Jeong, Dongjun Park, Yunyeong Kim, Jiyoung Park, Kwang young Park, Hee Taek Kim, Seung Kyu Shin, Jung-Oh Ahn","doi":"10.1016/j.psep.2026.108582","DOIUrl":"https://doi.org/10.1016/j.psep.2026.108582","url":null,"abstract":"Sterilizing exhaust gases in industrial fermentation, especially those using genetically modified microorganisms, poses significant biosafety challenges that require effective and cost-efficient solutions. This research methodically enhanced a dielectric barrier discharge (DBD) plasma system for treating fermentation exhaust. We developed three iterations: the first was a prototype that proved conceptually viable but exhibited limited flow capacity. The second version improved stability via electrode reconfiguration, although it faced airflow distribution limitations. The final model featured shortened electrodes, vertical alignment, thinner ceramics, and broader fluid pathways, resulting in enhanced discharge uniformity and power efficiency. The optimized system incorporated three modular reactors (90<ce:hsp sp=\"0.25\"></ce:hsp>cm × 60<ce:hsp sp=\"0.25\"></ce:hsp>cm × 150<ce:hsp sp=\"0.25\"></ce:hsp>cm) alongside a condenser and wet scrubber for complete treatment. Testing with <ce:italic>Escherichia coli</ce:italic>, <ce:italic>Corynebacterium glutamicum</ce:italic>, and <ce:italic>Saccharomyces cerevisiae</ce:italic> achieved 100% sterilization efficiency over 8–24<ce:hsp sp=\"0.25\"></ce:hsp>h of continuous operation at a flow rate of 3,000<ce:hsp sp=\"0.25\"></ce:hsp>L/min, consuming only 0.8<ce:hsp sp=\"0.25\"></ce:hsp>kW of power per module. This modular design provides operational flexibility, requires minimal maintenance, and ensures scalability across various fermentation sizes. We present both a viable industrial bioprocessing solution and foundational design guidelines for scaling plasma technologies, thereby enabling the sterilization of genetically modified microorganisms in line with increasingly stringent environmental regulations.","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"284 1","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146225","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 : 2026-02-09DOI: 10.1016/j.psep.2026.108586
Congcong Wu , Gaowei Wang , Tao Song , Tongqiang Xia , Yufei Niu , Feiqiang Guo , Peng Hou , Rabatuly Mukhammedrakhym
For the precise prediction of coal spontaneous combustion (CSC) temperature and effectively prevent coal mine fires, this study proposes a temperature prediction model integrating the Sparrow Search Algorithm (SSA) and Random Forest (RF). Firstly, the gas production characteristics during CSC were analyzed via coal temperature-programmed experiments, and the correlation intensity between temperature and indicator gases at each stage was quantified using the grey relational analysis method. Secondly, SSA was applied to optimize the hyperparameters of the RF model, thus constructing the SSA-RF CSC temperature prediction model. Under the same experimental conditions, the prediction performance of the proposed model was compared with that of five other models. In addition, the applicability of the model was verified using field data collected by the borehole bundle monitoring system. The results show that moisture content exerts a dual effect on the CSC process, an appropriate amount of moisture can promote CSC, while excessively high moisture content will inhibit this process. The mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2) of the SSA-RF model are 1.63 °C, 2.64 °C and 0.9974, respectively, indicating that its prediction accuracy is superior to that of the other five comparative models. Meanwhile, the results of feature importance evaluation of the SSA-RF model are highly consistent with those of the grey relational analysis, which verifies the reliability of the model in screening key indicators. Further verification with field data shows that the SSA-RF model still maintains high prediction accuracy, with MAE, RMSE and R2 values of 0.35 °C, 0.45 °C and 0.9898, respectively, demonstrating good engineering applicability.
{"title":"Prediction of coal spontaneous combustion temperature under variable moisture contents: A study based on the random forest model optimized by the sparrow search algorithm","authors":"Congcong Wu , Gaowei Wang , Tao Song , Tongqiang Xia , Yufei Niu , Feiqiang Guo , Peng Hou , Rabatuly Mukhammedrakhym","doi":"10.1016/j.psep.2026.108586","DOIUrl":"10.1016/j.psep.2026.108586","url":null,"abstract":"<div><div>For the precise prediction of coal spontaneous combustion (CSC) temperature and effectively prevent coal mine fires, this study proposes a temperature prediction model integrating the Sparrow Search Algorithm (SSA) and Random Forest (RF). Firstly, the gas production characteristics during CSC were analyzed via coal temperature-programmed experiments, and the correlation intensity between temperature and indicator gases at each stage was quantified using the grey relational analysis method. Secondly, SSA was applied to optimize the hyperparameters of the RF model, thus constructing the SSA-RF CSC temperature prediction model. Under the same experimental conditions, the prediction performance of the proposed model was compared with that of five other models. In addition, the applicability of the model was verified using field data collected by the borehole bundle monitoring system. The results show that moisture content exerts a dual effect on the CSC process, an appropriate amount of moisture can promote CSC, while excessively high moisture content will inhibit this process. The mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R<sup>2</sup>) of the SSA-RF model are 1.63 °C, 2.64 °C and 0.9974, respectively, indicating that its prediction accuracy is superior to that of the other five comparative models. Meanwhile, the results of feature importance evaluation of the SSA-RF model are highly consistent with those of the grey relational analysis, which verifies the reliability of the model in screening key indicators. Further verification with field data shows that the SSA-RF model still maintains high prediction accuracy, with MAE, RMSE and R<sup>2</sup> values of 0.35 °C, 0.45 °C and 0.9898, respectively, demonstrating good engineering applicability.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108586"},"PeriodicalIF":7.8,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146222","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}
This study aims to develop a sustainable multi-fuel strategy for diesel engines by examining the combustion, performance, and emission characteristics of industrial chicken-fat biodiesel (B100) enriched with 2-ethyl-1-hexanol (2-EH) and supplemented with ammonia (NH3) fumigation. The objective is to overcome limitations of neat biodiesel, such as high viscosity, low volatility, and incomplete combustion, while enhancing overall engine efficiency. Five test fuels (D100, B100, 2-EH5 %B100 +NH3 5lpm, 2-EH10 %B100 +NH3 5lpm, 2-EH15 %B100 +NH3 5lpm) were evaluated in a single-cylinder diesel engine operating at 1500 rpm under five brake-load conditions (0–100 %). Combustion parameters, performance metrics and emissions were measured. NH3 fumigation was supplied at 5 lpm using a controlled intake-manifold system. Combustion analysis demonstrated that B100 exhibited weaker premixed combustion than D100, as evidenced by lower in-cylinder pressure and heat-release rate (HRR) peaks. Under full load conditions, the blend 2-EH15 %B100 +NH3 5lpm achieved the greatest combustion, with in-cylinder pressure around 48.05 % higher than B100 and 3.22 % higher than D100. The maximum HRR was nearly 70 % greater than B100 and about 6.7 % higher than D100, indicating intensified premixed heat release near top dead centre. Brake thermal efficiency (BTE) increased by 14.8 % compared with B100 and 3.7 % over diesel, while brake specific energy consumption (BSEC) decreased by 28.7 % relative to B100. Significant emissions reductions in carbon monoxide (CO) by 37.5 %, hydrocarbon (HC) by 11.1 %, and smoke opacity by 35.3 % were observed compared with B100. However, oxides of nitrogen (NOx) emissions increased by 33.1 %, attributed to enhanced premixed combustion and higher in-cylinder temperatures. The synergistic combination of waste-derived biodiesel, higher alcohol, and NH3 fumigation enhances combustion phasing, improves thermal efficiency, and substantially lowers major pollutants except NOx. Although the strategy introduces a NOx penalty, it demonstrates strong potential for cleaner, more efficient diesel-engine operation and may be further optimized through future NOx mitigation technologies.
{"title":"Ammonia-assisted combustion of alcohol-enriched chicken fat biodiesel: Experimental investigation of a multi-fuel strategy in diesel engines","authors":"D. Premkumar , Ravikumar Jayabal , K.R. Padmavathi , Prajith Prabakar","doi":"10.1016/j.psep.2026.108577","DOIUrl":"10.1016/j.psep.2026.108577","url":null,"abstract":"<div><div>This study aims to develop a sustainable multi-fuel strategy for diesel engines by examining the combustion, performance, and emission characteristics of industrial chicken-fat biodiesel (B100) enriched with 2-ethyl-1-hexanol (2-EH) and supplemented with ammonia (NH<sub>3</sub>) fumigation. The objective is to overcome limitations of neat biodiesel, such as high viscosity, low volatility, and incomplete combustion, while enhancing overall engine efficiency. Five test fuels (D100, B100, 2-EH5 %B100 +NH<sub>3</sub> 5lpm, 2-EH10 %B100 +NH<sub>3</sub> 5lpm, 2-EH15 %B100 +NH<sub>3</sub> 5lpm) were evaluated in a single-cylinder diesel engine operating at 1500 rpm under five brake-load conditions (0–100 %). Combustion parameters, performance metrics and emissions were measured. NH<sub>3</sub> fumigation was supplied at 5 lpm using a controlled intake-manifold system. Combustion analysis demonstrated that B100 exhibited weaker premixed combustion than D100, as evidenced by lower in-cylinder pressure and heat-release rate (HRR) peaks. Under full load conditions, the blend 2-EH15 %B100 +NH<sub>3</sub> 5lpm achieved the greatest combustion, with in-cylinder pressure around 48.05 % higher than B100 and 3.22 % higher than D100. The maximum HRR was nearly 70 % greater than B100 and about 6.7 % higher than D100, indicating intensified premixed heat release near top dead centre. Brake thermal efficiency (BTE) increased by 14.8 % compared with B100 and 3.7 % over diesel, while brake specific energy consumption (BSEC) decreased by 28.7 % relative to B100. Significant emissions reductions in carbon monoxide (CO) by 37.5 %, hydrocarbon (HC) by 11.1 %, and smoke opacity by 35.3 % were observed compared with B100. However, oxides of nitrogen (NO<sub>x</sub>) emissions increased by 33.1 %, attributed to enhanced premixed combustion and higher in-cylinder temperatures. The synergistic combination of waste-derived biodiesel, higher alcohol, and NH<sub>3</sub> fumigation enhances combustion phasing, improves thermal efficiency, and substantially lowers major pollutants except NO<sub>x</sub>. Although the strategy introduces a NO<sub>x</sub> penalty, it demonstrates strong potential for cleaner, more efficient diesel-engine operation and may be further optimized through future NO<sub>x</sub> mitigation technologies.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108577"},"PeriodicalIF":7.8,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146265","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 : 2026-02-08DOI: 10.1016/j.psep.2026.108556
Van-Canh Nguyen , Ngoc-Linh Pham , The-Anh Cao , Nhat-Tan Nguyen , Nguyen Anh Thang , Nhu-Trang Le , Thuy-Duong Nguyen
This study proposes a hybrid data-driven framework for multi-objective optimization in finish milling of P20 tool steel molds, with focus on both process safety and environmental protection. The proposed framework combines Gaussian Process Regression (GPR) surrogate modeling, resampling-based data augmentation, and Bayesian multi-objective optimization to simultaneously minimize surface roughness (Ra, Rz) and specific cutting energy (SCE). The resampling-based data augmentation expanded the original experimental dataset (n = 16) to about six times, which significantly improve the accuracy and robustness of surrogate models. As a result, the GPR models achieved high prediction performance with R² values of 0.8680 for Ra, 0.9211 for Rz, and 0.9888 for SCE, while the corresponding MAPE values were 3.25 %, 4.45 %, and 14.73 %, respectively. In addition, Random Forest regression combined with SHAP analysis showed that cutting speed (Vc) is the most influential parameter for Ra prediction (43.4 % importance), whereas depth of cut (ap, 30.4 %) and width of cut (ae, 33.6 %) mainly control SCE, which provide useful guidance for parameter selection. Bayesian multi-objective optimization identified Pareto-optimal cutting conditions (Vc = 40 m/min, fz = 0.07–0.13 mm/tooth, ap = 0.5–2.0 mm, ae = 5.1–8.5 mm) that achieved fine surface quality (Ra = 0.55–0.65 µm) while reducing SCE by up to 92.4 % compared to baseline conditions. Experimental validation confirmed good predictive accuracy, with mean absolute errors below 5 % for surface roughness and about 7 % for energy consumption. For a typical P20 mold cavity with 500 cm³ material removal, the optimized parameters can save 0.099 kWh energy and reduce 0.056 kg CO₂ per part, leading to significant annual saving for industrial production. Process safety analysis also indicated that the optimized conditions maintain spindle load below 5 % of rated capacity, increase tool safety factor above 2.0–5.0, and reduce thermal load by 85–92 %, therefore reducing risks of tool failure, machine damage, and fire hazard. Overall, this study provides a practical and data-efficient optimization approach for sustainable and safe mold manufacturing.
{"title":"Data-driven multi-objective optimization for process-safe and sustainable finish milling of P20 tool steel","authors":"Van-Canh Nguyen , Ngoc-Linh Pham , The-Anh Cao , Nhat-Tan Nguyen , Nguyen Anh Thang , Nhu-Trang Le , Thuy-Duong Nguyen","doi":"10.1016/j.psep.2026.108556","DOIUrl":"10.1016/j.psep.2026.108556","url":null,"abstract":"<div><div>This study proposes a hybrid data-driven framework for multi-objective optimization in finish milling of P20 tool steel molds, with focus on both process safety and environmental protection. The proposed framework combines Gaussian Process Regression (GPR) surrogate modeling, resampling-based data augmentation, and Bayesian multi-objective optimization to simultaneously minimize surface roughness (R<sub>a</sub>, R<sub>z</sub>) and specific cutting energy (SCE). The resampling-based data augmentation expanded the original experimental dataset (n = 16) to about six times, which significantly improve the accuracy and robustness of surrogate models. As a result, the GPR models achieved high prediction performance with R² values of 0.8680 for R<sub>a</sub>, 0.9211 for R<sub>z</sub>, and 0.9888 for SCE, while the corresponding MAPE values were 3.25 %, 4.45 %, and 14.73 %, respectively. In addition, Random Forest regression combined with SHAP analysis showed that cutting speed (V<sub>c</sub>) is the most influential parameter for R<sub>a</sub> prediction (43.4 % importance), whereas depth of cut (a<sub>p</sub>, 30.4 %) and width of cut (a<sub>e</sub>, 33.6 %) mainly control SCE, which provide useful guidance for parameter selection. Bayesian multi-objective optimization identified Pareto-optimal cutting conditions (V<sub>c</sub> = 40 m/min, f<sub>z</sub> = 0.07–0.13 mm/tooth, a<sub>p</sub> = 0.5–2.0 mm, a<sub>e</sub> = 5.1–8.5 mm) that achieved fine surface quality (R<sub>a</sub> = 0.55–0.65 µm) while reducing SCE by up to 92.4 % compared to baseline conditions. Experimental validation confirmed good predictive accuracy, with mean absolute errors below 5 % for surface roughness and about 7 % for energy consumption. For a typical P20 mold cavity with 500 cm³ material removal, the optimized parameters can save 0.099 kWh energy and reduce 0.056 kg CO₂ per part, leading to significant annual saving for industrial production. Process safety analysis also indicated that the optimized conditions maintain spindle load below 5 % of rated capacity, increase tool safety factor above 2.0–5.0, and reduce thermal load by 85–92 %, therefore reducing risks of tool failure, machine damage, and fire hazard. Overall, this study provides a practical and data-efficient optimization approach for sustainable and safe mold manufacturing.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108556"},"PeriodicalIF":7.8,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138309","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}
Lithium-ion batteries have a significant safety risk of extensive fire and explosion accidents due to thermal runaway. One of the key issues of the recycling of end-of-life lithium-ion batteries is safe deactivation prior to the separation and recovery of the elements. This study aimed to improve the safety in the deactivation process of wastes of lithium-ion batteries by crushing in lime water under an inert atmosphere by investigating the reaction at the positive electrode. Especially, the solution conditions to generate O2 gas at the positive electrode were investigated to avoid hydrogen explosion caused by H2 gas generated at the negative electrode. The positive electrode retrieved from lithium-ion batteries was solely immersed in Li salt-added solutions. The generated gas was analysed by gas chromatography, and the shift of immersion potential was measured. The generation of O2 gas was accelerated and suppressed by the existence of Li+ cation and halide anions, respectively. The gas species was consistent with the immersion potential of the positive electrode. The behavior of waste of lithium-ion batteries during the deactivation by immersion in salt water is discussed. In addition, several reductants were added to the solution to utilize the function of sacrificial anode.
{"title":"Reaction at the positive electrode on Al foil of lithium-ion batteries in alkaline water and related reactions in the coexistence of halide ions","authors":"Kouji Yasuda, Ikuo Takemura, Ryota Domyo, Akihiro Kishimoto, Tetsuya Uda","doi":"10.1016/j.psep.2026.108551","DOIUrl":"10.1016/j.psep.2026.108551","url":null,"abstract":"<div><div>Lithium-ion batteries have a significant safety risk of extensive fire and explosion accidents due to thermal runaway. One of the key issues of the recycling of end-of-life lithium-ion batteries is safe deactivation prior to the separation and recovery of the elements. This study aimed to improve the safety in the deactivation process of wastes of lithium-ion batteries by crushing in lime water under an inert atmosphere by investigating the reaction at the positive electrode. Especially, the solution conditions to generate O<sub>2</sub> gas at the positive electrode were investigated to avoid hydrogen explosion caused by H<sub>2</sub> gas generated at the negative electrode. The positive electrode retrieved from lithium-ion batteries was solely immersed in Li salt-added solutions. The generated gas was analysed by gas chromatography, and the shift of immersion potential was measured. The generation of O<sub>2</sub> gas was accelerated and suppressed by the existence of Li<sup>+</sup> cation and halide anions, respectively. The gas species was consistent with the immersion potential of the positive electrode. The behavior of waste of lithium-ion batteries during the deactivation by immersion in salt water is discussed. In addition, several reductants were added to the solution to utilize the function of sacrificial anode.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108551"},"PeriodicalIF":7.8,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138310","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}
Large volumes of high-water-content waste slurry require efficient dewatering and resource utilization to achieve sustainable development. The recently proposed Binder-Pretreated Filtration Process (BPFP) addresses this need by enabling rapid dewatering and producing construction geomaterials; however, the pre-addition of binders causes hydration product loss during filtration, resulting in strength reduction, higher costs, and resource inefficiency. This study quantitatively evaluates the limitations and influencing factors of BPFP and proposes an optimized process with mechanistic insights. Results indicate that BPFP-treated filter cakes exhibit a 19 %–40 % strength reduction at 3 days and 7 %–18 % at 56 days, with short curing time, fast-hydrating binders, high initial water content, and extended pretreatment exacerbating these losses. To overcome these drawbacks, an Enhanced BPFP (EBPFP) was developed by incorporating small amounts of supplementary agents before binder pretreatment. Compared with BPFP, the optimal dosage of each supplementary agent in EBPFP achieved an additional 23 %–36 % strength gain, 11.15 %–20.26 % cost reduction, 17.22 %–20.18 % carbon emission reduction, and improved dewatering efficiency. Microstructural analysis revealed that BPFP-induced strength reduction is attributed to accelerated binder hydration in the high-water-content slurry environment, causing hydration product loss and increased porosity, whereas EBPFP suppresses early hydration, enhances C-S-H and AFt formation, and refines pore structure, thereby improving strength. Overall, this study deepens the understanding of binder behavior under slurry dewatering–solidification conditions and provides a cleaner production pathway for converting waste slurry into cost-effective, low-carbon construction geomaterials.
{"title":"Sustainable production of construction geomaterials from waste slurry through an optimized low-carbon dewatering–solidification process","authors":"Silin Wu , Shutong Dong , Wenwen Ding , Xiaohui Sun , Qi Zheng , Kaili Wu , Yongzheng Qi , Zhongping Chen","doi":"10.1016/j.psep.2026.108569","DOIUrl":"10.1016/j.psep.2026.108569","url":null,"abstract":"<div><div>Large volumes of high-water-content waste slurry require efficient dewatering and resource utilization to achieve sustainable development. The recently proposed Binder-Pretreated Filtration Process (BPFP) addresses this need by enabling rapid dewatering and producing construction geomaterials; however, the pre-addition of binders causes hydration product loss during filtration, resulting in strength reduction, higher costs, and resource inefficiency. This study quantitatively evaluates the limitations and influencing factors of BPFP and proposes an optimized process with mechanistic insights. Results indicate that BPFP-treated filter cakes exhibit a 19 %–40 % strength reduction at 3 days and 7 %–18 % at 56 days, with short curing time, fast-hydrating binders, high initial water content, and extended pretreatment exacerbating these losses. To overcome these drawbacks, an Enhanced BPFP (EBPFP) was developed by incorporating small amounts of supplementary agents before binder pretreatment. Compared with BPFP, the optimal dosage of each supplementary agent in EBPFP achieved an additional 23 %–36 % strength gain, 11.15 %–20.26 % cost reduction, 17.22 %–20.18 % carbon emission reduction, and improved dewatering efficiency. Microstructural analysis revealed that BPFP-induced strength reduction is attributed to accelerated binder hydration in the high-water-content slurry environment, causing hydration product loss and increased porosity, whereas EBPFP suppresses early hydration, enhances C-S-H and AFt formation, and refines pore structure, thereby improving strength. Overall, this study deepens the understanding of binder behavior under slurry dewatering–solidification conditions and provides a cleaner production pathway for converting waste slurry into cost-effective, low-carbon construction geomaterials.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108569"},"PeriodicalIF":7.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135193","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 : 2026-02-06DOI: 10.1016/j.psep.2026.108574
Jiaxuan Tang , Jialong Li , Luteng Zhang , Liangming Pan , Kian Jon Chua , Yongzheng Chen
In the event of a nuclear accident, radioactive iodine released into the environment can contaminate water sources, increasing total iodine levels and elevating thyroid disorder risks. Accurate quantification of iodine concentrations and species is crucial for environmental risk assessment. This study introduces a novel combined ICP-MS and UV-Vis method for high-precision measurement of gaseous iodine and sump water speciation. Conventional methods such as IC, ISE, and ICP-OES are limited in detecting ultra-low iodine concentrations in containment environments. While ICP-MS can achieve ppt-level detection, it is mainly suited for total iodine quantification and cannot resolve species due to plasma ionization. UV-Vis spectroscopy, on the other hand, takes advantage of distinct absorption peaks for different iodine species in the UV region, enabling accurate speciation quantification. By integrating these two techniques, this approach simultaneously provides quantitative total iodine measurement and speciation identification, overcoming the limitations of each individual method. Experimental results demonstrate that alkaline spray solutions can remove gaseous iodine effectively and lead to the formation of I2, I-, and I3- in sump water. ICP-MS enables precise quantification of trace gaseous iodine, with a relative error of + 1.71 % in repeatability tests and a recovery rate of 98.2 %-103.0 %. The measured iodine concentration (34.15 mg/L) closely matching the theoretical value (30.64 mg/L, 11.45 % deviation). Multi-wavelength UV-Vis analysis enables optimized speciation quantification, identifying characteristic absorption peaks at 226 nm (I-), 203 nm (I2), and 288 nm (I3-). The experimentally determined iodine distribution in sump water deviates by less than 15.5 % from theoretical estimates. The combined measurement approach supports improved monitoring capability and provides data relevant to risk control in containment environments.
{"title":"Assessment of iodine concentration and chemical speciation techniques for containment safety applications","authors":"Jiaxuan Tang , Jialong Li , Luteng Zhang , Liangming Pan , Kian Jon Chua , Yongzheng Chen","doi":"10.1016/j.psep.2026.108574","DOIUrl":"10.1016/j.psep.2026.108574","url":null,"abstract":"<div><div>In the event of a nuclear accident, radioactive iodine released into the environment can contaminate water sources, increasing total iodine levels and elevating thyroid disorder risks. Accurate quantification of iodine concentrations and species is crucial for environmental risk assessment. This study introduces a novel combined ICP-MS and UV-Vis method for high-precision measurement of gaseous iodine and sump water speciation. Conventional methods such as IC, ISE, and ICP-OES are limited in detecting ultra-low iodine concentrations in containment environments. While ICP-MS can achieve ppt-level detection, it is mainly suited for total iodine quantification and cannot resolve species due to plasma ionization. UV-Vis spectroscopy, on the other hand, takes advantage of distinct absorption peaks for different iodine species in the UV region, enabling accurate speciation quantification. By integrating these two techniques, this approach simultaneously provides quantitative total iodine measurement and speciation identification, overcoming the limitations of each individual method. Experimental results demonstrate that alkaline spray solutions can remove gaseous iodine effectively and lead to the formation of I<sub>2</sub>, I<sup>-</sup>, and I<sub>3</sub><sup>-</sup> in sump water. ICP-MS enables precise quantification of trace gaseous iodine, with a relative error of + 1.71 % in repeatability tests and a recovery rate of 98.2 %-103.0 %. The measured iodine concentration (34.15 mg/L) closely matching the theoretical value (30.64 mg/L, 11.45 % deviation). Multi-wavelength UV-Vis analysis enables optimized speciation quantification, identifying characteristic absorption peaks at 226 nm (I<sup>-</sup>), 203 nm (I<sub>2</sub>), and 288 nm (I<sub>3</sub><sup>-</sup>). The experimentally determined iodine distribution in sump water deviates by less than 15.5 % from theoretical estimates. The combined measurement approach supports improved monitoring capability and provides data relevant to risk control in containment environments.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108574"},"PeriodicalIF":7.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135194","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 : 2026-02-06DOI: 10.1016/j.psep.2026.108571
Jingyi Chi , Yanyun Zhao , Xiangming Hu , Xinlei Yang , Zhenglong He , Botao Qin
To address the issues of high-temperature evaporation, strong wind-induced shedding, and poor long-term adhesion to vertical substrates of fire-preventing gel materials in wildfires, this study developed a water-enhanced fire-preventing and extinguishing gel with “second-level gelation, strong adhesion, and long-term flame retardancy” using the high viscosity version of methyl hydroxyethyl cellulose (MHEC) and colloidal silica particles (CSP) as dual matrices, and introducing 3-aminopropyltriethoxysilane (APTES) and phytic acid (PA) to construct a Si-O-Si/P-Nsynergistic network. The optimal formulation (M1C1, MHEC: CSP=1:1) self-assembles in 0.4 min, with a static viscosity of 4.8 × 105 mPa・s and a viscosity of 4.1 × 104 mPa・s in the spray shear zone. When exposed to fire, it expands into closed-cell carbon-silica bubble walls within 0.5 min, providing 13 min of flame retardancy, and achieving a char residue rate > 40 %. M1C1A (modified with APTES) and M1C1AP (modified with APTES+PA) gel within 2 min, with viscosities reaching 315.0 % and 118.4 % of M1C1, respectively. TG-IR and Raman confirmed the “Si-O-Si + P-N carbon promotion” mechanism and “water retention-crack control-gas suppression-oxygen isolation” four-level protection chain; M1C1AP has an ID/IG ratio of 1.2. The gel exhibits shear-thinning properties, suitable for multiple scenarios, providing a solution for wildfire prevention and control.
{"title":"Design and performance of MHEC/CSP-based fire-preventing gel: Enhanced adhesion, water retention, and flame-retardant properties","authors":"Jingyi Chi , Yanyun Zhao , Xiangming Hu , Xinlei Yang , Zhenglong He , Botao Qin","doi":"10.1016/j.psep.2026.108571","DOIUrl":"10.1016/j.psep.2026.108571","url":null,"abstract":"<div><div>To address the issues of high-temperature evaporation, strong wind-induced shedding, and poor long-term adhesion to vertical substrates of fire-preventing gel materials in wildfires, this study developed a water-enhanced fire-preventing and extinguishing gel with “second-level gelation, strong adhesion, and long-term flame retardancy” using the high viscosity version of methyl hydroxyethyl cellulose (MHEC) and colloidal silica particles (CSP) as dual matrices, and introducing 3-aminopropyltriethoxysilane (APTES) and phytic acid (PA) to construct a Si-O-Si/P-Nsynergistic network. The optimal formulation (M<sub>1</sub>C<sub>1</sub>, MHEC: CSP=1:1) self-assembles in 0.4 min, with a static viscosity of 4.8 × 10<sup>5</sup> mPa・s and a viscosity of 4.1 × 10<sup>4</sup> mPa・s in the spray shear zone. When exposed to fire, it expands into closed-cell carbon-silica bubble walls within 0.5 min, providing 13 min of flame retardancy, and achieving a char residue rate > 40 %. M<sub>1</sub>C<sub>1</sub>A (modified with APTES) and M<sub>1</sub>C<sub>1</sub>AP (modified with APTES+PA) gel within 2 min, with viscosities reaching 315.0 % and 118.4 % of M<sub>1</sub>C<sub>1</sub>, respectively. TG-IR and Raman confirmed the “Si-O-Si + P-N carbon promotion” mechanism and “water retention-crack control-gas suppression-oxygen isolation” four-level protection chain; M<sub>1</sub>C<sub>1</sub>AP has an ID/IG ratio of 1.2. The gel exhibits shear-thinning properties, suitable for multiple scenarios, providing a solution for wildfire prevention and control.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108571"},"PeriodicalIF":7.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135195","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 : 2026-02-06DOI: 10.1016/j.psep.2026.108567
Yujun Huang , Yuhai Niu , Juan Zhang , Jinhai Liu , Zemin Wang , Sihan Chen , Zhimin Tian , Chengyu He , Yifan Xie , Shuming Liu
In traditional water treatment plants (WTPs), sludge discharge scheduling in sedimentation tanks often depends on qualitative human experience, lacking timely adjustments according to real-time operational conditions. This can lead to inappropriate and unstable solids content in discharged sludge, enhancing risks of water and energy waste or effluent water quality deterioration. Current research in online sludge discharge scheduling is limited due to inaccuracies in existing sludge status monitoring instruments, e.g., sludge level probes and concentration meters, and inadequate modeling of sludge production and distribution in sedimentation tanks. Here, we propose a novel scheduling framework for sludge discharge in WTP sedimentation tanks aiming to enhance the solids concentration of discharged sludge-water mixture without relying on specific sludge monitoring instruments, using only conventional water flow and quality meters instead. The framework predicts the expected initial solids content (ISC, %) through data-driven methods and models effluent solids content (ESC, %) based on sedimentation theory. The two steps help estimate the solids content and its variation of the discharged sludge-water mixture. The ISC prediction for the two sedimentation tanks achieves root mean squared error (RMSE) beneath 0.63 %, while the ESC prediction attains RMSE beneath 0.17 %. Integrating monitoring, simulation, prediction, and scheduling, our solution has the potential to stabilize effluent solids content at our case WTP. Moreover, under the scenario with a target average effluent solids content of 10 %, our solution can reduce 67 % of water consumption related with sludge discharge and energy consumption related with sludge dewatering at our case WTP.
{"title":"An online sludge discharge scheduling framework in water treatment plants integrating knowledge and data-driven approaches","authors":"Yujun Huang , Yuhai Niu , Juan Zhang , Jinhai Liu , Zemin Wang , Sihan Chen , Zhimin Tian , Chengyu He , Yifan Xie , Shuming Liu","doi":"10.1016/j.psep.2026.108567","DOIUrl":"10.1016/j.psep.2026.108567","url":null,"abstract":"<div><div>In traditional water treatment plants (WTPs), sludge discharge scheduling in sedimentation tanks often depends on qualitative human experience, lacking timely adjustments according to real-time operational conditions. This can lead to inappropriate and unstable solids content in discharged sludge, enhancing risks of water and energy waste or effluent water quality deterioration. Current research in online sludge discharge scheduling is limited due to inaccuracies in existing sludge status monitoring instruments, e.g., sludge level probes and concentration meters, and inadequate modeling of sludge production and distribution in sedimentation tanks. Here, we propose a novel scheduling framework for sludge discharge in WTP sedimentation tanks aiming to enhance the solids concentration of discharged sludge-water mixture without relying on specific sludge monitoring instruments, using only conventional water flow and quality meters instead. The framework predicts the expected initial solids content (ISC, %) through data-driven methods and models effluent solids content (ESC, %) based on sedimentation theory. The two steps help estimate the solids content and its variation of the discharged sludge-water mixture. The ISC prediction for the two sedimentation tanks achieves root mean squared error (RMSE) beneath 0.63 %, while the ESC prediction attains RMSE beneath 0.17 %. Integrating monitoring, simulation, prediction, and scheduling, our solution has the potential to stabilize effluent solids content at our case WTP. Moreover, under the scenario with a target average effluent solids content of 10 %, our solution can reduce 67 % of water consumption related with sludge discharge and energy consumption related with sludge dewatering at our case WTP.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108567"},"PeriodicalIF":7.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135200","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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