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Spectral-Based Machine Learning Enables Rapid and Large-Scale Adsorption Capacity Prediction of Heavy Metals in Soil 基于光谱的机器学习可快速、大规模预测土壤中重金属的吸附容量
IF 7.1 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-27 DOI: 10.1021/acsestengg.4c00325
Chongchong Qi, Tao Hu, Mengting Wu, Yong Sik Ok, Han Wang, Liyuan Chai, Zhang Lin
Accurate and large-scale estimation of the soil adsorption capacity of heavy metals (HMs) is vital to tackle soil HM contamination. Here, a novel framework has been developed to evaluate the adsorption capacity of HMs in soil using visible and near-infrared spectroscopy. Soil attributes were accurately estimated without any spectral preprocessing using a combined autoencoder (AE) and deep neural network (DNN) approach. Soil HM adsorption capability was then evaluated based on spectral-derived soil attributes, using 2,416 data points on Cd(II), Pb(II), and Cr(VI). The proposed AE-DNN models offer accurate estimations of soil attributes with an average R2 of 0.811 on the independent testing sets. The trained AE-DNN models can reveal patterns typically used by experts to identify bond assignments and promote data-driven knowledge discovery. By comparison with adsorption capacity maps based on actual and estimated soil attributes, we show that the spectral-based soil adsorption capacity evaluation is statistically reliable. Our adsorption capacity maps for the EU and USA identify known soil contamination sites and undocumented areas of high contamination risk. Our framework enables rapid and large-scale prediction of the adsorption capacity of HMs in soil and showcases important guidance for further soil contamination testing, soil management, and industrial planning.
准确、大规模地估算土壤对重金属(HMs)的吸附能力对于解决土壤重金属污染问题至关重要。在此,我们开发了一种新型框架,利用可见光和近红外光谱评估土壤中 HMs 的吸附能力。采用自动编码器(AE)和深度神经网络(DNN)相结合的方法,无需任何光谱预处理即可准确估算出土壤属性。然后,根据光谱得出的土壤属性,使用有关镉(II)、铅(II)和铬(VI)的 2,416 个数据点对土壤 HM 吸附能力进行了评估。所提出的 AE-DNN 模型能准确估计土壤属性,在独立测试集上的平均 R2 为 0.811。训练有素的 AE-DNN 模型可以揭示专家通常用于识别键分配的模式,促进数据驱动的知识发现。通过与基于实际土壤属性和估计土壤属性的吸附容量图进行比较,我们发现基于光谱的土壤吸附容量评估在统计学上是可靠的。我们为欧盟和美国绘制的吸附容量图识别了已知的土壤污染地点和未记录的高污染风险区域。我们的框架能够快速、大规模地预测土壤中 HMs 的吸附容量,并为进一步的土壤污染检测、土壤管理和工业规划提供重要指导。
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引用次数: 0
Low-Cost and Point-of-Use Sensing Device Based on 2D Diffusion-Controlled Colorimetric Sensing Array for Continuous and Multiplexed Air Pollution Monitoring 基于二维扩散控制比色传感阵列的低成本点用传感设备,用于连续和多重空气污染监测
IF 7.1 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-27 DOI: 10.1021/acsestengg.4c00416
Jingjing Yu, Wei Ding, Francis Tsow, Chinmay Chandrakant Dixit, Vishal Varun Tipparaju, Erica Forzani, Xiaojun Xian
The development of a low-cost and point-of-use sensing device capable of continuously and simultaneously detecting various air pollutants is essential for enhancing air pollution monitoring in communities and workplaces. This technology would enable real-time monitoring, facilitating prompt interventions to mitigate the impact of air pollution on human health and the environment. Colorimetric gas sensors are often used to detect different air pollutants owing to their high selectivity and sensitivity, low cost, and compact size. Nevertheless, continuous and multiplexed detection of gas with a colorimetric sensor often requires lifetime-extension methods and an expensive, space-demanding, and power-hungry optical imaging system as the signal transducer. To address these challenges, we introduce a fully integrated portable gas sensing device that uses cheap, miniaturized, and power-efficient electronic and sensing components. This device enables continuous and multiplexed monitoring of air pollutants through a two-dimensional (2D) diffusion-controlled colorimetric sensor array. By selecting sensing probes with specific colorimetric chemical reactions for different gas analytes, the 2D sensor array ensures specificity across a range of analytes. The test results demonstrate that our 2D diffusion-based colorimetric sensing device can be used for sensitive, selective, and multiplexed monitoring of different air pollutants (ammonia, carbon monoxide, carbon dioxide, and nitrogen dioxide) in a continuous manner. This device has proven effective in monitoring pollutants released from car exhaust. Our innovative chemical sensing approach has facilitated the creation of a compact, cost-effective, and easily deployable sensing device. This device offers continuous and multiplexed sensing capabilities, making it ideal for air pollution monitoring in communities and workplaces to provide evidence-based environmental data for effective air pollution management strategies.
开发一种能够连续、同时检测各种空气污染物的低成本点用传感设备,对于加强社区和工作场所的空气污染监测至关重要。这项技术将实现实时监测,便于及时采取干预措施,减轻空气污染对人类健康和环境的影响。比色气体传感器具有选择性高、灵敏度高、成本低、体积小等优点,通常用于检测不同的空气污染物。然而,使用比色传感器对气体进行连续和多路复用检测通常需要采用延长寿命的方法,以及昂贵、占用空间大且功耗高的光学成像系统作为信号转换器。为了应对这些挑战,我们推出了一种完全集成的便携式气体传感设备,该设备使用廉价、小型化和高能效的电子和传感元件。该设备通过二维(2D)扩散控制比色传感器阵列实现了对空气污染物的连续和多路复用监测。通过为不同的气体分析物选择具有特定比色化学反应的传感探针,二维传感器阵列确保了对一系列分析物的特异性。测试结果表明,我们基于二维扩散的比色传感装置可用于灵敏、选择性和多路复用地连续监测不同的空气污染物(氨、一氧化碳、二氧化碳和二氧化氮)。事实证明,该装置可有效监测汽车尾气中释放的污染物。我们创新的化学传感方法促进了一种结构紧凑、成本效益高且易于部署的传感装置的诞生。该装置具有连续和多路复用的传感能力,非常适合用于社区和工作场所的空气污染监测,为有效的空气污染管理策略提供基于证据的环境数据。
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引用次数: 0
Pipe Failure Prediction in the Water Distribution System Using a Deep Graph Convolutional Network and Temporal Failure Series 利用深度图卷积网络和时态故障序列预测输水系统中的管道故障
IF 7.1 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-27 DOI: 10.1021/acsestengg.4c00234
Yanran Xu, Zhen He
Ensuring the safety and reliability of the water distribution system (WDS) manifests significant importance for residential, commercial, and industrial needs and may benefit from the structure deterioration models for early warning of water pipe breaks. However, challenges exist in model calibration with limited monitoring data, unseen underground conditions, or high computing requirements. Herein, a novel deep learning-based DeeperGCN framework was proposed to predict pipe failure by cooperating with graph convolutional network (GCN) models for graph processing. The DeeperGCN model achieved much deeper architectures and was designed to utilize spatial and temporal data simultaneously. Two graph representation methods and three GCN models were compared, showing the best predictions with the “Pipe_as_Edge” method and the DeeperGEN model. To identify the priority of pipe maintenance directly, the prediction targets were assigned as a binary classification question to determine break or not over 1-, 3-, and 5-year periods, with prediction accuracies of 96.91, 96.73, and 97.23%, respectively. The issue of data imbalance was observed and addressed through varied evaluation metrics, resulting in the weighted F1 scores >0.96. The DeeperGCN framework demonstrated potential applications in visualizing pipe failure prediction with high accuracies of 97.09, 96.31, and 97.81% across three periods in 2015, for example.
确保配水系统(WDS)的安全性和可靠性对住宅、商业和工业需求具有重要意义,而结构劣化模型可用于水管破裂的早期预警。然而,在监测数据有限、地下条件不可见或计算要求高的情况下,模型校准存在挑战。本文提出了一种基于深度学习的新型 DeeperGCN 框架,通过与图卷积网络(GCN)模型合作进行图处理来预测管道故障。DeeperGCN 模型实现了更深层次的架构,旨在同时利用空间和时间数据。对两种图表示方法和三种 GCN 模型进行了比较,结果表明 "Pipe_as_Edge "方法和 DeeperGEN 模型的预测效果最佳。为了直接确定管道维护的优先级,预测目标被分配为一个二元分类问题,以确定在 1 年、3 年和 5 年期间是否断裂,预测准确率分别为 96.91%、96.73% 和 97.23%。通过不同的评估指标观察和解决了数据不平衡问题,加权 F1 分数为 0.96。DeeperGCN 框架在可视化管道故障预测方面展示了潜在的应用前景,例如在 2015 年的三个时段中,预测准确率分别高达 97.09%、96.31% 和 97.81%。
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引用次数: 0
Pipe Failure Prediction in the Water Distribution System Using a Deep Graph Convolutional Network and Temporal Failure Series 利用深度图卷积网络和时态故障序列预测输水系统中的管道故障
IF 7.4 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-27 DOI: 10.1021/acsestengg.4c0023410.1021/acsestengg.4c00234
Yanran Xu,  and , Zhen He*, 

Ensuring the safety and reliability of the water distribution system (WDS) manifests significant importance for residential, commercial, and industrial needs and may benefit from the structure deterioration models for early warning of water pipe breaks. However, challenges exist in model calibration with limited monitoring data, unseen underground conditions, or high computing requirements. Herein, a novel deep learning-based DeeperGCN framework was proposed to predict pipe failure by cooperating with graph convolutional network (GCN) models for graph processing. The DeeperGCN model achieved much deeper architectures and was designed to utilize spatial and temporal data simultaneously. Two graph representation methods and three GCN models were compared, showing the best predictions with the “Pipe_as_Edge” method and the DeeperGEN model. To identify the priority of pipe maintenance directly, the prediction targets were assigned as a binary classification question to determine break or not over 1-, 3-, and 5-year periods, with prediction accuracies of 96.91, 96.73, and 97.23%, respectively. The issue of data imbalance was observed and addressed through varied evaluation metrics, resulting in the weighted F1 scores >0.96. The DeeperGCN framework demonstrated potential applications in visualizing pipe failure prediction with high accuracies of 97.09, 96.31, and 97.81% across three periods in 2015, for example.

确保配水系统(WDS)的安全性和可靠性对住宅、商业和工业需求具有重要意义,而结构劣化模型可用于水管破裂的早期预警。然而,在监测数据有限、地下条件不可见或计算要求高的情况下,模型校准存在挑战。本文提出了一种基于深度学习的新型 DeeperGCN 框架,通过与图卷积网络(GCN)模型合作进行图处理来预测管道故障。DeeperGCN 模型实现了更深层次的架构,旨在同时利用空间和时间数据。对两种图表示方法和三种 GCN 模型进行了比较,结果表明 "Pipe_as_Edge "方法和 DeeperGEN 模型的预测效果最佳。为了直接确定管道维护的优先级,预测目标被分配为一个二元分类问题,以确定在 1 年、3 年和 5 年期间是否断裂,预测准确率分别为 96.91%、96.73% 和 97.23%。通过不同的评估指标观察和解决了数据不平衡问题,加权 F1 分数为 0.96。DeeperGCN 框架在可视化管道故障预测方面展示了潜在的应用前景,例如在 2015 年的三个时段中,预测准确率分别高达 97.09%、96.31% 和 97.81%。
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引用次数: 0
Acid Dosing Increases Recoverable Phosphorus during Different Occupancy Conditions in Full-Scale Urine Diversion System 在全规模尿液分流系统的不同占用条件下,加酸增加了可回收磷的含量
IF 7.4 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-21 DOI: 10.1021/acsestengg.4c0016410.1021/acsestengg.4c00164
Lucas Crane*, Daniella Saetta and Treavor H. Boyer*, 

Phosphorus (P) is a finite resource used in fertilizers. Urine contains high concentrations of P that can be recovered using urine diversion (UD), but current UD systems become clogged by P precipitation in piping, inhibiting their operations and reducing recoverable P. Dosing systems with acetic acid can prevent precipitation, resulting in more available nutrients for recovery. This study monitored a full-scale multistory UD system and implemented acid dosing to prevent clogging and produce urine suitable for P recovery. Both baseline (i.e., no acid) and acid dosing conditions were tested during normal and below-normal occupancies. In baseline systems, urine collected during below-normal occupancy had higher pH and greater nutrient losses compared to during normal occupancy. However, during both occupancies, baseline systems had clogs that decoupled occupancy patterns from urine collection in the tank and lowered the mass of recoverable P. During both occupancies, acid dosing dissolved pre-existing precipitate, resulting in ∼10× greater recoverable P than in baseline systems, and partially stabilized urine (>10%) and lowered pH (<9) until ∼7 days of operation, suggesting that urine can be immediately treated once the storage tank is full. The results demonstrate that acid dosing can prevent operation challenges in UD, improving UD’s technology readiness.

磷(P)是肥料中使用的一种有限资源。尿液中含有高浓度的磷,可通过尿液分流(UD)进行回收,但目前的 UD 系统会因管道中的磷沉淀而堵塞,从而影响其运行并减少可回收的磷。本研究监测了一个全规模的多层 UD 系统,并实施了加酸措施,以防止堵塞并产生适合回收 P 的尿液。在正常占用和低于正常占用期间,对基线(即不加酸)和加酸条件进行了测试。在基线系统中,与正常占用期间相比,低于正常占用期间收集的尿液 pH 值更高,养分损失也更大。然而,在这两种情况下,基线系统都会出现堵塞,从而使储水罐的占用模式与尿液收集脱钩,并降低了可回收磷的质量。在这两种情况下,加酸都能溶解预先存在的沉淀物,从而使可回收磷的质量比基线系统高出 10 倍,并能部分稳定尿液(10%)和降低 pH 值(9),直至运行 7 天,这表明一旦储水罐满了,就可以立即对尿液进行处理。研究结果表明,加酸可以避免尿液处理系统的运行难题,从而提高尿液处理系统的技术就绪程度。
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引用次数: 0
Acid Dosing Increases Recoverable Phosphorus during Different Occupancy Conditions in Full-Scale Urine Diversion System 在全规模尿液分流系统的不同占用条件下,加酸增加了可回收磷的含量
IF 7.1 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-21 DOI: 10.1021/acsestengg.4c00164
Lucas Crane, Daniella Saetta, Treavor H. Boyer
Phosphorus (P) is a finite resource used in fertilizers. Urine contains high concentrations of P that can be recovered using urine diversion (UD), but current UD systems become clogged by P precipitation in piping, inhibiting their operations and reducing recoverable P. Dosing systems with acetic acid can prevent precipitation, resulting in more available nutrients for recovery. This study monitored a full-scale multistory UD system and implemented acid dosing to prevent clogging and produce urine suitable for P recovery. Both baseline (i.e., no acid) and acid dosing conditions were tested during normal and below-normal occupancies. In baseline systems, urine collected during below-normal occupancy had higher pH and greater nutrient losses compared to during normal occupancy. However, during both occupancies, baseline systems had clogs that decoupled occupancy patterns from urine collection in the tank and lowered the mass of recoverable P. During both occupancies, acid dosing dissolved pre-existing precipitate, resulting in ∼10× greater recoverable P than in baseline systems, and partially stabilized urine (>10%) and lowered pH (<9) until ∼7 days of operation, suggesting that urine can be immediately treated once the storage tank is full. The results demonstrate that acid dosing can prevent operation challenges in UD, improving UD’s technology readiness.
磷(P)是肥料中使用的一种有限资源。尿液中含有高浓度的磷,可通过尿液分流(UD)进行回收,但目前的 UD 系统会因管道中的磷沉淀而堵塞,从而影响其运行并减少可回收的磷。本研究监测了一个全规模的多层 UD 系统,并实施了加酸措施,以防止堵塞并产生适合回收 P 的尿液。在正常占用和低于正常占用期间,对基线(即不加酸)和加酸条件进行了测试。在基线系统中,与正常占用期间相比,低于正常占用期间收集的尿液 pH 值更高,养分损失也更大。然而,在这两种情况下,基线系统都会出现堵塞,从而使储水罐的占用模式与尿液收集脱钩,并降低了可回收磷的质量。在这两种情况下,加酸都能溶解预先存在的沉淀物,从而使可回收磷的质量比基线系统高出 10 倍,并能部分稳定尿液(10%)和降低 pH 值(9),直至运行 7 天,这表明一旦储水罐满了,就可以立即对尿液进行处理。研究结果表明,加酸可以避免尿液处理系统的运行难题,从而提高尿液处理系统的技术就绪程度。
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引用次数: 0
Co-valorization of Food Waste and CO2 to Produce Volatile Fatty Acids Using Liter-Scale Tubular Microbial Electrosynthesis Cells 利用升级管式微生物电合成电池将厨余垃圾和二氧化碳共价生成挥发性脂肪酸
IF 7.1 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-20 DOI: 10.1021/acsestengg.4c00218
Yanhong Bian, Aaron M. Leininger, Weilan Zhang, Yanna Liang, Zhiyong Jason Ren
This study presents the simultaneous conversion of food waste and CO2 into volatile fatty acids (VFAs) using a 6 L tubular microbial electrosynthesis cell (MES). The MES reactor uses a bioanode to convert food waste into current and CO2, while on the cathode, H2 is produced and subsequently consumed by cathode microbes for the conversion of CO2 to VFAs. The study reveals that system performance is impacted by organic loading, applied voltage, and flow rate, and optimal operational conditions achieve a VFA titer of 1763 mg/L with the Coulombic efficiency (CE) exceeding 90% at the anode, highlighting efficient electron recovery from food waste. Resistance analysis indicates that the cathode contributed most to system resistance, while microbial community analysis shows a synergy between fermentative and electroactive bacteria in the anode and dominant acetogens in the cathode, facilitating efficient electron recovery and VFA synthesis, respectively. The research underscores the tubular MES’s potential for sustainable food waste treatment and CO2 valorization into valuable VFAs, contributing to waste management and greenhouse gas mitigation strategies.
本研究介绍了利用 6 升管式微生物电合成池(MES)将食物垃圾和二氧化碳同时转化为挥发性脂肪酸(VFAs)的方法。MES 反应器使用生物阳极将食物垃圾转化为电流和 CO2,同时在阴极产生 H2,随后阴极微生物消耗 H2 将 CO2 转化为挥发性脂肪酸。研究表明,系统性能受有机负载、应用电压和流速的影响,最佳运行条件下的 VFA 滴度为 1763 毫克/升,阳极的库仑效率(CE)超过 90%,突出显示了从食物垃圾中回收电子的效率。阻力分析表明,阴极对系统阻力的影响最大,而微生物群落分析表明,阳极的发酵菌和电活性菌与阴极的优势醋酸菌之间存在协同作用,分别促进了高效电子回收和 VFA 合成。这项研究强调了管式 MES 在可持续食品废物处理和将二氧化碳转化为有价值的 VFA 方面的潜力,有助于废物管理和温室气体减排战略。
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引用次数: 0
Removal and Oxidation of Low Concentration tert-Butanol from Potable Water using Nonthermal Plasma Coupled with Metal Oxide Adsorption 利用非热等离子体和金属氧化物吸附技术去除和氧化饮用水中的低浓度叔丁醇
IF 7.4 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-20 DOI: 10.1021/acsestengg.4c0016610.1021/acsestengg.4c00166
Cristina E. Stere*, Maicon Delarmelina, Mbongiseni W. Dlamini, Sarayute Chansai, Philip R. Davies, Graham J. Hutchings, C. Richard A. Catlow* and Christopher Hardacre*, 

Taste and odor are crucial factors in evaluating the quality of drinking water for consumers. Geosmin is an example of a pollutant commonly found in potable water responsible for earthy and musty taste, and odor even at low concentrations. We have investigated the use of a hybrid two-step adsorption-mineralization process for low-level volatile organic compounds removal from potable water using dielectric barrier discharge over common metal oxides (MO). The system proposed is a proof of principle with tert-butanol (TBA) used as a model compound for geosmin removal/degradation during wastewater treatment when combined with an appropriate metal oxide adsorbent. Initial assessments of the adsorption properties of titania by density functional theory (DFT) calculations and experimental tests indicated that the adsorption of geosmin and TBA with water present results in only weak interactions between the sorbate and the metal oxide. In contrast, the DFT results show that alumina could be a suitable adsorbent for these tertiary alcohols and were reinforced by experimental studies. We find that while there is a competitive effect between the water and TBA adsorption from gaseous/liquid feed, the VOC can be removed, and the alumina will be regenerated by the reactive oxygen species (ROS) produced by a dielectric barrier discharge (DBD). The use of alumina in conjunction with NTP leads to efficient degradation of the adsorbate and the formation of oxygenated intermediates (formates, carbonates, and carboxylate-type species), which could then be mineralized for the regeneration of the adsorbent. A reaction mechanism has been proposed based on the in-situ infrared measurements and DFT calculations, while the removal of TBA with conventional heating is indicative of a gradual desorption process as a function of temperature rather than the destruction of the adsorbate. Furthermore, steady performance was observed after several adsorption–regeneration cycles, indicating no alteration of the adsorption properties of alumina during the NTP treatment and demonstrating the potential of the approach to be applied in the treatment of high throughput of water, without the challenges faced by the biocatalysts or formation of toxic byproducts.

味道和气味是评估消费者饮用水质量的关键因素。土臭素是饮用水中常见的一种污染物,即使浓度很低,也会产生泥土味和霉味以及异味。我们研究了在普通金属氧化物(MO)上使用电介质阻挡放电的两步吸附-矿化混合工艺来去除饮用水中的低浓度挥发性有机化合物。提出的系统是一个原理验证,以叔丁醇(TBA)为模型化合物,与适当的金属氧化物吸附剂相结合,在废水处理过程中去除/降解地奥辛。通过密度泛函理论(DFT)计算和实验测试对二氧化钛的吸附特性进行的初步评估表明,地奥司明和叔丁醇与水的吸附只会导致吸附剂和金属氧化物之间产生微弱的相互作用。与此相反,DFT 结果表明,氧化铝可能是这些叔醇的合适吸附剂,实验研究也证实了这一点。我们发现,虽然气态/液态进料中的水和 TBA 吸附之间存在竞争效应,但挥发性有机化合物可以被去除,而且氧化铝会被介质阻挡放电(DBD)产生的活性氧(ROS)再生。将氧化铝与 NTP 结合使用,可有效降解吸附剂并形成含氧中间产物(甲酸盐、碳酸盐和羧酸盐类),然后将其矿化,用于吸附剂的再生。根据原位红外测量和 DFT 计算提出了一种反应机制,而传统加热法去除 TBA 的过程表明,这是一个随温度变化而逐渐解吸的过程,而不是吸附剂被破坏的过程。此外,经过几个吸附-再生周期后,观察到了稳定的性能,这表明氧化铝的吸附特性在 NTP 处理过程中没有发生改变,并证明了该方法在处理高吞吐量水方面的应用潜力,同时还避免了生物催化剂所面临的挑战或有毒副产品的形成。
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引用次数: 0
Removal and Oxidation of Low Concentration tert-Butanol from Potable Water using Nonthermal Plasma Coupled with Metal Oxide Adsorption 利用非热等离子体和金属氧化物吸附技术去除和氧化饮用水中的低浓度叔丁醇
IF 7.1 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-20 DOI: 10.1021/acsestengg.4c00166
Cristina E. Stere, Maicon Delarmelina, Mbongiseni W. Dlamini, Sarayute Chansai, Philip R. Davies, Graham J. Hutchings, C. Richard A. Catlow, Christopher Hardacre
Taste and odor are crucial factors in evaluating the quality of drinking water for consumers. Geosmin is an example of a pollutant commonly found in potable water responsible for earthy and musty taste, and odor even at low concentrations. We have investigated the use of a hybrid two-step adsorption-mineralization process for low-level volatile organic compounds removal from potable water using dielectric barrier discharge over common metal oxides (MO). The system proposed is a proof of principle with tert-butanol (TBA) used as a model compound for geosmin removal/degradation during wastewater treatment when combined with an appropriate metal oxide adsorbent. Initial assessments of the adsorption properties of titania by density functional theory (DFT) calculations and experimental tests indicated that the adsorption of geosmin and TBA with water present results in only weak interactions between the sorbate and the metal oxide. In contrast, the DFT results show that alumina could be a suitable adsorbent for these tertiary alcohols and were reinforced by experimental studies. We find that while there is a competitive effect between the water and TBA adsorption from gaseous/liquid feed, the VOC can be removed, and the alumina will be regenerated by the reactive oxygen species (ROS) produced by a dielectric barrier discharge (DBD). The use of alumina in conjunction with NTP leads to efficient degradation of the adsorbate and the formation of oxygenated intermediates (formates, carbonates, and carboxylate-type species), which could then be mineralized for the regeneration of the adsorbent. A reaction mechanism has been proposed based on the in-situ infrared measurements and DFT calculations, while the removal of TBA with conventional heating is indicative of a gradual desorption process as a function of temperature rather than the destruction of the adsorbate. Furthermore, steady performance was observed after several adsorption–regeneration cycles, indicating no alteration of the adsorption properties of alumina during the NTP treatment and demonstrating the potential of the approach to be applied in the treatment of high throughput of water, without the challenges faced by the biocatalysts or formation of toxic byproducts.
味道和气味是评估消费者饮用水质量的关键因素。土臭素是饮用水中常见的一种污染物,即使浓度很低,也会产生泥土味和霉味以及异味。我们研究了在普通金属氧化物(MO)上使用电介质阻挡放电的两步吸附-矿化混合工艺来去除饮用水中的低浓度挥发性有机化合物。提出的系统是一个原理验证,以叔丁醇(TBA)为模型化合物,与适当的金属氧化物吸附剂相结合,在废水处理过程中去除/降解地奥辛。通过密度泛函理论(DFT)计算和实验测试对二氧化钛的吸附特性进行的初步评估表明,地奥司明和叔丁醇与水的吸附只会导致吸附剂和金属氧化物之间产生微弱的相互作用。与此相反,DFT 结果表明,氧化铝可能是这些叔醇的合适吸附剂,实验研究也证实了这一点。我们发现,虽然气态/液态进料中的水和 TBA 吸附之间存在竞争效应,但挥发性有机化合物可以被去除,而且氧化铝会被介质阻挡放电(DBD)产生的活性氧(ROS)再生。将氧化铝与 NTP 结合使用,可有效降解吸附剂并形成含氧中间产物(甲酸盐、碳酸盐和羧酸盐类),然后将其矿化,用于吸附剂的再生。根据原位红外测量和 DFT 计算提出了一种反应机制,而传统加热法去除 TBA 的过程表明,这是一个随温度变化而逐渐解吸的过程,而不是吸附剂被破坏的过程。此外,经过几个吸附-再生周期后,观察到了稳定的性能,这表明氧化铝的吸附特性在 NTP 处理过程中没有发生改变,并证明了该方法在处理高吞吐量水方面的应用潜力,同时还避免了生物催化剂所面临的挑战或有毒副产品的形成。
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引用次数: 0
Co-valorization of Food Waste and CO2 to Produce Volatile Fatty Acids Using Liter-Scale Tubular Microbial Electrosynthesis Cells 利用升级管式微生物电合成电池将厨余垃圾和二氧化碳共价生成挥发性脂肪酸
IF 7.4 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2024-08-20 DOI: 10.1021/acsestengg.4c0021810.1021/acsestengg.4c00218
Yanhong Bian, Aaron M. Leininger, Weilan Zhang, Yanna Liang and Zhiyong Jason Ren*, 

This study presents the simultaneous conversion of food waste and CO2 into volatile fatty acids (VFAs) using a 6 L tubular microbial electrosynthesis cell (MES). The MES reactor uses a bioanode to convert food waste into current and CO2, while on the cathode, H2 is produced and subsequently consumed by cathode microbes for the conversion of CO2 to VFAs. The study reveals that system performance is impacted by organic loading, applied voltage, and flow rate, and optimal operational conditions achieve a VFA titer of 1763 mg/L with the Coulombic efficiency (CE) exceeding 90% at the anode, highlighting efficient electron recovery from food waste. Resistance analysis indicates that the cathode contributed most to system resistance, while microbial community analysis shows a synergy between fermentative and electroactive bacteria in the anode and dominant acetogens in the cathode, facilitating efficient electron recovery and VFA synthesis, respectively. The research underscores the tubular MES’s potential for sustainable food waste treatment and CO2 valorization into valuable VFAs, contributing to waste management and greenhouse gas mitigation strategies.

本研究介绍了利用 6 升管式微生物电合成池(MES)将食物垃圾和二氧化碳同时转化为挥发性脂肪酸(VFAs)的方法。MES 反应器使用生物阳极将食物垃圾转化为电流和 CO2,同时在阴极产生 H2,随后阴极微生物消耗 H2 将 CO2 转化为挥发性脂肪酸。研究表明,系统性能受有机负载、应用电压和流速的影响,最佳运行条件下的 VFA 滴度为 1763 毫克/升,阳极的库仑效率(CE)超过 90%,突出显示了从食物垃圾中回收电子的效率。阻力分析表明,阴极对系统阻力的影响最大,而微生物群落分析表明,阳极的发酵菌和电活性菌与阴极的优势醋酸菌之间存在协同作用,分别促进了高效电子回收和 VFA 合成。这项研究强调了管式 MES 在可持续食品废物处理和将二氧化碳转化为有价值的 VFA 方面的潜力,有助于废物管理和温室气体减排战略。
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ACS ES&T engineering
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