Regeneration of AgXO@SBA-15 for reactive adsorptive desulfurization of fuel

Adsorbent regeneration is critical for a continuous adsorption–regeneration process and often underestimated. In this work,the regeneration of bifunctional AgXO@SBA-15 for [O]-induced reactive adsorptive desulfurization of liquid fuel is reported and further investigated. The spent AgXO@SBA-15 was regenerated in various types of solvents followed by calcination and tested in multiple desulfurization–regeneration cycles. The effects of regenerate solvents were also compared systematically. The original and regenerated AgXO@SBA-15 was characterized by X-ray diffraction, transmission electron microscopy, energy-dispersive X-ray spectroscopy, N_2 adsorption, X-ray photoelectron spectroscopy and atomic absorption spectrometry. The recovery of desulfurization capacity using various solvents follows the order of acetonitrile [ acetone [ ethanol [ methanol [ water. Owing to the complete reduction of silver species to Ag~0 and severe agglomeration of Ag~0, the bifunctional AgXO@SBA-15 demonstrating [ 85%(2.60 mg-S/g) of sulfur removal dramatically reduced to \ 46%(1.56 mg-S/g) after only 1 st-cycle regeneration. It is suggested that polar organic species strongly adsorbed(or residual) on the spent AgXO@SBA-15, in that case, after solvent wash may contribute to the accelerated decomposition of Ag~+ to Ag~0 in the following calcination step. The desulfurization capacity decreased rather mildly in the later regeneration runs. Cautious choice of regeneration conditions and strategies to rational design stabilized adsorbents is required to avert the adsorbent deactivation.     

基于整体性视角的社区更新：框架、模式与案例 — —以佛山桂华邨社区为例

现行的政府单一主导、政府与开发 商合作的社区更新模式与业主的自主更新需 求产生了矛盾。针对现有研究对社区更新的 系统性缺乏关注的问题，本文从整体视角出 发，通过构建“参与主体—程序设计—法规 政策—资金调配”四维框架，分析现行社区 更新模式与业主自主更新需求产生冲突的内 在机制。在优化现有模式的基础上，提出三 种适应业主自主更新需求的理论模式。桂华 邨业主自主更新失败的实践案例证明了本文 所提出的四维框架的重要性。最后，从政府 视角对我国社区更新机制提出优化建议。     

A comparative assessment of local municipal food policy integration in the Netherlands

ABSTRACT

Local governments around the world increasingly engage in food governance, aiming to address food system challenges such as obesity, food waste, or food insecurity. However, the extent to which municipalities have actually integrated food across their policies remains unknown. This study addresses this question by conducting a medium-n systematic content analysis of local food policy outputs of 31 Dutch municipalities. Policy outputs were coded for the food goals and instruments adopted by local governments. Our analysis shows that most municipalities integrate food to a limited extent only, predominantly addressing health and local food production or consumption. Furthermore, municipalities seem hesitant to use coercive instruments and predominantly employ informative and organizational instruments. Nonetheless, a small number of municipalities have developed more holistic approaches to address food challenges. These cities may prove to be a leading group in the development of system-based approaches in Dutch local food policy.     

Understanding the impact of High Speed Railway on urban innovation performance from the perspective of agglomeration externalities and network externalities

Transportation infrastructure and innovation play an important role in promoting regional economic growth. However, previous studies have mainly focused on the economic agglomeration by increased accessibility, but ignored the important on inter-city economic linkages and the network externalities it generated. Based on the externality perspective, this paper uses the propensity score matching model (PSM-DID) and spatial econometric model to analyze the heterogeneous impact of HSR opening on urban innovation performance and compare the differential effects of agglomeration externalities and network externalities on knowledge spillovers. The empirical results suggest the following: (1) The opening of HSR significantly improves urban innovation performance, but there is significant spatial heterogeneity. (2) The opening of HSR not only promotes the agglomeration of production factors to cities, but also strengthens inter-city economic connections, thus improving urban innovation performance through agglomeration externalities and network externalities. However, compared to agglomeration externalities, network externalities have a superior strength of impact on urban innovation performance. (3) From the dynamic effect perspective, the opening of HSR has a hysteresis effect on urban innovation of 2–3 years, and differences exist between cities.     

Soft sensing of water depth in combined sewers using LSTM neural networks with missing observations

Information and communication technologies combined with in-situ sensors are increasingly being used in the management of urban drainage systems. The large amount of data collected in these systems can be used to train a data-driven soft sensor, which can supplement the physical sensor. Artificial Neural Networks have long been used for time series forecasting given their ability to recognize patterns in the data. Long Short-Term Memory (LSTM) neural networks are equipped with memory gates to help them learn time dependencies in a data series and have been proven to outperform other type of networks in predicting water levels in urban drainage systems. When used for soft sensing, neural networks typically receive antecedent observations as input, as these are good predictors of the current value. However, the antecedent observations may be missing due to transmission errors or deemed anomalous due to errors that are not easily explained. This study quantifies and compares the predictive accuracy of LSTM networks in scenarios of limited or missing antecedent observations. We applied these scenarios to an 11-month observation series from a combined sewer overflow chamber in Copenhagen, Denmark. We observed that i) LSTM predictions generally displayed large variability across training runs, which may be reduced by improving the selection of hyperparameters (non-trainable parameters); ii) when the most recent observations were known, adding information on the past did not improve the prediction accuracy; iii) when gaps were introduced in the antecedent water depth observations, LSTM networks were capable of compensating for the missing information with the other available input features (time of the day and rainfall intensity); iv) LSTM networks trained without antecedent water depth observations yielded larger prediction errors, but still comparable with other scenarios and captured both dry and wet weather behaviors. Therefore, we concluded that LSTM neural network may be trained to act as soft sensors in urban drainage systems even when observations from the physical sensors are missing.     

Predicting pollutant removal in constructed wetlands using artificial neural networks(ANNs)

Growth in urban population,urbanisation,and economic development has increased the demand for water,especially in water-scarce regions.Therefore,sustainable approaches to water management are needed to cope with the effects of the urbanisation on the water environment.This study aimed to design novel configurations of tidal-flow vertical subsurface flow constructed wetlands(VFCWs) for treating urban stormwater.A series of laboratory experiments were conducted with semi-synthetic influent stormwater to examine the effects of the design and operation variables on the performance of the VFCWs and to identify optimal design and operational strategies,as well as maintenance requirements.The results show that the VFCWs can significantly reduce pollutants in urban stormwater,and that pollutant removal was related to specific VFCW designs.Models based on the artificial neural network(ANN) method were built using inputs derived from data exploratory techniques,such as analysis of variance(ANOVA) and principal component analysis(PCA).It was found that PCA reduced the dimensionality of input variables obtained from different experimental design conditions.The results show a satisfactory generalisation for predicting nitrogen and phosphorus removal with fewer variable inputs,indicating that monitoring costs and time can be reduced.     

化学工程废液处理及再生技术分析

对化工企业而言,在化学工程中进行废液处理和再生技术是其发展的必然趋势。化学工程废液处理及再生技术也是当下化学界科学家研究项目中的重中之重。本文将对化学工程废液处理及再生技术进行深入的分析。     

中国城市天然气消费驱动因素分析

为推动我国能源革命,培育天然气成为主体能源之一,有必要进一步研究我国天然气消费量的发展趋势,探寻影响天然气消费量的驱动因素。为此,采用迪氏对数指标分解法,构建城市天然气消费量分解模型,将驱动因素分解为空间扩张、管网密度、人口密度、人口城镇化、居民天然气气化率、能源消费弹性、天然气替代、经济增长和管道规模等9个效应,并定量分析各效应对我国城市天然气消费量变动的贡献率。研究结果表明:(1)各省天然气消费量驱动因素存在着较大的差异;(2)管道密度效应、管网规模效应、经济增长效应、居民天然气气化率效应、空间扩张效应、能源消费弹性效应能显著推动城市天然气消费量的增长,而人口密度和人口城镇化效应的影响则并不显著。进而根据分效应贡献率和市场特征,将中国30个省区市天然气市场划分为成熟型、培育型、经济发展型和资源约束型等4种类型,并分析了各类型市场天然气消费的核心驱动因素,以期为因地制宜开展天然气产业规划和政策制定提供决策依据。     

Forging furnace with thermochemical waste-heat recuperation by natural gas reforming: Fuel saving and heat balance

This paper considers thermochemical recuperation (TCR) of waste-heat using natural gas reforming by steam and combustion products. Combustion products contain steam (H₂O), carbon dioxide (CO₂), and ballast nitrogen (N₂). Because endothermic chemical reactions take place, methane steam-dry reforming creates new synthetic fuel that contains valuable combustion components: hydrogen (H₂), carbon monoxide (CO), and unreformed methane (CH₄). There are several advantages to performing TCR in the industrial furnaces: high energy efficiency, high regeneration rate (rate of waste-heat recovery), and low emission of greenhouse gases (CO₂, NO_x). As will be shown, the use of TCR is significantly increasing the efficiency of industrial furnaces – it has been observed that TCR is capable of reducing fuel consumption by nearly 25%. Additionally, increased energy efficiency has a beneficial effect on the environment as it leads to a reduction in greenhouse gas emissions.     

Impact of Lake Michigan water level rise on complex bidirectional flow in the Chicago Area Waterway System (CAWS)

In the past decade, continuously rising water levels in Lake Michigan have been threatening lakefront areas, especially in metropolitan regions like the Greater Chicago area. This provides the motivation to analyze the impact that high lake levels have on the Chicago Area Waterway System (CAWS). As the only primary free connection between the CAWS and Lake Michigan, the Calumet Area waterway subsystem plays a key and unique role. In this work, a numerical model covering the Calumet subsystem and having Lake Michigan as a boundary condition, is set up, calibrated, and validated using limited field observations. It is found that the Calumet subsystem has become bidirectional, where both discharge and flow directions are controlled by lake levels. When lake levels are below −0.15 m (-0.5 ft, Chicago City Datum, CCD), the discharge in the Grand Calumet River is around zero, with water flowing along its east branch towards Indiana. When lake levels are above +0.46 m (+1.5 ft, CCD), the flow reverses direction and drains west into Illinois. In 2020, the mean lake-level was at +1.07 m (+3.5 ft, CCD), and the base discharge in the Grand Calumet River was approximately 8.5 m³/s (300 ft³/s). The higher Lake Michigan’s level is, the larger the discharge would be into Illinois. Potential impact of this extra discharge on Lake Michigan Diversion Accounting (LMDA) of the State of Illinois and flood management in the Chicago Sanitary and Ship Canal (CSSC), is analyzed; while the nature of the bidirectional flows is characterized with the intent of shedding light on this complex phenomenon.