Property-performance relationship of core-shell structured black TiO2 photocatalyst for environmental remediation

● Properties and performance relationship of CSBT photocatalyst were investigated. ● Properties of CSBT were controlled by simply manipulating glycerol content. ● Performance was linked to semiconducting and physicochemical properties. ● CSBT (W:G ratio 9:1) had better performance with lower energy consumption. ● Phenols were reduced by 48.30% at a cost of $2.4127 per unit volume of effluent. Understanding the relationship between the properties and performance of black titanium dioxide with core-shell structure (CSBT) for environmental remediation is crucial for improving its prospects in practical applications. In this study, CSBT was synthesized using a glycerol-assisted sol-gel approach. The effect of different water-to-glycerol ratios (W:G = 1:0, 9:1, 2:1, and 1:1) on the semiconducting and physicochemical properties of CSBT was investigated. The effectiveness of CSBT in removing phenolic compounds (PHCs) from real agro-industrial wastewater was studied. The CSBT synthesized with a W:G ratio of 9:1 has optimized properties for enhanced removal of PHCs. It has a distinct core-shell structure and an appropriate amount of Ti³⁺ cations (11.18%), which play a crucial role in enhancing the performance of CSBT. When exposed to visible light, the CSBT performed better: 48.30% of PHCs were removed after 180 min, compared to only 21.95% for TiO₂ without core-shell structure. The CSBT consumed only 45.5235 kWh/m³ of electrical energy per order of magnitude and cost $2.4127 per unit volume of treated agro-industrial wastewater. Under the conditions tested, the CSBT demonstrated exceptional stability and reusability. The CSBT showed promising results in the treatment of phenols-containing agro-industrial wastewater.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

云南曲靖地区铜的暴露与肺癌相关性研究

我国云南省曲靖的宣威和富源等地是全世界肺癌高发区,为了研究环境介质中铜(Cu)等重金属的暴露与体内分布特征,探讨Cu与肺癌的相关性,在当地开展肺癌环境流行病学调查,采集宣威和富源高发区人群饮食、饮水以及人体血浆和肺组织样品,微波消解ICP-MS法测定样品中Cu等元素.结果显示,当地居民使用燃料类型是影响肺癌高发的重要因素.高发区人群Cu的日摄入总量低于我国推荐的每日膳食中营养素供给量(RDA).肺癌组血液中Cu含量显著高于对照组,肺癌组织中Cu含量显著高于癌旁组织和正常组织,且肺癌患者的血浆和肺组织中Cu/Zn比值均升高.Pearson相关性分析结果表明,Cu和Ni、Cu和Pb呈显著正相关,提示在致癌作用上具有协同效应;Cu和Fe、Cu和Zn呈显著负相关,提示具有抑制或拮抗作用.多因素Logistic回归结果表明,Cu是肺癌发生的重要影响因素,人体中Cu含量和Cu/Zn比值可为肺癌的早期预防和诊断提供科学依据.     

苯并(a)芘神经毒性研究进展

苯并(a)芘(BaP)是一种广泛存在于环境中的多环芳烃,具有致癌、致畸、致突变性。目前BaP的神经毒性研究零散而不深入,本文主要总结分析了BaP的神经毒性表现,简要介绍了BaP诱发神经毒性呈现的剂量-效应关系,进一步系统阐述了目前研究中发现的可能分子机制,包括BaP诱导神经递质及其代谢物含量的改变,相关DNA及蛋白质的损伤,抗氧化系统及线粒体的改变等,以期为进一步研究提供参考。     

沈阳市经济发展演变与碳排放效应研究

正确认识城市碳排放状况,研究确保城市经济快速发展的碳减排有效措施,对促进城市经济的可持续发展、制定各种环境经济政策、确保环境社会协调发展起到至关重要的作用。论文基于热红外遥感、GIS 和大气扩散模型技术,提高了城市碳排放空间分布的模拟精度。在此基础上,分别采用环境库兹涅茨曲线（EKC）、迪氏对数指标分解法（LMDI）和系统动力学（SD）模型,分析城市经济发展与碳排放之间的耦合关系和演变态势,通过碳排放分解分析研究影响碳排放浓度变化的因素,以及城市三次产业对碳排放的生产效应、结构效应和强度效应,模拟自然发展模式和调控发展模式两种情景下城市经济发展与碳排放的发展演变趋势。研究结果表明：1989—2008 年期间沈阳市碳排放与人均GDP拟合曲线符合N型特征,沈阳市的年均碳排放已经跨过了转折点。经济增长是导致沈阳碳排放增长的主要因素。1999—2010 年沈阳市第二产业碳排放的生产效应最大,三次产业的强度效应对城市碳排放都有抑制作用。2013—2020 年调控发展模式下的城市碳排放呈下降趋势。调控管理在保证经济稳步增长的同时将有利于沈阳市碳排放的有效抑制。     

Employee responses to employment‐relationship practices: The role of psychological empowerment and traditionality

In studying the effect of employment‐relationship practices on employees, research has largely ignored individual differences, both cross‐culturally and within cultures. In this study, the authors examine the moderating effect of middle managers' traditionality, a within‐culture value orientation regarding submission to authority and endorsement of hierarchical role relationships, on their responses to an organization's employee–organization relationship practices. Based on social learning and social exchange theories, the authors expect the more traditional middle managers to respond less positively in terms of their performance and commitment to high levels of expected contributions and the associated psychological empowerment but respond more positively to high levels of offered inducements. Using a sample of 535 middle managers from 40 companies in China, the authors find support for all hypotheses except the moderating effect of traditionality on the relationship between offered inducements and performance. Additional analysis reveals that less‐traditional managers responded to economic rewards (but not developmental rewards) with higher job performance. The paper concludes with a discussion of implications for research and the practice of employment relationships. Copyright © 2014 John Wiley & Sons, Ltd.     

ISM在事故原因层次分析中的应用

基于复杂系统结构特征的分析方法和模型,对事故原因进行分类,将事故的9类常见原因分为5类,通过事故原因之间的影响关系,可生成达成矩阵,从而明确了不同层次之间的关系,并对同一层要素之间的关系进行了关联分析,该项研究为事故预防提供了一个新途径,对提高企业的安全管理水平有一定的参考价值。     

城市生态系统承载理论探索与实证--以长江三角洲为例

为深入地探讨城市生态系统内部各要素的相互作用关系,将自然生态系统承载力理论扩展到城市生态系统,提出城市生态系统的承载机制概念。分别从微观作用与宏观表现两个角度提出承载机制模型,即承载递阶模型与水桶模型,初步构建了承载理论框架。在承载理论指导下,采用层次结构模型建立了承载机制评价指标体系,提出承载机制定量评估模型,由此可计算出城市生态系统承载指数,该指数是研究资源支持系统、环境约束系统与社会经济活动三者协调性以及城市生态环境对社会经济活动供容能力的重要判据。最后对长三角具有代表性的8个城市进行了实证研究。结果表明：长三角8个^城市的综合承载指数排序依次为：上海、南京、无锡、宁波、杭州、苏州、常州、扬州。     

西北少数民族地区人地关系演变动态仿真研究——以甘南州为例

文章立足于人地关系理论,利用系统动态模型方法,构建人地关系演变动态仿真模型,以甘南州为例,对西北少数民族地区人地系统演进规律进行仿真模拟研究,旨在描述该区人地关系演变过程中可能出现的情景,为该区协调人地关系走向可持续发展提供理论依据。模拟结果表明:甘南州人地关系处于失调状态,人地矛盾突出,表现出不可持续的态势。加快转变经济发展方式,降低经济增长对自然资源的依赖程度,可以有效延缓资源枯竭的速度,对人地系统向可持续发展演进具有积极的推动作用,是协调甘南州人地关系走向可持续发展的必然选择。加快技术进步和加大环保投资对协调甘南州人地关系具有显著的推进作用。严格控制人口数量,提高人口素质,才能有效协调人地关系。