Bi/BiVO4/NiFe-LDH heterostructures with enhanced photoelectrochemical performance for streptomycin detection

Streptomycin (STR) plays an essential role in bacterial infection treatments. Selectivity and sensitivity of photoelectrochemical (PEC) sensors are the two most important parameters, which can be measured using the photosensitivity of its active material. We prepared a novel PEC sensor to detect STR using Bi/BiVO₄/LDH (layered double hydroxides) heterostructures as an active material, which is photoactive in the visible light wavelength range. The simultaneous presence of LDH and Bi/BiVO₄ enhanced the material photocurrent response, which was linear to the STR concentrations in the 0.01–500 nmol/L range. The STR detection limit by this sensor was 0.0042 nmol/L. Our novel PEC-based sensing strategy includes using an ultra-sensitive and highly selective sensor for STR detection. Additionally, the two-pot synthesis of Bi/BiVO₄/LDH developed in this work is environmentally friendly.     

压电石英传感器测定空气中氮氧化物

通过电化学活化和硅烷偶联剂在石英谐振器的金电极表面修饰对氮氧化物(NO_x)敏感的金属酞菁化合物,制成压电气体传感器.探讨了不同敏感材料对NO_x的响应灵敏度、检出限及载气流速、温度和干扰气体等对传感器的响应和回复特性的影响.结果表明:酞菁铅最敏感;其适宜的载气流速为40 mL/min,温度范围为10~40 ℃;在9.55×10_-4~1.91 mg/m₃质量浓度范围内,有良好的线性响应关系;用于大气中NO_x的测定,有较好的可靠性和准确性.使用寿命约300次.      

基于多模态感知的危险废物环境风险评估与预警研究

为了有效地防范化解危险废物的环境风险,亟须构建风险的精细化评估与实时智能预警系统。然而,危险废物特性复杂、全过程流转链条长,传统的单一感知数据并不能满足环境风险评估和预警的需求。因此,本文提出基于多模态感知的危险废物环境风险评估与预警方法,采用物联网、大数据、人工智能等技术手段,实现危险废物基础信息、环境要素、空间信息的多模态实时感知,并通过感知信息的融合、分析,进行准则判断或现象描述。围绕以上研究思路,本文针对危险废物贮存环节及非法倾倒两个重要风险因子释放情景,设计了基于多模态感知的风险评估与预警方法,以期为危险废物环境风险的管控提供相应的服务与决策。     

污水生化需氧量(BOD)的在线自动监测

采用由程序控制的自动采样器、自动稀释器和流动注射 微生物传感器组成的BOD在线自动监测仪 ,对污水BOD进行了在线自动监测。用该仪器监测配制标样和质控标样的结果具有良好的准确度和精密度。该仪器安装于污水处理厂出水口 ,连续运行 1 0d状态良好 ,且测定结果与标准稀释法测得的BOD5有良好的相关性     

基于IPSO-BP模型的火灾气体传感器气压补偿算法

为完善飞机火灾检测系统,设计一套方案,模拟试验不同气压下CO、CO2气体传感器采集气体的体积分数值,并与理论值比较,进而提出一种根据粒子适应度值动态调整学习因子的粒子群算法.采用改进的粒子群(IPSO)算法寻找反向传播(BP)神经网络的最优初始权值阈值,再利用寻优后的BP神经网络修正CO、CO2气体传感器的检测结果,消...     

Instream sensor results suggest soil–plant processes produce three distinct seasonal patterns of nitrate concentrations in the Ohio River Basin

The Ohio River Basin (ORB) is responsible for 35% of total nitrate loading to the Gulf of Mexico yet controls on nitrate timing require investigation. We used a set of submersible ultraviolet nitrate analyzers located at 13 stations across the ORB to examine nitrate loading and seasonality. Observed nitrate concentrations ranged from 0.3 to 2.8 mg L⁻¹ N in the Ohio River's mainstem. The Ohio River experiences a greater than fivefold increase in annual nitrate load from the upper basin to the river's junction with the Mississippi River (74–415 Gg year⁻¹). The nitrate load increase corresponds with the greater drainage area, a 50% increase in average annual nitrate concentration, and a shift in land cover across the drainage area from 5% cropland in the upper basin to 19% cropland at the Ohio River's junction with the Mississippi River. Time-series decomposition of nitrate concentration and nitrate load showed peaks centered in January and June for 85% of subbasin-year combinations and nitrate lows in summer and fall. Seasonal patterns of the terrestrial system, including winter dormancy, spring planting, and summer and fall growing-harvest seasons, are suggested to control nitrate timing in the Ohio River as opposed to controls by river discharge and internal cycling. The dormant season from December to March carries 51% of the ORB's nitrate load, and nitrate delivery is high across all subbasins analyzed, regardless of land cover. This season is characterized by soil nitrate leaching likely from mineralization of soil organic matter and release of legacy nitrogen. Nitrate experiences fast transit to the river owing to the ORB's mature karst geology in the south and tile drainage in the northwest. The planting season from April to June carries 26% of the ORB's nitrate and is a period of fertilizer delivery from upland corn and soybean agriculture to streams. The harvest season from July to November carries 22% of the ORB's nitrate and is a time of nitrate retention on the landscape. We discuss nutrient management in the ORB including fertilizer efficiency, cover crops, and nitrate retention using constructed measures.     

无线传感器网络在环境监测中的应用

介绍了一种基于无线传感器网络的环境监测系统组成及架构,讨论了系统网络节点、网关的硬件设计,并对基于TinyOS的应用程序组件结构和节点工作流程做了说明。     

浅析物联网技术在“蓝天保卫战”中的应用

大气污染防治工作事关民生和发展，打赢“蓝天保卫战”离不开物联网技术的应用。本文根据笔者对物联网技术的学习与理解，结合生活中观察引发的思考，以及相关文献资料检索，提出了自己对于物联网技术在“蓝天保卫战”中应用的构思。研究结果表明，运用物联网技术作为工具，构建大气污染的防控体系，国家层面与全民参与双管齐下，能够实现对污染要素的感知、监控和治理。物联网技术在控制大气污染方面有着非常好的前景，如果将物联网技术应用得当，能够对整个生态环境事业起到非常积极的作用。     

基于精细化管理的环境物联网发展趋势

环境物联网运用智能传感器等设备感知生态环境的变化,监测环境质量、监控企业的排污行为,通过环境数据的采集、传输、处理、整合,辅助环境管理决策。近年来环境物联网得到长足发展,但现有的环境物联网体系无法满足多种任务和应用场景的需求,主要问题体现在数据质量和精准度缺乏保证,数据传输能力有限,数据共享还未打通,数据分析应用能力还有待提升。笔者系统分析了环境物联网感知层、传输层和应用层的现状与问题,较全面地研究了物联网与大数据技术的最新进展,提出了环境物联网的发展方向以解决上述问题,为实现精细化管理与科学决策提供科学参考。     

基于厚膜传感器的空气质量监测仪性能及应用研究

介绍了一种基于厚膜传感器技术,可同时测量NO2、O3、CO三个因子的空气质量监测仪器。深入研究了仪器的检测原理,并对仪器的质量保证及数据存储传输进行了详细介绍。最后对仪器的检测性能进行了对比分析,通过和常规点式仪器的对比表明,该仪器NO2、O3、CO三因子的检测性能能够满足实际监测要求。另外,该仪器还具有集成性好、安装调试方便等特点,因此,在道路交通监测等领域中有广泛的应用前景。