变电站电磁环境监测布点建模仿真研究

针对变电站电磁环境自动监测站布点方案普遍存在的效率不高、科学性不足等问题,以某500 kV变电站电磁环境自动监测站选址为例,通过建模仿真得到该变电站工频电场和工频磁场的空间分布,并实测验证了仿真结果的准确性。通过统计该变电站工频电场和工频磁场的空间分布特征,提出了基于变电站空间场强分布特征的自动监测站布点方案,建议优先在场强中位数分界线附近区域布点,以更好地反映变电站电磁环境。研究结果可指导变电站电磁环境自动监测站选址,提高变电站电磁环境监测布点的科学性,提升监测效率。     

北京城区地下变电站与民用建筑合建后的电磁环境影响分析

文章对北京城区桃园220kV地下变电站厂界和地上建筑的电磁环境现场监测数据进行了分析,结果表明地下变电站对地上建筑产生的电磁环境影响较小。     

环境电磁辐射的监测方法

电磁辐射对环境的影响主要包括工频电场、工频磁场、无线电干扰以及对环境产生的噪声。根据《辐射环境保护管理导则电磁辐射监测仪器和方法》（HJ／T10．2—1996），对宜宾110kV吊黄楼变电站进行电磁环境监测，将监测所得结果对照国家规定的限值，对电磁污染水平进行评价。通过仪器的选择，监测点位的确定以及执行标准等方面的内容，比较系统的介绍了现行电磁辐射的环境监测方法。     

2013—2021年新疆乌鲁木齐市电磁环境水平调查与分析

为了解新疆乌鲁木齐市电磁环境水平及影响,开展了电磁环境水平调查,以具有代表性的区域点位为调查对象,2013—2021年电磁环境监测结果表明,乌鲁木齐市射频综合电场强度整体呈现逐年增加的趋势,年平均值从2013年的0.54 V/m上升到了2021年的1.31 V/m,但所有监测点位测值均远低于《电磁环境控制限值》(GB ...     

重庆城市电网工频电磁环境现状及安全性分析

在现场实测的基础上,分析研究了重庆城市电网中各种电压等级、各种类型变电站周边环境,多种形式架空线路下方区域以及地下电缆周围工频电磁环境的现状,对比国家现行标准限值,评价重庆城市电网的工频电磁环境的安全性,同时也指出随着架空线密度的增加,周围工频电场不但不增加,反而有降低的现象.目前擅自在输电线路下建房或增加房屋高度是危及电磁环境安全的主要问题,应加大监管力度,减少日后不必要的环保纠纷.     

2 20 kV高压输电线电磁辐射水平及防护距离预测

依据<500 kV超高压送变电工程电磁辐射环境影响评价技术规范>(HJ/T 24-1998)中的预测模式对监测点周围地面1.5 m处工频电场进行了验证性监测,表明实际测定结果与理论计算结果基本吻合.通过对220 kV双回同相、双回逆相和单回线路下地面1.5 m、4.5 m、和7.5 m处工频电场变化趋势分析,预测了220 kV高压输电线产生的电磁辐射水平,以及不同房屋结构的防护距离.提出了220 kV高压输电线电磁辐射的防护措施.     

北京城区道路电磁环境监测及与人口热力关联分析

用电设备和无线通信服务的增长导致城市电磁环境水平逐渐升高,对人体健康和电子系统正常工作构成潜在威胁。于2021年对北京城区约407 km道路上的28 578个采样点进行电磁环境监测,89%的采样点电磁环境水平在3 V/m以内,但存在少量电磁环境水平高于12 V/m的采样点。结合进一步频谱分析发现,地理坐标为116.48°E、39.91°N附近路段电磁环境水平超出了《电磁环境控制限值》(GB 8702—2014)要求。此外,利用关联分析经典算法Apriori对电磁环境和人口热力的关联规则进行提取,结果表明,电磁环境水平较高的区域往往具有极高等级的人口热力,从而为电磁环境风险的快速判别提供参考。建议重点加强对人口热力极高区域的电磁环境监测,同时持续关注城市电磁环境变化趋势,以实现对电磁环境风险的及早预警和处理。     

江西省通信基站电磁环境现状调查分析

通过对江西省2012—2014年监测的4 781个具有代表性的通信基站电磁环境数据统计,从行政区域、城乡环境和发展趋势等角度分析江西省通信基站电磁环境质量与管理现状。结果表明,江西省通信基站电磁环境影响整体控制在较低水平,98.7%的通信基站周边电磁环境功率密度4.0×10-2W/m2,可同时也面临部分通信基站周边公众活动区域电磁环境强度较高、电磁环境整体水平快速增强、中心城区通信基站电磁环境管理困难等问题。     

以环境质量为核心构建电磁环境标准体系的建议

结合当前我国电磁环境管理的需求，分析了现有电磁环境标准的制定情况及存在的问题，提出以环境质量为核心，构建具有5个不同层次的电磁环境标准体系，包括电磁环境质量标准、电磁辐射排放（控制）标准、电磁环境监测标准、电磁环境基础标准和电磁环境管理技术规范。根据标准的定位、作用、特征及相互关系，提出了电磁环境标准制修订的相关建议。     

北京市中心商区射频电磁环境测试与分析

各类无线技术的发展和应用导致公众曝露于环境中的电磁场辐射的程度越来越高,由此引发的对人体健康风险的担忧促使诸多国家和组织开展了相关研究,并制定了电磁环境控制限值,电磁环境的空间分布也成为至关重要的基础数据。于2019年10—12月对北京市中心3个典型商区的电磁环境进行了测试,测试频段为10 MHz～8 GHz,属于射频范围。通过空间插值方法对测试数据进行处理,从而得到测试区域的射频电磁环境空间分布地图。对测试数据的进一步分析表明,测试区域的射频电磁环境水平主要分布在0.5～2.5 V/m,随空间距离变化较为剧烈,总体上符合《电磁环境控制限值》(GB 8702—2014)的要求。建议在城市发展过程中,对射频电磁环境进行持续、精细的监测。     

环境空气自动监测的质量保证问题探讨

简要介绍了江苏省环境空气自动监测系统的发展现状，结合环境空气自动监测站日常工作中的质控措施，重点就子站运行、中心站数据处理、人员岗位、管理制度4个方面论述了环境空气自动监测系统的管理和质量保证。     

不同布置方式220 kV变电所对周围环境的电磁辐射分布

通过对不同布置方式220 kV电压等级变电所在运行中对周围环境产生的工频电场、磁感应强度和无线电干扰的监测分析,了解了不同布置方式220 kV电压等级变电所对周围环境电磁辐射的分布规律.指出在建设220 kV电压等级变电所的同时,只要做好建筑屏蔽和电缆入地等工作,就可以降低对周围环境的电磁辐射影响.     

Exploring the trade-off between benefit and risk perception of NIMBY facility: A social cognitive theory model

With reference to Social Cognitive Theory, this study contributes to the debate on large-scale energy projects that can be classified as NIMBY developments and their implementation in order to better understand drivers to public acceptance. Public acceptance is essential for the development of typical NIMBY facilities. This study draws on Social Cognitive Theory (SCT) to investigate the determinants of public acceptance of a NIMBY facility in Wuhan City, China, to explore how the trade-off between the perceived benefit and risk affected public acceptance. Guanshan power substation was selected as the case study, and a questionnaire was presented to 450 local residents. Using a structural equation model, this study revealed that the perceived benefit-risk was positively related to public acceptance. Self-efficacy positively affected public acceptance via the perceived benefit-risk. Furthermore, the social environment exerted a significant positive effect on public acceptance, self-efficacy and perceived benefit-risk. These findings highlight the importance of improving the social environment and taking perceived benefit-risk into account during the decision-making process for similar developments.     

Radon, helium and uranium survey in some thermal springs located in NW Himalayas, India: mobilization by tectonic features or by geochemical barriers?

Radon, helium and uranium measurements have been carried out in hot water springs in the Parbati and Beas valleys of Himachal Himalaya. Most of these hot springs are known as famous pilgrimage centers. The activity of dissolved radon in the liquid phase is found to vary widely, by an order of magnitude, between 10 and 750 Bq L(-1), whereas, the dissolved helium content in these thermal springs varies between 10 and 100 ppm. The uranium contents are low and vary from <0.01 to 5 microg L(-1). The measured values of radon, helium and uranium are possibly controlled by structural geology, namely the presence of pervious fault systems, and by the lithology of the leached host rocks. Redox-potential geochemical barriers cause the mobilization of uranile ions in solution (UO2+); the most plausible hypothesis is when the conditions are oxidising, confirming the importance of physico-chemical conditions up to the supergenic environment, to control the fluid geochemistry of the U-He-222Rn system. Some evidence is available from both geothermometric considerations and geochemical data which will be reported elsewhere, whereas the present study is focused on U decay series-noble gas geochemistry. The first analysis of collected 3He/4He data is consistent with a crustal signature at the studied thermal springs.     

石油化工工业区区域废水中COD_（Cr）和COD_（Mn）的相关性研究

连续同时监测天津市大港石化发展规划区区域废水中的ＣＯＤＣｒ和ＣＯＤＭｎ，并考查其线性相关性后得出ＣＯＤＣｒ＝４．９６ＣＯＤＭｎ＋１１６．３，相关系数为０．７５０。该回归方程适用于类似石油化工工业区区域废水中ＣＯＤＣｒ和ＣＯＤＭｎ间的换算     

The use of spatial autocorrelation analysis to identify PAHs pollution hotspots at an industrially contaminated site

The identification of contamination “hotspots” are an important indicator of the degree of contamination in localized areas, which can contribute towards the re-sampling and remedial strategies used in the seriously contaminated areas. Accordingly, 114 surface samples, collected from an industrially contaminated site in northern China, were assessed for 16 polycyclic aromatic hydrocarbons (PAHs) and were analyzed using multivariate statistical and spatial autocorrelation techniques. The results showed that the PCA leads to a reduction in the initial dimension of the dataset to two components, dominated by Chr, Bbf&Bkf, Inp, Daa, Bgp, and Nap were good representations of the 16 original PAHs; Global Moran’s I statistics indicated that the significant autocorrelations were detected and the autocorrelation distances of six indicator PAHs were 750, 850, 1,200, 850, 750, and 1,200 m, respectively; there were visible high–high values (hotspots) clustered in the mid-bottom part of the site through the Local Moran’s I index analysis. Hotspot identification and spatial distribution results can play a key role in contaminated site investigation and management.     

淡水中叶绿素a测定方法的探讨

对分光光度法测定叶绿素a中样品研磨转移损失,离心后750nm处吸光值达不到0.005要求,加酸消除脱镁叶绿素,加酸量及加酸后测定时间等方面进行对比实验研究,提出了对分光光度法测定叶绿素a修改建议.     

Predictions of soil organic carbon using laboratory-based hyperspectral data in the northern Tianshan mountains, China

This paper presents a study dealing with soil organic carbon (SOC) estimation of soil through the combination of soil spectroscopy and multivariate stepwise linear regression. Soil samples were collected in the three sub-regions, dominated by brown calcic soil, in the northern Tianshan Mountains, China. Spectral measurements for all soil samples were performed in a controlled laboratory environment by a portable ASD FieldSpec FR spectrometer (350–2,500 nm). Twelve types of transformations were applied to the soil reflectance to remove the noise and to linearize the correlation between reflectance and SOC content. Based on the spectral reflectance and its derivatives, hyperspectral models can be built using correlation analysis and multivariable statistical methods. The results show that the main response range of soil organic carbon is between 400 and 750 nm. Correlation analysis indicated that SOC has stronger correlation with the second derivative than with the original reflectance and other transformations data. The two models developed with laboratory spectra gave good predictions of SOC, with root mean square error (RMSE) <5.0. The use of the full visible near-infrared spectral range gave better SOC predictions than using visible separately. The multivariate stepwise linear regression of second derivate model (model A) is optimal for estimating SOC content, with a determination coefficient of 0.894 and RMSE of 0.322. The results of this research study indicated that, for the grassland regions, combining soil spectroscopy and mathematical statistical methods does favor accurate prediction of SOC.