中国环境噪声污染防治现状及建议

分析了中国环境噪声污染防治状况及变化趋势,归纳总结了"十一五"以来环境噪声污染防治的重要举措。论述了环境噪声污染防治监督管理工作现状及面临的问题,并提出了相应的对策建议,为进一步做好环境噪声污染防治工作提供了支持。     

国内外环境噪声监测方法比较及启示

综合比较了中国、日本、欧盟、美国和澳大利亚等国家或地区的环境噪声监测与评价方法,分析了声环境质量监测法、噪声地图预测法和噪声源监测法3种环境噪声评估方法的优缺点,认为声环境质量监测法适合现阶段中国环境噪声监测与管理需求,但下一步应结合噪声产生与传播预测方法改进中国声环境监测评价方法,增强对监测过程的质控,增加重点噪声源监测,以期更全面地反映城市声环境质量状况。     

道路交通噪声自动监测系统初探

环境噪声监测自动化是环境噪声监测发展的必然趋势。该文探讨了道路交通噪声自动监测系统的组成以及在相应的环保宣传方面的应用。     

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.     

兰州大学校园环境噪声的测量与分析

通过对兰州大学校园环境噪声的监测,分析了兰州大学校校园环境噪声环境状况,并对校内和校外周边环境噪声进行了对比分析,结果表明,兰州大学校园外部环境噪声大于校园内部,校内东部和西部环境噪声较南部和北部大,校外西部和北部环境噪声较东部和南部大。     

城区环境噪声污染图编制方法探讨

城市区域环境噪声污染图传统上是以实测数据用不同的颜色或花纹表示不同声级编制的平面图 ,较客观的反映了城区噪声污染状况 ,但图形生硬。现采用滑动加权平均法对原始数据进行处理 ,编制环境噪声污染等值线图 ,能较好地反映区域内整体环境噪声污染状况 ,图面直观。     

环境噪声监测中应注意的问题

结合工作实践,提出环境噪声监测中应注意的问题,供参考。1　环境噪声监测环境噪声一般指功能区噪声、区域环境噪声和交通噪声。中山市环境噪声功能区共划分为4类(1类区、2类区、3类区和4类区),每类布点2个,每季度监测1次。该市为国家环保模范城市,布点网格数>200。监测时间为昼6:00～22:00,夜22:00～6:00。监测仪器均采用AWA6218A、B两种型号噪声仪。监测时尽量使用同型号仪器,以避免产生误差。环境噪声监测技术要点见表1。表1　环境噪声监测技术要点项目名称功能区噪声交通噪声区域环境噪声布点原则各选择具有代表性的2个以上的长期…     

兰州交通大学校园噪声的监测与评价

对兰州交通大学校园环境噪声进行了实地监测,分析了兰州交通大学校园内教学区和学生生活区的环境噪声污染状况,结果表明,兰州交通大学教学区和生活区的噪声值存在不同程度的超标,其中生活区夜间噪声值超标最为严重。最后针对监测中发现的问题提出了相应的对策.     

基于BP神经网络城市环境噪声预测及实证研究

城市噪声污染严重影响着人们的生活与工作,采用合适的方法对噪声污染进行评价并预测,进而提出有效的预防及治理措施是噪声污染防治的关键问题,文章利用灰色关联分析选取了影响环境噪声的主要因素,采用BP(Back propagation,BP)神经网络对北京市1994~2006年的环境噪声污染进行评价并预测,验证结果误差较小,说明基于灰色关联的BP神经网络能够有效地对城市环境噪声污染进行评价和预测。     

浅析《社会生活环境噪声排放标准》在社会生活噪声纠纷监测中的应用

介绍了《社会生活环境噪声排放标准》与以往的噪声排放标准的进步之处,仔细分析了《社会生活环境噪声排放标准》在社会生活噪声纠纷监测中的应用指导作用,指出了实际使用该标准进行噪声测量时遇到的一些问题,并提出了一些符合实际操作要求的对策措施。     

立交桥噪声等值线评价方法及软件开发

提出了应用极坐标网格法对立交桥周围噪声环境进行预测评价计算，并绘制立交桥噪声等声级线图的方法，同时介绍了在ＦＯＸＰＲＯ数据库环境下开发的“立交桥噪声等值线计算软件”及其设计思想。     

噪声地图在环境噪声监测中的应用

以青岛理工大学新校区为例,采用变网格划分法,研究了基于地理信息系统(GIS)的噪声地图在区域环境噪声评价方面的应用。结果表明,噪声预测系统结合GIS,以数字与渲染图的方式能够直观地展现噪声污染在环境区域的分布状况,可用于指导区域的规划和环境噪声评价。     

A Method for Locating Influential Pollution Sources and Estimating Their Contributions

This work develops a source-oriented approach to locate the influential pollution sources and estimate their contributions to pollutant concentrations observed at a receptor site. The domain containing possible influential pollution sources is divided into systematic grid cells, and the influential grid sources are determined based on the locations of the segment endpoints of air trajectories arriving at the receptors. The contribution of each grid source is initially calculated using a formula derived from a Lagrangian box model and including the effects of source emissions, atmospheric dilution, and chemical transformation and deposition. The formula is described in detail in this study. Finally, the average contribution of each grid source is determined based on numerous analyzed events. The proposed approach was used to locate influential pollution sources and determine their contributions to a rural monitoring station during periods of high SO₂ pollution in southern Taiwan. The contributions of sources in various 2 km by 2 km grid cells, five districts, three source categories, 8 industrial areas, and a power plant were evaluated. The results show that the major influential sources were in the northwestern region of south Taiwan, and belonged to three district and point sources. Furthermore, two industrial areas close to the evaluated stations were also very significant, and contributed about 30% of the total pollution.     

风电机组噪声特性研究

以山东某平原风电场机组为例,对机组噪声进行仿真与测试研究.研究分析了风电机组噪声源频率特性、不同风速下的噪声声功率级及噪声的衰减特性,研究结果验证了Focus仿真软件在预测风电机组噪声源的可靠性.该研究为风电场噪声预测及降噪方案的研究提供了参考.     

北京典型区域声环境特征聚类分析

以北京西部某典型城市区域声环境为研究对象,在采集2010年该区域声环境质量历史监测数据的基础上,经完善声环境质量相关属性数据及定量化后,采用聚类分析方法对该研究区域声环境质量的网格样本进行统计分类研究。结果表明:研究区域分为3类较适宜,结合相关类别声环境网格空间中其他属性的定量特征,探讨了区域声环境质量影响的主控因素,提出了针对不同类别改善区域声环境质量的措施建议。     

基于可靠度的变压器声功率遗传算法研究

换流变压器是高压直流换流站中主要的噪声源,对换流变压器噪声的预测精度直接影响到后期整个换流站噪声预测模型的准确性,因此,准确获得换流变压器的声功率至关重要。根据《声学 户外声传播衰减 第2部分:一般计算方法》(ISO 9613-2:1996)中的户外声传播声功率计算方法,构建了声源声功率反推数学模型。利用某变压器周围大量测点现场实测数据,结合可靠度理论,识别并剔除了实测点中受相干声场影响较大的点,实现了换流变压器声功率反演计算,并对测点个数的选取进行了初步研究及优化。与其他声功率测量方法相比,该方法操作简单,对仪器设备要求较低,适用于复杂的声学环境,具有一定的应用前景。     

Objective approach for analysis of noise source characteristics and acoustic conditions in noisy computerized embroidery workrooms

It is highly important to analyze the acoustic properties of workrooms in order to identify best noise control measures from the standpoint of noise exposure limits. Due to the fact that sound pressure is dependent upon environments, it cannot be a suitable parameter for determining the share of workroom acoustic characteristics in producing noise pollution. This paper aims to empirically analyze noise source characteristics and acoustic properties of noisy embroidery workrooms based on special parameters. In this regard, reverberation time as the special room acoustic parameter in 30 workrooms was measured based on ISO 3382-2. Sound power quantity of embroidery machines was also determined based on ISO 9614-3. Multiple linear regression was employed for predicting reverberation time based on acoustic features of the workrooms using MATLAB software. The results showed that the measured reverberation times in most of the workrooms were approximately within the ranges recommended by ISO 11690-1. Similarity between reverberation time values calculated by the Sabine formula and measured values was relatively poor (R ²?=?0.39). This can be due to the inaccurate estimation of the acoustic influence of furniture and formula preconditions. Therefore, this value cannot be considered representative of an actual acoustic room. However, the prediction performance of the regression method with root mean square error (RMSE)?=?0.23 s and R ²?=?0.69 is relatively acceptable. Because the sound power of the embroidery machines was relatively high, these sources get the highest priority when it comes to applying noise controls. Finally, an objective approach for the determination of the share of workroom acoustic characteristics in producing noise could facilitate the identification of cost-effective noise controls.     

Decentralized control of units in smart grids for the support of renewable energy supply

Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced by a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10¹⁰⁰ feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets.