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81.
高精度管道泄漏监测报警定位系统是基于管理中心平台上集成了次声波泄漏监测定位技术、最新的卫星定位技术和通讯技术为一体的管道泄漏监测系统.通过在孤东采油厂原油外输线的研发应用,能够准确的监测到原油管线泄漏点,为打击盗油行为,提供了有力保障.  相似文献   
82.
根据在海外钻井工程服务项目HSE管理中积累的经验,介绍了国外防翻架的安全标准及其设计、选材、制作和安装要求,为中国油田服务承包商进行轻型车辆防翻架制作提供了参考。  相似文献   
83.
Chemical composition of precipitation and its sources in Hangzhou, China   总被引:2,自引:0,他引:2  
To understand the origin and chemical characteristics of precipitation in Hangzhou, rainwater samples were collected from June 2006 to May 2008. All samples were analyzed for pH, electrical conductivity, and major ions (NH??, Ca2?, Mg2?, Na?, K?, SO?2?, NO??, F?, and Cl?). Acidification of precipitation in Hangzhou was serious with volume-weighted mean pH value of 4.5, while frequency of acid rain was 95%. The calculated SO?2?/NO?? ratio in Hangzhou precipitation was 2.87, which indicated that the precipitation of Hangzhou belonged to sulfate-based acid rain. The results of acid neutralization analysis showed that not all the acidity in the precipitation of Hangzhou was neutralized by alkaline constituents. The results of sea salt contribution analysis showed that nearly all SO?2?, Ca2?, and Mg2? and 33.7% of K? were of non-sea origins, while all Na? and Cl? and 66.3% of K? originated from sea sources. The principal component analysis which was used to analyze the sources of various ions indicated that chemical compositions of precipitation in Hangzhou mainly came from terrestrial sources, factory emissions, fuel wood burning, and marine sources.  相似文献   
84.
突发事件区域应急联动影响因素的实证研究   总被引:1,自引:0,他引:1  
吴晓涛  吴丽萍 《灾害学》2011,26(3):139-144
在界定突发事件区域应急联动内涵的基础上,采用Delphi法,识别出突发事件区域应急联动的9个主要影响因素,即应急联动组织机构、应急联动法律法规、应急物资协同调配、应急队伍协同调配、应急预案动态协同、应急信息实时沟通、区域地理位置、区域灾害特征和区域合作基础。同时,运用ISM技术,确定区域应急联动9个影响因素的关联性,计算和分解可达性矩阵,绘制4级递阶有向图,得出区域应急联动影响因素的内在层次性,即划分出"基础层"、"过渡层"和"直接层",为有效构建突发事件区域应急联动机制提供了理论支持与科学依据。  相似文献   
85.
Understanding the formation mechanisms of secondary air pollution is very important for the formulation of air pollution control countermeasures in China. Thus, a large-scale outdoor atmospheric simulation smog chamber was constructed at Chinese Research Academy of Environmental Sciences (the CRAES Chamber), which was designed for simulating the atmospheric photochemical processes under the conditions close to the real atmospheric environment. The chamber consisted of a 56-m3 fluorinated ethylene propylene (FEP) Teflon film reactor, an electrically-driven stainless steel alloy shield, an auxiliary system, and multiple detection instrumentations. By performing a series of characterization experiments, we obtained basic parameters of the CRAES chamber, such as the mixing ability, the background reactivity, and the wall loss rates of gaseous compounds (propene, NO, NO2, ozone) and aerosols (ammonium sulfate). Oxidation experiments were also performed to study the formation of ozone and secondary organic aerosol (SOA), including α-pinene ozonolysis, propene and 1,3,5-trimethylbenzene photooxidation. Temperature and seed effects on the vapor wall loss and SOA yields were obtained in this work: higher temperature and the presence of seed could reduce the vapor wall loss; SOA yield was found to depend inversely on temperature, and the presence of seed could increase SOA yield. The seed was suggested to be used in the chamber to reduce the interaction between the gas phase and chamber walls. The results above showed that the CRAES chamber was reliable and could meet the demands for investigating tropospheric chemistry.  相似文献   
86.
针对铝穹顶储罐雷击问题,开展了回击后长持续时间雷电流分量作用下的铝合金板烧蚀损伤试验研究,分析了铝穹顶储罐损伤及油气燃爆风险。结果表明:当直流分量为164 C时,2 mm铝板发生穿孔,铝穹顶储罐存在雷击燃爆风险;当直流分量≤157 C时,未穿孔,背面温度最高为480℃,存在燃爆风险,铝穹顶储罐存在雷击燃爆风险;当直流分量196 C时,4 mm铝板发生穿孔;当直流分量为196 C时,6 mm铝板未发生穿孔,背面温升为125℃,小于205℃,铝穹顶储罐不存在雷击燃爆风险。  相似文献   
87.
• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.  相似文献   
88.
Environmental Science and Pollution Research - Climate change affects the change of vegetation, and the analysis of vegetation change and its drivers in different globe climate zones is important...  相似文献   
89.
Environmental Science and Pollution Research - The increased growth of vegetation has the potential to slow global climate warming. Therefore, analyzing and predicting the response assessment of...  相似文献   
90.
Environmental Science and Pollution Research - The geometric structure of the suspended carrier is an important factor that directly affects the effluent quality of the moving bed biofilm reactor,...  相似文献   
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