基于DPSIRM框架的区域水资源承载力综合评价

综合考虑影响水资源系统的资源、生态、环境、经济、社会等因素,论文通过对水资源系统内在机理研究,构建基于驱动力-压力-状态-影响-响应-管理（DPSIRM）概念框架的水资源承载力DPSIRM评价指标体系,给出各子系统明确的含义,以反映系统内部各要素之间的关系。在此基础上,将模拟退火算法用于投影寻踪优化,构建耦合SA-PP模型。并将模型应用于2003—2012年云南省水资源承载力综合评价,并分析投影特征值的历年变化特征。研究结果表明：2003—2012年云南省水资源承载力呈逐步上升趋势,即在当前社会经济发展水平下,云南省水资源承载力逐步增强,社会经济发展的规模处于水资源可支撑的规模范围内。2006年以前,水资源承载力呈加速增长趋势,其增长潜力较大。2006年以后,水资源承载力波动幅度较大,而2009和2011年年增幅趋于零。最佳投影方向各分量的大小反映了各评价指标对水资源承载力的影响程度,值越大则对应的评价指标对水资源承载力的影响程度越大。对水资源承载力影响程度最大的5项指标依次为：生活污水排放量、“三废”治理投资、人均GDP、单位GDP水耗和森林覆盖率。压力子系统对水资源承载力影响比重为26.15%,表明压力子系统是影响云南省水资源承载力的最重要因子。研究表明此模型具有实用性,可为区域水资源规划与管理提供科学决策依据。     

Public perception of environmental issues across socioeconomic characteristics: A survey study inWujin,China

In developing countries, there is controversy over the correct perception regarding environmental and developmental issues. Few studies have examined the perception of low-income nationals in regards to social and environmental issues. This paper looks at the relationship between socio-demographic factors and the groups’ perceived priority regarding environmental and social issues in Wujin County. The results indicated that most residents, specifically the young, government employed and the urban community consider environmental issues to be serious, especially in relation to air pollution and water pollution. Furthermore, many residents feel it is important to rank environmental problems that are related to other social and economic issues, and that environmental protection must be set as a priority in Wujin County. Compared to social issues, environmental concern was greater among the young, government employed, and the urban community, because of their higher education and affluence. In addition, 66.2% of residents consider environmental protection to be more important than economic development. Thus, environmental protection must be set as a high priority in Wujin County, in order to face the many social and environmental challenges inherent in development.     

Perception of people for the risk of Tianwan nuclear power plant

A questionnaire survey of residents’ risk perceptions related to Taiwan nuclear power plant in China was carried out to explore the determining factors that affect individual risk perception. This study proposed to pursue a more comprehensive understanding of factors that affected individual risk perception to nuclear power plants. Covariance structure analysis was conducted using risk perceptions of nuclear power as dependent variable and including interest and knowledge levels of nuclear power, acceptability, benefit perception, trust in nuclear power operation, and trust in government as independent variables. The use of the hypothesis of Elaboration likelihood model (ELM) was also proposed. The results showed that persons with higher levels of interest and knowledge of nuclear power had their own perceptions of risk closely associated with acceptability and potential benefits of nuclear power. In contrast, persons with no interest in and knowledge of nuclear power would have risk perceptions related to their trust in nuclear operation and the government, which partially supported the ELM hypothesis. All these results indicated that the government in China plays an important role in rational risk perceptions, and well-designed communication of risks will help the public to be involved in risk management and improve people’s rational acceptance of risk.     

高精度管道泄漏监测报警定位系统应用

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.     

国外轻型车辆防翻架的设计与制作

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。     

Chemical composition of precipitation and its sources in Hangzhou, China

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.     

A large-scale outdoor atmospheric simulation smog chamber for studying atmospheric photochemical processes: Characterization and preliminary application

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.     

铝穹顶储罐雷击损伤及燃爆风险研究

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。     

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• 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.     

Spatiotemporal changes and driving factors of vegetation in 14 different climatic regions in the global from 1981 to 2018

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...