Warm glow from green power: Evidence from Australian electricity consumers

Green electricity products are increasingly made available to consumers in many countries in order to address a number of environmental and social concerns. Most of the literature on this green electricity market focuses on consumers’ characteristics and product attributes that could affect participation. However, the contribution of this environmental consumerism to the overall environmental good does not depend on participation alone. The real impact relies on market participation for green consumers (the proportion of green consumers) combined with the level of green consumption intensity – the commitment levels, or proportion of consumption that is green. We design an online interface that closely mimics the real market decision environment for electricity consumers in Western Australia and use an error component model to analyze consumers’ choice of green electricity products and their commitment levels. We show that product attributes have limited impact on the choice of green products; however, there is still great potential for better participation by improving the design of green electricity programs. When green products are selected, most respondents select the minimum commitment possible, and this is insensitive to the premium being charged on green power, suggesting that we are largely observing a buy-in ‘warm glow’ for carbon mitigation.     

The role of situation awareness in accidents of large-scale technological systems

In the last two decades, several serious accidents at large-scale technological systems that have had grave consequences, such as that at Bhopal, have primarily been attributed to human error. However, further investigations have revealed that humans are not the primary cause of these accidents, but have inherited the problems and difficulties of working with complex systems created by engineers. The operators have to comprehend malfunctions in real time, respond quickly, and make rapid decisions to return operational units to normal conditions, but under these circumstances, the mental workload of operators rises sharply, and a mental workload that is too high increases the rate of error. Therefore, cognivitive human features such as situation awareness (SA)—one of the most important prerequisite for decision-making—should be considered and analyzed appropriately. This paper applys the SA Error Taxonomy methodology to analyze the role of SA in three different accidents: (1) A runaway chemical reaction at Institute, West Virginia killing two employees, injuring eight people, and requiring the evacuation of more than 40,000 residents adjacent to the facility, (2) The ignition of a vapor cloud at Bellwood, Illinois that killed one person, injured two employees, and caused significant business interruption, and (3) An explosion at Ontario, California injuring four workers and caused extensive damage to the facility. In addition, the paper presents certain requirements for cognitive operator support system development and operator training under abnormal situations to promote operators’ SA in the process industry.     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.     

获取日均值的大气监测时段选择

利用数理统计方法，以污染物瞬时监测数据为基础数据，选用控制在一定置信度下最大允许误差的统计公式确定出样本容量，并采用模糊集合运算—优化组合选择法，确定出获取日均值的最佳监测时段．     

Kinetic and equilibrium isotherm studies for the adsorptive removal of Brilliant Green dye from aqueous solution by rice husk ash

The present study deals with the adsorption of Brilliant Green (BG) on rice husk ash (RHA). RHA is a solid waste obtained from the particulate collection equipment attached to the flue gas lines of rice husk fired boilers. Batch studies were performed to evaluate the influences of various experimental parameters like initial pH (pH0), contact time, adsorbent dose and initial concentration (C0) on the removal of BG. Optimum conditions for BG removal were found to be pH0 approximately 3.0, adsorbent dose approximately 6 g L(-1) of solution and equilibrium time approximately 5 h for the C0 range of 50-300 mg L(-1). Adsorption of BG followed pseudo-second-order kinetics. Intra-particle diffusion does not seem to control the BG removal process. Equilibrium isotherms for the adsorption of BG on RHA were analyzed by Freundlich, Langmuir, Redlich-Peterson (R-P), Dubnin-Radushkevich (D-R), and Temkin isotherm models using a non-linear regression technique. Langmuir and R-P isotherms were found to best represent the data for BG adsorption onto RHA. Adsorption of BG on RHA is favourably influenced by an increase in the temperature of the operation. Values of the change in entropy (DeltaS0) and heat of adsorption (DeltaH0) for BG adsorption on RHA were positive. The high negative value of change in Gibbs free energy (DeltaG0) indicates the feasible and spontaneous adsorption of BG on RHA.     

气相色谱分析中样品介质不同对分析结果的影响

分析了用甲醇、乙酸乙酯和二硫化碳3种不同极性的介质配制的4种苯系物样品，在不同极性的石英毛细柱、不同的分流比、宽口径石英毛细柱、宽口径玻璃毛细柱和玻璃填充柱上的测量结果。指出不同介质的有机化合物样品在气相色谱上分析时，色谱柱的极性(非极性、中等极性、强极性)、色谱柱类型(毛细柱、宽口径毛细柱、填充柱)、分流比的大小、进样方式(分流、不分流)都对数据的一致性产生影响，但采用不分流方式的宽口径毛细柱或填充柱分析可使分析结果具有一致性或更准确。     

自制快速移液器在溶解氧测定中的应用

本文介绍了一种用于溶解氧测定的自制快速移液器．大量实践证明，这种移液器的应用，可明显提高溶解氧测定结果的准确度和精密度，并可缩短样品分析时间．     

航空维修差错分析及其管理

航空维修差错是诱发或直接导致飞行事故最重要的原因之一 ,对维修差错进行分类和分析有助于航空安全。笔者在分析航空维修环境变化的基础上 ,基于Reason模型构建了维修差错分类与诱因分析的框架 ,并结合机务维修的实际情况 ,对框架所包括的不安全行为、不安全行为的先兆、不安全的管理及组织因素进行了初步编码。文章还简要论述了维修差错的管理技术 ,指出借助框架编制详细的差错分类与分析编码系统是发展的方向。     

最小点火能的影响因素及计算误差分析研究

对可燃气体 (液体蒸气 )、可燃粉尘的最小点火能测试中的影响因素进行了分析总结 ,并结合实验分析了求得最小点火能精确值所需要的环境条件和设备设施条件———敏感条件 ;分析了敏感条件下运用常规测试方法和常规计算公式中存在较大误差的原因 ,进而提出了相对准确合理的测试方法及计算公式———直接积分法及拟合近似积分法 ,从而大大降低了误差度 ,获得了比较符合实际的数据。     

Mapping of temperature and line-of-sight errors in constituent retrievals for MIPAS/ENVISAT measurements

An optimized code for the near real-time retrieval of line of sight, temperature and volume-mixing ratio profiles of five key species (O₃, H₂O, HNO₃, CH₄ and N₂O) from infrared limb spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) experiment on board the ENVISAT-1 satellite was developed as part of an ESA-supported study. In this code line of sight and temperature are retrieved simultaneously among themselves, but sequentially with respect to the volume-mixing ratio of the five key species. The sequential retrieval leaves unaccounted the mapping of line of sight and temperature errors in the retrieved volume-mixing ratio of the constituents. This paper illustrates an algorithm that provides the a-posteriori evaluation of temperature and line-of-sight-induced error on the retrieved volume-mixing ratio of the MIPAS key species. It is shown that in most cases temperature and line-of-sight-induced error provides a significant contribution to the total volume-mixing ratio error. The variability of this error as a function of latitude, season and atmospheric model is also analyzed.