Ozone formation in California's San Joaquin Valley: a critical assessment of modeling and data needs

Data from the 1990 San Joaquin Valley Air Quality Study/Atmospheric Utility Signatures, Predictions, and Experiments (SJVAQS/AUSPEX) field program in California's San Joaquin Valley (SJV) suggest that both urban and rural areas would have difficulty meeting an 8-hr average O3 standard of 80 ppb. A conceptual model of O3 formation and accumulation in the SJV is formulated based on the chemical, meteorological, and tracer data from SJVAQS/AUSPEX. Two major phenomena appear to lead to high O3 concentrations in the SJV: (1) transport of O3 and precursors from upwind areas (primarily the San Francisco Bay Area, but also the Sacramento Valley) into the SJV, affecting the northern part of the valley, and (2) emissions of precursors, mixing, transport (including long-range transport), and atmospheric reactions within the SJV responsible for regional and urban-scale (e.g., down-wind of Fresno and Bakersfield) distributions of O3. Using this conceptual model, we then conduct a critical evaluation of the meteorological model and air quality model. Areas of model improvements and data needed to understand and properly simulate O3 formation in the SJV are highlighted.     

Automation design in advanced control rooms of the modernized nuclear power plants

This study evaluated the effects of levels of automation (LOAs) decisions in advanced control rooms of the modernized nuclear power plants. Following advancements in design of digitalized human–system interfaces (HSIs), the roles of human operators have changed significantly. Negative performance and safety consequences may occur as a result of these changes. These problems are viewed as the out-of-the-loop (OOTL) performance problems. This study conducted an experiment to compare the effects of different LOAs under different operating procedures on operating performance. Experimental results indicated that blended decision-making (level 6 LOA) generates the lowest mental workload. Furthermore, the pattern of SA observed in this study is found better SA at intermediate LOA and poorer SA at low level of automation and full automation. Subjective rating results suggest that LOAs distribute the roles of option generation, and selection between human and/or computer servers which significantly impacts automated system performance. This study provides a direction for the HSI designers in nuclear power plants (NPPs). Additionally, based on results obtained by this study, the user interfaces of PCTRAN system and the alarm reset system should be improved to ensure safe operation of NPPs.     

Numerical and experimental investigation of state of health of Li-ion battery

ABSTRACT

Estimation of State of Health (SoH) of Lithium-ion (Li-ion) battery is essential to predict the lifespan of batteries of an electric vehicle (EV). The efficient prediction of battery health indicates to the effective and safe operation of EV. However, delivering an effective and accurate method for the estimation of SoH in the real condition is truly a challenging task. The present study proposed a holistic procedure of combining both experimental and numerical investigations to conduct the fundamental study on coupled mechanical-electrochemical behavior of Li-ion battery. The proposed investigation highlighted the effect of stress on the capacity of the battery, considering capacity fade as an equivalent parameter to its health for real-time estimation of SoH. Finally, a simple model of Artificial Neural Network (ANN) is provided, which shows the linear dependency of stress with the SoH. The results obtained from the ANN model are validated with a Linear Regression (LR) model for a better understanding of the inspection. The predicted value of mean Square Error (MSE) and R square error in the ANN training model are found to be 0.000309 and 0.849687, respectively. Whereas for the test model, these predicted values are found to be 0.000438 and 0.819347, respectively.     

The Development of a Model to Examine Source-Receptor Relationships for Visibility on the Colorado Plateau

This paper describes the development and application of the Visibility and Haze in the Western Atmosphere (VISHWA) model to understand the source-receptor relationships that govern chemical species relevant to visibility degradation in the western United States. The model was developed as part of a project referred to as Visibility Assessment for Regional Emission Distributions (VARED), the objective of which is to estimate the contributions of various geographical regions, compounds, and emission

sources to light scattering and absorption by particles on the Colorado Plateau.

The VISHWA model is a modified version of a comprehensive Eulerian model, known as the Acid Deposition and Oxidant Model.1 The modifications were designed to obtain the computational efficiency required to simulate a one-year period at about 1/25th of real time, and at the same time incorporate mechanistic features relevant to realistic modeling of the fate and transport of visibility degrading species. The modifications included use of a condensed chemical mechanism; incorporation of reactions to simulate the formation of secondary organic particles; and use of a semi-Lagrangian advection scheme to preserve concentration peaks during advection.

The model was evaluated with 1992 air quality data from Project MOHAVE (Measurements of Haze and Visual Effects) intensive experiments. An important conclusion of this evaluation is that aqueous-phase oxidation of SO2 to sulfate in nonprecipitating clouds makes a significant contribution to observed sulfate levels during winter as well as summer. Model estimates of ambient sulfate

for the winter intensive were within a factor of 2 of the observations for 75% of the values. The corresponding statistic for the summer intensive was 90%. Model estimates of carbon were within a factor of 2 of the limited set of observations.     

Evaluation of Wind Fields Used in Grand Canyon Visibility Transport Commission Analyses

ABSTRACT

The Grand Canyon Visibility Transport Commission (GCVTC) was established by the U.S. Congress to assess the potential impacts of projected growth on atmospheric visibility at Grand Canyon National Park and to make recommendations to the U.S. Environmental Protection Agency on what measures could be taken to avoid such adverse impacts. A critical input to the assessment tool used by the commission was three-dimensional model-derived wind fields used to transport the emissions. This paper describes the evaluation of the wind fields used at various stages in the assessment. Wind fields evaluated included those obtained from the Colorado State University Regional Atmospheric Modeling System (RAMS), the National Meteorological Center's Nested Grid Model (NGM), and the National Oceanic and Atmospheric Administration's Atmospheric Transport and Dispersion (ATAD) trajectory model. The model-derived wind fields were evaluated at multiple vertical levels at several locations in the southwestern United States by determining differences between model predicted winds and winds that were measured using radiosonde and radar wind profiler data. Model-derived winds were also evaluated by determining the percent of time that they were within acceptable differences from measured winds.

All models had difficulties, generally meeting the acceptable criteria for less than 50% of the predictions. The RAMS model had a persistent bias toward southwesterly winds at the expense of other directions, especially failing to represent channeling by north-south mountain ranges in the lower levels. The NGM model exhibited a substantial bias in the summer months by extending northwesterly winds in the eastern Pacific Ocean well inland, in contrast to the observed southwesterlies at inland locations. The simpler ATAD trajectory model performed somewhat better than the other models, probably because of its use of more upper air sites. The results of the evaluation indicated that these wind fields could not be used to reliably predict source-receptor impacts on a particular day; thus, seasonally averaged impacts were used in the GCVTC assessment.     

新型自来水复合絮凝剂的研制与应用

研究用壳聚糖、聚铝和助剂A复合制备出一种成本低、絮凝效果好、出水Al3 含量少的新型自来水处理絮凝剂,并确定其最佳配比(体积比)为:0.1%壳聚糖:2%聚合氯化铝:0.1%助剂A=1:6:5.与传统聚铝类絮凝剂相比,其出水浊度和Al3 含量分别下降了2.97%和10.7%,并且药剂成本下降6.25%,有明显的经济和环境效益.     

Assessing team workload under automation based on a subjective performance measure

This study presents a subjective measure approach to assess how automation impacts teamwork. Hart and Staveland (1988) indicated that the subjective measure approach is the conventional most commonly used workload assessment method that represents the criteria against which other measures are evaluated. The subjective experience of an operating crew regarding workload normally involves the influence of many factors in addition to the objective demands imposed by a particular task. Therefore, this study first assumes that team workload is a hypothetical construct that represents the cost incurred by a specific crew to achieve a particular level of team performance. The concept of team workload is developed by applying individual workload concepts, principles, and relations to a team environment. Although teams are increasingly important in the workplace, team workload has seldom been evaluated in literature. Therefore, this study develops a subjective performance measure approach to optimize team workload. An illustrative example demonstrates the effectiveness of the proposed approach. Results of this study significantly contribute to research efforts in the field of workload measurement under automation.     

从循环经济视角看高职院校的专业长负责制

循环经济作为一种新的、科学的发展观,要求高等职业教育必须建立全新的适应循环经济发展的人才培养模式,在专业建设中凸显循环经济理念,用专业长负责制实现专业建设与社会需求的联通。以中国环境管理干部学院为例,以精品课建设为载体,从循环经济视角探讨了专业长负责制的推行,以及取得的成效。