基于CALPUFF模型的漳州市大气环境容量研究

研究表明：CALPUFF模式是运用于广域的大气扩散模型,在区域范围较大的复杂地形条件下的应用具有突出的优势.利用CALPUFF大气扩散模型模拟漳州市2009年气象场和污染物浓度场,采用监测值对模拟结果进行验证表明模型的适用性;基于现状污染源,建立大气污染物传递系数矩阵,结合线性优化法测算了不同环境空气质量标准下漳州市大气环境容量.     

Fe-Ce/GAC催化臭氧降解高浓度腐殖酸废水

采用浸渍焙烧法制备了Fe-Ce/GAC催化剂,并用于催化臭氧降解模拟高浓度腐殖酸废水.以废水COD、腐殖酸浓度为考察指标,研究了Fe-Ce/GAC催化剂的前驱体无机铁盐种类、焙烧温度、铁盐浓度、助剂稀土元素种类及浓度、分散剂硝酸钾浓度等不同制备条件对催化臭氧降解腐殖酸的效果.试验表明,在腐殖酸浓度为3.00 g·L~(-1)、pH值约8.0、温度为25℃、臭氧投量为1.24 g·h~(-1),反应40 min后COD、腐殖酸去除率仅为17.1%、43.0%;添加以2.0%硝酸铁、1.5%硝酸铈、1.0%硝酸钾溶液浸渍,经350℃焙烧3 h后制备的Fe-Ce/GAC催化剂,可使COD、腐殖酸去除率分别提高40.3%、31.8%.且Fe-Ce/GAC催化剂具有较好的稳定性,重复使用5次后,COD、腐殖酸去除率仅小幅降低了4.2%、9.1%.SEM图象显示活性炭经改性后,比表面积明显增大,有利于活性物质的负载;EDS分析表明催化剂负载了大量的Fe、Ce等金属物质;XRD图谱显示催化剂含有Fe_2O_3、CeO_2等多种活性物质.Fe-Ce/GAC催化臭氧的机理可解释为:活性成分氧化铁在催化过程中生成的羟基氧化铁会促进羟基自由基的生成,而铈元素在催化过程中不仅会提高催化剂的活性,而且生成的化学吸附氧可促进对有机物的吸附及氧化.     

Degradation of 2,4-dichlorophenoxyacetic acid in water by ozone-hydrogen peroxide process

IntroductionAt present, several types of organic pollutantsreferred to as environmental endocrine disruptors(ED) have been suggested to be associated withabnormal sexual development (Hu, 2000). It wasreported that the ED led to the decline of reproductive…     

基于等级全息建模的输油泵机组风险根源辨识*

为“挖掘”输油泵机组风险根源,降低设备预知性维护难度,结合输油泵多准则风险评价,提出1种基于等级全息建模的输油泵机组风险根源辨识方法,运用等级全息建模方法将输油泵系统分解为泵体结构、管理因素、环境因素、操作因素、技术因素、运行因素、设备安装7个子系统进行定性和定量分析。结果表明:相比危险与可操作性分析（HAZOP）、事故树分析（FTA）等传统风险辨识方法,等级全息建模（HHM）对轴承等关键部件以及压力等运行参数的监测更为深入,能够有效辨识输油泵机组高风险情景,提升输油泵的风险辨识效率。     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

An application of a modified theory of planned behavior model to investigate adolescents’ job safety knowledge,norms, attitude and intention to enact workplace safety and health skills

Introduction: For many reasons, including a lack of adequate safety training and education, U.S. adolescents experience a higher rate of job-related injury compared to adult workers. Widely used social-psychological theories in public health research and practice, such as the theory of planned behavior, may provide guidance for developing and evaluating school-based interventions to prepare adolescents for workplace hazards and risks. Method: Using a structural equation modeling approach, the current study explores whether a modified theory of planned behavior model provides insight on 1,748 eighth graders’ occupational safety and health (OSH) attitude, subjective norm, self-efficacy and behavioral intention, before and after receiving instruction on a free, national young worker safety and health curriculum. Reliability estimates for the measures were produced and direct and indirect associations between knowledge and other model constructs assessed. Results: Overall, the findings align with the theory of planned behavior. The structural equation model adequately fit the data; most path coefficients are statistically significant and knowledge has indirect effects on behavioral intention. Confirmatory factor analyses suggest that the knowledge, attitude, self-efficacy, and behavioral intention measures each reflect a unique dimension (reliability estimates ≥0.86), while the subjective norm measure did not perform adequately. Conclusion: The findings presented provide support for using behavioral theory (specifically a modified theory of planned behavior) to investigate adolescents’ knowledge, perceptions, and behavioral intention to engage in safe and healthful activities at work, an understanding of which may contribute to reducing the downstream burden of injury on this vulnerable population—the future workforce. Practical application: Health behavior theories, commonly used in the social and behavioral sciences, have utility and provide guidance for developing and evaluating OSH interventions, including those aimed at preventing injuries and promoting the health and safety of adolescent workers in the U.S., who are injured at higher rates than are adults.     

System safety assessment using safety entropy

Safety assessment has a primary role in hazardous operations. Most studies on safety assessment focus on risk and accident modeling, in which safety is absent. These top-down methods are highly dependent on the occurred accidents to establish accidental scenarios, which may make the assessment approach lagging behind the evolving modern systems. Moreover, this “special to general” logic is scientifically suspect in safety assessment. There is a call for the development of safety assessment methods in the presence of system safety to complement risk-focused safety analysis. These methods should provide a framework based on a bottom-up approach to examine system safety from the operational perspective. This paper has attempted to provide a potential solution. In particular, a novel concept of safety entropy is proposed to integrate with The Functional Resonance Analysis Method (FRAM), which is used to form the qualitative understanding of a system. A formula consisted of safety entropy, functional conformability, and system complexity has been established to determine the spontaneity of the safety state-changing process. The proposed method is applied to the safety assessment of a propane feed-control system. The results show the applicability of the method. Nevertheless, the model still needs to be further improved to fulfill better support for safety-related decision problems.     

Recent application of Computational Fluid Dynamics (CFD) in process safety and loss prevention: A review

In recent years, significant progress has been made to ensure that process industries are among the safest workplaces in the world. However, with the increasing complexity of existing technologies and new problems brought about by emerging technologies, a strong need still exists to study the fundamentals of process safety and predict possible scenarios. This is attained by conducting the corresponding consequence modeling and risk assessments. As a result of the continuous advancement of Computational Fluid Dynamics (CFD) tools and exponentially increased computation capabilities along with better understandings of the underlying physics, CFD simulations have been applied widely in the areas of process safety and loss prevention to gain new insights, improve existing models, and assess new hazardous scenarios. In this review, 126 papers from 2010 to 2020 have been included in order to systematically categorize and summarize recent applications of CFD for fires, explosions, dispersions of flammable and toxic materials from accidental releases, incident investigations and reconstructions, and other areas of process safety. The advantages of CFD modeling are discussed and the future of CFD applications in this research area is outlined.