Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

飞机实验室风吹雨气候环境试验技术研究

为了解决目前飞机整机风吹雨试验只能在外场自然环境条件下进行,试验周期长,费用大的难题,研究飞机实验室风吹雨试验技术。通过研究飞机遭遇极端气候风吹雨引起的环境效应,基于气候环境实验室风吹雨试验环境条件的建设能力,借鉴国内外相关环境试验标准以及国外飞机气候环境试验经验。规划了飞机整机实验室风吹雨试验项目和试验顺序,设计了飞机实验室风吹雨试验方法,总结了试验需要检测及评估的范畴。为飞机实验室风吹雨试验的实施提供技术参考。     

一种生物除臭方法及装置的研究

文章介绍了一种生物除臭的方法,这种方法是将装有碳质填料的反应包悬挂于好氧池中,反应包在好氧池中,历经曝气挂膜20~30天;就可以将装有碳质填料的反应包/或碳质填料放于生物除臭装置内;然后向生物除臭装置通入湿润的臭气,就可以将其生成水、二氧化碳、硫酸、硝酸和亚硝酸.使臭气被氧化,转化成无污染的物质,由于它的转化效率高,符合现代生产的高效性,因此一定会在生产实际中受到欢迎.     

低中放处置场环境评价参数灵敏度分析

选取90Sr、239Pu和14C为代表核素,采用单参数变分法对某低中水平放射性固体废物处置场环境影响评价中与核素迁移相关的主要评价参数开展了参数灵敏度分析.分析结果表明:对于低中放处置场而言,环境影响评价模式中主要评价参数的选择对最终评价结果的影响很大,因此在环境影响评价中开展不确定度及敏感度分析是必要的.     

中国低中放近地表处置场环境评价方法研究

放射性废物的处置是对其管理的最终步骤.放射性废物处置的基本安全目标是保护人类和环境免受电离辐射的有害影响.开展处置场环境影响评价可以量化它对人体健康和环境潜在影响.通过与IAEA近十几年的最新研究成果相比较,分析了中国低中放近地表处置场现行评价方法的不足,提出了改进方式,并对中国近地表处置场环境影响评价技术研究下一步应开展的工作进行了探讨.     

国内外可持续发展评价方法对比分析

国际、国内很多组织都对可持续性评价方法进行过研究分析,但大多是特定的案例研究.目前国内外对可持续发展评价方法没有一个全面系统的分析比较,使得不同地区比较起来很困难.本文对各种评价方法如环境可持续性指数法、生态足迹法、能值分析法和指标综合评价法的来源、理论和应用作了介绍.得出各方法适用范围:可持续性指数法适合于国家间的综合评价;生态足迹和能值分析法适合于各种范围,包括国家、区域、地区和小系统;指标体系综合评价法对于小范围更合适.同时对各种方法的优势和缺陷进行了分析讨论,得出:可持续性指数法信息量大,但是计算复杂;生态足迹法计算过程简单,但是缺失一些可持续性信息;能值分析法考虑问题全面,但是其原理涉及热力学知识,很难被一些学者认同;指标体系评价法变通性较大,可随着评价系统的变化而进行调整,但是主观性较强.通过分析指出不同方法适用范围并指出每种分析方法的优势和不足,为以后选择合适的分析方法评价对象的可持续性提供依据.     

欧美等发达国家水环境监测方法体系

分别简述了美国、欧盟和日本等发达国家或组织水环境监测方法体系发展历程,分析了其各自水环境监测方法体系特点。对中国水环境监测方法体系的制定与实施提出了建议。     

电镀污泥的热处理特性以及对金属回收的影响

焙烧-酸浸法可有效回收电镀污泥中的有价金属,而污泥的热处理特性是决定能否采用焙烧预处理的重要因素。研究了氧化焙烧和还原焙烧对污泥成分和金属浸出性的影响,并对焙烧前后的污泥进行了金属形态分析和X射线衍射(XRD)分析。结果表明,焙烧预处理实现了污泥减量和金属富集;ES1经氧化焙烧后金属浸出率接近原泥,Cu的浸出率达99%;ES2的还原焙烧效果优于氧化焙烧,特别是Cu的浸出率超过97%,XRD分析发现,还原焙烧过程中金属Cu被还原为铁铜合金;2种焙烧均造成了ES3中目标金属Ni的浸出率的降低;金属浸出性的下降与残渣态的形成有关。     

环境污染物导致氧化应激的关键信号通路及其检测方法

环境污染物能够以多种途径进入生物体内,在体内产生含氧自由基等活性氧物质,并通过多种信号通路及酶反应引起氧化应激,造成生物体内的脂质过氧化、蛋白质损伤、DNA表达改变、酶失活等,从而引发心血管疾病、风湿类疾病、感染及癌症等的发生。本文对环境污染物致氧化应激产生的原因、涉及的信号通路及酶反应、造成的危害,以及常见的基于细胞模型的氧化应激检测方法进行了综述,期望为评价环境污染物和检测氧化损伤提供参考。     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.