细水雾阻隔火焰热辐射的模拟研究

从热辐射传递方程出发，根据Mie散射理论,考虑雾滴对热辐射的散射和吸收特性，建立细水雾阻隔火焰热辐射的两通量模型，并给出简化算法；同时建立小尺度模拟实验系统，对理论模型进行验证。结果表明，两通量模型较为合理地预测了细水雾对火焰热辐射的衰减作用。在此基础上，应用上述理论模型进一步探讨火焰温度、细水雾特性参数、雾场厚度对阻隔热辐射效率的影响，为细水雾系统的实际工程应用提供了理论和依据。     

锂离子电池安全性特点及热模型研究

锂离子电池的安全问题越来越受到重视.本文从锂离子电池热安全性特点着手,分析了锂离子电池的着火、爆炸和电解液泄漏等安全事故特点.简单介绍了锂离子电池主要材料的产热特性、相互反应产热特性.讨论了锂离子电池热模型建立的两种途径,即量热仪途径和化学反应途径,通过这些热模型的建立,来指导锂离子电池的安全设计和管理.     

饮用水源水库铁锰垂直分布规律及原因

经对水温分层型季节性缺氧水库铁、锰污染的研究表明,Fe、Mn分布随着季节变化、水库水温分层而变化,呈现明显的垂直分布规律:高浓度Fe、Mn主要出现在水温分层期水库中、下层,与库底缺氧、pH值下降、基岩溶蚀、沉积物高浓度Fe、Mn释放造成的二次污染等密切相关,从而为自来水厂实施优化分层取水和污染控制提供了依据.     

红外和热分析联用在化工产品研究中的应用

运用实例论述了红外光谱分析与热分析联用在化工产品的产品开发和检测方面的应用。     

污染物排放相关指标计算方法的研究

针对传统的污染排放数据指标计算方法存在的问题,提出污染物排放指标应根据排污强度和经济指标确定的新思路,同时提出污染物排放指标数据的快速测算模型设计.建议通过环境监测数据或物料衡算数据确定每个排污单位的平均排污强度,作为计算机处理的参数,再由该排污单位申报每月的经济指标(产量或产值),输入计算机计算其产污量、排污量和去除量.实施计算机管理的关键是选取适当的数据计算模型.新思路应该能够规范计算程序,建立污染源动态数据库,对排污数据实行有效的统计分析.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

ACCURACY OF LAKE AND STREAM TEMPERATURES ESTIMATED FROM THERMAL INFRARED IMAGES1

Emitted thermal infrared radiation (TIR, λ= 8 to 14 μm) can be used to measure surface water temperatures (top approximately 100 μm). This study evaluates the accuracy of stream (50 to 500 m wide) and lake (300 to 5,000 m wide) radiant temperatures (15 to 22°C) derived from airborne (MASTER, 5 to 15 m) and satellite (ASTER 90 m, Landsat ETM+ 60 m) TIR images. Applied atmospheric compensations changed water temperatures by ?0.2 to +2.0°C. Atmospheric compensation depended primarily on atmospheric water vapor and temperature, sensor viewing geometry, and water temperature. Agreement between multiple TIR bands (MASTER ‐ 10 bands, ASTER ‐ 5 bands) provided an independent check on recovered temperatures. Compensations improved agreement between image and in situ surface temperatures (from 2.0 to 1.1°C average deviation); however, compensations did not improve agreement between river image temperatures and loggers installed at the stream bed (from 0.6 to 1.6°C average deviation). Analysis of field temperatures suggests that vertical thermal stratification may have caused a systematic difference between instream gage temperatures and corrected image temperatures. As a result, agreement between image temperatures and instream temperatures did not imply that accurate TIR temperatures were recovered. Based on these analyses, practical accuracies for corrected TIR lake and stream surface temperatures are around 1°C.     

不同环境体系下锂离子电池热失控特性实验研究

针对锂离子电池热失控引发的航空运输安全问题,自主设计并搭建锂离子电池热失控灾害演化及危险性分析实验平台。在敞开和密封环境体系下,对电加热触发荷电量(State of Charge,SOC)为0%、50%和100%的18650型锂离子电池热失控规律进行了实验研究。观察单体锂离子电池在敞开和密封体系中的热失控现象,并记录单体锂离子电池热失控时间、温度峰值及相应的温度变化。数据结果显示,相比敞开体系,密封体系有效的延缓了锂离子电池发生热失控的时间,并降低了锂离子热失控时释放的能量,为锂离子电池的航空运输安全性研究提供了理论依据和工程技术参考。     

Connecting the Dots: Public Engagement with Environmental Data

Air pollution and other environmental hazards are often imperceptible and need to be made publicly visible. The paper argues for the importance of visualizations in drawing public attention to imperceptible hazards and in providing the public with access to empirical data describing the risks. It also argues for critical inquiry into hazards’ selective visibility as it is produced by visualizations. The impact of visualizations and their selective visibility are considered through the example of a public art project called Particle Falls installed in 2014 in Pittsburgh, a city with a long history of both ignoring air pollution and working to ameliorate this problem. I examine the impact and selective visibility of Particle Falls by considering the underlying production of data, as well as context and support systems for this visualization, and by comparing it with other visualizations of local air quality.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.