建筑火灾中值得深入研究的几个问题

提出了一些建筑火灾中值得进一步研究的,流动、传热、热解、燃烧、污染物生成等方面的基础问题。着重讨论了烟气扩散、流动中的混沌现象,提出了建立建筑火灾数据库、专家系统的设想,和建立非线性燃烧模型、开发智能型火灾自动报警系统的技术思路。     

Evaluation of ecological network analysis: Validation of output

Ecological network analysis (ENA) is a modeling approach increasingly being used to evaluate food webs and provide an ecosystem-based approach to resource management. Unfortunately, validation of ENA output is rarely performed. This study represents part of a larger effort to critically evaluate ENA. Here we validate ENA output using stable isotope analysis (SIA), and where validation is not met, determine the effects of modifying trophic networks to reflect validation.     

基于随机森林的阻变型通风网络故障诊断方法*

为了在矿井通风网络发生阻变型故障时,能够快速准确判断出故障位置和故障量,提出1种基于随机森林的通风网络故障位置和故障量诊断方法。利用矿井通风仿真系统IMVS将唐安矿模拟故障生成空间数据集并进行数据预处理,构建基于随机森林的故障诊断模型,并利用该诊断模型对唐安矿矿井通风网络模拟故障位置和故障量进行判断和预测。引用多种方法对模型进行度量,通过唐安矿模拟实验验证基于随机森林的故障诊断模型的有效性。将随机森林和决策树的故障诊断准确率进行对比,研究结果表明:随机森林较决策树故障准确率有进一步的提高,并发现故障地点失误诊断多是相邻巷道,在一定程度上工作人员对故障地点的判断并不受其影响。     

辽宁云水资源分布特征及开发潜力分析

我国淡水资源短缺,人口增长、经济发展与水资源短缺的矛盾日益加剧,已严重影响着我国部分地区经济和社会持续健康发展。人工增雨、开发空中云水资源是缓解水资源短缺的一个重要途径。文章利用辽宁省气象台站网的常规探空、云和降水的观测资料,计算、分析了辽宁云水资源的分布状况及开发潜力,结果显示全省云水资源总量年均为4.83×10¹¹m³,具有较多的作业机会和较大的人工增雨潜力,开发云水资源大有可为。     

一种处理爆炸多能法的新方法

以多能法中距离－超压关系图为例,介绍了一种运用前馈多层感知器网络对现行多能法中查图步骤进行改进的方法。此法从很大程度上解决了多能法在爆炸灾害评估中手工查图误差大且不方便的缺点。模拟结果表明,该处理方法能够很好的逼近多能法中的超压函数P＝f(R0,C),最后提出了人工神经网络方法在爆炸破坏效应评估中进一步应用的设想。     

碳中和目标下海洋地球工程的国际法规制和政策启示

碳中和目标的实现需要充分开发海洋碳汇的潜力。海洋施肥、人工海洋上升流、海洋碱化是三种旨在提升海洋碳汇的地球工程技术。本文从海洋地球工程活动合法性、海洋环境保护义务和气候变化公约体系三个方面论述海洋地球工程的国际法框架。首先,《伦敦倾倒公约》和《伦敦议定书》中关于“倾倒”的定义不适用于海洋地球工程活动涉及的以吸收二氧化碳为目的投放铁或碱性物粉末或放置管道的行为。《关于规制以海洋施肥和其他以海洋地球工程活动为目的投放物质的伦敦议定书修正案》将海洋施肥活动限制在通过了完整的环境影响评价的“合理科学研究”范围内。目前这一限制不适用于其他海洋地球工程技术,但随着对其他技术研究的深入,修正案限制范围有可能会扩大。其次,《联合国海洋法公约》和《生物多样性公约》中有关海洋环境和海洋生态保护的公约条款适用于海洋地球工程活动,其中有关环境影响评价的义务与海洋地球工程的发展密切相关。再次,《联合国气候变化框架公约》以及《巴黎协定》中关于国家自主贡献的规定为实施海洋地球工程提供了鼓励性规则。最后,本文就中国关于该技术的实验活动以及未来应用该技术的场景下涉及的遵约和治理问题进行展望。当前不与国际法冲突的发展模式是进行小规模试验研究、建立海洋碳汇方法学标准、核算海洋碳汇经济价值,推动海洋碳汇换算核证自愿减排量进入碳市场交易;在实践中鼓励将开发海洋碳汇与低碳渔业养殖、陆海统筹增汇等方法相结合。未来能否大规模实施海洋地球工程技术取决于对海洋生态环境相关影响研究的进展。     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

River-Stream Connectivity Affects Fish Bioassessment Performance

Stream fish bioassessment methods assume that fish assemblages observed in sample sites reflect responses to local stressors, but fish assemblages are influenced by local factors as well as regional dispersal to and from connected streams. We hypothesized that fish movement to and from refugia and source populations in connected rivers (i.e., riverine dispersal) would weaken or decouple relations between fish community metrics and local environmental conditions. We compared fish-environment relations between streams that flow into large rivers (mainstem tributaries) and streams that lack riverine confluences (headwater tributaries) at multiple spatial grains using data from the USEPA's Environmental Monitoring and Assessment Program in the mid-Atlantic highlands, USA (n = 157 sites). Headwater and mainstem tributaries were not different in local environmental conditions, but showed important differences in fish metric responses to environmental quality gradients. Stream sites flowing into mainstem channels within 10 fluvial km showed consistently weaker relations to local environmental conditions than stream sites that lacked such mainstem connections. Moreover, these patterns diminished at longer distances from riverine confluences, consistent with the hypothesis of riverine dispersal. Our results suggest that (1) the precision of fish bioassessment metrics may be improved by calibrating scoring criteria based on the spatial position of sites within stream networks and (2) the spatial grain of fish bioassessment studies may be manipulated to suit objectives by including or excluding fishes exhibiting riverine dispersal.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.