Comparing the greenhouse gas emissions from three alternative waste combustion concepts

Three alternative condensing mode power and combined heat and power (CHP) waste-to-energy concepts were compared in terms of their impacts on the greenhouse gas (GHG) emissions from a heat and power generation system. The concepts included (i) grate, (ii) bubbling fluidised bed (BFB) and (iii) circulating fluidised bed (CFB) combustion of waste. The BFB and CFB take advantage of advanced combustion technology which enabled them to reach electric efficiency up to 35% and 41% in condensing mode, respectively, whereas 28% (based on the lower heating value) was applied for the grate fired unit. A simple energy system model was applied in calculating the GHG emissions in different scenarios where coal or natural gas was substituted in power generation and mix of fuel oil and natural gas in heat generation by waste combustion. Landfilling and waste transportation were not considered in the model. GHG emissions were reduced significantly in all of the considered scenarios where the waste combustion concepts substituted coal based power generation. With the exception of condensing mode grate incinerator the different waste combustion scenarios resulted approximately in 1 Mton of fossil CO₂-eq. emission reduction per 1 Mton of municipal solid waste (MSW) incinerated. When natural gas based power generation was substituted by electricity from the waste combustion significant GHG emission reductions were not achieved.     

净水厂氯气泄漏的环境风险分析

以丹阳净水厂为例,选取大气非正常排放模式,预测了液氯钢瓶阀门泄漏及爆炸对周围环境和保护目标的影响,并模拟了钢瓶爆裂事故的后果,计算出事故发生时的初始警戒区半径,提出了相应的氯气泄漏防范措施。     

大气细颗粒物在线源解析方法研究进展

基于对国内外关于PM2.5化学组分特征、二次气溶胶生成机理、源解析模型的研究综述,引入实现PM2.5在线源解析的2种可能方法,即气溶胶质谱+解析算法与3类化学组分组合观测+受体模型。重点阐述了气溶胶质谱及在线水溶性离子、EC/OC和金属元素仪器的应用研究现状,并分析了不同仪器测定结果的可靠性、优势及缺陷,在此基础上提出加强城市尺度的大气化学二次反应机理及关键技术参数研究、大气颗粒物化学组分连续观测应用于在线源解析的研究、基于多种信息来源和技术手段的在线源解析方法集成研究等建议。     

Measurements and Modelling of Air Pollution in a Street Canyon in Helsinki

A measuring campaign was conducted in the street canyon 'Runeberg street' in Helsinki in 1997. Hourly concentrations of carbon monoxide (CO), nitrogen oxides (NO_X), nitrogen dioxide (NO₂) and ozone (O₃) were measured at the street and roof levels, and the relevant hourly meteorological parameters were measured at the roof level. The hourly street level measurements and on-site electronic traffic counts were conducted during the whole year 1997, and roof level measurements were conducted during approximately two months, from 3 March to 30 April in 1997. The Operational Street Pollution Model (OSPM) was used to calculate the street concentrations and the results were compared with the measurements. The overall agreement between measured and predicted concentrations was good for CO and NO_x, but the model slightly overestimated the measured concentrations of NO₂. The database, which contains all measured and predicted data, is available for a further testing of other street canyon dispersion models.     

基于模糊评价法的建筑安全事故预测模型

针对建筑工程安全领域中许多对象具有"内涵明确,外延不明确"的特点,本文利用模糊数学对建筑安全事故影响因素进行度量,通过层次分析法确定各影响因素权重,提出了一种基于模糊评价法的建筑安全事故预测模型,解决了建筑生产中安全事故的即时预测,并通过实例给予说明,说明了模型在建筑安全事故预测中的有效性和实用性.     

液体火箭共底破裂爆炸安全设防距离

针对航天发射场一旦发生低温推进剂泄漏而导致火箭爆炸,会对人员和财产造成重大损失的问题,采用TNT当量模型和TNO(The Netherlands Organization)多能模型计算不同摩尔百分比的氢氧推进剂混合反应时产生爆炸冲击波的危害性,并模拟爆炸冲击波造成的事故影响范围,然后对两种模型的仿真结果加以对比分析,根据最不利原则选取出最终需要的结果,最后划分出安全设防距离。由仿真结果可知,不同的氢氧混合摩尔百分比造成的爆炸后果不同,同时TNT当量模型在爆炸近场处高估了爆炸超压值,在爆炸远场处低估了爆炸超压值,而TNO多能模型在理论上有效地对这一缺陷进行了弥补。对航天发射场的安全布局起到了一定的参考价值。     

基于ANP-DEA的城轨网络应急演练组合评价模型

应急演练综合评价是衡量应急演练效果好坏的关键。以城轨网络应急演练综合评价为研究对象,将城轨网络应急演练划分为演练准备、演练实施、演练总结三个阶段。针对评价指标间存在的关联关系,采用网络层次分析法(ANP)进行定量化处理,计算得到各评价指标综合权重,进而得到三个演练阶段的重要度。利用数据包络分析方法(DEA),分别计算三个阶段不同城轨线路应急演练的排序值,结合不同阶段的重要度,构建得到城轨网络应急演练的组合评价模型,实现对城轨网络应急演练效果的综合评价。结合算例,应用ANP-DEA组合模型,对某城轨网络的应急演练效果进行了综合评价。     

基于土壤模式生物的纳米材料毒理研究进展

随着纳米科技与工业的高速发展,大量的纳米材料被广泛应用并最终汇聚到土壤环境中,对土壤生态和人体健康造成潜在影响。由于土壤生物具有多样性,选择具有代表性、敏感性并便于获取的土壤模式生物作为实验受体进行纳米材料的生物安全评估及环境毒理效应研究尤为重要。较为系统地回顾和总结了几种典型土壤模式生物的特点,为纳米材料毒理研究中受试生物的选择提供参考,在此基础上整理了大量基于典型土壤模式生物的纳米材料毒性研究资料,归纳了不同层次的研究方法,分析探索了纳米材料毒性机理,并展望了未来的研究重点。     

Monitoring,imperfect detection,and risk optimization of a Tasmanian devil insurance population

Most species are imperfectly detected during biological surveys, which creates uncertainty around their abundance or presence at a given location. Decision makers managing threatened or pest species are regularly faced with this uncertainty. Wildlife diseases can drive species to extinction; thus, managing species with disease is an important part of conservation. Devil facial tumor disease (DFTD) is one such disease that led to the listing of the Tasmanian devil (Sarcophilus harrisii) as endangered. Managers aim to maintain devils in the wild by establishing disease‐free insurance populations at isolated sites. Often a resident DFTD‐affected population must first be removed. In a successful collaboration between decision scientists and wildlife managers, we used an accessible population model to inform monitoring decisions and facilitate the establishment of an insurance population of devils on Forestier Peninsula. We used a Bayesian catch‐effort model to estimate population size of a diseased population from removal and camera trap data. We also analyzed the costs and benefits of declaring the area disease‐free prior to reintroduction and establishment of a healthy insurance population. After the monitoring session in May–June 2015, the probability that all devils had been successfully removed was close to 1, even when we accounted for a possible introduction of a devil to the site. Given this high probability and the baseline cost of declaring population absence prematurely, we found it was not cost‐effective to carry out any additional monitoring before introducing the insurance population. Considering these results within the broader context of Tasmanian devil management, managers ultimately decided to implement an additional monitoring session before the introduction. This was a conservative decision that accounted for uncertainty in model estimates and for the broader nonmonetary costs of mistakenly declaring the area disease‐free.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.