"十三五"国家自然科学基金对能源环境管理领域的资助状况和趋势

能源环境管理是各界关注的热点话题,也是科学研究的重要方向.以国家自然科学基金资助能源环境管理领域的科研项目为基础数据信息,本文重点分析了"十三五"期间国家自然科学基金在该领域资助项目的总体特征、研究主题和热点变化,并结合新时代科学基金资助导向提出了可能的发展趋势.主要结论包括:①能源环境管理领域面上、青年、地区等自由探索类项目的立项绝对数和学科占比均呈上升趋势,并更多向青年学者倾斜,资助强度保持稳定;②碳、能源和环境是自由探索项目中出现频率最高的热词,与之相关的研究主题随着政策等调整具有动态变化特征;③能源环境管理领域重点、重大等引导类项目和优青、杰青、创新研究群体等人才类项目不断实现突破,增速明显,学科占比优势突出;④问题导向与本土情景、理论体系和一般规律、学科交叉融合,以及市场和微观主体作用是研究选题确立与项目申请时可能需要重点关注的方向.     

土壤中7种重金属和砷测定的精密度控制指标研究

通过对浙江省近700组实际土壤样品进行分析,研究了土壤中铜、铅、锌、铬、镍、镉、砷、汞7种重金属和砷测定的精密度控制指标(实验室内相对偏差和实验室间相对偏差),并与行业标准分析方法和文献进行了比较,旨在为环境监测质量控制与质量保证工作提供参考。经统计分析,建议实验室内相对偏差控制指标如下:铜,≤15%;铅,≤15%;锌,≤15%;铬,≤15%;镍,≤15%;镉,≤20%;砷,≤15%;汞,≤50%。建议实验室间相对偏差控制指标如下:铜,≤25%;铅,≤25%;锌,≤20%;铬,≤20%;镍,≤25%;镉,≤35%;砷,≤25%;汞,≤55%。     

Listing for change? Exploring the politics of relief lists in Bangladesh after Cyclone Sidr

Ideal notions of efficient aid are challenged continuously by realities on the ground in the wake of major disasters, such as dire needs, limited resources, and opportunism. This paper demonstrates how ‘relief lists’ can be productive entry points for a systematic inquiry into the pervasive politics of disaster assistance. Through an analysis of qualitative data collected during the five years after Cyclone Sidr struck Bangladesh on 15 November 2007, it examines how relief lists featured in both physical and phantom forms and then developed beyond their transparency-making aims, becoming elevated sites of struggle for post-disaster resources. Three list processes, selected to indicate the temporal, material, and spatial dynamics of relief encounters, are assessed in depth. Although recipients of cyclone relief appreciated its value, the paper argues that list politics also stimulated structures of vulnerability, including inequality. Gradually, relief, as governed after Sidr, also served to restore the differential vulnerability of the country's coastal poor.     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题，采用认知可靠性与失误分析方法（CREAM）中的扩展预测法，计算10项管制通用任务的人误概率；在此基础上，以管制行为形成因子作为根节点构建贝叶斯网络，建立其与情景控制模式的不确定关系模型，对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下，由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大，从方法的客观性、合理性和适用性角度分析，贝叶斯网络在研究该问题时更具优势。     

高应力巷道底臌变形机理及控制技术分析

为了分析高应力巷道底臌变形机理，以铜川玉华煤矿2407工作面巷道为研究背景，采用理论分析和现场观测相结合的研究方法。根据巷道底臌主要由原岩应力、支承应力、围岩遇水膨胀、流变作用而引起进行分析，推导出计算底臌量的表达式。针对玉华煤矿高应力巷道底臌变形，提出在巷道顶板采用锚网梁索支护，帮部采用锚网支护的原支护条件下，底板采用锚杆注浆和切槽联合支护方式控制底臌。现场观测结果表明:这种联合支护方式能够有效控制巷道底臌变形，底臌量降低了61.5%。将底臌量理论解与现场监测的结果进行比较，误差小于8.93%，验证了理论的合理性，为巷道底臌量分析提供了参考。     

分离岛式地铁站可用安全疏散时间计算与比较分析*

为研究大客流地铁车站风险因素，提出车站疏散能力分析的基本要素，结合某分离岛式地下车站，采用规范计算及精细网格模型对可用安全疏散时间进行计算与比较分析。结果表明:楼扶梯的通过效率、车站结构形式、疏散人员的数量及分布情况等因素对仿真模拟的结果产生影响；《地铁安全疏散规范》（GB/T 33668—2017）综合考虑了疏散至楼扶梯入口时间、楼扶梯上平均滞留时间及通道非均匀性偏差时间等，与仿真模拟结果的吻合度较高。研究结果可为国内类似车站的安全疏散设计及运营疏散组织提供参考。     

维修时间不确定性下配电网灾后维修队安排的鲁棒恢复研究*

为最小化灾后配电网损失量，准确描述完整维修队工作时间（分为路途时间与具体维修时间），依据台风路径对维修队所需路途时间进行分类，并利用期望概率描述具体维修时间的不确定性。建立2阶段分布式鲁棒优化模型，采用CCG算法分析国内某地区配电网算例发现:考虑维修时间不确定性可以有效减少配电网损失量。     

大型碳化硅生产园区面源源强及减排指标核算

以某年产25万吨大型碳化硅园区无组织排放面源为例,提出基于多个地面站气象数据的CALPUFF模型地面浓度反推方法,优化流场模拟,使得无组织面源源强核算结果更加准确,并以环境保护目标空气质量达标为原则,核算其大气污染物减排指标,得出具体结论:园区大气污染物SO2、NOX、CO、PM10年排放量分别为449.06t、86.98t、5158.58t、115.06t;无组织排放SO2、CO及PM10的减排比例分别为63.5%、19.2%、42.44%,对应减排量分别为285.16 t/a、990.45 t/a、48.83 t/a。     

污染源普查后区域环境管理应用探讨

在第二次全国污染源普查的基础上,利用污染源普查期间配置的软硬件,开发市级区域环境污染源管理平台,进行污染源数据的年度更新,拓展污染源普查软件应用,实现环境管理及环境执法移动终端的应用。拓展二污普一张图的功能,利用移动客户端机动实时及地定位导航等为环境管理执法和环境突发事件应急处置提供技术支持。     

How can process safety and a risk management approach guide pandemic risk management?

The coronavirus disease (COVID-19) brought the world to a halt in March 2020. Various prediction and risk management approaches are being explored worldwide for decision making. This work adopts an advanced mechanistic model and utilizes tools for process safety to propose a framework for risk management for the current pandemic. A parameter tweaking and an artificial neural network-based parameter learning model have been developed for effective forecasting of the dynamic risk. Monte Carlo simulation was used to capture the randomness of the model parameters. A comparative analysis of the proposed methodologies has been carried out by using the susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD) model. A SEIQRD model was developed for four distinct locations: Italy, Germany, Ontario, and British Columbia. The learning-based approach resulted in better outcomes among the models tested in the present study. The layer of protection analysis is a useful framework to analyze the effect of different safety measures. This framework is used in this work to study the effect of non-pharmaceutical interventions on pandemic risk. The risk profiles suggest that a stage-wise releasing scenario is the most suitable approach with negligible resurgence. The case study provides valuable insights to practitioners in both the health sector and the process industries to implement advanced strategies for risk assessment and management. Both sectors can benefit from each other by using the mathematical models and the management tools used in each, and, more importantly, the lessons learned from crises.