数据挖掘在预测组织事故防控效果中的应用*

为进一步探索数据挖据技术在组织事故预防工作中的融入性与适用性,基于24Model构建事故预控基础模型,通过预测准确率数值及接受者操作特性曲线（ROC曲线）对比分析随机森林（RF）、支持向量机(SVM)、决策树（DT）与神经网络（NN）4种方法对组织事故防控效果的预测性能。结果表明:针对事故率控制（Y1）、职业危害预防（Y2）、财产损失3类预测目标（Y3）,RF方法均能达到较高的准确率及稳定性,具有较优的预测性能。根据特征重要度（FI）排序,明确对组织事故水平影响最显著的因素为安全实践活动认知（SC5）及安全管理程序文件（SMS3）,FI值均大于0.150 0。研究结果可为有效预测组织事故防控效果提供方法依据,同时为企业安全工作的规划设计提供思路。     

探究环境监测数据在环境执法中的应用

伴随经济发展的迅速,人们对环境越来越重视,国家也制定了相应的环境执法与保护措施,保障环境质量。在环境执法的过程中,必须严格依照环境监测的数据,从而保障信息的准确性,使环境执法策略的开展能够顺应时代发展,符合目前发展的现状。因此,环境执法中环境监测数据占据重要的位置。基于此,本文分析了环境执法中环境监测数据的应用,笔者根据自身经验提出相应的建议。     

基于大数据技术构建生态环境信息化体系及其重点应用研究

本文首先分析了生态环境信息化体系的主要构成要素,其后基于大数据技术的生态环境信息化体系重点领域应用进行了深入研究。     

肥煤自燃全过程热动力学特征参数研究

实验测定了林西矿肥煤样品30~900℃煤自燃全过程热动力学特征参数,得出:TG/DTG曲线显示煤样DTG初始临界温度45℃,干裂温度122℃,活性温度195℃,增速温度265℃,质量极大值温度342℃,着火温度465℃,最大热失重速率温度515℃和燃尽温度690℃;DSC曲线显示,煤样初始放热温度60℃、最大热释放速率温度511℃。结合TG-DTG-DSC曲线综合分析可知,煤温达到510℃左右时煤样反应最剧烈。由煤自燃标志气体测定实验系统得出:煤温130℃后CO,CO 2释放量迅速增加,210℃增加速度下降;CH 4,C 2 H 6含量变化具有规律性且两者变化相近;C 2 H 4出现温度为130℃;C 2 H 4/C 2 H 6比值在190~350℃有较强的规律性,呈上升趋势且上升速度较快;350℃之后,CH 4,C 2 H 6,C 2 H 4体积分数均开始急剧增大;C 2 H 4/CO与C 2 H 4/CO 2变化趋势大致相同,在130~350℃时缓慢增长,达到350℃后比值呈指数形式上升。经拟合曲线,得到活化能的3个突变点温度:70,180,220℃,其中180℃与交叉点温度相吻合。通过以上研究,得到了肥煤自燃全过程的热力学特征参数,为实际生产中防治煤自燃提供了理论依据。     

矿井热宽温度环境人体热健康分区热调节模型*

为评价矿井热环境中工人职业健康安全状况,提出矿井热宽温度环境人体热健康状态的基本特征与生理要求,分析热宽温度环境人体分区热调节规律与热健康状态的对应关系。基于生物控制论的观点,提出热宽温度范围内不同热应力作用下人体分区热调节机制,建立人体分区热调节模型。结果表明:模型能实现对环境热应力作用下人体物理热平衡状态与生理状态的参数化描述,揭示多因素作用下人体热健康状态的热应力边界与变化规律。分区热调节模型提供了人体热健康状态定量模拟平台,通过参数调整可使模型适应研究需求,模型为井下热环境工人职业健康安全状况分析与评价提供了可参考的思路与方法。     

屏蔽服冷却系统对人体表面温度影响的研究*

为科学有效地论证多种方式组合的冷却屏蔽服在不同环境条件下对人体表面温度控制的效果,需要对冷却系统及人体敏感部位发热量进行客观评估。通过对5名健康男性的高温测试,探究人体在不同环境温度下体表温度的变化,得出胸部、背部及额头为热量最高部位,并构建以“人体-降温屏蔽服-外界环境”为主体的冷却系统数值模型,对不同环境中的屏蔽服冷却效果展开研究,分析穿戴冷却屏蔽服时人体躯干部分的温度分布及影响。结果表明:在屏蔽服中靠近胸部、背部部位引入相变材料和风扇,均可帮助人体降低体温,提高舒适度。     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

简述排污许可制下火电行业现状及发展

实施排污许可制度,是强化排污者责任、提高固定污染源环境管理效能、改善环境质量的重要制度保障。火电行业作为典型的高架固定源,先行试点实施排污许可制度。通过分析火电行业发展和环保现状,结合排污许可管理要点,简述排污许可制对火电行业发展的影响。