基于成本收益理论的井场作业人员不安全行为决策分析

为有效制定油气田井场作业人员不安全行为的防范措施,降低事故发生可能性,基于成本收益理论建立油气田井场作业人员的行为决策模型,通过仿真计算定量分析了不同影响因素对不安全行为产生的影响程度。结果表明:正向激励和负向激励对不安全行为的降低幅度为21.8%,17.2%,负向激励和监督力度共同作用下不安全行为可降低44.8%。油田企业在保证利润的前提下应优先提升HSE奖励水平,合理控制罚金水平的同时加大管理监督力度,从而有效减少作业人员不安全行为的发生,保障企业的安全生产。     

基于AHP-联系熵的应急预案实施过程风险评估

应急预案制定后的实施对于事故发生后预案的顺利运行至关重要,因此,有必要对应急预案实施过程的风险水平进行度量。以应急预案实施过程作为研究对象,基于风险理论与AHP-联系熵耦合方法开展风险评估。以应急预案实施过程风险水平为目标层,应急预案的宣传教育和培训、应急资源的定期检查落实、应急演习训练、应急预案的实用性检验、应急预案电子化、事故回顾等过程要素作为策略层,实施方法科学高效、调动工作者积极的态度、领导的重视和能力、设备的完整性作为方案层,形成应急预案实施过程风险评估三级模型;运用联系熵表征风险标准与应急预案实施过程风险水平这2个集对之间的关联性,在AHP结构模型和权重分配的基础上计算加权熵并得到目标层的总联系熵,对比标准熵区间得到应急预案实施过程的整体风险等级。结果表明,采用AHP-联系熵度量方法提高了评价结果的结构性和准确性,比传统直接加权的方法更符合实际情况。     

基于文本挖掘的煤矿安全隐患管理研究

为探寻安全隐患的内在特征,加深安全管理人员对安全隐患的理解,提升安全管理效率。以潞安集团司马煤业有限公司2009—2015年安全隐患记录为数据源,利用Word2Vec模型构建安全隐患词向量模型,从模型中获取各类安全隐患主要相关词,利用桑基图解释安全隐患在不同隐患地点、生产作业单位的特征分布,并进一步揭示相关安全隐患的细节特征。结果表明:词向量模型能有效发掘安全隐患特征,桑基图能突出呈现安全隐患的关键信息流动。上述措施有助于管理人员深刻理解安全隐患数据中蕴含的潜在规律,为煤矿安全隐患排查治理工作提供依据,指导安全管理实践。     

基于复合治理理论的基层应急管理模式优化*

为弥补传统基层应急管理模式的短板,解决信息壁垒、协调困难、公众参与不足等问题。从复合性视角出发,阐述复合治理理论内涵,探讨复合治理与应急管理在主体、思维、过程、空间、目标上的契合性,并进一步分析基层应急管理的现实背景和困境,进而构建基于复合治理理论的基层应急管理模式,阐明模式基本结构和工作流程,最终提出理念树立、平台搭建、机制保障、队伍建设、制度安排、文化营造、技术支撑方面的优化路径。结果表明:复合治理理论的应用可以加强基层应急管理能力,促进多元主体协同共治。     

基于蒙特卡洛模拟的多米诺事故风险量化管理*

为降低危化品相关的化工事故造成的人员伤亡和财产损失,以化工多米诺事故为研究对象,探讨由初始事故引发1个或多个次生事故的连锁反应机理与风险评估方法。提出应用蒙特卡洛模拟对多米诺事故风险进行动态量化的方法,梳理化工多米诺事故风险的识别、分析、评定、处理全周期管理流程,并以1个天然气压气站为案例,验证基于蒙卡模拟的化工多米诺事故风险量化方法的有效性。结果表明:该方法可以更准确地对化工多米诺事故风险进行定量评估。多米诺事故风险全周期管理流程的梳理能够有效指导化工企业开展安全管理、事故预防等工作。     

废荧光灯的环境污染对策探讨

废荧光灯管中的有害物质如果处置不当,会对人体健康和环境造成危害。目前国内大部分废荧光灯管未得到无害化处置,主要在指定的法规、有效的政策以及完善的运营机制方面存在很多弊端,应引起社会各界的关注和政府部门的重视。本文结合国内外废荧光灯管回收处置现状,针对存在的问题,提出源头控制、分类收集、多渠道回收、建立资金及资金补贴机制以及技术手段措施,为从根本上解决废旧灯管回收难的问题,并探索社会源危险废物的管理提供对策建议。     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

县级环境监测站垂直管理后工作思考

简要分析了县级环境监测站在监测监察执法垂直管理制度改革后面临的问题,并针对问题提出建议。     

西南山地区域森林火险综合预报模型研究——以重庆市为例

森林火灾严重破坏森林生态系统的结构和功能,针对其风险预报开展研究具有重要的理论意义和应用价值。通过融合气象、地表覆盖和人类活动等要素的方式构建森林火险综合预报模型,是西南山地区域森林火险综合预报业务化应用的重要发展方向。基于《森林火险气象等级》国家标准(GB/T 36743-2018),本文研究首先构建了重庆市森林火险气象风险预报模型。然后通过融合可燃物因素和人为因素的方式,进一步构建重庆市森林火险综合预报模型。最后利用历史火点数据针对上述两类模型的精度进行对比和分析。研究结果表明:重庆市森林火灾发生次数较多,且呈现出季节性规律;重庆市森林火灾的发生不仅受到气象条件的影响,而且受到地表覆盖和人类活动等多种要素条件的共同影响;与森林火险气象风险预报结果相比,森林火险综合预报结果在空间分布上具有更高的精细程度;森林火险综合预报模型能有效提高森林火险等级预报精度。