Reducing fugitive methane emissions from the North American oil and gas sector: a proposed science-policy framework

The shale gas boom in the United States spurred a shift in electricity generation from coal to natural gas. Natural gas combined cycle units emit half of the CO₂ to produce the same energy as a coal unit; therefore, the market trend is credited for a reduction in GHG emissions from the US power sector. However, methane that escapes the natural gas supply chain may undercut these relative climate benefits. In 2016, Canada, the United States and Mexico pledged to reduce methane emissions from the oil and natural gas sector 40–45% from 2012 levels by 2025. This article reviews the science-policy landscape of methane measurement and mitigation relevant for meeting this pledge, including changes in US policy following the 2016 presidential election. Considerable policy incoherence exists in all three countries. Reliable inventories remain elusive; despite government and private sector research efforts, the magnitude of methane emissions remains in dispute. Meanwhile, mitigation efforts vary significantly. A framework that integrates science and policy would enable actors to more effectively inform, leverage and pursue advances in methane measurement and mitigation. The framework is applied to North America, but could apply to other geographic contexts.

Key policy insights

• The oil and gas sector’s contribution to atmospheric methane concentrations is becoming an increasingly prominent issue in climate policy.

• Efforts to measure and control fugitive methane emissions do not presently proceed within a coherent framework that integrates science and policy.

• In 2016, the governments of Canada, Mexico and the United States pledged to reduce methane emissions from the oil and natural gas sector 40–45% from 2012 levels by 2025.

• The 2016 presidential election in the United States has halted American progress at the federal level, suggesting a heavier reliance on industry and subnational efforts in that country.

• Collectively or individually, the countries, individual agencies, or private stakeholders could use the proposed North American Methane Reduction framework to direct research, enhance monitoring and evaluate mitigation efforts, and improve the chances that continental methane reduction targets will be achieved.

     

基于扩展关系模型的整体空间数据管理

空间数据模型和数据管理是地理信息系统 (GIS)最重要的研究领域之一。该文介绍一体化的数据模型———扩展关系模型和以此为基础的 ,由作者设计的GIS软件原型系统———GEODBMS。GEODBMS使用统一的数据库管理系统 (DBMS)同时管理图形和属性数据 ;使用改进的四叉树———交叠四叉树索引空间目标 ;使用扩展的SQL语言进行空间查询 ;使用数据恢复和并发控制方法来加强分布式环境下数据的安全性和一致性维护     

基于组合权重与灰色关联度分析法的地铁深基坑开挖稳定性评价

伴随着城市的快速发展,地铁深基坑工程越来越多。在开挖过程中如何对其稳定性进行评价,是当前需要重点关注的问题。以成都地铁十七号线凤溪站深基坑支护开挖工程为依托,利用层次分析确定的主观权重与利用熵值法确定的客观权重计算获得组合权重,并与灰色关联度分析法相结合,通过现场数据采集并进行综合评判,客观评价地铁深基坑开挖的稳定性。结果表明,各监测项目对基坑稳定性的重要程度从大到小依次为桩顶水平位移（0.29）、地表沉降（0.24）、建筑物沉降（0.19）、桩顶沉降（0.18）、内支撑轴力（0.10）,基坑稳定性综合评判结果等级为"非常好"。所建立的评价模型可为类似地铁深基坑开挖稳定性评价提供新的方法。     

An indicator-based adaptive management framework and its development for data-limited fisheries in Belize

Decisions regarding the selection and implementation of management strategies that constrain fishing pressure can be among the most difficult choices that fisheries managers and stakeholders must make. These types of decisions often need to be confronted in a data-limited context, where few if any management measures are currently in place or fisheries are managed independent of adequate scientific advice. This situation can sometimes create a high risk of overfishing and potential loss of economic and social benefits. To address this situation, simple model-free indicator-based frameworks have the potential to be effective decision-making platforms for fisheries where quantitative estimates of biomass and fishing mortality based reference points are lacking. In this paper, a multi-indicator framework is developed that enables decision-makers to proceed with management decisions in data-limited situations. Model-free indicators are calculated using trends in observed data, rather than stock assessment derived estimates of biomass and fishing mortality. The framework developed is adaptive so that adjustments to catch or effort are recursive and can respond to changing environments, socioeconomic conditions, and fishing practices. Using stakeholder-defined objectives as a foundation, indicators and reference points of fishery performance are chosen that can be evaluated easily by undertaking analyses of available data. Indicators from multiple data streams are used so that uncertainty in one indicator can be hedged through careful interpretation and corroboration of information from alternative indicators. During the adaptive management cycle, managers and stakeholders evaluate each indicator against the associated reference points to determine performance measures, interpret the results using scientific and local knowledge, and adjust fishery management tactics accordingly using pre-defined harvest control rules. The framework facilitates the interpretation of situations in which performance measures suggest divergent stock abundance or productivity levels. A case study is presented on this framework's development for conch and lobster fisheries of Belize.     

Environmental management frameworks for offshore mining: the New Zealand approach

The New Zealand region contains untapped natural mineral, oil, and gas resources while also supporting globally unique and diverse faunal communities that need to be managed sustainably. In this paper key information from the international literature is reviewed that can underpin an Environmental Mining Management System which includes elements of Environmental Risk Assessment, Environmental Impact Assessment and Environmental Management Planning. This paper focuses on four developing areas of seafloor mining activities presently being undertaken or planned in the New Zealand region: hydrocarbons (oil and gas), minerals, ironsands and phosphorite nodules. A number of issues with the implementation of environmental management systems are identified including the difficulty of assessing new marine activities or technologies and the need for standardised reporting metrics. Finally, the development of ecosystem-based management and marine spatial planning is discussed which will be required to enhance environmental mining management frameworks in New Zealand.     

基于灰色关联分析法的松辽盆地CO_2地质储存适宜性评价

松辽盆地是中国主要的能源基地,随着中国振兴东北老工业基地政策的实施,如何应对工业和经济发展带来的CO_2排放量的增加,将成为亟需解决的问题。在盆地内进行CO_2地质储存将成为盆地内解决该问题的主要技术选择之一。以松辽盆地为研究对象,在深入分析松辽盆地CO_2地质储存条件的基础上,从储存规模、储存安全性和社会环境风险及经济适宜性4个方面综合考虑,构建了由16个指标组成的松辽盆地CO_2地质储存适宜性评价指标体系,利用灰色关联分析法对松辽盆地33个二级构造单元进行了盆地级适宜性评价工作,评价结果为进一步场地级目标靶区的筛选提供了科技支撑。     

基于树形结构的地震数据库系统设计方法

地震观测数据的大量增长给数据管理提出了新的要求. 本文将树形结构引入到数据库设计中, 提出了基于树形结构设计关系数据库的方法. 该方法简单、 直观、 易于数据的组织, 可以简化数据库的设计过程. 在ldquo;长江三峡工程诱发地震监测系统地震监测总站数据库rdquo;设计中应用了该方法, 并取得了良好的效果.      

基于灰色关联分析的遗传神经网络在水下爆破中质点峰值振动速度预测研究

水下爆破是一个复杂的、非线性的动态能量释放过程,其涉及到的影响因素众多。为了充分利用少量的实测数据,较准确地预测水下爆破质点峰值振动速度,引入灰色关联分析理论,并结合遗传神经网络较强的非线性映射优势和全局化的搜索能力,建立基于灰色关联分析的遗传神经网络模型(GRA-GA-BP)。该模型利用灰色关联分析理论,充分挖掘小样本潜在信息特征,较合理地确定了影响爆破振动速度的主要因素,解决了神经网络在多变量复杂系统中输入变量无法自动寻优的难题,从而增强了神经网络的适应能力和稳定性。采用该模型对广东台山核电站1期工程大襟岛水下爆破开挖质点峰值振动速度进行预测,并与传统的遗传神经网络及萨道夫斯基公式预测结果进行对比,发现GRA-GA-BP模型的预测值与实测值吻合更好,预测误差更稳定。研究方法可为小样本、多因素影响下类似工程质点峰值振动速度预测提供借鉴。     

Spatio-temporal data model based on relational database system

In this paper, the entity-relation data model for integrating spatio-temporal data is designed. In the design, spatio-temporal data can be effectively stored and spatiao-temporal analysis can be easily realized.     

煤炭地质勘查中煤层综合对比方法研究——以永陇矿区老爷岭普查区为例

大型陆相煤盆地边缘的煤层划分与对比是煤炭地质勘查的关键性基础工作。依据基础地质勘探资料,应用标志层法、煤层自身特征法、测井曲线组合法、灰色关联分析法等,对永陇矿区老爷岭普查区延安组煤层进行综合对比。研究结果表明,在成煤环境不稳定地区,应用地质、地球物理和灰色关联分析等方法进行煤层综合对比可以取得可靠的结果。