Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States, recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5–2× greater compared to official greenhouse gas inventory (GHGI) estimates, with the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions, for the production-segment only, that agrees within error with recent syntheses of site-level field studies and allows for isolation of equipment-level contributions. We find that unintentional emissions from liquid storage tanks and other equipment leaks are the largest contributors to divergence with the GHGI. If our proposed method were adopted in the United States and other jurisdictions, inventory estimates could better guide CH4 mitigation policy priorities.
Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States (US), recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5x-2x greater compared to official Environmental Protection Agency (EPA) greenhouse gas inventory (GHGI) estimates. Site-level field studies have isolated the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions using bootstrap resampling that agrees within error with recent syntheses of site-level field studies and allows for isolation of differences between our inventory and the GHGI at the equipment-level. We find that venting and malfunction-related emissions from tanks and other equipment leaks are the largest contributors to divergence with the GHGI. To further understand this divergence, we decompose GHGI equipment-level emission factors into their underlying component-level data. This decomposition shows that GHGI inventory methods are based on measurements of emission rates that are systematically lower compared with our updated synthesis of more recent measurements. If our proposed method were adopted in the US and other jurisdictions, inventory estimates could become more accurate, helping to guide methane mitigation policy priorities.
Resource depletion, global climate variability, and social issues are among the challenges currently driving a need for development, assessment, and implementation of more alternative energy sources and for more efficient energy use 1 . Increased energy literacy among the general population could foster these changes. Providing factual information about costs and emissions of different energy sources can influence persons' support for different sources 2 . Additionally, access to real-time energy use information (e.g., via a smart meter) has generally resulted in decreases in energy use 3 . Therefore, energy literacy holds a place of prominence within engineering education in order to foster the ability to weigh the complex issues surrounding various energy generation sources and the capability to develop strategies for reduced energy consumption. In recognition of this prominence, the United States Department of Energy (DOE) has advocated for promotion of energy literacy through energy education in strategic plans, other documents, and various events 4,5,6 . The DOE has devoted significant efforts to the development of a guide for general energy literacy principles to serve as the basis for educational efforts 7 .Energy literacy has been measured by testing broad energy knowledge through tests and questionnaires. Such efforts have shown generally low levels of energy literacy both in children 8,9,10,11 and adults 12,13,14 . Therefore, there is a need to develop educational activities to improve energy literacy. These activities have included high school energy competitions, development of interdisciplinary curricula, and field experiences and internships. As many of these educational endeavors culminate in some type of deliverable or other artifact, an opportunity exists to supplement measurement of energy literacy via tests of knowledge with measurement through observation of project artifacts. This type of approach could then be used to examine what factors might be contributing to higher levels of energy literacy, allowing refinement of the educational activities. The development of a rubric for the evaluation of energy literacy is in progress to capture the deliverables or outcomes of a competition or course 15,16,17 . Besides providing a direct form of assessment, rubric-based evaluation of artifacts may save time and effort associated with soliciting participation and completing a test or questionnaire. The rubric approach also allows for the evaluation of past works, which creates flexibility in the timing of observations and the ability to re-assess based on a different conception of energy literacy.Assessment of student learning is a central function of both formal and informal educational activities and settings, and has been instrumental in the advancement of engineering education 18 . Rubrics are a valuable way to assess competencies, such as those associated with energy literacy, because they allow for consistent assignment of scores based on established criteria and descriptions of performance 1...
Extending lube oil-drain intervals is a practical way to save money on engine operating costs. At the same time, there may be increased risk of engine damage with increased drain intervals. The risks and benefits can be difficult to weigh and, as a result, starting an oil-drain interval extension programme can be an intimidating endeavour. This paper combines oil-analysis programme data interpretation and life-cycle cost analysis (LCCA) into a methodology for weighing oil-drain interval options. LCCA has shown decreasing incremental cost savings as oil-drain intervals are further extended, indicating that highly extended drain intervals may not be necessary to reap the majority of available cost benefits. Using oil-analysis property trending with life-cycle cost savings can allow an engine operator to set an hours-based extended drain interval based on projected risks and benefits. This interval is set as the baseline under the protocol, but continual oil analysis is used as a precaution to protect against unpredictable events. This methodology helps to reduce the risk of engine damage and ensure that the most easily attainable cost savings are still captured, making the decision about how to extend oil-drain intervals more approachable.
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