New system for detecting, mapping, monitoring, quantifying and reporting fugitive gas emissions

2017 ◽  
Vol 57 (2) ◽  
pp. 561
Author(s):  
Tracy R. Tsai ◽  
Kendrick Du ◽  
Bill Stavropoulos
Keyword(s):  
Scale Up ◽  
Gas Detection ◽  
Barnett Shale ◽  
Fugitive Emissions ◽  
Coal Seam Gas ◽  
Large Size ◽  
Close Proximity ◽  
New System ◽  
Detection Technologies ◽  
Methane Detection

Coal seam gas (CSG) is an abundant energy source that’s been portrayed as having a lower Greenhouse Gas footprint than coal, but there have been concerns that fugitive emissions may be larger than estimated. Fugitive emissions associated with CSG development are engineered release points (valves and vents etc.) and unintentional equipment leaks. Various gas detection technologies are utilised across the industry that are effective at detecting large emissions sources in close proximity, but they are difficult to scale up to the large size needed for the CSG industry. We’ll present a summary of a trial utilising a new mobile methane detection and emission quantification system: the Picarro EQ (Emissions Quantification). After driving this instrument around CSG infrastructure, Picarro’s cloud-based analytics generate a map of methane measurements and emissions with wind indicators pointing to likely sources. Since all measurements are on a secure cloud-based service, any authorised operator can log into it to run reports and analytics. This system has been used to make measurements in the Barnett Shale, United States. We present results and demonstrate its usage within an operational CSG area to quantify and identify emissions from CSG infrastructure.

scholarly journals Isotopic signatures of major methane sources in the coal seam gas fields and adjacent agricultural districts, Queensland, Australia

2021 ◽  
Vol 21 (13) ◽  
pp. 10527-10555
Author(s):  
Xinyi Lu ◽  
Stephen J. Harris ◽  
Rebecca E. Fisher ◽  
James L. France ◽  
Euan G. Nisbet ◽  
...  
Keyword(s):  
Coal Seam ◽  
Treatment Plant ◽  
Source Attribution ◽  
Multiple Sources ◽  
Coal Seam Gas ◽  
Isotopic Signatures ◽  
Keeling Plot ◽  
Stable Isotopic ◽  
Close Proximity ◽  
Gas Fields

Abstract. In regions where there are multiple sources of methane (CH4) in close proximity, it can be difficult to apportion the CH4 measured in the atmosphere to the appropriate sources. In the Surat Basin, Queensland, Australia, coal seam gas (CSG) developments are surrounded by cattle feedlots, grazing cattle, piggeries, coal mines, urban centres and natural sources of CH4. The characterization of carbon (δ13C) and hydrogen (δD) stable isotopic composition of CH4 can help distinguish between specific emitters of CH4. However, in Australia there is a paucity of data on the various isotopic signatures of the different source types. This research examines whether dual isotopic signatures of CH4 can be used to distinguish between sources of CH4 in the Surat Basin. We also highlight the benefits of sampling at nighttime. During two campaigns in 2018 and 2019, a mobile CH4 monitoring system was used to detect CH4 plumes. Sixteen plumes immediately downwind from known CH4 sources (or individual facilities) were sampled and analysed for their CH4 mole fraction and δ13CCH4 and δDCH4 signatures. The isotopic signatures of the CH4 sources were determined using the Keeling plot method. These new source signatures were then compared to values documented in reports and peer-reviewed journal articles. In the Surat Basin, CSG sources have δ13CCH4 signatures between −55.6 ‰ and −50.9 ‰ and δDCH4 signatures between −207.1 ‰ and −193.8 ‰. Emissions from an open-cut coal mine have δ13CCH4 and δDCH4 signatures of -60.0±0.6 ‰ and -209.7±1.8 ‰ respectively. Emissions from two ground seeps (abandoned coal exploration wells) have δ13CCH4 signatures of -59.9±0.3 ‰ and -60.5±0.2 ‰ and δDCH4 signatures of -185.0±3.1 ‰ and -190.2±1.4 ‰. A river seep had a δ13CCH4 signature of -61.2±1.4 ‰ and a δDCH4 signature of -225.1±2.9 ‰. Three dominant agricultural sources were analysed. The δ13CCH4 and δDCH4 signatures of a cattle feedlot are -62.9±1.3 ‰ and -310.5±4.6 ‰ respectively, grazing (pasture) cattle have δ13CCH4 and δDCH4 signatures of -59.7±1.0 ‰ and -290.5±3.1 ‰ respectively, and a piggery sampled had δ13CCH4 and δDCH4 signatures of -47.6±0.2 ‰ and -300.1±2.6 ‰ respectively, which reflects emissions from animal waste. An export abattoir (meat works and processing) had δ13CCH4 and δDCH4 signatures of -44.5±0.2 ‰ and -314.6±1.8 ‰ respectively. A plume from a wastewater treatment plant had δ13CCH4 and δDCH4 signatures of -47.6±0.2 ‰ and -177.3±2.3 ‰ respectively. In the Surat Basin, source attribution is possible when both δ13CCH4 and δDCH4 are measured for the key categories of CSG, cattle, waste from feedlots and piggeries, and water treatment plants. Under most field situations using δ13CCH4 alone will not enable clear source attribution. It is common in the Surat Basin for CSG and feedlot facilities to be co-located. Measurement of both δ13CCH4 and δDCH4 will assist in source apportionment where the plumes from two such sources are mixed.

scholarly journals Large-Size Message Construction for ETI: Self-Interpretation in LINCOS

2004 ◽  
Vol 213 ◽  
pp. 499-504 ◽  
Author(s):  
Alexander Ollongren ◽  
Douglas A. Vakoch
Keyword(s):  
Propositional Logic ◽  
Constructive Logic ◽  
Minimal Set ◽  
Natural Languages ◽  
Abstract System ◽  
System A ◽  
Large Size ◽  
Meta Level ◽  
New System ◽  
Considerable Size

Messages for ETI written in a terrestrial language admitting linear notation, should be supplied with extra-linguistic annotations – also linearized in some way – as an aid for interpretation by recipients. In several papers the first author has advocated the use at the second level of an abstract system (a new Lingua Cosmica, still under development), based on constructive logic – with a minimal set of primitives. Expressions at the meta level explain the logic contents of messages.The interaction between any LINCOS and text may suffice for interpretation of both – provided the messages and annotations are of considerable size. Finding a measure for the sizes involved is, however, a non-trivial problem. As a result, one is interested in methods for interpreting a LINCOS without recourse to natural languages. The present paper is concerned with the problem of interpretation of the new system within itself. For that purpose, interpretation of parts of it and (complete) propositional logic in terms of each other is considered (commutativity). This leads to self-interpretation as all semantic terms reside in the closed context of the system.

Gas detection using large-size graphene with defects

2014 ◽  
Vol 116 (19) ◽  
pp. 193704 ◽  
Author(s):  
Shiu-Ming Huang ◽  
Yu-Fang Fan ◽  
Pushpendra Kumar
Keyword(s):  
Gas Detection ◽  
Large Size

Redesign of a Qwerty Keyboard Embedded in an Ultrasound Console

2000 ◽  
Vol 44 (26) ◽  
pp. 181-184
Author(s):  
Aline Baeck ◽  
Larry McCabe ◽  
Laura Militello
Keyword(s):  
User Interface ◽  
Continuous Improvement ◽  
Positive Response ◽  
Critical Issue ◽  
Evaluation Study ◽  
Anecdotal Evidence ◽  
Field Staff ◽  
Close Proximity ◽  
Ultrasound System ◽  
New System

A critical issue when designing a new ultrasound system is the design of the QWERTY keyboard, which is incorporated into the ultrasound console. The introduction by Acuson of a new system with improved imaging capabilities and an emphasis on the close proximity of frequently used controls was well-received by users. However, as part of Acuson's interest in continuous improvement of the user interface, feedback from field staff identified the QWERTY as having potential for improvement. This paper describes the issues explored in redesigning the QWERTY, an evaluation study to assess the benefits of potential redesign solutions, and the eventual solution implemented. Anecdotal evidence from our customers and field staff indicate a very positive response to the new QWERTY.

Characterization of Difference Size of IDE Pattern for Formaldehyde Detection Sensor

2015 ◽  
Vol 754-755 ◽  
pp. 917-922 ◽  
Author(s):  
M. Zaki ◽  
Uda Hashim ◽  
Mohd Khairuddin Md Arshad ◽  
M.F.M. Fathil ◽  
A.H. Azman ◽  
...  
Keyword(s):  
Gas Sensing ◽  
Low Cost ◽  
Electrical Characterization ◽  
Gas Detection ◽  
Si Substrate ◽  
Hard Mask ◽  
Large Size ◽  
Mask Design ◽  
The Ideal

This paper studies the effect of different gap sizes of IDE pattern on the surface morphology and electrical properties for the formaldehyde detection sensor. Two types of IDE chrome mask are designed to determine the ideal IDE pattern for formaldehyde gas detection by using conventional lithography. In the first method, IDE is transferred onto SiO2layer. In order to ensure that the perfect pattern with minimum defect structure is obtained, the process parameters should be optimized and controlled. In the second method, the aluminium is deposited directly on SiO2/Si substrate by using IDE hard mask design plate. The fabricated IDE pattern is further validated through morphological and electrical characterization. The average gap size of IDE sensor is approximately 100 μm and 400 μm for IDE chrome and IDE hard mask respectively. The latter method is preferable since for formaldehyde gas sensing large size is needed and moreover the process is simple and requires low cost. Characterization of difference IDE pattern is demonstrated by various measurements.

scholarly journals Implementing a new tuberculosis surveillance system in Zhejiang, Jilin and Ningxia: improvements, challenges and implications for China’s National Health Information System

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Wei-Xi Jiang ◽  
Fei Huang ◽  
Sheng-Lan Tang ◽  
Ni Wang ◽  
Xin Du ◽  
...  
Keyword(s):  
Information System ◽  
National Health ◽  
Surveillance System ◽  
Data Exchange ◽  
Data Extraction ◽  
Scale Up ◽  
Health Information System ◽  
Automatic Data ◽  
Technical Solutions ◽  
New System

Abstract Background China is still faced with the public health challenge of tuberculosis (TB), and a robust surveillance system is critical for developing evidence-based TB control policies. The Tuberculosis Information Management System (TBIMS), an independent system launched in 2005, has encountered several challenges in meeting the current needs of TB control. The Chinese government also planned to establish the National Health Information System (NHIS) aggregating data in different areas. The China National Health Commission-Gates TB Project Phase III launched a new TB surveillance system to address these challenges and also as a pilot for the countrywide implementation of the NHIS. This commentary highlights the improvements and challenges in implementing the new TB system and also discusses the implications for the roll-out of the NHIS. Main text The new TB surveillance system piloted in each prefecture of the project provinces was designed based on the local information system under the unified principle of organizing patient information under a unique ID and realizing the function of data exchange. Upon mid-2019, the data exchange successful rate reached almost 100%, and the system showed good performance in data completeness. Major improvements of the new system included achieving automatic data extraction instead of manual entry, assisting clinical service provision, and the augmented statistical functions. The major challenges in the implementation and scale-up of the new system were the licensing issue and the diversities of infrastructures that hinder the promotion of the new system at a low cost. This pilot also accumulated experiences for the roll-out of the NHIS regarding the technical solutions of reforming current information systems as well as effective training approaches for the developers and users of the new system. Conclusions The successful implementation of the new TB surveillance system in the three TB designated medical institutions demonstrated how the diverse infrastructures of the information system could be reformed to achieve the functions of automatic data extraction and data exchange and better cater to the needs of healthcare workers. This pilot also accumulated rich experiences and lessons learnt for developing technical solutions and personnel training for the scale-up of the NHIS.

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