{"title":"基于测量的排放评估和减少,通过加速检测和修复天然气分配网络中的大泄漏","authors":"Sean MacMullin , François-Xavier Rongère","doi":"10.1016/j.aeaoa.2023.100201","DOIUrl":null,"url":null,"abstract":"<div><p>A common practice within the current regulatory framework for gas distribution uses an approach where operators report their network emissions by applying an average emission factor for all leaks, sometimes sorted by pipe material and type of assets. Such an approach has two drawbacks: first, it does not account for the specificities of the gas systems and the maintenance processes of the operators; and second, it does not enable the prioritization of large leaks that is key for an effective emissions abatement program. This article describes a method using a mobile leak detection and quantification system to assess methane emissions from a gas distribution network and to reduce them by accelerating the detection and repair of larger leaks. The approach allows for data-driven system-wide emissions quantification that is specific to the network and not subject to operator’s leak detection practices that may affect their traditional emission factor-based reporting. Furthermore, we show that for a sensor with a sufficiently low detection limit, the calculated emissions are independent of the precision of the measurement if the uncertainties are correctly addressed. Such a result is important because it assures that methane emissions estimates are not biased and can be used to assess the performance of abatement programs. Finally, we illustrate how the approach can be practically implemented through a program where the largest leaks are rapidly identified and repaired to abate methane emissions while minimizing costs.</p></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measurement-based emissions assessment and reduction through accelerated detection and repair of large leaks in a gas distribution network\",\"authors\":\"Sean MacMullin , François-Xavier Rongère\",\"doi\":\"10.1016/j.aeaoa.2023.100201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A common practice within the current regulatory framework for gas distribution uses an approach where operators report their network emissions by applying an average emission factor for all leaks, sometimes sorted by pipe material and type of assets. Such an approach has two drawbacks: first, it does not account for the specificities of the gas systems and the maintenance processes of the operators; and second, it does not enable the prioritization of large leaks that is key for an effective emissions abatement program. This article describes a method using a mobile leak detection and quantification system to assess methane emissions from a gas distribution network and to reduce them by accelerating the detection and repair of larger leaks. The approach allows for data-driven system-wide emissions quantification that is specific to the network and not subject to operator’s leak detection practices that may affect their traditional emission factor-based reporting. Furthermore, we show that for a sensor with a sufficiently low detection limit, the calculated emissions are independent of the precision of the measurement if the uncertainties are correctly addressed. Such a result is important because it assures that methane emissions estimates are not biased and can be used to assess the performance of abatement programs. Finally, we illustrate how the approach can be practically implemented through a program where the largest leaks are rapidly identified and repaired to abate methane emissions while minimizing costs.</p></div>\",\"PeriodicalId\":37150,\"journal\":{\"name\":\"Atmospheric Environment: X\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Environment: X\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590162123000011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Environment: X","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590162123000011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Measurement-based emissions assessment and reduction through accelerated detection and repair of large leaks in a gas distribution network
A common practice within the current regulatory framework for gas distribution uses an approach where operators report their network emissions by applying an average emission factor for all leaks, sometimes sorted by pipe material and type of assets. Such an approach has two drawbacks: first, it does not account for the specificities of the gas systems and the maintenance processes of the operators; and second, it does not enable the prioritization of large leaks that is key for an effective emissions abatement program. This article describes a method using a mobile leak detection and quantification system to assess methane emissions from a gas distribution network and to reduce them by accelerating the detection and repair of larger leaks. The approach allows for data-driven system-wide emissions quantification that is specific to the network and not subject to operator’s leak detection practices that may affect their traditional emission factor-based reporting. Furthermore, we show that for a sensor with a sufficiently low detection limit, the calculated emissions are independent of the precision of the measurement if the uncertainties are correctly addressed. Such a result is important because it assures that methane emissions estimates are not biased and can be used to assess the performance of abatement programs. Finally, we illustrate how the approach can be practically implemented through a program where the largest leaks are rapidly identified and repaired to abate methane emissions while minimizing costs.