Methane emission reduction in China's natural gas industry: Construction of technology inventory and selection of optimal technology programs

SUSTAINABLE PRODUCTION AND CONSUMPTION(2024)

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摘要
Methane (CH4) is a potent yet short-lived greenhouse gas (GHG), and CH4 emissions from China's natural gas industry hinder its low-carbon and high-quality development. This paper addressed this challenge by compiling emission reduction technology inventory targeting CH4 emissions from process and vented within the natural gas industry. Using a multi-objective optimization model and the NSGA-II algorithm, various technology programs were generated to minimize both emissions and costs simultaneously. These programs underwent classification using quadrants and the osculating value method to identify optimal programs for emission reduction and costeffectiveness. This paper examined 30 potential programs as samples for upstream and midstream. The study demonstrated that for decision-makers with preferences, this paper employed quadrant classification, categorizing all potential programs into three categories: "emission reduction," "cost," and "comprehensive." This categorization met the demand preferences of different decision-makers. For decision-makers lacking specific preferences, the paper identified the best emission reduction technology programs under the current target using the osculating value method. Specifically, in the upstream, the most effective program achieved a 37.85 % reduction in emissions, highlighting "Reduced Emissions Completions for Hydraulically Fractured Gas Wells" as the critical technology. In the midstream, the best program achieved a reduction efficiency of 25.80 %, with "Replacing Wet Seals with Dry Seals in Centrifugal Compressors" contributing the most to emissions reduction. This study offers guidance and illuminating reference cases for the selection of CH4 emission reduction technologies within China's natural gas industry.
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关键词
Natural gas,Methane,Emission reduction technology,Multi -objective optimization,NSGA-II algorithm,Osculating value method
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