Estimation of the Annual Greenhouse Gas Emissions from the Town Gas Distribution System in Hong Kong in 2022

Estimating leaks in urban gas distribution systems is crucial for reducing greenhouse gas emissions from fugitive losses and mitigating costly waste. This study aimed to use a simplified methodology to estimate pipeline leakage in gas distribution systems and validate these estimations against established benchmarks or other gases globally. The estimation encompassed sources including third-party damage, long-term permeation, flaring, and purging during pipeline commissioning and decommissioning, as well as fugitive leakage, each requiring respective evaluation. Results showed that the total town gas leakage volume was around 695,044 m3 to 2,009,991 m3, accounting for 0.045% to 0.13% of the total town gas sales in 2022. Among the five leakage sources, fugitive leakage was the major contributor with the leakage volume of 1,938,914 m3. To comprehensively benchmark all emission factors (EFs), those from previously reported studies were adapted to the town gas scenario and combined with the current activity factors (AFs) in Hong Kong to calculate the leakage amounts. Comparing our results with different models, we observed variations in estimated leakage amounts based on years, regions, and sampling methods. Upgrades in pipeline materials led to reduced EFs and subsequently lower total gas leakage. Our findings support efforts to reduce greenhouse gas emissions by providing actionable data for policymakers and utility companies to address gas leakage issues.

Authors

Institutions

Publication Details

Journal
Atmosphere
Published
2025-05-26
DOI
https://doi.org/10.3390/atmos16060643
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimation of the Annual Greenhouse Gas Emissions from the Town Gas Distribution System in Hong Kong in 2022

Daisong Chen, Jin Shang, Tat Leung Chan
Atmosphere
Atmospheric and Environmental Gas Dynamics
article

Estimation of the Annual Greenhouse Gas Emissions from the Town Gas Distribution System in Hong Kong in 2022

Daisong Chen, Jin Shang, Tat Leung Chan
article en

Abstract

Estimating leaks in urban gas distribution systems is crucial for reducing greenhouse gas emissions from fugitive losses and mitigating costly waste. This study aimed to use a simplified methodology to estimate pipeline leakage in gas distribution systems and validate these estimations against established benchmarks or other gases globally. The estimation encompassed sources including third-party damage, long-term permeation, flaring, and purging during pipeline commissioning and decommissioning, as well as fugitive leakage, each requiring respective evaluation. Results showed that the total town gas leakage volume was around 695,044 m3 to 2,009,991 m3, accounting for 0.045% to 0.13% of the total town gas sales in 2022. Among the five leakage sources, fugitive leakage was the major contributor with the leakage volume of 1,938,914 m3. To comprehensively benchmark all emission factors (EFs), those from previously reported studies were adapted to the town gas scenario and combined with the current activity factors (AFs) in Hong Kong to calculate the leakage amounts. Comparing our results with different models, we observed variations in estimated leakage amounts based on years, regions, and sampling methods. Upgrades in pipeline materials led to reduced EFs and subsequently lower total gas leakage. Our findings support efforts to reduce greenhouse gas emissions by providing actionable data for policymakers and utility companies to address gas leakage issues.

AtmosphereVol. 16(6)
City University of Hong Kong (HK)
City University of Hong Kong
Openalex Percentile: Top 88%
Atmospheric and Environmental Gas Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.