Performance Evaluation of Fixed-Point Continuous Monitoring Systems: Influence of Averaging Time in Complex Emission Environments
Quantifying methane emissions from facilities with complex emissions profiles can present a substantial challenge. Real-world emission scenarios can involve dynamic operational background emissions and temporally overlapping asynchronous emission events with varying rates from multiple sources. Prev...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/9/2801 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Quantifying methane emissions from facilities with complex emissions profiles can present a substantial challenge. Real-world emission scenarios can involve dynamic operational background emissions and temporally overlapping asynchronous emission events with varying rates from multiple sources. Previous studies have involved simpler testing setups, often with synchronous emission sources and constant rates. This work is among the first to assess the performance of continuous monitoring systems (CMSs) under dynamic, overlapping emission scenarios with time-varying baselines. The data were collected as part of a novel single-blind controlled release study, where release sources and emission rates are not disclosed during the testing period. Several error metrics are defined and evaluated across a range of relevant averaging times, demonstrating that despite significant error variance in short-duration estimates, the low bias of the system results in substantially improved emission estimates when aggregated to longer timescales. Over the 4-week duration of this study, 700 kg of methane was released by the testing center, while the estimated quantity shows a final mass of 673 kg, an underestimation by 27 kg (4%). These results demonstrate that advanced CMSs can accurately quantify cumulative site-level emissions in complex scenarios, highlighting their potential for enhanced future emissions monitoring and regulatory applications in the oil and gas sector. |
|---|---|
| ISSN: | 1424-8220 |