Continuous Monitoring of Atmospheric Halocarbons with a Dewater-Thermo Desorption Unit and GC-ECD: Insights from Industrial and Urban Environments
Bibliographic record
Abstract
In the face of the complex composition of atmospheric pollutants, our laboratory has developed a Thermo Desorption Unit (TD) for capturing and concentrating trace-level volatile organic compounds (VOCs) in air samples. Because of the humid climate, we added a Dewater Unit (DW) before the TD to remove excess moisture from air samples while retaining polar and non-polar species to keep sample integrity. This setup has been successfully utilized in the past by connecting the DW-TD units with gas chromatography (GC) equipped with flame ionization detection (FID) and mass spectrometry (MS). While the data quality from GC-FID was extremely stable and robust, the drift and, thus, instability in MS is significant by comparison. In this research, we attempted to use electron capture detection (ECD) to test the stability of the DW-TD units by exploiting ECD’s high sensitivity, stability, and ease of operation. Another prominent advantage of ECD is that it only needs high-purity nitrogen gas as both the carrier and make-up gas. We exploited ECD's highly sensitive and selective properties to measure trace-level atmospheric chlorofluorocarbons (CFCs) and halocarbons to demonstrate the performance of the self-built DW-TD apparatuses. Since CFCs have extremely long atmospheric lifetimes and are well-mixed in the atmosphere due to the Montreal Protocol banning them from most applications, they exhibit certain background mixing levels during a relatively short period of time, e.g., weeks, with variability smaller than most GC’s analytical precisions. We then utilized this property to assess the stability of our homemade instrument. During the one-month continuous online analysis of DW-TD/GC-ECD at an industrial park known for semiconductor and electronics manufacturing, the mole fractions of CFC-12 was found to be 485.19±0.22 ppt (parts per trillion), with RSD (Relative Standard Deviations) = 0.06%. Although CFC-11, CFC-113, and CCl4 have long been phased out, abrupt rises in signal were still detected, suggesting emissions still existed in this industrial complex. By filtering out data with relatively stable mole fractions in between events, the RSD for CFC-11, CFC-113, and CCl4 was found to be 0.12%, 0.36%, and 0.30%, respectively. To further validate the high-value events observed in the industrial park, we conducted an additional one-month continuous online analysis of DW-TD/GC-ECD at a university campus in Taipei as a contrast of environment. This comparative study yielded stable background mole fractions for CFC-12, CFC-11, CFC-113, and CCl4, with RSD of 0.05%, 0.10%, 0.32%, and 0.29%, respectively. These results will be compared with the variability from AGAGE's online data using Medusa/GC-MS and the offline data of NOAA by GC-MS. The occurrence of the high-value events during the month-long measurements can be traced back to emission sources by utilizing backward trajectories to the potential sources for further investigation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".