Impact of NH3 Emissions on Particulate Matter Pollution in South Korea: A Case Study of the Seoul Metropolitan Area
Why this work is in the frame
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Bibliographic record
Abstract
We analyzed the multi-year relationship between particulate matter (PM10 and PM2.5) concentrations and possible precursors including NO2, SO2, and NH3 based on local observations over the Seoul Metropolitan Area (SMA) from 2015 to 2017. Surface NH3 concentrations were obtained from Cross-track Infrared Sounder (CrIS) retrievals, while other pollutants were observed at 142 ground sites. We found that NH3 had the highest correlation with PM2.5 (R = 0.51) compared to other precursors such as NO2 and SO2 (R of 0.16 and 0.14, respectively). The correlations indicate that NH3 emissions are likely a limiting factor in controlling PM2.5 over the SMA in a high-NOx environment. This implies that the current Korean policy urgently requires tools for controlling local NH3 emissions from the livestock industry (for example, from hog manure). These findings provide the first satellite-based trace gas evidence that implementing an NH3 control strategy could play a key role in improving air quality in the SMA.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it