Investigation of NO <sub>x</sub> emissions and NO <sub>x</sub> -related chemistry in East Asia using CMAQ-predicted and GOME-derived NO <sub>2</sub> columns
Bibliographic record
Abstract
Abstract. In this study, NO2 columns from the US EPA Models-3/CMAQ model simulations carried out using the 2001 ACE-ASIA (Asia Pacific Regional Aerosol Characterization Experiment) emission inventory over East Asia were compared with the GOME-derived NO2 columns. There were large discrepancies between the CMAQ-predicted and GOME-derived NO2 columns in the fall and winter seasons. In particular, while the CMAQ-predicted NO2 columns produced larger values than the GOME-derived NO2 columns over South Korea for all four seasons, the CMAQ-predicted NO2 columns produced smaller values than the GOME-derived NO2 columns over North China for all seasons with the exception of summer (summer anomaly). It is believed that there might be some error in the NOx emission estimates as well as uncertainty in the NOx chemical loss rates over North China and South Korea. Regarding the latter, this study further focused on the biogenic VOC (BVOC) emissions that were strongly coupled with NOx chemistry during summer in East Asia. This study also investigated whether the CMAQ-modeled NO2/NOx ratios with the possibly overestimated isoprene emissions were higher than those with reduced isoprene emissions. Although changes in both the NOx chemical loss rates and NO2/NOx ratios from CMAQ-modeling with the different isoprene emissions affected the CMAQ-modeled NO2 levels, the effects were found to be limited, mainly due to the low absolute levels of NO2 in summer. Seasonal variations of the NOx emission fluxes over East Asia were further investigated by a set of sensitivity runs of the CMAQ model. Although the results still exhibited the summer anomaly possibly due to the uncertainties in both NOx-related chemistry in the CMAQ model and the GOME measurements, it is believed that consideration of both the seasonal variations in NOx emissions and the correct BVOC emissions in East Asia are critical. Overall, it is estimated that the NOx emissions are underestimated by ~57.3% in North China and overestimated by ~46.1% in South Korea over an entire year. In order to confirm the uncertainty in NOx emissions, the NOx emissions over South Korea and China were further investigated using the ACE-ASIA, REAS (Regional Emission inventory in ASia), and CAPSS (Clean Air Policy Support System) emission inventories. The comparison between the CMAQ-calculated and GOME-derived NO2 columns indicated that both the ACE-ASIA and REAS inventories have some uncertainty in NOx emissions over North China and South Korea, which can also lead to some errors in modeling the formation of ozone and secondary aerosols in South Korea and North China.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".