Application of ARPS–CMAQ modeling system for urban air pollutant emission abatement
Bibliographic record
Abstract
A coupled advanced regional prediction system – community multi-scale air quality (ARPS – CMAQ) modeling system was applied to develop an abatement strategy for air pollutant emission in the Handan region of the northern China. The system was evaluated by comparing the simulated concentrations of particulate matter less than 10 µm (PM10) with the observed results in the study area during the four representative months in 2005. A process of planning emission abatement was applied by gradually reducing PM10 emissions from the original GIS-based emission inventory until a modeling emission scenario was obtained under which the simulated PM10 concentrations could satisfy the desired air quality objective. The air quality objective was represented by an air quality guideline satisfaction ratio of 80% to reach a daily PM10 concentration of 150 µg/m3 after the year 2010. The modeling system and results could provide sound basis for decision makers to develop an effective air quality management strategy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".