Estimating Urban Scale Semi-volatile Organic Compound Emissions and Fate Using a Coupled Multimedia and Atmospheric Transport Model
Bibliographic record
Abstract
Cities are sources of persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs), to surrounding regions and beyond. A spatially resolved, (5×5 km2), dynamic contaminant fate model named Spatially Oriented or SO-MUM was developed by coupling the fugacity based Multimedia Urban Model (MUM) (Diamond et al., 2001; Diamond et al., 2010c) and the Boundary Layer Forecast Model and Air Pollution Prediction System (BLFMAPS) which was developed at Environment Canada (Daggupaty et al., 2006). MUM was updated to contain a revised surface film sub-model which takes into account the dynamic nature of surface films. SO-MUM was illustrated by application to the City of Toronto, Canada. Spatially resolved air emissions of Σ88PCB were estimated to be ~230 (40-480) kg y-1, 280 (50-580) g y-1 km-2, and 90 (16-190) mg y-1 capita-1 and Σ26PBDE were estimated to be 28 (6-63) kg y-1, 34 (7-77) g y-1 km-2 and 11 (2-25) mg y-1 capita-1. These emissions were back-calculated from measured air concentrations and spatial chemical mass inventories yielding emission rates per mass inventory of 0.4 (0.05-1.6) and 0.1 (0.01-0.7) g kg-1inventory y-1, for Σ88PCBs and Σ26PBDEs, respectively. Approximately 30% and 16% of PCB and PBDE emissions emanate from the city’s downtown. Air advection accounted for ~95% (PCB) and ~70% (PBDE) of total air emission losses with the remaining balance depositing to the city. The metric “Urban Travel Distance” or UTD was introduced for quantifying the extent of an urban plume resulting from spatially heterogeneous emissions. For PCBs and PBDEs the UTDs were ~25 and ~30 km. The updated surface film sub-model indicated that films “bounce” higher vapor pressure semi-volatile organic compounds (SVOCs) back into the air but they act as a transient sink from air for lower vapor pressure SVOCs, thereby facilitating transport to surface waters. Model calculations suggest that if the PCB inventory is reduced, volatilization from near-shore Lake Ontario will become a net source of PCBs to air, but that neither near-shore Lake Ontario nor soil would become a significant volatilization PBDE source to air.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".