Particle and VOC emission factor measurements for anthropogenic sources in West Africa
Bibliographic record
Abstract
A number of campaigns have been carried out to establish the emission factors of pollutants from fuel combustion in West Africa, as part of work package 2 (“Air Pollution and Health”) of the DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) FP7 program. Emission sources considered here include wood (hevea and iroko) and charcoal burning, charcoal making, open trash burning, and vehicle emissions, including trucks, cars, buses and two-wheeled vehicles. Emission factors of total particulate matter (TPM), elemental carbon (EC), primary organic carbon (OC) and volatile organic compounds (VOCs) have been established. In addition, emission factor measurements were performed in combustion chambers in order to reproduce field burning conditions for a tropical hardwood (hevea), and obtain particulate emission factors by size (PM 0.25 , PM 1 , PM 2.5 and PM 10 ). Particle samples were collected on quartz fiber filters and analyzed using gravimetric method for TPM and thermal methods for EC and OC. The emission factors of 58 VOC species were determined using offline sampling on a sorbent tube. Emission factor results for two species of tropical hardwood burning of EC, OC and TPM are 0.98 ± 0.46 g kg −1 of fuel burned (g kg −1 ), 11.05 ± 4.55 and 41.12 ± 24.62 g kg −1 , respectively. For traffic sources, the highest emission factors among particulate species are found for the two-wheeled vehicles with two-stroke engines (2.74 g kg −1 fuel for EC, 65.11 g kg −1 fuel for OC and 496 g kg −1 fuel for TPM). The largest VOC emissions are observed for two-stroke two-wheeled vehicles, which are up to 3 times higher than emissions from light-duty and heavy-duty vehicles. Isoprene and monoterpenes, which are usually associated with biogenic emissions, are present in almost all anthropogenic sources investigated during this work and could be as significant as aromatic emissions in wood burning (1 g kg −1 fuel). EC is primarily emitted in the ultrafine fraction, with 77 % of the total mass being emitted as particles smaller than 0.25 µm. The particles and VOC emission factors obtained in this study are generally higher than those in the literature whose values are discussed in this paper. This study underlines the important role of in situ measurements in deriving realistic and representative emission factors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".