Atmospheric ammonia variability and link with PM formation: a case study over the Paris area
Bibliographic record
Abstract
Abstract. The Paris megacity experiences frequent particulate matter (PM2.5, PM with a diameter less than 2.5 μm) pollution episodes in springtime (March–April). At this time of the year, large parts of the particles consist of ammonium sulfate and nitrate which are formed from ammonia (NH3) released during fertilizer spreading practices and transported from the surrounding areas to Paris. There is still limited knowledge on the emission sources around Paris, their magnitude and seasonality. Using space-borne NH3 observation records of 10-years (2008–2017) and 5-years (2013–2017) provided by the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-Track Infrared Sounder (CrIS) instrument, regional pattern of NH3 variabilities (seasonal and inter-annual) are derived. Observations reveal identical high seasonal variabilities with three major NH3 hot spots found from March to August. The high inter-annual variability is discussed with respect to atmospheric total precipitation and temperature. A detailed analysis of the seasonal cycle is performed using both IASI and the CrIS instrument data, together with outputs from the CHIMERE atmospheric model. For months of high NH3 concentrations (March to August) the CHIMERE model shows good correspondence with correlation slopes of 0.98 and 0.71 when comparing with IASI and CrIS, respectively. It is found that the model is only able to reproduce half of the observed atmospheric temporal NH3 variability in the domain. In term of spatial variability, the CHIMERE monthly NH3 concentrations in springtime show a slight underrepresentation over Belgium and the United-Kingdom and overrepresentation in agricultural areas in the French Brittany/Pays de la Loire and Plateau du Jura region, as well as in the north part of Switzerland. Using HYSPLIT cluster analysis of back-trajectories, we show that NH3 total columns measured in spring over Paris are enhanced when air masses are originated from the Northeast (e. g., Netherlands and Belgium), highlighting the long-range transport importance on the NH3 budget over Paris. Finally, we quantify the key meteorological parameters driving the specific conditions important for the PM2.5 formation from NH3 in the Ile-de-France region in springtime. Data-driven results based on surface PM2.5 measurements from the Airparif network and IASI NH3 observations show that a combination of the factors, e. g. a low boundary layer of ~500 m, a relatively low temperature of 5 °C and a high relative humidity of 70 %, contributes to favor PM2.5 and NH3 correlation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".