Response of particle number concentrations to Clean Air Action: Lessons from the first long-term aerosol measurements in a typical urban valley, West China
Notice bibliographique
Résumé
Abstract. The strictest ever Clean Air Action (CAA) has been implemented by Chinese government since 2013 to alleviate the severe haze pollution. The PM2.5 mass concentration was found to be largely reduced in response to emission mitigation policies, but response of particle number concentrations (PNCs) to CAA was less evaluated in the previous studies, which may be largely different from PM2.5 mass due to newly formed particle impacts. In this work, the first in-situ observation of particle number size distributions (PNSDs) during 2012–2019 in urban Lanzhou was used to analyze long-term PNCs variations and CAA impacts. The average number of particles in nucleation (N13–25, particle number in the size range of 13–25 nm), Aitken (N25–100, particle number in the size range of 25–100 nm) and accumulation (N100–800, particle number in the size range of 100–800 nm) modes were respectively 2514.0 cm−3, 10768.7 cm−3, and 3258.4 cm−3, and N25–100 accounted for about 65.1 % of total PNCs during the campaign. K-means clustering technique was used to classify the hourly mean PNSDs into six clusters, and each cluster corresponded to a specific source and influencing factor. The polluted clusters governed the winter PNCs before 2016, and their occurrence was less and less frequent after 2016, which was largely dominated by reduction in primary emissions. However, the contribution of new particle formation (NPF) events to summer N13–25 decreased from 50 % to about 10 % during 2013 to 2015, and then increased to reach around 60 % in 2019. The trends of size-resolved PNCs for each cluster were quantified by Theil-Sen regression. The size-segregated PNCs exhibited downward trends for all clusters during 2012–2015, especially in spring. The annual relative slopes of spring PNCs varied from −54.7 % to −17.2 %, −42.6 % to −14.1 %, and −40.7 % to −17.5 % per year for 13–25, 25–100, and 100–800 nm size ranges, and the reduction in the polluted clusters was much larger than NPF clusters. The ultrafine particle number was increased and the amplitude was much greater during 2016–2019. The annual relative slopes of N13–25 varied between 8.0 % in fall and 135.5 % in spring for NPF cluster. In response to CAA, the increased daytime net radiation, higher ambient temperature and lower relative humidity at noon for NPF events also could partly explain the higher N13–25 induced by the more frequent nucleation events after 2016, especially in spring. The air mass were mainly from the adjacent regions of urban Lanzhou and less affected by long-range transport for NPF events, and the thus particles were not easily grown by coagulation during transport processes, which was helpful for occurrence of NPF events. Therefore, some effective control measures cooperatively controlled particle number and mass should be took for the Chinese megacities.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».