Notice bibliographique
Résumé
It is very well known that air pollution causes death, and a wide spectrum of health conditions, with considerable burden for the world's population [1].There is evidence also for the association of air pollution with SARS-CoV-2 transmission, COVID-19 infection severity, and its mortality [2][3][4].The World Health Organization (WHO) has launched air quality guidelines (AQG) 2021 about 15 years after 2005 AQGs for short-and long-term exposure to a range of air pollutants, such as particulate matter (PM 2.5 and PM 10 ), ozone (O 3 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ) and carbon monoxide (CO) [5].In brief, most 2021 AQGs are lower compared to 2005 using updated WHO methodology, and given the fact that new evidence shows health effects occur even at lower exposure levels [6][7][8].The updated WHO AQGs are based on thorough systematic reviews and meta-analyses of evidence up to mid-2020 [5].Of notable updates, the 2021 AQG compared to 2005 for annual mean exposure to PM 2.5 reduced from 10 to 5 µg/m 3 , PM 10 reduced from 20 to 15, and NO 2 reduced from 40 to 10 µg/ m 3 .Furthermore, there is new 2021 AQG for peak season O 3 (60 µg/m 3 ) and 24-hour exposure to CO (4 mg/m 3 ).The AQG for 24-hour exposure to SO 2 increased from 20 µg/ m 3 in 2005 to 40 µg/m 3 in 2021, which is due to updated evidence and methodology for AQGs.Amongst other updates, the 2021 AQGs also provide good practice statements for certain types of PM, such as black carbon/elemental carbon, ultrafine particles, and dust-and sandstorms.It is notable that WHO AQGs further provide Interim Targets (ITs) for most pollutants for stepwise progress towards achieving the AQGs.As WHO emphasized, it is very important to note that the 2005 WHO AQGs remain valid for pollutants and those averaging times not covered in 2021 update [5].As shown in Figure 1, it is evident that there is inequality in exposure to air pollution across the world with low-and middle-income countries (LMICs) experiencing higher exposure levels for most pollutants.Currently, large world populated areas do not meet the WHO AQG 2021 for annual mean exposure to PM 2.5 , annual mean NO 2 , and seasonal maximum O 3 , and many countries are even in a position that need to consider IT1 for PM 2.5 (35 µg/m 3 ) as the first step to achieve, which is indeed challenging.NO 2 is considerably higher within urban areas, and ground level O 3 has high values across the Middle East and India (Figure 1).The WHO AQGs 2021 have important implications for WHO member states and public health.With the launch of WHO AQGs 2021, WHO has provided the member states with a tool that need to be adopted to protect public health from air pollution as a so-called "silent killer."As stated in a joint statement by Hoffmann et al. [12], which is endorsed by more than hundred medical, public health, scientific and patient representative societies, such as European Respiratory Society (ERS) and the International Society of Environmental Epidemiology (ISEE), immediate action is needed to use these guidelines for emission reduction policy making and adopt these science-based guidelines and interim targets as national air quality standards.Clearly, healthy lungs and healthy hearts need clean air [3,13].
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,015 | 0,071 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,011 | 0,008 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,024 | 0,029 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 0,029 |
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 ».