Bibliographic record
Abstract
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].
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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 | 0.015 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.024 | 0.029 |
| Insufficient payload (model declined to judge) | 0.031 | 0.029 |
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".