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Record W3207538733 · doi:10.3389/ijph.2021.1604483

WHO Air Quality Guidelines Need to be Adopted

2021· editorial· en· W3207538733 on OpenAlexfundno aff
Heresh Amini

Bibliographic record

VenueInternational Journal of Public Health · 2021
Typeeditorial
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersNovo Nordisk FondenUniversity of British ColumbiaNovo Nordisk
KeywordsPublic healthEnvironmental healthQuality (philosophy)Political scienceMedicineNursing

Abstract

fetched live from OpenAlex

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].

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.031
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.071
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.001
Science and technology studies0.0030.003
Scholarly communication0.0110.008
Open science0.0040.002
Research integrity0.0240.029
Insufficient payload (model declined to judge)0.0310.029

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.

Opus teacher head0.206
GPT teacher head0.474
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations23
Published2021
Admission routes1
Has abstractyes

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