ArticlePNAS nexus2026
Significant benefits of pollution alerts for cleaner air and better health.
Article in PNAS nexus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
While air quality has improved in many cities, short-term spikes in urban pollution continue to cause elevated health risks. To mitigate such risks, pollution alerts trigger short-term interventions (e.g. temporary industrial curtailments or shutdowns, on-road traffic restrictions, construction bans with dust control, and public health advisories) to rapidly cut emissions and exposure. However, the effectiveness of such alerts has remained uncertain. Here, we analyzed air quality and weather data from 57 cities across northern China between 2018 and 2022 and used a two-step machine learning chain to predict counterfactual concentrations under a no-alert (no-intervention) scenario. Our findings show that interventions enacted under alerts effectively reduced pollutant concentrations, with particulate matter (PM) decreasing by 20-40% and nitrogen dioxide (NO
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.