{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T19:17:58Z","timestamp":1789759078910,"version":"4.0.1"},"reference-count":12,"publisher":"American Association for the Advancement of Science (AAAS)","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72474010"],"award-info":[{"award-number":["72474010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hangzhou Natural Science Foundation","award":["2025SZRJJ1809"],"award-info":[{"award-number":["2025SZRJJ1809"]}]},{"name":"Science and Technology Projects of Xizang Autonomous Region, China","award":["XZ202501ZY0072"],"award-info":[{"award-number":["XZ202501ZY0072"]}]}],"content-domain":{"domain":["spj.science.org"],"crossmark-restriction":true},"short-container-title":["Health Data Sci"],"published-print":{"date-parts":[[2026,1,1]]},"abstract":"<jats:p>\n                    In the Anthropocene, high-impact weather (HIW) events are increasingly compressing massive air pollution loads into narrow temporal windows, posing acute health risks that conventional environmental health frameworks were not designed to capture. Despite growing recognition of these dangers, critical gaps persist in the nowcasting of atmospheric health risks, as existing tools such as the air quality index (AQI) and the global burden of disease (GBD) framework remain anchored in chronic exposure paradigms and long-term concentration averages.\u00a0This manuscript focuses on a pressing standard-index paradox in China: While air quality guidelines\/standards (AQG\/AQS) are being tightened, the risk-communication AQIs have largely remained static, creating a widening gap in public health protection. As a pilot study, leveraging a recently developed global function between short-term PM\n                    <jats:sub>2.5<\/jats:sub>\n                    and cardiovascular mortality (CVD), we conducted a trade-off analysis across AQI cutoff values and identified that the lower boundary for moderately polluted events yields the highest leveraging efficiency. Under the prevailing ambient AQS, the optimal warning threshold is approximately 90 \u03bcg\/m\u00b3, suggesting that health-protective warnings should be extended to cover some slightly polluted days as well. These findings underscore that nowcasting the health risks of acute air pollution episodes is of substantial public health importance, and that a risk-based warning strategy should be considered to replace China\u2019s current AQI-based communication framework.\n                  <\/jats:p>","DOI":"10.34133\/hds.0460","type":"journal-article","created":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T05:05:26Z","timestamp":1782104726000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":1,"title":["Understudied Health Risks of High-Impact Pollution Weather: The Case for Revising Short-Term PM\n                    <sub>2.5<\/sub>\n                    Standard and Indexes"],"prefix":"10.34133","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0873-5992","authenticated-orcid":true,"given":"Pengfei","family":"Li","sequence":"first","affiliation":[{"name":"National Institute of Health Data Science, \rPeking University, Beijing 100191, China."},{"name":"Advanced Institute of Information Technology, \rPeking University, Hangzhou 311215, China."},{"name":"PKU-WUHAN Institute for Artificial Intelligence, Wuhan 430074, China."},{"name":"Institute for Artificial Intelligence, \rPeking University, Beijing 100871, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3519-3952","authenticated-orcid":true,"given":"Jingyi","family":"Wu","sequence":"additional","affiliation":[{"name":"Advanced Institute of Information Technology, \rPeking University, Hangzhou 311215, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongkang","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, \rPeking University Health Science Centre, Beijing 100191, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Xue","sequence":"additional","affiliation":[{"name":"Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, \rPeking University Health Science Centre, Beijing 100191, China."},{"name":"State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Centre for Environment and Health, \rPeking University, Beijing 100871, China."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"World Meteorological Organization. Early Warnings for All: The UN Global Early Warning Initiative for the Implementation of Climate Adaptation. 2022. https:\/\/earlywarningsforall.org\/site\/early-warnings-all."},{"key":"e_1_3_2_3_2","unstructured":"Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2021 (GBD 2021). Air Pollution Exposure Estimates and Risk Curves 1990-2021. 2024. https:\/\/ghdx.healthdata.org\/record\/ihme-data\/gbd-2021-air-pollution-exposure-estimates-1990-2021."},{"issue":"10440","key":"e_1_3_2_4_2","doi-asserted-by":"crossref","first-page":"2162","DOI":"10.1016\/S0140-6736(24)00933-4","article-title":"Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990\u20132021: A systematic analysis for the Global Burden of Disease Study 2021","volume":"403","author":"Brauer M","year":"2024","unstructured":"Brauer M, Roth GA, Aravkin AY, Zheng P, Abate KH, Abate YH, Abbafati C, Abbasgholizadeh R, Abbasi MA, Abbasian M, et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990\u20132021: A systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403(10440):2162\u20132203.","journal-title":"Lancet"},{"key":"e_1_3_2_5_2","unstructured":"World Health Organization. WHO global air quality guidelines: Particulate matter (PM2.5 and PM10) ozone nitrogen dioxide sulfur dioxide and carbon monoxide. 2021. https:\/\/www.who.int\/publications\/i\/item\/9789240034228."},{"issue":"11","key":"e_1_3_2_6_2","doi-asserted-by":"crossref","first-page":"101488","DOI":"10.1016\/j.oneear.2025.101488","article-title":"Improved global air quality health index reveals ozone and nitrogen dioxide as main drivers of air-pollution-related acute mortality","volume":"8","author":"Huang W","year":"2025","unstructured":"Huang W, Li T, Masselot P, Xu R, Gasparrini A, Sera F, Bell ML, Hashizume M, Breitner S, Tong S, et al. Improved global air quality health index reveals ozone and nitrogen dioxide as main drivers of air-pollution-related acute mortality. One Earth. 2025;8(11):101488.","journal-title":"One Earth"},{"key":"e_1_3_2_7_2","article-title":"Short-term PM2.5 exposure and cardiovascular mortality: A global exposure-response analysis to inform alert thresholds","author":"Yang Y","year":"2026","unstructured":"Yang Y, Deng J, Zhou P, Li P, Guan T, Xue T, Zhu T. Short-term PM2.5 exposure and cardiovascular mortality: A global exposure-response analysis to inform alert thresholds. J Am Coll Cardiol. 2026.","journal-title":"J Am Coll Cardiol"},{"key":"e_1_3_2_8_2","doi-asserted-by":"crossref","first-page":"e727","DOI":"10.1016\/S2542-5196(23)00189-4","article-title":"Air pollution and climate change","volume":"7","author":"Pinho-Gomes A-C","year":"2023","unstructured":"Pinho-Gomes A-C, Roaf E, Fuller G, Fowler D, Lewis A, ApSimon H, Noakes C, Johnstone P, Holgate S. Air pollution and climate change. Lancet Planet Heath. 2023;7:e727\u2013e728.","journal-title":"Lancet Planet Heath"},{"key":"e_1_3_2_9_2","doi-asserted-by":"crossref","DOI":"10.1016\/j.jenvman.2024.123517","article-title":"The declining effectiveness of air quality index in China: A perspective of air pollution alert system","volume":"373","author":"Yue J","year":"2025","unstructured":"Yue J, Zhang J, He Q, Jiang T, Li D. The declining effectiveness of air quality index in China: A perspective of air pollution alert system. J Environ Manag. 2025;373: Article 123517.","journal-title":"J Environ Manag"},{"key":"e_1_3_2_10_2","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.jes.2022.03.036","article-title":"Prospect of China\u2019s ambient air quality standards","volume":"123","author":"Wang Z","year":"2023","unstructured":"Wang Z, Tan Y, Guo M, Cheng M, Gu Y, Chen S, Wu X, Chai F. Prospect of China\u2019s ambient air quality standards. J Environ Sci. 2023;123:255\u2013269.","journal-title":"J Environ Sci"},{"key":"e_1_3_2_11_2","unstructured":"China\u2019s Ministry of Ecology and Environment. Ambient Air Quality Standards (GB 3095-2026). 2026. https:\/\/www.mee.gov.cn\/ywgz\/fgbz\/bz\/bzwb\/dqhjbh\/dqhjzlbz\/202602\/t20260225_1144419.shtml"},{"issue":"5","key":"e_1_3_2_12_2","doi-asserted-by":"crossref","first-page":"2101186","DOI":"10.1183\/13993003.01186-2021","article-title":"Moving beyond AUC: Decision curve analysis for quantifying net benefit of risk prediction models","volume":"58","author":"Sadatsafavi M","year":"2021","unstructured":"Sadatsafavi M, Adibi A, Puhan M, Gershon A, Aaron SD, Sin DD. Moving beyond AUC: Decision curve analysis for quantifying net benefit of risk prediction models. Eur Respir J. 2021;58(5):2101186.","journal-title":"Eur Respir J"},{"key":"e_1_3_2_13_2","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.ress.2015.05.003","article-title":"Reliability and effectiveness of early warning systems for natural hazards: Concept and application to debris flow warning","volume":"142","author":"S\u00e4ttele M","year":"2015","unstructured":"S\u00e4ttele M, Br\u00fcndl M, Straub D. Reliability and effectiveness of early warning systems for natural hazards: Concept and application to debris flow warning. Reliab Eng Syst Saf. 2015;142:192\u2013202.","journal-title":"Reliab Eng Syst Saf"}],"container-title":["Health Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/spj.science.org\/doi\/pdf\/10.34133\/hds.0460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T08:00:21Z","timestamp":1787644821000},"score":1,"resource":{"primary":{"URL":"https:\/\/spj.science.org\/doi\/10.34133\/hds.0460"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,1]]},"references-count":12,"alternative-id":["10.34133\/hds.0460"],"URL":"https:\/\/doi.org\/10.34133\/hds.0460","relation":{},"ISSN":["2765-8783"],"issn-type":[{"value":"2765-8783","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,1]]},"assertion":[{"value":"2026-04-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-03","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-21","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"0460"}}