| [1] | Marinho-Reis P, Entwistle JA, Hursthouse AS, et al. Perspectives on environment and human health: an editorial. Geosciences, 2022; 12, 408. doi: 10.3390/geosciences12110408 |
| [2] | Drakvik E, Altenburger R, Aoki Y, et al. Statement on advancing the assessment of chemical mixtures and their risks for human health and the environment. Environ Int, 2020; 134, 105267. doi: 10.1016/j.envint.2019.105267 |
| [3] | Sun YH, Zhu BC. Study on legal system of environmental health risk assessment in the United States. J Jishou Univ (Soc Sci), 2018; 39, 15−25. (In Chinese) |
| [4] | Campbell MJ. Environmental epidemiology: risk assessment. J Roy Stat Soc, 1984; 147, 115−6. |
| [5] | Teorell T. Kinetics of distribution of substances administered to the body, Ⅰ: the extravascular modes of administration. Arch Int Pharmacodyn et Ther, 1937; 57, 205−25. |
| [6] | Teorell T. Kinetics of distribution of substances administered to the body, Ⅱ: the intravascular modes of administration. Arch Int Pharmacodyn et Ther, 1937; 57, 226−40. |
| [7] | United Nations Environment Programme. Stockholm convention on persistent organic pollutants (POPs). https://chm.pops.int/. [2025-05-19]. |
| [8] | United Nations Environment Programme. Rotterdam convention on the prior informed consent procedure for certain hazardous chemicals and pesticides in international trade. https://www.pic.int/. [2025-05-19]. |
| [9] | Shi XX, Wang ZZ, Sun XL, et al. Toxicological data bank bridges the gap between environmental risk assessment and green organic chemical design in One Health world. Green Chem, 2023; 25, 2170−219. doi: 10.1039/D2GC03973G |
| [10] | Besse H, Rojas-Rueda D. Environmental justice mapping tools in the United States: a review of national and state tools. Sci Total Environ, 2025; 962, 178449. doi: 10.1016/j.scitotenv.2025.178449 |
| [11] | Ministry of Ecology and Environment of the People’s Republic of China. List of priority new pollutants for control (2023 version). https://www.mee.gov.cn/gzk/gz/202212/t20221230_1009192.shtml. [2025-05-19]. (In Chinese) |
| [12] | State Council of the People’s Republic of China. People’s Republic of China the fourteenth five-year plan for national economic and social development and outline of long-term goals to 2035. https://www.gov.cn/xinwen/2021-03/13/content_5592681.htm. [2025-05-19]. (In Chinese) |
| [13] | James AK, Nehzati S, Dolgova NV, et al. Rethinking the minamata tragedy: what mercury species was really responsible?. Environ Sci Technol, 2020; 54, 2726−33. doi: 10.1021/acs.est.9b06253 |
| [14] | Zhu HW, Jia YB. Analysis of soft law nature of "Scientific Standard" in American administrative litigation-taking "Benzene Pollution" Case in 1980 as an example. Legal Syst Soc, 2017; 8, 51−3. (In Chinese) |
| [15] | National Research Council (US) Committee on the Institutional Means for Assessment of Risks to Public Health. Risk assessment in the federal government: managing the process. National Academies Press. 1983. |
| [16] | United States Environmental Protection Agency. Risk assessment and management: framework for decision making. Chicago: United States Environmental Protection Agency, 1984. https://nepis.epa.gov/Exe/ZyPDF.cgi/20008KTF.PDF?Dockey=20008KTF.PDF. [2025-03-25]. |
| [17] | Li CM, Zhang LL, Zheng YT, et al. Reference for China from Japan’s environmental management of chemicals. Mod Chem Ind, 2019; 39, 1−4. (In Chinese) |
| [18] | Critser R, Locke P. How should the 3 R’s be revised and why?. AMA J Ethics, 2024; 26, E724−9. doi: 10.1001/amajethics.2024.724 |
| [19] | United States Environmental Protection Agency. Basic information about the integrated risk information system. https://www.epa.gov/iris/basic-information-about-integrated-risk-information-system. [2025-03-25]. |
| [20] | European Chemicals Agency. EINECS: European inventory of existing commercial chemical substances. http://publications.europa.eu/resource/cellar/96869ff3-4bd7-4f81-bb78-b75d88108df8.0001.02/DOC_1. [2025-04-06]. |
| [21] | Vainio H, Coleman M, Wilbourn J. Carcinogenicity evaluations and ongoing studies: the IARC databases. Environ Health Perspect, 1991; 96, 5−9. doi: 10.1289/ehp.91965 |
| [22] | Organisation for Economic Co-operation and Development. Test No. 401: acute oral toxicity. https://doi.org/10.1787/9789264040113-en. [2025-05-19]. |
| [23] | Menditto A, Ouane-Keita F, Chiodo F, et al. Critical selection of toxicological data on chemicals. The example of the international register of potentially toxic chemicals data bank. Ann Ist Super Sanita, 1994; 30, 425−31. |
| [24] | United States Environmental Protection Agency. Risk assessment guidance. https://www.epa.gov/risk/risk-assessment-guidance. [2025-05-09]. |
| [25] | Japanese Ministry of Economy TaIM, Ti. Act on the evaluation of chemical substances and the regulation of their manufacture. https://www.meti.go.jp/policy/chemical_management/kasinhou/index.html. [2025-04-06]. |
| [26] | Armstrong V, Karyakina NA, Nordheim E, et al. Overview of REACH: issues involved in the registration of metals. NeuroToxicology, 2021; 83, 186−98. doi: 10.1016/j.neuro.2020.01.010 |
| [27] | Taylor K. Ten Years of REACH - an animal protection perspective. Altern Lab Anim, 2018; 46, 347−73. doi: 10.1177/026119291804600610 |
| [28] | Krewski D, Acosta D Jr, Andersen M, et al. Toxicity testing in the 21st century: a vision and a strategy. J Toxicol Environ Health, Part B, 2010; 13, 51−138. doi: 10.1080/10937404.2010.483176 |
| [29] | European Chemicals Agency. Practical guide - how to use and report (Q)SARs. https://echa.europa.eu/documents/10162/7250/pg_report_qsars_en.pdf/407dff11-aa4a-4eef-a1ce-9300f8460099. [2025-05-09]. |
| [30] | Kim D, Cho S, Jeon JJ, et al. Inhalation toxicity screening of consumer products chemicals using OECD test guideline data-based machine learning models. J Hazard Mater, 2024; 478, 135446. doi: 10.1016/j.jhazmat.2024.135446 |
| [31] | EFSA Scientific Committee, More SJ, Bampidis V, et al. Guidance on harmonised methodologies for human health, animal health and ecological risk assessment of combined exposure to multiple chemicals. EFSA J, 2019; 17, e05634. |
| [32] | United States Environmental Protection Agency. Guidance for applying quantitative data to develop data-derived extrapolation factors for interspecies and intraspecies extrapolation. 2014. https://www.epa.gov/sites/default/files/2015-01/documents/ddef-finalpdf. [2025-05-09]. |
| [33] | European Commission. Enhanced exposure assessment and omic profiling for high priority environmental exposures in Europe. https://cordis.europa.eu/project/id/308610/reporting. [2025-04-06]. |
| [34] | United Nations Environment Programme. Global chemicals outlook II summary for policymakers: from legacies to innovative solutions: implementing the 2030 agenda for sustainable development. https://www.saicm.org/Portals/12/Documents/meetings/OEWG3/inf/OEWG3-INF-3%20GCOII-Summary.pdf. [2025-04-06]. |
| [35] | Peng JJ, Bao ZJ, Li JY, et al. DeepRisk: a deep learning approach for genome-wide assessment of common disease risk. Fundam Res, 2024; 4, 752−60. doi: 10.1016/j.fmre.2024.02.015 |
| [36] | United Nations Environment Programme. The global water quality database GEMStat. https://wbwaterdata.org/dataset/the-global-water-quality-database-gemstat. [2025-04-07]. |
| [37] | United States Environmental Protection Agency. TRI pollution prevention (P2) search. https://enviro.epa.gov/envirofacts/tri/p2/p2-search. [2025-04-07]. |
| [38] | Li JY, Hosegood I, Powell D, et al. A global aircraft-based wastewater genomic surveillance network for early warning of future pandemics. Lancet Glob Health, 2023; 11, e791−5. |
| [39] | Linares C, Martinez GS, Kendrovski V, et al. A new integrative perspective on early warning systems for health in the context of climate change. Environ Res, 2020; 187, 109623. doi: 10.1016/j.envres.2020.109623 |
| [40] | Huang L, Duan QN, Liu YX, et al. Artificial intelligence: a key fulcrum for addressing complex environmental health issues. Environ Int, 2025; 198, 109389. doi: 10.1016/j.envint.2025.109389 |
| [41] | Qiu YN, Mintenig S, Barchiesi M, et al. Using artificial intelligence tools for data quality evaluation in the context of microplastic human health risk assessments. Environ Int, 2025; 197, 109341. doi: 10.1016/j.envint.2025.109341 |
| [42] | Weichert FG, Inostroza PA, Ahlheim J, et al. AI-aided chronic mixture risk assessment along a small European river reveals multiple sites at risk and pharmaceuticals being the main risk drivers. Environ Int, 2025; 197, 109370. doi: 10.1016/j.envint.2025.109370 |
| [43] | Wittwehr C, Blomstedt P, Gosling JP, et al. Artificial intelligence for chemical risk assessment. Comput Toxicol, 2020; 13, 100114. doi: 10.1016/j.comtox.2019.100114 |
| [44] | Sari OF, Amer E, Bader-El-Den M, et al. AI-driven risk assessment in food safety using EU RASFF database. Food Bioprocess Technol, 2025; 18, 6282−303. doi: 10.1007/s11947-025-03819-4 |
| [45] | Bhowmik RT, Most SP. A personalized respiratory disease exacerbation prediction technique based on a novel spatio-temporal machine learning architecture and local environmental sensor networks. Electronics, 2022; 11, 2562. doi: 10.3390/electronics11162562 |
| [46] | European Chemicals Agency. Guidance on information requirements and chemical safety assessment chapter R. 6: QSARs and grouping of chemicals. Guidance for the Implementation of REACH. https://echa.europa.eu/documents/10162/17224/information_requirements_r6_en.pdf/77f49f81-b76d-40ab-8513-4f3a533b6ac9. [2025-05-09]. |
| [47] | EFSA Scientific Committee, More SJ, Bampidis V, et al. Guidance on the use of the threshold of toxicological concern approach in food safety assessment. ESFA J, 2019; 17, e05708. |
| [48] | Organisation for Economic Co-operation and Development. Guidance document on the characterisation, validation and reporting of Physiologically Based Kinetic (PBK) models for regulatory purposes. 2021. https://doi.org/10.1787/d0de241f-en. [2025-05-09]. |
| [49] | European Commission. Animal-free safety assessment of chemicals: project cluster for implementation of novel strategies (ASPIS). https://aspis-cluster.eu/. [2025-05-09]. |
| [50] | EFSA Scientific Committee, More S, Bampidis V, et al. Scientific committee guidance on appraising and integrating evidence from epidemiological studies for use in EFSA’s scientific assessments. EFSA J, 2024; 22, e8866. |
| [51] | European Chemicals Agency. Guidance on information requirements and chemical safety assessment. https://echa.europa.eu/guidance-documents/guidance-on-information-requirements-and-chemical-safety-assessment. [2025-05-09]. |
| [52] | European Commission. EU action plan: 'towards zero pollution for air, water and soil'. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52021DC0400. [2025-05-09]. |
| [53] | European Commission. An integrated European ‘flagship’ program driving mechanism-based toxicity testing and risk assessment for the 21st century. https://cordis.europa.eu/project/id/681002/reporting. [2025-03-31]. |
| [54] | United States Environmental Protection Agency. ORD staff handbook for developing IRIS assessments. https://iris.epa.gov/Document/&deid=356370. [2025-03-31]. |
| [55] | United States Environmental Protection Agency. EPA: IRIS chemicals. https://comptox.epa.gov/dashboard/chemical-lists/iris. [2025-03-31]. |
| [56] | National Research Council, Division on Earth and Life Studies, Board on Environmental Studies and Toxicology, et al. Science and decisions: advancing risk assessment. National Academies Press. 2009. |
| [57] | Phanumartwiwath A, Liana D, Duan HX. Association of environmental phenol and paraben exposure with allergic biomarkers in eczema: findings from NHANES 2005-2006. Arch Dermatol Res, 2025; 317, 452. doi: 10.1007/s00403-025-03981-x |
| [58] | Calafat AM, Wong LY, Kuklenyik Z, et al. Polyfluoroalkyl chemicals in the U. S. population: data from the national health and nutrition examination survey (NHANES) 2003-2004 and comparisons with NHANES 1999-2000. Environ Health Perspect, 2007; 115, 1596−602. doi: 10.1289/ehp.10598 |
| [59] | Centers for Disease Control and Prevention. National health and nutrition examination survey. https://www.cdc.gov/nchs/nhanes/index.html. [2025-05-09]. |
| [60] | Zhang M, Lu Y, Wu ZZ, et al. Historical evolution and prospects of hygienic Standards for design of industrial enterprises. Labour Prot, 2016; (7): 86-9. (In Chinese) |
| [61] | Qu GP, Peng JX. Environmental awakening: the human environment conference and China’s first national environmental protection conference. China Environmental Science Press. 2010. (In Chinese) |
| [62] | Guo XB. History and evolution of China’s ambient air quality standards revision and changes in air pollution and health issues. J Environ Hyg, 2019; 9, 309−11. (In Chinese) |
| [63] | Niu S R, Chen C J. Global environment monitoring system and its implementation in China. Environ Prot, 1982; (6), 19-20, 23. (In Chinese) |
| [64] | He XZ. Indoor air pollution from coal burning and genetic susceptibility to lung cancer-- etiological study of lung cancer in Xuanwei for 22 years. J Pract Oncol, 2001; 16, 369-70. (In Chinese) |
| [65] | Chen MM, Zhao SL, Li GG. Discussion on multi-department environmental monitoring scientific data sharing system: a case study of the Huaihe River basin environment and health monitoring network. In: Proceedings of the 4th National Forum on Environment and Health. Chinese Society for Environmental Sciences. 2009, 108-13. (In Chinese) |
| [66] | Zhang T, Hu GJ, Deng AP, et al. Research ideas on establishing provincial environmental and health investigation and risk assessment system-take Jiangsu Province as an example. Environ Monit Forewarn, 2021; 13, 24−30. (In Chinese) |
| [67] | Zhao XG, Duan XL, Wang BB. Environmental exposure related activity patterns survey of Chinese population (Children). China Environment Publishing Group. 2016. (In Chinese) |
| [68] | Ministry of Environmental Protection. Exposure factors handbook of Chinese population (Adults Volume). China Environmental Science Press. 2013. (In Chinese) |
| [69] | Han JX, Xu DQ, Xu DG, et al. Air pollution health impact monitoring and health risk assessment technology and its application - China, 2006-2019. China CDC Wkly, 2022; 4, 577−81. doi: 10.46234/ccdcw2022.125 |
| [70] | Zhang YS, Xu WP, Zhi Y, et al. Preliminary study on technical system of environmental health risk assessment in China. Environ Sust Dev, 2019; 44, 15−7. (In Chinese) |
| [71] | Ministry of Ecology and Environment of the People’s Republic of China. Technical standards framework for environmental risk assessment and management control of chemical substances (2024 edition). https://www.mee.gov.cn/xxgk2018/xxgk/xxgk06/202410/W020241016524329384551.pdf. [2025-05-09]. (In Chinese) |
| [72] | Wang Q, Chen C, Xu HY, et al. The graded heat-health risk forecast and early warning with full-season coverage across China: a predicting model development and evaluation study. Lancet Reg Health West Pac, 2025; 54, 101266. |
| [73] | Li TT, Wang Q, Sun QH. Strengthen research on early warning of environmental health risks and promote public health services. J Shandong Univ (Health Sci), 2021; 59, 1−5. (In Chinese) |
| [74] | Cao ZJ, Lin SB, Zhao F, et al. Cohort profile: China national human biomonitoring (CNHBM)-a nationally representative, prospective cohort in Chinese population. Environ Int, 2021; 146, 106252. doi: 10.1016/j.envint.2020.106252 |
| [75] | Wu LL, Yan BW, Han JS, et al. TOXRIC: a comprehensive database of toxicological data and benchmarks. Nucleic Acids Res, 2023; 51, D1432−45. doi: 10.1093/nar/gkac1074 |
| [76] | Chemical Multimedia Environmental Database Query System. Chinese Software Copyright: 2019SR0773508. [2025-05-09]. |
| [77] | Chemical Predictive Toxicology Platform (CPTP 2.0). Chinese Software Copyright: 2022SR0120414. [2025-05-09]. |
| [78] | Shanghai Institute of Organic Chemistry of CAS. Chemistry Database [1978-2025]. https://organchem.csdb.cn. [2025-05-09]. (In Chinese) |
| [79] | Li RX. Machine learning prediction models of autonomic neurotoxicity of chemicals. Dalian University of Technology. 2023. (In Chinese) |
| [80] | Huang Y. Machine learning models for predicting lung toxicity induced by metal oxide nanoparticles. Dalian University of Technology. 2023. (In Chinese) |
| [81] | An Y, Huang NJ, Chen XL, et al. High-risk prediction of cardiovascular diseases via attention-based deep neural networks. IEEE/ACM Trans Comput Biol Bioinform, 2021; 18, 1093−105. doi: 10.1109/TCBB.2019.2935059 |
| [82] | Zhao YX, Yang DY, Huang ML, et al. The application of next-generation computational toxicology in food safety risk assessment. Environ Chem, 2025; 44, 756−63. (In Chinese) |
| [83] | Beijing Jiuan Xingzhong Technical Consulting Services Co. , Ltd. AI chemical expert system. http://www.jaxz.net/index.html#contentUS. [2025-05-09]. (In Chinese) |
| [84] | Hines DE, Edwards SW, Conolly RB, et al. A case study application of the aggregate exposure pathway (AEP) and adverse outcome pathway (AOP) frameworks to facilitate the integration of human health and ecological end points for cumulative risk assessment (CRA). Environ Sci Technol, 2018; 52, 839−49. doi: 10.1021/acs.est.7b04940 |
| [85] | Lee BE, Kim DK, Lee H, et al. Recapitulation of first pass metabolism using 3D printed microfluidic chip and organoid. Cells, 2021; 10, 3301. doi: 10.3390/cells10123301 |
| [86] | Li XH, Fourches D. Inductive transfer learning for molecular activity prediction: Next-Gen QSAR models with MolPMoFiT. J Cheminform, 2020; 12, 27. doi: 10.1186/s13321-020-00430-x |
| [87] | Li ZW. Multimedia distribution of organic flame retardants in indoor environments and human exposure simulation in urban Beijing. University of Chinese Academy of Sciences (UCAS). 2022. (In Chinese) |
| [88] | Chen YY. Social security governance in China: a multidimensional dynamic study of emergency risks. China Social Sciences Press. 2024. (In Chinese) |
| [89] | Wang Y. Characteristics of PM2.5 pollution and evolution of fossil fuel combustion and other source in autumn and winter at Xi ’an. Institute of Earth Environment, Chinese Academy of Sciences. 2022. (In Chinese) |
| [90] | Zheng SW, Wang WX. Single-cell RNA sequencing profiling cellular heterogeneity and specific responses of fish gills to microplastics and nanoplastics. Environ Sci Technol, 2024; 58, 5974−86. doi: 10.1021/acs.est.3c10338 |
| [91] | Butterfield GL, Reisman SJ, Iglesias N, et al. Gene regulation technologies for gene and cell therapy. Mol Ther, 2025; 33, 2104−22. doi: 10.1016/j.ymthe.2025.04.004 |
| [92] | Yang YJ. Application of microbial electrochemical sensors in biotoxicity detection of environmental pollutants. University of Chinese Academy of Sciences (UCAS). 2021. (In Chinese) |
| [93] | Wang LY, Guo YD. Construction of paper-based microfluidic chip for multiple ions visual detection and its application. Chem Res Appl, 2024; 36, 48−55. (In Chinese) |
| [94] | Ma DH. Prenatal mother-to-infant transfer and metabolic degradation behavior of per- and polyfluoroalkyl substances. University of Chinese Academy Sciences. 2021. (In Chinese) |
| [95] | Outeiral C, Strahm M, Shi JY, et al. The prospects of quantum computing in computational molecular biology. WIREs Comput Mol Sci, 2021; 11, e1481. doi: 10.1002/wcms.1481 |
| [96] | Li YJ, Chen SP, Hwang K, et al. Spatio-temporal data fusion techniques for modeling digital twin city. Geo-Spat Inform Sci, 2025; 28, 541−64. doi: 10.1080/10095020.2024.2350175 |