Disrupting Noxious Synergies of Indoor Air Pollutants and their Impact in Childhood Health and Wellbeing, using Advanced Intelligent Multisensing and Green Interventions

利用先进的智能多传感和绿色干预措施，破坏室内空气污染物的有害协同作用及其对儿童健康和福祉的影响

• 批准号: 10051924
• 金额: $ 55.96万
• 依托单位: THE UNIVERSITY OF MANCHESTER
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10051924
• 关键词: Disrupting; Noxious; Synergies; Indoor; Air

While the number and types of indoor air pollutants is rising, much is suspected but little is known about the impact of their potentially synergistic interactions, upon human health. Highly susceptible populations include children, allergy and asthma sufferers, and a low socioeconomic background, however no specific guidance is available. SynAir-G aims to reveal and quantify synergistic interactions between different pollutants affecting health, from mechanisms to real-life, focusing on the school setting. We will develop a comprehensive and responsive multipollutant monitoring system, advance environmentally friendly interventions, and disseminate the generated knowledge to relevant stakeholders in accessible and actionable formats. To achieve these objectives, SynAir-G will construct and deploy novel and improved sensors of chemical and biological (allergens, microbes) pollutants. These will be tested in a real-world setting, in participating schools of 5 countries around Europe and eventually combined into a multisensing platform. In the same setting, pollutants will be linked to theirsources and two eco-friendly air-purifying devices will be assessed. Health outcome data will be obtained from children using a gamified app and prospective monitoring, respecting privacy. Highly susceptible children,such asthose with allergy or asthma, will act as sentinels to increase sensitivity of the system, that will be able to provide stratified (susceptibility-specific) alerts. Explainable AI will support the near-real time analysis and response. In parallel, cell and mouse models will evaluate the mechanisms and complex dose-responses of the synergistic parameters. SynAir-G will thus provide FAIR data on air pollutants and their sources, a comprehensive and personalized user-friendly solution to monitoring indoor air quality, and proposals for possible interventions and an improved regulatory framework, robustly supporting the Zero Pollution Action Plan. SynAir-G is part of the Indoor air and health cluster.

虽然室内空气污染物的数量和类型正在增加，但人们对它们潜在的协同相互作用对人类健康的影响有很多怀疑，但知之甚少。高度易感人群包括儿童，过敏和哮喘患者，以及低社会经济背景，但没有具体的指导。SynAir-G旨在揭示和量化影响健康的不同污染物之间的协同作用，从机制到现实生活，重点是学校环境。我们将建立一个全面和反应灵敏的多污染物监测系统，推进环境友好型干预措施，并以可访问和可操作的形式向相关利益攸关方传播所产生的知识。为了实现这些目标，SynAir-G将构建和部署新型和改进的化学和生物（过敏原，微生物）污染物传感器。这些将在真实世界的环境中进行测试，在欧洲5个国家的参与学校中进行测试，并最终组合成一个多传感平台。在同一环境中，污染物将与其来源联系起来，并将评估两种生态友好的空气净化装置。健康结果数据将使用游戏化应用程序和前瞻性监测从儿童中获得，尊重隐私。高度敏感的儿童，如过敏或哮喘，将作为哨兵，以增加系统的灵敏度，这将能够提供分层（敏感性特定）警报。可解释的人工智能将支持近乎实时的分析和响应。同时，细胞和小鼠模型将评估协同参数的机制和复杂的剂量反应。因此，SynAir-G将提供有关空气污染物及其来源的FAIR数据，一个全面和个性化的用户友好的室内空气质量监测解决方案，以及可能的干预措施和改进的监管框架，有力地支持零污染行动计划。SynAir-G是室内空气和健康集群的一部分。