Modeling Exposures to Chemicals from Multiple Sources and Routes

Georgopoulos, Panos G.; Isukapalli, Sastry S.; Krishnan, Kannan

doi:10.1002/9780470686263.ch16

Quantitative Modeling in Toxicology 2010

DOI: 10.1002/9780470686263.ch16

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Modeling Exposures to Chemicals from Multiple Sources and Routes

Panos G. Georgopoulos

Sastry S. Isukapalli

Kannan Krishnan

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Cited by 2 publications

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“…The single compartment mass balance-based model is a common mechanistic model that has been widely used in studies to explore IAQ with proper validation against real-world data [138][139][140]. Liu and Zhai [94] integrated a probability-based adjoint inverse method into the single compartment mass balance-based model to back-track indoor pollution sources.…”

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confidence: 99%

Low-Cost Air Quality Sensing towards Smart Homes

et al. 2021

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The evolution of low-cost sensors (LCSs) has made the spatio-temporal mapping of indoor air quality (IAQ) possible in real-time but the availability of a diverse set of LCSs make their selection challenging. Converting individual sensors into a sensing network requires the knowledge of diverse research disciplines, which we aim to bring together by making IAQ an advanced feature of smart homes. The aim of this review is to discuss the advanced home automation technologies for the monitoring and control of IAQ through networked air pollution LCSs. The key steps that can allow transforming conventional homes into smart homes are sensor selection, deployment strategies, data processing, and development of predictive models. A detailed synthesis of air pollution LCSs allowed us to summarise their advantages and drawbacks for spatio-temporal mapping of IAQ. We concluded that the performance evaluation of LCSs under controlled laboratory conditions prior to deployment is recommended for quality assurance/control (QA/QC), however, routine calibration or implementing statistical techniques during operational times, especially during long-term monitoring, is required for a network of sensors. The deployment height of sensors could vary purposefully as per location and exposure height of the occupants inside home environments for a spatio-temporal mapping. Appropriate data processing tools are needed to handle a huge amount of multivariate data to automate pre-/post-processing tasks, leading to more scalable, reliable and adaptable solutions. The review also showed the potential of using machine learning technique for predicting spatio-temporal IAQ in LCS networked-systems.

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Low-Cost Air Quality Sensing towards Smart Homes

et al. 2021

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Roadmap for action for advancing aggregate exposure to chemicals in the EU

Lamon,

Doyle,

Paini

et al. 2024

EFSA Supporting Publications

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The European Food Safety Authority (EFSA) has a goal to efficiently conduct aggregate exposure assessments (AEAs) for chemicals using both exposure models and human biomonitoring (HBM) data by 2030. To achieve EFSA's vision, a roadmap for action for advancing aggregate exposure (AE) in the EU was developed. This roadmap was created by performing a series of engagement and data collection activities to map the currently available methods, data, and tools for assessing AE of chemicals, against the needs and priorities of EFSA. This allowed for the creation of a AEA framework, identification of data and knowledge gaps in our current capabilities, and identification of the challenges and blockers that would hinder efforts to fill the gaps. The roadmap identifies interdependent working areas (WAs) where additional research and development are required to achieve EFSA's goal. It also proposes future collaboration opportunities and recommends several project proposals to meet EFSA's goals. Eight proposal projects supported by SWOT analysis are presented for EFSA's consideration. The project proposals inform high‐level recommendations for multi‐annual and multi‐partner projects. Recommendations to improve stakeholder engagement and communication of EFSA's work on AEA were gathered by surveying stakeholders on specific actions to improve EFSA's communication on AE, including webinars, virtual training, social media channels, and newsletters.

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Modeling Exposures to Chemicals from Multiple Sources and Routes

Cited by 2 publications

References 45 publications

Low-Cost Air Quality Sensing towards Smart Homes

Low-Cost Air Quality Sensing towards Smart Homes

Roadmap for action for advancing aggregate exposure to chemicals in the EU

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