Design of a decision support system for improving air quality assessment

Establishing a system that allows the transition from environmental and traffic monitoring to environmental management at the personal level has become a necessity. Such a system will improve the life quality, reduce health costs and increase the support of vulnerable groups (i.e., the elderly, chil...

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Bibliographic Details
Main Authors: G. SUCIU, M. BĂLĂNESCU, A. PASAT, C. NĂDRAG, C. BĂLĂCEANU, R. MATEI, V. SUCIU, A. VASILESCU
Format: Article
Language:English
Published: Cluj University Press 2018-03-01
Series:Aerul şi Apa: Componente ale Mediului
Subjects:
Online Access:http://aerapa.conference.ubbcluj.ro/2018/PDF/26_SUCIU_etal_221_227.pdf
Description
Summary:Establishing a system that allows the transition from environmental and traffic monitoring to environmental management at the personal level has become a necessity. Such a system will improve the life quality, reduce health costs and increase the support of vulnerable groups (i.e., the elderly, children). ESTABLISH project aims to advance an innovative platform which allows converting environmental (sensor) data into actionable information for users to provide a healthier and safer environment thereby improving the quality of life. Smart adaptive services providing real-time feedback tailored to specific user and application needs will be developed by combining networked sensors and other data sources with adaptive models. This paper will present the on-going research within the ESTABLISH project related to the development of a decision support component which assesses the air quality. Based on real-time monitoring and quantification methods, and certain types of notifications for risk groups and general populations, the proposed system links pollutant concentrations to individual health risks. The proposed decision support for air quality assessment is structured on two components. The first component is represented by the comparison with the limit values provided by the legislation, and the second is the forecast of near-real-time air pollution episodes (based on trigger values). Thus, for each pollutant considered (PM2.5, PM10, SO2, NO2, O3, and CO) the frequency of pollutants concentrations measurement, the averaging periods according to the legislation, the averaging period and the limit values used for the notification component were established.
ISSN:2067-743X