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ONLINE SERVICES FOR URBAN ENVIRONMENT MONITORING
Abstract
Urban meteorological parameters and traffic emissions are characterized by microterritorial variability. Online weather and traffic information is the basis for creating online services to provide users with information about the toxicological risk, noise effects and thermal stress risk. The purpose of this work is to assess the possibilities of online environmental modeling. The methodology includes special field studies to select model parameters, developing models for online calculations of noise levels, concentrations of pollutants from traffic flows and microterritorial changes in temperature and wind speed, as well as tools for providing processing and storage of information. As a result, it was found that the concentration of nitrogen and carbon oxides in the roadside zone reaches maximum permissible values, which corresponds to the modeling results. The noise level exceeds 70 dBA and also corresponds to the simulation results. The effective temperature mitigation inside closed-canopy green areas compared to open space is several Celsius degrees and provides protection from thermal stress in accordance with the proposed model. The result of the work is the development of a test version of three services, including calculation of the concentration of pollutants during traffic congestion; calculation of the noise level produced by intensive traffic flow and calculation of the effective temperature during thermal stress for the hottest summertime. It is during thickening of traffic flows that the highest concentrations of pollutants are observed and at this time the risks of toxicological and noise effects are significant. The research conditions correspond in time and space to the highest level of local environmental risk. To perform online calculations, in addition to the parameters obtained during field studies, real-time information about the weather and traffic flow speed is required. The online services can be used both for users to make immediate decisions and for city policies to reduce emissions risks and to create urban green islands of thermal safety with a closed canopy that protects during extreme heat
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References3
Shepelev V, Slobodin I, Gritsenko A and Fadina O (2022) FORECASTING THE AMOUNT OF TRAFFIC-RELATED POLLUTANT EMISSIONS BY NEURAL NETWORKS. Front. Built Environ. 8:945615. DOI: 10.3389/fbuil.2022.945615;
Ivanov A.V, Platov A.Yu., Stepanov D.V., Ostanina I. M. (2018) ONLINE MONITORING OF URBAN ENVIRONMENT. 18th International Multidisciplinary Scientific GeoConference SGEM 2018. Conference proceedings. 2018. Volume 18 Issue 2.2, pp. 339-346..
Novikova, S.V., NEURAL NETWORK SIMULATION FOR SOLVING THE MONITORING PROBLEMS UNDER CONDITIONS OF INCOMPLETE FUZZY INFORMATION (BY AN EXAMPLE OF ECOLOGICAL MONITORING), Doctoral (Tech.) Dissertation, Kazan: Kazan State Technical University, 2013, p. 258.
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