The effect of Turbulence Models on Numerical Prediction of Air Flow within Street Canyons

November 15-17, Belgrad

Traffic induced air pollution modeling: Scenario analysis for air quality management in street canyon

This study was supported by the Riga City research project DMV-17-60-lī-03.02.2017. The authors wish to thank the Riga City Council and Latvian Environment, Geology and Meteorology Centre for data used in this study.Mathematical models are intensively used in environmental science for various reasons - status quo assessment, statistical modeling, forecasting, and planning, scenario analysis. Traffic flow and related atmospheric pollution modeling is one of the most complex challenges because of various aspects, - wide versa of affecting factors, daily, diurnal, weekly, monthly and yearly variability and non-stability of them. In the present study atmospheric model OSPM (Operational Street Pollution Model) is used to calculate NOx and PM10 concentration levels in the historical center (street canyon) of the city of Riga (Latvia) in order to make further assumptions (e.g., for the traffic load) for minimizing traffic induced air pollution in street canyons. In total five different scenarios were analyzed involving prioritizations of public transport, restrictions for old private cars or flow limitations in traffic jam situations during working days.Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART

Development and evaluation of land use regression models for black carbon based on bicycle and pedestrian measurements in the urban environment

Land use regression (LUR) modelling is increasingly used in epidemiological studies to predict air pollution exposure. The use of stationary measurements at a limited number of locations to build a LUR model, however, can lead to an overestimation of its predictive abilities. We use opportunistic mobile monitoring to gather data at a high spatial resolution to build LUR models to predict annual average concentrations of black carbon (BC). The models explain a significant part of the variance in BC concentrations. However, the overall predictive performance remains low, due to input uncertainty and lack of predictive variables that can properly capture the complex characteristics of local concentrations. We stress the importance of using an appropriate cross-validation scheme to estimate the predictive performance of the model. By using independent data for the validation and excluding those data also during variable selection in the model building procedure, overly optimistic performance estimates are avoided. (C) 2017 Elsevier Ltd. All rights reserved

Mathematical Simulation Analysis of Body Temperature Observations Covid-19 Patients

At the end of January 2022 as many as 33 countries with new cases of 85% new variant called omicron which is the concern of the World Health Organization. Patients who have been diagnosed with COVID-19 are analyzed for temperature starting from the appearance of fever and until they experience recovery, followed by a decrease in body temperature and loss of fever. This study aims to conduct a mathematical simulation analysis of the observation of the body temperature of covid 19 patients. The research method is descriptive analysis by analyzing using mathematical simulations on the fever of covid 19 patients until the temperature changes to normal again. In February - March 2022, this research was carried out at the general practitioner clinic in Surabaya, Putat Gede, Sukomanunggal sub-district, with positive results from a swab examination and an infrared thermometer. The study population was patients with positive Covid-19 swab results, with a large study sample of 30 Covid-19 patients. The results showed that there was a mathematical simulation with a fever variation of 38 C. – 39.5 C occurs in covid 19 patients. The temperature is decreasing day by day approaching the normal body temperature according to the fever that is gone and healing occurs in Covid 19 patients