Application of an ISCST3 model for predicting urban air pollution in the Izmir metropolitan area

2002 ◽  
Vol 18 (5) ◽  
pp. 498 ◽  
Author(s):  
Tolga Elbir
Keyword(s):  
Air Pollution ◽  
Metropolitan Area ◽  
Urban Air Pollution ◽  
Urban Air

A modelling system for predicting urban air pollution: model description and applications in the Helsinki metropolitan area

2000 ◽  
Vol 34 (22) ◽  
pp. 3723-3733 ◽  
Author(s):  
A. Karppinen ◽  
J. Kukkonen ◽  
T. Elolähde ◽  
M. Konttinen ◽  
T. Koskentalo ◽  
...  
Keyword(s):  
Air Pollution ◽  
Metropolitan Area ◽  
Urban Air Pollution ◽  
Model Description ◽  
Urban Air ◽  
Helsinki Metropolitan Area ◽  
Modelling System ◽  
Air Pollution Model

A Generalized Urban Air Pollution Model and Its Application to the Study of SO2 Distributions in the St. Louis Metropolitan Area

1974 ◽  
Vol 13 (2) ◽  
pp. 185-204 ◽  
Author(s):  
C. C. Shir ◽  
L. J. Shieh
Keyword(s):  
Air Pollution ◽  
Metropolitan Area ◽  
Urban Air Pollution ◽  
Atmospheric Stability ◽  
Air Pollutant ◽  
Multiple Point ◽  
Urban Air ◽  
Subjective Analysis ◽  
Analysis Scheme ◽  
Air Pollution Model

Abstract A generalized urban air pollution model, based on numerical integration of the concentration equation, is developed for the study of air pollutant distributions over an urban area. The model computes the temporal and three-dimensional spatial concentration distributions resulting from specified multiple point and area sources by using currently available meteorological and source inventory data. A new method based on experiments and a turbulence transport model is used to estimate the turbulent diffusivity and atmospheric stability. Special treatments of the finite-difference scheme to accommodate the large variations of concentrations are discussed. An effort has been made to avoid any subjective analysis scheme for the preparation of the input data. The model was used to study SO2 distributions in the St. Louis metropolitan area during 25 consecutive days in February 1965. The computed results were evaluated with respect to observed data by using various statistic methods. The computed results agree favorably with experimental measurements for both long-term and short-term average concentrations. Computations also indicate the model's capabilities and flexibilities for dealing with the rapid variations of atmospheric conditions. The advantages and limitations of the model are also discussed.

An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache
Keyword(s):  
Air Pollution ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Urban Air Pollution ◽  
Warning System ◽  
Air Pollutant ◽  
Pollution Level ◽  
Urban Air ◽  
Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

scholarly journals Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

2020 ◽  
Vol 1 (3) ◽  
pp. 100047 ◽  
Author(s):  
Donghai Liang ◽  
Liuhua Shi ◽  
Jingxuan Zhao ◽  
Pengfei Liu ◽  
Jeremy A. Sarnat ◽  
...  
Keyword(s):  
United States ◽  
Air Pollution ◽  
Urban Air Pollution ◽  
Case Fatality ◽  
The United States ◽  
Mortality Rates ◽  
Urban Air

The impact of COVID-19 pandemic in Mediterranean urban air pollution and mobility

2021 ◽  
pp. 1-16
Author(s):  
Nikolaos Sifakis ◽  
Maria Aryblia ◽  
Tryfon Daras ◽  
Stavroula Tournaki ◽  
Theocharis Tsoutsos
Keyword(s):  
Air Pollution ◽  
Urban Air Pollution ◽  
Urban Air ◽  
The Impact

Intensive field campaigns as a means for improving scientific knowledge to address urban air pollution

2021 ◽  
Vol 246 ◽  
pp. 118094
Author(s):  
Erik Velasco ◽  
Armando Retama ◽  
Miguel Zavala ◽  
Marc Guevara ◽  
Bernhard Rappenglück ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scientific Knowledge ◽  
Urban Air Pollution ◽  
Urban Air ◽  
Field Campaigns

Urban Air Pollution Mapping Using Fleet Vehicles as Mobile Monitors and Machine Learning

2021 ◽  
Vol 55 (8) ◽  
pp. 5579-5588
Author(s):  
Bu Zhao ◽  
Long Yu ◽  
Chunyan Wang ◽  
Chenyang Shuai ◽  
Ji Zhu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Urban Air Pollution ◽  
Urban Air
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