Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey

Abstract

As in other countries of the world, the Turkish government is implementing many preventive partial and total lockdown practices against the virus’s infectious effect. When the first virus case has been detected, the public authorities have taken some restriction to reduce people and traffic mobility, which has also turned into some positive affect in air quality. To this end, the paper aims to examine how this pandemic affects traffic mobility and air quality in Istanbul. The pandemic does not only have a human health impact. This study also investigates the social and environmental effects. In our analysis, we observe, visualize, compare and discuss the impact of the post- and pre-lockdown on Istanbul’s traffic mobility and air quality. To do so, a geographic information system (GIS)-based approach is proposed. Various spatial analyses are performed in GIS with the statistical data used; thus, the environmental effects of the pandemic can be better observed. We test the hypothesis that this has reduced traffic mobility and improved air quality using traffic density cluster set and air monitoring stations (five air pollutant parameters) data for five months. The results shows that there are positive changes in terms of both traffic mobility and air quality, especially in April–May. PM10, SO2, CO, NO2 and NOx parameter values improved by 21.21%, 16.55%, 18.82%, 28.62% and 39.99%, respectively. In addition, there was a 7% increase in the average traffic speed. In order for the changes to be permanent, it is recommended to integrate e-mobility and sharing systems into the current transportation network.

Air Quality and Active Transportation Modes: A Spatiotemporal Concurrence Analysis in Guadalajara, Mexico

“…The link between air quality and active transportation modes assessed in this study is recognized locally and worldwide [7,26]. When using active transportation mode systems, such as MiBici and SITEUR, people perform physical activity, contributing to their health [41].…”

“…A statistical spatiotemporal approach was used. The year 2019 was chosen as the most recent year without potential changes to travel behaviors due to the COVID-19 pandemic [7]. Figure 3 shows the conceptual model used to identify the number of active mode users exposed to poor air quality episodes in the reference year.…”

“…Different modes of transport are associated with specific effects of bad air conditions on health [7,8], for instance, the private car is recognized as the most polluting mode of transport [9][10][11]. Recently, urban policies in large metropolises have promoted active transportation modes through investments in infrastructure, in particular, for improvements for pedestrians, cyclists, and users of mass transport systems.…”

“…This fact shows the importance of cross-temporal and spatial studies to identify the pollution impacts on city inhabitants. This is also recognized in existing literature [6,7,[18][19][20][21][22][23][24]. Despite studies in Europe [7,[25][26][27], there is a lack of analysis of large databases of temporal exposure to air pollution concerning active mode users in Latin American metropolises.…”

A Study on Near Real-Time Carbon Emission of Roads in Urban Agglomeration of China to Improve Sustainable Development under the Impact of COVID-19 Pandemic

“…Forster et al [11] estimated that CO 2 emissions would fall by 13% in 2020. Meanwhile, there are also some discussions of post-and pre-lockdown traffic mobility, CO 2 emissions and air quality [12] and noises [13]. On the whole, the reduction in CO 2 emissions caused by the COVID-19 pandemic was unprecedented.…”