The Effect of COVID-19 Pandemic on Emitted PM2.5 in Urban Road Networks: Using Loop Data and Kriging Method for Passenger Cars in the Central Part of the City of Lodz

In this paper, the effect of the COVID-19 pandemic on the emission of PM2.5 generated by passenger cars is investigated. First, traffic data collected from the inductive loop sensors is analyzed. Second, the traffic flow for the whole network system is estimated using an isometric transformed network and the Euclidean space, and the representative one is selected. Then, an emission model is presented for measuring the level of PM2.5 emissions by the passenger cars, and the integration process is given. Finally, the model is implemented on the central part of the city of Lodz, and the value of emissions before and after the COVID-19 pandemic is measured. Finally, the outputs and the process of the model calibration are depicted. Results show that before the pandemic, PM2.5 pollution was highly concentrated in the center and peripheral parts of the area under consideration, and it would gradually drop outside rush hours and grow at peak hours. After the lockdown, the pollution load throughout the whole area, and across its central parts in particular, decreased dramatically. Outputs also illustrate that restrictions not only lower the car-induced PM2.5 but also have a significant effect on the impact zones, areas affected by the pollutants. Another finding is that although the COVID-19 outbreak clearly poses a serious threat to life and health, it has had an exceptionally positive impact on the natural environment, becoming an unconventional mechanism for its restoration.