## 4 Conclusions  
The source of NO\({}_{2}\) pollution in cities comes from burning fuel (cars, buses, trucks and power plants), so road traffic is the main source of NO\({}_{2}\). In accordance with other published work in this area, we have noticed a remarkable decrease in NO\({}_{2}\) during the COVID-19 lockdown. On the other hand, pollutants related to domestic heating showed constant or higher levels. CO and PM\({}_{10}\) pollutants in cities are mostly related to individual domestic heating sources (gas, fossil fuels and biomass) and heating plants, thus showing almost the same level for PM\({}_{10}\), while CO showed a slight increase. It has to be noted that the source of PM pollution might not always be local pollution, but could come from remote areas, brought by the wind. It could be observed that the PM concentrations did not decline remarkably despite a reduction in traffic, which leads to the conclusion that  
Figure 5: The results of the ANN calibration, trained on data from 2019 as well as 2020 and applied to data from 2021.  
the PM concentration locally varies according to the dominant PM pollution source in the observed area that corresponds to the specific micro-meteorological climate. A convolutional ANN has been proposed in this paper to explore the possibilities of modeling the influence of relative humidity and air temperature on the low-cost measurements. We have concluded that for the CO measurements, no significant improvement could be achieved, but for those of NO\({}_{2}\) and PM\({}_{10}\) a clear improvement can be observed. When training the developed convolutional network on 2019 data and testing it on 2020 data (during the COVID-19 lockdown), an improvement of 0.346 is achieved for the NO\({}_{2}\) R2 value, and an improvement of 0.126 is achieved for the PM\({}_{10}\) R2 value. This shows that the data from a regular period can be used to train a model which can then improve the performance of low-cost sensors even during a different day-to-day regime. It is important to note that our developed model uses sequences of data, and that this choice is made because when the same train/test data splitting methodology was attempted with single measurement points and simpler machine learning models (fully connected ANN and random forest) no improvement could be achieved. In our future work, we will explore the influence of the lockdown on different pollutants. An exploration of more complex convolutional neural networks will also be performed, including an expansion of the network input parameters (both meteorological and other pollutants) as well as the possibilities of cross-calibration between low-cost sensors. Conceptualization, I.V. and D.D. ; methodology, D.D and Z.C. ; software, I.V. ; validation, Z.C. ; formal analysis, I.V., Z.C. and D.D. ; investigation, I.V. and Z.C. ; resources, I.V. ; data curation, D.D. and Z.C. ; writing--original draft preparation, I.V., Z.C. and D.D. ; writing--review and editing, Z.C. and D.D.D. ; visualization, I.V. ; supervision, D.D. and Z.C. ; project administration, I.V. ; funding acquisition, I.V., Z.C. and D.D. All authors have read and agreed to the published version of the manuscript. This research was funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia. The APC is partially covered by the Ministry of Education, Science and Technological Development of the Republic of Serbia. The authors declare no conflict of interest. The Government of the Republic of Serbia Web Portal, COVID-19. 15 March 2020. Available online: [[https://www.srbija.gov.rs/vest/en/151398/state-of-emergency-declared-throughout-serbia.php](https://www.srbija.gov.rs/vest/en/151398/state-of-emergency-declared-throughout-serbia.php)]([https://www.srbija.gov.rs/vest/en/151398/state-of-emergency-declared-throughout-serbia.php](https://www.srbija.gov.rs/vest/en/151398/state-of-emergency-declared-throughout-serbia.php)) (accessed on 27 October 2021). UN (United Nations): Air Quality Improvements from COVID Lockdowns Confirmed.