The Use of Public Data from Low-Cost Sensors for the Geospatial Analysis of Air Pollution from Solid Fuel Heating during the COVID-19 Pandemic Spring Period in Krakow, Poland

Danek, Tomasz; Zaręba, Mateusz

doi:10.3390/s21155208

Cited by 32 publications

(37 citation statements)

References 22 publications

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“…1). The correlation coefficient between their measurements in the presented period was high -over 0.93 (Danek and Zaręba, 2021).…”

Section: Methodsmentioning

confidence: 60%

“…For the rest of this day, there was no wind and the temperature was around 6-8 Celsius degrees. Later in the evening on this day, the effect of diffusion and gravity fall of pollutants into the city was shown by Danek and Zaręba (2021). Fig.…”

Section: 32mentioning

confidence: 89%

“…Data were collected hourly between 3 rd March 2021 and 16 th April 2021. The legibility of the PM measurements was proved by the time-series analysis of the government station and the Airly LCS (Danek and Zaręba, 2021). Manufacturer guarantee accuracy of Airly sensors for -PM 1 5 µg m -3 in the range 0-100 µg m -3 and 10 µg m -3 over 100 µg m -3 ; for PM 2.5 10 µg m -3 in the range 0-100 µg m -3 , 10% for measurements in the range 101-500 µg m -3 , and 20% over concentration 500 µg m -3 ; for PM 10 accuracy is the same as for PM 2.5 (Airly, 2021a).…”

Section: Methodsmentioning

confidence: 99%

“…It has been shown that the migration of PM from neighboring municipalities to Krakow city, on days with no wind takes place by gravity fall or by diffusion as the city is located in the valley (Danek and Zaręba, 2021). Our goal was to check how the migration process of air pollutions depends on an additional external factor like the wind.…”

Section: Analysis Of Air Pollution Inflow Concerning Main Wind Directionmentioning

confidence: 99%

“…For this purpose, we used spatial-temporal analysis of temperature and PMs concentration together with kernel density estimate of PMs and temperature concerning Predicted Mean Vote (PMV) and Perceived Temperature (PT) indicators (Jendritzky et al, 2001). We have indicated the places that were the main sources of air pollution transported to Krakow by diffusion during the spring lockdown in Poland (Danek and Zaręba, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Air Pollution Migration during COVID-19 Lockdown in Krakow, Poland

Zaręba

Danek

2022

Aerosol Air Qual. Res.

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The historical analysis of particulate matter (PM) concentration proved that pro-clean-air legislation and grassroots movement have a positive impact on air quality in Krakow. However, when the temperature drops in late autumn, winter, and early spring, the problem of smog still occurs in the city. In a 24-hours averaging period, the concentration of PM 10 has exceeded EU norms in 10 days in pandemic March 2021. It is estimated that 50% of the carbon fraction in PM 10 measured in Krakow comes from domestic heating. This is mostly caused by the migration of air pollutants from neighboring municipalities (where the use of fossil fuels for heating is allowed) to Krakow (where this type of households heating is forbidden). In this paper, we analyzed PM 10 concentrations in Krakow and neighboring municipalities. Moreover, we showed the main migration directions of air pollutants in connection with wind direction. We used statistical analysis to examine the relations between PM 10 concentrations and other physical characteristics of the atmosphere. It includes measurements of pressure, temperature, and humidity. We were collecting data during early spring 2021 when car transportation was limited due to the COVID-19 lockdown in Poland. Car transportation in Krakow is responsible for up to 20% of the PM 10 carbon fraction concentration. It allowed for observation of air pollutions from solid fuel heating with minimum traffic-generated pollution background. The Airly© low-cost sensors (LCS) network was used for this study.

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“…1). The correlation coefficient between their measurements in the presented period was high -over 0.93 (Danek and Zaręba, 2021).…”

Section: Methodsmentioning

confidence: 60%

Section: 32mentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%

Section: Analysis Of Air Pollution Inflow Concerning Main Wind Directionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Analysis of Air Pollution Migration during COVID-19 Lockdown in Krakow, Poland

Zaręba

Danek

2022

Aerosol Air Qual. Res.

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Representation of Air Pollution in Augmented Reality: Tools for Population–Wide Behavioral Change

Pochwatko¹,

Jędrzejewski²,

Kopeć³

et al. 2023

Digital Interaction and Machine Intelligence

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Air quality affects health and, unfortunately, has been deteriorating rapidly recently. The problem is significant in smaller towns where the important source of pollution is the heating of households and water from individual sources. Therefore, the inhabitants have an influence on a significant reduction of pollution in their area, but at the same time, they are very often not aware of it. Raising awareness about household-related air pollution plays a vital role as systemic solutions proposed by state and local authorities require the support of local communities. The situation has recently become even more serious as we are facing a crisis caused by the Russian war in Ukraine, which has led to an increase in energy and fuel prices and has postponed restrictions on the use of solid fuels or even incentives to use inferior fuels. Pathologies, such as burning garbage in old-style furnaces, have still not been eliminated. One of the ways of raising citizens’ awareness was to be public, easily accessible information about air quality. Many portals, services, and applications currently provide local air quality data, but few people use them. One reason may be that the figures and graphs can be confusing or unattractive to audiences who are not used to reading scientific reports. Visualizing air quality with augmented reality overcomes these obstacles. A mobile application that can use local elements as triggers and a symbolic representation of air quality based on data read in real-time from sensors is simple, attractive for non-experts, and has an additional educational value. We present the experience of creating such an application and prototype tests with the participation of potential users. Unfortunately, the collected results confirm the low awareness of excessive pollution in a given area and its negative impact on health. However, the interest of potential users and positive opinions about the tested prototype fill with optimism.

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Application of GIS-Based AHP Model for the Impact Assessment of COVID-19 Lockdown on Environment Quality: The Case of Kabul City, Afghanistan

Ahmadi

Sahak

Ayoobi

et al. 2022

J Indian Soc Remote Sens

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The COVID-19 pandemic has negatively impacted the industrial, financial, and social aspects of our daily life due to the implementation of lockdown to protect against the spread of the virus. In addition, the lockdown deduced by COVID-19 has promising positive impacts on air quality and environmental pollution. This study aims to monitor the effects of lockdown on environmental degradation during the pandemic in Kabul city, the capital of Afghanistan, using geospatial data and a statistical model of the Analytical Hierarchy Process (AHP). To achieve the purpose of the study, the most essential influencing factors on air quality were generated from different sources using Google Earth Engine (GEE) and GIS environment; Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Moisture Index NDMI) were calculated using Sentinel-2MSI, Carbon Monoxide (CO) was obtained from Sentinel-5P TROPOMI, and land surface temperature was retrieved from MODIS data. The generated thematic layers (before COVID-19, and during a lockdown of COVID-19) were weighted and rated using the AHP analysis. The weighted layers were spatially overlayed to obtain the final output. Consequently, the environmental quality degradation maps before and during COVID-19 were generated to assess the differences over the 22 districts of Kabul city. The findings of the study show that Kabul city is covered by the very low, low, moderate, high, and very high degradation of the environment by 3.17%, 5.33%, 20.54%, 26.63%, 44.32% before COVID-19 in 201,9 respectively, while the percentages are changed to 4.37%, 8.99%. 16.55%, 37.47%, and 32.62% during the lockdown caused by COVID-19 in 2020. The changes in the percentage of environmental degradation in Kabul city particularly in high and very high zones confirm the positive impact of the lockdown of COVID-19.

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The Use of Public Data from Low-Cost Sensors for the Geospatial Analysis of Air Pollution from Solid Fuel Heating during the COVID-19 Pandemic Spring Period in Krakow, Poland

Cited by 32 publications

References 22 publications

Analysis of Air Pollution Migration during COVID-19 Lockdown in Krakow, Poland

Analysis of Air Pollution Migration during COVID-19 Lockdown in Krakow, Poland

Representation of Air Pollution in Augmented Reality: Tools for Population–Wide Behavioral Change

Application of GIS-Based AHP Model for the Impact Assessment of COVID-19 Lockdown on Environment Quality: The Case of Kabul City, Afghanistan

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