key: cord-0604288-one7dief authors: Kaloni, Dewansh; Lee, Yee Hui; Dev, Soumyabrata title: Impact of COVID19-induced Lockdown on Air Quality in Ireland date: 2021-06-06 journal: nan DOI: nan sha: a00c7d6acb7952b081a4fcba545cc4408f454bf2 doc_id: 604288 cord_uid: one7dief Air pollution has been a long-existing problem for most of the major metropolitan cities of the world. Several measures including strict climate laws and reduction in the number of vehicles were implemented by several nations. However, in the recent wake of the COVID19 pandemic, there has been a renewed interest in revisiting the problem of low air quality. Several countries implemented strict lockdown measures halting the vehicular traffic and other economic activities, in order to reduce the spread of COVID19. In this paper, we analyze the impact of such COVID19-induced lockdown on the air quality of the atmosphere. Our case study is based in the city of Dublin, Ireland. We analyze the average concentration of common gaseous pollutant majorly responsible for industrial and vehicular pollution, textit{viz.} nitrogen dioxide (NO$_2$). These concentrations are obtained from the tropospheric column of the atmosphere collected by Sentinel-5P, which is an earth observation satellite of European Space Agency. We observe that Dublin had a significant drop in the level of NO$_2$ concentration, owing to the strict lockdown measures implemented across the nation. The increasing urbanization of the major cities in the world has put a major impact of the environment. This lead to increased vehicular emissions and related green-house gas emissions to the world. The degradation of the air quality caused serious long-term damage to the lungs, heart disease [1] , and other respiratory diseases [2] . Therefore, remote sensing analysts continually recorded the amount of atmospheric pollutants. This assisted in generating preventive measures and providing early health warnings to the citizens. Satellite measurements are usually popular for these cases because of its wide availability [3] . With the recent onset The ADAPT Centre for Digital Content Technology is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund. Send correspondence to S. Dev: soumyabrata.dev@ucd.ie of the COVID19 pandemic, the researchers found an opportune moment to understand the impact of reduced vehicular movement and human activity on the atmospheric air quality. In this paper, we focus our case study for the city of Dublin in Ireland. Ireland confirmed its first confirmed case of COVID-19 on 29-Feb-2020 and thereby saw growth in the number of cases continuously in the month of March. The number of cases suddenly rose in the middle of the month of March, and consequently, schools and colleges were closed down to arrest the spread of the pandemic. Subsequently, the government imposed a strict lockdown to further curtail the spread [4] . The lockdown was imposed on 24-Mar-2020 and subsequently, three days later all non-essential travel were banned to curtain the spread and avoid community transmission as much as possible. This presented a surprisingly great reduction in pollutant levels. We delve further into the concentration of the individual pollutants obtained from the TROPOMI instrument's dataset. We compare the average concentration of such pollutant with that of the previous year data for the month of March and April to quantify the improvement in the air quality [5] . The main contributions of the paper include: • we establish the importance of Sentinel-5P satellite data to monitor the atmospheric pollutants; • we demonstrate that the lockdown induced because of COVID19 significantly reduced the pollutant concentration in Ireland; • we also share the source-code of our methodology in the spirit of reproducible research 1 . The rest of the paper is arranged as follows. Subsection 2.1 discusses about the Dataset and the TROPOMI instrument of Sentinel-5P data used for our analysis and the data format of files obtained from the sources. Subsection 2.2 discusses with the methodology used to obtain large sized satellite data, resolving it to usable form and the processing techniques followed to obtain daily average concentration. Subsection 2.3 briefly explains the change in nitrogen dioxide concentration for Ireland followed by Subsection 2.4 which explains the drop in concentration of NO 2 in the atmosphere of Dublin using satellite data. Finally, Section 3 concludes the paper and discusses the future work. This study mainly focuses on Ireland and involved processing data specifically for Dublin. We systematically analyze the data obtained from satellite observations. The data obtained from TROPOMI 2 are stored in NetCDF format. The NetCDF stands for Network Common Data Form, and is the format of file used to multidimensional data to study atmospheric features. The Sentinel-5P data uses NetCDF files to share and store files in an array-like structure stacked together. It is generally used to share climate data and for related purposes. The NetCDF4 file contains both the data and the metadata for the product. The data used for this study is nitrogendioxide_tropospheric_column product of the file which gives the total atmospheric NO 2 column between the surface and the top of the troposphere, which stands for tropospheric vertical column of nitrogen dioxide [6] . The data points included in this region of interest are thereby used for the subsequent computation of pollutant concentration.The measurements are stored and archived in individual NetCDF files. Each NetCDF file indicate the concentration of trace gas for the selected day of the study. We then combined all the obtained files into a single file by adding a new dimension of time to the dataset for comparative study 3 . This combined file provides us with data points for the area spread across the time dimension. Our obtained combined NetCDF file provides us the estimate of the average daily concentration of the various atmospheric pollutants. We process these files to obtain the pollutant concentrations of the different pollutant gases. We replace the NaN values of the data grid to 0, and thereby calculate the sum of the all the measurement values in the particular grid. We divide the resultant sum by the number of non-zero values to have a daily average for the region. This enables us to calculate the average concentration of a particular pollutant over the selected region of Dublin [7] . We performed the primary analysis on Ireland using panoply (geo-referenced data viewer by NASA Goddard Institute of We observe that the lockdown significantly reduced the concentration of nitrogen dioxide for the corresponding months of the two years. We show the lockdown period in green color. Space Studies). We generated the spatial concentration maps of nitrogen dioxide for the country from global dataset for dates during lockdown. The nitrogen dioxide concentration was above average on 24-Mar-2020, which dropped significantly on 28-Mar-2020, when strict lockdown was imposed. Subsequent day of 29th March followed the trend of sharp reduction in pollutant concentration. Lockdown stopped nearly all vehicular and industrial activities around the country, which was depicted by improvement in the NO 2 pollutant concentration plots. Figure 1 shows the daily NO 2 concentration plot for Ireland for initial days of lockdown, and we observe a sharp drop in the NO 2 concentration because of the lockdown. To subset Dublin from the global dataset, latitude range from 53.24 • to 53.41 • and longitude range from -6.11 • to -6.45 • was fixed and the concentration data points for the area were chosen. The combined file provided us with data points on the concentration of nitrogen dioxide for the area spread across the time dimension for better analysis. Daily average concentration plot for Feb-2019, Mar-2019 and Apr-2019 is shown in Figure 2 (a) and daily average concentration plot for Feb-2020, Mar-2020 and Apr-2020 are shown in Fig. 2(b) . The last 10 days of March 2019 recorded the average NO 2 concentration of 5.489 µmol/m 2 , whereas the last 10 days of Mar-2020 recorded the average concentration of 3.044 µmol/m 2 , a drop of about 44.54%. The average concentration for the initial 10 days of Apr-2020 recorded 3.072 µmol/m 2 , which indicated towards the similar trend of drop in NO 2 concentration post lockdown. Figure 2 (b) shows the trend of continuous concentration drop after lockdown. The calculated average concentration of NO 2 for Apr-2019 was 7.075 µmol/m 2 whereas for Apr-2020 it was 3.831 µmol/m 2 , recording a significant drop of 45.8%. The significant improvement in NO 2 concentration was be-cause of the strict lockdown imposed in Dublin for the month of April [8] . The time-series plot for 2019 and 2020 shows the drop in NO 2 concentration post 24-Mar-2020 (lockdown was imposed) in comparison to the same period in Mar-2019. Figure 3 shows the average fifteen days concentration comparison for both the years of the city for March and April. The city noticed a increasing trend of NO 2 concentration for Mar-Apr 2019, the trend for 2020 was very much different due to lockdown. The second half of Mar-2020 recorded a 31.17% drop as compared to same period last year which was mainly due to the partial lockdown in the city. A complete lockdown further improved the NO 2 concentration for the first half of Apr-2020 by 46.35% as compared to the first half of Apr-2019. Fig. 3 : We compute the fifteen-days average nitrogen dioxide concentration for the months of March and April, and demonstrate it via a stacked bar chart for both the years -2019 and 2020. We observe from the bar plot that there is a reduced NO 2 concentration from second half of March 2020 and beyond. Such remote sensing techniques of analysis can be beneficial for monitoring the atmosphere in remote regions of the earth which lack ground-based monitoring stations with zero new installments. The COVID-19 lockdown brought a rare opportunity for researchers to understand the environment much better and thereby attempt to influence the policymakers to implement stricter environmental laws. Our future work include the short-term forecasting of pollutant data from historical data. We intend to use the popular LSTM-based models [9] to learn the underlying pattern of such time-series pollutant data and propose relevant recommendations to city planners and environmental agencies. Furthermore, we also plan to use a multi-sensor framework involving ground-based sky cameras [10] and monitoring stations [11] , in addition to the satellite measurements. Predicting stroke from electronic health records Outdoor air pollution and asthma Correlating satellite cloud cover with sky cameras Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India An exploratory study of impact of lockdown on the air quality of Delhi Sentinel-5P TROPOMI Tropospheric NO 2 1-orbit l2 7km x 3.5km Estimating ground-level ozone concentrations in Eastern China using satellite-based precursors Impact of COVID-19 on Irish air quality Forecasting precipitable water vapor using LSTMs An extremely-low cost ground-based whole sky imager Systematic study of weather variables for rainfall detection