Air Quality in Southeast Brazil during COVID-19 Lockdown: A Combined Satellite and Ground-Based Data Analysis

Forecasting the concentration of NO2 using statistical and machine learning methods: A case study in the UAE

Nitrogen dioxide (NO2) is the most active pollutant gas emitted in the industrial era and is highly correlated with human activities. Tracking NO2 emissions and predicting their concentrations represent important steps toward controlling pollution and setting rules to protect people's health indoors, such as in factories, and in outdoor environments. The concentration of NO2 was affected by the COVID-19 lockdown period and decreased because of restrictions on outdoor activities. In this study, the concentration of NO2 was predicted at 14 ground stations in the United Arab Emirates (UAE) during December 2020 based on training over a full time period of two years (2019-2020). Statistical and machine learning models, such as autoregressive integrated moving average (ARIMA), seasonal autoregressive integrated moving average (SARIMA), long short-term memory (LSTM), and nonlinear autoregressive neural network (NAR-NN), are used with both open- and closed-loop architectures. The mean absolute percentage error (MAPE) was used to evaluate the performance of the models, and the results ranged from "very good" (MAPE of 8.64% at the Liwa station with the closed loop) to "acceptable" (MAPE of 42.45% at the Khadejah School station with the open loop). The results show that the predictions based on the open loop are generally better than those based on the closed loop because they yield statistically significantly lower MAPE values. For both loop types, we selected stations exhibiting the lowest, medium, and highest MAPE values as representative cases. In addition, we demonstrated that the MAPE value is highly correlated with the relative standard deviation of NO2 concentration values.

Dramatic Lockdown Fossil Fuel CO2 Decrease Detected by Citizen Science-Supported Atmospheric Radiocarbon Observations

COVID-19 lockdowns resulted in dramatic changes to fossil fuel CO₂ emissions around the world, most prominently in the transportation sector. Yet travel restrictions also hampered observational data collection, making it difficult to evaluate emission changes as they occurred. To overcome this, we used a novel citizen science campaign to detect emission changes during lockdown and engage youth in climate science. Citizen scientists collected grass samples from their garden or local park, from which we analyzed the radiocarbon content to infer the recently added atmospheric fossil fuel CO₂ mole fraction at each sampling location. The local fossil fuel CO₂ mole fractions during lockdown were compared with a "normal" nonlockdown period. Our results from 17 sites in five cities around New Zealand demonstrate dramatic reductions in traffic emissions of 75 ± 3% during the most severe lockdown restriction period. This is consistent with sparse local traffic count information and a much larger decrease in traffic emissions than reported in global aggregate estimates of emission changes. Our results demonstrate that despite nationally consistent rules on travel during lockdown, emission changes varied by location, with inner-city sites typically dominated by bus traffic showing smaller decreases in emissions than elsewhere.

The Impact of Traffic and Meteorology on Urban Particle Mass and Particle Number Concentrations: Student-Led Studies Using Mobile Measurements before, during, and after the COVID-19 Pandemic Lockdowns

A series of student-led research activities were performed using a cargo bicycle equipped with air chemistry instrumentation to study the dynamics of aerosol particles in urban air before, during, and after the COVID-19 lockdown periods. The studies examined a high-traffic route and a low-traffic route around the city center of Münster, Germany. A complex picture emerged for how the particle number concentrations (PN) and particle mass concentrations (PM, specifically PM10) were affected by the day of the week, the route selected, the meteorological conditions, and the traffic intensity. Traffic had the most impact on PN through the multitude of exhaust plumes from motorized vehicles. The impact of traffic on PM10 was rather low, which is also mirrored in the general pattern of the low response of PM10 to the pandemic lockdown in Germany. Instead, PM10 responded more to the day of the week. Presumably, PM10 responds either to a specific traffic component, such as commercial low-duty vehicles, or to other business, such as construction activity. Meteorological conditions exert their impact mostly through the relative humidity, which affects particle growth. As such, future research could examine PN and PM10 responses over all seasons of the year. In any case, this student-led study in which high-resolution data were acquired deepened our understanding and broadened our view on particle dynamics in urban air. Well-trained university graduates will contribute to meeting further challenges in studying and combatting air pollution.

Effects of the COVID-19 Pandemic on the Air Quality of the Metropolitan Region of São Paulo: Analysis Based on Satellite Data, Monitoring Stations and Records of Annual Average Daily Traffic Volumes on the Main Access Roads to the City

This paper presents an analysis of the effects of the COVID-19 pandemic on the air quality of the Metropolitan Region of São Paulo (MRSP). The effects of social distancing are still recent in the society; however, it was possible to observe patterns of environmental changes in places that had adhered transportation measures to combat the spread of the coronavirus. Thus, from the analysis of the traffic volumes made on some of the main access highways to the MRSP, as well as the monitoring of the levels of fine particulate matter (PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2), directly linked to atmospheric emissions from motor vehicles–which make up about 95% of air polluting agents in the region in different locations–we showed relationships between the improvement in air quality and the decrease in vehicles that access the MRSP. To improve the data analysis, therefore, the isolation index parameter was evaluated to provide daily information on the percentage of citizens in each municipality of the state that was effectively practicing social distancing. The intersection of these groups of data determined that the COVID-19 pandemic reduced the volume of vehicles on the highways by up to 50% of what it was in 2019, with the subsequent recovery of the traffic volume, even surpassing the values from the baseline year. Thus, the isolation index showed a decline of up to 20% between its implementation in March 2020 and December 2020. These data and the way they varied during 2020 allowed to observe an improvement of up to 50% in analyzed periods of the pollutants PM2.5, CO and NO2 in the MRSP. The main contribution of this study, alongside the synergistic use of data from different sources, was to perform traffic flow analysis separately for light and heavy duty vehicles (LDVs and HDVs). The relationships between traffic volume patterns and COVID-19 pollution were analyzed based on time series.

Monitoring the Impact of COVID-19 Lockdown on the Production of Nitrogen Dioxide (NO2) Pollutants Using Satellite Imagery: A Case Study of South Asia

Among the numerous anthropogenic pollutants, nitrogen dioxide (NO2) is one of the leading contaminants mainly released by burning fossil fuels in industrial and transport sectors. This study evaluates the impact of COVID-19 lockdown on the growing trend of NO2 emissions in South Asia. Satellite imagery data of Sentinel-5 Precursor with Tropomi instrument was employed in this study. The analysis was performed using time series data from February–May 2019 and February–May 2020. The time frame from February–May 2020 was further divided into two sub-time-frames, i.e., from 1 February–20 March (pre-lockdown) and from 21 March–May 2020 (lockdown). Results show the concentration of NO2 pollutants over the region declined by 6.41% from February–May 2019 to February–May 2020. Interestingly, an increasing trend of NO2 concentration by 6.58% occurred during the pre-lockdown phase in 2020 (1 February–20 March) compared to 2019 (February–May). However, the concentration of NO2 pollutants reduced considerably by 21.10% during the lockdown phase (21 March–10 May) compared to the pre-lockdown phase in 2020. Furthermore, the country-specific detailed analysis demonstrates the significant impact of COVID-19-attributed lockdown on NO2 concentration in South Asia.

Air Pollution Observations in Selected Locations in Poland during the Lockdown Related to COVID-19

The coronavirus disease (COVID-19) has caused huge changes in people’s daily habits and had a significant impact on the economy. The lockdowns significantly reduced road traffic and meant that many people worked remotely. Therefore, the question arose as to how the reduced road traffic and stays of residents at home affected the degree of pollution and the structure of major air pollutants. To answer this question, the article presents an analysis of changes in typical air pollutants (PM10, PM2.5, NO2) in the five largest Polish cities and one of the voivodships. The data from the Polish State Environmental Monitoring were used for the analysis. The analysis showed that the period of the first lockdown in Poland (April 2020), despite the reduced road traffic, resulted in a significant increase in PM10 emissions (9–91% during working days and an average of 30% on Saturdays and Sundays), a slight increase in PM2.5 emissions (on average from 2% to 11% for all analyzed locations), and a reduction in NO2 emissions (on average from 6% to 11% for all analyzed locations) compared to the period before the lockdown. However, the changes were not homogeneous—in Łódź and Warsaw, in most cases, an increase in all analyzed pollutants was observed, and the greatest decrease in pollution took place in Małopolska voivodship (including Kraków). Comparing the data from April 2020 to the data from April 2019, the overall difference in the PMs concentrations was small, although there are places where there has been a significant decrease (Wrocław, Poznań), and there were also places where the concentration increased (Warsaw, Łódź, Małopolska). In the case of nitrogen dioxide, pollution concentration decreased in most locations. The only exception was the background stations in Warsaw, where the increase was 27%.