Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world

COPD Exacerbations, Air Pollutant Fluctuations, and Individual-Level Factors in the Pandemic Era

Purpose

Pandemic-era associations between air pollutant exposures and exacerbations of chronic obstructive pulmonary disease (COPD) are under-explored. Given the considerable observed pandemic-era pollutant fluctuations, these associations were investigated along with possible individual-level risk factors.

Patients and Methods

Participants with spirometry-confirmed COPD from Canadian Cohort Obstructive Lung Disease (CanCOLD) were included, with data collected before ("pre-pandemic") and during ("pandemic") the COVID-19 pandemic. Nitrogen dioxide (NO2), fine particulate matter (PM2.5), ground-level ozone (O3), total oxidant (Ox) and weather data were obtained from national databases. Associations between each air pollutant and "symptom-based" exacerbations (increased dyspnea or sputum volume/purulence ≥48hrs) and "event-based" exacerbations ("symptom-based" plus requiring antibiotics, corticosteroids, or unscheduled healthcare use) were estimated in separate models. Generalized estimating equations (GEE) models were reported as rate ratios (RRs) per interquartile range (IQR) increment in pollutant concentration with 95% confidence intervals (95% CIs).

Results

NO2, PM2.5, and Ox (NO2+O3) concentrations (but not O3) fell significantly during the pandemic. In the 673 participants with COPD included, both symptom-based and event-based exacerbation rates were likewise significantly higher during the pre-pandemic period. During the pre-pandemic period, Ox was positively associated with symptom-based exacerbations (RR: 1.21 [1.08,1.36]). During the pandemic period, Ox was positively associated with symptom-based (1.46 [1.13,1.89]) and event-based (1.43 [1.00,2.05]) exacerbations. Fewer self-reported pandemic protective behaviors, and higher viral infectious symptoms, were also associated with exacerbations. In stepwise multivariable risk-factor analyses, female gender (1.23 [1.04,1.45] and 1.41 [1.13,1.76]) and co-morbid asthma (1.65 [1.34,2.03] and 1.54 [1.19,2.00]) were associated with symptom-based and event-based exacerbations, respectively, blood eosinophils (1.42 [1.10,1.84]) were associated with event-based exacerbations, and each IQR increment in Ox was associated with symptom-based exacerbations (1.31 [1.06,1.61]).

Conclusion

Ox exposure was consistently associated with symptom-based COPD exacerbations, and female gender, co-morbid asthma, and blood eosinophilia were found to be relevant risk factors.

Dynamics of atmospheric emissions and meteorological variables in Bangladesh from pre-to post-COVID-19 lockdown

Following the COVID-19 restrictions, there was a sharp decline in global air quality and related environmental metrics. Due to the limited availability of in situ atmospheric data in Bangladesh, this study collected data on various air pollutants (NO2, SO2, CO, and PM2.5), greenhouse gases (CO2, CH4, and O3), as well as meteorological variables like Land Surface Temperature (LST), Relative Humidity (RH), Precipitation, surface albedo and Aerosol Optical Depth (AOD) from different datasets by Google Earth Engine (GEE), the International Energy Agency (IEA), NASA Giovanni, and NASA Power Access Viewer, covering periods before (2019), during (2020), and after (2021-2023) the COVID-19 lockdown in Bangladesh. GIS-based assessment alongside Principal Component Analysis (PCA) has been performed to explore the patterns, trends and correlations among the observed variables. Results showed in 2020 compared to 2019, NO2, SO2, CO, PM2.5, and CO2 concentrations decreases by 1.94, 16.67, 1.95, 2.08, and 6 %, respectively, while CH4 and O3 continued to rise. Meteorological variables exhibited a 0.16 °C decreases in LST, 6.4 % increases in RH, a 6 % reduction in AOD, and 6.36 % declines in surface albedo. Post-lockdown in 2021, air pollutants surged (NO2, SO2, CO, and PM2.5 increases by 17.3, 23.6, 0.6, and 8.3 %, respectively), with CO2, LST, and AOD rising by 8.5 %, 0.13 °C, and 8.3 %, and a slight 0.46 % decrease in RH compared to 2019 due to resuming more economic activities, transportation and industrial production works. The years 2022-2023 saw slight improvements in most variables except CH4, though concentrations did not revert to those of 2019. The findings of correlation coefficients revealed that pollutants and GHG are highly correlated with the meteorological variables specially with RH. This study underscores the substantial shifts in atmospheric variables from pre-to post-lockdown periods, offering valuable insights for more effective management of the greenhouse effect and air pollution control strategies.

Comparative Assessment of the Impact of COVID-19 Lockdown on Air Quality: A Multinational Study of SARS-CoV-2 Hotspots

In response to the global COVID-19 pandemic, nations implemented lockdown measures to contain the virus. This study assessed air pollution levels during and after lockdowns, focusing on the following heavily affected locations: Oulu and Helsinki in Finland, Paris in France, Madrid in Spain, Milan in Italy, and Wuhan in China. Air Quality Index (AQI) data from these locations over two years were analyzed to understand the effects of lockdowns. The study compared COVID-19 lockdowns in these six cities with SARS-CoV-2 measurements using statistical methods. Variations in outdoor pollutants were evaluated through tests, revealing significant differences. Parametric analyses and regression were employed to study the impacts of lockdown measures on pollution and their relationships. The study comprehensively analyzed the effects of COVID-19 lockdowns on air quality, identifying differences, quantifying changes, and exploring patterns in each city. Pollutant correlations varied among cities during the lockdowns. Regression analysis highlighted the impact of independent variables on pollutants. Decreases in NO2 were observed in Helsinki, Madrid, Oulu, Paris, and Milan, reflecting reduced traffic and industrial activities. Reductions in PM2.5 and PM10 were noted in these cities and in Wuhan, except for O3 levels, which increased. The reduction in human activities improved air quality, particularly for NO2 and PM10. Regional variations underscore the need for tailored interventions. The study observed a substantial decrease in both PM2.5 and NO2 levels during the COVID-19 lockdowns, indicating a direct correlation between reduced human activities, such as transportation and industrial operations, and improved air quality. This underscores the potential impact of environmental measures and suggests the need for sustainable practices to mitigate urban pollution.

Air pollution analysis in Northwestern South America: A new Lagrangian framework

This study examines the spatiotemporal variations of PM2.5, PM10, SO2, O3, NO, and NO2 concentrations in Northwestern South America (NWSA). We assess the efficacy of existing policies, identify underlying phenomena, and highlight areas for further research. Significant findings have emerged by analyzing reanalysis and in-situ data, employing the WRF-Chem model, and utilizing a new Lagrangian framework designed to overcome some drawbacks common to analysis of pollution Long-Range Transport. Wildfires in the first half of the year and volcanic activity (for SO2) in July-August contribute to over 90 % of the pollutant's advection, leading to high pollution levels in urban areas. SO2 volcanic emissions contribute to secondary PM, explaining the peak in PM concentrations in Cali in July. In the second half of the year, pollutant behavior varies based on factors such as city characteristics, vehicular-volume, air temperature, wind speed, and boundary layer height, and O3 is influenced by solar radiation and the NO/NO2 ratio. Diurnal variations of PM and NOx correlate with vehicular density, SO2 with industrial activity, and O3 depends on solar radiation. Trend analysis reveals decreasing PM10 levels except in three Cundinamarca cities and Cali suggesting the need to implement/evaluate control plans in those locations. Although data is limited, NO and NO2 levels show an increasing trend due to the rising number of vehicles. SO2 levels are decreasing, except in Cali, potentially influenced by the nearby industrial and polluted city of Yumbo. O3 displays a downward trend in most cities, except Bogotá, due to the NO/NO2 ratio favoring O3 increase. These findings provide a starting point for further research to deepen our understanding of NWSA air pollution. Such investigations are essential before modifying existing policies or enacting new ones. Collaborative efforts at the international, regional, and inter-city levels are crucial for effective air quality management.

Multilevel analysis identifying the factors associated with RSV detection in infants admitted for viral bronchiolitis in the era of the COVID-19 pandemic

OBJECTIVES

To identify factors independently associated with respiratory syncytial virus (RSV) detection in infants admitted for viral bronchiolitis during 3 consecutive years, before and during the COVID-19 pandemic, in Bogota, Colombia, a middle-income country with a subtropical highland climate.

METHODS

An analytical cross-sectional study was conducted before and during the COVID-19 pandemic, including patients with a diagnosis of viral bronchiolitis admitted to all the hospitals of the city between January 2019 and November 2021. We evaluated a set of a priori-selected predictor variables that included individual, healthcare system, meteorological, air pollutant, and COVID-19 variables. Since the variables analyzed are hierarchical in nature, multilevel modeling was used to identify factors independently associated with detection of RSV as the causative agent of viral bronchiolitis.

RESULTS

A total of 13,177 patients were included in the study. After controlling for potential confounders, it was found that age (odds ratio [OR] 0.86; 95% confidence interval [CI] 0.76-0.97), a third level of medical care institution (OR 3.05; 95% CI 1.61-5.76), temperature (OR 1.60; 95% CI 1.24-2.07), rainfall (OR 1.003, 95% CI 1.001, 1.005), NO2 (OR 0.97; 95% CI 0.95-0.99), CO (OR 0.99; 95% CI 0.99-0.99), and COVID-19 pandemic period (OR 0.84, 95% CI 0.71-0.99) were independently associated with RSV detection in our sample of patients.

CONCLUSIONS

The identified factors associated with RSV detection provide additional scientific evidence that may be useful in the development of specific interventions aimed at ameliorating or preventing the impact of RSV in Bogota and probably other similar low- to middle-income countries in high-risk infants.

Impact of Regional Mobility on Air Quality during COVID-19 Lockdown in Mississippi, USA Using Machine Learning

Social distancing measures and shelter-in-place orders to limit mobility and transportation were among the strategic measures taken to control the rapid spreading of COVID-19. In major metropolitan areas, there was an estimated decrease of 50 to 90 percent in transit use. The secondary effect of the COVID-19 lockdown was expected to improve air quality, leading to a decrease in respiratory diseases. The present study examines the impact of mobility on air quality during the COVID-19 lockdown in the state of Mississippi (MS), USA. The study region is selected because of its non-metropolitan and non-industrial settings. Concentrations of air pollutants-particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ozone (O3), nitrogen oxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)-were collected from the Environmental Protection Agency, USA from 2011 to 2020. Because of limitations in the data availability, the air quality data of Jackson, MS were assumed to be representative of the entire region of the state. Weather data (temperature, humidity, pressure, precipitation, wind speed, and wind direction) were collected from the National Oceanic and Atmospheric Administration, USA. Traffic-related data (transit) were taken from Google for the year 2020. The statistical and machine learning tools of R Studio were used on the data to study the changes in air quality, if any, during the lockdown period. Weather-normalized machine learning modeling simulating business-as-scenario (BAU) predicted a significant difference in the means of the observed and predicted values for NO2, O3, and CO (p < 0.05). Due to the lockdown, the mean concentrations decreased for NO2 and CO by -4.1 ppb and -0.088 ppm, respectively, while it increased for O3 by 0.002 ppm. The observed and predicted air quality results agree with the observed decrease in transit by -50.5% as a percentage change of the baseline, and the observed decrease in the prevalence rate of asthma in MS during the lockdown. This study demonstrates the validity and use of simple, easy, and versatile analytical tools to assist policymakers with estimating changes in air quality in situations of a pandemic or natural hazards, and to take measures for mitigating if the deterioration of air quality is detected.

Beyond intergovernmental cooperation: domestic politics of transboundary air pollution in Korea and Singapore

This study explores why the implementation of domestic environmental policies that tackle transboundary air pollution has been undermined by comparing the cases of the Republic of Korea (Korea) and Singapore. Heavy smog recurs in Korea and Singapore every year despite various attempts to reduce air pollution through the signing of environmental cooperation agreements and the introduction of domestic measures. While existing scholarship has examined intergovernmental cooperation aimed at mitigating transboundary air pollution, this study focuses on domestic factors affecting policy implementation processes at the national level. How do domestic factors shape governmental policy actions within environmental cooperation agreements in the cases of Korea and Singapore? I employed a process-tracing method to analyze the entanglement of domestic stakeholders from the late 1990s to 2019. By drawing upon domestic politics theory, I find that domestic dynamics, intricately linked to other stakeholders, have limited the effectiveness of policies implemented to address poor air quality. This finding suggests that domestic politics play a critical role in establishing effective regional environmental cooperation in the long run.

Characterization of Polycyclic Aromatic Hydrocarbons (PAHs) associated with fine aerosols in ambient atmosphere of high-altitude urban environment in Sikkim Himalaya

Polycyclic Aromatic Hydrocarbons (PAHs) compounds are ubiquitous in ambient air due to their persistence, carcinogenicity, and mutagenicity. Gangtok being one of the cleanest cities in India located in Eastern Himalayan region, witnesses high developmental activities with enhanced urbanization affecting the ambient air quality. The present study aims to measure PM_2.5 and PAHs in the ambient atmosphere of the Sikkim Himalaya to understand the influence of natural and anthropogenic activities on aerosol loading and their chemical characteristics. The PM_2.5 samples were collected and analysed for the duration from Jan 2020 to Feb 2021.The seasonal mean concentrations of PM_2.5 and PAHs were observed to be high during autumn and low during summer season. Overall, the annual mean concentration of PM_2.5 was found higher than the prescribed limit of World Health Organization and National Ambient Air Quality Standards. The concentration of the 16 individual PAHs were found to be highest during autumn season (55.26 ± 37.15 ng/m³). Among the different PAHs, the annual mean concentration of fluorene (3.29 ± 4.07 ng/m³) and naphthalene (1.15 ± 3.76 ng/m³) were found to be the highest and lowest, respectively. The Molecular Diagnostic Ratio (MDR) test reveals higher contribution from heavy traffic activities throughout the winter and autumn seasons. The other possible sources identified over the region are fossil fuel combustion, and biomass burning. The multivariate statistical analysis (Multifactor Principal Component Analysis) also indicates a strong association between PM_2.5 /PAHs and meteorological variables across the region in different seasons. The precipitation and wind pattern during the study period suggests that major contribution of the PM_2.5 and PAHs were from local sources, with minimal contribution from long-range transport. The findings are important for comprehending the trends of PAH accumulation over a high-altitude urban area, and for developing sustainable air quality control methods in the Himalayan region.

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways.

The oxidative potential of airborne particulate matter in two urban areas of Chile: More than meets the eye

Oxidative potential (OP) has gained attention as a parameter that can reveal the ability of different properties of particulate matter (PM) to generate reactive oxygen species (ROS) as one single value. Moreover, OP is also believed to be a predictor of toxicity and hence the health effects of PM. This study evaluated the OP of PM₁₀, PM_2.5,and PM_1.0samples using dithiothreitol assays in two cities of Chile (Santiago and Chillán). The results showed that the OP was different between cities, PM size fractions, and seasons. Additionally, OP was strongly correlated with certain metals and meteorological variables. Higher mass-normalized OP was observed during cold periods in Chillán and warm periods in Santiago and was associated with PM_2.5 and PM₁. On the other hand, volume-normalized OP was higher during winter in both cities and for PM₁₀. Additionally, we compared the OP values to the Air Quality Index (AQI) scale and found cases of days that were classified as having "good" air quality (supposed to be less harmful to health) showing extremely high OP values that were similar to those on days that were classified as "unhealthy". Based on these results,we suggest using the OP as a complementary measure to the PM mass concentration because it includes important new information related to PM properties and compositions that could help improvecurrent air quality management tools.

Climate change: Comparing "green" and "polluting" nation-states

Some nation-states, i.e., Norway, Sweden, and Denmark, repeatedly score the highest in environmental indicators such as the Environmental Performance Index (EPI) and the Climate Change Performance Index (CCPI). Their cities win environmental awards; they have well-developed recycling systems; they perform well with biodegradable waste; and their citizens show awareness of environmental problems, protesting publicly and even sueing their governing bodies if they don't do the same. For these and other reasons, recent scholarship defined these countries as "exemplary" green nation-states. The question is, which factors pushed them toward the green transition faster than others? And overall, what stops top polluting countries such as China, the United States and Russia from walking the same path? This article attempts to answer these questions by looking at climate change through a theoretical framework based on theories of nationalism and case studies of green nation-states. It compares three of said top polluting countries, China, the United States, and Russia, with "exemplary" green nation-states, and argues that the pace of greener nation-states rests on (1) a tradition of ecologism and environmentalism rooted in the long run, (2) the lock in of "green nationalism," a form of nationalism grounded on sustainability, (3) free and effective environmental movements, (4) inclusivity and welfare, and (5) a sense of national pride in environmental achievements. The available evidence seems to suggest that top polluting nation-states lack one or more of these factors.

A qualitative and quantitative synthesis of the impacts of COVID-19 on soundscapes: A systematic review and meta-analysis

The current prolonged coronavirus disease (COVID-19) pandemic has substantially influenced numerous facets of our daily lives for over two years. Although a number of studies have explored the pandemic impacts on soundscapes worldwide, their works have not been reviewed comprehensively nor systematically, hence a lack of prospective soundscape goals based upon global evidence. This review study examines evidence of the COVID-19 crisis impacts on soundscapes and quantifies the prevalence of unprecedented changes in acoustic environments. Two key-research classes were identified based on a systematic content analysis of the 119 included studies: (1) auditory perceptual change and (2) noise level change due to the COVID-19 pandemic/lockdown. Our qualitative synthesis ascertained the substantial adverse consequences of pandemic soundscapes on human health and well-being while beneficial aspects of the COVID-19 pandemic on soundscapes were yet identified. Furthermore, meta-analysis results highlight that the observed average noise-level reduction (148 averaged samples derived from 31 studies) varied as a function of the stringency level of the COVID-19 confinement policies imposed by the governments, which would be further moderated by urban morphology and main noise sources. Given these collective findings, we propose soundscape materiality, its nexus with related the United Nations' sustainable development goals (SDGs), and prospective approaches to support resilient soundscapes during and after the pandemic, which should be achieved to enhance healthy living and human well-being.

Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.

Strict lockdown measures reduced PM2.5 concentrations during the COVID-19 pandemic in Kolkata, India

The COVID-19 situation is a critical state throughout the world that most countries have been forced to implement partial to total lockdown to control the COVID-19 disease outbreak. And displays the natural power to rejuvenate herself without the interference of human beings. So, the top-level emergency response including full quarantine actions are significant measures against the COVID-19 and resulted in a notable reduction in PM2.5 in the atmosphere. India was severely attacked by COVID-19, and as a result, the Government of India has imposed a nationwide lockdown from 24th March (2020) to 30th May (2020) in different phases. The COVID-19 outbreak and lockdown had a significant negative impact on India's socioeconomic structure but had a positive impact on environmental sustainability in terms of improved air quality due to the 68 days of the shutdown of India's industrial, commercial, construction, and transportation systems. The current study looked at the spatio-temporal changes in PM2.5 concentrations at different air quality monitoring stations (AQMS) in Kolkata during the COVID-19 period. The study revealed that the average concentration of PM2.5 (µg/m3) was slightly high (139.82) in the pre-lockdown period which was rapidly reduced to 37.77 (72.99% reduction) during the lockdown period and it was further increased (137.11) in post-lockdown period. The study also shows that the average concentration of PM2.5 was 66.83 in 2018, which slightly increased to 70.43 (5.39%) in 2019 and dramatically decreased to 37.77 (46.37%) in the year 2020 due to the COVID-19 outbreak and lockdown. The study clearly shows that air quality improves during lockdown periods in Kolkata, but it is not a permanent solution rather than temporary. Therefore, it is necessary to make the proper policies and strategies by policymakers and government authorities, and environmental scientists to maintain such good air quality by controlling several measures of air pollutants.

Research on COVID-19 and air pollution: A path towards advancing exposure science

The COVID-19 pandemic has resulted in an extraordinary incidence of morbidity and mortality, with almost 6 million deaths worldwide at the time of this writing (https://covid19.who.int/). There has been a pressing need for research that would shed light on factors - especially modifiable factors - that could reduce risks to human health. At least several hundred studies addressing the complex relationships among transmission of SARS-CoV-2, air pollution, and human health have been published. However, these investigations are limited by available and consistent data. The project goal was to seek input into opportunities to improve and fund exposure research on the confluence of air pollution and infectious agents such as SARS-CoV-2. Thirty-two scientists with expertise in exposure science, epidemiology, risk assessment, infectious diseases, and/or air pollution responded to the outreach for information. Most of the respondents expressed value in developing a set of common definitions regarding the extent and type of public health lockdown. Traffic and smoking ranked high as important sources of air pollution warranting source-specific research (in contrast with assessing overall ambient level exposures). Numerous important socioeconomic factors were also identified. Participants offered a wide array of inputs on what they considered to be essential studies to improve our understanding of exposures. These ranged from detailed mechanistic studies to improved air quality monitoring studies and prospective cohort studies. Overall, many respondents indicated that these issues require more research and better study design. As an exercise to solicit opinions, important concepts were brought forth that provide opportunities for scientific collaboration and for consideration for funding prioritization. Further conversations on these concepts are needed to advance our thinking on how to design research that moves us past the documented limitations in the current body of research and prepares us for the next pandemic.

NASA Satellite Measurements Show Global-Scale Reductions in Free Tropospheric Ozone in 2020 and Again in 2021 During COVID-19

NASA satellite measurements show that ozone reductions throughout the Northern Hemisphere (NH) free troposphere reported for spring-summer 2020 during the COronaVIrus Disease 2019 pandemic have occurred again in spring-summer 2021. The satellite measurements show that tropospheric column ozone (TCO) (mostly representative of the free troposphere) for 20°N-60°N during spring-summer for both 2020 and 2021 averaged ∼3 Dobson Units (DU) (or ∼7%-8%) below normal. These ozone reductions in 2020 and 2021 were the lowest in the 2005-2021 record. We also include satellite measurements of tropospheric NO2 that exhibit reductions of ∼10%-20% in the NH in early spring-to-summer 2020 and 2021, suggesting that reduced pollution was the main cause for the low anomalies in NH TCO in 2020 and 2021. Reductions of TCO ∼2 DU (7%) are also measured in the Southern Hemisphere in austral summer but are not associated with reduced NO2.

NO2 pollution over selected cities in the Po Valley in 2018-2021 and its possible effects on boosting COVID-19 deaths

This work analyzes nitrogen dioxide (NO₂) pollution over a set of cities in the Po Valley in northern Italy, using satellite and in situ observations. The cities include Milan, Bergamo, and Brescia, the first area of the COVID-19 outbreak and diffusion in Italy, with a higher mortality rate than in other parts of Italy and Europe. The analysis was performed for three years, from May 2018 to April 2021, including the period of first-wave diffusion of COVID-19 over the Po Valley, that is, January 2020–April 2020. The study aimed at giving a more general picture of the NO₂ temporal and spatial variation, possibly due to the lockdown adopted for the pandemic crisis containment and other factors, such as the meteorological conditions and the seasonal cycle. We have mainly investigated two effects: first, the correlation of NO₂ pollution with atmospheric parameters such as air and dew point temperature, and second the possible correlation between air quality and COVID-19 deaths, which could explain the high mortality rate. We have found a good relationship between air quality and temperature. In light of this relationship, we can conclude that the air quality improvement in March 2020 was primarily because of the lockdown adopted to prevent and limit virus diffusion. We also report a good correlation between NO₂ pollution and COVID-19 deaths, which is not seen when considering a reference city in the South of Italy. The critical factor in explaining the difference is the persistence of air pollution in the Po Valley in wintertime. We found that NO₂ pollution shows a seasonal cycle, yielding a non-causal correlation with the COVID-19 deaths. However, causality comes in once we read the correlation in the context of current and recent epidemiological evidence and leads us to conclude that air pollution may have acted as a significant risk factor in boosting COVID-19 fatalities.

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.