Global, continental, and national variation in PM2.5, O3, and NO2 concentrations during the early 2020 COVID-19 lockdown

A global comparative study on the impact of COVID-19 policy on atmospheric nitrogen dioxide (NO2): Evidence from remote sensing data in 2019-2022

A significant body of research has documented the profound changes in global atmospheric conditions during the COVID-19 pandemic. However, there is still an inadequate comprehensive comparison and assessment of countries before, during, and after the pandemic. Variations in restriction policies, human behaviors, and national traits lead to significant differences in how restriction policies affect atmospheric pollution. This study focuses on NO2, a pollutant with high temporal sensitivity, and utilizes the Oxford COVID-19 policy stringency index along with demographic information. Through spatial-temporal mapping, we analyzed NO2 emission fluctuations and calculated the emission changes in each country. Drawing from this analysis, we explored the relationships among these factors and found that over the span of 2019-2022, across 193 countries, global NO2 emissions displayed a distinct trajectory: initially decreasing, subsequently rebounding, and eventually fluctuating. Most countries exhibited seasonal variations in NO2 emissions. Additionally, the study uncovered a correlation between the stringency of COVID-19 policies and the reduction in NO2 emissions: as policies became stricter, emissions significantly decreased in most countries. In contrast, in countries with lower population densities, stricter policies paradoxically led to an increase in emissions. These findings underscore the importance of considering demographic factors and geographical context in the formulation and implementation of environmental policies.

Policy implications for synergistic management of PM2.5 and O3 pollution from a pattern-process-sustainability perspective in China

In recent years, the pattern of air pollution in China has changed profoundly, and PM2.5 and surface ozone (O3) have become the main air pollutants affecting the air quality of cities and regions in China. The synergistic control of the two has become the key to the sustainable improvement of air quality in China. In this study, we investigated and analyzed the spatial and temporal distribution patterns, exposure health risks, key drivers, and sustainable characteristics of PM2.5 and O3 concentrations in China from 2013 to 2022 at the national and city cluster scales by combining methodological models such as spatial statistics, trend analysis, exposure-response function, Hurst index, and multi-scale geographically weighted regression (MGWR) model. Ultimately, a synergistic management system for PM2.5 and O3 pollution was proposed. The results showed that: (1) The PM2.5 concentration decreased at a rate of 1.45 μg/m3 per year (p < 0.05), while the O3 concentration increased at a rate of 2.54 μg/m3 per year (p < 0.05). The trends of the two concentrations showed significant differences in spatial distribution. (2) Population exposure risks to pollutants showed an increasing trend, with PM2.5 and O3 increasing by 55.1 % and 42.7 %, respectively. The annual deaths associated with exposure to PM2.5 and O3 demonstrated a decreasing and inverted U-shaped trend, respectively, with annual average deaths of 1.312 million and 98,000. Significant regional disparities in health risks from these pollutants were influenced by socio-economic factors such as industrial activities and population density. In the future, it is expected that more than half of China's regions will be exposed to rising risks of PM2.5 and O3 population exposure. (3) Key drivers of regional exacerbation in PM2.5 and O3 levels include the number of industrial enterprises above designated size (NSIE) and population agglomeration (PA), while the disposable income of urban residents (URDI), technological innovation (TI), and government attention level (GAL) emerged as primary factors in controlling pollution hotspots, ranked in order of influence from greatest to least as TI > GAL > URDI. Overall, this study sheds light on the current status of air pollution and health risk sustainability in China and enhances the understanding of future air pollution dynamics in China. The results of the study may help to develop effective targeted control measures to synergize the management of PM2.5 and O3 in different regions.

First close insight into global daily gapless 1 km PM2.5 pollution, variability, and health impact

Here we retrieve global daily 1 km gapless PM2.5 concentrations via machine learning and big data, revealing its spatiotemporal variability at an exceptionally detailed level everywhere every day from 2017 to 2022, valuable for air quality monitoring, climate change, and public health studies. We find that 96%, 82%, and 53% of Earth's populated areas are exposed to unhealthy air for at least one day, one week, and one month in 2022, respectively. Strong disparities in exposure risks and duration are exhibited between developed and developing countries, urban and rural areas, and different parts of cities. Wave-like dramatic changes in air quality are clearly seen around the world before, during, and after the COVID-19 lockdowns, as is the mortality burden linked to fluctuating air pollution events. Encouragingly, only approximately one-third of all countries return to pre-pandemic pollution levels. Many nature-induced air pollution episodes are also revealed, such as biomass burning.

COVID-19's environmental impacts: Challenges and implications for the future

Strict measures have curbed the spread of COVID-19, but waste generation and movement limitations have had an unintended impact on the environment over the past 3 years (2020-2022). Many studies have summarized the observed and potential environmental impacts associated with COVID-19, however, only a few have quantified and compared the effects of these unintended environmental impacts; moreover, whether COVID-19 policy stringency had the same effects on the main environmental topic (i.e., CO2 emissions) across the 3 years remains unclear. To answer these questions, we conducted a systematic review of the recent literature and analyzed the main findings. We found that the positive environmental effects of COVID-19 have received more attention than the negative ones (50.6 % versus 35.7 %), especially in emissions reduction (34 % of total literature). Medical waste (14.5 %) received the highest attention among the negative impacts. Although global emission reduction, especially in terms of CO2, has received significant attention, the positive impacts were temporary and only detected in 2020. Strict COVID-19 policies had a more profound and significant effect on CO2 emissions in the aviation sector than in the power and industry sectors. For example, compared with 2019, international aviation related CO2 emissions dropped by 59 %, 49 %, and 25 % in 2020, 2021, and 2022, respectively, while industry related ones dropped by only 3.16 % in 2020. According to our developed evaluation matrix, medical wastes and their associated effects, including the persistent pollution caused by antibiotic resistance genes, heavy metals and microplastics, are the main challenges post the pandemic, especially in China and India, which may counteract the temporary environmental benefits of COVID-19. Overall, the presented results demonstrate methods to quantify the environmental effects of COVID-19 and provide directions for policymakers to develop measures to address the associated environmental issues in the post-COVID-19 world.

Elemental composition of atmospheric PM10 during COVID-19 lockdown and recovery periods in Moscow (April-July 2020)

Changes in the concentrations of PM10-bound potentially toxic elements (PTEs) during the COVID-19 lockdown period and after the revocation of restrictions were analyzed using the data received at the Aerosol Complex of Moscow State University in April-July 2020. During the lockdown, the input of biomass combustion products enriched in PTEs from the Moscow region hindered the decrease in pollutant concentrations. After the introduction of the self-isolation regime, lower concentrations of most PTEs occurred due to the decrease in anthropogenic activity and the rainy meteorological conditions. After the revocation of restrictive measures, the PTE concentrations began to increase. Multivariate statistical analysis (APCA-MLR) identified the main sources of atmospheric pollutants as urban dust, non-exhaust traffic emissions, and combustion and exhaust traffic emissions. PM10 particles were significantly enriched with Sb, Cd, Sn, Bi, S, Pb, Cu, Mo, and Zn. The total non-carcinogenic and carcinogenic risks, calculated according to the U.S. EPA model, decreased by 24% and 23% during the lockdown; after the removal of restrictions, they increased by 61% and 72%, respectively. The study provides insight into the PTE concentrations and their main sources at different levels of anthropogenic impact.

Linkage between Airborne Particulate Matter and Viral Pandemic COVID-19 in Bucharest

The long-distance spreading and transport of airborne particulate matter (PM) of biogenic or chemical compounds, which are thought to be possible carriers of SARS-CoV-2 virions, can have a negative impact on the incidence and severity of COVID-19 viral disease. Considering the total Aerosol Optical Depth at 550 nm (AOD) as an atmospheric aerosol loading variable, inhalable fine PM with a diameter ≤2.5 µm (PM2.5) or coarse PM with a diameter ≤10 µm (PM10) during 26 February 2020-31 March 2022, and COVID-19's five waves in Romania, the current study investigates the impact of outdoor PM on the COVID-19 pandemic in Bucharest city. Through descriptive statistics analysis applied to average daily time series in situ and satellite data of PM2.5, PM10, and climate parameters, this study found decreased trends of PM2.5 and PM10 concentrations of 24.58% and 18.9%, respectively compared to the pre-pandemic period (2015-2019). Exposure to high levels of PM2.5 and PM10 particles was positively correlated with COVID-19 incidence and mortality. The derived average PM2.5/PM10 ratios during the entire pandemic period are relatively low (<0.44), indicating a dominance of coarse traffic-related particles' fraction. Significant reductions of the averaged AOD levels over Bucharest were recorded during the first and third waves of COVID-19 pandemic and their associated lockdowns (~28.2% and ~16.4%, respectively) compared to pre-pandemic period (2015-2019) average AOD levels. The findings of this research are important for decision-makers implementing COVID-19 safety controls and health measures during viral infections.

Spatial-temporal evolution patterns and drivers of PM2.5 chemical fraction concentrations in China over the past 20 years

The quantitative assessment of the spatial and temporal variability and drivers of fine particulate matter (PM2.5) fraction concentrations are important for pollution control and public health preservation in China. In this study, we investigated the spatial temporal variation of PM2.5 chemical component based on the PM2.5 chemical component datasets from 2000 to 2019 and revealed the driving forces of the differences in the spatial distribution using geodetector model (GD), multi-scale geographically weighted regression model (MGWR), and a two-step clustering approach. The results show that: the PM2.5 chemical fraction concentrations show a trend of first increasing (2000-2007) and then decreasing (2007-2019). From 2000 to 2019, the change rates of PM2.5, organic matter (OM), black carbon (BC), sulfates (SO2- 4), ammonium (NH+ 4), and nitrates (NO- 3) were -0.59, -0.23, -0.07, -0.15, -0.02, and 0.04μg/m3/yr in the entirety of China. The secondary aerosol (i.e., SO2- 4, NO- 3, and NH+ 4; SNA) had the highest fraction in PM2.5 concentrations (55.6-68.1% in different provinces), followed by OM and BC. Spatially, North, Central, and East China are the regions with the highest PM2.5 chemical component concentrations in China; meanwhile, they are also the regions with the most significant decrease in PM2.5 chemical fraction concentrations. The GD and MGWR model shows that among all variables, the number of enterprises, disposable income, private car ownership, and the share of secondary industry non-linearly enhance the differences in the spatial distribution of PM2.5 component concentrations. Electricity consumption has the strongest influence on NH+ 4 emissions in Northwest China and BC and OM emissions in Northeast China.

Biological effects of particulate matter samples during the COVID-19 pandemic: a comparison with the pre-lockdown period in Northwest Italy

In 2020, during the COVID-19 pandemic, containment measures were applied inducing potential changes in air pollutant concentrations and thus in air toxicity. This study evaluates the role of restrictions on biological effects of particulate matter (PM) in different Northwest Italy sites: urban background, urban traffic, rural, and incinerator. Daily PM samples collected in 2020 were pooled according to restrictions: January/February (no restrictions), March and April (first lockdown), May/June and July/August/September (low restrictions), October/November/December (second lockdown). The 2019 samples (pre-pandemic period) were pooled as 2020 for comparison. Pools were extracted with organic solvents and extracts were tested to assess cytotoxicity (WST-1 assay) and genotoxicity (comet assay) on BEAS-2B cells, mutagenicity (Ames test) on TA98 and TA100 Salmonella typhimurium strains, and estrogenic activity (gene reporter assay) on MELN cells. Pollutant concentrations were also analyzed (PM10, PM2.5, polycyclic aromatic hydrocarbons). No difference was observed for PM and polycyclic aromatic hydrocarbon concentrations between 2020 and 2019. During lockdown months (2020), PM cytotoxicity/genotoxicity was significantly lower in some sites than during 2019, while considering PM mutagenicity/estrogenic activity some differences were detected but without statistical significance. PM extract effects decreased in some sites during 2020; this may be due to lockdowns that reduced/modified pollutant emissions and may be related also to complex PM origin/formation and to meteorological conditions. In conclusion, the study confirms that PM biological effects cannot be assessed considering only the PM concentration and suggests to include a battery of bioassay for air quality monitoring in order to protect human health from air pollution effects.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11869-023-01381-6.

Spatial interpolation of regional PM2.5 concentrations in China during COVID-19 incorporating multivariate data

During specific periods when the PM_2.5 variation pattern is unusual, such as during the coronavirus disease 2019 (COVID-19) outbreak, epidemic PM_2.5 regional interpolation models have been relatively little investigated, and little consideration has been given to the residuals of optimized models and changes in model interpolation accuracy for the PM_2.5 concentration under the influence of epidemic phenomena. Therefore, this paper mainly introduces four interpolation methods (kriging, empirical Bayesian kriging, tensor spline function and complete regular spline function), constructs geographically weighted regression (GWR) models of the PM_2.5 concentration in Chinese regions for the periods from January-June 2019 and January-June 2020 by considering multiple factors, and optimizes the GWR regression residuals using these four interpolation methods, thus achieving the purpose of enhancing the model accuracy. The PM_2.5 concentrations in many regions of China showed a downward trend during the same period before and after the COVID-19 outbreak. Atmospheric pollutants, meteorological factors, elevation, zenith wet delay (ZWD), normalized difference vegetation index (NDVI) and population maintained a certain relationship with the PM_2.5 concentration in terms of linear spatial relationships, which could explain why the PM_2.5 concentration changed to a certain extent. By evaluating the model accuracy from two perspectives, i.e., the overall interpolation effect and the validation set interpolation effect, the results showed that all four interpolation methods could improve the numerical accuracy of GWR to different degrees, among which the tensor spline function and the fully regular spline function achieved the most stable effect on the correction of GWR residuals, followed by kriging and empirical Bayesian kriging.

Assessing regional emissions of vehicle-based tire wear particle from macro-to micro/nano-scales with pandemic lockdowns and electromobility scenarios implications

Despite increasing the public awareness of ubiquity of microplastics (MPs) in air, the issue on particular source of tire wear particles (TWPs) emission into atmosphere and their exposure-associated human health has not received the attention it deserves. Here we linked vehicle kilometers traveled (VKT) estimates covering demography, socio-environmental, and transportation features and emission factors to predict regional emission patterns of TWP-derived atmospheric MPs. A data-driven probabilistic approach was developed to consider variability across the datasets and uncertainty of model parameters in terms of country-level and vehicle-type emissions. We showed that country-specific VKT from billion to trillion vehicle-kilometer resulted in 103-105 metric tons of airborne TWP-derived atmospheric MPs annually in the period 2015-2019, with the highest emissions from passenger cars and heavy-duty vehicles. On average, we found that airborne TWP emissions from passenger cars by country had substantial decreased (up to ∼33%) during COVID-19 lockdowns in 2020 and pronounced increased (by a factor ∼1.9) from vehicle electrification by the next three decades. We conclude that the stunning mass of airborne TWP is a predominant source of atmospheric MP. We underscore the necessity of TWP emissions control among the United States, China, and India. Our findings can be of great use to environmental transportation planners for devising vehicle/tire-oriented decision support tools. Our data offer information to enhance TWP-exposure estimates, to examine long-term exposure trends, and subsequently to improve health risk assessment during pandemic outbreak and future electrification.

Effect of restricted emissions during COVID-19 on atmospheric aerosol chemistry in a Greater Cairo suburb: Characterization and enhancement of secondary inorganic aerosol production

To prevent the rapid spreading of the COVID-19 pandemic, the Egyptian government had imposed partial lockdown restrictions which led emissions reduction. This served as ideal conditions for a natural experiment, for study the effect of partial lockdown on the atmospheric aerosol chemistry and the enhanced secondary inorganic aerosol production in a semi-desert climate area like Egypt. To achieve this objective, SO₂, NO₂, and PM_2.5 and their chemical compositions were measured during the pre-COVID, COVID partial lockdown, and post-COVID periods in 2020 in a suburb of Greater Cairo, Egypt. Our results show that the SO₂, NO₂, PM_2.5 and anthropogenic elements concentrations follow the pattern pre-COVID > post-COVID > COVID partial lockdown. SO₂ and NO₂ reductions were high compared with their secondary products during the COVID partial lockdown compared with pre-COVID. Although, PM_2.5, anthropogenic elements, NO₂, SO₂, SO₄ ^2-, NO₃ ^-, and NH₄ ⁺ decreased by 39%, 38-55%, 38%, 32.9%. 9%, 14%, and 4.3%, respectively, during the COVID partial lockdown compared with pre-COVID, with the secondary inorganic ions (SO₄ ^2-, NO₃ ^-, and NH₄ ⁺) being the dominant components in PM_2.5 during the COVID partial lockdown. Moreover, the enhancement of NO₃ ^- and SO₄ ^2- formation during the COVID partial lockdown was high compared with pre-COVID. SO₄ ^2- and NO₃ ^- formation enhancements were significantly positive correlated with PM_2.5 concentration. Chemical forms of SO₄ ^2- and NO₃ ^- were identified in PM_2.5 based on their NH₄ ⁺/SO₄ ^2- molar ratio and correlation between NH₄ ⁺ and both NO₃ ^- and SO₄ ^2-. The particles during the COVID partial lockdown were more acidic than those in pre-COVID.

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.

Cumulative effects of air pollution and climate drivers on COVID-19 multiwaves in Bucharest, Romania

Over more than two years of global health crisis due to ongoing COVID-19 pandemic, Romania experienced a five-wave pattern. This study aims to assess the potential impact of environmental drivers on COVID-19 transmission in Bucharest, capital of Romania during the analyzed epidemic period. Through descriptive statistics and cross-correlation tests applied to time series of daily observational and geospatial data of major outdoor inhalable particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) or ≤ 10 µm (PM10), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), carbon monoxide (CO), Aerosol Optical Depth at 550 nm (AOD) and radon (²²²Rn), we investigated the COVID-19 waves patterns under different meteorological conditions. This study examined the contribution of individual climate variables on the ground level air pollutants concentrations and COVID-19 disease severity. As compared to the long-term average AOD over Bucharest from 2015 to 2019, for the same year periods, this study revealed major AOD level reduction by ~28 % during the spring lockdown of the first COVID-19 wave (15 March 2020-15 May 2020), and ~16 % during the third COVID-19 wave (1 February 2021-1 June 2021). This study found positive correlations between exposure to air pollutants PM2.5, PM10, NO₂, SO₂, CO and ²²²Rn, and significant negative correlations, especially for spring-summer periods between ground O₃ levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance with COVID-19 incidence and deaths. For the analyzed time period 1 January 2020-1 April 2022, before and during each COVID-19 wave were recorded stagnant synoptic anticyclonic conditions favorable for SARS-CoV-2 virus spreading, with positive Omega surface charts composite average (Pa/s) at 850 mb during fall- winter seasons, clearly evidenced for the second, the fourth and the fifth waves. These findings are relevant for viral infections controls and health safety strategies design in highly polluted urban environments.

Urban air quality in Xinjiang and snow chemistry of Urumqi Glacier No. 1 during COVID-19's restrictions

The unprecedented COVID-19 outbreak impacted the world in many aspects. Air pollutants were largely reduced in cities worldwide in 2020. Using samples from two snow pits dug separately in 2019 and 2020 in Urumqi Glacier No. 1 (UG1) in the Xinjiang Uygur Autonomous Region (Xinjiang), China, we measured water-stable isotopes, soluble ions, and black and organic carbon (BC and OC). Both carbon types show no significant variations in the snow-pit profiles dated from 2018 through 2020. The deposition of anthropogenically induced soluble ions (K⁺, Cl^-, SO₄^2-, and NO₃^-) in the snow decreased to 20-40% of their respective concentrations between 2019 and 2020; however, they increased 2- to fourfold from 2018 to 2019. We studied the daily concentrations of SO₂ (2019-2020), NO₂ (2015-2020), CO (2019-2020), and PM_2.5 (2019-2020) measured in the sixteen major cities and towns across Xinjiang. The variabilities in these air pollutants were supposed to illustrate the air quality in the urban area and represent the change in the source area. The NO₂ decreased in response to mobility restrictions imposed by local governments, while SO₂, CO, and PM_2.5 did not consistently correspond. This difference indicates that the restriction measures primarily affected traffic. The increases in chemical species in the snow from 2018 to 2019 and the subsequent decreases from 2019 to 2020 were consistent with the variations in SO₂ and NO₂ measured in urban air and estimated by MERRA-2 model. Therefore, the pandemic could possibly have an impact on snow chemistry of the Tien-Shan glaciers via reduced traffic and industrial intensity; more evidence would be obtained from ice cores, tree rings, and other archives in the future.

The Atmospheric Environment Effects of the COVID-19 Pandemic: A Metrological Study

Since the COVID-19 outbreak, the scientific community has been trying to clarify various problems, such as the mechanism of virus transmission, environmental impact, and socio-economic impact. The spread of COVID-19 in the atmospheric environment is variable and uncertain, potentially resulting in differences in air pollution. Many scholars are striving to explore the relationship between air quality, meteorological indicators, and COVID-19 to understand the interaction between COVID-19 and the atmospheric environment. In this study, we try to summarize COVID-19 studies related to the atmospheric environment by reviewing publications since January 2020. We used metrological methods to analyze many publications in Web of Science Core Collection. To clarify the current situation, hotspots, and development trends in the field. According to the study, COVID-19 research based on the atmospheric environment has attracted global attention. COVID-19 and air quality, meteorological factors affecting the spread of COVID-19, air pollution, and human health are the main topics. Environmental variables have a certain impact on the spread of SARS-CoV-2, and the prevalence of COVID-19 has improved the atmospheric environment to some extent. The findings of this study will aid scholars to understand the current situation in this field and provide guidance for future research.

Impacts of exposure to air pollution, radon and climate drivers on the COVID-19 pandemic in Bucharest, Romania: A time series study

During the ongoing global COVID-19 pandemic disease, like several countries, Romania experienced a multiwaves pattern over more than two years. The spreading pattern of SARS-CoV-2 pathogens in the Bucharest, capital of Romania is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation. Through descriptive statistics and cross-correlation analysis applied to daily time series of observational and geospatial data, this study aims to evaluate the synergy of COVID-19 incidence and lethality with air pollution and radon under different climate conditions, which may exacerbate the coronavirus' effect on human health. During the entire analyzed period 1 January 2020-21 December 2021, for each of the four COVID-19 waves were recorded different anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere, and favorable stability conditions during fall-early winter seasons for COVID-19 disease fast-spreading, mostly during the second, and the fourth waves. As the temporal pattern of airborne SARS-CoV-2 and its mutagen variants is affected by seasonal variability of the main air pollutants and climate parameters, this paper found: 1) the daily outdoor exposures to air pollutants (particulate matter PM2.5 and PM10, nitrogen dioxide-NO₂, sulfur dioxide-SO₂, carbon monoxide-CO) and radon - ²²²Rn, are directly correlated with the daily COVID-19 incidence and mortality, and may contribute to the spread and the severity of the pandemic; 2) the daily ground ozone-O₃ levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance are anticorrelated with the daily new COVID-19 incidence and deaths, averageingful for spring-summer periods. Outdoor exposure to ambient air pollution associated with radon is a non-negligible driver of COVID-19 transmission in large metropolitan areas, and climate variables are risk factors in spreading the viral infection. The findings of this study provide useful information for public health authorities and decision-makers to develop future pandemic diseases strategies in high polluted metropolitan environments.

Mediating Role of Fine Particles Abatement on Pediatric Respiratory Health During COVID-19 Stay-at-Home Order in San Diego County, California

Lower respiratory tract infections disproportionately affect children and are one of the main causes of hospital referral and admission. COVID-19 stay-at-home orders in early 2020 led to substantial reductions in hospital admissions, but the specific contribution of changes in air quality through this natural experiment has not been examined. Capitalizing on the timing of the stay-at-home order, we quantified the specific contribution of fine-scale changes in PM2.5 concentrations to reduced respiratory emergency department (ED) visits in the pediatric population of San Diego County, California. We analyzed data on pediatric ED visits (n = 72,333) at the ZIP-code level for respiratory complaints obtained from the ED at Rady Children's Hospital in San Diego County (2015-2020) and ZIP-code level PM2.5 from an ensemble model integrating multiple machine learning algorithms. We examined the decrease in respiratory visits in the pediatric population attributable to the stay-at-home order and quantified the contribution of changes in PM2.5 exposure using mediation analysis (inverse of odds ratio weighting). Pediatric respiratory ED visits dropped during the stay-at-home order (starting on 19 March 2020). Immediately after this period, PM2.5 concentrations, relative to the counterfactual values based in the 4-year baseline period, also decreased with important spatial variability across ZIP codes in San Diego County. Overall, we found that decreases in PM2.5 attributed to the stay-at-home order contributed to explain 4% of the decrease in pediatric respiratory ED visits. We identified important spatial inequalities in the decreased incidence of pediatric respiratory illness and found that brief decline in air pollution levels contributed to a decrease in respiratory ED visits.

Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India

The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM2.5 concentrations and an enhancement in the O3 concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O3 formation, comprising 89.4%, 83.1%, and 88.9% of the O3 sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O3 concentrations at the surface layer. Compared with the Pre1 period, the O3 enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O3 removal rate by horizontal transport. During the Tri period, a slower consumption of O3 by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O3. Emission and aerosol processes constituted the major positive contributions to the net surface PM2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM2.5 production from emission and aerosol processes. The increased vertical transport rate of PM2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM2.5 during the Lock periods.

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes

La Oroya is a city in the Peruvian Andes that has suffered a serious deterioration in its air quality, especially due to the high rate of sulfur dioxide (SO2) emissions, which underlines the importance of knowing its sources of contamination and variation over the years. In this sense, this study aimed to evaluate the immission levels and determine the sources of SO2 contamination in La Oroya. This analysis was performed using the hourly concentration data of SO2, and meteorological variables (wind speed and direction), which were analyzed for a period of three years (2018-2020). Graphs of time series, wind and pollutant roses, bivariate polar graphs, clustering k-means, nonparametric statistical tests, and the application of the conditional bivariate probability function were performed to analyze the data and identify the emission sources. The mean concentration of SO2 was 264.2 μg m-3 for the study period, where 55.66 and 2.37% of the evaluated days exceeded the guideline values recommended by the World Health Organization and the Peruvian Environmental Quality Standard for air for 24 h, respectively. The results showed a defined pattern for the daily and monthly variations, with peaks in the morning hours (0900-1000 h LT) and at the end of the year (December), respectively. The main sources of SO2 emissions identified were light and heavy vehicles that travel through the Central Highway, the La Oroya Metallurgical Complex, the transit of vehicles within the city, and the diesel-electric locomotives that provide cargo transportation services and tourism passenger transportation. The article attempts to contribute to the development of adequate air quality management policies.

Association of population migration with air quality: Role of city attributes in China during COVID-19 pandemic (2019-2021)

Atmospheric pollution studies have linked diminished human activity during the COVID-19 pandemic to improve air quality. This study was conducted during January to March (2019-2021) in 332 cities in China to examine the association between population migration and air quality, and examined the role of three city attributes (pollution level, city scale, and lockdown status) in this effect. This study assessed six air pollutants, namely CO, NO2, O3, PM10, PM2.5, and SO2, and measured meteorological data, with-in city migration (WCM) index, and inter-city migration (ICM) index. A linear mixed-effects model with an autoregressive distributed lag model was fitted to estimate the effect of the percent change in migration on air pollution, adjusting for potential confounding factors. In summary, lower migration was associated with decreased air pollution (other than O3). Pollution change in susceptibility is more likely to occur in NO2 decrease and O3 increase, but unsusceptibility is more likely to occur in CO and SO2, to city attributes from low migration. Cities that are less air polluted and population-dense may benefit more from decreasing PM10 and PM2.5. The associations between population migration and air pollution were stronger in cities with stringent traffic restrictions than in cities with no lockdowns. Based on city attributes, an insignificant difference was observed between the effects of ICM and WCM on air pollution. Findings from this study may gain knowledge about the potential interaction between migration and city attributes, which may help decision-makers adopt air-quality policies with city-specific targets and paths to pursue similar air quality improvements for public health but at a much lower economic cost than lockdowns.

Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities

The COVID-19 prevention and control measures are taken by China's government, especially traffic restrictions and production suspension, had spillover effects on air quality improvement. These effects differed among cities, but these differences have not been adequately studied. To provide more knowledge, we studied the air quality index (AQI) and five air pollutants (PM2.5, PM10, SO2, NO2, and O3) before and after the COVID-19 outbreak in Shanghai, Wuhan, and Tangshan. The pollution data from two types of monitoring stations (traffic and non-traffic stations) were separately compared and evaluated. We used monitoring data from the traffic stations to study the emission reduction caused by traffic restrictions. Based on monitoring data from the non-traffic stations, we established a difference-in-difference model to study the emission reduction caused by production suspension. The COVID-19 control measures reduced AQI and the concentrations of all pollutants except O3 (which increased greatly), but the magnitude of the changes differed among the three cities. The control measures improved air quality most in Wuhan, followed by Shanghai and then Tangshan. We investigated the reasons for these differences and found that differences in the characteristics of these three types of cities could explain these differences in spillover effects. Understanding these differences could provide some guidance and support for formulating differentiated air pollution control measures in different cities. For example, whole-process emission reduction technology should be adopted in cities with the concentrated distribution of continuous process enterprises, whereas vehicles that use cleaner energy and public transport should be vigorously promoted in cities with high traffic development level.

Exposure Risk of Global Surface O3 During the Boreal Spring Season

Surface ozone (O₃) is an oxidizing gaseous pollutant; long-term exposure to high O₃ concentrations adversely affects human health. Based on daily surface O₃ concentration data, the spatiotemporal characteristics of O₃ concentration, exposure risks, and driving meteorological factors in 347 cities and 10 major countries (China, Japan, India, South Korea, the United States, Poland, Spain, Germany, France, and the United Kingdom) worldwide were analyzed using the MAKESENS model, Moran' I analysis, and Generalized additive model (GAM). The results indicated that: in the boreal spring season from 2015 to 2020, the global O₃ concentration exhibited an increasing trend at a rate of 0.6 μg/m³/year because of the volatile organic compounds (VOCs) and NOx changes caused by human activities. Due to the lockdown policies after the outbreak of COVID-19, the average O₃ concentration worldwide showed an inverted U-shaped growth during the study period, increasing from 21.9 μg/m³ in 2015 to 27.3 μg/m³ in 2019, and finally decreasing to 25.9 μg/m³ in 2020. According to exposure analytical methods, approximately 6.32% of the population (31.73 million people) in the major countries analyzed reside in rapidly increasing O₃ concentrations. 6.53% of the population (32.75 million people) in the major countries were exposed to a low O₃ concentration growth environment. Thus, the continuous increase of O₃ concentration worldwide is an important factor leading to increasing threats to human health. Further we found that mean wind speed, maximum temperature, and relative humidity are the main factors that determine the change of O₃ concentration. Our research results are of great significance to the continued implementation of strict air quality policies and prevention of population hazards. However, due to data limitations, this research can only provide general trends in O₃ and human health, and more detailed research will be carried out in the follow-up.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12403-022-00463-7.

Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.

Differential health and economic impacts from the COVID-19 lockdown between the developed and developing countries: Perspective on air pollution

It is enlightening to determine the discrepancies and potential reasons for the degree of impact from the COVID-19 control measures on air quality as well as the associated health and economic impacts. Analysis of air quality, socio-economic factors, and meteorological data from 447 cities in 46 countries indicated that the COVID-19 control measures had significant impacts on the PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) concentrations in 20 (reduced PM2.5 concentrations of -7.4-29.1 μg m-3) of the selected 46 countries. In these 20 countries, the robustly distinguished changes in the PM2.5 concentrations caused by the control measures differed between the developed (95% confidence interval (CI): -2.7-5.5 μg m-3) and developing countries (95% CI: 8.3-23.2 μg m-3). As a result, the COVID-19 lockdown reduced death and hospital admissions change from the decreased PM2.5 concentrations by 7909 and 82,025 cases in the 12 developing countries, and by 78 and 1214 cases in the eight developed countries. The COVID-19 lockdown reduced the economic cost from the PM2.5 related health burden by 54.0 million dollars in the 12 developing countries and by 8.3 million dollars in the eight developed countries. The disparity was related to the different chemical compositions of PM2.5. In particular, the concentrations of primary PM2.5 (e.g., BC) in cities of developing countries were 3-45 times higher than those in developed countries, so the mass concentration of PM2.5 was more sensitive to the reduced local emissions in developing countries during the COVID-19 control period. The mass fractions of secondary PM2.5 in developed countries were generally higher than those in developing countries. As a result, these countries were more sensitive to the secondary atmospheric processing that may have been enhanced due to reduced local emissions.

Pollutant Concentration Changes During the COVID-19 Lockdown in Barcelona and Surrounding Regions: Modification of Diurnal Cycles and Limited Role of Meteorological Conditions

One of the consequences of the COVID-19 lockdowns has been the modification of the air quality in many cities around the world. This study focuses on the variations in pollutant concentrations and how important meteorological conditions were for those variations in Barcelona and the surrounding area during the 2020 lockdown. Boundary-layer height, wind speed, and precipitation were compared between mid-March and April 2016-2019 (pre-lockdown) and the same period in 2020 (during lockdown). The results show the limited influence of meteorological factors on horizontal and vertical dispersion conditions. Compared with the pre-lockdown period, during lockdown the boundary-layer height slightly increased by between 5% and 9%, mean wind speed was very similar, and the fraction of days with rainfall increased only marginally, from 0.33 to 0.34, even though April 2020 was extremely wet in the study area. Variations in nitrogen dioxide ( NO 2 ), particulate matter with a diameter less than 10 μ m (PM10), and ozone ( O 3 ) concentrations over a 10-year period showed a 66% reduction in NO 2 , 37% reduction in PM10, and 27% increase in O 3 at a traffic station in Barcelona. The differences in the daily concentration cycle between weekends and weekdays were heavily smoothed for all pollutants considered. The afternoon NO 2 peak at the traffic station was suppressed compared with the average daily cycle. The analysis of ozone was extended to the regional scale, revealing lower concentrations at rural sites and higher ones in urban zones, especially in Barcelona and the surrounding area. The results presented not only complement previous air quality COVID-19 lockdown studies but also provide insights into the effects of road-traffic reduction.

Contributions of Traffic and Industrial Emission Reductions to the Air Quality Improvement after the Lockdown of Wuhan and Neighboring Cities Due to COVID-19

Wuhan was locked down from 23 January to 8 April 2020 to prevent the spread of the novel coronavirus disease 2019 (COVID-19). Both public and private transportation in Wuhan and its neighboring cities in Hubei Province were suspended or restricted, and the manufacturing industry was partially shut down. This study collected and investigated ground monitoring data to prove that the lockdowns of the cities had significant influences on the air quality in Wuhan. The WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model was used to evaluate the emission reduction from transportation and industry sectors and associated air quality impact. The results indicate that the reduction in traffic emission was nearly 100% immediately after the lockdown between 23 January and 8 February and that the industrial emission tended to decrease by about 50% during the same period. The industrial emission further deceased after 9 February. Emission reduction from transportation and that from industry was not simultaneous. The results imply that the shutdown of industry contributed significantly more to the pollutant reduction than the restricted transportation.

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

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic provided an opportunity for the environment to reduce ambient pollution despite the economic, social and health disruption to the world. The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different countries of the world before and after 2020. In this ecological study, we used AQI obtained from the free available databases such as the World Air Quality Index (WAQI). Bivariate correlation analysis was used to explore the correlations between meteorological and AQI variables. Mean differences (standard deviation: SD) of AQI parameters of different years were tested using paired-sample t-test or Wilcoxon signed-rank test as appropriate. Multivariable linear regression analysis was conducted to recognize meteorological variables affecting the AQI parameters.

RESULTS

AQI-PM2.5, AQI-PM10 and AQI-NO2 changes were significantly higher before and after 2020, simultaneously with COVID-19 restrictions in different cities of the world. The overall changes of AQI-PM2.5, AQI-PM10 and AQI-NO2 in 2020 were - 7.36%, - 17.52% and - 20.54% compared to 2019. On the other hand, these results became reversed in 2021 (+ 4.25%, + 9.08% and + 7.48%). In general, the temperature and relative humidity were inversely correlated with AQI-PM2.5, AQI-PM10 and AQI-NO2. Also, after adjusting for other meteorological factors, the relative humidity was inversely associated with AQI-PM2.5, AQI-PM10 and AQI-NO2 (β = - 1.55, β = - 0.88 and β = - 0.10, P < 0.01, respectively).

CONCLUSIONS

The results indicated that air quality generally improved for all pollutants except carbon monoxide and ozone in 2020; however, changes in 2021 have been reversed, which may be due to the reduction of some countries' restrictions. Although this quality improvement was temporary, it is an important result for planning to control environmental pollutants.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM_2.5, PM₁₀, PMC (coarse fraction of PM), NO₂, SO₂, NOx, CO, O₃ and the total gaseous oxidant (OX = NO₂ + O₃) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO₂ and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO₂ and between 30% and 40% in mean PM_2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM_2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO₂/CO ratio). Some Chinese cities showed similar increases in PM_2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O₃ concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO₂ anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO₂/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO₂ decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO₂ + O₃) showed that primary NO₂ emissions at urban locations were greater than the O₃ production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO₂ and O₃ concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM_2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

The Interplay between Housing Environmental Attributes and Design Exposures and Psychoneuroimmunology Profile-An Exploratory Review and Analysis Paper in the Cancer Survivors' Mental Health Morbidity Context

Adult cancer survivors have an increased prevalence of mental health comorbidities and other adverse late-effects interdependent with mental illness outcomes compared with the general population. Coronavirus Disease 2019 (COVID-19) heralds an era of renewed call for actions to identify sustainable modalities to facilitate the constructs of cancer survivorship care and health care delivery through physiological supportive domestic spaces. Building on the concept of therapeutic architecture, psychoneuroimmunology (PNI) indicators-with the central role in low-grade systemic inflammation-are associated with major psychiatric disorders and late effects of post-cancer treatment. Immune disturbances might mediate the effects of environmental determinants on behaviour and mental disorders. Whilst attention is paid to the non-objective measurements for examining the home environmental domains and mental health outcomes, little is gathered about the multidimensional effects on physiological responses. This exploratory review presents a first analysis of how addressing the PNI outcomes serves as a catalyst for therapeutic housing research. We argue the crucial component of housing in supporting the sustainable primary care and public health-based cancer survivorship care model, particularly in the psychopathology context. Ultimately, we illustrate a series of interventions aiming at how housing environmental attributes can trigger PNI profile changes and discuss the potential implications in the non-pharmacological treatment of cancer survivors and patients with mental morbidities.

PM2.5, NO2, wildfires, and other environmental exposures are linked to higher Covid 19 incidence, severity, and death rates

Numerous studies have linked outdoor levels of PM_2.5, PM₁₀, NO₂, O₃, SO₂, and other air pollutants to significantly higher rates of Covid 19 morbidity and mortality, although the rate in which specific concentrations of pollutants increase Covid 19 morbidity and mortality varies widely by specific country and study. As little as a 1-μg/m³ increase in outdoor PM_2.5 is estimated to increase rates of Covid 19 by as much as 0.22 to 8%. Two California studies have strongly linked heavy wildfire burning periods with significantly higher outdoor levels of PM_2.5 and CO as well as significantly higher rates of Covid 19 cases and deaths. Active smoking has also been strongly linked significantly increased risk of Covid 19 severity and death. Other exposures possibly related to greater risk of Covid 19 morbidity and mortality include incense, pesticides, heavy metals, dust/sand, toxic waste sites, and volcanic emissions. The exact mechanisms in which air pollutants increase Covid 19 infections are not fully understood, but are probably related to pollutant-related oxidation and inflammation of the lungs and other tissues and to the pollutant-driven alternation of the angiotensin-converting enzyme 2 in respiratory and other cells.

Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China

In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.

The Impact of the COVID-19 Pandemic on Gaseous and Solid Air Pollutants Concentrations and Emissions in the EU, with Particular Emphasis on Poland

This article presents the research on the analysis of the impact of social isolation caused by the COVID-19 pandemic on gaseous air pollutant concentrations. For this purpose, the authors presented (thermal maps) and analyzed the concentrations of selected gases such as NO2, CO, SO2, and PM2.5 particles during the strict quarantine period in Poland and other EU countries. Statistical analysis of the concentration level of these gases was performed. It was noticed that in Poland, Germany, and France, the concentrations of such gases as CO, NO2, and PM2.5 particles decreased, while in Italy and Spain, the tendency was the opposite. To verify whether the discovered dependencies are not a natural continuation of the trends shaping the given phenomenon, the time series of gas and PM2.5 particle emissions were analyzed. On this basis, the emission forecast up to 2023 was created, using the ARIMA class models. The obtained results allowed to construct five scenarios for the development of NO2, CO, SO2, and PM2.5 emissions until 2023, considering the impact of the COVID-19 pandemic. It was stated that in the optimistic scenario, in 2023, a decrease in CO, NO2, and PM2.5 emissions could be achieved by maximums of 51%, 95%, and 28%, respectively.