Changes in U.S. air pollution during the COVID-19 pandemic

An investigation of aquatic oil spills in the Philippines from 2000 to 2021

As an archipelago, the Philippines is heavily engaged in domestic and foreign shipping activities which makes it highly vulnerable to oil pollution. It is the purpose of this present paper to make a follow-up review of the oil spill situation in the Philippines which provides analysis and evaluation of aquatic oil spills in the past 22 years. Results showed that the frequency and volume of oil spills generally occur in areas with high maritime traffic and experienced short-term decreases on periods affected by economic recessions. The sources and causes of oil spills are discussed while examining the possible influences of the changing climate. While, these had been identified, there is a gap in the incident reporting of oil spills. It is recommended that data records on oil spill incidents in the Philippines be systematic, consistent and comprehensively entail information not limited to date, locality, source, cause, and spillage amount.

Six Diagnoses of Separation: Impact of COVID-19 on Pediatric Emergency Department Visits: A Multicenter Study

BACKGROUND

Coronavirus disease 2019 (COVID-19) arrived in the New York metropolitan area in early March 2020. Recommendations were made to self-quarantine within households and limit outside visits, including those to clinics and hospitals, to limit the spread of the virus. This resulted in a decrease in pediatric emergency department (ED) visits. However, it is unclear how this affected visits for some common diagnoses such as anxiety, appendicitis, asthma, headaches, seizures, and urinary tract infection (UTI). These diagnoses were chosen a priori, as they were felt to represent visits to the ED, for which the diagnoses would likely not be altered based on COVID exposure or quarantine due to their acute nature.

OBJECTIVES

Our goal was to investigate the effect of COVID-19 on common pediatric diagnoses seen in the pediatric ED using a large multihospital database.

METHODS

We conducted a retrospective cohort study of consecutive pediatric patients (age ≤ 21 years) between March 1 and November 30 in 2019 and 2020 in 28 hospital EDs within 150 miles of New York City. We compared the change in the number of visits from 2019 to 2020 for the following diagnoses: anxiety, appendicitis, asthma, headache, seizures, and UTI.

RESULTS

Our database contained 346,230 total pediatric visits. From 2019 to 2020, total visits decreased by 61%. Decreases for specific diagnoses were 75% for asthma, 64% for headaches, 47% for UTI, 32% for anxiety, 28% for seizures, and 18% for appendicitis (p value for each comparison < 0.0001).

CONCLUSIONS

We found a marked decrease in ED visits for six common pediatric diagnoses after COVID-19 arrived in our area. We suspect that this decrease was due to recommendations to quarantine and fear of contracting the virus. Further studies on other diagnoses and potential complications due to the delay in seeking care are needed.

Chemical explosion, COVID-19, and environmental justice: Insights from low-cost air quality sensors

OBJECTIVES

To examine the impact of the Intercontinental Terminals Company (ITC) fire and COVID-19 on airborne particulate matter (PM) concentrations and the PM disproportionally affecting communities in Houston using low-cost sensors.

METHODS

We compared measurements from a network of low-cost sensors with a separate network of monitors from the Environmental Protection Agency (EPA) in the Houston metropolitan area from Mar 18, 2019, to Dec 31, 2020. Further, we examined the associations between neighborhood-level sociodemographic status and air pollution patterns by linking the low-cost sensor data to EPA environmental justice screening and mapping systems.

FINDINGS

We found increased PM levels during ITC fire and pre-COVID-19, and lower PM levels after the COVID-19 lockdown, comparable to observations from the regulatory monitors, with higher variations and a greater number of locations with high PM levels detected. In addition, the environmental justice analysis showed positive associations between higher PM levels and the percentage of minority, low-income population, and demographic index.

IMPLICATION

Our study indicates that low-cost sensors provide pollutant measures with higher spatial variations and a better ability to identify hot spots and high peak concentrations. These advantages provide critical information for disaster response and environmental justice studies.

SYNOPSIS

We used measurements from a low-cost sensor network for air pollution monitoring and environmental justice analysis to examine the impact of anthropogenic and natural disasters.

Changes in air pollution due to COVID-19 lockdowns in 2020: Limited effect on NO2, PM2.5, and PM10 annual means compared to the new WHO Air Quality Guidelines

Background

Lockdowns have been fundamental to decreasing disease transmission during the COVID-19 pandemic even after vaccines were available. We aimed to evaluate and compare changes in air quality during the first year of the pandemic in different cities around the world, investigate how these changes correlate with changes in mobility, and analyse how lockdowns affected air pollutants' annual means.

Methods

We compared the concentrations of NO₂, PM_2.5, and PM₁₀ in 42 cities around the world in the first months of the pandemic in 2020 to data from 2016-2019 and correlated them with changes in mobility using Human Development Indexes (HDIs). Cities with the highest decreases in air pollutants during this period were evaluated for the whole year 2020. We calculated the annual means for these cities and compared them to the new World Health Organization (WHO) Air Quality Guidelines. A Student's t-test (95% confidence interval) was used to evaluate significant changes.

Results

Highest decreases in NO₂, PM_2.5, and PM₁₀ were between -50 and -70%. Cities evaluated for the whole year 2020 generally showed a recovery in air pollution levels after the initial months of the pandemic, except for London. These changes positively correlated with year-long mobility indexes for NO₂ and PM_2.5 for some cities. The highest reductions in air pollutants' annual means were from -20 to -35%. In general, decreases were higher for NO₂, compared to PM_2.5 and PM₁₀. All analysed cities showed annual means incompliant with the new WHO Air Quality Guidelines for NO₂ of 10 μg/m³, with values 1.7 and 4.3 times higher. For PM_2.5, all cities showed values 1.3 to 7.6 times higher than the WHO Guidelines of 5 μg/m³, except for New Delhi, with a value 18 times higher. For PM₁₀, only New York complied with the new guidelines of 15 μg/m³ and all the other cities were 1.1 to 4.2 times higher, except for New Delhi, which was 11 times higher.

Conclusions

These data show that even during a pandemic that highly affected mobility and economic activities and decreased air pollution around the world, complying with the new WHO Guidelines will demand a global strategical effort in the way we generate energy, move in and around the cities, and manufacture products.

A perception-based study of the indoor and outdoor acoustic environments in India during the COVID-19 pandemic

This work presents the results of a perception-based study of changes in the local soundscape at residences across India during the last 2 years of the COVID-19 pandemic and their effects on well-being, productivity during work from home (WFH), online education, anxiety, and noise sensitivity. Using emails and social media platforms, an online cross-sectional survey was conducted involving 942 participants. The responses showed that a greater percentage of participants felt that the indoor environment was noisier during the 2020 lockdown, which was attributed to increased home-entertainment usage, video-calling, and family interaction. The outdoor soundscape was much quieter during the 2020 lockdown due to drastically reduced traffic and commercial activities; however, during the 2021 lockdown, it was perceived to be comparable with pre-COVID times. While changes in indoor soundscape were shown to affect peace, happiness, and concentration while increasing annoyance, the reduction in outdoor noise positively impacted these aspects. The responses indicate that indoor soundscape changes adversely affected productivity and online education. Consequently, only 15% of participants now prefer the WFH model, while 62% have reservations about online education. In some cases, the responses demonstrate a significant influence of demography and suggest the improvement of the acoustic design of residences to support work.

Assessment of the dynamics of urban surface temperatures and air pollution related to COVID-19 in a densely populated City environment in East Java

The COVID-19 pandemic that has hit the whole world has caused losses in various aspects. Several countries have implemented lockdowns to curb the spread of the SARS-CoV-2 virus that caused death. However, for developing countries such as Indonesia, it is not suitable for lockdown because it considers the economic recession. Instead, the Large-scale Social Restrictions (LSSR) regulation is applied, the same as the partial lockdown. Thus, it is hypothesized that implementing LSSR that limits anthropogenic activities can reduce heat emissions and air pollution. Utilization of remote sensing data such as Terra-MODIS LST and Sentinel-5P images to investigate short-term trends (i.e., comparison between baseline year and COVID-19 year) in surface temperature, Surface Urban Heat Islands Intensity (SUHII), and air pollution such as NO₂, CO, and O₃ in Malang City and Surabaya City, East Java Province. Spatial downscaling of LST using the Random Forest Regression technique was also carried out to transform the spatial resolution of the Terra-MODIS LST image to make it feasible on a city scale. Raster re-gridding was also implemented to refine the Sentinel-5P spatial resolution. The accuracy of LST spatial downscaling results is quite satisfactory in both cities. Surface temperatures in both cities slightly decreased (below 1 °C) during LSSR was applied (P < 0.05). SUHII in both cities experienced a slight increase in both cities during LSSR. NO₂ gas was reduced significantly (P < 0.05) in Malang City (∼38%) and Surabaya City (∼28%) during LSSR phase due to reduced vehicle traffic and restrictions on anthropogenic activities. However, CO and O₃ gases did not indicate anomaly during LSSR. Moreover, this study provides insight into the correlation between SUHII change and the distribution of air pollution in both cities during the pandemic year. Air temperature and wind speed are also added as meteorological factors to examine their effect on air pollution. The proposed models of spatial downscaling LST and re-gridding satellite-based air pollution can help decision-makers control local air quality in the long and short term in the future. In addition, this model can also be applied to other ecological research, especially the input variables for ecological spatial modeling.

Understanding Air Quality Changes after Implementation of Mitigation Measures during a Pandemic: A Scoping Review of Literature in the United States

Traffic-related emissions continue to be a significant source of air pollution in the United States (US) and around the globe. Evidence has shown that previous policies implemented to restrict-traffic flows have affected air pollution levels. Thus, mitigation strategies associated with the COVID-19 pandemic that modified population-level mobility patterns provide a unique opportunity to study air pollution change across the US. For instance, to slow the spread of the pandemic, state and local governments started implementing various mitigation actions, including stay-at-home directives, social distancing measures, school closures, and travel restrictions. This scoping review aimed to summarize the existing evidence about how air quality changed through mitigation practices throughout the pandemic in the US. We found 66 articles that fit our inclusion criteria. Generally, the consolidated results revealed that nitrogen dioxide (NO2) and carbon monoxide (CO) decreased across the country. Studies observed mixed directions and magnitudes of change for fine and coarse particulate matter (PM2.5, PM10), ozone (O3), and sulfur dioxide (SO2). Few articles tried to explain this notable heterogeneity in air quality changes by associating contextual factors, such as mobility, traffic flow, and demographic factors. However, all studies agreed that the change in air pollution was nonuniform across the US and even varied within a city.

Assessing residential indoor and outdoor bioaerosol characteristics using the ultraviolet light-induced fluorescence-based wideband integrated bioaerosol sensor

We assessed and compared indoor and outdoor residential aerosol particles in a third-floor apartment from August through September 2020. The measurements were conducted using a direct-reading ultraviolet light-induced fluorescence (UV-LIF) wideband integrated bioaerosol spectrometer (WIBS). It measures individual particle light scattering and fluorescence from which particle properties can be derived. The number concentrations of total aerosol particles (TAP) and total fluorescent aerosol particles (TFAP) were significantly higher indoors. Daily and hourly TFAP mean concentrations followed the same trends as the TAP, both indoors and outdoors. The daily mean rank of the TFAP fraction (TFAP/TAP) was significantly higher indoors (23%) than outdoors (19%). Particles representing bacteria dominated indoors while particles representing fungi and pollen dominated outdoors. The mean volume-weighted median diameters for TFAP were 1.67 μm indoors and 2.09 μm outdoors. Higher TFAP fraction indoors was likely due to occupants' activities that generated or resuspended particles. This study contributes to understanding the characteristics of residential aerosol particles in situations when occupants spend most of their time indoors. Based on our findings, a large portion of all indoor aerosol particles could be biological (15-20%) and of respirable particle size (≥95%). Using a novel direct reading UV-LIF-based sensor can help quickly assess aerosol exposures relevant to human health.

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.

Greenhouse Gas Emission: Perception during the COVID-19 Pandemic

The period 2020/2021 was an unprecedented and historic time for industrial, economic, and societal activities all over the world with great challenges to human health, the ecosystems, and other aspects of human endeavors owing to the COVID-19 or SARS-CoV-2 (CV-19) pandemic which is now a topical aspect of research interest. Despite the negative impacts of the CV-19 pandemic, there are also positive reports during the CV-19 pandemic such as the reduction of gas flare, reduction in the burning of fossil fuels from automobile exhaust and a reduction in the other ensuing factors of greenhouse gases emissions (which is one of the major drives for global warming and climate change as well as other environmental effluences). Hence, this brief perspective review study is centered on greenhouse gas (GHG) emission. The study employs a methodical approach to analyze some already available research studies from existing publications and databases on GHG emission using the perception during the CV-19 pandemic. The specific findings from this review show that, from the meteorological perspective, the global response to the catastrophe ensuing from the CV-19 pandemic has a great influence on the reduction of GHGs, the reduction in the burning of fossil fuels from automobiles and industrial devices, and the reduction in the other ensuing factors of GHG emission. Hence, it will not be far from the truth to conclude that there is a possible positive connection between the CV-19 pandemic and GHG emissions. The study has a direct impact on the environment owing to the negative and positive environmental consequences of the CV-19 pandemic. Suggestions and recommendations in the form of future prospects of GHG emission vis-à-vis global warming and climate change are also discussed. Furthermore, suggestions on how to improve food security and agriculture during a pandemic such as the CV-19 outbreak period are highlighted.

Changes in air quality over different land covers associated with COVID-19 in Turkey aided by GEE

With the increased urbanization, the rise of the manufacturing industry, and the use of fossil fuels, poor air quality is one of the most serious and pressing problems worldwide. The COVID-19 outbreak prompted absolute lockdowns in the majority of countries throughout the world, posing new research questions. The study's goals were to analyze air and temperature parameters in Turkey across various land cover classes and to investigate the correlation between air and temperature. For that purpose, remote sensing data from MODIS and Sentinel-5P TROPOMI were used from 2019 to 2021 over Turkey. A large amount of data was processed and analyzed in Google Earth Engine (GEE). Results showed a significant decrease in NO₂ in urban areas. The findings can be used in long-term strategies for lowering global air pollution. Future research should look at similar investigations in various study sites and evaluate changes in air metrics over additional classes.

Mortensen L, Requia W, Lange T, Loft S, Kuenzli N, Schwartz J, Amini H. Stringency of COVID-19 Containment Response Policies and Air Quality Changes: A Global Analysis across 1851 Cities

The COVID-19 containment response policies (CRPs) had a major impact on air quality (AQ). These CRPs have been time-varying and location-specific. So far, despite having numerous studies on the effect of COVID-19 lockdown on AQ, a knowledge gap remains on the association between stringency of CRPs and AQ changes across the world, regions, nations, and cities. Here, we show that globally across 1851 cities (each more than 300 000 people) in 149 countries, after controlling for the impacts of relevant covariates (e.g., meteorology), Sentinel-5P satellite-observed nitrogen dioxide (NO₂) levels decreased by 4.9% (95% CI: 2.2, 7.6%) during lockdowns following stringent CRPs compared to pre-CRPs. The NO₂ levels did not change significantly during moderate CRPs and even increased during mild CRPs by 2.3% (95% CI: 0.7, 4.0%), which was 6.8% (95% CI: 2.0, 12.0%) across Europe and Central Asia, possibly due to population avoidance of public transportation in favor of private transportation. Among 1768 cities implementing stringent CRPs, we observed the most NO₂ reduction in more populated and polluted cities. Our results demonstrate that AQ improved when and where stringent COVID-19 CRPs were implemented, changed less under moderate CRPs, and even deteriorated under mild CRPs. These changes were location-, region-, and CRP-specific.

CO2 emissions persistence: Evidence using fractional integration

The main cause of climate change are carbon dioxide emissions. In the context of the COVID-19 pandemic, the number of emissions has been significantly reduced for the first time in many years. Now it is necessary to answer the question of whether CO2 emissions are stationary or not, because the results will let us know whether environmental policies have to be strengthened rather than relaxed in intensity. To this end, this paper investigates the persistence in CO2 emissions in a group of countries to determine if shocks in the series have permanent or transitory effects. The results, based on fractional integration indicate evidence of mean reversion, with values of the differencing parameter constrained between 0 and 1 in all cases, independently of the assumption made about the error term (white noise or autocorrelation). Focusing on the areas under examination, it is obtained that the EU27+UK, Japan and the US present the lowest degrees of integration, while Russia, China and India display the highest values. Decreasing time trends are only observed for the EU27+UK and US.

Exposure to outdoor and indoor air pollution and risk of overweight and obesity across different life periods: A review

Due to the highly evolved industrialization and modernization, air quality has deteriorated in most countries. As reported by the World Health Organization (WHO), air pollution is now considered as one of the major threats to global health and a principal risk factor for noncommunicable diseases. Meanwhile, the increasing worldwide prevalence of overweight and obesity is attracting more public attentions. Recently, accumulating epidemiological studies have provided evidence that overweight and obesity may be partially attributable to environmental exposure to air pollution. This review summarizes the epidemiological evidence for the correlation between exposure to various outdoor and indoor air pollutants (mainly particulate matter (PM), nitrogen oxides (NO_x), ozone (O₃), and polycyclic aromatic hydrocarbons (PAHs)) and overweight and obesity outcomes in recent years. Moreover, it discusses the multiple effects of air pollution during exposure periods throughout life and sex differences in populations. This review also describes the potential mechanism underlying the increased risk of obesity caused by air pollution, including inflammation, oxidative stress, metabolic imbalance, intestinal flora disorders and epigenetic modifications. Finally, this review proposes macro- and micro-measures to prevent the negative effects of air pollution exposure on the obesity prevalence.

PM2.5 decadal data in cold vs. mild climate airports: COVID-19 era and a call for sustainable air quality policy

Airports are identified hotspots for air pollution, notably for fine particles (PM_2.5) that are pivotal in aerosol-cloud interaction processes of climate change and human health. We herein studied the field observation and statistical analysis of 10-year data of PM_2.5 and selected emitted co-pollutants (CO, NO_x, and O₃), in the vicinity of three major Canadian airports, with moderate to cold climates. The decadal data analysis indicated that in colder climate airports, pollutants like PM_2.5 and CO accumulate disproportionally to their emissions in fall and winter, in comparison to airports in milder climates. Decadal daily averages and standard errors of PM_2.5 concentrations were as follows: Vancouver, 5.31 ± 0.017; Toronto, 6.71 ± 0.199; and Montreal, 7.52 ± 0.023 μg/m³. The smallest and the coldest airport with the least flights/passengers had the highest PM_2.5 concentration. QQQ-ICP-MS/MS and HR-S/TEM analysis of aerosols near Montreal Airport indicated a wide range of emerging contaminants (Cd, Mo, Co, As, Ni, Cr, and Pb) ranging from 0.90 to 622 μg/L, which were also observed in the atmosphere. During the lockdown, a pronounced decrease in the concentrations of PM_2.5 and submicron particles, including nanoparticles_, in residential areas close to airports was observed, conforming with the recommended workplace health thresholds (~ 2 × 10⁴ cm^-3), while before the lockdown, condensable particles were up to ~ 1 × 10⁵ cm^-3. Targeted reduction of PM_2.5 emission is recommended for cold climate regions.

Impact of COVID-19 lockdown on the atmospheric boundary layer and instability process over Indian region

The abrupt reduction in the human activities during the first lockdown of the COVID-19 pandemic created unprecedented changes in the background atmospheric conditions. Several studies reported the anthropogenic and air quality changes observed during the lockdown. However, no attempts are made to investigate the lockdown effects on the Atmospheric Boundary Layer (ABL) and background instability processes. In this study, we assess the lockdown impacts on the ABL altitude and instability parameters (Convective Available Potential Energy (CAPE) and Convective Inhibition Energy (CINE)) using WRF model simulations. Results showed a unique footprint of COVID-19 lockdown in all these parameters. Increase in the visibility, surface temperature and wind speed and decrease in relative humidity during the lockdown is noticed. However, these responses are not uniform throughout India and are significant in the inland compared to the coastal regions. The spatial variation of temperature (wind speed) and relative humidity shows an increase and decrease over the Indo Gangetic Plain (IGP) and central parts of India by 20% (100%) and 40%, respectively. Increase (80%) in the ABL altitude is larger over the IGP and central parts of India during lockdown of 2020 compared to similar time period in 2015-2019. This increase is attributed to the stronger insolation due to absence of anthropogenic activity and other background conditions. At the same time, CAPE decreased by 98% in the IGP and central parts of India, where it shows an increase in other parts of India. A prominent strengthening of CINE in the IGP and a weakening elsewhere is also noticed. These changes in CAPE and CINE are mainly attributed to the dearth of saturation in lower troposphere levels, which prevented the development of strong adiabatic ascent during the lockdown. These results provide a comprehensive observation and model-based insight for lockdown induced changes in the meteorological and thermo-dynamical parameters.

Unexpected reduction in ozone levels in a mid-size city during COVID-19 lockdown

The current study evaluated ozone levels through passive samplers installed in 4 different points in a medium-sized city (Rio Grande, Brazil) with naturally low NO₂ levels during a week of COVID-19 lockdown. Additionally, we evaluated the consequences of this response with regard to human health risk assessment and reduction of hospital admissions and ozone-related deaths. The reduction in ozone levels, one month after the implementation of containment measures, varied between 26 and 64% (average of 44%), in the different studied sites. The reduction of human mobility during the pandemic reduced the levels of ozone in Rio Grande city and consequently will bring benefits to health services in the municipality. This unexpected reduction in O₃ levels must be related to the low 'natural' levels of NO₂ in the city, which make the contribution of other precursors important for the fluctuation of O₃ levels.

Field measurements of indoor and community air quality in rural Beijing before, during, and after the COVID-19 lockdown

The coronavirus (COVID-19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID-19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID-19 lockdown in homes with different energy use patterns. Using calibrated real-time PM_2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID-19 lockdown. Community pollution was higher during the lockdown (61 ± 47 μg/m³ ) compared with before (45 ± 35 μg/m³ , p < 0.001) and after (47 ± 37 μg/m³ , p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM_2.5 during the COVID-19 lockdown. Indoor-generated PM_2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID-19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID-19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.

The Chinese Spring Festival Impact on Air Quality in China: A Critical Review

It is known that the sharp change of air pollutants affects air quality. Chinese Spring Festival is the most important holiday for Chinese people, and the celebration of the holiday with fireworks and the movement of people all around the country results in significant change in multiple air pollutant emissions of various sources. As many cities and rural areas suffer from the air pollution caused by firework displays and more residential fuel consumption, there is an urgency to examine the impact of the Chinese Spring Festival on air quality. Hence, this paper firstly gives an overall insight into the holiday's impact on ambient and household air quality in China, both in urban and rural areas. The main findings of this study are: (1) The firework displays affect the air quality of urban and rural atmosphere and household air; (2) the reduction in anthropogenic emissions improves the air quality during the Chinese Spring Festival; (3) the household air in urban areas was affected most by firework burning, while the household air in rural homes was affected most by fuel consumption; and (4) the short-term health impact of air pollution during the holidays also need more concern. Although there have been many publications focused on the holiday's impact on ambient and household air quality, most of them focused on the measurement of pollutant concentration, while studies on the formation mechanism of air pollution, the influence of meteorological conditions, and the health outcome under the effect of the Chinese Spring Festival are rare. In the future, studies focused on these processes are welcomed.

The Effects of Pandemic Restrictions on Public Health-Improvements in Urban Air Quality

The present study aims to provide evidence on the effects of pandemic curtailment measures on public health, targeting the changes in breathable air quality, within urban areas. The analyzed period covers the full impact of lockdowns in Europe in 2020. We used everyday data for each analyzed pollutant, NO₂, SO_2, CO, PM_2.5 and PM₁₀, from urban monitoring stations that provided real-time concentrations (provided by Copernicus Atmosphere Monitoring Service, Environmental Protection Agency repository and European Environment Agency map services) and satellite data (provided by NASA Orbiting Carbon Observatory 2). In the present study, the urban air quality was computed using a composite index that was further analyzed in comparison with pandemic restrictions. Descriptive statistics, charts and maps were used to visualize the data that covered the analyzed countries. Our results show that air pollution was reduced by 12% after lockdowns in European urban areas, with a 0.76 correlation between air pollution and pandemic restrictions. All air pollutants registered significant drops.

Environmental risk of Covid-19 recovery

During Covid-19 pandemic world economy experienced negative growth rate, therefore energy consumption and consequently emission pollution decreased. According to Environmental Kuznets Curve, it is expected that energy consumption and emission pollution increase in response to Covid-19 economic recovery, even higher than its pre-pandemic level. The goal of this paper is to study the environmental risk of Covid-19 economic recovery. We use an Environmentally-Augmented Global Vector Autoregressive Model (E-GVAR) to trace dynamic effects of Covid-19 economic recovery on pollution emission. Using generalized impulse response functions (GIRFs), we investigated the effect of positive economic shocks in real per capita income in China and USA economies on total C O 2 equivalent emission pollution. The results show that positive economic recovery affects emission pollution significantly. China and emerging economies may experience high risk while Europe region is moderately affected by this positive shock. A positive Economic Shock in China decrease pollution emission in USA over time. It can be attributed to substitution effect of Chinese product in global market. Generally, our results demonstrate spillover effect of transition shocks from large economies to the rest of world and highlights the importance of linkages in the world economy.

The impact of the Covid-19 pandemic on the incidence of diseases and the provision of primary care: A registry-based study

Introduction

The Covid-19 pandemic had a tremendous impact on healthcare but uncertainty remains about the extent to which primary care provision was affected. Therefore, this paper aims to assess the impact on primary care provision and the evolution of the incidence of disease during the first year of the Covid-19 pandemic in Flanders (Belgium).

Methods

Care provision was defined as the number of new entries added to a patient’s medical history. Pre-pandemic care provision (February 1, 2018–January 31, 2020) was compared with care provision during the pandemic (February 1, 2020-January 31, 2021). A large morbidity registry (Intego) was used. Regression models compared the effect of demographic characteristics on care provision and on acute and chronic diagnoses incidence both prior and during the pandemic.

Results

During the first year of the Covid-19 pandemic, overall care provision increased with 9.1% (95%CI 8.5%;9.6%). There was an increase in acute diagnoses of 5.1% (95%CI 4.2%;6.0%) and a decrease in the selected chronic diagnoses of 12.8% (95% CI 7.0%;18.4%). Obesity was an exception with an overall incidence increase. The pandemic led to strong fluctuations in care provision that were not the same for all types of care and all demographic groups in Flanders. Relative to other groups in the population, the pandemic caused a reduction in care provision for children aged 0–17 year and patients from a lower socio-economic situation.

Conclusion

This paper strengthened the claim that Covid-19 should be considered as a syndemic instead of a pandemic. During the first Covid-19 year, overall care provision and the incidence of acute diagnoses increased, whereas chronic diseases’ incidence decreased, except for obesity diagnoses which increased. More granular, care provision and chronic diseases’ incidence decreased during the lockdowns, especially for people with a lower socio-economic status. After the lockdowns they both returned to baseline.

Chang impact analysis of level 3 COVID-19 alert on air pollution indicators using artificial neural network

In this study, mean monthly and diurnal variations in fine particulate matters (PM_2.5), nitrate, sulfate, and gaseous precursors were investigated during the Level 3 COVID-19 alert from May 19 to July 27 in 2021. For comparison, the historical data during the identical period in 2019 and 2020 were also provided to determine the effect of the Level 3 COVID-19 alert on aerosols and gaseous pollutants concentrations in Taichung City. A machine learning model using the artificial neural network technique coupled with a kinetic model was applied to predict NO_x, O₃, nitrate (NO₃ ^-), and sulfate (SO₄ ^2-) to investigate potential emission sources and chemical reaction mechanism. D during the Level 3 COVID-19 alert, a decrease in NO_x concentration due to a decrease in traffic flow under the NO_x-saturated regime was observed to enhance the secondary NO₃ ^- and O₃ formation. The present models were shown to predict 80.1, 77.0, 72.6, and 67.2% concentrations of NO_x, O₃, NO₃ ^-, and SO₄ ^2-, respectively, which could help decision-makers for pollutant emissions reduction policies development and air pollution control strategies. It is recommended that more long-term datasets, including water soluble inorganic salts (WIS), precursors including OH radicals, NH₃, HNO₃, and H₂SO₄, be provided by regulatory air quality monitoring stations to further improve the prediction model accuracy.

Effects of the COVID-19 pandemic on the environment, waste management, and energy sectors: a deeper look into the long-term impacts

The COVID-19 pandemic not only has caused a global health crisis but also has significant environmental consequences. Although many studies are confirming the short-term improvements in air quality in several countries across the world, the long-term negative consequences outweigh all the claimed positive impacts. As a result, this review highlights the positive and the long-term negative environmental effects of the COVID-19 pandemic by evaluating the scientific literature. Remarkable reduction in the levels of CO (3 - 65%), NO₂ (17 - 83%), NO_x (24 - 47%), PM_2.5 (22 - 78%), PM₁₀ (23 - 80%), and VOCs (25 - 57%) was observed during the lockdown across the world. However, according to this review, the pandemic put enormous strain on the present waste collection and treatment system, resulting in ineffective waste management practices, damaging the environment. The extensive usage of face masks increased the release of microplastics/nanoplastics (183 to 1247 particles piece^-1) and organic pollutants in land and water bodies. Furthermore, the significant usages of anti-bacterial hand sanitizers, disinfectants, and pharmaceuticals have increased the accumulation of various toxic emerging contaminants (e.g., triclocarban, triclosan, bisphenol-A, hydroxychloroquine) in the treated sludge/biosolids and discharged wastewater effluent, posing great threats to the ecosystems. This review also suggests strategies to create long-term environmental advantages. Thermochemical conversions of solid wastes including medical wastes and for treated wastewater sludge/biosolids offer several advantages through recovering the resources and energy and stabilizing/destructing the toxins/contaminants and microplastics in the precursors.

Potential hotspot modeling and monitoring of PM2.5 concentration for sustainable environmental health in Maharashtra, India

Modern human civilization has suffered from the disastrous impact of COVID-19, but it teaches us the lesson that the environment can restore its stability without human activity. The Government of India (GOI) has launched many strategies to prevent the situation of COVID-19, including a lockdown that has a great impact on the environment. The present study focuses on the analysis of Particulate Matter 2.5 (PM2.5) concentration levels in pre-locking, lockdown, and unlocking phases across ten major cities of Maharashtra (MH) that were the COVID hotspot of India during the COVID-19 outbreak; phase-wise and year-wise (2018-2020) hotspot analysis, box diagram and line graph methods were used to assess spatial variation in PM2.5 across MH cities. Our study showed that the PM2.5 concentration level was severe at pre-lockdown stage (January-March) and it decreased dramatically at the lockdown stage, later it also increased in its previous position at the unlocking stages, i.e., PM2.5 decreased dramatically (59%) during the lockdown period compared to the pre-lockdown period due to the shutdown of outdoor activities. It returns to its previous position due to the unlocking situation and increases (70%) compared to the lockdown period which illustrated the ups and downs of PM2.5 and ensures the position of different cities in the Air Quality Index (AQI) categories at different times. In the pre-lockdown phase, maximum PM2.5 concentration was in Navi Mumbai (NAV) (358) and Mumbai (MUM) (338), and Pune (PUN) (335) and Nashik NAS (325) subsequently, whereas at the last of the lockdown phase, it becomes Chandrapur (CHN) (82), Nagpur (NAG) (76), and Solapur (SOL) (45) subsequently. Hence, the restoration of the environment during the lockdown phase was temporary rather than permanent. Therefore, our findings propose that several effective policies of government such as relocation of polluting industries, short-term lockdown, odd-even vehicle number, installation of air purifier, and government strict initiatives are needed in making a sustainable environment.

Spatiotemporal representativeness of air pollution monitoring in Dublin, Ireland

The importance of selecting appropriate air pollution monitoring sites in a city is vital for accurately reporting air quality, enhancing the quality of high-resolution modelling and informing policy to implement measures to deliver cleaner air in the urban environment. COVID-19 restrictions impacted air quality in urban centres worldwide as reduced mobility led to changes in traffic-related air pollution (TRAP). As such, it offered a unique dataset to examine the spatial and temporal variations in air quality between monitoring stations in Dublin, Ireland. Firstly, an analysis of mobility data showed reductions across almost all sectors after COVID-19 restrictions came into place, which was expected to lower TRAP. In addition, similar changes in air quality were evident to other cities around the world: reductions in fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations and an increase in ozone (O₃) concentrations. Average daily and diurnal concentrations for these three pollutants presented more statistically significant spatial and temporal changes during COVID-19 restrictions at monitoring sites with urban or traffic classifications than suburban background sites. Furthermore, substantial reductions in the range of average hourly pollutant concentrations were observed, 79% for PM_2.5 and 75% for NO₂, with a modest 24% reduction for O₃. Correlation analysis of air pollution between monitoring sites and years demonstrated an improvement in the R² for NO₂ concentrations only, suggesting that spatiotemporal homogeneity was most notable for this TRAP due to mobility restrictions during COVID-19. The spatiotemporal representativeness of monitoring stations across the city will change with greener transport, and air quality during COVID-19 can provide a benchmark to support the introduction of new policies for cleaner air.

Analysis of the Impact of the COVID-19 Pandemic on the Value of CO2 Emissions from Electricity Generation

The study analyzed the impact of the COVID-19 pandemic on the carbon dioxide emissions from electricity generation. Additionally, monthly seasonality was taken into account. It was assumed (research hypothesis) that both the COVID-19 pandemic (expressed in individual waves of infection cases) and the month have a significant impact on CO2 emissions. Analysis of variance (ANOVA) and non-parametric Kruskal–Wallis tests were used to evaluate the significance of the influence of individual explanatory variables on the CO2 emission. The identification of the studied series (CO2 emission) was first made by means of a linear regression model with binary variables and then by the ARMAX model. The analysis shows that in the consecutive months and periods of the COVID-19 pandemic, CO2 emissions differ significantly. The highest increase in emissions was recorded for the second wave of the pandemic, as well as in January and February. This is due to the overlapping of both the increase in infections (favoring stays at home) and the winter season. It can be concluded that working plants, schools and factories had the same demand for electricity, but sources of increased consumption were people staying at home and in hospitals as a result of deteriorated health, isolation or quarantine.

Emissions of nitrogen dioxide in the northeast U.S. during the 2020 COVID-19 lockdown

We have quantified the emissions of Nitrogen dioxide (NO₂) in the Northeast megalopolis of the United States during the COVID-19 lockdown. The measurement of NO₂ emission serves as the indicator for the emission of the group of nitrogen oxides (NO_x). Approximately 56% of NO₂ emissions in the US are from mobile sources, and the remainder is from stationary sources. Since 2002, clean air regulations have resulted in approximately 5% compound annual reduction of NO_x emissions in the US (8.2% in the study area). Therefore, when studying the impact of sporadic events like an epidemic on emissions, it is necessary to account for the persistent reduction of emissions due to policy driven emission reduction measures. Using spaceborne sensors, ground monitors, National Emission Inventory data, and the US Motor Vehicle Emission Simulator, we quantified the reduction of total NO_x emissions, distinguishing stationary sources from on-road mobile sources (trucks and automobiles). When considering total NO_x emissions (stationary and mobile combined), we find that the pandemic restrictions resulted in 3.4% reduction of total NO_x emissions in the study area in 2020. This is compared to (and in addition to) the expected 8.2% policy driven reduction of NO_x emissions in 2020. This somewhat low reduction of emissions is because most stationary sources (factories, power plants, etc.) were operational during the pandemic. Truck traffic, a significant source of mobile emissions, also did not decline significantly (average 4.8% monthly truck traffic reduction in the study area between March and August 2020), as they were delivering goods during the lockdown. On the other hand, automobile traffic, responsible for 24% of total NO_x emissions, dropped significantly, 52% in April, returning to near normal after 5 months. While the reduction of automobile traffic was significant, especially in the early months of the pandemic, its effect on emissions was relatively insignificant.

A mini-review: positive impact of COVID-19 on Arial health and ecology

COVID-19 can cause global pandemics; however, no specific vaccine has been recommended for COVID-19. Nearly 216 countries are trying to stop the spread of the disease, recover from it, and improve its mobility. In a way that people have not experienced in recent years, the COVID-19 pandemic affected humans through the year 2020. To stop the spread of the disease, many governments declared a complete lockdown.The nationwide lockdown had some positive effects on the environment even though it led to a decline in global economic growth. Air pollution levels reduced dramatically as a result of this lockdown on pollution. Most of Europe's populated cities saw a reduction in NO2 concentration of 45-54%. COVID-19 and air, water, and ecology are connected via two pathways, one occurring before the spread of the disease and the other following after. As a result of industrial activity, transportation, and high human density, pollutants were high in many areas before the disease spread. There was a reduction in population movements as well as a decline in human activities which resulted in a reduction in carbon dioxide emissions, an improvement of the ozone layer, as well as improvements in the Earth's weather and environment. As a result of a COVID-19 pandemic, human activities are negatively impacted, and the environment is positively affected. Our objective is to provide an assessment of the impact of human activities on the environment and ecology. During times of lockdown, there is a correlation between atmospheric changes and the behavior of natural creatures. Several significant findings are presented, including air pollution reduction, air quality improvement, ozone healing, and ecological sustainability. COVID-19 is beneficial for aerial health, aquatic health, and ecology in this paper.

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi, Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th-March 31st) and during the partial lockdown (April 1st-April 22nd) with "current" data obtained in 2020 and "historical" data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

The impact of the COVID-19 pandemic on air pollution: A global assessment using machine learning techniques

In response to the COVID-19 pandemic, most countries implemented public health ordinances that resulted in restricted mobility and a resultant change in air quality. This has provided an opportunity to quantify the extent to which carbon-based transport and industrial activity affect air quality. However, quantification of these complex effects has proven to be difficult, depending on the stringency of restrictions, country-specific emission source profiles, long-term trends and meteorological effects on atmospheric chemistry, emission levels and in-flow from nearby countries. In this study, confounding factors were disentangled for a direct comparison of pandemic-related reductions in absolute pollutions levels, globally. The non-linear relationships between atmospheric processes and daily ground-level NO 2 , PM₁₀, PM_2.5 and O 3 measurements were captured in city- and pollutant-specific XGBoost models for over 700 cities, adjusting for weather, seasonality and trends. City-level modelling allowed adaptation to the distinct topography, urban morphology, climate and atmospheric conditions for each city, individually, as the weather variables that were most predictive varied across cities. Pollution forecasts for 2020 in absence of a pandemic were generated based on weather and formed an ensemble for country-level pollution reductions. Findings were robust to modelling assumptions and consistent with various published case studies. NO 2 reduced most in China, Europe and India, following severe government restrictions as part of the initial lockdowns. Reductions were highly correlated with changes in mobility levels, especially trips to transit stations, workplaces, retail and recreation venues. Further, NO 2 did not fully revert to pre-pandemic levels in 2020. Ambient PM_2.5 pollution, which has severe adverse health consequences, reduced most in China and India. Since positive health effects could be offset to some extent by prolonged exposure to indoor pollution, alternative transport initiatives could prove to be an important pathway towards better health outcomes in these countries. Increased O 3 levels during initial lockdowns have been documented widely. However, our analyses also found a subsequent reduction in O 3 for many countries below what was expected based on meteorological conditions during summer months (e.g., China, United Kingdom, France, Germany, Poland, Turkey). The effects in periods with high O 3 levels are especially important for the development of effective mitigation strategies to improve health outcomes.

Effect of COVID-19 Response Policy on Air Quality: A Study in South China Context

Mass suspension of anthropogenic activities is extremely rare, the quarantine due to the coronavirus disease 2019 (COVID-19) represents a natural experiment to investigate the impact of anthropogenic activities on air quality. The mitigation of air pollution during the COVID-19 lockdown has been reported from a global perspective; however, the air pollution levels vary in different regions. This study initiated a novel synthesis of multiple-year satellite observations, national ground measurements towards SO2, NO2 and O3 and meteorological conditions to evaluate the impact of the COVID-19 lockdown in Beihai, a specific city in a less developed area in southwest China, to reveal the potential implications of control strategies for air pollution. The levels of the major air pollutants during the COVID-19 lockdown (LP) and during the same period of previous years (SP) were compared and a series of statistical tools were applied to analyze the sources of air pollution in Beihai. The results show that air pollutant levels decreased with substantial diversity during the LP. Satellite-retrieved NO2 and SO2 levels during the LP decreased by 5.26% and 22.06%, while NO2, SO2, PM2.5 and PM10 from ground measurements during the LP were 25.6%, 2.7%, 22.2% and 22.2% lower than during SP, respectively. Ground measured SO2 concentrations during the LP were only 2.7% lower than during the SP, which may be attributed to uninterrupted essential industrial activities, such as power plants. Polar plots analysis shows that NO2 concentrations were strongly associated with local emission sources, such as automobiles and local industry. Additionally, the much lower levels of NO2 concentrations during the LP and the absence of an evening peak may highlight the significant impact of the traffic sector on NO2. The decrease in daily mean O3 concentrations during the LP may be associated with the reduction in NO2 concentrations. Indications in this study could be beneficial for the formulation of atmospheric protection policies.

Rethinking Outdoor Courtyard Spaces on University Campuses to Enhance Health and Wellbeing: The Anti-Virus Built Environment

Responding to the events surrounding the COVID-19 pandemic, this study explores how to improve health and wellbeing and reduce infections in outdoor open spaces on university campuses to maximize their potential as a response to future crises. The study identifies the relationship between human behavior (social) and the various physical and environmental elements of these spaces. A case study and mixed-methods approach were undertaken, comprising four modes of inspection: user analysis layer using questionnaires and observations to survey students’ needs and behavior; context analysis layer using space syntax and CFD to examine the space’s physical and environmental conditions; design solutions reflecting an understanding of virus transmission; and a performance analysis layer to test the performance of ‘anti-virus’ courtyards. The findings demonstrated that students are willing to use the open spaces that they used before the pandemic, at the same frequency. This indicates a need to redesign the current spaces to prevent the spread of viruses. The study highlights the social, physical, and environmental implications to be considered in designs for outdoor anti-virus spaces. It provides a comprehensive process for transforming outdoor spaces on university campuses into anti-virus spaces that meet users’ needs. These findings have implications for the designing and retrofitting of open spaces to reduce infection.

Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran

The COVID-19 epidemic has caused unprecedented impacts on the travel and tourism industry. The current study traced the impacts of COVID-19 on tourism in Iran using an “Impact Pathway (IP)” approach to identify impacts and possible mitigation strategies. The results illustrate two main impact pathways: negative impacts along the economic-institutional and socio-cultural dimensions, and positive impacts along the physical-environmental dimension. Using SWOT (strengths, weaknesses, opportunities, and threats) and ANP (analytic network process) models, we identified defensive and review strategies as optimal for increasing resilience against the impacts of COVID-19. These strategies control the threats and weaknesses of negative impacts and enhance the opportunities and strengths emerging from the COVID-19 pandemic for tourism. We use this information to identify optimal strategies for dealing with the impacts of this crisis on tourism. Most prominently among them is the development of an integrated management system that improves the coordination of the response of local government to crisis and that better orchestrates the combined efforts and integration of non-governmental organizations.

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO₂), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

An overview of effects of COVID-19 on mobility and lifestyle: 18 months since the outbreak

The outbreak of SARS-COV-2 has led to the COVID-19 pandemic in March 2020 and caused over 4.5 million deaths worldwide by September 2021. Besides the public health crisis, COVID-19 affected the global economy and development significantly. It also led to changes in people's mobility and lifestyle during the COVID-19 pandemic. In addition to short-term changes, the drastic transformation of the world may account for the potentially disruptive long-term impacts. Recognizing the adverse effects of the COVID-19 pandemic is crucial in mitigating the negative behavioral changes that directly relate to people's psychological and social well-being. It is important to stress that citizens and governments face an uncertain situation since nobody knows exactly how the viruses and cures will develop. Better understanding uncertainties and evaluating behavioral changes contribute to addressing the future of urban development, public transportation, and behavioral strategies to tackle COVID-19 negative consequences. The major sources of impacts on short-term (route, departure time, mode, teleshopping, and teleworking) and medium and long-term (car ownership, work location, choice of job, and residential location) mobility decisions are mostly reviewed and discussed in this paper.

Heterogeneous impacts of mobility restrictions on air quality in the State of Sao Paulo during the COVID-19 pandemic

Air quality in the State of Sao Paulo was evaluated during the first general State plan of mobility restrictions due to the COVID-19 pandemic (24th March to May 31, 2020). Nitrogen dioxide (NO₂), ozone (O₃), particulate matter PM₁₀ and PM_2.5 and sulphur dioxide (SO₂) concentrations were assessed in cities of the Sao Paulo State with a monitoring station and compared to historical data. Linear regression models were built to investigate the relationship between the isolation of the population - determined using mobile phone monitoring data - and the concentration of each pollutant during the studied period. Although the reduction of pollutants such as NO₂, SO₂ and PM_2.5 is very clear, the economic and climatic characteristics of each region were decisive in the general behaviour of O₃ and PM₁₀. It was not possible to establish a correlation between the pollutants and the isolation index, partly due to the lack of data, partly due to the compliance of the population to those measurements, which was variable over time. Another important limitation factor was the absence of data related to the pollutants of interest in many of the stations. However, the isolation measures carried out in the State opened the opportunity to individually assess the air quality measurements in each of the stations, enabling an understanding that will allow in the future the design of air quality policies together with local sanitary policies.

The Impact of COVID-19 Strict Lockdown on the Air Quality of Smart Cities of Rajasthan, India

Aim:

The main focus of this study is to evaluate the air quality by comparing the concentration of particulate matter PM2.5, PM10, NO2, CO, SO2, and ozone of smart cities of Rajasthan before the lockdown and during the period of lockdown.

Background:

In India, the first case of the COVID-19 was reported on January 30th, 2020. Indian government declared strict lockdown, i.e., public health emergency in India on March 24th, 2020, which is implemented from March 25th, 2020, to April 14th, 2020, for 21 days.

Objective:

The objective of this study is to evaluate the air quality by comparing the levels of all parameters of air pollution during the COVID-19 lockdown period with values registered in the pre-lockdown period.

Methods:

Data were obtained from four automatic monitoring stations under the control of the Central Pollution Control Board, New Delhi (https://www.cpcb.nic.in/). Data regarding all the parameters were recorded as 24 hours average period.

Results:

CO levels showed the highest significant reduction in Udaipur (50.76%) followed by Jaipur (19.96%), Ajmer (17.11%), and Kota (5.51%) due to the ban on transport and driving. The levels of PM2.5, PM10, NO2, and SO2 were also decreased substantially for each smart city. Ozone concentrations were recorded greater than before due to decreased nitrogen oxides levels.

Conclusion:

This study can be useful considering our present role in environmental restoration or environmental destruction. It will also be helpful in updating our present plan toward the assurance and conservation of nature.

Atmospheric pollutants response to the emission reduction and meteorology during the COVID-19 lockdown in the north of Africa (Morocco)

Climate and air quality change due to COVID-19 lockdown (LCD) are extremely concerned subjects of several research recently. The contribution of meteorological factors and emission reduction to air pollution change over the north of Morocco has been investigated in this study using the framework generalized additive models, that have been proved to be a robust technique for the environmental data sets, focusing on main atmospheric pollutants in the region including ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter (PM_2.5 and PM₁₀), secondary inorganic aerosols (SIA), nom-methane volatile organic compounds and carbon monoxide (CO) from the regional air pollution dataset of the Copernicus Atmosphere Monitoring Service. Our results, indicate that secondary air pollutants (PM_2.5, PM₁₀ and O₃) are more influenced by metrological factors and the other air pollutants reported by this study (NO₂ and SO₂₎. We show a negative effect for PBHL, total precipitation and NW10M on PM (PM_2.5 and PM₁₀ ), this meteorological parameters contribute to decrease in PM_2.5 by 9, 2 and 9% respectively, before LCD and 8, 1 and 5% respectively during LCD. However, a positive marginal effect was found for SAT, Irradiance and RH that contribute to increase PM_2.5 by 9, 12 and 18% respectively, before LCD and 17, 54 and 34% respectively during LCD. We found also that meteorological factors contribute to O₃, PM_2.5, PM₁₀ and SIA average mass concentration by 22, 5, 3 and 34% before LCD and by 28, 19, 5 and 42% during LCD respectively. The increase in meteorological factors marginal effect during LCD shows the contribution of photochemical oxidation to air pollution due to increase in atmospheric oxidant (O₃ and OH radical) during LCD, which can explain the response of PM to emission reduction. This study indicates that PM (PM_2.5, PM₁₀) has more controlled by SO₂ due to the formation of sulfate particles especially under high oxidants level. The positive correlation between westward wind at 10 m (WW10M), Northward Wind at 10 m (NW10M) and PM indicates the implication of sea salt particles transported from Mediterranean Sea and Atlantic Ocean. The Ozone mass concentration shows a positive trend with Irradiance, Total and SAT during LCD; because temperature and irradiance enhance tropospheric ozone formation via photochemical reaction.This study shows the contribution of atmospheric oxidation capacity to air pollution change.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00477-022-02224-z.

Impact of the Levels of COVID-19 Pandemic Prevention and Control Measures on Air Quality: A Case Study of Jiangsu Province, China

In order to control the spread of the COVID-19 pandemic, the prevention and control measures of public health emergencies were initiated in all provinces of China in early 2020, which had a certain impact on air quality. In this study, taking Jiangsu Province in China as an example, the air pollution levels in different regions under different levels of pandemic prevention and control (PPC) measures are evaluated. The implementation of the prevention and control policies of COVID-19 pandemic directly affected the concentration of air pollutants. No matter what level of PPC measures was implemented, the air quality index (AQI) and pollutant concentrations of NO2, CO, PM10 and PM2.5 were all reduced by varied degrees. The higher the level of PPC measures, the greater the reduction was in air pollutant concentrations. Specifically, NO2 was the most sensitive to PPC policies. The concentrations of CO and atmospheric particulate matter (PM10 and PM2.5) decreased most obviously under the first and second level of PPC. The response speed of air quality to different levels of PPC measures varied greatly among different cities. Southern Jiangsu, which has a higher level of economic development and is dominated by secondary and tertiary industries, had a faster response speed and a stronger responsiveness. The results of this study reflect the economic vitality of different cities in economically advanced regions (i.e., Jiangsu Province) in China. Furthermore, the results can provide references for the formulation of PPC policies and help the government make more scientific and reasonable strategies for air pollution prevention and control.

Environmental Factors Influencing COVID-19 Incidence and Severity

Emerging evidence supports a link between environmental factors-including air pollution and chemical exposures, climate, and the built environment-and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and coronavirus disease 2019 (COVID-19) susceptibility and severity. Climate, air pollution, and the built environment have long been recognized to influence viral respiratory infections, and studies have established similar associations with COVID-19 outcomes. More limited evidence links chemical exposures to COVID-19. Environmental factors were found to influence COVID-19 through four major interlinking mechanisms: increased risk of preexisting conditions associated with disease severity; immune system impairment; viral survival and transport; and behaviors that increase viral exposure. Both data and methodologic issues complicate the investigation of these relationships, including reliance on coarse COVID-19 surveillance data; gaps in mechanistic studies; and the predominance of ecological designs. We evaluate the strength of evidence for environment-COVID-19 relationships and discuss environmental actions that might simultaneously address the COVID-19 pandemic, environmental determinants of health, and health disparities.

Temporal and Spatial Distribution Analysis of Atmospheric Pollutants in Chengdu-Chongqing Twin-City Economic Circle

In order to study the temporal and spatial distribution characteristics of atmospheric pollutants in cities (districts and counties) in the Chengdu–Chongqing Twin-city Economic Circle (CCEC) and to provide a theoretical basis for atmospheric pollution prevention and control, this paper combined Ambient Air Quality Standards (AAQS) and WHO Global Air Quality Guidelines (GAQG) to evaluate atmospheric pollution and used spatial correlation to determine key pollution areas. The results showed that the distribution of atmospheric pollutants in CCEC presents a certain law, which was consistent with the air pollution transmission channels. Except for particulate matter with an aerodynamic diameter equal to or less than 2.5 μm (PM_2.5) and ozone (O₃), other pollutants reached Grade II of AAQS in 2020, among which particulate matter with an aerodynamic diameter equal to or less than 10 μm (PM₁₀), PM_2.5, sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and carbon monoxide (CO) have improved. Compared with the air quality guidelines given in the GAQG, PM₁₀, PM_2.5, NO₂ and O₃ have certain effects on human health. The spatial aggregation of PM₁₀ and PM_2.5 decreased year by year, while the spatial aggregation of O₃ increased with the change in time, and the distribution of NO₂ pollution had no obvious aggregation. Comprehensive analysis showed that the pollution problems of particulate matter, NO₂ and O₃ in CCEC need to be further controlled.

Pittsburgh Air Pollution Changes During the COVID-19 Lockdown

The rapid spread of COVID-19 resulted in various public lockdowns across the globe. Previous studies showed that resultant travel restrictions improved air quality. The novel results presented here focus on source-specific changes and compare air quality for multiple years controlled for precipitation. This study sought to analyze air pollution changes in Pittsburgh, a city where an industrial past and present has led to elevated levels of particulate matter with representative diameter of ≤ 2.5μm (PM_2.5). Data from the Allegheny County Health Department, from monitors located near a variety of site types, were analyzed with generalized linear models that used a gamma distribution with a log link to determine the magnitude and significance of changes in air pollution during the COVID-19 lockdown. The hypothesis was that nitrogen dioxide (NO₂), which is primarily linked to vehicular traffic, would decrease significantly while potential decreases in particulate matter (PM_2.5 and PM₁₀) would be less apparent. Results of the regression models showed that NO₂ was significantly reduced during lockdown at both monitoring sites and that PM₁₀ was also significantly reduced at the majority of monitoring sites. However, decreases in PM_2.5 pollution were only observed at half of the monitoring locations, and the location which observed the greatest decreases is located adjacent to an industrial source. Decreases in PM_2.5 at this monitoring site were likely a result of reduced industrial processes both dependent and independent of the COVID-19 lockdown. This study suggests that industrial sources are a larger contributor of particulate matter than vehicular transportation in the city of Pittsburgh and that future air pollution reduction efforts should focus attention on emission reduction at these industrial facilities.

Spatiotemporal analysis of COVID-19, air pollution, climate, and meteorological conditions in a metropolitan region of Iran

The COVID-19 pandemic has a close relationship with local environmental conditions. This study explores the effects of climate characteristics and air pollution on COVID-19 in Isfahan province, Iran. A number of COVID-19 positive cases, main air pollutants, air quality index (AQI), and climatic variables were received from March 1, 2020, to January 19, 2021. Moreover, CO, NO₂, and O₃ tropospheric levels were collected using Sentinel-5P satellite data. The spatial distribution of variables was estimated by the ordinary Kriging and inverse weighted distance (IDW) models. A generalized linear model (GLM) was used to analyze the relationship between environmental variables and COVID-19. The seasonal trend of nitrogen dioxide (NO₂), wind speed, solar energy, and rainfall like COVID-19 was upward in spring and summer. The high and low temperatures increased from April to August. All variables had a spatial autocorrelation and clustered pattern except AQI. Furthermore, COVID-19 showed a significant association with month, climate, solar energy, and NO₂. Suitable policy implications are recommended to be performed for improving people's healthcare and control of the COVID-19 pandemic. This study could survey the local spread of COVID-19, with consideration of the effect of environmental variables, and provides helpful information to health ministry decisions for mitigating harmful effects of environmental change. By means of the proposed approach, probably the COVID-19 spread can be recognized by knowing the regional climate in major cities. The present study also finds that COVID-19 may have an effect on climatic condition and air pollutants.

Detecting Moving Trucks on Roads Using Sentinel-2 Data

In most countries, freight is predominantly transported by road cargo trucks. We present a new satellite remote sensing method for detecting moving trucks on roads using Sentinel-2 data. The method exploits a temporal sensing offset of the Sentinel-2 multispectral instrument, causing spatially and spectrally distorted signatures of moving objects. A random forest classifier was trained (overall accuracy: 84%) on visual-near-infrared-spectra of 2500 globally labelled targets. Based on the classification, the target objects were extracted using a developed recursive neighbourhood search. The speed and the heading of the objects were approximated. Detections were validated by employing 350 globally labelled target boxes (mean F1 score: 0.74). The lowest F1 score was achieved in Kenya (0.36), the highest in Poland (0.88). Furthermore, validated at 26 traffic count stations in Germany on in sum 390 dates, the truck detections correlate spatio-temporally with station figures (Pearson r-value: 0.82, RMSE: 43.7). Absolute counts were underestimated on 81% of the dates. The detection performance may differ by season and road condition. Hence, the method is only suitable for approximating the relative truck traffic abundance rather than providing accurate absolute counts. However, existing road cargo monitoring methods that rely on traffic count stations or very high resolution remote sensing data have limited global availability. The proposed moving truck detection method could fill this gap, particularly where other information on road cargo traffic are sparse by employing globally and freely available Sentinel-2 data. It is inferior to the accuracy and the temporal detail of station counts, but superior in terms of spatial coverage.

The Impact of COVID-19 Related Changes on Air Quality in Birmingham, Alabama, United States

Air pollution is responsible for a wide range of health effects in exposed populations. Variations in local air pollution can affect local population health outcomes. The strict regulations imposed during the peak of the COVID-19 pandemic ('lockdowns') resulted in a unique situation where human mobility was limited significantly, resulting in improved air quality in several major cities. The main goal of this study was to investigate if lockdowns during the COVID-19 pandemic significantly impacted air quality in Birmingham, Alabama-a city with a history of high air pollution levels-with a focus on PM2.5 (Particulate Matter with an aerodynamic diameter ≤2.5 µm) and NO2 (Nitrogen dioxide). Daily air pollutant and traffic data were obtained for the Birmingham Metropolitan Area for the period January to October 2020, and previous years. Mean PM2.5 and NO2 concentrations and traffic volumes during the official city/state lockdown period (24 March to 30 April 2020) were compared to pre- and post-lockdown means. The mean PM2.5 and NO2 concentrations during the lockdown did not significantly differ from that of the pre- or post-lockdown periods. However, NO2 significantly decreased even after the lockdown order was removed, with the mean decreasing significantly compared to pre-lockdown and lockdown periods. Both PM2.5 and NO2 annual means in 2020 were significantly lower than the annual means in 2019, indicating the occurrence of significant changes over the longer term that were not limited by defined lockdown periods. Traffic significantly increased after the lockdown order was removed but did not correlate with the two pollutants studied. Therefore, we conclude that the Stay at Home/lockdown regulations and other COVID-19 restrictions had an impact on the air quality of Birmingham Alabama; although these lockdown impacts varied for each pollutant and were not limited only by the official lockdown dates/periods.

Associations of combined exposures to ambient temperature, air pollution, and green space with hypertension in rural areas of Anhui Province, China: A cross-sectional study

Hypertension (HTN) was a major preventable cause of cardiovascular disease (CVD), contributing to a huge disease burden. Ambient temperature, air pollution and green space were important influencing factors of HTN, and few studies have assessed the effects and interactions of ambient temperature, air pollution and green space on HTN in rural areas. In this study, we selected 8400 individuals randomly in rural areas of Anhui Province by a multi-stage stratified cluster sampling. A total of 8383 individuals were included in the final analysis. We collected particulate pollutants and meteorological data from the local air quality monitoring stations and National Center for Meteorological Science from January 1 to December 31, 2020, respectively. The normalized differential vegetation index (NDVI) of Anhui Province in 2020 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The average annual mean exposure concentrations of air pollution, meteorological factors, and NDVI were calculated for each individual based on the geocoded residential address. HTN was defined according the Chinese Guidelines for Prevention and Treatment of HTN. The effects and interactions of ambient temperature, air pollution and green space on HTN were evaluated by generalized linear model and interaction model, respectively. In this study, the prevalence of HTN was 24.14%. The adjusted odd ratio of HTN for each 1 μg/m³ increasing in PM_2.5 and PM₁₀, 1 °C of ambient temperature, and 0.1 of NDVI were:1.276 (1.013, 1.043), 1.012 (1.006, 1.018), 0.862 (0.862, 0.981) and 0.669 (0.611, 0.733), respectively. The results showed that air pollutants were positively correlated with HTN, while ambient temperature and green space were negatively correlated with HTN. Meanwhile, the negative associations of green space on HTN could decrease with the increasing concentrations of air pollution, but increase with the rising of ambient temperature.

Air pollution perception in ten countries during the COVID-19 pandemic

As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by individuals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants (N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration; conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.