The impact of COVID-19 lockdown on the air quality of Eastern Province, Saudi Arabia

Identification of particulate matter (PM10 and PM2.5) sources using bivariate polar plots and k-means clustering in a South American megacity: Metropolitan Area of Lima-Callao, Peru

The identification of different air pollution sources is essential to effectively control atmospheric pollution, particularly in megacities of emerging countries with rapid economic development, such as the Metropolitan Area of Lima-Callao (MALC). The objective of this research was to identify the main sources of particulate matter pollution by applying bivariate polar plots and the k-means clustering algorithm. These statistical techniques were applied to hourly in situ data of four variables collected over a 5-year period (2015-2019) by the Automatic Air Quality Monitoring Network of the MALC: wind direction, wind speed, PM10, and PM2.5 concentrations. Average PM10 concentrations ranged from 34 μg m-3 (CDM station) to 126.7 μg m-3 (VMT station), while average PM2.5 concentrations ranged from 16.8 μg m-3 (CDM station) to 41.2 μg m-3 (ATE station). The diurnal variation of PM presented two peaks, one in the morning (from 0800 to 1000 h) and the other at night (from 1900 to 2300 h), with the highest concentrations of PM10 recorded at the ATE (0800 h: 155.8 μg m-3) and VMT (2100 h: 154.6 μg m-3) stations, and PM2.5 at the ATE station (0800 h: 60.3 μg m-3 and 2300 h: 37.5 μg m-3). The results showed that the contributions of PM10 are directly related to emissions from industrial activities, automotive fleet, construction, demolition, wind erosion, and the suspension and resuspension of particulates from unpaved roads. Meanwhile, high concentrations of PM2.5 are mainly attributed to vehicle exhaust emissions, industrial emissions, secondary particulate formation, and drag by the action of the winds. The major source of particulate matter contamination is the vehicle fleet, and within this, automobiles, station wagons, combi vans, and 2 and 3-wheel motorcycles are those that have the greatest contribution. These results were supported by non-parametric statistical tests such as Kruskal-Wallis and Mann-Whitney U and validated by the conditional bivariate probability function. The findings of this work may help to implement pollution prevention and control strategies in the future within this South American megacity.

Pathogenesis of COVID19 and the applications of US FDA-approved repurposed antiviral drugs to combat SARS-CoV-2 in Saudi Arabia: A recent update by review of literature

Still, there is no cure for the highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-caused coronavirus disease 2019 (COVID19). The COVID19 pandemic caused health emergencies which resulted in enormous medical and financial consequences worldwide including Saudi Arabia. Saudi Arabia is the largest Arab country of the Middle East. The urban setting of Saudi Arabia makes it vulnerable towards SARS-CoV-2 (SCV-2). Religious areas of this country are visited by millions of pilgrims every year for the Umrah and Hajj pilgrimage, which contributes to the potential COVID19 epidemic risk. COVID19 throws various challenges to healthcare professionals to choose the right drugs or therapy in clinical settings because of the lack of availability of newer drugs. Current drug development and discovery is an expensive, complex, and long process, which involves a high failure rate in clinical trials. While repurposing of United States Food and Drug Administration (US FDA)-approved antiviral drugs offers numerous benefits including complete pharmacokinetic and safety profiles, which significantly shorten drug development cycles and reduce costs. A range of repurposed US FDA-approved antiviral drugs including ribavirin, lopinavir/ritonavir combination, oseltamivir, darunavir, remdesivir, nirmatrelvir/ritonavir combination, and molnupiravir showed encouraging results in clinical trials in COVID19 treatment. In this article, several COVID19-related discussions have been provided including emerging variants of concern of, COVID19 pathogenesis, COVID19 pandemic scenario in Saudi Arabia, drug repurposing strategies against SCV-2, as well as repurposing of US FDA-approved antiviral drugs that might be considered to combat SCV-2 in Saudi Arabia. Moreover, drug repurposing in the context of COVID19 management along with its limitations and future perspectives have been summarized.

Air quality changes in NE Romania during the first Covid 19 pandemic wave

This study analyzes for the first time uniformly and causally the level of pollution and air quality for the NE-Romania Region, one of the poorest region in the European Union. Knowing the level of pollution and air quality in this region, which can be taken as a benchmark due to its positional and economic-geographical attributes, responds to current scientific and practical needs. The study uses an hourly database (for five pollutants and five climate elements), from 2009 to 2020, from 19 air quality monitoring stations in northeastern Romania. Pollutant levels were statistically and graphically/cartographically modeled for the entire 2009-2020 interval on the distributive-spatial and regime, temporal component. Inter-station differences and similarities were analyzed causally. Taking advantage of the emergency measures between March 16 and May 14, 2020, we observed the impact of the event on the regional air quality in northeastern Romania. During the emergency period, the metropolitan area of Suceava (with over 100,000 inhabitants) was quarantined, which allowed us to analyze the impact of the quarantine period on the local air quality. We found that, in this region, air quality falls into class I (for NO2, SO2 and CO), II for O3 and III for PM10. During the lockdown periods NO2 and SO2 decreased for the entire region by 8.6 and 14.3%, respectively, and in Suceava by 13.9 and 40.1%, respectively. The causes of the reduction were anthropogenic in nature.

A Retrospective Chart Review Evaluating Changes in 25-Hydroxyvitamin D Levels among Patients Attending the University Healthcare Centre during the COVID-19 Pandemic

COVID-19-pandemic-related home confinement aids in limiting the spread of the virus but restricts exposure to sunlight, thereby possibly affecting 25(OH)D concentrations. This study aimed to investigate the effect of lockdown measures on 25(OH)D levels in outpatients visiting the healthcare centre over a period of two years. In this retrospective chart review, outpatients who visited a university healthcare centre for a health check-up over a period of two years were included. The patients' 25(OH)D serum levels and status were compared before, during, and after the lockdown periods. A total of 7234 patients were included in this study, with a mean age of 34.66 ± 16.78. The overall prevalence of 25(OH)D insufficiency, deficiency and sufficiency was 33.8%, 30.7% and 35.4%, respectively. The proportion of individuals with 25-(OH) D deficiency prior to lockdown was 29% and this proportion increased in the lockdown and post-lockdown periods to 31.1% and 32%, respectively. Although gender was less likely to have an impact on the 25 (OH) D level during the lockdown period (p = 0.630), we found an association between gender and 25 (OH) D status in the pre-lockdown and post-lockdown periods (p < 0.001 and p < 0.001, respectively). Another association between nationality and 25 (OH)D levels was found before, during and after the lockdown periods (p < 0.001). In addition, the youngest population, aged between 1 and 14, was strongly affected by the home confinement. Age had a positive and significant (p < 0.05) effect on 25 (OH) D status regardless of the different periods. Moreover, in the pre-lockdown period, male outpatients had 1.56 chance of having a sufficient level of 25 (OH)D. However, during the lockdown period, this chance decreased to 0.85 and then increased to 0.99 after the lockdown period. We found no statistically significant difference in the mean serum concentrations or in the prevalence of vitamin D insufficiency when we compared values from before, during and immediately after the COVID-19 lockdown period. However, there was a generally increased prevalence of vitamin D insufficiency in our study population. Another association between gender, nationality and age groups with 25(OH) D was found. Regular exposure to UVR is recommended for maintaining adequate vitamin D levels and to prevent vitamin D deficiency. Further research is needed to determine the best indications for vitamin D supplementation if confinement periods are extended and to consider the potential health consequences of prolonged confinement periods not only on vitamin D status but also on overall public health. The findings of this study may be considered by stakeholders for a targeted supplementation approach for risk groups.

Investigating impacts of COVID-19 on urban mobility and emissions

The COVID-19 pandemic has severely impacted human activities in a way never documented in modern history. The prevention policies and measures have abruptly changed well-established urban mobility patterns. In this context, we exploit different sources of urban mobility data to gain insights into the effects of restrictive policies on the daily mobility and exhaust emissions in pandemic and post-pandemic periods. Manhattan, the most densely populated borough in New York City, is chosen as the study area. We collect data generated by taxis, sharing bikes, and road detectors between 2019 and 2021, and estimate exhaust emissions using the COPERT (Computer Programme to calculate Emissions from Road Transport) model. A comparative analysis is conducted to identify important changes in urban mobility and emission patterns, with a particular focus on the lockdown period in 2020 and its counterparts in 2019 and 2021. The results of the paper fuel the discussion on urban resilience and policy-making in a post pandemic world.

The positive impact of the Omicron pandemic lockdown on air quality and human health in cities around Shanghai

The Omicron pandemic broke out in Shanghai in March 2022, and some infected people spread to some cities in the Yangtze River Delta (YRD) region. To achieve the dynamic zero-COVID target as soon as possible, Shanghai and nine cities that were heavily affected by Shanghai implemented the lockdown measures. This paper aims to quantify the impact of the lockdown on air quality and human health. A difference-in-difference (DID) model was first used to measure the impact of the lockdown on air quality in these ten cities. Based on the results of the DID model, we estimated the PM2.5-related health and economic benefits using the concentration-response function and the value of statistical life method. Results showed that the lockdown has reduced the concentrations of PM2.5, PM10, SO2, NO2, and CO by 9.87 μg/m3, 17.31 μg/m3, 0.75 μg/m3, 9.03 μg/m3, and 0.07 mg/m3, respectively. The number of avoided premature deaths due to PM2.5 reduction was estimated to be 35,342. The resulting economic benefits totaled 18.86 billion US dollars. We investigated the reasons for the air quality improvement in these ten cities and found the "3 + 11" policy has had a great impact on air quality. Compared with the first COVID-19 lockdown in early 2020, the effect of the lockdown in 2022 was smaller. These findings demonstrated that reductions in anthropogenic emissions would achieve substantial air quality improvement and health benefits. This paper re-emphasized continuous efforts to improve air quality are essential to protect public health.

An assessment of aerosol optical depth over three AERONET sites in South Africa during the year 2020

It is important to notice that the world health organization (WHO) on  the 11th of March 2020,  declared COVID-19 a global pandemic and in response governments around the world introduced lockdowns that restricted human and traffic movements including South Africa. This pandemic resulted in a total lockdown from 26 March until 16 April 2020 in South Africa with expected  decrease in atmospheric aerosols. In this present study,  the aerosol optical depth (AOD) over Southern Africa based on ground-based remotely sensed data derived from three AERONET sites (Durban, Skukuza and Upington) during 2020 were used to detrermine the restriction resopnse on atmospheric aerosol pollution  The study used data from 2019, 2018 and 2017  as base years. The AERONET derived data was complemented with the HYSPLIT Model and NCEP/NCAR Reanalysis data. The study findings show that peak increase of AOD corresponds to Angstrom exponent (AE) enhancement for two sites Durban and Skukuza during winter (JJA) while the Upington site showed a different trend where peak AOD were observed in spring (SON). The study also observed the influence of long transport airmasses particularly those originating from the Atlantic and Indian ocean moreso for the Durban and Skukuza sites (summer and autumn) thus these sites received fresh marine aerosols however this was not the case for Upington which fell under the influence of short-range inland airmasses and was likely to receive anthropogenic and dust aerosols. The major results  suggest that the lockdowns did not translate into a significant decrease in AOD levels compared to previous immediate years. The results has presented restriction response of AOD over South Africa but additional analysis is required using more locations to compare results.

An assessment of NO2 atmospheric air pollution over three cities in South Africa during 2020 COVID-19 pandemic

To contain the spread of COVID-19 in 2020, several governments around the world imposed national lockdowns including that of South Africa. The purpose of this study was to investigate and give an overview of nitrogen dioxide column levels during the year 2020 over three South African cities (Johannesburg, Durban and Cape Town) using AURA OMI derived measurements, the HYSPLIT model, complemented with NCEP/NCAR reanalysis data. Our findings were that in 2020, all the cities recorded their daily maximum mean NO₂ column levels during the winter season at 14.1 × 10¹⁵ molecules per cm², 3.1 × 10¹⁵ molecules per cm² and 1.7 × 10¹⁵ molecules per cm² for Johannesburg, Durban, and Cape Town respectively. Across all seasons, Cape Town recorded the lowest seasonal mean at 0.6 × 10¹⁵ molecules per cm² (summer 2020) while the highest seasonal mean was recorded over Johannesburg at 9 × 10¹⁵ molecules cm² (winter 2020). Furthermore, an interannual comparison analysis indicated that during summer, there were increases of 6%, 1% and 30% for Johannesburg, Durban and Cape Town respectively. During winter, Johannesburg saw an increase of 19% while a 2% increase was recorded in Durban with Cape town recording a 16% decrease in NO₂ column levels. The study also recorded that Cape Town and Durban were mainly influenced by long-range transport air masses originating from the South Atlantic Ocean, South America, Antarctica and the Indian Ocean particularly during the summer and autumn seasons possibly leading to the formation of marine nitrate aerosols.

Assessing Radiation Dosage in Pediatric Head and Neck Computed Tomography Examinations During COVID-19 in a Tertiary Hospital in Saudi Arabia, Jeddah

This study aimed to assess the practice of imaging and optimization of the radiation dose in pediatric head and neck computed tomography (CT) examinations during the coronavirus disease of 2019 (COVID-19) period. This study is based on a retrospective analysis of pediatric head CT records, conducted in the Radiology Department of the King Abdulaziz University Hospital in Jeddah, Saudi Arabia. We examined the data of all pediatric patients between 0 and 14 years of age who underwent head CT scans between March and September in both 2019 (before the COVID-19 pandemic) and 2020 (during the COVID-19 pandemic). In total, we analyzed 1005 scans; 531 (52.8%) were performed before and 474 (47.2%) during COVID-19. The dose parameters were similar; however, the exposure time was significantly lower during COVID-19 (5432 ms vs. 5811 before; p < 0.001). In contrast, the mean total CTDI_vol and dose-length product (DLP) were slightly higher during COVID-19 than those before (23.34 mGy vs. 22.04 mGy (p-value=0.565) and 577.36 mGy*cm vs. 518.93 mGy*cm (p-value=0.193) respectively). These changes could be attributed to the desire to limit the contact between technicians and patients. The limitation of contact with the patient allows the technicians to be independent during the scan, possibly accounting for this slight decrease.

Impact of COVID-19 Pandemic Lockdown on the Prognosis, Morbidity, and Mortality of Patients Undergoing Elective and Emergency Abdominal Surgery: A Retrospective Cohort Study in a Tertiary Center, Saudi Arabia

The SARS-CoV-2 pandemic's main concerns are limiting the spread of infectious diseases and upgrading the delivery of health services, infrastructure, and therapeutic provision. The goal of this retrospective cohort study was to evaluate the emergency experience and delay of elective abdominal surgical intervention at King Abdul-Aziz University Hospital from October 2019 to October 2020, with a focus on post-operative morbidity and mortality before and during the COVID-19 pandemic. This study compares two groups of patients with emergent and elective abdominal surgical procedures between two different periods; the population was divided into two groups: the control group, which included 403 surgical patients, and the lockdown group, which included 253 surgical patients. During the lockdown, surgical activity was reduced by 37.2% (p = 0.014), and patients were more likely to require reoperations and blood transfusions during or after surgery (p= 0.002, 0.021, and 0.018, respectively). During the lockdown period, the average length of stay increased from 3.43 to 5.83 days (p = 0.002), and the patients who developed complications (53.9%) were more than those in the control period (46.1%) (p = 0.001). Our tertiary teaching hospital observed a significant decline in the overall number of surgeries performed during the COVID-19 pandemic and lockdown period. During the lockdown, abdominal surgery was performed only on four patients; they were positive for COVID-19. Three of them underwent exploratory laparotomy; two of the three developed shock post-operative; one patient had colon cancer (ASA score 3), one had colon disease (ASA score 2), and two had perforated bowels (ASA scores 2 and 4, respectively). Two out of four deaths occurred after surgery. Our results showed the impact of the COVID-19 lockdown on surgical care as both 30-day mortality and total morbidity have risen considerably.

A district-level vulnerability assessment of next COVID-19 variant (Omicron BA.2) in Uttarakhand using quantitative SWOT analysis

COVID-19 has had an impact on the entire humankind and has been proved to spread in deadly waves. As a result, preparedness and planning are required to better deal with the epidemic's upcoming waves. Effective planning, on the other hand, necessitates detailed vulnerability assessments at all levels, from the national to the state or regional. There are several issues at the regional level, and each region has its own features. As a result, each region needs its own COVID-19 vulnerability assessment. In terms of climate, terrain and demographics, the state of Uttarakhand differs significantly from the rest of India. As a result, a vulnerability assessment of the next COVID-19 variation (Omicron BA.2) is required for district-level planning to meet regional concerns. A total of 17 variables were chosen for this study, including demographic, socio-economic, infrastructure, epidemiological and tourism-related factors. AHP was used to compute their weights. After applying min-max normalisation to the data, a district-level quantitative SWOT is created to compare the performance of 13 Uttarakhand districts. A COVID-19 vulnerability index (normalised R i ) ranging between 0 and 1 was produced, and district-level vulnerabilities were mapped. Quantitative SWOT results depict that Dehradun is a best performing district followed by Haridwar, while Bageshwar, Rudra Prayag, Champawat and Pithoragarh are on the weaker side and the normalised Ri proves Dehradun, Nainital, Champawat, Bageshwar and Chamoli to be least vulnerable to COVID-19 (normalised R i ≤ 0.25) and Pithoragarh to be the most vulnerable district (normalised R i > 0.90). Pauri Garwal and Uttarkashi are moderately vulnerable (normalised R i 0.50 to 0.75).

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.

Changes in Air Quality and Drivers for the Heavy PM2.5 Pollution on the North China Plain Pre- to Post-COVID-19

Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.

The lock-down effects of COVID-19 on the air pollution indices in Iran and its neighbors

Introduction

The COVID-19 restrictions have a lot of various peripheral negative and positive effects, like economic shocks and decreasing air pollution, respectively. Many studies showed NO2 reduction in most parts of the world.

Methods

Iran and its land and maritime neighbors have about 7.4% of the world population and 6.3% and 5.8% of World COVID-19 cases and deaths, respectively. The air pollution indices of them such as CH4 (Methane), CO_1 (CO), H2O (Water), HCHO (Tropospheric Atmospheric Formaldehyde), NO2 (Nitrogen oxides), O3 (ozone), SO2 (Sulfur Dioxide), UVAI_AAI [UV Aerosol Index (UVAI)/Absorbing Aerosol Index (AAI)] are studied from the First quarter of 2019 to the fourth quarter of 2021 with Copernicus Sentinel 5 Precursor (S5P) satellite data set from Google Earth Engine. The outliers are detected based on the depth functions. We use a two-sample t test, Wilcoxon test, and interval-wise testing for functional data to control the familywise error rate.

Result

The adjusted p value comparison between Q2 of 2019 and Q2 of 2020 in NO2 for almost all countries is statistically significant except Iraq, UAE, Bahrain, Qatar, and Kuwait. But, the CO and HCHO are not statistically significant in any country. Although CH4, O3, and UVAI_AAI are statistically significant for some countries. In the Q2 comparison for NO2 between 2020 and 2021, only Iran, Armenia, Turkey, UAE, and Saudi Arabia are statistically significant. However, Ch4 is statistically significant for all countries except Azerbaijan.

Conclusions

The comparison with and without adjusted p values declares the decreases in some air pollution in these countries.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40808-022-01528-x.

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.

Sustainable development goals under threat? Multidimensional impact of COVID-19 on our planet and society outweigh short term global pollution reduction

The Sustainable Development Goals (SDGs) call on all nations to accomplish 17 broad global development goals by 2030. However, the COVID-19 pandemic presents a challenging period in human history, causing large-scale impacts on society and the environment as governments shift priorities and divert funding in response to this pandemic. Through a literature survey and data acquirement from various international organizations (e.g. United Nations and European Space Agency), this manuscript is intended to provide critical insights into the impacts of the COVID-19 pandemic on the SDGs. We briefly describe this pandemic's positive and short-term effects on the environment, followed by a critical evaluation of its potential long-term impacts on the environment, society, and the SDGs. On the basis of COVID-19 effects, the SDGs are classified into three categories: directly-affected SDGs, indirectly-affected SDGs, and a stand-alone category. The COVID-19-induced lockdowns and restrictions resulted in a short-term decline in environmental pollution and greenhouse gases (GHG) emissions, providing valuable data for climate advocates and researchers. These positive impacts were essentially temporary due to the synchronized global response to the pandemic. The halted focus on the progress of the SDGs greatly impacts the global green transition to a healthy and sustainable world. COVID-19 threatens to impede the progress toward a prosperous, environment-friendly, and sustainable global development in multiple ways. These multi-dimensional threats have been critically evaluated, along with a description of potential solutions to curtail the adverse effects of COVID-19 on the SDGs. Considering the limited data regarding the impacts of the pandemic on the SDGs, diverse collaborative studies at the regional and global levels are recommended.

Data-Driven Prediction of COVID-19 Daily New Cases through a Hybrid Approach of Machine Learning Unsupervised and Deep Learning

Air pollution is associated with respiratory diseases and the transmission of infectious diseases. In this context, the association between meteorological factors and poor air quality possibly contributes to the transmission of COVID-19. Therefore, analyzing historical data of particulate matter (PM2.5, and PM10) and meteorological factors in indoor and outdoor environments to discover patterns that allow predicting future confirmed cases of COVID-19 is a challenge within a long pandemic. In this study, a hybrid approach based on machine learning and deep learning is proposed to predict confirmed cases of COVID-19. On the one hand, a clustering algorithm based on K-means allows the discovery of behavior patterns by forming groups with high cohesion. On the other hand, multivariate linear regression is implemented through a long short-term memory (LSTM) neural network, building a reliable predictive model in the training stage. The LSTM prediction model is evaluated through error metrics, achieving the highest performance and accuracy in predicting confirmed cases of COVID-19, using data of PM2.5 and PM10 concentrations and meteorological factors of the outdoor environment. The predictive model obtains a root-mean-square error (RMSE) of 0.0897, mean absolute error (MAE) of 0.0837, and mean absolute percentage error (MAPE) of 0.4229 in the testing stage. When using a dataset of PM2.5, PM10, and meteorological parameters collected inside 20 households from 27 May to 13 October 2021, the highest performance is obtained with an RMSE of 0.0892, MAE of 0.0592, and MAPE of 0.2061 in the testing stage. Moreover, in the validation stage, the predictive model obtains a very acceptable performance with values between 0.4152 and 3.9084 for RMSE, and a MAPE of less than 4.1%, using three different datasets with indoor environment values.

Analysis of Particulate Matter Concentration Changes before, during, and Post COVID-19 Lockdown: A Case Study from Victoria, Mexico

The lockdown measures implemented due to the SARS-CoV-2 pandemic to reduce the epidemic curve, in most cases, have had a positive impact on air quality indices. Our study describes the changes in the concentration levels of PM2.5 and PM10 during the lockdown and post-lockdown in Victoria, Mexico, considering the following periods: before the lockdown (BL) from 16 February to 14 March, during the lockdown (DL) from 15 March to 2 May, and in the partial lockdown (PL) from 3 May to 6 June. When comparing the DL period of 2019 and 2020, we document a reduction in the average concentration of PM2.5 and PM10 of −55.56% and −55.17%, respectively. Moreover, we note a decrease of −53.57% for PM2.5 and −51.61% for PM10 in the PL period. When contrasting the average concentration between the DL periods of 2020 and 2021, an increase of 91.67% for PM2.5 and 100.00% for PM10 was identified. Furthermore, in the PL periods of 2020 and 2021, an increase of 38.46% and 31.33% was observed for PM2.5 and PM10, respectively. On the other hand, when comparing the concentrations of PM2.5 in the three periods of 2020, we found a decrease between BL and DL of −50.00%, between BL and PL a decrease of −45.83%, and an increase of 8.33% between DL and PL. In the case of PM10, a decrease of −48.00% between BL and DL, −40.00% between BL and PL, and an increase of 15.38% between the DL and PL periods were observed. In addition, we performed a non-parametric statistical analysis, where a significant statistical difference was found between the DL-2020 and DL-2019 pairs (x2 = 1.204) and between the DL-2021 and DL-2019 pairs (x2 = 0.372), with a p<0.000 for PM2.5, and the contrast between pairs of PM10 (DL) showed a significant difference between all pairs with p<0.01.

Modelling the Effect of COVID-19 Lockdown on Air Pollution in Makkah Saudi Arabia with a Supervised Machine Learning Approach

To reduce the spread of COVID-19, lockdowns were implemented in almost every single country in the world including Saudi Arabia. In this paper, the effect of COVID-19 lockdown on O3, NO2, and PM10 in Makkah was analysed using air quality and meteorology data from five sites. Two approaches were employed: (a) comparing raw measured concentrations for the lockdown period in 2019 and 2020; and (b) comparing weather-corrected concentrations estimated by the machine learning approach with observed concentrations during the lockdown period. According to the first approach, the average levels of PM10 and NO2 decreased by 12% and 58.66%, respectively, whereas the levels of O3 increased by 68.67%. According to the second approach, O3 levels increased by 21.96%, while the levels of NO2 and PM10 decreased by 13.40% and 9.66%, respectively. The machine learning approach after removing the effect of changes in weather conditions demonstrated relatively less reductions in the levels of NO2 and PM10 and a smaller increase in the levels of O3. This showed the importance of adjusting air pollutant levels for meteorological conditions. O3 levels increased due to its inverse correlation with NO2, which decreased during the lockdown period.

Evaluating the risk factor of novel public health disaster “Omicron” variant: an Indian prospective

COVID-19 epidemic is destroying world health and gradually increasing the mortality rate. The economy was also affected due to the spreading of the newly developed virus. The named COVID-19 progressively develops and affecting in the human body. The new Delta variant Omicron is first noticed in South Africa. After that many cases are recorded worldwide and finally India has recorded the first case of Omicron on 24 November 2021 from Karnataka. This study is to identify the Omicron variant affected states and UTs in India. The graphical results indicate the geographical location-wise spreading of the Omicron virus in India. The destibution of confirmed and death cases indicate the speed of spreading this health disaster in India. After that total of 781 cases were registered and 241 people were discharged from this. Mostly affected states and UTs are Delhi, Maharashtra, Karnataka, Telangana, Kerala, and Rajasthan, where Tripura, Bihar, Jharkhand, Assam, and Sikkim have not any Omicron recorded. Delhi (238), Maharashtra (167), Gujarat (73), and Kerala (65), where Himachal Pradesh, Goa, Manipur, and Ladakh have recorded one case each. The correlation between total cases and discharge is very high and the R2 value is strong positive (0.80). This situation is indicating that Omicron is gripped by public health. If we don’t maintain the social distancing and WHO notified guidelines, this condition may more harmful for human livelihood and increase the health emergency very soon.

Effects of the COVID-19 lockdown and recovery on People's mobility and air quality in the United Arab Emirates using satellite and ground observations

The stringent COVID-19 lockdown measures in 2020 significantly impacted people's mobility and air quality worldwide. This study presents an assessment of the impacts of the lockdown and the subsequent reopening on air quality and people's mobility in the United Arab Emirates (UAE). Google's community mobility reports and UAE's government lockdown measures were used to assess the changes in the mobility patterns. Time-series and statistical analyses of various air pollutants levels (NO2, O3, SO2, PM10, and aerosol optical depth-AOD) obtained from satellite images and ground monitoring stations were used to assess air quality. The levels of pollutants during the initial lockdown (March to June 2020) and the subsequent gradual reopening in 2020 and 2021 were compared with their average levels during 2015-2019. During the lockdown, people's mobility in the workplace, parks, shops and pharmacies, transit stations, and retail and recreation sectors decreased by about 34%-79%. However, the mobility in the residential sector increased by up to 29%. The satellite-based data indicated significant reductions in NO2 (up to 22%), SO2 (up to 17%), and AOD (up to 40%) with small changes in O3 (up to 5%) during the lockdown. Similarly, data from the ground monitoring stations showed significant reductions in NO2 (49% - 57%) and PM10 (19% - 64%); however, the SO2 and O3 levels showed inconsistent trends. The ground and satellite-based air quality levels were positively correlated for NO2, PM10, and AOD. The data also demonstrated significant correlations between the mobility and NO2 and AOD levels during the lockdown and recovery periods. The study documents the impacts of the lockdown on people's mobility and air quality and provides useful data and analyses for researchers, planners, and policymakers relevant to managing risk, mobility, and air quality.

Evidence from Thailand on Easing COVID-19’s International Travel Restrictions: An Impact on Economic Production, Household Income, and Sustainable Tourism Development

Even though international travel restrictions are being used to keep the COVID-19 pandemic under control, these measures cannot be considered as long-term solutions to the ongoing crisis. Limitations on traveling activities have tremendous adverse consequences on a country’s economy, particularly leading in radically expanding economic downturn and a shrinking tourism industry. To overcome this hardship, several countries have eased COVID-19 travel restrictions. However, there are still questions concerning the benefit to society as the impact assessment of this implementation transmitting to an economy has not been explicitly investigated. In response to this, we aim to assess the impacts of this implementation as to provide a guideline to global countries for their future adoption. By calculating the output and household income multipliers from the tourism input–output table, this study utilizes a case study from Thailand to indicate that prolonging the full mobility restrictions of international tourists, which results in a yearly loss of revenue in Thai tourism industry, would cost country production up to 144.97 billion USD and up to 45.4 billion USD for loss of household income. When international travel limitations were relaxed, production and household damage would fall to 142.24 billion USD (+1.88%) and 44.7 billion USD (+1.54%), respectively. At individual sectors level, our calculation identified that the most damage of production activities would exist in public utility, agriculture, and food manufacturing sectors. In the perspective of household income, those in the agricultural sector would have greatest impact. This impact results from the Thai tourism industry positioned as a buyer in an economy, having most impact on sectors selling their products or inputs to the tourism industry. As suggested by the input–output multipliers, we emphasize that strengthening the resilience of tourism-related sectors and reforming the tourism industry in relation to potential consumption and production patterns are critical for sustainable tourism development.

Increased Shamal winds and dust activity over the Arabian Peninsula during the COVID-19 lockdown period in 2020

While anthropogenic pollutants have decreased during the lockdown imposed as an effort to contain the spread of the Coronavirus disease 2019 (COVID-19), changes in particulate matter (PM) do not necessarily exhibit the same tendency. This is the case for the eastern Arabian Peninsula, where in March-June 2020, and with respect to the same period in 2016-2019, a 30 % increase in PM concentration is observed. A stronger than normal nocturnal low-level jet and subtropical jet over parts of Saudi Arabia, in response to anomalous convection over the tropical Indian Ocean, promoted enhanced and more frequent episodes of Shamal winds over the Arabian Peninsula. Increased surface winds associated with the downward mixing of momentum to the surface fostered, in turn, dust lifting and increased PM concentrations. The stronger low-level winds also favoured long-range transport of aerosols, changing the PM values downstream. The competing effects of reduced anthropogenic and increased dust concentrations leave a small positive signal (<5 W m-2) in the net surface radiation flux (Rnet), with the former dominating during daytime and the latter at night. However, in parts of the Arabian Gulf, Sea of Oman and Iran Rnet increased by >20 W m-2 with respect to the baseline period, owing to a clearer environment and weaker winds. It is concluded that a reduction in anthropogenic emissions due to the lockdown does not necessarily go hand in hand with lower particulate matter concentrations. Therefore, emissions reduction strategies need to account for feedback effects in order to reach the planned long-term outcomes.

COVID-19 in Saudi Arabia: An Overview

BACKGROUND

Saudi Arabia, a prominent Arabian country, has 35. 3 million persons living in 2.2 million square kilometers, undergone serious threats recently due to the COVID-19 pandemic. With the built-in infrastructure and disciplined lifestyle, the country could address this pandemic.

AIMS

This analysis of COVID-19 cases in Saudi Arabia attempts to assess the situation, explore its global percentage share, percentage of population affected, and local distribution from the beginning of infection until recently, tracing historical developments and changes.

DATA AND METHODS

This analysis made use of data released by the Ministry of Health on a daily basis for a number of parameters. They are compiled on an excel sheet on a daily basis: the dataset has undergone rigorous analysis along with the trends and patterns; proportion to the world statistics and geographic distribution.

RESULTS

COVID-19 spread rapidly in the country with periodic variations, during June-August, 2020. But, recoveries accelerated in the period, thus bridging the gap of increasing infections. In comparison with the world statistics, the country proportions are lower, while the percentage of population affected is similar. It appears that the intensity varied across all 13 administrative areas.

CONCLUSION

COVID-19 transmission since March 2020 is considered to be widespread, creating excess burden on the public health system, delineated into stages (early infection, rapid spread, declining, stabilizing, and second wave). Control measures are set, stage-wise, without impinging upon normal life but to ensure that the proportion of globally affected persons is lesser than the population share: credit goes to the Ministry of Health. Area-wise spread depends largely on population density and development infrastructure dimensions. Ultimately, the disciplined life in compliance with law and order paved the way for effective program implementation and epidemic control.

Impact of COVID-19 Pandemic on Air Quality: A Systematic Review

With the emergence of the COVID-19 pandemic, several governments imposed severe restrictions on socio-economic activities, putting most of the world population into a general lockdown in March 2020. Although scattered, studies on this topic worldwide have rapidly emerged in the literature. Hence, this systematic review aimed to identify and discuss the scientifically validated literature that evaluated the impact of the COVID-19 pandemic and associated restrictions on air quality. Thus, a total of 114 studies that quantified the impact of the COVID-19 pandemic on air quality through monitoring were selected from three databases. The most evaluated countries were India and China; all the studies intended to evaluate the impact of the pandemic on air quality, mainly concerning PM10, PM2.5, NO2, O3, CO, and SO2. Most of them focused on the 1st lockdown, comparing with the pre- and post-lockdown periods and usually in urban areas. Many studies conducted a descriptive analysis, while others complemented it with more advanced statistical analysis. Although using different methodologies, some studies reported a temporary air quality improvement during the lockdown. More studies are still needed, comparing different lockdown and lifting periods and, in other areas, for a definition of better-targeted policies to reduce air pollution.

Poor Air Quality in Urban Settings: A Comparison of Perceptual Indicators, Causes and Management in Two Cities

Poor air quality (PAQ) is a global concern, especially in urban areas, and is often seen as an important element of social sustainability given its negative impact on health and quality of life. However, little research has been undertaken in cities of the developing world to explore how residents perceive poor air quality, its main causes, what control measures should be used to address PAQ and where the main responsibility rests for implementing control measures. The research described in this paper sought to address these points, using a questionnaire-based survey (n = 262) in Nigeria’s federal capital city of Abuja (n = 137) and the state-capital city of Enugu (n = 125). The survey took place during the COVID-19 pandemic (October 2020 to March 2021), and was stratified to ensure representation across a number of demographic groups such as gender, age, education and income. The results were analysed using the Kruskal–Wallis non-parametric test and Hochberg’s post hoc test available in SPSS version 28. The study found that the ranking of perceptual indicators and the main causes of PAQ had much agreement between respondents from both cities and between demographic groups. Smoke, odour and dust particles were perceived to be the most important indicators of PAQ, while the main sources of PAQ were waste and bush burning, vehicle use and power generators. The two most preferred control measures were proper waste management and the avoidance of bush burning. However, there was a significant difference between the two cities in terms of the main organisations responsible for addressing PAQ, with respondents from Abuja citing the federal government, while those from Enugu cited the state government. Interestingly, younger people in Enugu noted that the government should take more responsibility in controlling PAQ than did the older demographic in that city, but this difference was not seen in Abuja. Overall, this study reveals that residents in these two Nigerian cities clearly recognise their exposure to PAQ and it suggests that these perceptual indicators, and views on sources and interventions should be central to designing policies to control this important issue.

Assessing the Impacts of Human Activities on Air Quality during the COVID-19 Pandemic through Case Analysis

COVID-19 is the latest of many pandemic affecting the world in the past few decades, and it has had a significant impact on the global environment. Some research has analysed the effects of the pandemic on air quality; however, very few studies have employed relationship analytics. In order to analyse the potential relationship between pandemic-related information and air quality data from a more holistic and detailed point of view, we propose a methodology based on pure data analysis. Three types of data were collected, namely air quality index, pandemic-related events, and number of COVID cases. Data were collected from five cities—Wuhan, New York, Seoul, Melbourne, and Singapore—to further analyse the response of air quality index to COVID events, thus revealing how human activity influences air quality from a pandemic perspective. The results show that a potential connection does exist in most cases and provide more evidence showing that air pollution declined during the pandemic. However, the strength of this relationship may also be related to other factors, such as geography, politics, population density, and measures imposed by local authorities, etc. This study provides another perspective to assist stakeholders in improving environmental decision making.

Changes in air quality in-taxis and in working conditions of taxi drivers pre- and post-lockdown, during the COVID-19 pandemic in the Paris area

We evaluated the impact of the lockdown restriction measures in the Paris area on the variation of in-vehicle ultrafine particle (UFP) and black carbon (BC) concentrations between the pre- and post-lockdown period and professional drivers' working conditions and practices. The study was conducted with 33 taxi drivers. UFP and BC were measured inside their vehicles with DiSCmini^® and microAeth^® , respectively, on two typical working days pre- and post-lockdown. Job characteristics were self-reported. Our results showed that post-lockdown, both the number of clients and journey duration significantly decreased. Taxi drivers opened their windows significantly more and reduced the use of air recirculation. UFP decreased significantly by 32% and BC by 31% post-lockdown, with a weaker positive correlation compared to pre-lockdown. The reduction of in-vehicle UFP was due mainly to the reduction of traffic flow and ventilation settings, though the latter probably varied according to traffic conditions. The variation of in-vehicle BC also tended to be related to the decrease in traffic flow post-lockdown. We emphasize the role of traffic emissions on in-vehicle air pollution and that preventive measures such ventilation settings would help to minimize the exposure of professional drivers and passengers to air pollutants.

Assessment of potential benefits of traffic and urban mobility reductions during COVID-19 lockdowns: dose-response calculations for material corrosions on built cultural heritage

Air pollution, particularly in urban areas, puts human health in danger and has adverse impacts on the built environment. It can accelerate the natural corrosion rate of cultural heritages and monuments, leading to premature aging and lowering their aesthetic value. Globally, at the beginning of 2020, to tackle the spread of novel COVID-19, the lockdown was enforced in the most hard-hit countries. Therefore, this study assesses, as a first time, the plausible benefits of traffic and urban mobility reductions on the natural process of deterioration of materials during COVID-19 lockdown in twenty-four major cities on five continents. The potential risk is estimated based on exceeding the tolerable degradation limits for each material. The notable impact of COVID-19 mobility restrictions on air quality was evidenced in 2020 compared to 2019. The introduced mobility restrictions in 2020 could decrease the surface recession rate of materials. Extremely randomized trees analysis showed that PM10 was the main influencing factor for corrosion of portland, copper, cast bronze, and carbon steel with a relative importance of 0.60, 0.32, 0.90, and 0.64, respectively, while SO2 and HNO3 were mainly responsible for corrosion of sandstone and zinc with a relative importance of 0.60 and 0.40, respectively. The globally adverse governed meteorological conditions in 2020 could not positively influence the movement restrictions around the world in air quality improvements. Our findings can highlight the need for additional policies and measures for reducing ambient pollution in cities and the proximity of sensitive cultural heritage to avoid further damage.

Analyzing the severity of coronavirus infections in relation to air pollution: evidence-based study from Saudi Arabia

COVID-19 is one of the major pandemics in history. It has caused various health problems to majority of countries in the world. Several researchers have examined and developed studies regarding concerns on air pollution being considered a major risk factor causing respiratory infections. Such infections are carried out by microorganisms, thus further affecting the immune system. The present study involves the relationship between air pollutants and the total COVID-19 infections along with the estimation of death rates in several regions of Saudi Arabia. The major goal of this study comprises the analysis of the relationship between air pollutants concentration, such as PM10, NO₂, CO, SO₂, and O₃, and the widespread outbreak of COVID-19. This scenario involves the transmission, number of patients, critical cases, and death rates. Results show that the estimation of recorded COVID-19 cases was in the most polluted regions; the mortality rate and critical cases were also more distinct in these regions than in other regions in Saudi Arabia. The finding of this study demonstrates a positive correlation between the mean values of PM10, NO₂, CO, and SO₂ pollutants. The results represent the significant relationship between air pollution resulting from a high concentration of NO₂ and COVID-19 infections and deaths. In addition, a null hypothesis of the relation between other pollutants and COVID-19 infections cannot be rejected. The study also indicates a significant correlation between the means of NO₂ and CO and the total number of critical cases. Negative correlations are obtained between the mean of O₃ and the total number of cases, total deaths, and critical case per cumulative days.

PM2.5 and PM10 during COVID-19 lockdown in Kuwait: Mixed effect of dust and meteorological covariates

This study investigated the impact of COVID-19 lockdown on particulate matter concentrations, specifically PM2.5 and PM10, in Kuwait. We studied the variations in PM2.5 and PM10 between the lockdown in 2020 with the corresponding periods of the years 2017-2019, and also investigated the differences in PM variations between the 'curfew' and 'non curfew' hours. We applied mixed-effect regression to investigate the factors that dictate PM variability (i.e., dust and meteorological covariates), and also processed satellite-based aerosol optical depths (AOD) to determine the spatial variability in aerosol loads. The results showed low PM2.5 concentration during the lockdown (33 μg/m3) compared to the corresponding previous three years (2017-2019); however, the PM10 concentration (122.5 μg/m3) increased relative to 2017 (116.6 μg/m3), and 2019 (92.8 μg/m3). After removing the 'dust effects', both PM2.5 and PM10 levels dropped by 18% and 31%, respectively. The mixed-effect regression model showed that high temperature and high wind speed were the main contributors to high PM2.5 and PM10, respectively, in addition to the dust haze and blowing dust. This study highlights that the reductions of anthropogenic source emissions are overwhelmed by dust events and adverse meteorology in arid regions, and that the lockdown did not reduce the high concentrations of PM in Kuwait.

Using Daily Nighttime Lights to Monitor Spatiotemporal Patterns of Human Lifestyle under COVID-19: The Case of Saudi Arabia

A novel coronavirus, COVID-19, appeared at the beginning of 2020 and within a few months spread worldwide. The COVID-19 pandemic had some of its greatest impacts on social, economic and religious activities. This study focused on the application of daily nighttime light (NTL) data (VNP46A2) to measure the spatiotemporal impact of the COVID-19 pandemic on the human lifestyle in Saudi Arabia at the national, province and governorate levels as well as on selected cities and sites. The results show that NTL brightness was reduced in all the pandemic periods in 2020 compared with a pre-pandemic period in 2019, and this was consistent with the socioeconomic results. An early pandemic period showed the greatest effects on the human lifestyle due to the closure of mosques and the implementation of a curfew. A slight improvement in the NTL intensity was observed in later pandemic periods, which represented Ramadan and Eid Alfiter days when Muslims usually increase the light of their houses. Closures of the two holy mosques in Makkah and Madinah affected the human lifestyle in these holy cities as well as that of Umrah pilgrims inside Saudi Arabia and abroad. The findings of this study confirm that the social and cultural context of each country must be taken into account when interpreting COVID-19 impacts, and that analysis of difference in nighttime lights is sensitive to these factors. In Saudi Arabia, the origin of Islam and one of the main sources of global energy, the preventive measures taken not only affected Saudi society; impacts spread further and reached the entire Islamic society and other societies, too.

Studying the effect of particulate matter as SARS-CoV-2 transmitters

Background: Studies of risk factors are especially valuable at this difficult time in the midst of a pandemic. High levels of particulate matter (PM) represent a serious risk factor on health. While this is a direct impact on health, indirect effects are worth considering too.

Design and methods: The aim of this study was to investigate the role of PM in the transmission of viruses, especially SARSCoV- 2. Also, we sought to understand dynamics of PM in still air at high and low altitudes. Historic AQI and physical PM measurements were collected between August and September 2020 using air quality detector. Potential correlations between the number of total confirmed COVID-19 cases and average air quality index (AQI) from varied geographic locations were also assessed.

Results: Airborne PM levels were weakly associated with COVID-19 cases after analysing 77 territories. PM remained longer in the air at high altitudes compared to measurements made at sea level. This suggests that the link between PM and COVID- 19 transmission could be aggravated in areas of high altitude.

Conclusions: This article highlights that particulate matter can be involved in SARS-CoV-2 transmission. However, confounding factors may have impacted the association between the two variables. These findings can serve as a foundation for future studies on the effect of air pollutants and fine particulate matter on viral transmission.

Reduction of surface radiative forcing observed from remote sensing data during global COVID-19 lockdown

The calamity of the COVID-19 pandemic during the early half of 2020 not only caused a huge physical and economic loss but altered the social behavior of the whole world. The social and economic stagnation imposed in many countries and served as a major cause of perturbation in atmospheric composition. This paper utilized the relation between atmospheric composition and surface radiation and analyzed the impact of global COVID-19 lockdown on land surface solar and thermal radiation. Top of atmosphere (TOA) and surface radiation are obtained from the Clouds and Earth's Radiant Energy System (CERES) and European Reanalysis product (ERA5) reanalysis product. Aerosol Optical Depth (AOD) is obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) while Nitrogen dioxide (NO₂)_, and sulfur dioxide (SO₂) are obtained from Ozone Monitoring Instrument (OMI). Observations of all mentioned parameters are studied for the global lockdown period of 2020 (from January to July) and compared with the corresponding months of the previous four years (2016-19) observations. Regarding surface radiation, April 2020 is the most affected month during the pandemic in which 0.2% increased net solar radiation (NSR), while 3.45% and 4.8% decreased net thermal radiation (NTR) and net radiation (NR) respectively was observed. Average radiative forcing during March-May 2020 was observed as 1.09 Wm^-2, -2.19 Wm^-2 and -1.09 Wm^-2 for NSR, NTR and NR, respectively. AOD was reduced by 0.2% in May 2020 while NO₂ and SO₂ were reduced by 5.4% and 8.8%, respectively, in April 2020. It was observed that NO₂ kept on reducing since January 2020 while SO₂ kept on reducing since February 2020 which were the pre-lockdown months. These results suggest that a more sophisticated analysis is needed to explain the atmosphere-radiation relation.

Coupled multifractal methods to reveal changes in nitrogen dioxide and tropospheric ozone concentrations during the COVID-19 lockdown

Due to COVID-19 pandemic, the lockdown effects on air pollution level are undeniable. Several studies around the world have detected an uneven behaviour in tropospheric ozone (O ₃) concentrations. In this work, Seville (Spain) is used as example of faced to traffic place in which the nitrogen dioxide (NO ₂) is drastically reduced (41%) while O ₃ has no significant changes. In order to evaluate the existence of differences in O ₃ behaviour that is not detected by statistical procedures, a multifractal approach was used to assess the coupled scale relationship between NO ₂ and O ₃ during the 2020 lockdown against a period reference (2017-2019). For this purpose, the two main coupled multifractal method were employed: multifractal detrended cross-correlation and joint multifractal analysis. While cross-correlation analysis did not detect differences between the cross-correlated fluctuations of NO ₂ and O ₃ in the periods analysed, the joint multifractal analysis, based on the partition function and the method of moments, found a loss of variability in O ₃ during the lockdown. This leads to a loss of multifractal characteristic of O ₃ time series. The drastically reduction of primary pollutants during the lockdown might be the responsible of the tendency to monofractality in O ₃ time series. These differences were found for a wide temporal extent ranging from 80 min to ~28 days.

The Impact of COVID-19 Lockdowns on Air Quality—A Global Review

The outbreak of the COVID-19 pandemic has emerged as a serious public health threat and has had a tremendous impact on all spheres of the environment. The air quality across the world improved because of COVID-19 lockdowns. Since the outbreak of COVID-19, large numbers of studies have been carried out on the impact of lockdowns on air quality around the world, but no studies have been carried out on the systematic review on the impact of lockdowns on air quality. This study aims to systematically assess the bibliographic review on the impact of lockdowns on air quality around the globe. A total of 237 studies were identified after rigorous review, and 144 studies met the criteria for the review. The literature was surveyed from Scopus, Google Scholar, PubMed, Web of Science, and the Google search engine. The results reveal that (i) most of the studies were carried out on Asia (about 65%), followed by Europe (18%), North America (6%), South America (5%), and Africa (3%); (ii) in the case of countries, the highest number of studies was performed on India (29%), followed by China (23%), the U.S. (5%), the UK (4%), and Italy; (iii) more than 60% of the studies included NO2 for study, followed by PM2.5 (about 50%), PM10, SO2, and CO; (iv) most of the studies were published by Science of the Total Environment (29%), followed by Aerosol and Air Quality Research (23%), Air Quality, Atmosphere & Health (9%), and Environmental Pollution (5%); (v) the studies reveal that there were significant improvements in air quality during lockdowns in comparison with previous time periods. Thus, this diversified study conducted on the impact of lockdowns on air quality will surely assist in identifying any gaps, as it outlines the insights of the current scientific research.

Effect of easing lockdown and restriction measures on COVID-19 epidemic projection: A case study of Saudi Arabia

OBJECTIVES

In this study we compared two predictions of COVID-19 cases in the Kingdom Saudi Arabia (KSA) using pre-and post-relaxation of lockdown period data to provide an insight regarding rational exit strategies. We also applied these projections to understand economic costs versus health benefit of lockdown measures.

METHODS

We analyzed open access data on COVID-19 cases from March 6 to January 16, 2021 in the KSA. To understand the epidemic projection during the pre- and post-lockdown period, we used two types of modeling: the SIR model, and the time series model. We also estimated the costs and benefits of lockdown- QALY gained compared to the costs of lockdown considering the payment threshold of the Government.

RESULTS

Prediction using lockdown period data suggested that the epidemic might slow down significantly after 109 thousand cases and end on October 6, 2020. However, analysis with latest data after easing lockdown measures suggested that epidemic might be close to an end on October 28, 2021 with 358 thousand cases. The peak has also been shifted from May 18, 2020 to Jun 24, 2020. While earlier model predicted a steady growth in mid-June, the revised model with latest data predicted it in mid-August. In addition, we estimated that 4986 lives would have been saved if lockdown continued but the cost per life saved would be more than $378 thousand, which is way above not only the KSA threshold, but also the threshold of any other highly advanced economies such as the UK and the USA.

CONCLUSIONS

Our results suggest that relaxation of lockdown measures negatively impacts the epidemic. However, considering the negative impact of prolong lockdown measures on health and economy, countries must decide on the best timing and strategy to exit from such measures to safely return to normal life with minimum loss of lives and economy considering its economic and health systems' capacity. Instead of focusing only on health, a balanced approach taking economy under consideration is recommended.

Implications of Social Isolation in Combating COVID-19 Outbreak in Kingdom of Saudi Arabia: Its Consequences on the Carbon Emissions Reduction

The aftermath of the COVID-19 pandemic has two striking impacts on the economy of the Kingdom of Saudi Arabia. First, the economic contraction of business and economic activities. Second, the effect of oil prices dropping as energy demand decreases in the international market. This study seeks to underpin the linkage between GDP growth, oil price, foreign direct investment (FDI), air transport, social globalization and carbon dioxide emission by applying time-series econometrics techniques of the following: fully modified ordinary least squares, dynamic ordinary least squares and canonical tests. The results of the Johansen cointegration test and empirical analysis trace a long-run equilibrium relationship between the highlighted variables. Our study shows that a 1% increase in FDI attraction increases economic growth by 0.004%; similarly, air transport and oil rent from KSA increased economic growth by 0.547% and 0.005%, respectively. These outcomes are indicative of the GDP growth ambition of the KSA economy in order to intensify FDI attraction and the air transportation sector. However, we also observe that increases in CO2 emission increase GDP growth. Thus, this suggests that the economic growth in KSA is not green, indicating the need for green economic growth pursuit targets.

Can COVID-19 and environmental research in developing countries support these countries to meet the environmental challenges induced by the pandemic?

Meeting the huge impact of COVID-19 on the environment requires better research on pandemic and pollution. What is the research capacity of the COVID-19 and environment in developing countries? Can this research capacity support developing countries to deal with the environmental challenges induced by the pandemic? This work is addressed to comprehensively assess the research capacity of the COVID-19 and environment in developing countries using bibliometric analysis techniques and content analysis approach to mining the Web of Science database. The results of data mining were unexpected: the global leader of the COVID-19 and environmental research was not these developed countries, but these developing countries so far, the end of 2020. Developing countries have published more papers on the pandemic and environment than developed countries, and developing countries also dominate pandemic and environmental research in terms of research institutions and authors. The results showed that (i) the impact of COVID-19 and the environment was bidirectional; (ii) energy consumption has posed great impact on environment; (iii) application of big data and artificial intelligence played an important role in improving environmental quality during the COVID-19 pandemic. Finally, policy recommendations such as formulating relevant policies and environmental standards, strengthening international exchanges and cooperation, and adjusting and improving energy consumption structure that were put forward for developing countries to meet the environmental challenges induced by the pandemic were offered. Graphical abstract.

Impact of lockdown during the COVID-19 outbreak on multi-scale air quality

One of the multi-facet impacts of lockdowns during the unprecedented COVID-19 pandemic was restricted economic and transport activities. This has resulted in the reduction of air pollution concentrations observed globally. This study is aimed at examining the concentration changes in air pollutants (i.e., carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and particulate matters (PM_2.5 and PM₁₀) during the period March-April 2020. Data from both satellite observations (for NO₂) and ground-based measurements (for all other pollutants) were utilized to analyze the changes when compared against the same months between 2015 and 2019. Globally, space borne NO₂ column observations observed by satellite (OMI on Aura) were reduced by approximately 9.19% and 9.57%, in March and April 2020, respectively because of public health measures enforced to contain the coronavirus disease outbreak (COVID-19). On a regional scale and after accounting for the effects of meteorological variability, most monitoring sites in Europe, USA, China, and India showed declines in CO, NO₂, SO₂, PM_2.5, and PM₁₀ concentrations during the period of analysis. An increase in O₃ concentrations occurred during the same period. Meanwhile, four major cities case studies i.e. in New York City (USA), Milan (Italy), Wuhan (China), and New Delhi (India) have also shown a similar reduction trends as observed on the regional scale, and an increase in ozone concentration. This study highlights that the reductions in air pollutant concentrations have overall improved global air quality likely driven in part by economic slowdowns resulting from the global pandemic.

Effect of COVID-19 pandemic-induced lockdown (general holiday) on air quality of Dhaka City

A worldwide pandemic of COVID-19 has forced the Government of Bangladesh to implement a lockdown during April-May 2020 by restricting people's movement; shutdown of industries and motor vehicles; and closing markets, public places, and schools to contain the virus. This type of strict measures caused an outcome, the reduction of urban air pollution, around the world. The present study aims to investigate the reduction of the concentration of pollutants in the air of Dhaka City and the reduction of the Air Quality Index (AQI). Necessary time-series data of the concentration of PM_2.5, NO₂, SO₂, and CO have been collected from the archive of the Air Quality Monitoring Station of the US Embassy in Dhaka and Sentinel-5P. The time-series data have been analyzed by descriptive statistics, and AQI was calculated following an appropriate formula suggested by the Environmental Protection Agency (EPA) based on the criteria pollutants. The study found that the concentrations of PM_2.5, NO₂, SO₂, and CO during April-May 2020 have been reduced by 26, 30, 07, and 07%, respectively, compared with the preceding year's concentrations. Moreover, the AQI has also been reduced by about 35% on average during the lockdown period than the same times of the previous year. However, the magnitude of pollution reduction in Dhaka is lower than in other cities and countries globally, including Delhi, Sao Paulo, Wuhan, Spain, Italy, the USA. The main reasons may include, among others, the poor implementation of lockdown (especially in the first week of April and the second fortnight of May), pre-existing pollution, transboundary pollution, incineration of solid waste, etc. This study will help policymakers figure out how to regulate pollution sources and improve the air quality of Dhaka.

Decision support system for ranking relevant indicators for reopening strategies following COVID-19 lockdowns

The pandemic caused by the spread of the SARS-CoV-2 virus forced governments around the world to impose lockdowns, which mostly involved restricting non-essential activities. Once the rate of infection is manageable, governments must implement strategies that reverse the negative effects of the lockdowns. A decision support system based on fuzzy theory and multi-criteria decision analysis principles is proposed to investigate the importance of a set of key indicators for post-COVID-19 reopening strategies. This system yields more reliable results because it considers the hesitation and experience of decision makers. By including 16 indicators that are utilized by international organizations for comparing, ranking, or investigating countries, our results suggest that governments and policy makers should focus their efforts on reducing violence, crime and unemployment. The provided methodology illustrates the suitability of decision science tools for tackling complex and unstructured problems, such as the COVID-19 pandemic. Governments, policy makers and stakeholders might find in this work scientific-based guidelines that facilitate complex decision-making processes.

Impact of lockdown on particulate matter concentrations in Colombia during the COVID-19 pandemic

The first confirmed case of COVID-19 in Colombia was reported on March 6, 2020. For this reason, on March 25, preventive isolation was declared mandatory. These measures involved the suspension of economic activities and drastically reduced the number of vehicles on the road. The objective of this study is to evaluate the impact of the lockdown due to the COVID-19 pandemic on PM_2.5 concentrations at 5 monitoring stations and aerosol optical depth values of the Terra/MODIS satellite. We analyzed and compared the weekly and monthly concentrations of PM_2.5 before and during the lockdown between the week of January 6 to June 22, 2020, and compared the daily values obtained from the Terra/MODIS satellite for the months of January-June during the years 2018-2020 to elucidate the effects of the lockdown. Similar to other monitored sites in the world, we observed substantial reductions in weekly PM_2.5 concentrations, from 41 to 84% (Bogotá), from 13 to 66% (Funza), from 17 to 57% (Boyacá), from 35 to 86% (Valledupar) and 31 at 60% (Risaralda). Unlike other studies, the aerosol optical depth values increased up to 59% during the months of lockdown compared to previous years and up to 70% of the weekly mean when compared to before the lockdown. These spatiotemporal behaviors of PM_2.5 and the aerosol optical depth in Colombia are influenced by reductions in vehicular flow during quarantine, regional rainfall, and height of the planetary boundary layer. Emissions from economic activities affect pollutant levels in the area. The analysis of the levels of pollutants during the lockdown provides a baseline for regulatory agencies to establish mitigation plans.

The influence of COVID-19 preventive measures on the air quality in Abu Dhabi (United Arab Emirates)

The preventive and cautionary measures taken by the UAE and Abu Dhabi governments to reduce the spread of the coronavirus disease (COVID-19) and promote social distancing have led to a reduction of mobility and a modification of economic and social activities. This paper provides statistical analysis of the air quality data monitored by the Environment Agency - Abu Dhabi (EAD) during the first 10 months of 2020, comparing the different stages of the preventive measures. Ground monitoring data is compared with satellite images and mobility indicators. The study shows a drastic decrease during lockdown in the concentration of the gaseous pollutants analysed (NO2, SO2, CO, and C6H6) that aligns with the results reported in other international cities and metropolitan areas. However, particulate matter (PM10 and PM2.5) averaged concentrations followed a markedly different trend from the gaseous pollutants, indicating a larger influence from natural events (sand and dust storms) and other anthropogenic sources. The ozone (O3) levels increased during the lockdown, showing the complexity of O3 formation. The end of lockdown led to an increase of the mobility and the air pollution; however, air pollutant concentrations remained in lower levels than during the same period of 2019. The results in this study show the large impact of human activities on the quality of air and present an opportunity for policymakers and decision-makers to design stimulus packages to overcome the economic slow-down, with strategies to accelerate the transition to resilient, low-emission economies and societies more connected to the nature that protect human health and the environment.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11869-021-01000-2.

Impacts of the COVID-19 lockdown on air quality and its association with human mortality trends in megapolis Mexico City

Mexico City is the second most populated city in Latin America, and it went through two partial lockdowns between April 1 and May 31, 2020, for reducing the COVID-19 propagation. The present study assessed air quality and its association with human mortality rates during the lockdown by estimating changes observed in air pollutants (CO, NO₂, O₃, SO₂, PM₁₀ and PM_2.5) between the lockdown (April 1-May 31) and prelockdown (January 1-March 31) periods, as well as by comparing the air quality data of lockdown period with the same interval of previous 5 years (2015-2019). Concentrations of NO₂ (- 29%), SO₂ (- 55%) and PM₁₀ (- 11%) declined and the contents of CO (+ 1.1%), PM_2.5 (+ 19%) and O₃ (+ 63%) increased during the lockdown compared to the prelockdown period. This study also estimated that NO₂, SO₂, CO, PM₁₀ and PM_2.5 reduced by 19-36%, and O₃ enhanced by 14% compared to the average of 2015-2019. Reduction in traffic as well as less emission from vehicle exhausts led to remarkable decline in NO₂, SO₂ and PM₁₀. The significant positive associations of PM_2.5, CO and O₃ with the numbers of COVID-19 infections and deaths, however, underscored the necessity to enforce air pollution regulations to protect human health in one of the important cities of the northern hemisphere. Graphical abstract.

Influence of lockdown caused by the COVID-19 pandemic on air pollution and carcinogenic content of particulate matter observed in Croatia

Due to the pandemic of SARS-CoV-2 in Croatia, all unnecessary activities were prohibited during the designated lockdown period (March-May 2020). With reduced human activity, levels of some air pollutants decreased. In this study, mass concentrations of the PM₁ particle fraction (particulate matter with an equivalent aerodynamic diameter < 1 μm) and polycyclic aromatic hydrocarbons (PAHs) in PM₁ and NO₂ were measured and compared with concentrations measured in the same period the year before. Air pollutant concentrations were measured at two measuring sites: urban residential and urban traffic. Our results show a concentration decrease by 35% for NO₂ and PM₁ particles and by 26% for total PAHs at the traffic measuring site. At the residential measuring site, only concentrations of NO₂ decreased slightly, but PM₁ particles and PAHs were similar to the year before.

Influence of lockdown caused by the COVID-19 pandemic on air pollution and carcinogenic content of particulate matter observed in Croatia

Due to the pandemic of SARS-CoV-2 in Croatia, all unnecessary activities were prohibited during the designated lockdown period (March-May 2020). With reduced human activity, levels of some air pollutants decreased. In this study, mass concentrations of the PM₁ particle fraction (particulate matter with an equivalent aerodynamic diameter < 1 μm) and polycyclic aromatic hydrocarbons (PAHs) in PM₁ and NO₂ were measured and compared with concentrations measured in the same period the year before. Air pollutant concentrations were measured at two measuring sites: urban residential and urban traffic. Our results show a concentration decrease by 35% for NO₂ and PM₁ particles and by 26% for total PAHs at the traffic measuring site. At the residential measuring site, only concentrations of NO₂ decreased slightly, but PM₁ particles and PAHs were similar to the year before.

Emission reduction of black carbon and polycyclic aromatic hydrocarbons during COVID-19 pandemic lockdown

The global pandemic COVID-19 necessitated various responses throughout the world, including social distancing, use of mask, and complete lockdown. While these measures helped prevent the community spread of the virus, the resulting environmental benefits of lockdown remained mostly unnoticed. While many studies documented improvements in air quality index, very few have explored the reduction in black carbon (BC) aerosols and polycyclic aromatic hydrocarbons (PAHs) concentrations due to lockdown. In this study, we evaluated the changes in concentrations of BC, PAHs, and PM_2.5 before and during the lockdown period. Our results show that lockdown resulted in a significant reduction in concentrations of these pollutants. The average mass concentration of BC, PAHs, and PM_2.5 before the lockdown was 11.71 ± 3.33 μgm^-3, 108.71 ± 27.77 ngm^-3, and 147.65 ± 41.77 μgm^-3, respectively. During the lockdown period, the concentration of BC, PAHs, and PM_2.5 was 2.46 ± 0.95 μgm^-3, 23.19 ± 11.21 ngm^-3, and 50.31 ± 11.95 μgm^-3, respectively. The diagnostic ratio analysis for source apportionment showed changes in the emission sources before and during the lockdown. The primary sources of PAHs emissions before the lockdown were biomass, coal combustion, and vehicular traffic, while during the lockdown, PAHs emissions were primarily from the combustion of biomass and coal. Similarly, before the lockdown, the BC mass concentrations came from fossil-fuel and wood-burning, while during the lockdown period, most of the BC mass concentration came from wood-burning. Human health risk assessment demonstrated a significant reduction in risk due to inhalation of PAHs and BC-contaminated air.

The influence of COVID-19 preventive measures on the air quality in Abu Dhabi (United Arab Emirates)

The preventive and cautionary measures taken by the UAE and Abu Dhabi governments to reduce the spread of the coronavirus disease (COVID-19) and promote social distancing have led to a reduction of mobility and a modification of economic and social activities. This paper provides statistical analysis of the air quality data monitored by the Environment Agency - Abu Dhabi (EAD) during the first 10 months of 2020, comparing the different stages of the preventive measures. Ground monitoring data is compared with satellite images and mobility indicators. The study shows a drastic decrease during lockdown in the concentration of the gaseous pollutants analysed (NO₂, SO₂, CO, and C₆H₆) that aligns with the results reported in other international cities and metropolitan areas. However, particulate matter (PM₁₀ and PM_2.5) averaged concentrations followed a markedly different trend from the gaseous pollutants, indicating a larger influence from natural events (sand and dust storms) and other anthropogenic sources. The ozone (O₃) levels increased during the lockdown, showing the complexity of O₃ formation. The end of lockdown led to an increase of the mobility and the air pollution; however, air pollutant concentrations remained in lower levels than during the same period of 2019. The results in this study show the large impact of human activities on the quality of air and present an opportunity for policymakers and decision-makers to design stimulus packages to overcome the economic slow-down, with strategies to accelerate the transition to resilient, low-emission economies and societies more connected to the nature that protect human health and the environment.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11869-021-01000-2.