Impact of COVID -19 pandemic lockdown on distribution of inorganic pollutants in selected cities of Nigeria

Unintended consequences of implementing non-pharmaceutical interventions for the COVID-19 response in Africa: experiences from DRC, Nigeria, Senegal, and Uganda

INTRODUCTION

The coronavirus (COVID 19) pandemic is one of the most terrifying disasters of the twenty-first century. The non-pharmaceutical interventions (NPIs) implemented to control the spread of the disease had numerous positive consequences. However, there were also unintended consequences-positively or negatively related to the nature of the interventions, the target, the level and duration of implementation. This article describes the unintended economic, Psychosocial and environmental consequences of NPIs in four African countries.

METHODS

We conducted a mixed-methods study in the Democratic Republic of Congo (DRC), Nigeria, Senegal and Uganda. A comprehensive conceptual framework, supported by a clear theory of change was adopted to encompass both systemic and non-systemic interventions. The data collection approaches included: (i) review of literature; (ii) analysis of secondary data for selected indicators; and (ii) key informant interviews with policy makers, civil society, local leaders, and law enforcement staff. The results were synthesized around thematic areas.

RESULTS

Over the first six to nine months of the pandemic, NPIs especially lockdowns, travel restrictions, curfews, school closures, and prohibition of mass gathering resulted into both positive and negative unintended consequences cutting across economic, psychological, and environmental platforms. DRC, Nigeria, and Uganda observed reduced crime rates and road traffic accidents, while Uganda also reported reduced air pollution. In addition, hygiene practices have improved through health promotion measures that have been promoted for the response to the pandemic. All countries experienced economic slowdown, job losses heavily impacting women and poor households, increased sexual and gender-based violence, teenage pregnancies, and early marriages, increased poor mental health conditions, increased waste generation with poor disposal, among others.

CONCLUSION

Despite achieving pandemic control, the stringent NPIs had several negative and few positive unintended consequences. Governments need to balance the negative and positive consequences of NPIs by anticipating and instituting measures that will support and protect vulnerable groups especially the poor, the elderly, women, and children. Noticeable efforts, including measures to avoid forced into marriage, increasing inequities, economic support to urban poor; those living with disabilities, migrant workers, and refugees, had been conducted to mitigate the negative effects of the NIPs.

A bibliometric analysis of the impact of COVID-19 social lockdowns on air quality: research trends and future directions

Social lockdowns improved air quality during the COVID-19 pandemic. Governments had previously spent a lot of money addressing air pollution without success. This bibliometric study measured the influence of COVID-19 social lockdowns on air pollution, identified emerging issues, and discussed future perspectives. The researchers examined the contributions of countries, authors, and most productive journals to COVID-19 and air pollution research from January 1, 2020, to September 12, 2022, from the Web of Sciences Core Collection (WoS). The results showed that (a) publications on the COVID-19 pandemic and air pollution were 504 (research articles) with 7495 citations, (b) China ranked first in the number of publications (n = 151; 29.96% of the global output) and was the main country in international cooperation network, followed by India (n = 101; 20.04% of the total articles) and the USA (n = 41; 8.13% of the global output). Air pollution plagues China, India, and the USA, calling for many studies. After a high spike in 2020, research published in 2021 declined in 2022. The author's keywords have focused on "COVID-19," "air pollution," "lockdown," and "PM25." These keywords suggest that research in this area is focused on understanding the health impacts of air pollution, developing policies to address air pollution, and improving air quality monitoring. The COVID-19 social lockdown served as a specified procedure to reduce air pollution in these countries. However, this paper provides practical recommendations for future research and a model for environmental and health scientists to examine the likely impact of COVID-19 social lockdowns on urban air pollution.

COVID-19 pandemic, port congestion, and air quality: Evidence from China

The emergency of COVID-19 leads to almost all unnecessary activities being banned because of city lockdowns, which results in the economy and human mobility being strictly restricted. While affecting economic development, it has brought some environmental benefits. As a critical link to collection and distribution, ports have been deeply impacted by COVID-19, including quarantine time and operational efficiency, and even cause unexpected port congestion. This study empirically examines the relationship between the COVID-19 pandemic, port congestion and air quality in Chinese port cities using classical and system panel models. We find that the COVID-19 pandemic and port congestion significantly influence air quality in port cities. Managerial implications include the ensuring of port workers' shifts, the unblocking of port logistics, and the cooperation between transportation, customs, and quarantine departments, which can reduce the time of ships at berths and improve the air quality in port cities.

Association Between Weather Parameters and SARS-CoV-2 Confirmed Cases in Two South African Cities

Several approaches have been used in the race against time to mitigate the spread and impact of COVID-19. In this study, we investigated the role of temperature, relative humidity, and particulate matter in the spread of COVID-19 cases within two densely populated cities of South Africa-Pretoria and Cape Town. The role of different levels of COVID-19 restrictions in the air pollution levels, obtained from the Purple Air Network, of the two cities were also considered. Our results suggest that 26.73% and 43.66% reduction in PM2.5 levels were observed in Cape Town and Pretoria respectively for no lockdown (Level 0) to the strictest lockdown level (Level 5). Furthermore, our results showed a significant relationship between particulate matter and COVID-19 in the two cities. Particulate matter was found to be a good predictor, based on the significance of causality test, of COVID-19 cases in Pretoria with a lag of 7 days and more. This suggests that the effect of particulate matter on the number of cases can be felt after 7 days and beyond in Pretoria.

Impacts of COVID-19 Restrictions on Regional and Local Air Quality Across Selected West African Cities

The emergence of COVID-19 brought with it panic and a sense of urgency causing governments to impose strict restrictions on human activities and vehicular movements. With anthropogenic emissions, especially waste management (domestic and municipal), traffic, and industrial activities, said to be a significant contributor to ambient air pollution, this study assessed the impacts of the imposed restrictions on the concentrations and size distribution of atmospheric aerosols and concentration of gaseous pollutants over West African subregion and seven major COVID-19 epicenters in the subregion. Satellite retrievals and reanalysis data sets were used to study the impact of the restrictions on Aerosol Optical Depth (AOD) and atmospheric concentrations NO2, SO2, CO, and O3. The anomalies were computed for 2020 relative to 2017-2019 (the reference years). In 2020 relative to the reference years, for area-averaged AOD levels, there was a consequential mean percentage change between -6.7% ± 21.0% and 19.2% ± 27.9% in the epicenters and -10.1% ± 15.4% over the subregion. The levels of NO2 and SO2 also reduced substantially at the epicenters, especially during the periods when the restrictions were highly enforced. However, the atmospheric levels of CO and ozone increased slightly in 2020 compared to the reference years. This study shows that "a one cap fits all" policy cannot reduced the level of air pollutants and that traffic and industrial processes are not the predominant sources of CO in major cities in the subregion.

COVID-19 induced restriction in developing countries and its impacts on pollution load: case study of Lagos mega city

Sudden outbreak of COVID-19 pandemic globally in 2020 warranted urgent course of actions to guide against its escalation. The first and immediate measure adopted by several nations was the imposition of restriction on transport, industrial, commercial and social activities; and this step has thus, provided a platform for the impact assessment of the restrictions on ambient air quality, especially in developing nations such as Nigeria. The levels of four criteria air pollutants (PM_2.5, SO₂, NO₂, and PM₁₀) in ambient air of Lagos city before, during and after the restriction periods were compared to establish the extent of change caused by the restrictions. The results revealed a decline of 74.0, 79.7, 55.0 and 58.5% in the levels of SO₂, NO₂, PM_2.5, and PM₁₀, respectively during the lockdown period. The results also revealed that, despite the huge reduction in the atmospheric emissions witnessed during lockdown period, air quality within the region was still poor, as the levels of most of the pollutants were above the recommended limits. These findings suggested that apart from the restricted activities, there are other air pollution sources within the city which increased the pollution load in the ambient air. Conclusively, while the restriction led to untold economic hardship, it equally enhanced quality of ambient air. Cleaner technology is advocated to ensure reduction in the consumption of fossil fuel instead of the common practice of end-of-pipe technology, for environmental sustainability.

COVID-19 Vaccines and Public Anxiety: Antibody Tests May Be Widely Accepted

Background

More than 200 countries are experiencing the coronavirus disease (COVID-19) pandemic. COVID-19 vaccination strategies have been implemented worldwide, and repeat COVID-19 outbreaks have been seen. The purpose of this study was to investigate the impact of COVID-19 vaccination on the reduction of perceived anxiety and the association between public anxiety and antibody testing intention during the COVID-19 pandemic.

Methods

Chinese adults aged 18 and over were surveyed using an anonymous online questionnaire in April and May 2021. The questionnaire collected sociodemographic characteristics, vaccination characteristics, perceived anxiety due to COVID-19, and attitudes toward future antibody testing after COVID-19 vaccination. Perceived anxiety was assessed on a visual analog scale (VAS). Multivariate logistic regression analysis was used to determine the factors influencing future antibody detection.

Results

A total of 3,233 people were investigated, 3,209 valid questionnaires were collected, and the response rate was 99.3%. Of the 3,209 respondents, 2,047 were vaccinated, and 1,162 were unvaccinated. There was a significant difference in anxiety levels between vaccinated and unvaccinated respondents (24.9±25.4 vs. 50.0±33.1, respectively). With the local spread of COVID-19 in mainland China, the public anxiety VAS scores increased by 15.4±25.6 (SMD=120%) and 33.8±31.7 (SMD=49%) among vaccinated and unvaccinated respondents, respectively. Of the 2,047 respondents who were vaccinated, 1,626 (79.4%) thought they would accept antibody testing. Those who displayed more anxiety about acquiring COVID-19 disease were more likely to accept COVID-19 antibody testing. If the antibody test results showed protective antibodies, 1,190 (58.1%) were more likely to arrange travel plans in China, while 526 (25.7%) thought they would feel safer traveling abroad.

Conclusion

COVID-19 vaccination strategies help reduce public anxiety. However, public anxiety may be elevated as the local transmission of COVID-19 occurs in mainland China, which is usually caused now by imported cases. Those who display more anxiety choose to have antibody testing. Improving the accessibility of COVID-19 antibody tests can help ease public anxiety and enhance the confidence of some people to participate in social activities.

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.

Predicting COVID-19 Cases From Atmospheric Parameters Using Machine Learning Approach

The dynamical nature of COVID-19 cases in different parts of the world requires robust mathematical approaches for prediction and forecasting. In this study, we aim to (a) forecast future COVID-19 cases based on past infections, (b) predict current COVID-19 cases using PM2.5, temperature, and humidity data, using four different machine learning classifiers (Decision Tree, K-nearest neighbor, Support Vector Machine, and Random Forest). Based on RMSE values, k-nearest neighbor and support vector machine algorithms were found to be the best for predicting future incidences of COVID-19 based on past histories. From the RMSE values obtained, temperature was found to be the best predictor for number of COVID-19 cases, followed by relative humidity. Decision tree models was found to perform poorly in the prediction of COVID-19 cases considering particulate matter and atmospheric parameters as predictors. Our results suggests the possibility of predicting virus infection using machine learning. This will guide policy makers in proactive monitoring and control.

Dealing with impact of COVID-19 on transportation in a developing country: Insights and policy recommendations

While developed nations have established policy frameworks for dealing with various macroeconomic shocks, developing countries respond to the influx of COVID-19 on heterogeneous scales, borne out of varying institutional bottlenecks. These inadequate transport facilities are not diversified enough to deal with an impending public health crisis. With the growing divergence in public transport management procedures and societal responses and willingness to adjust to a "new normal" transport procedures in time of COVID-19 and post-pandemic, it becomes expedient to learn evidence-based policy responses to transport service delivery. Qualitative data from semi-structured interviews with commuters and operators were thematically analysed to understand the impact of COVID-19 on transportation in Lagos Nigeria. The analysis revealed that increased cost of transportation, financial sustainability, changes in travel needs and loss of revenue were the significant impacts of the pandemic. This study contributes such that transport stakeholders can better understand how to navigate their transportation needs at this time of global uncertainty. The understanding of these impacts advances policy recommendations that are most inclined to the development objectives of developing nations in the time of COVID-19 and beyond. The limitations and suggestions for further research were discussed.

The Role of Meteorological Variables and Aerosols in the Transmission of COVID-19 During Harmattan Season

The role of atmospheric parameters and aerosols in the transmission of COVID-19 within tropical Africa, especially during the harmattan season, has been under-investigated in published papers. The harmattan season within the West African region is associated with significant dust incursion from the Bodele depression and biomass burning. In this study, the correlation between atmospheric parameters (temperature and humidity) and aerosols with COVID-19 cases and fatalities within seven locations in tropical Nigeria during the harmattan period was investigated. COVID-19 infection cases were found to be significantly positively correlated with atmospheric parameters (temperature and humidity) in the southern part of the country while the number of fatalities showed weaker significant correlation with particulate matters only in three locations. The significant correlation values were found to be between 0.22 and 0.48 for particulate matter and -0.19 to -0.32 for atmospheric parameters. Although, temperature and humidity showed negative correlations in some locations, the impact is smaller compared to particulate matter. In December, COVID-19 cases in all locations showed strong correlation with particulate matter except in Kano State. It is suggested that a reduction in atmospheric particulate matter can be used as a control measure for the spread of COVID-19.

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.

Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review

The ongoing COVID-19 global pandemic is touching every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and non-pharmaceutical interventions of lockdown and confinement implemented citywide, regionally or nationally are affecting virus transmission, people's travel patterns, and air quality. Many studies have been conducted to predict the diffusion of the COVID-19 disease, assess the impacts of the pandemic on human mobility and on air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This literature review aims to analyze the results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 viral transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also explores the spatio-temporal aspects of lockdown and confinement measures on coronavirus diffusion, human mobility, and air quality. Additionally, we discuss policy implications, which will be helpful for policy makers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

The impact of COVID-19 pandemic on nitrogen dioxide levels in Nigeria

The Coronavirus disease (COVID-19) has been transmitted worldwide over a very short time after it originated in China in December 2019. In an attempt to control its spread and reduce its health impacts, several countries including those in the African continent imposed restrictive measures that was termed "lockdown". The outcomes of this lockdown have been reported to be beneficial to air quality worldwide. The main objective of this study is to assess the impact of lockdown due to COVID-19 on nitrogen dioxide (NO2) levels over six major cities in Nigeria. Maps extracted from satellite (Sentinel-5P) were used to indicate the significant reduction in the level of NO2 in the selected cities in Nigeria during two time-intervals, pre-lockdown (December, 2019) and during lockdown (April, 2020). The results show a significant reduction in NO2 levels during the lockdown period compared with its levels during the pre-lockdown period in 2019. The reduction in NO2 concentration levels during lockdown is likely due to less traffic, social distancing and restrictions on business and human activities. There could be an element of uncertainty in the results due to seasonality, as the comparison is done with a different season. However, the magnitude of change due to lockdown is probably much higher than the seasonal variability. Although COVID-19 has negatively impacted the health and economic status of all regions worldwide, it has benefited some aspects of air quality in most countries including Nigeria. This indicates that anthropogenic activities may be managed to reduce air pollution and positively impact the health of human beings.

Regional Scale Impact of the COVID-19 Lockdown on Air Quality: Gaseous Pollutants in the Po Valley, Northern Italy

The impact of the reduced atmospheric emissions due to the COVID-19 lockdown on ambient air quality in the Po Valley of Northern Italy was assessed for gaseous pollutants (NO2, benzene, ammonia) based on data collected at the monitoring stations distributed all over the area. Concentration data for each month of the first semester of 2020 were compared with those of the previous six years, on monthly, daily, and hourly bases, so that pre, during, and post-lockdown conditions of air quality could be separately analyzed. The results show that, as in many other areas worldwide, the Po Valley experienced better air quality during 2020 spring months for NO2 and benzene. In agreement with the reductions of nitrogen oxides and benzene emissions from road traffic, estimated to be −35% compared to the regional average, the monthly mean concentration levels for 2020 showed reductions in the −40% to −35% range compared with the previous years, but with higher reductions, close to −50%, at high-volume-traffic sites in urban areas. Conversely, NH3 ambient concentration levels, almost entirely due the emissions of the agricultural sector, did not show any relevant change, even at high-volume-traffic sites in urban areas. These results point out the important role of traffic emissions in NO2 and benzene ambient levels in the Po Valley, and confirm that this region is a rather homogeneous air basin with urban area hot-spots, the contributions of which add up to a relatively high regional background concentration level. Additionally, the relatively slow response of the air quality levels to the sudden decrease of the emissions due to the lockdown shows that this region is characterized by a weak exchange of the air masses that favors both the build-up of atmospheric pollutants and the development of secondary formation processes. Thus, air quality control strategies should aim for structural interventions intended to reduce traffic emissions at the regional scale and not only in the largest urban areas.

Air-pollutant mass concentration changes during COVID-19 pandemic in Shanghai, China

To curb the spread of the coronavirus, China implemented lockdown policies on January 23, 2020. The resulting extreme changes in human behavior may have influenced the air pollutants concentration. However, despite these changes, hazy weather persisted in Shanghai and became a public issue. This study aims to investigate air pollutant mass concentration changes during the lockdown in Shanghai. Air pollutant mass concentration data and meteorological data during the pre-lockdown period and the level I response lockdown period were analyzed by statistical analysis and a Lagrangian particle diffusion model. The data was classified in three periods: P1 (pre-lockdown: 10 days before the Spring Festival), P2 (the first 10 days after lockdown: during the Spring Festival celebration), and P3 (the second 10 days after lockdown: after the Spring Festival). Data for the same period in 2019 were used as a reference. The results indicate that the Spring Festival holiday in 2019 resulted in a reduction in energy consumption, which led to a decrease in PM_2.5 (26.4%) and NO₂ (43.41%) mass concentration, but an increase in ozone mass concentration (31.39%) in P2 compared with P1. The integrated effect of the Spring Festival holiday and lockdown in 2020 resulted in a decrease in PM_2.5 (36.5%) and NO₂ (51.9%) mass concentrations, but an increase in ozone mass concentration (43.8%) in P2 compared with P1. After the Spring Festival, the mass concentrations of PM_2.5, SO₂, and NO₂ increased by 74.41%, 5.52%, and 53.28%, respectively in P3 compared with P2 in 2019. However, PM_2.5 and SO₂ concentrations in 2020 continued to decrease, by 14.74% and 4.61%, respectively, while NO₂ mass concentration increased by 7.82% in P3 compared with P2. We also found that PM_2.5 mass concentration is susceptible to regional transmission from the surrounding cities. PM_2.5 and other gaseous pollutants show different correlations in different periods, while NO₂ and O₃ always show a strong negative correlation. The principal components before the Spring Festival in 2019 were O₃ and NO₂, and after the Spring Festival, they were PM_2.5 and CO, while the principal components before the lockdown in 2020 were PM_2.5 and CO, and during lockdown they were O₃ and NO₂.