The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality. © 2023 by the authors.

Epidemics: Some Preliminary Results

This chapter presents a novel model based on the operatorial approach for the spread of infections in a healthy population. The model efficiently describes the interactions between healthy and infected populations, and their transformation into recovered or deceased individuals. We apply our model to real situations, showing the efficacy of our method by analyzing Chinese data for SARS-2003 and COVID-19. Our model is in good agreement with the long-term behavior of the diseases, particularly in determining the number of infected and deceased individuals over time. Additionally, we demonstrate how the model can be easily adapted to account for lockdown measures, resulting in a drastic reduction of the number of infected individuals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Impact of the COVID-19 Pandemic on Global Economic Growth: An Analytical Study

The COVID-19 pandemic originated in China and quickly spread to practically every country on the planet. Because there is no cure for the virus, countries are taking steps to prevent it from spreading. Many sectors, particularly the service sector, have seen significant reductions in activities, if not a full halt, due to these policies aimed at restricting human interaction. As a result, I will statistically assess the pandemic that has a significant impact on economic growth rates in both developing as well as developed countries. Without a doubt, the economy's consequences will be determined by how long the pandemic lasts and when it returns to normal economic activity. The impacts of the COVID-19 pandemic on global economic growth are assessed in this paper. © 2022 IEEE.

Efficiency of UVC radiation as an air disinfectant in a real environment

Microbial contamination of indoor air in public spaces plays an important role in the SARSCoV-2 pandemic. So far, most studies on the reduction of airborne microbial load by UVC irradiation have been conducted as simulations or in laboratory environments. The aim of our study is to demonstrate the efficiency of Upper-Room Ultraviolet Germicidal Irradiation (UVGI) in a real environment like a supermarket. Restrictions on the use of harmful SARSCoV-2 particles for testing in public areas could be circumvented by using airborne germs as indicators. The results of this study show significant germ (bacterial and fungal) reductions by use of UVGI during business hours in a supermarket. Referring to known susceptibility values of airborne germs from previous work, we were able to estimate the effectiveness of the UVGI-system used against corona viruses. It met the requirements for complete disinfection. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

The Construction of Intelligent Homework System in Schools under the Concept of Wisdom Education

The mega-scale online education conducted nationwide during the COVID-19 epidemic has enabled online learning to move from individualized participation to full participation, practicing and advancing the development of wisdom education to a large extent. In the post-epidemic era, a new educational order that integrates online and offline learning is gradually taking shape, and online learning has become a new norm from emergency. The popularization and promotion of online education has been the general trend. The "double reduction"policy has led to a trust dilemma, a communication dilemma, a cooperation dilemma and an organizational dilemma in the practice of home-school-society collaborative parenting, and an unprecedented challenge for school education and teachers teaching. This study proposes an intelligent operating system based on big data and adaptive learning traction model, rooted in rich pedagogical theories, to solve the above-mentioned challenges in online education by virtue of "wisdom". © 2023 IEEE.

Real human close contact-based analysis on COVID-19 combined interventions

COVID-19 has threatened human lives. However, the efficiency of combined interventions on COVID-19 has not been accurately analyzed. In this study, an improved SEIR model considering both real human indoor close contact behaviors and personal susceptibility to COVID-19 was established. Taking Hong Kong as an example, a quantitative efficiency assessment of combined interventions (i.e. close contact reduction, vaccination, mask-wearing, school closures, workplace closures, and body temperature screening in public places) was carried out. The results showed that the infection risk of COVID-19 of students, workers, and non-workers/students were 3.1%, 8.7%, and 13.6%, respectively. The basic reproduction number R0 was equal to 1 when the close contact reduction rate was 59.9% or the vaccination rate reached 89.5%. The results could provide scientific support for interventions on COVID-19 prevention and control. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Who is More Likely (Not) to Make Home-Based Work Trips During the COVID-19 Pandemic? The Case of Scotland

In this study, we used survey data (n = 6,000) to investigate the work trip patterns of Scottish residents at various points of the COVID-19 pandemic. We focused specifically on the reported patterns of weekly work trips made during the government-enforced lockdown and subsequent phases of restriction easing. This was of particular importance given the widespread changes in work trips prompted by COVID-19, including a significant rise in telecommuting and a reduction in public transport commuting trips. The survey data showed that the vast majority of respondents (;85%) made no work trips during lockdown, dropping to;77% following the easing of some work-related restrictions. Zero-inflated hierarchical ordered probit models were estimated to determine the sociodemographic and behavioral factors affecting the frequency of work trips made during three distinct periods. The model estimation results showed that the socioeconomic characteristics of respondents influenced work trips made throughout the pandemic. In particular, respondents in households whose main income earner was employed in a managerial/professional occupation were significantly more likely to make no work trips at all stages of the pandemic. Those with a health problem or disability were also significantly more likely to make no work trips throughout the pandemic. Other interesting findings concern respondents' gender, as males were more likely to complete frequent work trips than females throughout the pandemic, and differences between densely populated areas and the rest of Scotland, as respondents from a large city (Edinburgh or Glasgow) were significantly more likely to make frequent work trips as restrictions were eased. © National Academy of Sciences: Transportation Research Board 2021.

Successful Implementation of Gas Driven Electric Power Grid Project for Wells and Facilities Electrification, Yielding GHG Emissions and Cost Benefits

Objectives/Scope: Kuwait Energy is exploring, developing, and operating four concessions located in the Western Desert and the Gulf of Suez in Egypt;the company implemented many projects that had a significant impact on saving operating expenses and reducing greenhouse emissions to preserve the environment. One of these recent executed projects was replacing scattered diesel generators with a Central gas-driven electric power grid in Al- Jahraa field in East Abu-Sennan concession. In this , we present the challenges we faced during the planning phase and execution strategy applied to overcome these challenges. Methods: Al-Jahraa Field includes 13 running wells, a waterflood station, and a main oil and gas production plant. The field electricity is supplied by 15 scattered diesel generators for wells and facilities, consuming 100,000 liters of diesel per month. During the feasibility study phase of the project, many challenges were faced which had a negative impact on the project's economical assessment and that would result in cancelling the project, the challenges were summarized as following;the existence of wells at long distances from the site of the proposed main power station, which would require extending long lengths of electric power cables at a high cost, also the expected delay in the implementation and commissioning of the project resulting from the long delivery time of materials, especially copper cables and main switchgear during the COVID-19 pandemic. Several scenarios were studied for connecting the wells to the power station: The first scenario was to connect all wells and field facilities directly to the main power station. In this case, the estimated power cable lengths required to be extended were 25,000 Mt, in addition to using two 1 MW generators, one in service and the other would be a standby generator to provide backup power during a repair or maintenance service. This option economic model showed negative NPV due to the high cost of cables and extended execution time. Therefore, this option was cancelled. The second alternative was to connect each group of wells to three power stations to be operated using three diesel generators of 500 kVA for each station, with three backup generators. But the implementation of this option would lead to saving the cost of copper cables by 50%, but the cost of purchasing generators would increase due to the increase in the number of stations accordingly, in addition to the increase in operating expenses resulting from the increase in fuel consumption and maintenance cost compared to the first option. The third alternative, in which the economics of the project proved to be the best, is to divide the wells into three groups. Each of the two remote groups of wells are connected to an electric distribution panel, and then the two panels are connected by a main cable to the main power station. Moreover, the project cost was reduced by 50% due to the implementation of the following innovative optimization approach: • Re-using ESP cables instead of copper cables optimized both cost and delivery time as these materials are pulled from ESP wells. • These cables are designed for harsh downhole conditions increases its durability and extends its lifetime. • Using step-up and step-down transformers enabled us to reduce cable sizing, which also reflected on the lower cost of the project and, accordingly, increased its feasibility to be constructed. • An Incremental development approach, was followed in the management and implementation of the project, led to the speed of project delivery, and reduced the project risks and uncertainties. Results: The project was completed and commissioned within the allocated budget and time frame, leading to: ◦ 100% reduction of diesel fuel consumption levels. ◦ +68% reduction in total emissions;emissions are reduced by 2.5tons per year on average. ◦ reduced operational costs for each kilowatt hour generated due to using associated gas as fuel and releasing 13 rental generators. ◦ With the replacement of 1 rental generators with just one, the amount of maintenance waste, such as batteries, used oil, oil filters, fuel filters, and so on, is significantly reduced. ◦ These projects showed positive economic indicators (+NPV), with less than 1 years of payback. Conclusion: From this project's planning, execution, and results, we can claim that if risk assessments, detailed scope of work, good resource and time management, and cost-effective choices were addressed carefully, shall result in outstanding performance. The design of a high-efficiency electrical power supply system and use of associated gas in power generation reduces levels of fuel consumption, GHG emissions, and operational costs. Power generation project is a repeated case performed in one of our own assets in Egypt due to positive results and are easily transferable to sister IOCs & NOCs. Copyright © 2023, Society of Petroleum Engineers.

Analysis of Public Transportation in Montevideo, Uruguay During the COVID-19 Pandemic

This article presents the analysis of the demand and the characterization of mobility using public transportation in Montevideo, Uruguay, during the COVID-19 pandemic. A urban data-analysis approach is applied to extract useful insights from open data from different sources, including mobility of citizens, the public transportation system, and COVID cases. The proposed approach allowed computing significant results to determine the reduction of trips caused by each wave of the pandemic, the correlation between the number of trips and COVID cases, and the recovery of the use of the public transportation system. Overall, results provide useful insights to quantify and understand the behavior of citizens in Montevideo, regarding public transportation during the COVID-19 pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Reliability and Lifetime of a Novel 222-nm KrCl Excilamp

Recent studies in the epidermis have shown that Far-UVC (200-230nm) is a promising candidate against Novel Coronavirus (SARS-Cov-2) with little DNA damage. Due to the consideration that conventional Far-UVC KrCl excilamps may emit 200-230 nm radiation (typically 222-nm peak wavelength) but with some harmful UV radiation beyond 230 to 280 nm, a novel design of Far-UVC KrCl excilamps with the filter and reflector is introduced to reduce the harmful UV radiation from 10.9% to 2.5% at the cost of 30%~40% reduction in the total irradiance. In our study, the radiant characteristics and service life of the novel Far-UVC KrCl excilamps of 40~75 Watt (electrical power) with 222-nm peak wavelength were investigated. The service life was assessed under aging at the ambient temperatures (Ta) of 25 and 85 for 500 hours, respectively. The results showed that both the ambient temperature and the root mean square of current (Irms) into the excilamps have a substantial effect on the lifetime of the KrCl excilamps. Furthermore, although no significant change of the off-nominal emission ratio existed during the lifetime test, it was observed that the high ambient temperature has a negative effect on the filtering of the harmful radiation. © 2023 IEEE.

Decision-Making in Mask Disposal Techniques Using Soft Set Theory

In 2003, Maji, Biswas, and Roy developed a method for applying soft set theory to a decision-making problem using Pawlak's rough set approach. Further, research proved that Maji's soft set reductions were inaccurate in 2005, leading to the development of a new method by Chen et al. This article applies soft theory to waste management and disposal decision-making problems. The excessive masks discarded during the COVID-19 era, in particular, must be managed effectively, and the current paper provides a method for better decision-making of the same. The algorithms used are first to compute the reductions and then the reduct soft set is used to choose the ideal objects for decision problems, and then the choice value is calculated. Predefined parameters are sometimes not enough to make precise decisions to solve general or real-time issues. Therefore, additional parameters are added into the existing set, either as a new parameter or generated by the handling of existing ones. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Remote Monitoring of COVID-19 Patients Following Discharge from a Tertiary Care Center

The COVID-19 pandemic has affected people, healthcare systems and caregivers on a global scale causing bottlenecks in hospital resources and overload of healthcare systems. The presence of disease sequelae in patients hospitalized due to CO VID-19 warrants additional care and monitoring of these patients. Remote monitoring techniques have been implemented in several domains of healthcare such as cardiology, cardiac rehabilitation and nephrology. Monitoring of vital signs using these technologies has allowed the tracking of patients with more granularity, resulting in better clinical outcomes such as reduction in hospitalizations. Therefore, we hypothesize that remote monitoring is beneficial in managing CO VID-19 patients post-hospitalization, enabling home-based patient follow-up. In this study, we investigated the use of remote monitoring on a COVID-19 patient cohort discharged from a tertiary care center. A post-hoc division of patients into two groups (alert-generating patients and non-alert generating patients) was performed. The longitudinal progression of sensor and questionnaire data was studied using linear mixed-effect models. The measured heart rate values were statistically significant in terms of the intercept (p < 0.001), indicating a difference between the two patient groups at baseline immediately post-discharge. © 2022 Creative Commons.

Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction

This study measures the total factor carbnon dioxide (CO2) emissions performance of the metal industry, iron and steel, nonferrous metal, and metal processing industries in 39 Japanese prefectures from 2008 to 2019. The true fixed-effects panel stochastic frontier model identifies regional carbon efficiency as well as the inefficiency determinants. The main results are as follows. First, a decrease in the coal ratio and an increase in the electricity ratio in total energy consumption improves efficiency. This result suggests that electrification in the metal industry, especially conversion from blast furnaces to electric furnaces in the iron and steel industry, contributes to reducing carbon emissions. Second, industrial agglomeration improves carbon emissions performance in the metal industry. This implies that agglomeration and decarbonization policies focusing on there are more effective, rather than a uniform national policy. Third, compared to the cumulative CO2 emissions over the sample period, 49,017 × 103 tons, the cumulative CO2 mitigation potential is 29,703 × 103 tons, indicating that CO2 emissions can be reduced by 60.6% without affecting the output. Forth, to examine the green economic recovery with efficiency in Japan's metal industry after COVID-19, we present a simple scenario analysis where a k% replacement coal ratio with an electricity ratio in total energy consumption, assuming that each prefecture will achieve the maximum CO2 emission amount during the sample period. By replacing 10% of the coal ratio with the electricity ratio, CO2 emissions can be reduced by 23.0%. In the case of a 20% replacement, CO2 emissions can be reduced by 33.0%. Our results show that Japan's targets in the post-COVID-19 green recovery process should be a decrease in coal consumption, an increase in electricity, and industrial agglomeration. © 2023 Elsevier Ltd

Impact of the UK's COVID-19 lockdown on the residential electricity consumption

Extreme disruptive scenarios such as pandemic lockdown force people to alter regular daily routines, impacting their energy consumption pattern. The implication of such a disruptive scenario for a more extended period on energy consumption is uncertain. This study aimed to investigate the impact of COVID-19 lockdown on residential electricity consumption in 100 houses from the southwestern UK. For the study, we analysed highly granular (1-minutely) electricity consumption data for April-September 2020 compared to the same months in 2019 for the same houses. Our study showed statistically significant differences during the lockdown period (the analysed six months) in energy demand. The minutely average electricity demand was 1.4-10% lower during April-September 2020 than in 2019. Our analysis showed that not all houses had similar type of changes during the lockdown. Some houses demonstrated a 38% increase in electricity demand, whereas some houses showed a 54% reduction during the lockdown period compared to 2019. Some houses showed significantly higher electricity use during the morning and afternoon than in 2019, which might be due to working and schooling from homes during the lockdown. © International Building Performance Simulation Association, 2022

COVID-19 Lockdown Effects on a Highly Contaminated Coastal Site: The Mar Piccolo Basin of Taranto

The COVID-19 pandemic has had a dramatic socio-economic impact on mankind;however, the COVID-19 lockdown brought a drastic reduction of anthropic impacts on the environment worldwide, including the marine–coastal system. This study is concentrated on the Mar Piccolo basin of Taranto, a complex marine ecosystem model that is important in terms of ecological, social, and economic activities. Although many numerical studies have been conducted to investigate the features of the water fluxes in the Mar Piccolo basin, this is the first study conducted in order to link meteo-oceanographic conditions, water quality, and potential reduction of anthropic inputs. In particular, we used the model results in order to study the response of the Mar Piccolo basin to a drastic reduction in the leakage of heavy metal IPAs from industrial discharges during the two months of the mandated nationwide lockdown. The results show the different behavior of the two sub-basins of Mar Piccolo, showing the different times necessary for a reduction in the concentrations of heavy metals even after a total stop in the leakage of heavy metal IPAs. The results highlight the high sensitivity of the basin to environmental problems and the different times necessary for the renewal of the water in both sub-basins. © 2023 by the authors.

Changes of Air Pollutants in Urban Cities during the COVID-19 Lockdown-Sri Lanka

In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyzes the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health. © The Author(s).

A New UAV-Based Social Distance Detector for COVID-19 Outbreaks Reduction, Using IoT, Computer Vision and Deep Learning Technologies

Nowadays, we are living in a dangerous environment and our health system is under the threatened causes of Covid19 and other diseases. The people who are close together are more threatened by different viruses, especially Covid19. In addition, limiting the physical distance between people helps minimize the risk of the virus spreading. For this reason, we created a smart system to detect violated social distance in public areas as markets and streets. In the proposed system, the algorithm for people detection uses a pre-existing deep learning model and computer vision techniques to determine the distances between humans. The detection model uses bounding box information to identify persons. The identified bounding box centroid's pairwise distances of people are calculated using the Euclidean distance. Also, we used jetson nano platform to implement a low-cost embedded system and IoT techniques to send the images and notifications to the nearest police station to apply forfeit when it detects people's congestion in a specific area. Lastly, the suggested system has the capability to assist decrease the intensity of the spread of COVID-19 and other diseases by identifying violated social distance measures and notifying the owner of the system. Using the transformation matrix and accurate pedestrian detection, the process of detecting social distances between individuals may be achieved great confidence. Experiments show that CNN-based object detectors with our suggested social distancing algorithm provide reasonable accuracy for monitoring social distancing in public places, as well. © 2022 Lavoisier. All rights reserved.

Dielectric Spectroscopy: Revealing the True Colors of Biological Matter

Accurate characterization of biological matter, for example, in tissue, cells, and biological fluids, is of high importance. For example, early and correct detection of abnormalities, such as cancer, is essential as it enables early and effective type-specific treatment, which is crucial for mortality reduction [1]. Moreover, it is imperative to investigate the effectiveness and toxicity of pharmaceutical treatments before administration in clinical practice [2]. However, biological matter characterization still faces many challenges. State-of-the-art imaging and characterization methods have drawbacks, such as the requirement to attach difficult-to-find and costly labels to the biological target (e.g., COVID-19 rapid tests), expensive equipment (e.g., magnetic resonance imaging), low accuracy (e.g., ultrasound), use of ionizing radiation (e.g., X-rays), and invasiveness [3]. The characterization of biological matter using microwave (μW), millimeter-wave (mmW), and terahertz (THz) spectroscopy is a promising alternative: it is label-free, does not require ionizing radiation, and can be noninvasive. Moreover, there is a significant difference in how different biological materials absorb, reflect, and transmit electromagnetic (EM) waves [4] that is due to the difference in their dielectric properties. The dielectric properties are described by the frequency-dependent material parameter called the complex permittivity f, which expresses how the material responds to an external oscillating electric field. The complex permittivity of a material determines how the material absorbs, reflects, and transmits EM waves at different frequencies (Figure 1). Since each biological material's permittivity spectrum is different, it acts as an EM fingerprint. A material's complex permittivity can be calculated from the reflection and transmission of EM waves through the material, described by the S-parameters, which can be measured using a vector network analyzer (VNA) transmitting and receiving EM waves over a range of frequencies. The amplitude and phase of the transmitted and reflected EM waves at different frequencies are influenced by different underlying biological effects at different scales. That causes the entire spectrum to provide information from the supracellular to the molecular and even atomic scale. © 2000-2012 IEEE.

Digital Transformation for Promoting Renewable Energy & Sustainability: A Systematic Approach for Carbon Footprint Reduction in Well Construction

As the industry recovers from the recent downturn in petroleum commodity prices and the economic impacts from coronavirus (COVID-19), governing authorities in most countries are imposing methodological measures to promote the reduction of carbon footprint. This affects every industry including the petroleum sector. Therefore, most investors and stakeholders have increased their focus on Environmental, Social, and Corporate Governance (ESG) policies. During the well construction phase, a transition from a hydraulic to an electric tong is achieved, resulting in carbon footprint reduction. Achieving carbon neutrality or carbon emission reduction while producing hydrocarbons is one of the topmost key performance indicators (KPIs) in the industry. With the implementation of digital technologies in the tubular and casing connection make-up process, a hydraulic tong is substituted with an electric tong of an equivalent specification. The energy consumption for both systems are calculated and compared. Other important KPIs on tracking operational cost are also assessed and the results are then compared to determine the benefits of implementing the upgraded digitalized tong solution. The electric tong digitalized solution, commercially available in the petroleum industry, is a key enabler for carbon emission reduction while running tubulars in/out of the wellbore. This solution is one of the milestones that serve as foundation to advocate carbon reduction. Eventually, this will lead to establishing carbon neutrality during hydrocarbon extraction and production. The results concluded that a digitalized solution eventually reduced personnel on board working in the "red zone," which eventually leads to carbon emission reductions caused by a decrease in fuel consumption. The decrease of 43% in CO2 emission is observed while performing tubular connection process. Moreover, an overall comparison between a legacy system with the digitalized electric system displayed more than 59% reduction in CO2 during the tubular running services. In addition to carbon reduction, this electric power and control solution allows for more precise torque control, leading to enhanced system integrity and increased reliability achieved by cleaner energy. With this digital solution, not only is the safety and well-being of rig personnel enhanced to avoid any recordable incidents, the reduction of carbon emission is also achieved, aligning to the objectives of current ESG regulatory authorities. This paper will provide comprehensive details on the novelty of this technology and solution offered to the industry. © 2022, Offshore Technology Conference. All rights reserved.

Air Quality Index (AQI) Did Not Improve during the COVID-19 Lockdown in Shanghai, China, in 2022, Based on Ground and TROPOMI Observations

The lockdowns from the coronavirus disease of 2019 (COVID-19) have led to a reduction in anthropogenic activities and have hence reduced primary air pollutant emissions, which were reported to have helped air quality improvements. However, air quality expressed by the air quality index (AQI) did not improve in Shanghai, China, during the COVID-19 outbreak in the spring of 2022. To better understand the reason, we investigated the variations of nitrogen dioxide (NO2), ozone (O3), PM2.5 (particular matter with an aerodynamic diameter of less than 2.5 μm), and PM10 (particular matter with an aerodynamic diameter of less than 10 μm) by using in situ and satellite measurements from 1 March to 31 June 2022 (pre-, full-, partial-, and post-lockdown periods). The results show that the benefit of the significantly decreased ground-level PM2.5, PM10, and NO2 was offset by amplified O3 pollution, therefore leading to the increased AQI. According to the backward trajectory analyses and multiple linear regression (MLR) model, the anthropogenic emissions dominated the observed changes in air pollutants during the full-lockdown period relative to previous years (2019–2021), whereas the long-range transport and local meteorological parameters (temperature, air pressure, wind speed, relative humidity, and precipitation) influenced little. We further identified the chemical mechanism that caused the increase in O3 concentration. The amplified O3 pollution during the full-lockdown period was caused by the reduction in anthropogenic nitrogen oxides (NOx) under a VOC-limited regime and high background O3 concentrations owing to seasonal variations. In addition, we found that in the downtown area, ground-level PM2.5, PM10, and NO2 more sensitively responded to the changes in lockdown measures than they did in the suburbs. These findings provide new insights into the impact of emission control restrictions on air quality and have implications for air pollution control in the future. © 2023 by the authors.