City Lockdown Research Articles

Chinese Journalists’ Witnessing Practice in Health Disasters

ABSTRACT While “ears-and-eyes” and “mouthpieces” are two normative roles of Chinese journalists, the latter has long been more emphasized in the mobilization model of disaster reporting. Based on in-depth interviews with Chinese journalists who witnessed city lockdowns during the COVID-19 pandemic, this study examines how they performed the two roles to determine the extent to which their witnessing experiences could be transformed into media discourses. It argues that journalists’ bearing witness on disaster sites presupposed not only eyewitnessing but also earwitnessing in the form of survivor interviewing, fact checking, and truth investigation. While the “mouthpiece” orientation of news media may have obscured the potential of journalistic witnessing for timely exposing public suffering, there existed journalist-media negotiations on performing the two roles. Highlighting the role asymmetry between “ears-and-eyes” and “mouthpieces”, this study examines the veracity gap in Chinese journalists’ witnessing practice that derives from the tension between journalistic autonomy and structural restraints, which may contribute to the further theorization of journalistic witnessing.

Does COVID-19 lockdown matter for air pollution in the short and long run in China? A machine learning approach to policy evaluation

This paper leverages a data-driven two-step approach to effectively evaluate the effects of COVID-19 lockdown on air pollution in both the short and long-term in China. Using air pollution, meteorological conditions, and air mass clusters from 34 air quality monitoring stations in Beijing from 2015 to 2022, this study first employs a deweathering machine learning technique to decouple the confounding effects of meteorological on the air pollution. Furthermore, a detrending percentage change indictor is applied to remove the influence of seasonal variations on air pollution. The findings reveal that: (1) Human interventions are the primary drivers of changes in air pollution concentrations, whereas meteorological factors have a relatively minor impact. (2) During the COVID-19 lockdown, significant variations in air pollution levels are observed, with the effects of city lockdown ranging from a decrease of 40.11% ± 14.81% to an increase of 20.28% ± 14.36%. Notably, there is a decline in concentrations of NO2, PM2.5, CO, and PM10, while the levels of O3 and SO2 increase even during the strictest lockdown period. (3) In the year following the COVID-19 lockdown, there is a rebound in overall air pollution levels. However, by the second year, a general decline in air pollution is observed, except for O3. Therefore, it is imperative to integrate the confounding effects of meteorological factors into air quality management policies under various future scenarios: adopt high-intensity control measures for sudden air quality deteriorations, advance green recovery initiatives for long-term emission reductions, and coordinate efforts to reduce composite atmospheric pollution.

Resilience analysis of urban commercial area under the COVID-19 epidemic using night-time light remote sensing data

ABSTRACT The global outbreak of the novel coronavirus has had a great impact on commercial areas, particularly in Wuhan, the first city in China affected by the epidemic. Exploring the changing pattern of these areas during the epidemic period is crucial for effectively restoring the urban economic level and promoting economic development on the basis of epidemic prevention and control in the post-epidemic era. The paper proposes a resilience analysis of urban commercial areas during the COVID-19 epidemic using time-series night-time light remote sensing data. Based on the constructed time-series night-time light remote sensing dataset and considering the urban impervious surface, the urban commercial area was extracted under multi-scale segmentation. Based on night-time light data before and after the epidemic, the resilience of representative commercial areas in Wuhan City, Hubei Province during the COVID-19 epidemic was analysed using a modified improved resilience assessment framework. The results showed that the lighting values of commercial areas and impervious areas decreased by up to 30% following the implementation of city lockdown measures. The change of light brightness in the commercial areas was more prominent, and the range of change is larger than that in the non-commercial areas. The lighting brightness of the commercial areas exhibited a significant downward trend throughout the entire lockdown period, and the downward trend will still remain for a period of time after unlocking. Among all the commercial areas, Wuguang commercial area demonstrated the highest recovery rate during the lockdown period and instantaneous recovery rate after the lockdown, with relatively low closure loss and the highest level of resilience.

A Metric of Societal Burden Based on Virus Succession to Determine Economic Losses and Health Benefits of China's Lockdown Policies: Model Development and Validation.

The COVID-19 pandemic had a profound impact on the global health system and economic structure. Although the implementation of lockdown measures achieved notable success in curbing the spread of the pandemic, it concurrently incurred substantial socioeconomic costs. The objective of this study was to delineate an equilibrium between the economic losses and health benefits of lockdown measures, with the aim of identifying the optimal boundary conditions for implementing these measures at various pandemic phases. This study used a model to estimate the half-lives of the observed case fatality rates of different strains. It was based on global infection and death data collected by the World Health Organization and strain sequence time series data provided by Nextstrain. The connection between the health benefits and economic losses brought by lockdown measures was established through the calculation of disability-adjusted life years. Taking China's city lockdowns as an example, this study determined the cost-benefit boundary of various lockdown measures during the evolution of COVID-19. The study reveals a direct proportionality between economic losses due to lockdowns and the observed case fatality rates of virus strains, a relationship that holds true irrespective of population size or per capita economic output. As SARS-CoV-2 strains evolve and population immunity shifts, there has been a notable decrease in the observed case fatality rate over time, exhibiting a half-life of roughly 8 months. This decline in fatality rates may offset the health benefits of maintaining unchanged lockdown measures, given that the resultant economic losses might exceed the health benefits. The initial enforcement of lockdown in Wuhan led to significant health benefits. However, with the decline in the observed case fatality rate of the virus strains, the economic losses increasingly outweighed the health benefits. Consequently, it is essential to consistently refine and enhance lockdown strategies in accordance with the evolving fatality and infection rates of different virus strains, thereby optimizing outcomes in anticipation of future pandemics.

Spatiotemporal Dynamics of COVID‐19 Pandemic City Lockdown: Insights From Nighttime Light Remote Sensing

AbstractThe global COVID‐19 outbreak severely hampered the growth of the global economy, prompting the implementation of the strictest prevention policies in China. Establishing a significant relationship between changes in nighttime light and COVID‐19 lockdowns from a geospatial perspective is essential. In light of nighttime light remote sensing, we evaluated the spatiotemporal dynamic effects of COVID‐19 city lockdowns on human activity intensity in the Zhengzhou region. Prior to the COVID‐19 outbreak, nighttime light in the Zhengzhou region maintained a significant growth trend, even under regular control measures. However, following the October 2022 COVID‐19 lockdown, nighttime light experienced a substantial decrease. In the central area of Zhengzhou, nighttime light decreased by at least 18% compared to pre‐lockdown levels, while in the sub‐center, the decrease was around 14%. The areas where nighttime light decreased the most in the central region were primarily within a 15 km radius, while in the sub‐center, the decrease was concentrated within a 5 km radius. These changes in both statistical data and nighttime light underscored the significant impact of the COVID‐19 lockdown on economic activities in the Zhengzhou region.

Short Communication: Genetic diversity and identification of unique Omicron variant markers of SARS-CoV-2 in Indonesia

Abstract. Suardana IBK, Mahardika BK, Santosa AAANA, Mahardika GN. 2024. Short Communication: Genetic diversity and identification of unique Omicron variant markers of SARS-CoV-2 in Indonesia. Biodiversitas 25: 1781-1787. The rapid and global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused enormous socioeconomic disruptions, such as local and global travel, country or city lockdown, and manymore. We tested the hypothesis that global introduction and local substitution markers that are unique to Indonesia due to the global travel restrictions could be identified. All complete and high-coverage genomes of all Omicron variant sequences submitted from Indonesia were downloaded from the Global Initiative on Sharing All Influenza Data (GISAID), in October 27, 2022, and aligned with the Wuhan-Hu-1 strain and randomly selected Nextstrain Omicron clades. Genetic diversity was calculated using Tajima’s neutrality test, and phylogeny was constructed using the neighbour-joining method in Mega 11. The overall whole genome diversity of the Omicron variant detected in Indonesia is 0.0008, with the three highest coding region diversities being Open Reading Frame 6 (ORF6), Envelope, and Spike protein. The Tajima D value of the whole genome is -2.669, while the three highest Tajima values are ORF6, Envelope and ORF10. The phylogeny shows that there are 168 sequences of Indonesian Omicron variants, which do not share branches with Nextstrain Omicron clades. Unique amino acid substitutions to Wuhan-Hu-1 of the Omicron variants detected in Indonesia occurred in some coding regions, mainly in ORF1AB and Spike. We encourage country-based analysis as a lesson for future pandemic events.

A traffic-induced shift of ultrafine particle sources under COVID-19 soft lockdown in a subtropical urban area

During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics. The soft lockdown era, marked by a 20–27% dip in overall traffic yet a surprising surge in early morning motorcycle activity, presented a natural experiment. We observed a consequential shift in the urban aerosol regime: the decrease in primary emissions from traffic substantially amplified the role of aged particles and secondary aerosols. This shift was particularly pronounced under stagnant atmospheric conditions, where reduced dilution exacerbated the influence of alternative emission sources, notably solvent evaporation, and was further accentuated with the resumption of normal traffic flows. A distinct seasonal trend emerged as warmer months approached, with aromatic VOCs such as toluene, ethylbenzene, and xylene not only increasing but also significantly contributing to more frequent particle growth events. These findings spotlight the criticality of targeted strategies at traffic hotspots, especially during periods susceptible to weak atmospheric dilution, to curb UFP and precursor emissions effectively. As we stand at the cusp of widespread vehicle electrification, this study underscores the imperative of a holistic approach to urban air quality management, embracing the complexities of primary emission reductions and the resultant shifts in atmospheric chemistry.

Economic Development after Covid

The identification of Covid cases in China marked the beginning of a global crisis. The virus was first discovered in early 2020, leading to the lockdown of Wuhan city. Subsequently, it spread to India and the rest of the world, causing significant changes in the global economy. This article highlights various economic developments that have occurred during the Covid period, including the growth of the internet, advancements in the medical field, improvements in the IT sector, increased online transactions, enhanced family interactions, and improved healthcare for the people. However, it is important to acknowledge that the outbreak of the Covid-19 pandemic is a tragic event unfolding worldwide, reminiscent of the Spanish flu outbreak in 1918-19. Given the considerable uncertainty surrounding the economic outlook and the associated risks, quantifying the economic impact is challenging. Any unforeseen increase in uncertainty can jeopardize both economic growth and financial stability. In light of this, economists at the International Monetary Fund emphasize the need for targeted economic policies, fiscal measures, and appropriate monetary and financial stability policies to strengthen the global economy.

The game of lies by stock investors in social media: a study based on city lockdowns in China

The potential hypotheses for finance research based on social media sentiment revolve around the reliability of investor sentiment expressed on social media and the causal relationship between financial markets and this sentiment. The central hypothesis we focus on is derived from the "lie game" played by investors on social media. This study is the first to explore three states of this lie game in the context of the Chinese stock market: the "equilibrium state", the "confusion state", and the "subversion state". Our findings indicate that the "equilibrium" state is the typical state of the lie game, where increased investor sentiment results in more positive market behavior, and higher stock prices lead to increased investor sentiment. We also examine the effect of significant social events, such as the "lockdown in Wuhan" and the "lockdown in Shanghai", on the lie game's outcome. The successful lockdown in Wuhan and the public's opposition to the politicization of COVID-19 reinforced the "equilibrium" state of the game. However, the Shanghai lockdown's failure to promptly halt the spread of COVID-19 led to the intertwining of the economy and COVID-19 in public discourse, shifting the lie game's outcome from an "equilibrium state" to a "subversive state". We emphasize that the "confusion state" and "subversion state" outcomes of the lie game are concerning, and managing public opinion and the externalization of domestic conflicts can help reduce this risk. This study offers a fresh perspective on the traditional issues of investor sentiment reliability and the causal relationship between investor sentiment and stock markets.

The dynamics of community resilience perception between two waves of COVID-19 in 2020 and 2022: A longitudinal study from Shanghai

This study aims to compare and analyze how perception of community resilience in Shanghai changed between two periods of city lockdown, one imposed from January to March 2020 and the other April to June 2022 and the key factors affecting such change. The Communities Advancing Resilience Toolkit Assessment (CART) Survey was used in the study. Multiple linear regression analysis shows that: (1) In 2022, when the pandemic impact was more severe and lockdown measures stricter compared to 2020, the perceived level of community resilience was lower. (2) During the two periods of lockdown, community engagement had a consistent impact on the perception of community resilience. In 2022, formal support provided by local organizations and institutions and residents' participation in affiliated volunteer groups had a significantly positive influence on the perception of community resilience. (3) During the wave of infection in 2022, factors such as the convenience of government-provided emergency services and the adequacy of emergency supplies had a significant positive impact on the perception of community resilience. (4) Whether an individual was COVID-19 positive or a close contact had a significant negative impact on community resilience. An individual's income level had no significant impact on the perception of community resilience.

Unveiling the influence of transparency in risk communication: Shifting from information disclosure to uncertainty reduction

While the importance of government transparency is extensively discussed in risk communication literature, its practical application in risk contexts presents intricate challenges. This study introduces a redefined concept of transparency in the context of risk, covering two dimensions: information disclosure and uncertainty reduction. To investigate the impact of transparency, ranging from mere information disclosure to significant uncertainty reduction, a hierarchical multiple regression model is employed. Specifically, trust in government serves as a benchmark for information disclosure, while indicators for information disclosure strategies and public vulnerability are incorporated into the model as proxies for uncertainty reduction. The proposed model undergoes validation in a city lockdown scenario in China using self-report data from 435 college students, with anxiety serving as a benchmark for transparency outcomes. The findings suggest that indicators of uncertainty reduction (information disclosure strategies, individual vulnerability) exert much larger effects on anxiety than mere information disclosure (indicated by government trust). This implies that government transparency should prioritize uncertainty reduction, involving diverse strategies and addressing public vulnerabilities.

Certification of stroke centers at primary hospitals and the improvement of thrombolysis n South China during 2020-2022.

IVT use declined globally in 2020 due to the Corona Virus Disease 2019 (COVID-19) pandemic, but it increased in South China. This study was conducted to evaluate the association of establishing Stroke Prevention Centers (SPCs) at primary hospitals with IVT increase in South China. We conducted a longitudinal observational study across 336 hospitals in 114 areas in South China during 2020-2022. Data regarding certified stroke centers, IVT volumes, and IVT rates were collected. Correlations between IVT rates and the number or density of stroke centers were accessed. IVT use was compared among areas with different levels of stroke centers or on different certification process. During 2020-2022, there were 83, 125, and 152 stroke centers, with 26, 65, and 92 SPCs, respectively. IVT therapies were 12,795, 17,266, and 20,411, representing a 29.8% increase/year (all p < 0.001). IVT rates increased from 7.2% in 2020 to 8.8% and 10.4% in 2021 and 2022, demonstrating a 22.2% increase/year (all p < 0.001). IVT rates correlated with the number and density of SPCs (all p < 0.05). IVT rates were higher in areas equipped with SPCs than in those without stroke centers (all p < 0.05). IVT rates consistently increased during the SPC certification process from 1 year before through the certification and subsequent maintenance (both p < 0.05). Well-organised SPCs and IVT therapy demonstrated substantial increase during the 3-year period. Certification of SPCs at primary hospitals is associated with improved IVT therapy in South China even with city lockdown during COVID-19 pandemic.

Anthropogenic Drivers of Hourly Air Pollutant Change in an Urban Environment during 2019–2021—A Case Study in Wuhan

Wuhan experienced a noticeable enhancement in air quality from January to April 2020 due to the epidemic lockdown. The improvement was a combined result of anthropogenic emission reduction and meteorological variability. Environmental policymakers are often concerned about the impact of industrial production and human activities on improvements in environmental sustainability. This study split and quantified the impact of anthropogenic emissions on the pollution level changes of six major air pollutants (CO, SO2, NO2, O3, PM10, and PM2.5) for the first half year of 2019 to 2021 in Wuhan with an improved meteorological normalization algorithm. The results show sharp decreases in anthropogenic pollutant loads during 2020, except for O3, with the ranking of NO2 &gt; PM10 &gt; SO2 &gt; CO &gt; PM2.5. The decrease in NO2 emissions caused by humans was more than 50% compared to 2019. The low NO2 led to a decrease in O3 consumption, resulting in high O3 concentrations from February to April 2020 during the city lockdown. Moreover, except O3, the impact of anthropogenic and weather influences on air pollution exhibited opposing effects; that is, meteorology tended to aggravate pollution, while human intervention was conducive to improving air quality, and human factors played the dominant role. Of all six pollutants, O3 is the one that is relatively least subject to anthropogenic emissions. Although concentrations of SO2, NO2, PM10, and PM2.5 rebounded in 2021, none of them were able to return to their pre-lockdown levels, suggesting the epidemic’s continuous inhibition of people’s activities. Compared with 2019 and 2021, the atmospheric oxidation capacity and secondary aerosol formation showed an overall decreasing trend during 2020. This study provides a reference for assessing the effectiveness of anthropogenic emission reduction policies.

The emergence and successful elimination of SARS-CoV-2 dominant strains with increasing epidemic potential in Taiwan’s 2021 outbreak

Taiwan’s experience with severe acute respiratory syndrome coronavirus (SARS-CoV) in 2003 guided its development of strategies to defend against SARS-CoV-2 in 2020, which enabled the successful control of Coronavirus disease 2019 (COVID-19) cases from 2020 through March 2021. However, in late-April 2021, the imported Alpha variant began to cause COVID-19 outbreaks at an exceptional rate in Taiwan. In this study, we aimed to determine what epidemiological conditions enabled the SARS-CoV-2 Alpha variant strains to become dominant and decline later during a surge in the outbreak. In conjunction with contact-tracing investigations, we used our bioinformatics software, CoVConvert and IniCoV, to analyze whole-genome sequences of 101 Taiwan Alpha strains. Univariate and multivariable regression analyses revealed the epidemiological factors associated with viral dominance. Univariate analysis showed the dominant Alpha strains were preferentially selected in the surge’s epicenter (p = 0.0024) through intensive human-to-human contact and maintained their dominance for 1.5 months until the Zero-COVID Policy was implemented. Multivariable regression found that the epidemic periods (p = 0.007) and epicenter (p = 0.001) were two significant factors associated with the dominant virus strains spread in the community. These dominant virus strains emerged at the outbreak’s epicenter with frequent human-to-human contact and low vaccination coverage. The Level 3 Restrictions and Zero-COVID policy successfully controlled the outbreak in the community without city lockdowns. Our integrated method can identify the epidemiological conditions for emerging dominant virus with increasing epidemiological potential and support decision makers in rapidly containing outbreaks using public health measures that target fast-spreading virus strains.

The Korean Wave during the coronavirus pandemic: an analysis of social media activities in Indonesia

ABSTRACT This paper investigates the temporal dynamic of Korean Wave (also known as Hallyu) as an online entertainment consumption and emotions experienced in the first five-month period during the pandemic. The COVID-19 pandemic has caused cities across the globe to regulate restrictions of social distancing and mobility. Previous studies suggest that city lockdowns may lead to public health problems due to restriction on human interaction. This study aims to examine the changing pattern of online entertainment consumption and how it was impacted by consumers during the COVID-19 pandemic. This paper uses Google’s trend data to examine the dynamics of search terms and Natural language processing (NLP) model using twitter’s text data to analyse cultural consumption and emotional analysis. The study reveals an increasing trend in search terms related to the Korean Wave during the lockdown. Simultaneously, the text analysis of tweets showed that positive experiences occurred three-fold compared to negative experiences, suggesting happiness and joy were received with the cultural consumption. The study highlights the possibility of employing user-generated data, such as that of Google and Twitter, as an alternative source to understand the behaviour and wellbeing of the urban population for both urban and media studies.

Characterizing load profile-based enterprise profiling under COVID-19 lockdown policy: A provincial case in China

The COVID-19 epidemic has led to devastating consequences worldwide due to strict social distancing measures, travel bans, city lockdowns, and other activity restrictions. Numerous lessons have been accumulated by various industries or sectors in the process of coping with COVID-19. In our paper, the actual electricity consumption of 1.145 million enterprises in a province of China is investigated in the normal period, the breakout period, and the recovery period. An artificial intelligence based enterprise profiling model is established to characterize power consumption profile geographically, temporally, and industrially. The recovery rate of enterprise power consumption is proposed as a key indicator representing the status of production resumption. Under lockdown measures, enterprise in different regions or sectors exhibits diversified responses in power consumption, the unsupervised learning model and the correlated coefficient extract the abstract characteristics and labels from various enterprise power profile. Ultimately, enterprises with similar electricity consumption characteristics are grouped and labeled to provide customized power services. Accurate enterprise profiling can effectively aid in facing with the challenges of insufficient orders, tight capital chains, and rising costs caused by the epidemic.

Do city lockdowns effectively reduce air pollution?

Severe air pollution remains a problem in developing countries such as India and China owing to unfavourable winter climate conditions that encourage the diffusion of air pollutants. Although city lockdowns can alleviate serious air pollution, they incur significant social costs. This study explored the effect of China's COVID-19 lockdown on air pollution. Machine learning was utilised to eliminate weather-related fluctuations in air pollutant concentrations, and two difference-in-difference models were employed to estimate the effects of general epidemic prevention and enhancement measures on air pollution and evaluate the total impact of city lockdown on air pollutant concentrations. By carefully examining the proportion of these effects in the overall impact, this study analysed the cost-effectiveness of city-level lockdown measures on air pollution. Results indicate that city lockdowns significantly reduced the concentrations of five air pollutants: NO2 (−28.3 %), PM10 (−21.41 %), PM2.5 (−15.83 %), CO (−8.66 %), and SO2 (−4.2 %). The contributions of the enhancement measures are 41.82 % for PM2.5, 42.66 % for PM10, −4.04 % for CO, and 31.83 % for NO2. This suggests that city lockdowns may not be cost-effective compared to general epidemic prevention measures. Thus, this study recommends limited city lockdown measures for severe air pollution, similar to the general epidemic prevention measures.

Research on the Impact of COVID-19 on Futures Market

This paper focuses on the specific impacts of COVID-19 on the performance and trading conditions of various global futures markets. The major impact of COVID-19 on the economy includes the raised concern of market stress, city lockdowns and travel restrictions. These factors can negatively affect the performance of future markets in different ways and to different degrees. This paper will explore the topics of the interconnectedness of several commodity futures performances, the volatility and return of major commodity futures, the relationship between various contemporary financial indicators and the performance of crude oil future, as well as the general performance of innovative future types. The study has found that the interconnected linkages between several commodity futures appeared under COVID pandemics. Furthermore, the study shows that COVID-19 has a considerable influence on both the short-term and long-term volatilities of industry-related and consumer staple-related futures to different degrees. Lastly, the coronavirus crisis has an overwhelmingly negative impact on the prices of innovative forms of the future, including the carbon future and Bitcoin future.

Wearable Biosensor with Molecularly Imprinted Conductive Polymer Structure to Detect Lentivirus in Aerosol.

The coronavirus disease (COVID-19) pandemic has increased pressure to develop low-cost, compact, user-friendly, and ubiquitous virus sensors for monitoring infection outbreaks in communities and preventing economic damage resulting from city lockdowns. As proof of concept, we developed a wearable paper-based virus sensor based on a molecular imprinting technique, using a conductive polyaniline (PANI) polymer to detect the lentivirus as a test sample. This sensor detected the lentivirus with a 4181 TU/mL detection limit in liquid and 0.33% to 2.90% detection efficiency in aerosols at distances ranging from 30 cm to 60 cm. For fabrication, a mixture of a PANI monomer solution and virus were polymerized together to form a conductive PANI sensing element on a polyethylene terephthalate (PET) paper substrate. The sensing element exhibited formation of virus recognition sites after the removal of the virus via ultrasound sonication. A dry measurement technique was established that showed aerosol virus detection by the molecularly imprinted sensors within 1.5 h of virus spraying. This was based on the mechanism via which dispensing virus droplets on the PANI sensing element induced hybridization of the virus and molecularly imprinted virus recognition templates in PANI, influencing the conductivity of the PANI film upon drying. Interestingly, the paper-based virus sensor was easily integrated with a wearable face mask for the detection of viruses in aerosols. Since the paper sensor with molecular imprinting of virus recognition sites showed excellent stability in dry conditions for long periods of time, unlike biological reagents, this wearable biosensor will offer an alternative approach to monitoring virus infections in communities.

The impact of COVID-19 lockdown on the variation of sea surface chlorophyll-a in Bohai Sea, China

To prevent the pandemic of COVID-19, Chinese government implemented restrict city lockdown policy, which directly changed human daily habitats and customs, and further influence environment. Using the GOCI-derived sea surface chlorophyll-a Level-2 products, the impacts of city lockdown policy on sea surface chlorophyll-a in the coastal regions of Bohai Sea were evaluated by difference-in-differences (DiD) model. To improve the spatiotemporal coverage of the remote sensing data, data interpolating empirical orthogonal functions were employed to reconstruct the sea surface chlorophyll-a data. The results of DiD model showed that the city lockdown policy will contribute to a significant increment (with the range 1.12–1.14 mg/m3) of sea surface chlorophyll-a within 15 km from the coastline; meanwhile, the impact strength weakens with the distance to coastline increases. Applying the DiD model for the cities with human development index larger than 0.77, the inference is more prominent and significant with the increment (1.15–1.29 mg/m3) of sea surface chlorophyll-a; while non-significant increment of sea surface chlorophyll-a was detected for the cities with a human development index smaller than 0.77. The detected 15 km delimiter can be regarded as a guidance for environmental manager to make sampling strategies.