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

Shanableh, Abdallah; Al‐Ruzouq, Rami; Hamad, Khaled; Gibril, Mohamed Barakat A.; Khalil, Mohamad Ali; Khalifa, Inas; Traboulsi, Yahya El; Pradhan, Biswajeet; Jena, Ratiranjan; Alani, Sama; Alhosani, Mohamad; Stietiya, Mohammed Hashem; Bardan, Mayyada Al; Mansoori, Saeed Al

doi:10.1016/j.rsase.2022.100757

Cited by 8 publications

(5 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Significant reductions were also found with varying rates for respirable particulate matter (PM 10 ) (21-70%), CO (5.8-55%), and SO 2 (8.7-30%) in the same context. In Abu Dhabi in the United Arab Emirates (UAE), NO 2 had decreased up to 40%, while the SO 2 , CO, and C 6 H 6 had decreased by 12.2, 25.8, and 19.9%, respectively [31]. Similar findings were also found out in Egypt as well; it was found that AAI has decreased by 30% and NO 2 decreased by 15% and 30% over Cairo and Alexandria governorates, respectively [30].…”

Section: Introductionsupporting

confidence: 62%

Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage

et al. 2023

View full text Add to dashboard Cite

This study investigates the impact of the COVID-19 pandemic and the Ever Given ship blockage on the air quality in Suez Canal region. Nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and aerosol optical depth (AOD) were studied, and data were obtained from satellite instruments. The study compared monthly average data for 2020, 2021, and 2022 with a baseline period of 2017–2019 to investigate the pandemic’s effect. The study also analyzed the corresponding period of the canal blockage to identify its impact on air pollution levels. The pandemic had a significant role in decreasing NO2 by 2.5 × 1014 molecule/cm2 and SO2 by 0.05 DU due to reduced car traffic and industrial activities. A reduction in AOD by 20% and CO concentration in the range from 3.5% to 4.7% was reported in early 2020. During the blockage, NO2 and SO2 levels decreased by 14.4% and 66.0%, respectively, while CO and AOD index increased by 12.68% and 51.0%, respectively. The study concludes that the containment measures during the pandemic had a positive impact on the environment, which shows how the reduction in the anthropogenic activities, especially industrial and transportation activities, have improved the air quality. Thus, stricter actions are needed to protect the environment; for example, the transition towards the using of electric vehicle is necessary, which is part of Egypt’s strategy to transition towards a green economy. The government should also adopt a policy to trade carbon emissions reduction certificates to help reduce air pollution.

show abstract

Section: Introductionsupporting

confidence: 62%

Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage

et al. 2023

View full text Add to dashboard Cite

show abstract

“…ArCOV-19, an extensive Arabic COVID-19 Twitter dataset, chronicling one year from January 27, 2020 to January 31, 2021, and comprising a substantial repository of approximately 2.7 million tweets. We sampled the dataset for the months of March, April, May, and June of 2020, as this timeframe corresponds with the months of the COVID-19 lockdown [9], [10], [11], [12]. Our dataset began on March 11, when COVID-19 was considered a pandemic by the World Health Organization (WHO) [13].…”

Section: Methodology Dataset Collectionmentioning

confidence: 99%

Corpus Analysis of Coronavirus Disease-19 (COVID-19)-Related Loneliness in Twitter (Preprint)

Shurafa,

Zaghouani

2024

Preprint

View full text Add to dashboard Cite

BACKGROUND Loneliness is a complex mental health issue involving feelings of isolation, disconnectedness, and a lack of purpose in life. The coronavirus disease (COVID-19) pandemic and lockdowns significantly increased social isolation, contributing to a global rise in loneliness on social online platforms. However, research on mental health expressions in Arabic on social media is limited, exacerbating the lack of understanding of loneliness and mental health issues in these communities. Stigma and societal resistance in the Middle East hinder individuals from seeking mental health support, a trend which was particularly noticeable amidst the challenges of the pandemic. OBJECTIVE This study aimed to conduct a corpus analysis of an open-source dataset to gain insights into the origin of how loneliness was expressed in Arabic on Twitter during the initial months of COVID-19 regulations. Additionally, it explored temporal trends during the same time period to enhance comprehension of the prevalence of loneliness and mental health struggles during the initial months of the pandemic. METHODS Grounded in corpus linguistic methodology, the study also employs thematic analysis, explores temporal trends, and conducts Inter-Annotator Agreement (IAA) to comprehend the prevalence of loneliness and mental health struggles during the pandemic's early stages. RESULTS Our analysis of Twitter data using AntConc revealed crucial insights into the origins of mental health challenges and loneliness during the early days of the COVID-19 pandemic. Employing sophisticated linguistic techniques, we identified over 18,000 instances of loneliness-related terms, which deepened our understanding of the issue. Emotions were expressed through various themes, with a significant focus on COVID-19 news and opinions. The advanced search features of AntConc were instrumental in this process, allowing us to gauge word frequency and locate relevant tweets. The association between loneliness and the pandemic was clear, especially with the word "corona" being the most frequent collocate. Thematic analysis identified the seven key themes that were despair in the face of uncertainty, grief for the loss of life, hope through faith, opinions on COVID-19, opinions on isolation, COVID-19 news, and fear of illness which characterized the emotional landscape during this time. Inter-Annotator Agreement highlighted the diversity of interpretations. CONCLUSIONS Our study demonstrates the crucial role social media plays in capturing and understanding human emotions during major global events like the COVID-19 pandemic. Our AntConc analysis offers insights into mental health and loneliness during the early COVID-19 pandemic. It highlights the Arabic-speaking online community's experiences and contributes to global understanding of mental health and social media dynamics. This approach can be applied to different languages, enriching our understanding of loneliness and mental health during crises.

show abstract

“…Analysis of human mobility during lockdown (Lan et al, 2021;Shanableh et al, 2022;Shao et al, 2022), improved quality of agricultural ecosystems during lockdown as measured through UV-aerosol indices obtained from the Sentinel-5 Precursor satellite (Pokhariyal et al, 2021), and the impact of the lockdown has had a positive impact on the biosphere as it restricts development and exploitation activities (Bhandari et al, 2021), Evaluation of mapping green spaces and ventilation in urban areas as areas that can accelerate physical and mental healing during COVID-19 (Lu et al, 2022;Pouya & Aghlmand, 2022), tracing of cooling and ecological status of urban surfaces using landsat 8 imagery during lockdown (Firozjaei et al, 2021;Mijani et al, 2022), Providing prevention against COVID-19 virus infection through mapping areas with high infection rates (Annamalai et al, 2022).…”

Section: Figure 1 Bibliometric Keyword Analysis Graphmentioning

confidence: 99%

A Bibliometric Analysis: Remote Sensing Literature in Dimensions.ai Database

Azhari,

Iman Hilman,

Siti Fadjarajani

et al. 2022

SPATIAL

View full text Add to dashboard Cite

This research using bibliometric analysis aims to identify and visualize research developments in the field of remote sensing studies. The data is obtained from 2021-2022 through dimensions.ai with criteria for articles that have a digital object identifier (DOI). The data generated were 2645 articles which were then analyzed using the VosViewer device. The data analyzed includes the development of popular keywords, affiliations, countries and authors who do a lot of research in the field of remote sensing. The results of the study found 4 clusters with 216 items for keywords, 6 clusters and 36 items for authors, 15 clusters and 323 items for affiliation, 7 clusters and 61 items for country analysis which mostly conducted research on remote sensing.

show abstract

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

Cited by 8 publications

References 84 publications

Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage

Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage

Corpus Analysis of Coronavirus Disease-19 (COVID-19)-Related Loneliness in Twitter (Preprint)

A Bibliometric Analysis: Remote Sensing Literature in Dimensions.ai Database

Contact Info

Product

Resources

About