ORCID Profile
0000-0002-2241-5894
Current Organisation
University of Greenwich
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Publisher: MDPI AG
Date: 09-06-2022
DOI: 10.3390/SU14127075
Abstract: This research studies the data on air quality and construction activities from 29 January 2020 to 30 April 2020. The analysis focuses on three s le districts of Hangzhou’s Xiacheng, Gongshu, and Xiaoshan districts. The s les, respectively, represent low-level, mid-level, and high-level districts in the scale of construction projects. The correlative relationships are investigated, respectively, in the periods of ‘pandemic lockdown (29 January 2020–20 February 2020)’ and ‘after pandemic lockdown (21 February 2020–30 April 2020)’. The correlative equations are obtained. Based on the guideline values of air parameters provided by the Chinese criteria and standards, the recommended maximum scales of construction projects are defined. The numbers of construction sites are 16, 118, and 311 for the Xiacheng, Gongshu, and Xiaoshan districts during the imposed lockdown period, respectively, and 19, 88, 234, respectively, after the lockdown period. Because the construction site is only one influential factor on the air quality, and the database is not large enough, there are some limitations in the mathematical model and the management plan. Possible problem solving techniques and future studies are introduced at the end of the research study.
Publisher: MDPI AG
Date: 12-05-2021
DOI: 10.3390/SU13105395
Abstract: The COVID-19 pandemic has spread rapidly all over the world, affecting many countries to varying degrees. In this study, an in-depth analysis of the factors influencing the spread of COVID-19 is offered mainly through big data in the European Union (EU) context. In doing so, the data of the first wave of the pandemic are assessed. Afterward, we evaluate the impacts of the COVID-19 spread in specific countries and regions. Based on the existing literature, mobility is recognized as a significant direct factor affecting disease transmission. The same applies to the case of COVID-19. However, compared with the analysis of mobility itself, this paper explores more profound reasons that affect mobility, ranging from policy and economy to geographical and transportation factors. Specifically, this paper studies nine EU countries based on their population density and the degree of impact of the epidemic in the first six months (February to July 2020) of the pandemic. Our study aims to illustrate how policies, economies, and geographical locations (including transportation factors) directly or indirectly affect the spread of the novel coronavirus by applying the SEIR model to analyze all selected countries’ big data. The key findings of this research are: (1) the timeliness of relevant policies and the effectiveness of government implementation indirectly limit the spread of the epidemic by reducing population mobility (2) a better medical level would contribute to detect, isolate, and treat patients, and help control the epidemic and (3) the large land borders and developed transportation between countries exacerbate the spread of the COVID-19. The paper contributes to ongoing research on COVID-19 by addressing the above points.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Ayotunde Dawodu.