Statistical Analysis of Air Quality by Emission of Different Woods: Facing the Threats of Global Pandemic with Healthcare 4.0

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Madhulika Singh ◽  
Komal Singh ◽  
Luv Dhamija ◽  
Mayank Sharma ◽  
Priyanshi Garg ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Air Quality ◽  
Global Pandemic

scholarly journals A Quantitative Study on Statistical Associations between Extroversion-Introversion Personality Traits and Anxiety in Different Stages of Lockdown during the Covid-19 Pandemic

2021 ◽  
Vol 04 (12) ◽  
Author(s):  
Podchara Soemphornwiwat ◽  
Keyword(s):  
High School ◽  
High School Students ◽  
Statistical Analysis ◽  
The Other ◽  
School Students ◽  
Significance Level ◽  
Statistical Correlations ◽  
Global Pandemic ◽  
State Of Mind ◽  
The Given

The Covid-19 pandemic has caused several changes in the human state of mind, in particular adapting to the culture of the new normal while lockdown measures are implemented. This study explored the effect of the lockdown measure on the level of anxiety of high school students, comparing those identified as introverts and extroverts. Participants (N = 103) filled out the given survey, which determined that they were both introverts or extroverts and the level of anxiety that they had before, during, and after the lockdown caused by the pandemic. According to statistical analysis, the result showed that the level of anxiety perceived by those feeling the sense of extroversion was statistically higher than those with introversion, at the significance level of 95%. In addition, the analysis revealed that there was no correlation between extroverts and anxiety before, during, and after the lockdown measures. On the other hand, there were statistical correlations between the level of introversion and the level of anxiety in every stage of lockdown: before, during and after, indicating that the lockdowns due to the global pandemic did not affect extroverted people anxiety as much as it affected introverts. Moreover, it also showed that the level of anxiety of the introverts has become even more intensified even after the lockdown.

Nursing Homes in Spain and Their High Number of Deaths by COVID-19 as an Alarm in the Study of Indoor Air Quality

2021 ◽  
pp. 118-145
Author(s):  
Gastón Sanglier Contreras ◽  
Jose Amílcar Rizzo Sierra ◽  
Eduardo José López Fernández ◽  
Roberto Alonso González Lezcano
Keyword(s):  
Energy Efficiency ◽  
Statistical Analysis ◽  
Air Quality ◽  
Nursing Homes ◽  
Population Density ◽  
Indoor Air Quality ◽  
Autonomous Communities ◽  
La Mancha ◽  
Number Of Factors ◽  
Determining Factor

Nursing homes have been one of the most prominent targets of the COVID-19 coronavirus in Spain. The factors that have determined that this is the case are very diverse. In this study, physical agents and chemical pollutants, population density, and different capacities of the residences are analyzed to see their influence on the number of elderly people who have died in the geriatric centres in the different autonomous communities (AACC) of Spain. A statistical analysis has been carried out on the variables observed. The conclusions show that in many places where this overflow of deaths has occurred, the residences were private, with some exceptions. The influence of physical agents and pollutants has been shown to be a determining factor, especially for the communities of Extremadura and Castilla-La Mancha, although it is true that the large number of factors makes the study complicated. The dilemma between air quality and energy efficiency is of great importance, especially when human health is at stake.

scholarly journals Impact on Air Quality of the COVID-19 Lockdown in the Urban Area of Palermo (Italy)

2020 ◽  
Vol 17 (20) ◽  
pp. 7375 ◽  
Author(s):  
Marcello Vultaggio ◽  
Daniela Varrica ◽  
Maria Grazia Alaimo
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Area ◽  
Human Mobility ◽  
Infected People ◽  
National Crisis ◽  
Global Pandemic ◽  
Pm 10 ◽  
The Impact

At the end of 2019, the first cases of coronavirus disease (COVID-19) were reported in Wuhan, China. Thereafter, the number of infected people increased rapidly, and the outbreak turned into a national crisis, with infected individuals all over the country. The COVID-19 global pandemic produced extreme changes in human behavior that affected air quality. Human mobility and production activities decreased significantly, and many regions recorded significant reductions in air pollution. The goal of our investigation was to evaluate the impact of the COVID-19 lockdown on the concentrations of the main air pollutants in the urban area of Palermo (Italy). In this study, the trends in the average concentrations of CO, NO2, O3, and PM10 in the air from 1 January 2020 to 31 July 2020 were compared with the corresponding average values detected at the same monitoring stations in Palermo during the previous five years (2015–2019). During the lockdown period (10 March–30 April), we observed a decrease in the concentrations of CO, NO2, and particulate matter (PM)10, calculated to be about 51%, 50%, and 45%, respectively. This confirms that air pollution in an urban area is predominantly linked to vehicular traffic.

scholarly journals Comparing carbon dioxide levels within urban transport microenvironments during rush hour and non-rush traffic

2015 ◽  
Author(s):  
Ming Hei (Alan) Leung ◽  
BCIT School of Health Sciences, Environmental Health ◽  
Bobby Sidhu
Keyword(s):  
Carbon Dioxide ◽  
Statistical Analysis ◽  
Air Quality ◽  
Primary Objective ◽  
Urban Transport ◽  
P Value ◽  
Confined Spaces ◽  
Significant Difference ◽  
Carbon Dioxide Levels ◽  
American Society

  Introduction: Commuters spend countless hours within tightly confined spaces with limited ventilation that may be filled with many contaminants. By analyzing if there is a significant difference between levels of carbon dioxide between rush and non-rush hour conditions, it can be determined if some commuters are subjected to poorer levels of air quality during certain times of the day. Objectives: The primary objective of this study is to understand whether there are significant ventilation deficiencies during rush compared to non-rush hour times in urban transport microenvironments. Methods: Analysis of urban transport microenvironments was done using the TSI brand QTrak Indoor Air Quality (IAQ) Monitor to gather data on carbon dioxide at 1-minute intervals on the 99 B-line express bus that runs between Broadway and Commercial Skytrain Station and the Broadway and Cambie Street Skytrain Station. Results: A one tailed T-test was done on the NCSS 9 statistical software to compare if rush hour urban microenvironments had significantly higher concentrations of carbon dioxide than when compared to non-rush hour. Statistical analysis determined that since the P-value was well above the alpha level of 0.05 (i.e. P<0.05), it gives reason to accept the null hypothesis, which states that rush hour concentrations were not higher than non-rush hour. Conclusion: Statistical analysis determined that the overall concentrations of carbon dioxide during rush hour were not significantly higher than non-rush hour times. This result may have been attributed to conditions and factors during data collection that could not be controlled by the researcher. Due to the length of the route, exposure times were found to be within time-weighted averages as set out by the American Conference of Industrial Hygienists (ACGIH), though it was still not within the recommended limit of 1000 ppm as set out by the American Society of Heating, Refrigeration and Air-Conditioning (ASHRAE).  

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

2021 ◽  
Author(s):  
Md Mokhlesur Rahman ◽  
Kamal Chandra Paul ◽  
Md. Amjad Hossain ◽  
G. G. Md. Nawaz Ali ◽  
Md. Shahinoor Rahman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Urban Form ◽  
Human Mobility ◽  
Virus Transmission ◽  
Past Research ◽  
Policy Implications ◽  
Viral Spread ◽  
Global Pandemic ◽  
Review Study

The ongoing COVID-19 global pandemic is affecting every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and citywide implemented lockdown measures are affecting virus transmission, people&rsquo;s travel patterns, and air quality. Many studies have been conducted to predict the COVID-19 diffusion, assess the impacts of the pandemic on human mobility and air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This review study aims to analyze 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 transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel purposes 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 of the people. 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 discusses policy implications, which will be helpful for policymakers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

scholarly journals The effect of increasing indoor ventilation on artificially generated aerosol particle counts

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258382
Author(s):  
Ashwin Johri
Keyword(s):  
Air Quality ◽  
Aerosol Particle ◽  
Constant Temperature ◽  
Small Particle ◽  
Narrow Range ◽  
Effective Solution ◽  
Fixed Amount ◽  
Global Pandemic ◽  
Particle Counts ◽  
Indoor Aerosol

The COVID-19 global pandemic has caused millions of infections and deaths despite mitigation efforts that involve physical distancing, mask-wearing, avoiding indoor gatherings and increasing indoor ventilation. The purpose of this study was to compare ways to improve indoor ventilation and assess its effect on artificially generated aerosol counts. It was hypothesized that inbuilt kitchen vents would be more effective in reducing indoor aerosol counts than opening windows alone. A fixed amount of saline aerosol was dispersed in the experimental area using a nebulizer under constant temperature and a narrow range of humidity. A laser air quality monitor was used to record small particle counts every 30 minutes from baseline to 120 minutes for four different experimental groups for each combination of kitchen vents and windows. The results of the study demonstrate that aerosol counts were lowest with the kitchen exhaust vents on. This study suggests that liberal use of home exhaust systems like the kitchen vents could achieve significantly more air exchange than open windows alone and may present an effective solution to improving indoor ventilation, especially during the colder months when people tend to congregate indoors in closed spaces. There were no safety concerns involved when conducting this experiment.

Sign in / Sign up

Export Citation Format

Share Document