ABSTRACT
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.
ABSTRACT
In 2021, the airline industry was affected by COVID-19, and many airlines suffered losses. The main reason for the loss were the decline in revenue and the surge in costs. Therefore, in terms of creating the competitive advantage of airlines, "price war" is no longer applicable, and improving service quality has become an effective means. Customer satisfaction is the most effective indicator to measure service quality. In this study, a satisfaction evaluation system is established based on structural equation model and customer satisfaction importance matrix. Then, a questionnaire is designed to analyze the influence of different factors on customer satisfaction. The research finds that brand image and perceived quality have a great impact on customer satisfaction. In addition, some suggestions for airlines to improve customer satisfaction are given. © 2023 SPIE.
ABSTRACT
The rise of breathlessness is directly linked to COVID-19, to climate change due to air quality from pollution and to anxious experience. This chapter's phenomenology of breathlessness and anxiety show on the one hand how insidious yet more and more prevalent these experiences are becoming, regardless of the specific disease and more of an expression of climate change. On the other hand, the rise of COVID-19 poses a particular threat quite apart from the fact it is a consequence of the way that we treat nature. This is because it is spread through close personal contact with other humans, specifically through inspiration of their breath. The threat posed by this new disease means that our very way of being with others will be altered profoundly. Studies show that breathlessness from COVID-19 is worsened by climate change as areas of high pollution put more and more people at risk. This pandemic shows our fundamental reliance on the Earth, writ large. The dire consequences of humanity's damaging treatment of the planet are a stark reminder of this. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
ABSTRACT
The impact of air pollutants on human health is a major issue that developing nations are facing in last decade. Effect of particulate matter especially PM2.5 and PM10 has been severely affecting mortality and morbidity in Rajasthan state as per global lead medical journal Lancet recent publication. Twelve air pollutant-monitoring sta tions in Jaipur city are not enough to predict the exact concentration of air pollutants in each of the 91 wards of Jaipur. In absence of accurate concentration at micro level, it becomes a major challenge for urban planners to remedial strategies. In this paper through GIS spatial distribution, a comparative study of particulate matter at each of the 91 wards during pre-lockdown for the year 2019 and post-lockdown 2020 was done. Results for 2020 showed slightly less pollution;similarly, air purity index, an indicator for healthier environment, was determined for each ward. © 2023 Scientific Publishers. All rights reserved.
ABSTRACT
The European Air Transportation Network was significantly impacted by the COVID-19 pandemic, resulting in an unprecedented loss of flight connections. Utilizing a combination of graph representation learning and time series analysis, this paper studies the evolution of both the global connectivity as well as the structure of the European Air Transportation Network from January 2020 to December 2022. Specifically, it finds strong differences in recovery rates for flights across six different market segments. In terms of network structure, the study finds that structural roles that are present in the pre-covid network have seen a loss in performance over the course of the pandemic, but have recovered to pre-covid levels. Using regional changes in structural roles, this study identifies Italy as the region with the strongest increase and the United Kingdom as the region with the strongest decrease in structural role, finding substantial differences in recovery rates per market segment. Lastly, this study pays special attention on the effect of the Russia-Ukrainian war on the European Air Transportation Network. © 2023 IEEE.
ABSTRACT
Central Asian cities are one of the hotspots for air pollution worldwide. There are limited studies and knowledge regarding air quality variation in this region. This study investigated PM2.5 temporal variations and the influence of meteorological parameters on PM2.5 concentrations for six major cities in Central Asia: Almaty and Astana (Kazakhstan), Ashgabat (Turkmenistan), Bishkek (Kyrgyzstan), Dushanbe (Tajikistan), and Tashkent (Uzbekistan). The results show severe air quality deterioration in the cities with annual PM2.5 concentrations up to ten-fold higher than the limits. A clear seasonal pattern with winter peaks was observed in Almaty, Bishkek, and Astana, whereas winter and summer were highly polluted in Tashkent and Dushanbe. Based on the pollution profiles, cities were classified into several clusters. Episodes with high PM2.5 concentrations were evaluated for regional pollutant transportation using the HYSPLIT model. The results of this investigation highlight a significant discrepancy in official emissions inventory studies. While previous studies have suggested that transportation is the primary source of air pollution, the approach to estimate the share of emission sources was based on an outdated methodology that obscures information on the most hazardous pollutants, including PM2.5. This study shows that coal combustion is the primary source of PM2.5 pollution in most cities, offering policymakers critical insights into the sources of air pollution in the region. These findings demonstrate the need for policymakers to take swift action to address coal use and adopt effective measures to mitigate PM2.5 pollution, thereby improving the health and well-being of the population.
ABSTRACT
In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.
ABSTRACT
PurposeThe COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.Design/methodology/approachThe current study identifies the focus areas of the research conducted on the COVID-19 pandemic. s of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.FindingsBased on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.Originality/valueWhile similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.
ABSTRACT
PM2.5 was continuously collected in Ho Chi Minh City (HCMC), Vietnam, during the period from September 2019 to August 2020, which included the period of socioeconomic suppression caused by restrictions imposed in the face of the coronavirus disease of 2019. The concentrations of PM2.5 mass, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were determined to evaluate the seasonal variations in PM2.5, the effect of socioeconomic suppression on PM2.5, and potential PM2.5 sources in HCMC. The PM2.5 mass concentration during the sampling period was 28.44 +/- 11.55 mu g m(-3) (average +/- standard deviation). OC, EC, and total WSIs accounted for 30.7 +/- 6.6%, 9.7 +/- 2.9%, and 24.9 +/- 6.6% of the PM2.5 mass, respectively. WSOC contributed 46.4 +/- 10.1% to OC mass. NO3-, SO42-, and NH4+ were the dominant species in WSIs (72.7 +/- 17.7% of the total WSIs' mass). The concentrations of PM2.5 mass and total WSIs during the rainy season were lower than those during the dry season, whereas the concentrations of carbonaceous species during the rainy season were higher. The concentrations of PM2.5 mass and chemical species during the socioeconomic suppression period significantly decreased by 45%-61% compared to the values before this period. The OC/EC ratio (3.28 +/- 0.61) and char-EC/soot-EC (4.88 +/- 2.72) suggested that biomass burning, coal combustion, vehicle emissions, cooking activities are major PM2.5 sources in HCMC. Furthermore, the results of a concentration-weighted trajectory analysis suggested that the geological sources of PM2.5 were in the local areas of HCMC and the northeast provinces of Vietnam (where coal-fired power plants are located).
ABSTRACT
Despite an increased emphasis on improvement in airline service quality concerning consumer behavior, such as passenger repurchasing as a result of their behavioral intention over the last several decades, there is still much less concern with the nature of airline service quality than should exist in the so-called "logistics service quality” and less concern with examining the specific behavioral intention preceding repurchasing behavior together with the theory of planned behavior. As such, this study aims to explore these issues, along with the psychological factors of the theory of planned behavior, that can lead to repurchasing behavior via word-of-mouth intention (WOMI). With an online survey of 383 respondents experienced with flying, the results reveal that the logistics service quality and each determinant in the theory positively influence a passenger's repurchasing behavior through WOMI. Accordingly, service marketers can implement service design and apply integrated marketing communication by learning from repurchasing behavior that was formed by the given factors to retain their existing customers. Moreover, this study is the first to empirically and explicitly validate dimensions of airline services through the lens of logistics that are deemed fit with the nature of the airlines. It advances the understanding of theory approaching and connects what has hampered its advancement in a body of knowledge, simultaneously in a context of airline context where it should not be relegated to transportation and consumer and service orientation.
ABSTRACT
We analysed the impact of the number of air routes on international tourism arrivals, using a dynamic panel data model to control for endogeneity. The analysis considers China's tourist arrivals before COVID-19, from its seventeen main source countries. The results show a significant positive effect of international air routes on arrivals. Beyond the overall effect, we differentiate long-haul and short-haul routes, and incorporate potential non-linearities. The conclusion is that air routes have a positive decreasing effect on inbound tourism demand from long-haul markets, but they are not significant for short-haul markets. Given the current post-pandemic challenges, understanding the effect of air routes on tourism demand might be incorporated into destination management strategies.
ABSTRACT
Housing quality and affordability are well established as social determinants of health through direct and indirect mechanisms. Respiratory illnesses related to housing are nearly all the result of housing disrepair that allows intrusion into the home of environmental agents that are directly or indirectly associated with disease. Structural deficiencies such as leaks, cracks in the foundation or holes in the home's exterior can facilitate the presence of mould, which is causally linked to the development of asthma and is associated with exacerbation of asthma symptoms in children and adults. Indoor cleanliness can also contribute to the presence of mice and cockroaches. Proper ventilation can improve air quality, reducing exposure to PM, VOCs and infectious respiratory agents. Disparities in exposure to the housing conditions associated with respiratory disease are readily apparent across socioeconomic lines. Low-income families are less likely to be able to afford the costs of maintaining a home, which prevents them from making repairs that could improve respiratory health.Copyright © ERS 2023.
ABSTRACT
Low quality of the air is becoming a major concern in urban areas. High values of particulate matter (PM) concentrations and various pollutants may be very dangerous for human health and the global environment. The challenge to overcome the problem with the air quality includes efforts to improve healthy air not only by reducing emissions, but also by modifying the urban morphology to reduce the exposure of the population to air pollution. The aim of this contribution is to analyse the influence of the green zones on air quality mitigation through sensor measurements, and to identify the correlation with the meteorological factors. Actually, the objective focuses on identifying the most significant correlation between PM2.5 and PM10 concentrations and the wind speed, as well as a negative correlation between the PM concentrations and wind speed across different measurement locations. Additionally, the estimation of slight correlation between the PM concentrations and the real feel temperature is detected, while insignificant correlations are found between the PM concentrations and the actual temperature, pressure, and humidity. In this paper the effect of the pandemic restriction rules COVID-19 lockdowns and the period without restriction are investigated. The sensor data collected before the pandemic (summer months in 2018), during the global pandemic (summer months 2020), and after the period with restriction measures (2022) are analysed.
ABSTRACT
In recent years, the concentration levels of various air pollutants have been constantly increasing, primarily due to the high vehicle flow. In 2020, however, severe lockdowns in Greece were imposed to reduce the spread of the COVID-19 pandemic, which led to a rapid reduction in the concentration levels of air pollutants such as PM2.5 and PM10 in the atmosphere. Initially, this paper seeks to identify the correlation between the concentration levels of PM10 and the traffic flow by acquiring data from low-cost IoT devices which were placed in Thessaloniki, Greece, from March to August 2020. The correlation and the linearity between the two parameters were further investigated by applying descriptive analytics, regression techniques, Pearson correlation, and independent T-testing. The obtained results indicate that the concentration levels of PM10 are strongly correlated to the vehicle flow. Therefore, the results hint that the decrease in the vehicle flow could result in improving the quality of environmental air. Finally, the acquired results point out that the temperature and humidity are weakly correlated with the concentration levels of PM10 present in the atmosphere.
ABSTRACT
African aviation has witnessed steady growth pre-COVID and as result of increased demand for air travel, there is an urgent need to improve the air transport infrastructure. This chapter examines the underlining complexities and challenges that are undermining the African region's propensity to exploit its growth trajectory. The chapter explores multiple differences in regional airport infrastructure. Infrastructure is considered a key component of the investment climate, reducing costs of doing business and enabling people to access markets. In general, Africa, by every measure of infrastructure coverage, lags behind their peers in other parts of the developing world. Poor infrastructure of most African airports is seen as a principal reason why the region continues to struggle to fulfil its undoubtedly economic potential. These infrastructure problems can hardly be solved due to limited financial resources and will therefore consequently lead to retaining infrastructure problems. The chapter proposes a series of blueprint measures in order to galvanize Africa's growth potential within air transport development. This calls for speeding up privatization and allowing more private equity investments to support air infrastructure improvements. The most desired option to finance airport infrastructure would be the Public–Private Partnership (PP). However, on the local level, banks have relative weak capital coffers, which also limit access to infrastructure capital loans. Investors see some underlining risks in financing airport projects in Africa, namely uncertainty related to forecasts of passenger growth numbers. Other risks are embedded in currency markets, whereby most domestic airport infrastructure with project revenues is generated in local currencies, but servicing foreign debt and equity involves payment in foreign currency. The chapter finally examines the impact of COVID-19 on airport operations. From 2019 to 2021, airports were severely affected by the global pandemic causing massive loss of revenues for both airport operators and airlines. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Air pollution in India is a serious health issue. A countrywide lockdown was imposed in India in response to the COVID-19 pandemic, firstly for three weeks starting from March 24 to April 14, 2020, and then extended until May 3, 2020. Because of the restrictions imposed, pollution levels in cities all over the country have dropped dramatically in just a few days, raised questions among scientists about lockdown as the most effective alternative approach for reducing air pollution. Hyderabad was chosen for this study because it is India's 5th largest city by area and 4th largest city by population, as well as major industrial centre in South-East Asia with strong air quality statistics. In light of the recent COVID-19 outbreak around the country, a detailed analysis based on air quality parameters from six distinct air quality monitoring sites in Hyderabad, Telangana, has been performed. For simple interpretation of air quality data, establishing a correlation between different pollutants, identifying sources of pollution, and determining the most significant parameters, different multivariate statistical approaches such as Cluster analysis (CA), Principle component analysis (PCA), correlation analysis, and multiple linear regression analysis (MLR) were used. The aim of this study is to evaluate the major air pollution sources in Hyderabad and to identify the most significant air pollutants based on their individual contributions to the Air Quality Index (AQI). Variation in air quality parameters collected for six air quality monitoring stations were represented using box or whisker plots. The data set has been grouped into four major clusters depending on the similarities in the air quality data. Major sources of air pollution in each cluster were identified using PCA. MLR analysis was used to create models for predicting AQI for each cluster based on concentrations of important air contaminants. The findings revealed that PM10 and PM2.5 play a significant role in determining AQI levels. © 2023 Author(s).
ABSTRACT
COVID-19 pandemic has resulted in a halt to the daily lifestyle of people around the world and bound them to abide by the lockdown measures enforced to prevent the disease from further spreading. In India also, lockdown has been enforced from March 2020. As a result, the level of air pollutants in the atmosphere goes on decreasing. To know the air quality pattern of Bangalore city, ten stations around the city were selected. Air quality data of these stations has been availed from the Central Pollution Control Board (CPCB) of India website. Box chart concept of graphical representation has been applied to show the range of temporal variation of the air pollutants selected (CO, NO2, Ozone, PM2.5, PM10 and SO2) for the study area over two distinct periods (pre-lockdown and post-lockdown). It has been observed that all the pollutants level were drastically or significantly reduced except for SO2 which showed mixed behavior during the entire study period probably due to no restriction on the operation of power plants. GIS based contour mapping is done for each pollutant over the entire study area and separately for two distinct periods (pre-lockdown and post-lockdown). It was found that, change in CO level over the entire study area was significant and the reason behind it was complete restriction on vehicular movement which is the primary reason for CO emission in atmosphere. Reduction in PMs and ozone was also noticeable, but change in SO2 over the entire study area was almost insignificant. To find out the probable sources of pollution during the lockdown and before the lockdown period and the most significant parameters statistical approach has been adopted. The whole data set has been grouped based on similarity and divided into three distinct clusters for both pre-lockdown and post-lockdown period separately using Hierarchical Agglomerative Cluster Analysis (HACA) concept. Principal Component Analysis (PCA) was done for each of the clusters and each time period considered. From the results of PCA it can be confirmed that the most significant parameters were PM10, PM2.5, ozone and SO2. Results suggest that the probable sources of pollution during pre-lockdown period were vehicular emissions, power plants, industrial activities etc. In contrast, during post-lockdown period the sources of pollution were power plants, construction sites and household pollution only. MLR (Multiple Linear Regression) models were developed to predict Air Quality Index (AQI). Most of the models showed good fit with adjusted R2 value more than 0.9. Regression coefficient (R2) values for PM10 followed PM2.5 were highest in each cluster. © 2023 Author(s).
ABSTRACT
The novel coronavirus (COVID-19) outbreak has impacted the aviation industry worldwide. Several restrictions and regulations have been implemented to prevent the virus's spread and maintain airport operations. To recover the trustworthiness of air travelers in the new normality, improving airport service quality (ASQ) is necessary, ultimately increasing passenger satisfaction in airports. This research focuses on the relationship between passenger satisfaction and the ASQ dimensions of airports in Thailand. A three-stage analysis model was conducted by integrating structural equation modeling, Bayesian networks, and artificial neural networks to identify critical ASQ dimensions that highly impact overall satisfaction. The findings reveal that airport facilities, wayfinding, and security are three dominant dimensions influencing overall passenger satisfaction. This insight could help airport managers and operators recover passenger satisfaction, increase trustworthiness, and maintain the efficiency of the airports in not only this severe crisis but also in the new normality.
ABSTRACT
This study outlines the stress factors and the impact of the COVID-19 pandemic on the stress variables among aviation workers, which includes airline employees, flight crews, pilots, maintenance crews, air traffic controllers, airport or ground workers, engineers, training personnel, and other aviation-related personnel. A review was done on 37 research papers using systematic literature review (SLR) and discovered nine stress factors among aviation workers which are working hours, workloads, internal factors, ergonomic issues, job uncertainty, job demands, organizational issues, team conflict, and the COVID-19 itself. The findings of this study could provide insights to employers in the aviation industry for mitigation actions that could help to successfully reduce and eliminate stress factors in the workplace. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.