ABSTRACT
The COVID-19 pandemic has disrupted the 'real' world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 'new normal', we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making;second, the insights gained assist the networking community in better planning for the future. © 2023 the authors.
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
Transportation problems have always been a global concern. The challenges in traffic congestion were easily observed during pre-pandemic times. However, traffic congestion still persists even during the COVID-19 pandemic (2020 and present) where there has been less number of vehicles because of travel restrictions. The emergence of wireless communication technologies and intelligent transportation systems (ITS) pave the way for solving some of the problems found in the transportation industry. Subsequently, traffic control systems are used at various intersections to manage the flow of traffic and reduce car collisions. However, some intersections are better off without these traffic control systems. The proposed study will analyze a T-junction road in five different setups using different types of traffic controllers. The simulation tool used is SUMO. The study found that an adaptive or vehicle-actuated traffic controller is the ideal method for regulating traffic flow in a T-junction with a one-way or two-way main road. It was observed in the simulation that it reduced the potential car collisions in the non-TL junction. However, the average speed and completion time of the road network was affected by the method. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on travel behavior have also been sudden and wide ranging. This study describes the drastic changes in human behavior using the analysis of highway volume data as a representation of personal activity and interaction. Same-day traffic volumes for 2019 and 2020 across Florida were analyzed to identify spatial and temporal changes in behavior resulting from the disease or fear of it and statewide directives to limit person-to-person interaction. Compared to similar days in 2019, overall statewide traffic volume dropped by 47.5%. Although decreases were evident across the state, there were also differences between rural and urban areas and between highways and arterials both in terms of the timing and extent. The data and analyses help to demonstrate the early impacts of the pandemic and may be useful for operational and strategic planning of recovery efforts and for dealing with future pandemics.
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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.
ABSTRACT
This work is an analysis of the implications of the potential new regulatory policies being recently proposed in the European Union, in particular the mandatory blending of SAF (on top of the already existing CORSIA or ETS), to address aviation emissions from a technical, operational and economic perspective. As a continuation of previous work from the Department of Aerospace Systems, Air Transport and Airports from the ETSIAE (Universidad Politécnica de Madrid), the air traffic structure of the European Union in 2019 has been analysed based on publicly available data from EUROCONTROL and EUROSTAT. The output has been used as the reference scenario for the implementation of the mandatory blending of SAF, expected to take over at the beginning of 2025, since it is expected that by then, air traffic will reach the pre-COVID levels. The results show that all the policy options considered so far have uneven impact among the different stakeholders and that before deciding going forward with any of the presented options, extra work needs to be done to overcome the different challenges that would potentially arise. © 2022 ICAS. All Rights Reserved.
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We recently concluded a four-year University Leadership Initiative (ULI) project sponsored by NASA, which investigated multiple aviation communications technology areas aimed at enhancing future aviation safety. These areas were dual-band air-ground communications for air traffic management, detection and interdiction of small drones, and high-capacity terrestrial airport communications networking. In this paper we report on flight test results of our dual-band radios. These radios were designed to use a spectrally efficient multi-carrier modulation, filterbank multicarrier (FBMC), which we had previously shown to improve resilience to high-power distance measurement equipment (DME) adjacent-channel interference, in comparison to existing orthogonal frequency division multiplexing (OFDM) schemes. In our NASA project, we designed the FBMC radios to extend performance even further, using the following techniques: (i) simultaneous dual-band transmission and reception;(ii) ground station (GS) spatial diversity;(iii) higher-order modulation for a factor of 5 capacity increase over QPSK;(iv) a Doppler-resilient option using a smaller number of subcarriers;and, (v) 5-MHz bandwidth C-band transmissions for an order of magnitude capacity increase over existing 500-kHz channel schemes. To our knowledge, these are novel achievements for civil aviation, and our flight test results attained a technology readiness level (TRL) of 5. In this paper we briefly describe the project history, in which we spent approximately one year working with Boeing to participate in one of their Eco-Demonstrator flight trials, and obtained special temporary authorizations to transmit in both the L-band and C-band, from the FAA, the FCC, and the DoD. When COVID-19 dispersed worldwide, Boeing was no longer able to support us, so we revised our plans and teamed with the South Carolina Civil Air Patrol (SC CAP) to conduct smaller-scale flight tests. This paper summarizes the radio designs and the novel features we employed, as well as analyses, computer simulations, and laboratory tests prior to terrestrial mobile testing, all of which culminated in our successful flight tests. We show example flight test results that serve as proof of concept for all the five aforementioned radio performance enhancements. Example results include signal-to-noise ratio and bit error ratio, diversity gains, and throughput gains through both higher-order modulation and wider bandwidth channels. We also report on some lessons learned, and some ideas for future advancement of our work. © 2023 IEEE.
ABSTRACT
The COVID‐19 pandemic resulted in a widespread lockdown during the spring of 2020. Measurements collected on a light rail system in the Salt Lake Valley (SLV), combined with observations from the Utah Urban Carbon Dioxide Network observed a notable decrease in urban CO2 concentrations during the spring of 2020 relative to previous years. These decreases coincided with a ∼30% reduction in average traffic volume. CO2 measurements across the SLV were used within a Bayesian inverse model to spatially allocate anthropogenic emission reductions for the first COVID‐19 lockdown. The inverse model was first used to constrain anthropogenic emissions for the previous year (2019) to provide the best possible estimate of emissions for 2020, before accounting for emission reductions observed during the COVID‐19 lockdown. The posterior emissions for 2019 were then used as the prior emission estimate for the 2020 COVID‐19 lockdown analysis. Results from the inverse analysis suggest that the SLV observed a 20% decrease in afternoon CO2 emissions from March to April 2020 (−90.5 tC hr−1). The largest reductions in CO2 emissions were centered over the northern part of the valley (downtown Salt Lake City), near major roadways, and potentially at industrial point sources. These results demonstrate that CO2 monitoring networks can track reductions in CO2 emissions even in medium‐sized cities like Salt Lake City.Alternate :Plain Language SummaryHigh‐density measurements of CO2 were combined with a statistical model to estimate emission reductions across Salt Lake City during the COVID‐19 lockdown. Reduced traffic throughout the COVID‐19 lockdown was likely the primary driver behind lower CO2 emissions in Salt Lake City. There was also evidence that industrial‐based emission sources may of had an observable decrease in CO2 emissions during the lockdown. Finally, this analysis suggests that high‐density CO2 monitoring networks could be used to track progress toward decarbonization in the future.
ABSTRACT
Background: In March 2020, the world health organization declared COVID-19 a world wide pandemic. Countries introduced public health measures to contain and reduce its spread. The effect of mandated societal lockdown to reduce the transmission of corona virus disease 2019 (COVID-19) on road traffic accidents is not known. For this we performed an in-depth analysis singdata of emergency and trauma centre UPUMS, Saifai. As most of the manpower was involved in managing Covid patients directly or indirectly, it was a challenge to manage these mass casualty patients who require intensive care as well as Medicolegal documentation, record keeping, Consent for life saving procedures in absence of Relatives. Material(s) and Method(s): We reviewed data on total 2876 road traffic accident records in UPUMS, Saifai from January 1, 2020 through September 30, 2020. We treated March 20th as the first day of mandated societal lock down and 1st July as the first day of re-opening. Result(s): We have found that the reis increase in road traffic accidents resulting in serious or fatal injuries during lockdown and post-lockdown period. There was increased Medicolegal burden in spite of the decreased medical resources, manpower as most of manpower and resources were being utilized for covid patients. Conclusion(s): Road traffic accidents are a prominent contributor to hospitalization and may negatively impact the existing hospital resources directed towards COVID-19.Copyright © 2023, World Informations Syndicate. All rights reserved.
ABSTRACT
The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by∼10% because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions and even led to substantial increases in O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over the NCP, which contributed 90 % of the PM2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM2.5 emissions, were the main drivers of the unexpected PM2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.
ABSTRACT
SARS-CoV-2 is a pandemic that affects road traffic flaw and crashes globally. This study attempted to compare the situation of road traffic crashes in the city of Budapest before and after the SARS-CoV-2 pandemic to better understand its long-term percussive effects. The study considers 12208 road traffic crashes that registered between 20 May 2018 – 31 December 2021. The rate and severity of road traffic crashes during the SARS-CoV-2 pandemic examined by using a percentage frequency distribution and a severity index. This study depicted that most crashes reported during the normal daytime between15:01-18:00 (peak hour). The study indicated that during the SARS-CoV-2 pandemic the road traffic crashes were reduced by 20.15%. A rear-end collision was one of the most common type of catastrophes highly registered. Road users, particularly drivers, heavily endorsed crashes. Even though the proportion of road traffic crashes caused by alcohol consumption was modest (6%), the rate of alcohol consumption and its concentration increased slightly during the SARS-CoV-2 pandemic. At the same time the number of crashes caused by high-speed traffic maneuvers reduced. Improper interpretation of road traffic signs, road pavement condition and failure to respect proper sight distance were influential reasons of road traffic crashes among the top. Meanwhile, the distributional impact of careless driving in the aftermath of the SARS-CoV-2 pandemic causes a shift in rank. Therefore, this study proved that during SARS-CoV-2 pandemics road traffic crashes reduced, the rate and concentration of alcohol consumption increased, and careless driving was encouraged.
ABSTRACT
The global COVID-19 pandemic has had a great impact on transportation across the United States. However, there is a lack of studies investigating the pandemic's impact on vehicular traffic at the later stage of the pandemic. Therefore, this paper studies the change of freeway traffic patterns in two metropolitan counties in the State of Utah at the latter stage of the pandemic. We found that with the relaxation of travel restriction and the COVID vaccine, vehicular traffic has recovered to equaling, if not exceeding, pre-pandemic levels. Truck traffic is higher than the pre-pandemic level due to the growth of online shopping and on-demand delivery. To help responsive agencies to prepare for the near-future traffic pattern, a traffic prediction model based on an innovative approach integrating machine learning with graph theory is proposed. The evaluation shows that the proposed prediction model has a desirable performance. The mean absolute percentage prediction error is between 0.38% and 1.74% for different jurisdictions. On average, the modal outperforms the traditional long short-term memory model by 31.20% in terms of root mean squared prediction error.
ABSTRACT
The city of Christchurch, New Zealand, incurred significant damage due to a series of earthquakes in 2010 and 2011. The city had, by the late 2010s, regained economic and social normalcy after a sustained period of rebuilding and economic recovery. Through the concerted rebuilding effort, a modern central business district (CBD) with redesigned infrastructure and amenities was developed. The Christchurch rebuild was underpinned by a commitment of urban planners to an open and connected city, including the use of innovative technologies to gather, use and share data. As was the case elsewhere, the COVID-19 pandemic brought about significant disruptions to social and economic life in Christchurch. Border closures, lockdowns, trading limitations and other restrictions on movement led to changes in traditional consumer behaviors and affected the retail sector's resilience. In this study, we used CBD pedestrian traffic data gathered from various locations to predict changes in retail spending and identify recovery implications through the lens of retail resilience. We found that the COVID-19 pandemic and its related lockdowns have driven a substantive change in the behavioral patterns of city users. The implications for resilient retail, sustainable policy and further research are explored. © 2023 by the authors.
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This study develops a replicable urban toolkit for decision-makers to improve the quality of life in Cairo for residents and visitors affected by traffic noise. Our case study in Cairo was selected using the Aviation Design Environmental Tool (AEDT) used worldwide for airports. To simulate the COVID-19 era and days after, the noise contour mapping was performed using the Predictor-LimA software at eight receiver locations at six building heights with three assumptions of 100 %, 70 %, and 50 % traffic flow. The case study ends with lessons that can be used in regional planning, urban planning, and design to raise public awareness of noise effects in public spaces. Our analysis confirmed a deep relationship between traffic flow and noise, so controlling urban activities by reducing unnecessary uses is beneficial. We recommend that urban planners and designers incorporate noise prediction into outdoor environments' planning and design processes. (c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
ABSTRACT
The Song of the Cell tells the story of how we came to understand ourselves and other complex living organisms as mosaics of these atoms of life. There is the "dividing cell”, which takes us to the 2001 Nobel Prize in Physiology or Medicine that Nurse won, alongside Leland Hartwell and Tim Hunt, for elucidating the roles of cyclin and cyclin-dependent kinase proteins in regulating the cell cycle, and to the invention of reproductive in-vitro fertilisation by Patrick Steptoe and Robert Edwards during the 1970s. Quite what the "new human” of the subtitle refers to is never fully clear, but the ability to reprogramme cell states, as for example, in the method devised by stem-cell researcher Shinya Yamanaka to induce mature somatic cells back to pluripotency, might have the potential to grow organs in vitro, to regenerate tissues in vivo, and even to create synthetic embryo-like structures without the involvement of fertilisation. Mukherjee rightly admits that this view goes too far, but it might at least be understood as suggesting that trying to attack cancer at the genetic level is like hoping to stop traffic jams by fixing the faulty brakes of the car that caused the last one.
ABSTRACT
This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions.
ABSTRACT
Background: Perforating ocular injuries in particular carry a high risk of visual morbidity in all age groups. Risk factors associated with ocular trauma include gender, age, occupation, and lower socioeconomic status. Eye injuries are causing a major concern to the general ophthalmologists both in the developed and developing countries. Background: The objective of this article is to study the profile of penetrating ocular injuries before and during the period of lockdown. Materials and Methods: A study was done to make a comparative analysis of the penetrating ocular injuries occurring during the period of lockdown of 3 months (April 1, 2020-June 30, 2020) and 3 months (January 1, 2020-March 31, 2020) before lockdown. Results: The study included 33 patients hospitalized before lockdown and 45 hospitalizations during the lockdown in all age groups. Injuries were more common in males. The injuries reported in the age group of 0-15 years before lockdown were 36.36% while during lockdown 60% injuries were observed. Modes of injuries reported before lockdown were indoor injuries (36.36%) and road traffic accidents (36.36%) while during lockdown, the major mode of injuries were indoor injuries (76.6%) whereas the road traffic accidents (10.0%) declined. Conclusion: During the lockdown, indoor injuries were more common in comparison to the outdoor injuries such as road traffic accidents, the latter being more prevalent before lockdown. During lockdown, increase in the indoor leisure activities of children led to a rise in the cases of eye injuries and an increase of almost double the number was observed. In addition to this, immobilization led to a decrease in the injuries due to road traffic accidents. The coronavirus disease-19 lockdown did have an impact on the profile of penetrating ocular injuries.
ABSTRACT
COVID-19 continues to threaten the world. Relaxing local travel behaviours on preventing the spread of COVID-19, may increase the infection risk in subsequent waves of SARS-CoV-2 transmission. In this study, we analysed changes in the travel behaviour of different population groups (adult, child, student, elderly) during four pandemic waves in Hong Kong before January 2021, by 4-billion second-by-second smartcard records of subway. A significant continuous relaxation in human travel behaviour was observed during the four waves of SARS-CoV-2 transmission. Residents sharply reduced their local travel by 51.9%, 50.1%, 27.6%, and 20.5% from the first to fourth pandemic waves, respectively. The population flow in residential areas, workplaces, schools, shopping areas, amusement areas and border areas, decreased on average by 30.3%, 33.5%, 41.9%, 58.1%, 85.4% and 99.6%, respectively, during the pandemic weeks. We also found that many other cities around the world experienced a similar relaxation trend in local travel behaviour, by comparing traffic congestion data during the pandemic with data from the same period in 2019. The quantitative pandemic fatigue in local travel behaviour could help governments partially predicting personal protective behaviours, and thus to suggest more accurate interventions during subsequent waves, especially for highly infectious virus variants such as Omicron.
ABSTRACT
The excessive traffic congestion in vehicles lowers the service quality of urban bus system, reduces the social distance of bus passengers, and thus, increases the spread speed of epidemics, such as coronavirus disease. In the post-pandemic era, it is one of the main concerns for the transportation agency to provide a sustainable urban bus service to balance the travel convenience in accessibility and the travel safety in social distance for bus passengers, which essentially reduces the in-vehicle passenger congestion or smooths the boarding-alighting unbalance of passengers. Incorporating the route choice behavior of passengers, this paper proposes a sustainable service network design strategy by selecting one subset of the stops to maximize the total passenger-distance (person × kilometers) with exogenously given loading factor and stop-spacing level, which can be captured by constrained non-linear programming model. The loading factor directly determines the in-vehicle social distance, and the stop-spacing level can efficiently reduce the ridership with short journey distance. Therefore, the sustainable service network design can be used to help the government minimize the spread of the virus while guaranteeing the service quality of transport patterns in the post-pandemic era. A real-world case study is adopted to illustrate the validity of the proposed scheme and model.
ABSTRACT
The COVID-19 prevention and control measures are taken by China's government, especially traffic restrictions and production suspension, had spillover effects on air quality improvement. These effects differed among cities, but these differences have not been adequately studied. To provide more knowledge, we studied the air quality index (AQI) and five air pollutants (PM2.5, PM10, SO2, NO2, and O3) before and after the COVID-19 outbreak in Shanghai, Wuhan, and Tangshan. The pollution data from two types of monitoring stations (traffic and non-traffic stations) were separately compared and evaluated. We used monitoring data from the traffic stations to study the emission reduction caused by traffic restrictions. Based on monitoring data from the non-traffic stations, we established a difference-in-difference model to study the emission reduction caused by production suspension. The COVID-19 control measures reduced AQI and the concentrations of all pollutants except O3 (which increased greatly), but the magnitude of the changes differed among the three cities. The control measures improved air quality most in Wuhan, followed by Shanghai and then Tangshan. We investigated the reasons for these differences and found that differences in the characteristics of these three types of cities could explain these differences in spillover effects. Understanding these differences could provide some guidance and support for formulating differentiated air pollution control measures in different cities. For example, whole-process emission reduction technology should be adopted in cities with the concentrated distribution of continuous process enterprises, whereas vehicles that use cleaner energy and public transport should be vigorously promoted in cities with high traffic development level.