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Nat Commun ; 12(1): 3841, 2021 06 22.
Article in English | MEDLINE | ID: covidwho-1279878


Aviation is an important contributor to the global economy, satisfying society's mobility needs. It contributes to climate change through CO2 and non-CO2 effects, including contrail-cirrus and ozone formation. There is currently significant interest in policies, regulations and research aiming to reduce aviation's climate impact. Here we model the effect of these measures on global warming and perform a bottom-up analysis of potential technical improvements, challenging the assumptions of the targets for the sector with a number of scenarios up to 2100. We show that although the emissions targets for aviation are in line with the overall goals of the Paris Agreement, there is a high likelihood that the climate impact of aviation will not meet these goals. Our assessment includes feasible technological advancements and the availability of sustainable aviation fuels. This conclusion is robust for several COVID-19 recovery scenarios, including changes in travel behaviour.

Aviation/statistics & numerical data , COVID-19/epidemiology , Climate Change , Global Warming , Vehicle Emissions/toxicity , Air Pollution/adverse effects , COVID-19/transmission , COVID-19/virology , Carbon Dioxide/chemistry , Humans , Ozone/chemistry , Paris , SARS-CoV-2/isolation & purification
Disaster Med Public Health Prep ; 14(5): e19-e23, 2020 10.
Article in English | MEDLINE | ID: covidwho-851031


OBJECTIVE: The effectiveness of air traffic restriction in containing the spread of infectious diseases is full of controversy in prior literature. In January 2020, the Civil Aviation Administration of China (CAAC) announced air traffic restriction in response to the coronavirus disease (COVID-19) pandemic. This study's aim is to empirically examine the policy effectiveness. METHOD: The data from 2 third-party platforms are used in this investigation. The COVID-19 data from the platform DXY and the air traffic data from Airsavvi are matched to each other. The robust panel regression with controlling city effect and time effect is conducted. RESULTS: The curvilinear relations are found between the air traffic restriction and the existing cases, and the recovery rate (quadratic term = 9.006 and -0.967, respectively). As the strength of air traffic restriction is growing, the negative effect (-8.146) of air traffic restriction on the existing cases and the positive effect (0.961) of air traffic restriction on the recovery rate, respectively, begin decreasing. CONCLUSION: On the macro level, the air traffic restriction may help alleviate the growth of existing cases and help raise the recovery rate of COVID-19 in megacities of China, but both these effects will marginally recede as the restriction strength is intensifying.

Aviation/standards , COVID-19/prevention & control , Pandemics/prevention & control , Air Pollutants/adverse effects , Air Pollutants/supply & distribution , Aviation/methods , Aviation/statistics & numerical data , COVID-19/epidemiology , China/epidemiology , Cities/statistics & numerical data , Humans , Pandemics/statistics & numerical data
Int J Environ Res Public Health ; 17(10)2020 05 12.
Article in English | MEDLINE | ID: covidwho-245076


Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic.

Air Travel , Aviation/statistics & numerical data , Coronavirus Infections/epidemiology , Coronavirus , Pandemics , Pneumonia, Viral/epidemiology , Betacoronavirus , COVID-19 , Coronavirus Infections/transmission , Global Health , Humans , Pneumonia, Viral/transmission , Risk Assessment , SARS-CoV-2 , Spatial Analysis , Uncertainty