Dataset Information

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021.

ABSTRACT: As an underdeveloped region, the aviation industry in Africa is developing rapidly, and its carbon emissions play an essential role in achieving carbon neutrality in the aviation industry in underdeveloped areas. However, the problem of carbon transfer caused by passenger flow on international routes has not been addressed, especially in Africa. This paper first calculates the CO₂ emissions of African international routes from 2019 to 2021 based on the Modified Fuel Percentage Method (MFPM) and the ICAO standard methods. Then, we measure African routes' carbon transfer and carbon compensation. The most carbon transfer routes between African countries and from countries outside Africa to African countries are from Ethiopia to Kenya and from Honduras to Ghana. Relatively poor countries bear a significant amount of carbon transfer.

SUBMITTER: Cui Q

PROVIDER: S-EPMC10198027 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021.

Cui Qiang Q Chen Bin B

Scientific data 20230519 1

As an underdeveloped region, the aviation industry in Africa is developing rapidly, and its carbon emissions play an essential role in achieving carbon neutrality in the aviation industry in underdeveloped areas. However, the problem of carbon transfer caused by passenger flow on international routes has not been addressed, especially in Africa. This paper first calculates the CO<sub>2</sub> emissions of African international routes from 2019 to 2021 based on the Modified Fuel Percentage Method ...[more]

PMID: 37208402

Similar Datasets

Project description:PurposeThe objectives of the International epidemiology databases to evaluate AIDS (IeDEA) are to (i) evaluate the delivery of combination antiretroviral therapy (ART) in children, adolescents and adults in sub-Saharan Africa, (ii) to describe ART regimen effectiveness, durability and tolerability, (iii) to examine HIV-related comorbidities and coinfections and (iv) to examine the pregnancy-related and HIV-related outcomes of women on ART and their infants exposed to HIV or ART in utero or via breast milk.ParticipantsIeDEA is organised in four regions (Central, East, Southern and West Africa), with 240 treatment and care sites, six data centres at African, European and US universities, and almost 1.4 million children, adolescents and adult people living with HIV (PLWHIV) enrolled.Findings to dateThe data include socio-demographic characteristics, clinical outcomes, opportunistic events, treatment regimens, clinic visits and laboratory measurements. They have been used to analyse outcomes in PLWHIV-1 or PLWHIV-2 who initiate ART, including determinants of mortality, of switching to second-line and third-line ART, drug resistance, loss to follow-up and the immunological and virological response to different ART regimens. Programme-level estimates of mortality have been corrected for loss to follow-up. We examined the impact of coinfection with hepatitis B and C, and the epidemiology of different cancers and of (multidrug resistant) tuberculosis, renal disease and of mental illness. The adoption of 'Treat All', making ART available to all PLWHIV regardless of CD4+ cell count or clinical stage was another important research topic.Future plansIeDEA has formulated several research priorities for the 'Treat All' era in sub-Saharan Africa. It recently obtained funding to set up sentinel sites where additional data are prospectively collected on cardiometabolic risks factors as well as mental health and liver diseases, and is planning to create a drug resistance database.

Project description:Yellow fever is a vector-borne disease endemic in tropical regions of Africa, where 90% of the global burden occurs, and Latin America. It is notoriously under-reported with uncertainty arising from a complex transmission cycle including a sylvatic reservoir and non-specific symptom set. Resulting estimates of burden, particularly in Africa, are highly uncertain. We examine two established models of yellow fever transmission within a Bayesian model averaging framework in order to assess the relative evidence for each model's assumptions and to highlight possible data gaps. Our models assume contrasting scenarios of the yellow fever transmission cycle in Africa. The first takes the force of infection in each province to be static across the observation period; this is synonymous with a constant infection pressure from the sylvatic reservoir. The second model assumes the majority of transmission results from the urban cycle; in this case, the force of infection is dynamic and defined through a fixed value of R0 in each province. Both models are coupled to a generalised linear model of yellow fever occurrence which uses environmental covariates to allow us to estimate transmission intensity in areas where data is sparse. We compare these contrasting descriptions of transmission through a Bayesian framework and trans-dimensional Markov chain Monte Carlo sampling in order to assess each model's evidence given the range of uncertainty in parameter values. The resulting estimates allow us to produce Bayesian model averaged predictions of yellow fever burden across the African endemic region. We find strong support for the static force of infection model which suggests a higher proportion of yellow fever transmission occurs as a result of infection from an external source such as the sylvatic reservoir. However, the model comparison highlights key data gaps in serological surveys across the African endemic region. As such, conclusions concerning the most prevalent transmission routes for yellow fever will be limited by the sparsity of data which is particularly evident in the areas with highest predicted transmission intensity. Our model and estimation approach provides a robust framework for model comparison and predicting yellow fever burden in Africa. However, key data gaps increase uncertainty surrounding estimates of model parameters and evidence. As more mathematical models are developed to address new research questions, it is increasingly important to compare them with established modelling approaches to highlight uncertainty in structures and data.

Dataset Information

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021.

Publications

Aviation carbon transfer and compensation of international routes in Africa from 2019 to 2021.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets