Introduction: All economic sectors including the service sector, along with healthcare, education and research, need to reduce their greenhouse gas emissions to limit global temperature increases. In this study, we aim to globally assess the awareness and current actions taken by Academic Research Institutions (ARIs) or governments regarding the reduction of carbon dioxide equivalent (COe) emissions for clinical research.
Methods: We designed a cross-sectional survey-based study, which was distributed within the International Clinical Trials Center Network (ICN). The survey population comprised representatives of the ICN who had extensive experience in academic clinical research and profound knowledge and understanding of the local context.
Results: The response rate was 80%. Responding ARIs were from 15 different countries and 4 continents. Around half of the ARIs reported that almost none of their research projects considered reducing their carbon footprint. The other half of the ARIs were not familiar with this subject at all. According to 60% of the respondents, greenhouse gas emissions are not assessed by Institutional Review Boards (IRBs)/Ethics Committees (ECs) or competent authorities, while 40% did not know. Neither IRBs/ECs nor competent authorities currently advise sponsors and investigators on reducing the carbon footprint of their clinical research projects. As for reducing greenhouse gas emissions in clinical research, virtual conferences and meetings were the most commonly implemented measures by ARIs across all regions. Finally, we have put together an action plan/checklist advising researchers on carbon footprint reduction for clinical trials.
Conclusion: Currently, greenhouse gas emissions are neglected during the planning phase of a research project, and they are not yet addressed or assessed by default during the approval procedures by IRBs/ECs or competent authorities. Thus, all involved stakeholders within clinical research need to be made aware of it through advice from ARIs and IRBs/ECs, among others.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10510862 | PMC |
http://dx.doi.org/10.1136/bmjgh-2023-012754 | DOI Listing |
This study intends to optimize the carbon footprint management model of power enterprises through artificial intelligence (AI) technology to help the scientific formulation of carbon emission reduction strategies. Firstly, a carbon footprint calculation model based on big data and AI is established, and then machine learning algorithm is used to deeply mine the carbon emission data of power enterprises to identify the main influencing factors and emission reduction opportunities. Finally, the driver-state-response (DSR) model is used to evaluate the carbon audit of the power industry and comprehensively analyze the effect of carbon emission reduction.
View Article and Find Full Text PDFHeliyon
November 2024
Department of Civil Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, 10140, Thailand.
This study introduces an innovative approach to enhancing recycled aggregate concrete (RAC) by incorporating nanosilica (NS) and natural fibers (NF), specifically sisal fiber (SF) and palm fiber (PF). This novel combination aims to overcome the inherent limitations of RAC, such as reduced strength and durability, while promoting sustainability in construction. The research focuses on evaluating the mechanical properties of RAC, including compressive and flexural strengths, through the integration of NS and NF.
View Article and Find Full Text PDFGut Liver
January 2025
Department of Internal Medicine, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul, Korea.
Background/aims: Although gastrointestinal endoscopy (GIE) is a major contributor to the carbon footprint of national healthcare, the amount of medical waste generated by GIE procedures is not reported in South Korea. This study aimed to measure the amount of medical waste generated from GIE procedures in South Korea.
Methods: We conducted a 5-day audit of medical waste generated during GIEs at seven hospitals.
Sci Rep
January 2025
College of Forestry, Guizhou University, Guiyang, 550025, Guizhou, China.
Evaluating and predicting how carbon storage (CS) is impacted by land use change can enable optimizing of future spatial layouts and coordinate land use and ecosystem services. This paper explores the changes in and driving factors of Zunyi CS from 2000 to 2020, predicts the changes in CS under different development scenarios, and determines the optimal development scenario. Woodland and farmland are the main land use types in Zunyi.
View Article and Find Full Text PDFNat Commun
January 2025
School of Biotechnology and Key Laboratory of Industrial Biotechnology of Ministry of Education, Jiangnan University, Wuxi, China.
Photosynthesis harvests solar energy to convert CO into chemicals, offering a potential solution to reduce atmospheric CO. However, integrating photosynthesis into non-photosynthetic microbes to utilize one-carbon substrates is challenging. Here, a photosynthesis system is reconstructed in E.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!