This study expands the original two-dimensional carbon footprint model into a three-dimensional model form. Introduce two indicators of carbon footprint depth (CF) and size (CF) to form a three-dimensional carbon footprint model (CF), which is used to respectively represent the occupation and consumption of natural capital reserves by human activities' carbon emissions. Based on the 3D carbon footprint model, this paper calculated the CF, CF, and CF for four different urban agglomerations of China (BTH, YRD, PRD, and CY) spanning from 2000 to 2017. Building on this, the study analyzed the spatial-temporal and dynamic characteristics of the multivariate collaboration between CF, CF, and GDP using a multivariate collaborative relationship model. The research findings reveal that (1) from 2000 to 2017, the utilization of natural capital stock in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Chengyu (CY) urban agglomerations were in an unsustainable development state, with their CF exceeding 1. Among these regions, the degree of natural capital consumption was PRD > BTH > YRD > CY. (2) There manifests an obvious regional complementary characteristic of CF and CF. Regions coupled with abundant land resources (such as Chengde and Hangzhou) tend to have high CF and low CF, whereas area with fewer land resources (such as Tianjin and Shanghai) exhibits the opposite pattern. (3) In four urban agglomerations, the relationship of temporal multivariate collaboration among CF, CF, and GDP exhibits a declining trend from 2000 to 2017, with an average value ranging from 0.4 to 0.6. The change in their multivariate spatial collaboration was not pronounced throughout the course of the study.
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http://dx.doi.org/10.1007/s10661-025-13660-z | DOI Listing |
Environ Monit Assess
January 2025
College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, 350000, China.
This study expands the original two-dimensional carbon footprint model into a three-dimensional model form. Introduce two indicators of carbon footprint depth (CF) and size (CF) to form a three-dimensional carbon footprint model (CF), which is used to respectively represent the occupation and consumption of natural capital reserves by human activities' carbon emissions. Based on the 3D carbon footprint model, this paper calculated the CF, CF, and CF for four different urban agglomerations of China (BTH, YRD, PRD, and CY) spanning from 2000 to 2017.
View Article and Find Full Text PDFFront Psychol
January 2025
i-FOOD Team, IIA-FoodUPV, Universitat Politècnica de València, Valencia, Spain.
Introduction: Due to the current climatic situation of the planet and the increase in concern for the environment, the Universitat Politècnica de València (UPV) aims to be a model for the university community in terms of the preservation of the ecosystem and prevention of the environmental impact caused by daily tasks; thus, aligning itself with the goals of the 2030 Agenda. For this reason, a project has been launched to carry out the green transformation of the UPV toward a university that prioritizes sustainability in all its areas.
Methods: As part of this project, a survey was conducted using anonymous online questionnaires for the student population and employees.
Front Transplant
January 2025
Department of Surgical, Medical, Biomolecular Pathology and Intensive Care, University of Pisa, Pisa, Italy.
Background And Aims: There is growing interest in the environmental impact of surgical procedures, yet more information is needed specifically regarding liver transplantation. This study aims to quantify the total greenhouse gas emissions, or carbon footprint, associated with adult whole-size liver transplantation from donors after brain death, including the relevant back-table graft preparation.
Methods: The carbon footprint was calculated retrospectively using a bottom-up approach.
Heliyon
January 2025
Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, 100083, China.
In the context of carbon neutrality, the oil and gas industry is facing increasingly stringent environmental regulatory pressures, posing severe challenges to enterprise sustainability development. This study proposes a new comprehensive calculation model to investigate the effects of low-carbon transformation and development of petrochemical enterprises in recent years. It can effectively quantify the relative efficiency of different samples in the same time interval and the efficiency change of a single sample in the time series.
View Article and Find Full Text PDFMar Pollut Bull
January 2025
University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Ivana Lučića 5, 10002 Zagreb, Croatia.
Seaborn trade has a share of about 80 % in global supply chains and is responsible for approximately 10 % of global carbon emissions. This is why the environmental impact of ships and the shipbuilding process matter. Despite that, this topic is addressed rather sparsely in the present literature body.
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