We propose a methodology to add new technologies into Environmentally Extended Input-Output (EEIO) models based on a Supply and Use framework. The methodology provides for adding new industries (new technologies) and a new commodity under the assumption that the new commodity will partially substitute for a functionally-similar existing commodity of the baseline economy. The level of substitution is controlled by a percentage (%) as a variable of the model. In the Use table, a percentage of the current use of the existing commodity is transferred to the new commodity. The Supply or Make table is modified assuming that the new industries are the only ones producing the new commodity. We illustrate the method for the USEEIO model, for the addition of second generation biofuels, including naphtha, jet fuel and diesel fuel. The new industries' inputs, outputs and value-added components needed to produce the new commodity are drawn from process-based life cycle inventories (LCIs). Process-based LCI inputs and outputs per physical functional unit are transformed to prices and assigned to commodities and environmental flow categories for the EEIO model. This methodology is designed to evaluate the environmental impacts of substituting products in the current US economy with bio-versions, produced by new technologies, that are intended to reduce negative environmental impacts. However, it can be applied for any new commodity for which the substitution assumption is reasonable.
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http://dx.doi.org/10.3390/app12147016 | DOI Listing |
Front Public Health
September 2024
Faculty of Medicine and Health, Central Clinical School, Heart Research Institute, The University of Sydney, Newtown, NSW, Australia.
Healthcare is a major generator of greenhouse gases, so consideration of this contribution to climate change needs to be quantified in ways that can inform models of care. Given the availability of activity-based financial data, environmentally-extended input-output (EEIO) analysis can be employed to calculate systemic carbon footprints for healthcare activities, allowing comparison of different patient care pathways. We thus quantified and compared the carbon footprint of two common care pathways for patients with stable coronary artery disease, with similar clinical outcomes: coronary stenting and coronary artery bypass surgery (CABG).
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
April 2024
Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, Chongqing University, Chongqing, 400045, China.
Increased global attention is being paid to the food-health-climate trilemma. In this study, we evaluate the climate impacts of Mexico's food consumption patterns by creating a high-resolution (262 sectors) Environmentally Extended Input-Output (EEIO) model called MXEEIO. We focus on the differences between food away from home (FAFH) and food at home (FAH) and compare Mexico's results with those of the USA.
View Article and Find Full Text PDFClim Dyn
October 2023
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK.
Unlabelled: The interannual variability of the Equatorial Eastern Indian Ocean (EEIO) is highly relevant for the climate anomalies on adjacent continents and affects global teleconnection patterns. Yet, this is an area where seasonal forecasting systems exhibit large errors. Here we investigate the reasons for these errors in the ECMWF seasonal forecasting system SEAS5 using tailored diagnostics and a series of numerical experiments.
View Article and Find Full Text PDFAppl Sci (Basel)
July 2022
US Environmental Protection Agency, Center for Environmental Solutions and Emergency Response, Cincinnati, OH 45268, USA.
We propose a methodology to add new technologies into Environmentally Extended Input-Output (EEIO) models based on a Supply and Use framework. The methodology provides for adding new industries (new technologies) and a new commodity under the assumption that the new commodity will partially substitute for a functionally-similar existing commodity of the baseline economy. The level of substitution is controlled by a percentage (%) as a variable of the model.
View Article and Find Full Text PDFInt J Environ Res Public Health
June 2022
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Eco-efficiency analysis can provide useful information about sustainability in the tourism industry, which has an important role in both global economy recovery and Sustainable Development Goals (SDGs), generating considerable indirect carbon emissions with respect to the supply chain due to its significant connections to other industries. This study, from the perspective of tourism sectors, including tourism hotels, travel agencies, and scenic spots, integrated the environmentally extended input-output analysis (EEIO) and data envelopment analysis (DEA) models to develop a research framework, analyzing the indirect carbon emissions of the tourism supply chain, evaluating eco-efficiency with respect to both direct carbon emissions and total carbon emissions (including direct and indirect parts), and exploring the driving factors of eco-efficiency of tourism sectors using Tobit regression models. This study took Gansu as a case, a province in China characterized by higher carbon intensity, an underdeveloped economy, and rapid tourism growth.
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