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BackgroundUniversities, as innovation drivers in science and technology worldwide, should be leading the Great Transformation towards a carbon–neutral society and many have indeed picked up the challenge. However, only a small number of universities worldwide are collecting and publishing their carbon footprints, and some of them have defined zero emission targets. Unfortunately, there is limited consistency between the reported carbon footprints (CFs) because of different analysis methods, different impact measures, and different target definitions by the respective universities.ResultsComprehensive CF data of 20 universities from around the globe were collected and analysed. Essential factors contributing to the university CF were identified. For the first time, CF data from universities were not only compared. The CF data were also evaluated, partly corrected, and augmented by missing contributions, to improve the consistency and comparability. The CF performance of each university in the respective year is thus homogenized, and measured by means of two metrics: CO2e emissions per capita and per m2 of constructed area. Both metrics vary by one order of magnitude across the different universities in this study. However, we identified ten universities reaching a per capita carbon footprint of lower than or close to 1.0 Mt (metric tons) CO2e/person and year (normalized by the number of people associated with the university), independent from the university’s size. In addition to the aforementioned two metrics, we suggested a new metric expressing the economic efficiency in terms of the CF per $ expenditures and year. We next aggregated the results for all three impact measures, arriving at an overall carbon performance for the respective universities, which we found to be independent of geographical latitude. Instead the per capita measure correlates with the national per capita CFs, and it reaches on average 23% of the national impacts per capita. The three top performing universities are located in Switzerland, Chile, and Germany.ConclusionThe usual reporting of CO2 emissions is categorized into Scopes 1–3 following the GHG Protocol Corporate Accounting Standard which makes comparison across universities challenging. In this study, we attempted to standardize the CF metrics, allowing us to objectively compare the CF at several universities. From this study, we observed that, almost 30 years after the Earth Summit in Rio de Janeiro (1992), the results are still limited. Only one zero emission university was identified, and hence, the transformation should speed up globally.

Recent attention has focused on the high rates of annual carbon sequestration in vegetated coastal ecosystems--marshes, mangroves, and seagrasses--that may be lost with habitat destruction ('conversion'). Relatively unappreciated, however, is that conversion of these coastal ecosystems also impacts very large pools of previously-sequestered carbon. Residing mostly in sediments, this 'blue carbon' can be released to the atmosphere when these ecosystems are converted or degraded. Here we provide the first global estimates of this impact and evaluate its economic implications. Combining the best available data on global area, land-use conversion rates, and near-surface carbon stocks in each of the three ecosystems, using an uncertainty-propagation approach, we estimate that 0.15-1.02 Pg (billion tons) of carbon dioxide are being released annually, several times higher than previous estimates that account only for lost sequestration. These emissions are equivalent to 3-19% of those from deforestation globally, and result in economic damages of $US 6-42 billion annually. The largest sources of uncertainty in these estimates stems from limited certitude in global area and rates of land-use conversion, but research is also needed on the fates of ecosystem carbon upon conversion. Currently, carbon emissions from the conversion of vegetated coastal ecosystems are not included in emissions accounting or carbon market protocols, but this analysis suggests they may be disproportionally important to both. Although the relevant science supporting these initial estimates will need to be refined in coming years, it is clear that policies encouraging the sustainable management of coastal ecosystems could significantly reduce carbon emissions from the land-use sector, in addition to sustaining the well-recognized ecosystem services of coastal habitats.

An integrated method is required for comprehensive assessment of the environmental impacts and economic benefits of rice production systems. Therefore, the objective of this study was to apply different footprinting approaches (carbon footprint (CF), nitrogen footprint (NF), water footprint (WF)) and determine the economic return on organic rice farming (OF) and conventional rice farming (CVF) at the farm scale. Over the 4-year study period (2018–2021), the results showed lower net greenhouse gas (GHG) emissions in OF (3289.1 kg CO2eq ha−1 year−1) than in CVF (4921.7 kg CO2eq ha−1 year−1), indicating that the use of OF can mitigate the GHG emissions from soil carbon sequestration. However, there was a higher CF intensity in OF (1.17 kg CO2eq kg−1 rice yield) than in CVF (0.93 kg CO2eq kg−1 rice yield) due to the lower yield. The NF intensities of OF and CVF were 0.34 and 11.94 kg Neq kg−1 rice yield, respectively. The total WF of CVF (1470.1 m3 ton−1) was higher than that in OF (1216.3 m3 ton−1). The gray water in CVF was significantly higher than that in OF due to the use of chemical fertilizers, herbicides, and pesticides. Although the rice yield in OF was nearly two times lower than that in CVF, the economic return was higher due to lower production costs and higher rice prices. However, more field studies and long-term monitoring are needed for future research.

This study focuses to investigate the relationship between globalization and the ecological footprint for Malaysia from 1971 to 2014. The results of the Bayer and Hanck cointegration test and the ARDL bound test show the existence of cointegration among variables. The findings disclose that globalization is not a significant determinant of the ecological footprint; however, it significantly increases the ecological carbon footprint. Energy consumption and economic growth stimulate the ecological footprint and carbon footprint in Malaysia. Population density reduces the ecological footprint and carbon footprint. Further, financial development mitigates the ecological footprint. The causality results disclose the feedback hypothesis between energy consumption and economic growth in the long run and short run.

Urban regions are responsible for a significant proportion of carbon emissions. The carbon footprint (CF) is a practical measure to identify the responsibility of individuals, cities, or nations in climate change. Numerous CF studies have focused on national accounts, and a few combined consumer consumption and global supply chains to estimate additionally detailed spatial CF. However, the drivers of temporal change in detailed spatial CF are largely unknown, along with regional, spatial, and socioeconomic disparities. Here, we uncovered the drivers of changes in household CFs in EU regions, at the finest scale currently available, between 2010 and 2015. This study mapped the household CFs of 83 macro-regions across 27 EU nations and identified the driving factors underlying their temporal change. We combined multi-regional input-output tables and micro-consumption data from 275 247 and 272 045 households in 2010 and 2015, respectively. We decomposed EU regional CF, employing structural decomposition analysis, into five driving factors: emission intensity, supply chain structure, population, per capita consumption, and final demand share. For a deeper assessment of changes in the contribution of consumption patterns, we further categorized the regional CF into 15 factors, including 11 per capita consumption categories. We found that household CF drivers vary depending on region, population density, income, and consumption patterns. Our results can help policymakers adopt climate policies at the regional level by reflecting on the residents’ socioeconomic, spatial, and consumption conditions, for further ambitious climate actions.

The expansion of Xi’an City has caused the consumption of energy and land resources, leading to serious environmental pollution problems. For this purpose, this study was carried out to measure the carbon carrying capacity, net carbon footprint and net carbon footprint pressure index of Xi’an City, and to characterize the carbon sequestration capacity of Xi’an ecosystem, thereby laying a foundation for developing comprehensive and reasonable low-carbon development measures. This study expects to provide a reference for China to develop a low-carbon economy through Tapio decoupling principle. The decoupling relationship between CO2 and driving factors was explored through Tapio decoupling model. The time-series data was used to calculate the carbon footprint. The auto-encoder in deep learning technology was combined with the parallel algorithm in cloud computing. A general multilayer perceptron neural network realized by a parallel BP learning algorithm was proposed based on Map-Reduce on a cloud computing cluster. A partial least squares (PLS) regression model was constructed to analyze driving factors. The results show that in terms of city size, the variable importance in projection (VIP) output of the urbanization rate has a strong inhibitory effect on carbon footprint growth, and the VIP value of permanent population ranks the last; in terms of economic development, the impact of fixed asset investment and added value of the secondary industry on carbon footprint ranks third and fourth. As a result, the marginal effect of carbon footprint is greater than that of economic growth after economic growth reaches a certain stage, revealing that the driving forces and mechanisms can promote the growth of urban space.

The healthcare sector is a significant contributor to global carbon emissions, in part due to extensive travelling by patients and health workers. To evaluate the potential of telemedicine services based on videoconferencing technology to reduce travelling and thus carbon emissions in the healthcare sector. A life cycle inventory was performed to evaluate the carbon reduction potential of telemedicine activities beyond a reduction in travel related emissions. The study included two rehabilitation units at Umeå University Hospital in Sweden. Carbon emissions generated during telemedicine appointments were compared with care-as-usual scenarios. Upper and lower bound emissions scenarios were created based on different teleconferencing solutions and thresholds for when telemedicine becomes favorable were estimated. Sensitivity analyses were performed to pinpoint the most important contributors to emissions for different set-ups and use cases. Replacing physical visits with telemedicine appointments resulted in a significant 40-70 times decrease in carbon emissions. Factors such as meeting duration, bandwidth and use rates influence emissions to various extents. According to the lower bound scenario, telemedicine becomes a greener choice at a distance of a few kilometers when the alternative is transport by car. Telemedicine is a potent carbon reduction strategy in the health sector. But to contribute significantly to climate change mitigation, a paradigm shift might be required where telemedicine is regarded as an essential component of ordinary health care activities and not only considered to be a service to the few who lack access to care due to geography, isolation or other constraints.

PurposeThe provision of healthcare is a substantial global contributor to greenhouse gas (GHG) emissions. Several medical specialties and national health systems have begun evaluating their carbon emission contributions. The aim of this review is to summarise and describe the carbon footprint resulting from the provision of adult, paediatric and neonatal critical care.MethodsA systematic search of Embase, Cochrane and Web of Science was performed in January 2023. Studies reporting any assessment of the carbon footprint of critical care were included. No language restrictions were applied. GHG emissions from life cycle assessments (LCA) were reported, in addition to waste, electricity and water use. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed.ResultsIn total, 13 studies assessing and describing the environmental impact of 36 adult or paediatric intensive care units (ICUs) were included. Two studies described full LCAs, seven reported waste only, two provided audits of unused medical supplies, one reported electricity use, and one study described a Material Flow Analysis. The estimated carbon emissions from critical care range between 88 kg CO2e/patient/day and 178 kg CO2e/patient/day. The two predominant sources of carbon emissions in critical care originate from electricity and gas use, as well as consumables. Waste production ranged from 1.1 to 13.7 kg/patient/day in the 6 studies where mean waste could be calculated.ConclusionThere is a significant carbon footprint that results from intensive care provision. Consumables and waste constitute important, measurable, and modifiable components of anthropogenic emissions. There remains uncertainty due to a lack of literature, several unstudied areas of carbon emissions from critical care units, and within measured areas, measurement and reporting of carbon emissions are inconsistent.

Climate change is the 21st century's biggest global health threat, endangering health care systems worldwide. Health care systems, and hospital care in particular, are also major contributors to greenhouse gas emissions. This study used a systematic search and screening process to review the carbon footprint of hospital services and care pathways, exploring key contributing factors and outlining the rationale for chosen services and care pathways in the studies. This state-of-the-science review searched the MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCOhost), GreenFILE (EBSCOhost), Web of Science, Scopus, and the HealthcareLCA databases for literature published between 1 January 2000 and 1 January 2024. Gray literature was considered up to 1 January 2024. Inclusion criteria comprised original research reporting on the carbon footprint of hospital services or care pathways. Quality of evidence was assessed according to the guidelines for critical review of product life cycle assessment (LCA). PROSPERO registration number: CRD42023398527. Of 5,415 records, 76 studies were included, encompassing 151 hospital services and care pathways across multiple medical specialties. Reported carbon footprints varied widely, from carbon dioxide ( ) equivalents ( ) for an hour of intravenously administered anesthesia to 10,200 for a year of hemodialysis treatment. Travel, facilities, and consumables were key contributors to carbon footprints, whereas waste disposal had a smaller contribution. Relative importance of carbon hotspots differed per service, pathway, medical specialty, and setting. Studies employed diverse methodologies, including different LCA techniques, functional units, and system boundaries. A quarter of the studies lacked sufficient quality. Hospital services and care pathways have a large climate impact. Quantifying the carbon footprint and identifying hotspots enables targeted and prioritized mitigation efforts. Even for similar services, the carbon footprint varies considerably between settings, underscoring the necessity of localized studies. The emerging field of health care sustainability research faces substantial methodological heterogeneity, compromising the validity and reproducibility of study results. This review informs future carbon footprint studies by highlighting understudied areas in hospital care and providing guidance for selecting specific services and pathways. https://doi.org/10.1289/EHP14754.