[Analysis of food carbon footprint and its socio-demographic disparities in China in 2018].

OBJECTIVE: To analyze food carbon footprint and its socio-demographic disparities among adults in China. METHODS: A total of 12 777 adults aged 18 years and above from the China Health and Nutrition Survey in 2018 who have completed dietary and socio-demographic data were analyzed. The information of food intake were collected by 24 h recalls combined with the weighing of household seasonings. Food consumption was converted into energy intake by the China Food Composition Table. Carbon footprint of 26 food groups were calculated by the food carbon footprint database based on life-cycle assessment(LCA), multinomial logit model was used to analyze the association of socio-demographic factors and food carbon footprint. RESULTS: Average food carbon footprint were decreased with increasing age while increased with increasing income and education levels, and was higher among male than that among female, was higher among urban residents than that among rural residents, was higher in the south than that in the north. Multinomial logit analysis showed that compared with people aged 18-44, the likelihood of occurring high carbon footprint in 60y and above group were 29%(OR=0.71, 95%CI 0.61-0.83) lower than that occurring low carbon footprint. Women were 11%(OR=0.89, 95%CI 0.81-0.99) and 25%(OR=0.75, 95%CI 0.67-0.84) less likely to appear medium and high carbon footprint than low carbon footprint, compared with their male counterparts. In comparison to people living in cities, rural dwellers were 24%(OR=0.76, 95%CI 0.69-0.85) and 38%(OR=0.62, 95%CI 0.55-0.70) less likely to appear medium and high carbon footprint than low carbon footprint. People in the south were 3.89 times(95%CI 3.52-4.30) and 11.35 times(95%CI 10.01-12.88) more likely to occur medium and high carbon footprint than low carbon footprint, compared with people in the north. Participants were more likely to occur medium carbon footprint and high carbon footprint with the increasing income level(OR>1), and were more likely to occur high carbon footprint with the increasing education level(OR>1). CONCLUSION: The food carbon footprint of adults in China in 2018 show different socio-demographic disparities, gender, income and education level are significant factors.

The carbon footprint of a Dutch academic hospital-using a hybrid assessment method to identify driving activities and departments.

Background: The healthcare sector is responsible for 7% of greenhouse gas (GHG) emissions in the Netherlands. However, this is not well understood on an organizational level. This research aimed to assess the carbon footprint of the Erasmus University Medical Center to identify the driving activities and sources. Methods: A hybrid approach was used, combining a life cycle impact assessment and expenditure-based method, to quantify the hospital's carbon footprint for 2021, according to scope 1 (direct emissions), 2 (indirect emissions from purchased energy), and 3 (rest of indirect emissions) of the GHG Protocol. Results were disaggregated by categories of purchased goods and services, medicines, specific product groups, and hospital departments. Results: The hospital emitted 209.5 kilotons of CO2-equivalent, with scope 3 (72.1%) as largest contributor, followed by scope 2 (23.1%) and scope 1 (4.8%). Scope 1 was primarily determined by stationary combustion and scope 2 by purchased electricity. Scope 3 was driven by purchased goods and services, of which medicines accounted for 41.6%. Other important categories were medical products, lab materials, prostheses and implants, and construction investment. Primary contributing departments were Pediatrics, Real Estate, Neurology, Hematology, and Information & Technology. Conclusion: This is the first hybrid analysis of the environmental impact of an academic hospital across all its activities and departments. It became evident that the footprint is mainly determined by the upstream effects in external supply chains. This research underlines the importance of carbon footprinting on an organizational level, to guide future sustainability strategies.

Carbon footprint of a laser unit: a study of two centres in the UK.

PURPOSE: Climate change has serious consequences for our wellbeing. Healthcare systems themselves contribute significantly to our total carbon footprint, of which emissions from surgical practice are a major component. The primary sources of emissions identified are anaesthetic gases, disposal of single-use equipment, energy usage, and travel to and from clinical areas. We sought to quantify the waste generated by laser surgery which, to our knowledge, has not been previously reported. METHODS: The carbon footprint of two laser centres operating within the United Kingdom were measured. The internationally recognised Greenhouse Gas Protocol was used as a guiding framework to classify sources of waste and conversion factors issued by the UK government were used to quantify emissions. RESULTS: The total carbon footprints per day at each unit were 299.181 carbon dioxide equivalents (kgCo2eq) and 121.512 kgCO2eq, respectively. We found the carbon footprint of individual laser treatments to be approximately 15 kgCO2eq per procedure. The biggest overall contributor to the carbon footprint was found to be the emissions generated from staff, patient and visitor travel. This was followed by electricity usage, and indirect emissions from physical waste and laundry. CONCLUSIONS: The carbon footprint of laser procedures was considerably less than the average surgical operation in the UK. This initial study measures the carbon footprint of a laser center in a clinical setting and allows us to identify where improvements can be made to eventually achieve a net carbon zero health care system.

Herpes zoster in older adults: Impact on carbon footprint in the United States.

We provide estimates for (I) annual herpes zoster (HZ) cases, (II) carbon costs related to healthcare utilization, and (III) annual carbon emissions due to HZ among ≥50 years of age (YOA) United States (US) population. We estimated the annual number of HZ cases in the US based on available incidence data and demographic data of individuals ≥50 YOA. Both the healthcare resource utilization (HCRU) associated with HZ cases and the unit carbon dioxide equivalent (i.e. CO2e) costs associated with each type of HCRU in the US were estimated based on literature and studies available online. The carbon footprint associated with HZ annually among US adults ≥50 YOA was estimated by multiplying the unit carbon estimates by the HCRU. In the US population aged ≥50 YOA in 2020 (i.e. approximately 118 million), approximately 1.1 million cases of HZ occur annually assuming no vaccination. Based on 2 sources of HCRU the average kgCO2e per HZ patient ranged from 61.0 to 97.6 kgCO2e, with values by age group ranging from 40.9 kgCO2e in patients aged 50-59 to 195.9 kgCO2e in patients ≥80 YOA. The total annual HZ associated carbon ranged between 67,000 and 107,000 tons of CO2e in the US population aged ≥50 YOA. The impact of HZ on carbon footprint in the US results in considerable greenhouse gas (GHG)emissions. Assuming no vaccination, the burden of HZ is projected to rise over the coming years with the aging populations consequently worsening its impact on GHG emissions. (Figure 1).

Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

BACKGROUND: Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine. OBJECTIVE: This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants. METHODS: We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States. RESULTS: The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons. CONCLUSIONS: These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

The carbon footprint of critical care: a systematic review.

PURPOSE: The 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. METHODS: A 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. RESULTS: In 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. CONCLUSION: There 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.

Analysis on influencing factors of carbon emissions from China's pulp and paper industry and carbon peaking prediction.

China's pulp and paper industry (CPPI) has been always the main carbon emission source in recent years. However, the analysis on influencing factors of carbon emissions from this industry is insufficient. To address the issue, the CO2 emissions from CPPI are estimated in the period of 2005-2019, the driving factors of CO2 emissions are investigated by the logarithmic mean Divisia index (LMDI) method, the decoupling state of economic growth and CO2 emissions is determined by Tapio decoupling model, and finally, future CO2 emissions are predicted under four scenarios by the STIRPAT model to explore the potential of carbon peaking. The results show that CPPI exhibits a rapid increase and a fluctuating downward trend in CO2 emissions during the period of 2005-2013 and 2014-2019, respectively. The main promoting and inhibiting factors to the increase of CO2 emission are per capita industrial output value and energy intensity, respectively. There are five decoupling states of CO2 emissions and economic growth during the study period, and the CO2 emissions exhibit a weak decoupling state with the industrial output value growth in most years of the study period. It is very difficult to realize the carbon peaking goal by 2030 under the baseline and fast development scenarios. Therefore, efficient low carbon and strong low-carbon development policies are necessary and urgent for the realization of carbon peaking goal and the sustainable development of CPPI.

In the era of globalization, can renewable energy and eco-innovation be viable for environmental sustainability in BRICS economies?

Although energy is a necessary component of production and hence a contaminant, the environmental effect varies depending on the type of energy used. Renewable sources of energy can provide ecological advantages, particularly when contrasted with fossil fuels, which emit high levels of CO2 emissions. Thus, the research explores the impact of eco-innovation (ECO), green energy (REC), and globalization (GLOB) on the ecological footprint (ECF) in the BRICS nations using the panel nonlinear autoregressive distributed lag (PNARDL) technique between 1990 and 2018. The empirical results indicate that there is cointegration in the model. The results from the PNARDL show that a positive shift in renewable energy, eco-innovation, and globalization decreases the ecological footprint, while positive (negative) shifts in non-renewable energy and economic growth intensify the ecological footprint. The paper suggests several policy recommendations based on these results.

Does the frequency of stochastic convergence in per capita ecological footprint matter?

Among the environmental economics research issues, the issue of convergence has received quite a lot of attention, which is also known as stationary analysis. In this research strand, whether shocks to the time series variable are permanent or temporary is tested via the unit root tests. In this study, based on the theory and empirical works of stochastic convergence, we evaluate the convergence for the BASIC member countries, including Brazil, South Africa, India, and China. We use a variety of methodologies to see whether the convergence of ecological footprint holds for these countries or not. We first use the wavelet decomposition technique to decompose the series into the short run, middle run, and long run, and then we run several unit root tests to confirm the stationarity property of the series. The methodologies implemented in this study allow us to apply econometric tests to the original series as well as to the decomposed series. The results of panel CIPS test demonstrate that the null hypothesis of unit root could be rejected for the short run but not for the middle and long run, implying that long-lasting impact might prevail due to any shocks to the ecological footprint in the middle and long run. The results for individual countries varied.

Study on temporal and spatial differentiation of biocapacity in Shenyang from a multi-scale perspective.

Biocapacity of a region exhibits spatial differences owing to the limitations of regional scale and natural conditions. Based on the multi-scale perspective, we comprehensively studied and analyzed the temporal and spatial differences of the biocapacity of a region in an attempt to establish the groundwork for optimizing urban development and its utilization framework. By adopting the ecological footprint model along with multi-scale difference evaluation method, the municipal and county scales are incorporated into a unified analysis framework in this paper, thereby facilitating the exploration of the temporal and spatial differences in the biocapacity of Shenyang-a city in China-from 2005 to 2019. The results demonstrated that: 1) At the municipal scale, the biocapacity per capita fluctuated between 1.35 hm2/person and 2.22 hm2/person. It revealed an "up-down-up" trend, which appeared consistent with the Kuznets cycle; at the county scale, the biocapacity depicted spatial differences, while those of downtown and surrounding districts/counties developed a two-level ascending hierarchical structure. 2) The time series of footprint size and depth first ascended and then declined, and can be classified into four types: closed type, inverted U-type, S-type, and M-type. Among them, S-type and M-type have the phenomenon of over-utilizing the stock capital. 3) For a long time, the regional difference of biocapacity has mostly dwelt on two scales with an evident scale effect, and the biocapacity of Liaozhong District was the worst.

Single-item substitutions can substantially reduce the carbon and water scarcity footprints of US diets.

BACKGROUND: Human food systems substantially affect the environment, but the impacts vary widely by food. Guidance to individuals to reduce their dietary impacts would benefit from easy advice, but little is known about the specific population impacts of simple changes on self-selected diets. OBJECTIVES: The objective was to estimate the potential impact of a single dietary substitution on the carbon and water scarcity footprints of self-selected diets in the United States. METHODS: This cross-sectional modeling study used 24-h dietary recall data from the 2005-2010 waves of the NHANES. Greenhouse gas emissions (GHGE) in the production of foods as well as irrigated water use, characterized by its relative scarcity at production locations, were matched to all foods in the recalls using previously developed databases. Impacts were summed to create carbon and water scarcity footprints for diets (n  = 16,800) of adults aged >18 y. Diet quality was assessed using the Healthy Eating Index (HEI). Foods with the highest impact on GHGE and selected additional foods were substituted for calorically equivalent, less impactful items. Footprints were calculated before and after these hypothetical substitutions. RESULTS: The highest impact foods were all beef items, and 19.8% of individuals consumed them (n = 3320). After substitution of these items with poultry or pork, the mean carbon and water scarcity footprints among those with substitutions significantly decreased (P < 0.001) by 48.4 ± 0.6% and 29.9 ± 0.4%, respectively. Across the entire sample, these represented mean reductions of 9.6 ± 0.3% and 5.9 ± 0.2%, respectively. The mean HEI after substitutions was 3.6 ± 0.1% higher than before (P < 0.001). None of the selected additional foods had population impacts as large as the beef substitutions. CONCLUSIONS: Simple substitutions can be made in individuals' diets to substantially reduce their carbon and water scarcity footprints without sacrificing dietary quality. Such substitutions may be easier to promote than complex dietary patterns.

Nematode community structure along elevation gradient in high altitude vegetation cover of Gangotri National Park (Uttarakhand), India.

The study was undertaken to understand the dynamics of soil nematode communities association along elevation gradient and associated variables in high-altitude regions of Western Himalaya. The diversity and distribution pattern of soil nematodes were investigated at four elevation ranges (Elv1, Elv2, Elv3, and Elv4 each of 500 m class) along altitudinal gradient (3000-5000 m). The nematode community comprised 58 genera of which 37 genera showed sensitivity towards altitudinal variation and the community structure also varied among elevation classes. It was found that elevation significantly affect the nematodes trophic group, diversity composition, and the nematode indices. Nematode generic richness and evenness index indicated a relatively low biodiversity of soil nematodes is supported at higher altitudes. Moreover, maturity indices reflected lower sustenance of k-strategic nematodes at higher elevations. Structure index depicted fewer connections in the soil food web at higher elevations. Nematode faunal profile showed low nutrient and low disturbance in the region. Carbon footprint of the whole nematode assemblage declined along the elevation. Overall substantial differences in the nematode composition, abundance, trophic structure, and contribution to belowground carbon cycling were observed with change in elevation. These findings could be utilized as useful tool in the long-term monitoring and to understand the region's soil health.