Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

Building back better: Granular energy technologies in green recovery funding programs

Summary Granular energy technologies with smaller unit sizes and costs deploy faster, create more jobs, and distribute benefits more widely than lumpy large-scale alternatives. These characteristics of granularity align with the aims of fiscal stimulus in response to COVID-19. We analyze the technological granularity of 93 green recovery funding programs in France, Germany, South Korea, and the UK that target £72.9 billion for low-carbon energy technologies and infrastructures across five emissions-intensive sectors. We find that South Korea's "New Deal” program is the most technologically granular with strong weighting toward distributed renewables, smart technologies, electric vehicle charge points, and other relatively low unit cost technologies that are quick to deploy. The UK has the least granular portfolio, concentrating large amounts of public money on small numbers of mega-scale energy projects with high implementation risks. We demonstrate how technological granularity has multiple desirable characteristics of green recovery: jobs, speed, and distributed benefits.

Annual Variation of PM2.5 Chemical Composition in Ho Chi Minh City, Vietnam Including the COVID-19 Outbreak Period

PM2.5 was continuously collected in Ho Chi Minh City (HCMC), Vietnam, during the period from September 2019 to August 2020, which included the period of socioeconomic suppression caused by restrictions imposed in the face of the coronavirus disease of 2019. The concentrations of PM2.5 mass, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were determined to evaluate the seasonal variations in PM2.5, the effect of socioeconomic suppression on PM2.5, and potential PM2.5 sources in HCMC. The PM2.5 mass concentration during the sampling period was 28.44 +/- 11.55 mu g m(-3) (average +/- standard deviation). OC, EC, and total WSIs accounted for 30.7 +/- 6.6%, 9.7 +/- 2.9%, and 24.9 +/- 6.6% of the PM2.5 mass, respectively. WSOC contributed 46.4 +/- 10.1% to OC mass. NO3-, SO42-, and NH4+ were the dominant species in WSIs (72.7 +/- 17.7% of the total WSIs' mass). The concentrations of PM2.5 mass and total WSIs during the rainy season were lower than those during the dry season, whereas the concentrations of carbonaceous species during the rainy season were higher. The concentrations of PM2.5 mass and chemical species during the socioeconomic suppression period significantly decreased by 45%-61% compared to the values before this period. The OC/EC ratio (3.28 +/- 0.61) and char-EC/soot-EC (4.88 +/- 2.72) suggested that biomass burning, coal combustion, vehicle emissions, cooking activities are major PM2.5 sources in HCMC. Furthermore, the results of a concentration-weighted trajectory analysis suggested that the geological sources of PM2.5 were in the local areas of HCMC and the northeast provinces of Vietnam (where coal-fired power plants are located).

Getting Proactive with Pharma Packaging

According to market research, the pharmaceutical packaging sector is expected to grow at a compound annual rate of 7.4% between 2022 and 2031, reaching an estimated USS178.8 billion (€171.8 billion) by the end of the forecast period (1). "Pharmaceutical waste continues to be a huge problem, so to eliminate non-biodegradable and single-use plastics from the supply chain, more research is taking place around bio-based PET [polyethylene terephthalate]. "By designing a product's primary and secondary packaging well from the outset (including investing ample resources into the process), manufacturers can reduce the amount of materials used and wasted, test new eco materials, ensure safety compliance and efficacy, and benefit from cheaper transportation costs," Quelch surmises. [...]pharma companies can benefit from a packaging supplier with a true global footprint," he says.

Research on cold chain logistics optimization model considering low-carbon emissions

Cold chain logistics distribution orders have increased due to the impact of COVID-19. In view of the increasing difficulty of route optimization and the increase of carbon emissions in the process of cold chain logistics distribution, a mathematical model for route optimization of cold chain logistics distribution vehicles with minimum comprehensive cost is established by considering the cost of carbon emission intensity comprehensively in this paper. The main contributions of this paper are as follows: 1) An improved hybrid ant colony algorithm is proposed, which combined simulated annealing algorithm to get rid of the local optimal solution. 2) Chaotic mapping is introduced in pheromone update to accelerate convergence and improve search efficiency. The effectiveness of the proposed method in optimizing cold chain logistics distribution path and reducing costs is verified by simulation experiments and comparison with the existing classical algorithms. © 2023 The Author(s). Published by Oxford University Press.

Could Cryptocurrency Policy Uncertainty Facilitate US Carbon Neutrality?

Investigating the essential impact of the cryptocurrency market on carbon emissions is significant for the U.S. to realize carbon neutrality. This exploration employs low-frequency vector auto-regression (LF-VAR) and mixed-frequency VAR (MF-VAR) models to capture the complicated interrelationship between cryptocurrency policy uncertainty (CPU) and carbon emission (CE) and to answer the question of whether cryptocurrency policy uncertainty could facilitate U.S. carbon neutrality. By comparison, the MF-VAR model possesses a higher explanatory power than the LF-VAR model;the former's impulse response indicates a negative CPU effect on CE, suggesting that cryptocurrency policy uncertainty is a promoter for the U.S. to realize the goal of carbon neutrality. In turn, CE positively impacts CPU, revealing that mass carbon emissions would raise public and national concerns about the environmental damages caused by cryptocurrency transactions and mining. Furthermore, CPU also has a mediation effect on CE;that is, CPU could affect CE through the oil price (OP). In the context of a more uncertain cryptocurrency market, valuable insights for the U.S. could be offered to realize carbon neutrality by reducing the traditional energy consumption and carbon emissions of cryptocurrency trading and mining.

Going Green Post COVID-19: Employer Perspectives on Skills Needs

Achieving a just transition to a low carbon economy and society, in the wake of the COVID-19 pandemic, is arguably one of the greatest policy challenges facing governments. It is also of deep concern to businesses, employees and the organisations that represent them. Much of the focus, particularly at policy level, has been on the potential of this transition to create new jobs especially through the growth of renewable energy and clean technology. In this paper, we argue that this focus on ‘green jobs', and in particular new green jobs, grossly underestimates the skills needs of a future workforce able to deliver a transition to a more sustainable low-carbon economy. The focus of this study is to gain an understanding of what skills are required to support the transition beyond these sectors. It critically reports on the results of a series of in-depth interviews with senior managers in key organisations within Cambridgeshire and Peterborough, UK. It sheds a light on the significant employment transitions taking place in organisations who are not specifically focused on delivering ‘green' products or services. It finds widespread acknowledgement of the importance of a green recovery, albeit predicated by economic growth. The key skills needs reported, at all levels were likely to be ‘soft' transferrable skills rather than ‘hard' technical skills. COVID-19 was recognised as both a disrupter and as a catalyst for a green transition.

Why China Cannot Decarbonise

[...]it is often argued—as by Yifei Li and Judith Shapiro, for example—that China's dictatorship should be an advantage in this context: ‘Given the limited time that remains to mitigate climate change and protect millions of species from extinction, we need to consider whether a green authoritarianism can show us the way' (Li and Shapiro 2020, quoted from the publisher's book description). Since CCP bosses do not have to contend with public hearings, environmental studies, recalcitrant legislatures, labour unions, a critical press, and so on, Xi should be able to force state-owned polluters to stop polluting or else, and ram through his promised transition to renewable energy (see Smith 2017, 2020c). Climate Action Tracker estimates that in 2021 China's emissions increased by 3.4 per cent to 14.1 gigatonnes of carbon dioxide equivalent (GtCO2e)—nearly triple those of the United States (4.9 GtCO2e) with a gross domestic product just three-fourths as large (CAT n.d.;EIA 2022). Since 2019, China's emissions have exceeded those of all developed countries combined and presently account for 33 per cent of total global emissions (Larsen et al. 2021;IEA 2021). In the first half of 2021, rebounding from the first wave of Covid-19, China's carbon dioxide emissions surged past pre-pandemic levels to reach an all-time high 20 per cent increase in the second quarter before dropping back in late 2021 and the first half of 2022 as the real estate collapse, Omicron lockdowns, and drought-induced hydropower reductions slashed economic growth to near zero in the summer (Hancock 2021;Myllyvirta 2022a;Riordan and Hook 2022). China promised to stop building coal-fired power plants abroad, but it is building more than 200 new coal-fired plants at home in a drive to boost economic growth, maintain jobs in coal-dependent regions, and ensure energy self-sufficiency—locking the country into coal reliance for many decades to come, derailing the transition to renewables, and dooming Xi's UN pledge to transition to a green and low-carbon mode of development (Xie 2020).

Two-year outcome of extracorporeal membrane oxygenation in COVID-19 related severe respiratory failure

Objectives: We sought to evaluate 2-year outcome of V-V ECMO support for COVID-19 related severe respiratory failure in our center. Method(s): Retrospective analysis of 41 consecutive patients (73% male, mean age 51.6+/-14.2 years, mean BMI 35.1+/-12.5 kg/m2) with critical hypoxemic and/or hypercapnic refractory respiratory failure (mean P/F ratio 67.9+/-14.3 mmHg, mean pCO2 77.6.0+/-185.7 mmHg, Murray Score 3.71+/-0.4) on V-V ECMO support from October 2020 to January 2022 Results: With mean support duration of 234.4+/-63.2 hours, 29 patients (70.7%) were successfully weaned off. Finally, 19 of them (46.3%) were discharged home with good neurological outcome (CPC 1,2). During followup, 30-day, 6-, 12-, and 24 -month survival rate was 61.3%, 46.2%, 41.9%, and 41,9% respectively. In survivor group shorter symptoms onset to respiratory failure time (4+/-4.7 vs. 7+/-6.7 days, p=0.04), higher P/F ration (86+/-41.5 vs. 65+/-37.5 mmHg, p=0.04) and norepinephrine support (0.03+/-0.06 vs. 0.09+/-0.12 ug/kg/min, p=0.04), and lower IL-6 level (12.3+/-7.5 vs. 25.9+/-8.8 ng/l, p=0.03) p=0.01) were analysed before cannulation. Mean in-ICU stay and in-hospital stay in survivors;groups reached 32.5+/-27.7 days and 42.6+/-35.8 days, respectively. All long-term survivors (17 patients) complained about slight functional health limitation only with normal 6MWT (542.6+/- 89.2 min), near to normal spirometry parameters (FEV/VC 87+/-7.4%, DLCO 63.1+/-13.7%, KCO 82.,1+/-19.4%) and minimal neurological disability (CPC 1-2) Conclusion(s): 2-year outcome of V-V ECMO support in COVID-19 severe respiratory failure is acceptable even in the scope of low-volume ECMO centre. Reported functional status of long-term survivors was good despite the complicated and prolonged in-hospital stay. (Table Presented).

The inspiratory activity of respiratory center and respiratory muscles strength after COVID-19.

The respiratory pump that provides pulmonary ventilation includes the respiratory center, peripheral nervous system, chest and respiratory muscles. The aim of this study was to evaluate the activity of the respiratory center and the respiratory muscles strength after COVID-19 (COronaVIrus Disease 2019). Methods. The observational retrospective cross-sectional study included 74 post-COVID-19 patients (56 (76%) men, median age - 48 years). Spirometry, body plethysmography, measurement of lung diffusing capacity (DLCO), maximal inspiratory and expiratory pressures (MIP and MEP), and airway occlusion pressure after 0.1 sec (P0.1) were performed. In addition, dyspnea was assessed in 31 patients using the mMRC scale and muscle strength was assessed in 27 of those patients using MRC Weakness scale. Results. The median time from the COVID-19 onset to pulmonary function tests (PFTs) was 120 days. The total sample was divided into 2 subgroups: 1 - P0.1 <= 0.15 kPa (norm), 2 - > 0.15 kPa. The lung volumes, airway resistance, MIP, and MEP were within normal values in most patients, whereas DLCO was reduced in 59% of cases in both the total sample and the subgroups. Mild dyspnea and a slight decrease in muscle strength were also detected. Statistically significant differences between the subgroups were found in the lung volumes (lower) and airway resistance (higher) in subgroup 2. Correlation analysis revealed moderate negative correlations between P0.1 and ventilation parameters. Conclusion. Measurement of P0.1 is a simple and non-invasive method for assessing pulmonary function. In our study, an increase in P0.1 was detected in 45% of post-COVID-19 cases, possibly due to impaired pulmonary mechanics despite the preserved pulmonary ventilation as well as normal MIP and MEP values.Copyright © Savushkina O.I. et al., 2023.

Nanomaterial-based smart coatings for antibacterial, antifungal, and antiviral activities

Infectious diseases caused by different pathogens (parasites, protozoa, bacteria, viruses, and fungi) have affected the world at various times in the form of epidemics and pandemics. The coronavirus has also directly affected the world's economy and public health. Various drugs such as antibiotics, antimicrobials, antifungals, and antivirals have been investigated to combat these diseases. However, these fatal infections are still a major concern because of their transmission through contaminated surfaces, human-to-human contact, airborne diffusion, and microbial resistance. Therefore, considerable efforts are required to suppress the transmission of these pathogens. Smart coatings are able to sense their environment and adapt their properties according to the stimulus. Furthermore, various parameters of coating technology can be controlled on a molecular level to influence the morphology. Nanomaterial (NM)-based smart coatings are 99.99% effective against bacteria, viruses, and fungi because of the unique properties of NMs involved. Moreover, NM-based smart coatings are 1000-fold more efficient than traditional coating technologies. Besides their antifungal, antiviral, and antibacterial application, they are anticorrosive and self-cleaning. This chapter summarizes various NM-based smart coatings (organic, inorganic, and carbon) implemented in antibacterial, antifungal, and antiviral applications. Furthermore, the application of these coatings in various fields and their associated challenges will be discussed. © 2023 Elsevier Inc. All rights reserved.

Tocilizumab Initiation based on Indicator in Patients Infected by Coronavirus-19 to Prevent Intubation

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has created severe medical and economic consequences worldwide since 2019. Tocilizumab is one of the therapies considered capable of improving the condition of patients with COVID-19. However, there is not much information about the best time to give tocilizumab. METHOD(S): This was an analytical study with a retrospective cohort design, using the data of 125 patients infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with signs of acute respiratory distress syndrome in Dr. Moewardi Hospital, Surakarta, from March to August 2020. We analyzed various available clinical data to see which factors into clinical improvement with tocilizumab therapy. RESULT(S): Most patients showed clinical improvement after administration of tocilizumab. During the follow-up period, 21 patients died despite tocilizumab therapy. Significant risk factors associated with the need for intubation were heart rate, neutrophil, lymphocyte, pH, PaCO2, and PO2. The most influential variable on the need for intubation without being associated with other risk factors was PaO2 (p = 0.003, Confidence Intervals 95%). CONCLUSION(S): Tocilizumab has a role in treating patients infected by SARS-CoV-2, preventing the need for intubation when given to patients in good saturation condition with oxygen supplementation without positive pressure (PaO2 >65mmHg;SpO2 >93%).Copyright © 2023 Septian Adi Permana, Adhrie Sugiarto, Sidharta Kusuma Manggala, Muhammad Husni Thamrin, Purwoko Purwoko, Handayu Ganitafuri.

Anomalies of O3, CO, C2H2, H2CO, and C2H6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability

Anomalies of tropospheric columns of ozone (O3), carbon monoxide (CO), acetylene (C2H2), formaldehyde (H2CO), and ethane (C2H6) are quantified during the 2020 stringent COVID-19 world-wide lockdown using multiple ground-based Fourier-transform infrared spectrometers covering urban and remote conditions. We applied an exponential smoothing forecasting approach to the data sets to estimate business-as-usual values for 2020, which are then contrasted with actual observations. The Community Atmosphere Model with chemistry (CAM-chem) is used to simulate the same gases using lockdown-adjusted and business-as-usual emissions. The role of meteorology, or natural variability, is assessed with additional CAM-chem simulations. The tropospheric column of O3 declined between March and May 2020 for most sites with a mean decrease of 9.2% ± 4.7%. Simulations reproduce these anomalies, especially under background conditions where natural variability explains up to 80% of the decline for sites in the Northern Hemisphere. While urban sites show a reduction between 1% and 12% in tropospheric CO, the remote sites do not show a significant change. Overall, CAM-chem simulations capture the magnitude of the anomalies and in many cases natural variability and lockdowns have opposite effects. We further used the long-term record of the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument to capture global anomalies of CO. Reductions of CO vary highly across regions but North America and Europe registered lower values in March 2020.The absence of CO reduction in April and May, concomitant with reductions of anthropogenic emissions, is explained by a negative anomaly in the hydroxyl radical (OH) found with CAM-chem.The implications of these findings are discussed for methane (CH4), which shows a positive lifetime anomaly during the COVID-19 lockdown period. The fossil fuel combustion by-product tracer C2H2 shows a mean drop of 13.6% ± 8.3% in urban Northern Hemisphere sites due to the reduction in emissions and in some sites exacerbated by natural variability. For some sites with anthropogenic influence there is a decrease in C2H6.The simulations capture the anomalies but the main cause may be related to natural variability. H2CO declined during the stringent 2020 lockdown in all urban sites explained by reductions in emissions of precursors. Copyright: © 2023 The Author(s).

Incidence of heparin resistance and heparin failure in patients receiving extracorporeal membrane oxygenation - an exploratory retrospective analysis

Objectives: Unfractionated heparin (UFH) remains the anticoagulation of choice at most centres for patients receiving extracorporeal membrane oxygenation (ECMO). One disadvantage of UFH relies on its individual dosing requirement to achieve target values. In this context heparin resistance has been described, defined as doses exceeding 35,000 IU UFH/d. However, the incidence of heparin resistance and its association with thromboembolic complications despite anticoagulation within target ranges remains unknown. Method(s): This retrospective study included adults receiving venovenous (VV) and venoarterial (VA) ECMO, or extracorporeal CO2-removal (ECCO2R) between 2010 and May 2022. The primary outcome was the incidence of heparin resistance (>35,000 IU of UFH/d). Secondary outcomes were heparin failure (thromboembolic complications despite anticoagulation within target ranges) and survival. A multivariable poisson regression model was fitted to analyse the effect of heparin resistance, COVID-19 and ECMO type on the incidence rate of thromboembolic events. Result(s): Of 197 included patients, 33 (16.8%) had heparin resistance. Patients with COVID-19 (n=51) had a higher rate of heparin resistance compared to nonCOVID-19 patients (37% vs. 9.6%, P<0.001). Thromboembolic complications occurred at a rate of 5.89/100 ECMO days. There was a significant effect of COVID-19 (incidence rate ratio (IRR) 2.12, 95% confidence interval (CI) 1.4 to 3.3, P<0.001) and ECMO type (VA ECMO: IRR 2.35;95% CI 1.43 to 3.87, P<0.001;ECCO2R: IRR 2.63, 95% CI 1.37 to 4.9, P=0.003;reference VV ECMO) on incidence rate of thromboembolic events, but not of heparin resistance (IRR 1.11, 95% CI 0.7 to 1.76, P=0.7). ECMO duration was longer (25d (IQR 11-33) vs. 8d (IQR 4-18), P<0.001) in patients with heparin resistance, but hospital survival did not differ (23 (70%) vs. 91 (57%), P=0.2). Conclusion(s): The study revealed a high incidence of heparin failure in ECMO patients, especially in those with COVID-19. Heparin resistance had no effect on the incidence rate of thromboembolic events, whereas our data suggest an increased risk in patients with COVID19, VA ECMO and ECCO2R.

Role of telemedicine in anesthesia: Are we ready yet?

Telemedicine is a modality which utilizes technology to provide and support health care across large distances. It has redefined the practices of medicine in many specialties and continues to be a boon for clinicians on many frontiers. Its role in the branch of anesthesia remains largely unexplored but has shown to be beneficial in all the three phases: pre-operative, intra-operative, and post-operative. Now time has come that anesthesiologists across the globe reassess their strategies and utilize the telemedicine facilities in the field of anesthesia.Copyright © 2021 EDP Sciences. All rights reserved.

Can We Detect Urban‐Scale CO2 Emission Changes Within Medium‐Sized Cities?

The COVID‐19 pandemic resulted in a widespread lockdown during the spring of 2020. Measurements collected on a light rail system in the Salt Lake Valley (SLV), combined with observations from the Utah Urban Carbon Dioxide Network observed a notable decrease in urban CO2 concentrations during the spring of 2020 relative to previous years. These decreases coincided with a ∼30% reduction in average traffic volume. CO2 measurements across the SLV were used within a Bayesian inverse model to spatially allocate anthropogenic emission reductions for the first COVID‐19 lockdown. The inverse model was first used to constrain anthropogenic emissions for the previous year (2019) to provide the best possible estimate of emissions for 2020, before accounting for emission reductions observed during the COVID‐19 lockdown. The posterior emissions for 2019 were then used as the prior emission estimate for the 2020 COVID‐19 lockdown analysis. Results from the inverse analysis suggest that the SLV observed a 20% decrease in afternoon CO2 emissions from March to April 2020 (−90.5 tC hr−1). The largest reductions in CO2 emissions were centered over the northern part of the valley (downtown Salt Lake City), near major roadways, and potentially at industrial point sources. These results demonstrate that CO2 monitoring networks can track reductions in CO2 emissions even in medium‐sized cities like Salt Lake City.Alternate :Plain Language SummaryHigh‐density measurements of CO2 were combined with a statistical model to estimate emission reductions across Salt Lake City during the COVID‐19 lockdown. Reduced traffic throughout the COVID‐19 lockdown was likely the primary driver behind lower CO2 emissions in Salt Lake City. There was also evidence that industrial‐based emission sources may of had an observable decrease in CO2 emissions during the lockdown. Finally, this analysis suggests that high‐density CO2 monitoring networks could be used to track progress toward decarbonization in the future.

A Bibliometric Analysis of Sustainable Food Consumption: Historical Evolution, Dominant Topics and Trends

The major goal of this study is to trace the emergence of SFC-related research across time, using a thematic map and a list of corresponding publications. In addition, this study aims to determine the author who has made the most significant contribution to this particular field. This study provides a comprehensive bibliometric analysis of the historical development and current trends in sustainable food consumption research, examining 2265 articles published between 1990 and 2023. Using the bibliometrics package of R Studio software version 4.2.1 and its Biblioshiny package, articles from the Scopus and Web of Science databases are examined. In the field of sustainable food consumption, we identify five distinct research phases: initial stagnation, infant growth, post-economic crisis, expanding phase and COVID-19 and post-pandemic. While research on broader sustainability topics can be traced back to the early 20th century, a very limited number of articles on sustainable food consumption was published in the 1990s. However, the number of publications increased incrementally over time, with a notable uptick in interest around 2015, and the subject was still being discussed in 2022. The emergence of the COVID-19 pandemic marked the beginning of the most recent phase of research, which analyzed the consumption patterns of consumers before and after the pandemic. Our study highlights key authors, documents and sources related to sustainable food consumption. The United States, Italy and the United Kingdom emerged as the most active contributors to the research on sustainable food consumption and were additionally the countries with the largest global market shares for organic products. Major sub-themes including organic food, food waste, sustainable development and food security, together with consumer behavior and organic products appeared as being the most researched sub-themes of recent times. The results of this study suggest that more research is related to sustainable food consumption in countries with a low organic food market share. In addition, the investigation of actual data on food waste, carbon footprints and greenhouse gas emissions resulting from food production and consumption is essential to gain holistic insights.

GCC Hydrocarbon Economies and COVID: Old Trends, New Realities

The book considers the impact of COVID-19 on the GCC member states through the prism of challenges faced by their hydrocarbon sector. Yet, the publication's discourse is not solely focused on the problems experienced by the oil and gas industries of the GCC member states after the beginning of the COVID pandemic. Instead, the contributors will analyze how these challenges and subsequent response to them affected other aspects of the GCC socio-economic and political development, from direct impact of the COVID on the energy sector of the GCC to socio-economic consequences of the oil market crisis for the region and its potential fallouts for the international relations of the Gulf. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023, corrected publication 2023.

The evaluation of government subsidy policies on carbon emissions in the port collection and distribution network: a case study of Guangzhou Port

The collection and distribution network of ports is the main cause of carbon emissions. The carbon peak is a basic policy in China, and the subsidy policy is one of the common measures used by the government to incentivize carbon reduction. We analyzed the transportation methods and the flow direction of a port and proposed a carbon emission calculation method based on emission factors. Based on the transportation time and the cost, a generalized transportation utility function was constructed, and the logit model was used to analyze the impacts of subsidy policies on transportation, thus calculating the effects of the subsidies on carbon reduction. We used Guangzhou Port as a case study, and calculated the carbon reduction effects in six different subsidy policy scenarios and concluded that the absolute carbon reduction value was proportional to the subsidy intensity. In addition, we constructed a subsidy carbon reduction efficiency index and found that the Guangzhou Port collection and distribution network had higher subsidy carbon reduction efficiency in low-subsidy scenarios. Finally, a sensitivity analysis was conducted on the subsidy parameters, and scenario 8 was found to have the highest subsidy carbon reduction efficiency. This achievement can provide decision support for the carbon emission strategy of the port collection and distribution network.

Meeting the Hospital Oxygen Demand with a Decentralized Autonomous PV System: Effect of PV Tracking Systems

When it comes to supplying oxygen, current standard hospitals in Iran have proven inadequate in the face of the COVID-19 pandemic, particularly during infection peaks. Power disruptions drastically reduce the oxygen pressure in hospitals, putting patients' health at risk. The present study is the first to attempt to power an oxygen concentrator with a solar-energy-based system. The HOMER 2.81 package was used for technical–economic–environmental–energy analysis. The most notable aspects of this work include evaluating different available solar trackers, using up-to-date equipment price data and up-to-date inflation rate, considering the temperature effects on solar cell performance, sensitivity analysis for the best scenario, considering pollution penalties, and using a three-time tariff system with price incentives for renewable power. The study has been carried out at Hajar Hospital, Shahrekord, Chaharmahal and Bakhtiari Province, Iran. The study showed that, by supplying 60% of the power demand, the dual-axis solar tracking system offered the highest annual power output (47,478 kWh). Furthermore, generating power at—$0.008/kWh due to selling power to the grid, the vertical-axis tracker was found to be the most economical design. Comparing the configuration with a vertical-axis tracker with the conventional scenario (relying on the power distribution grid), the investment is estimated to be recovered in three years with $234,300 in savings by the end of the 25th year. In the best economic scenario, 6137 kg CO2 is produced, and the analysis revealed the negative impact of a temperature rise on the performance and solar power output.