• Energy Research
• 12. Responsible consumption close
• US close
• RO close
• COVID-19 close

{"references": ["Liu, Z., Ciais, P., Deng, Z., Lei, R., Davis, S. J., Feng, S., Zheng, B., Cui, D., Dou, X., Zhu, B., Guo, R., Ke, P., Sun, T., Lu, C., He, P., Wang, Y., Yue, X., Wang, Y., Lei, Y., Zhou, H., Cai, Z., Wu, Y., Guo, R., Han, T., Xue, J., Boucher, O., Boucher, E., Chevallier, F., Tanaka, K., Wei, Y., Zhong, H., Kang, C., Zhang, N., Chen, B., Xi, F., Liu, M., Br\u00e9on, F.-M., Lu, Y., Zhang, Q., Guan, D., Gong, P., Kammen, D. M., He, K. & Schellnhuber, H. J. (2020). Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic. Nature Communications 11, 5172 (2020). https://doi.org/10.1038/s41467-020-18922-7", "Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J. F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K., Thomson, A., Velders, G. J. M., & van Vuuren, D. P. (2011). The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109(1\u20132), 213\u2013241. https://doi.org/10.1007/s10584-011-0156-z", "Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P. & Wilbanks, T. J. (2010). The next generation of scenarios for climate change research and assessment. Nature, 463(7282), 747\u2013756. https://doi.org/10.1038/nature08823", "Myhre, G., Highwood, E. J., Shine, K. P., & Stordal, F. (1998). New estimates of radiative forcing due to well mixed greenhouse gases. Geophysical Research Letters, 25(14), 2715\u20132718. https://doi.org/10.1029/98gl01908", "Strassmann, K. M. and Joos, F. (2018). The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle\u2013climate simulations, Geosci. Model Dev., 11, 1887\u20131908, https://doi.org/10.5194/gmd-11-1887-2018", "Thomas, M. A., and Lin, T. (2018). A dual model for emulation of thermosteric and dynamic sea-level change. Climatic Change, 148(1\u20132), 311\u2013324. https://doi.org/10.1007/s10584-018-2198-y"]} Supplementary materials for Gonzalez, A. R., & Lin, T. (2022). Translated Emission Pathways (TEPs): Long-Term Simulations of COVID-19 CO2 Emissions and Thermosteric Sea Level Rise Projections. Earth's Future. In Press. Summary: This study introduces climate science to a broader audience by presenting an accessible research framework and environmental data related to the ongoing COVID-19 pandemic. A series of translated emission pathways (TEPs) were constructed based on the CO2 emission patterns from the various phases of COVID-19 response. In addition to resembling the forcing scenarios used within climate research, a thermosteric sea level rise analysis was incorporated to further emphasize the environmental benefits that can be obtained from long-term sustainability. As a promising start for including the general public in climate change discussion, this research promotes collective environmental action that mirrors the recommendations of the scientific community. We acknowledge the Carbon Monitor initiative (Liu et al., 2020) for providing the COVID-19 CO2 sectoral emission data used to construct the proposed TEPs. In addition, we acknowledge the developers of the BernSCM (Strassmann and Joos, 2018) that was utilized in this study to relate TEP CO2 emissions to their respective CO2 atmospheric concentrations. Furthermore, we thank the Texas Tech University McNair Scholars Program and the Multi-Hazard Sustainability (HazSus) research group for guidance and support throughout the course of this study. Analyses presented herein were performed using the RedRaider computing cluster at Texas Tech University. We thank the team at the High Performance Computing Center (HPCC) for their generous support. In addition, the equipment support from the Vice President for Research & Innovation for T.L.'s HazSus Research Group is gratefully acknowledged.

The United Nations’ Sustainable Development Goals (SDGs) rest on a set of broadly accepted values within a human rights framework. The SDGs seek to improve human lives, improve the planet, and foster prosperity. This paper examines the human rights framework and the principles of social justice and shows that, while the SDGs do not specifically state that there is human right to food, the SDGs do envision a better, more just, world which rests upon the sufficiency of the global food supply, on environmental sustainability, and on food security for all. Then the paper examines the interrelationships between the SDGs, food access and waste, and human rights within a framework of social justice. Finally, it looks at the potential pandemic of hunger wrought by COVID-19, showing that COVID-19 serves as an example of a crisis that has raised unprecedented challenges to food loss and waste in the global food supply system and tests our commitment to the principles espoused by the SDGs.

This article examines outstanding “sustainable” skyscrapers that received international recognition, including LEED certification. It identifies vital green features in each building and summarizes the prominent elements for informing future projects. Overall, this research is significant because, given the mega-scale of skyscrapers, any improvement in their design, engineering, and construction will have mega impacts and major savings (e.g., structural materials, potable water, energy, etc.). Therefore, the extracted design elements, principles, and recommendations from the reviewed case studies are substantial. Further, the article debates controversial design elements such as wind turbines, photovoltaic panels, glass skin, green roofs, aerodynamic forms, and mixed-use schemes. Finally, it discusses greenwashing and the impact of COVID-19 on sustainable design.

We assess the effect of the COVID-19 pandemic on global fossil fuel consumption and CO2 emissions over the two-year horizon 2020Q1-2021Q4. We apply a global vector autoregressive (GVAR) model, which captures complex spatial-temporal interdependencies across countries associated with the international propagation of economic impact due to the virus spread. The model makes use of a unique quarterly data set of coal, natural gas, and oil consumption, output, exchange rates and equity prices, including global fossil fuel prices for 32 major CO2 emitting countries spanning the period 1984Q1-2019Q4. We produce forecasts of coal, natural gas and oil consumption, conditional on GDP growth scenarios based on alternative IMF World Economic Outlook forecasts that were made before and after the outbreak. We also simulate the effect of a relative price change in fossil fuels, due to global scale carbon pricing, on consumption and output. Our results predict fossil fuel consumption and CO2 emissions to return to their pre-crisis levels, and even exceed them, within the two-year horizon despite the large reductions in the first quarter following the outbreak. Our forecasts anticipate more robust growth for emerging than for advanced economies. The model predicts recovery to the pre-crisis levels even if another wave of pandemic occurs within a year. Our counterfactual carbon pricing scenario indicates that an increase in coal prices is expected to have a smaller impact on GDP than on fossil fuel consumption. Thus, the COVID-19 pandemic would not provide countries with a strong reason to delay climate change mitigation efforts.

The COVID-19 pandemic affects all of society and hinders day-to-day activities from a straightforward perspective. The pandemic has an influential impact on almost everything and the characteristics of the pandemic remain unclear. This ultimately leads to ineffective strategic planning to manage the pandemic. This study aims to elucidate the typical pandemic characteristics in line with various temporal phases and its associated measures that proved effective in controlling the pandemic. Besides, an insight into diverse country's approaches towards pandemic and their consequences is provided in brief. Understanding the role of technologies in supporting humanity gives new perspectives to effectively manage the pandemic. Such role of technologies is expressed from the viewpoint of seamless connectivity, rapid communication, mobility, technological influence in healthcare, digitalization influence, surveillance and security, Artificial Intelligence (AI), and Internet of Things (IoT). Furthermore, some insightful scenarios are framed where the full-fledged implementation of technologies is assumed, and the reflected pandemic impacts in such scenarios are analyzed. The framed scenarios revolve around the digitalized energy sector, an enhanced supply chain system with effective customer-retailer relationships to support the city during the pandemic scenario, and an advanced tracking system for containing virus spread. The study is further extended to frame revitalization strategies to highlight the expertise where significant attention needs to be provided in the post-pandemic period as well as to nurture sustainable development. Finally, the current pandemic scenario is analyzed in terms of occurred changes and is mapped into SWOT factors. Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution based Multi-Criteria Decision Analysis, these SWOT factors are analyzed to determine where prioritized efforts are needed to focus so as to traverse towards sustainable cities. The results indicate that the enhanced crisis management ability and situational need to restructure the economic model emerges to be the most-significant SWOT factor that can ultimately support humanity for making the cities sustainable.

In the near future, the year 2050, agricultural production should expand to fulfill the needs of approximately 9.7 billion inhabitants. Such an objective should be harmonized with social, economic, and environmental sustainability aspects to maintain safe food production and food security worldwide. For more than a year, the COVID-19 pandemic has raised and is still strongly disrupting the agro-livestock production sector, similar to several other economic sectors. In this sector, the relationships between suppliers, producers, and consumers should always continue to maintain the activity of the production chain, which are impaired by social distancing decisions taken following the emergence of the COVID-19 pandemic. In this study, a global cross-sectional survey (translated into four languages: Arabic, English, French, and Spanish) was shared with people belonging to the agricultural sector to identify: (1) the role of the agricultural information and communication technologies (ICTs) in agro-livestock farming systems sustainability during the period of COVID-19 pandemic, (2) the need for such technologies in the agricultural sector, and (3) the factors that affect the use of such technologies. The results showed that the most frequently used agricultural ICTs were social media (Facebook and/or WhatsApp; 27.3%) and online platforms and Internet services (26.3%), whereas robotic vehicles and/or drones (6.6%) were less frequently used. During the emergence of the pandemic, the major reasons impacting agro-livestock farming systems’ sustainability were social distancing (30.0%), shortage of labor (17.7%), maintaining precision farm management (14.8%), product marketing (14.2%), access production inputs (7.2%), and others (16.1%). Applying agricultural ICTs solved many obstacles related to the production process, such as maintaining precision farm management (25.6%), product marketing (23.6%), and access production inputs (16.1%). The subgroup analyses of the results considering the degree of country advancement, size of agribusinesses, and role/position of respondents in the farm highlighted the importance of supporting the use, availability, and awareness of agricultural ICTs at least for some groups of people such as those belong to developing countries, laborers, and small-scale agri-business holders. This cross-sectional study highlights the urgent need to turn to and to expand the use of new agricultural ICTs to meet the growing demand for food production in the world and to ensure the resilience and sustainability of farming systems, specifically under unexpected and extreme conditions.

The COVID-19 pandemic has altered all aspects of human life since its breakout in March 2020 in the USA and around the world. There has been a tremendous increase in the use of plastic products as most of the PPE (masks, gloves, and other medical equipment) are made from plastic. Therefore, the generation of plastic waste was expected to increase significantly, which was also reported by many news agencies and organizations. This study determines the increase in plastic waste in municipal solid waste (MSW) and investigates its effect on landfill volume consumption during the COVID-19 pandemic. MSW samples were collected from the working face of Irving Hunter Ferrell landfill from May 2020 to December 2020. During every attempted sample collection, eight bags of MSW samples, each weighing 20–25 lbs., were collected. The MSW samples collected from the landfill were characterized and later the volume was estimated to evaluate the potential effects on landfill airspace. Based on the experimental investigations, it was found that plastic waste generation increased significantly during the pandemic (increasing from an 18.5% pre-pandemic level to 30% during the pandemic). Volumetric estimation suggests that the increased amount of plastic waste occupies 20% more volume in landfills. Quantification and estimation of the volume of the increased amount of plastic waste can be useful in predicting the impact of the pandemic on the lifetime of landfills.

Abstract The ongoing COVID-19 pandemic increases the consumption of respirators. In this work, we propose a novel and effective waste respirator processing system that aims to protect public health and mitigate climate change. Respirator sterilization and pre-processing technologies are incorporated simultaneously to resist viral infection and facilitate unit processes for manufacturing and separating products, so the greenhouse gas (GHG) emission can be reduced via carbon reallocation from CO2 to downstream products. High-fidelity process simulations are performed to extract detailed life cycle inventories used for evaluating environmental performance. Results reveal the economic viability in terms of the payback time (seven years) and the internal rate of return (21.5%). The proposed waste respirator processing system reduces GHG emissions by 59.08% compared to incineration, which reflects the potential of climate change mitigation.