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{"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.

Abstract Coal energy landscapes have changed dramatically over the last decades, including geographic shifts in production and consumption, technological changes that have reduced labour demand and led to relatively new mining practices (e.g. invasive mountain-top approaches), changed economic footprints, a shutdown of capacities or a complete end of mining in many regions with massive impacts on regional and local economies, community well-being, social capital, et cetera. Then the Covid-19 pandemic and Russia´s invasion of Ukraine have fundamentally affected the global economy, disrupted energy markets, and shattered existing estimates about development trends, challenging the progress and speed of the low-carbon energy transition and coal phase-out. This article provides a brief reflection on the changing landscapes of coal and their possible futures, and serves as an introduction to the Special Issue of Moravian Geographical Reports on “The death of coal in the energy transition? Regional perspectives”.

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.

Considering the important role of energy in modern society, it is imperative to study the current situation and future development of energy under the influence of COVID-19. This paper identifies the current research hotspots, proposes future research directions accordingly, and summarizes the methodologies via a bibliometric analysis. Five research hotspots include COVID-19 and the changes of energy consumption, COVID-19 and the fluctuation of the energy market, COVID-19 and the development of renewable energy, COVID-19 and climate impacts caused by energy consumption, and COVID-19 and the energy policy. According to the influence mechanism of COVID-19 on each hotspot, the pandemic has exerted short-term influencs on energy consumption, energy price, and air pollution. Meanwhile, the pandemic could have a far-reaching impact on the renewable energy sector, climate, and energy policy. In addition, the main methodologies are reviewed, revealing that regression analysis and scenario analysis are commonly used as the quantitative and qualitative methods, respectively. Moreover, given the nonlinear relations between the pandemic and energy, an artificial neural networks model is used to enhance the prediction efficiency of energy demand and price. Finally, policy implications for obtaining clean, low-carbon, safe, and efficient energy in the context of COVID-19 are proposed.

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.

Abstract Fossil fuel and aerosol emissions have played important roles on climate over the Indian subcontinent over the last century. As the world transitions toward decarbonization in the next few decades, emissions pathways could have major impacts on India’s climate and people. Pathways for future emissions are highly uncertain, particularly at present as countries recover from COVID-19. This paper explores a multimodel ensemble of Earth system models leveraging potential global emissions pathways following COVID-19 and the consequences for India’s summertime (June–July–August–September) climate in the near- and long-term. We investigate specifically scenarios which envisage a fossil-based recovery, a strong renewable-based recovery and a moderate scenario in between the two. We find that near-term climate changes are dominated by natural climate variability, and thus likely independent of the emissions pathway. By 2050, pathway-induced spatial patterns in the seasonally-aggregated precipitation become clearer with a slight drying in the fossil-based scenario and wetting in the strong renewable scenario. Additionally, extreme temperature and precipitation events in India are expected to increase in magnitude and frequency regardless of the emissions scenario, though the spatial patterns of these changes as well as the extent of the change are pathway dependent. This study provides an important discussion on the impacts of emissions recover pathways following COVID-19 on India, a nation which is likely to be particularly susceptible to climate change over the coming decades.