As global temperatures warm and populations and incomes rise, the demand for cooling will soar, creating a positive feedback loop between global warming and electricity-related carbon dioxide (CO₂) emissions. This study explores the relationship between temperature, electricity, air conditioning (AC) and CO₂ emissions, and the sustainability of cooling in the Kingdom of Saudi Arabia. With the highest share of AC in household electricity consumption in the world and its already very hot summers warming by 3 °C in many areas over the last 40 years, Saudi Arabia provides an important case study of how the cooling challenge can be managed. Data from the European Centre for Medium-Range Weather Forecasts (ECMWF ERA5) is used to illustrate local warming trends (1979–2018) and show the relationship between temperature and power generation within a typical year using hourly data (2011–2015). Using annual data (2010–2018), we then show that since 2016 the rapid growth in the Kingdom’s electricity demand for AC and its associated CO₂ emissions have plateaued. This suggests energy efficiency measures, higher electricity prices and a shift from the use of oil towards gas in the power sector are having a positive effect on energy sustainability. We identify key policies and technologies that will be important for the sustainable use of cooling in Saudi Arabia and beyond.

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment $L$ was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

The relationship between economic development and energy consumption has important policy and geopolitical implications intersecting with future energy demand, economic growth and climate change. All countries in the GCC share a common goal to transition to economies less reliant on oil and gas. As part of this transition diversification and energy efficiency strategies have become major strategic priorities. If successful, such policies are likely to significantly change the relationship between domestic energy consumption and GDP. To inform discussion on this topic, this paper assesses the relationship between energy consumption at a sector level and GDP in the GCC relative to a reference group of OECD countries. While there is variation within each grouping and across sectors, the clear result is that energy consumption and economic growth are strongly linked to all sectors in the GCC. This is in contrast to the OECD group where energy and GDP have decoupled. These results highlight both the scope for further improvement in energy efficiency and the need for deeper integration of energy-intensive industry and higher value-added activities and services. We suggest a greater focus on energy productivity—or how maximum value can be obtained from energy consumption—can help guide industrial policy and increase the profile of energy efficiency efforts across the GCC.

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of April 17, 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.