The risk of human-induced climate change and the volatility of world oil markets make non-fossil fuel options important. This paper investigates the potential for wind, solar-PV and biomass (WSB) to deliver energy. The focus is on land opportunities and constraints and on production costs as a function of resource availability and depletion and of innovation dynamics. The context is provided by the IPCC SRES scenarios as simulated with the IMAGE 2.2 model. We explicitly consider several sources of uncertainty, aspects of the food vs. energy trade-off and the effects of interaction between the three options through their claims on land. We show that 'potential production' concepts are strongly dependent on the chosen land-use scenario-and should therefore be used with an indication of the underlying assumptions. Our results indicate a potential for liquid biofuels in the order of 75-300 EJ year À1 and for electricity from WSB options at production costs below 10 b kWh À1 of 200-300 PWh year À1. Theoretically, future electricity demand can be amply met from WSB sources in most regions by 2050 below 10 b kWh À1 , but major uncertainties are the degree to which land is actually available and the rate and extent at which specific investment costs can be reduced. In some regions, competition for land among the three WSB options may significantly reduce the total potential as estimated from simple addition-which is another source of uncertainty.
Reducing hunger while staying within planetary boundaries of pollution, land use and fresh water use is one of the most urgent sustainable development goals. It is imperative to understand future food demand, the agricultural system, and the interactions with other natural and human systems. Studying such interactions in the long-term future is often done with Integrated Assessment Modelling. In this paper we develop a new food demand model to make projections several decades ahead, having 46 detailed food categories and population segmented by income and urban vs rural. The core of our model is a set of relationships between income and dietary patterns, with differences between regions and income inequalities within a region. Hereby we take a different, more long-term-oriented approach than elasticity-based macroeconomic models (Computable General Equilibrium (CGE) and Partial Equilibrium (PE) models). The physical and detailed nature of our model allows for fine-grained scenario exploration. We first apply the model to the newly developed Shared Socioeconomic Pathways (SSP) scenarios, and then to additional sustainable development scenarios of food waste reduction and dietary change. We conclude that total demand for crops and grass could increase roughly 35-165% between 2010 and 2100, that this future demand growth can be tempered more effectively by replacing animal products than by reducing food waste, and that income-based consumption inequality persists and is a contributing factor to our estimate that 270 million people could still be undernourished in 2050.
Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO 2 emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65-75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9-10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO 2 emissions via increased electricity use.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.