Integrated policy assessment and optimisation over multiple sustainable development goals in Eastern Africa

Abstract

Heavy reliance on traditional biomass for household energy in eastern Africa has significant negative health and environmental impacts. The African context for energy access is rather different from historical experiences elsewhere as challenges in achieving energy access have coincided with major climate ambitions. Policies focusing on household energy needs in eastern Africa contribute to at least three sustainable development goals (SDGs): climate action, good health, and improved energy access. This study uses an integrated assessment model to simulate the impact of land policies and technology subsidies, as well as the interaction of both, on greenhouse gas (GHG) emissions, exposure to air pollution and energy access in eastern Africa under a range of socioeconomic pathways. We find that land policies focusing on increasing the sustainable output of biomass resources can reduce GHG emissions in the region by about 10%, but also slightly delay progress in health and energy access goals. An optimised portfolio of energy technology subsidies consistent with a global Green Climate Funds budget of 30–35 billion dollar, can yield another 10% savings in GHG emissions, while decreasing mortality related to air pollution by 20%, and improving energy access by up to 15%. After 2030, both land and technology policies become less effective, and more dependent on the overall development path of the region. The analysis shows that support for biogas technology should be prioritised in both the short and long term, while financing liquefied petroleum gas and ethanol technologies also has synergetic climate, health and energy access benefits. Instead, financing PV technologies is mostly relevant for improving energy access, while charcoal and to a lesser extend fuelwood technologies are relevant for curbing GHG emissions if their finance is linked to land policies. We suggest that integrated policy analysis is needed in the African context for simultaneously reaching progress in multiple SDGs.

Implications of different income distributions for future residential energy demand in the U.S.

“…This result is consistent with recent finding by various studies [32,[62][63][64][65][66][67]. We also find that the transition to a more egalitarian society could generate some moderate tradeoffs with other societal priorities or SDGs, such as an increment of CO 2 and air pollutant emissions from the residential sector, or a requirement for some additional investments in the power sector, as pointed by different studies [15,[68][69][70][71][72]. However, these adverse side-effects could be ameliorated if the more equal income distribution is combined with a limited use of fossil fuels, or a more rapid adoption of more efficient and/or cleaner technologies and building shells by households.…”

A multi-model analysis of long-term emissions and warming implications of current mitigation efforts

“…GCAM has been used to produce scenarios for national and international assessments ranging from the very first IPCC scenarios through the present Shared Socioeconomic Pathways (SSPs) (Calvin et al, 2017). Recent use cases include (Markandya et al, 2018), (Huang et al, 2019), and(de Ven et al, 2019).…”

Priorities for science to support national implementation of the sustainable development goals: A review of progress and gaps

“…IAMs and modeling tools are available for modeling at different scales (Allen et al, 2016). Several new studies have advanced global modeling to assess the feasibility of achieving the SDGs and the necessary transformations across multiple goals (Campagnolo & Davide, 2019;Moyer & Hedden, 2020;Randers et al, 2018Randers et al, , 2019 or focused on specific goals and interlinkages (Fujimori et al, 2019;Grubler et al, 2018;Lucas et al, 2019;Obersteiner et al, 2016;Van de Ven et al, 2019). National-scale integrated modeling studies have also begun to emerge to support SDG implementation in developed countries (Allen, Metternicht, Wiedmann, & Pedercini, 2019;Gao & Bryan, 2017) and developing countries (Banerjee, Cicowiez, Horridge, & Vargas, 2017;Collste et al, 2017;Duan, Mo, Fan, & Wang, 2018;Hinz et al, 2020;Pedercini et al, 2018;Pedercini et al, 2019;Qu, Shi, Zhang, & Liu, 2020).…”