JP

Abstract: Sub-Saharan Africa (SSA) is a global hot spot for aerosol emissions, which affect the regional climate and air quality. In this paper, we use ground-based observations to address the large uncertainties in the source-resolved emission estimation of carbonaceous aerosols. Ambient fine fraction aerosol was collected on filters at the high-altitude (2590 m a.s.l.) Rwanda Climate Observatory (RCO), a SSA background site, during the dry and wet seasons in 2014 and 2015. The concentrations of both the carbonaceous and inorganic ion components show a strong seasonal cycle, with highly elevated concentrations during the dry season. Source marker ratios, including carbon isotopes, show that the wet and dry seasons have distinct aerosol compositions. The dry season is characterized by elevated amounts of biomass burning products, which approach ∼95 % for carbonaceous aerosols. An isotopic mass-balance estimate shows that the amount of the carbonaceous aerosol stemming from savanna fires may increase from 0.2 µg m−3 in the wet season up to 10 µg m−3 during the dry season. Based on these results, we quantitatively show that savanna fire is the key modulator of the seasonal aerosol composition variability at the RCO.

A strong focus on climate-related financial risk has emerged in the past two years. Investors, particularly large institutional investors, have increasingly sought to understand whether the companies they’re investing in are exposed to climate risk. Central banks, particularly those in Europe, have also been concerned about systemic risks. For good reason: during the financial crisis of 2008, the failure of a few large financial institutions threatened the entire system.

Abstract: Limiting global warming in line with the goals in the Paris Agreement will require substantial technological and behavioural transformations. This challenge drives many of the current modelling trends. This article undertakes a review of 17 state-of-the-art recursive-dynamic computable general equilibrium (CGE) models and assesses the key methodologies and applied modules they use for representing sectoral energy and emission characteristics and dynamics. The purpose is to provide technical insight into recent advances in the modelling of current and future energy and abatement technologies and how they can be used to make baseline projections and scenarios 20-80 years ahead. Numerical illustrations are provided. In order to represent likely energy system transitions in the decades to come, modern CGE tools have learned from bottom-up studies. Three different approaches to baseline quantification can be distinguished: (a) exploiting bottom-up model characteristics to endogenize responses of technological investment and utilization, (b) relying on external information sources to feed the exogenous parameters and variables of the model, and (c) linking the model with more technology-rich, partial models to obtain bottom-up- and pathway-consistent parameters.

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