• Energy Research
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Energy mix persistence is a defining characteristic of energy systems, for reasons including the long‐lived nature of energy infrastructure and the role of local endowments. This persistence is evident in current energy‐type use being strongly influenced by past use. Our analysis uses data for eight energy types and a large sample of countries, finding varying degrees of energy mix persistence. We also find evidence that carbon pricing appears to have played a key role in tilting energy mixes from coal towards renewable energy. Our estimates provide empirical support to policymakers seeking to implement carbon pricing to transition their energy systems in a lower‐carbon direction.

Abstract We evaluated three Integrated Assessment Models (IAMs: IGSM, MERGE, MiniCAM) by: (i) comparing their global Primary Energy year-2000 initializations and projections for 2010 and 2015 to historical data; (ii) mapping their CO2 emissions projections against observations; and (iii) examining model-output diagnostics. The IAMs underestimated historical primary energy consumption and initial/projected CO2 emissions in both reference and stabilization scenarios (particularly for combustion fuels) but overestimated usage of non-biomass renewables, causing underestimates of future CO2 emissions that, for the stabilization scenarios, are wildly optimistic. Mitigation technology breakdowns in the policy scenarios vary enormously across IAMs, suggesting that confidence in their projections might be misplaced, or that options for mitigation have greater scope than is supposed. Most increases in carbon-free technologies in the stabilization scenarios are already captured in the reference cases. Energy-conversion efficiencies in electricity generation improve over time, but, (except for gas-powered generation in IGSM), efficiencies in the policy scenarios are less than in the reference. Electrification results diverge widely: IGSM has little change over the 21st century, while MiniCAM and MERGE have major electrification increases in their policy scenarios. We suggest: 1) comprehensive model output suitable for secondary analysis should be more readily available; 2) directly comparable reference and policy-driven mitigation scenarios are essential for assessing mitigation measures; 3) model validation using historical, source-specific energy data is crucial for assessing model credibility; 4) separation of mitigation contributions into no-policy and policy-driven amounts is needed to assess the effectiveness of mitigation policies; and 5) detailed inter-model comparisons can provide important insights into model credibility.

AbstractMultinational conservation initiatives that prioritize investment across a region invariably navigate trade-offs among multiple objectives. It seems logical to focus where several objectives can be achieved efficiently, but such multi-objective hotspots may be ecologically inappropriate, or politically inequitable. Here we devise a framework to facilitate a regionally cohesive set of marine-protected areas driven by national preferences and supported by quantitative conservation prioritization analyses, and illustrate it using the Coral Triangle Initiative. We identify areas important for achieving six objectives to address ecosystem representation, threatened fauna, connectivity and climate change. We expose trade-offs between areas that contribute substantially to several objectives and those meeting one or two objectives extremely well. Hence there are two strategies to guide countries choosing to implement regional goals nationally: multi-objective hotspots and complementary sets of single-objective priorities. This novel framework is applicable to any multilateral or global initiative seeking to apply quantitative information in decision making.

AbstractAs losses from extreme weather events grow, many governments are looking to privatize the financing and incentivization of climate adaptation through insurance markets. In a pure market approach to insurance for extreme weather events, individuals become responsible for ensuring they are adequately covered for risks to their own properties, and governments no longer contribute funds to post‐disaster recovery. Theoretically, insurance premiums signal the level of risk faced by each household, and incentivize homeowners to invest in adaptive action, such as retrofitting, or drainage work, to reduce premiums. Where risk is considered too high by insurance markets, housing is devalued, in theory leading to retreat from risky areas. In this review article, we evaluate the suitability of private insurance as a mechanism for climate adaptation at a household and community level. We find a mismatch between social understandings of responsibility for climate risks, and the technocratic, market‐based home insurance products offered by private insurance markets. We suggest that by constructing increasingly individualized, technical, and calculative evaluations of risk, market‐based models of insurance for extreme weather events erode the solidaristic and collective discourses and practices that support adaptive behavior.This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation

AbstractAs global mean sea level continues to rise, thresholds corresponding to coastal inundation impacts are exceeded more frequently. This paper aims to relate sea level rise (SLR) observations and projections to their physical on‐the‐ground impacts. Using a large coastal city as an example, we show that in Sydney, Australia, frequencies of minor coastal inundation have increased from 1.6 to 7.8 days per year between 1914 and present day. We attribute over 80% of the observed coastal inundation events between 1970 and 2015 to the predominantly anthropogenic increases in global mean sea level. Further, we find that impact‐producing coastal inundation will occur weekly by 2050 under high‐ and medium‐emission/SLR scenarios and daily by 2100 under high emissions. The proportion of tide‐only coastal inundation events (i.e., where no storm surge is required to exceed flood thresholds) will increase with SLR, such that most coastal inundation events, including those considered historically severe, will become a predictable consequence of SLR and astronomical tides. These findings are important for coastal managers as frequency, severity, and predictability of inundation impacts can all now be related to the amount of SLR (e.g., a planning allowance or SLR projection). By incorporating known historical inundation events, this allows contextualization, visualization, and localization of global SLR and the changing nature of future coastal inundation risk.

Abstract A type of smart window using thermochromic glazing (TCG) is a promising technology for green buildings owing to the self-regulating feature and low-maintenance need. Its most important feature, thermo-optical properties that regulate the blockage of solar heat, is directly linked to the variation of surface temperatures. However, challenges from the inhomogeneity of thermo-optical properties, the coupled solar radiation and natural convection, and varying outdoor conditions all seriously hinder the understanding of its mechanism. In this paper, a validated Computational Fluid Dynamics (CFD) model achieves the simulation of inhomogeneous tinting of TCG by defining the thermo-optical properties of each finite volume according to the surface temperature. Solar radiation and natural convection at outdoor, indoor and the cavity are solved to reflect glazing temperature more accurately. The case studies compared six different switching temperatures in the range of 20 ∼ 42.5 °C with a transition gradient of 10 °C. Averaged meteorological data for both summer and winter, sunny days and cloudy days are selected to present realistic climate impacts. The result reveals the overall saving in transmitted solar radiation in summer and heating penalties in winter. It suggests the best switching temperatures for each climate condition. With the seasonal operation, the highest saving in solar heat gain is 20.9% when adopting a switching temperature of 25–35 °C, while the lowest saving can be negative, meaning TCG is not suitable for those climate zones. The proposed evaluation criteria help to quantify the applicability of TCG with the input of the summer/winter day ratio and sunny/cloudy ratio. The best region to apply TCG is where summer days are longer and winter solar radiation is significantly lower. The in-depth understanding of this temperature-sensitive process benefits the optimization of TCG in buildings, especially for its seasonal operation needs.

Climate change presents risks to health that must be addressed by both decision-makers and public health researchers. Within the application of Environmental Health Impact Assessment (EHIA), there have been few attempts to incorporate climate change-related health risks as an input to the framework. This study used a focus group design to examine the perceptions of government, industry and academic specialists about the suitability of assessing the health consequences of climate change within an EHIA framework. Practitioners expressed concern over a number of factors relating to the current EHIA methodology and the inclusion of climate change-related health risks. These concerns related to the broad scope of issues that would need to be considered, problems with identifying appropriate health indicators, the lack of relevant qualitative information that is currently incorporated in assessment and persistent issues surrounding stakeholder participation. It was suggested that improvements are needed in data collection processes, particularly in terms of adequate communication between environmental and health practitioners. Concerns were raised surrounding data privacy and usage, and how these could impact on the assessment process. These findings may provide guidance for government and industry bodies to improve the assessment of climate change-related health risks.