54 research outputs found

    Climate impacts of energy technologies depend on emissions timing

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    Energy technologies emit greenhouse gases with differing radiative efficiencies and atmospheric lifetimes. Standard practice for evaluating technologies, which uses the global warming potential (GWP) to compare the integrated radiative forcing of emitted gases over a fixed time horizon, does not acknowledge the importance of a changing background climate relative to climate change mitigation targets. Here we demonstrate that the GWP misvalues the impact of CH[subscript 4]-emitting technologies as mid-century approaches, and we propose a new class of metrics to evaluate technologies based on their time of use. The instantaneous climate impact (ICI) compares gases in an expected radiative forcing stabilization year, and the cumulative climate impact (CCI) compares their time-integrated radiative forcing up to a stabilization year. Using these dynamic metrics, we quantify the climate impacts of technologies and show that high-CH[subscript 4]-emitting energy sources become less advantageous over time. The impact of natural gas for transportation, with CH[subscript 4] leakage, exceeds that of gasoline within 1–2 decades for a commonly cited 3 W m[superscript −2] stabilization target. The impact of algae biodiesel overtakes that of corn ethanol within 2–3 decades, where algae co-products are used to produce biogas and corn co-products are used for animal feed. The proposed metrics capture the changing importance of CH[subscript 4] emissions as a climate threshold is approached, thereby addressing a major shortcoming of the GWP for technology evaluation.New England University Transportation Center (DOT Grant DTRT07-G-0001

    Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

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    Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs

    Greater fuel efficiency is potentially preferable to reducing NOx emissions for aviation’s climate impacts

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    Aviation emissions of nitrogen oxides (NOx) alter the composition of the atmosphere, perturbing the greenhouse gases ozone and methane, resulting in positive and negative radiative forcing effects, respectively. In 1981, the International Civil Aviation Organization adopted a first certification standard for the regulation of aircraft engine NOx emissions with subsequent increases in stringency in 1992, 1998, 2004 and 2010 to offset the growth of the environmental impact of air transport, the main motivation being to improve local air quality with the assumed co-benefit of reducing NOx emissions at altitude and therefore their climate impacts. Increased stringency is an ongoing topic of discussion and more stringent standards are usually associated with their beneficial environmental impact. Here we show that this is not necessarily the right direction with respect to reducing the climate impacts of aviation (as opposed to local air quality impacts) because of the tradeoff effects between reducing NOx emissions and increased fuel usage, along with a revised understanding of the radiative forcing effects of methane. Moreover, the predicted lower surface air pollution levels in the future will be beneficial for reducing the climate impact of aviation NOx emissions. Thus, further efforts leading to greater fuel efficiency, and therefore lower CO2 emissions, may be preferable to reducing NOx emissions in terms of aviation’s climate impacts

    How much information is lost by using global-mean climate metrics? an example using the transport sector

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    Metrics are often used to compare the climate impacts of emissions from various sources, sectors or nations. These are usually based on global-mean input, and so there is the potential that important information on smaller scales is lost. Assuming a non-linear dependence of the climate impact on local surface temperature change, we explore the loss of information about regional variability that results from using global-mean input in the specific case of heterogeneous changes in ozone, methane and aerosol concentrations resulting from emissions from road traffic, aviation and shipping. Results from equilibrium simulations with two general circulation models are used. An alternative metric for capturing the regional climate impacts is investigated. We find that the application of a metric that is first calculated locally and then averaged globally captures a more complete and informative signal of climate impact than one that uses global-mean input. The loss of information when heterogeneity is ignored is largest in the case of aviation. Further investigation of the spatial distribution of temperature change indicates that although the pattern of temperature response does not closely match the pattern of the forcing, the forcing pattern still influences the response pattern on a hemispheric scale. When the short-lived transport forcing is superimposed on present-day anthropogenic CO2 forcing, the heterogeneity in the temperature response to CO2 dominates. This suggests that the importance of including regional climate impacts in global metrics depends on whether small sectors are considered in isolation or as part of the overall climate change

    Assigning historical responsibilities for extreme weather events

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    Recent scientific advances make it possible to assign extreme events to human-induced climate change and historical emissions. These developments allow losses and damage associated with such events to be assigned country-level responsibility

    Assigning historical responsibilities for extreme weather events

    No full text
    Recent scientific advances make it possible to assign extreme events to human-induced climate change and historical emissions. These developments allow losses and damage associated with such events to be assigned country-level responsibility
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