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A quantitative approach to evaluating the GWP timescale through implicit discount rates.

ABSTRACT: The 100-year global warming potential (GWP) is the primary metric used to compare the climate impacts of emissions of different greenhouse gases (GHGs). The GWP relies on radiative forcing rather than damages, assumes constant future concentrations, and integrates over a timescale of 100 years without discounting; these choices lead to a metric that is transparent and simple to calculate, but have also been criticized. In this paper, we take a quantitative approach to evaluating the choice of time horizon, accounting for many of these complicating factors. By calculating an equivalent GWP timescale based on discounted damages resulting from CH₄ and CO₂ pulses, we show that a 100-year timescale is consistent with a discount rate of 3.3% (interquartile range of 2.7% to 4.1% in a sensitivity analysis). This range of discount rates is consistent with those often considered for climate impact analyses. With increasing discount rates, equivalent timescales decrease. We recognize the limitations of evaluating metrics by relying only on climate impact equivalencies without consideration of the economic and political implications of metric implementation.

SUBMITTER: Sarofim MC

PROVIDER: S-EPMC6711200 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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A quantitative approach to evaluating the GWP timescale through implicit discount rates.

Sarofim Marcus C MC Giordano Michael R MR

Earth system dynamics : ESD 20180101

The 100-year global warming potential (GWP) is the primary metric used to compare the climate impacts of emissions of different greenhouse gases (GHGs). The GWP relies on radiative forcing rather than damages, assumes constant future concentrations, and integrates over a timescale of 100 years without discounting; these choices lead to a metric that is transparent and simple to calculate, but have also been criticized. In this paper, we take a quantitative approach to evaluating the choice of ti ...[more]

PMID: 31456907

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Project description:PurposeTo explore the potential of a chip-based miniaturized capillary gel electrophoresis device in a quantitative evaluation of the human tear protein profile and to validate the method.MethodsA total of 5 μl of tears were collected from 25 patients diagnosed as having mild to moderate dry eye according to Dry Eye Workshop guidelines and from 20 matched normal volunteers. Protein analysis was performed with the 2100 Bioanalyzer; different protein kit assays were evaluated (Protein 80 kit, Protein 230 kit, High Sensitivity Protein 250 kit) for sizing and quantifying protein samples from 5 to 80 kDa, 14 to 230 kDa, and 5 to 250 kDa, respectively. A standard protein ladder was loaded on each chip to allow an estimation of the appropriate molecular weight of the separated proteins; a sample buffer containing a lower and an upper marker was used to check the correct alignment of each lane. Virtual bands generated by the Bioanalyzer were identified and validated as follows: tear samples were run in parallel and proteins separated by one-dimensional and two-dimensional sodium dodecyl sulfate-PAGE and characterized by immunoblotting, enzymatic digestion, and analysis with liquid chromatography-mass spectrometry followed by a search of the SProt human protein database.ResultsAnalyses were successfully performed by using as small as a 2 μl tear sample. The Protein 230 kit was selected as the best chip kit, able to differentiate all the proteins of interest. The measurement noise parameters were low, and reproducibility and repeatability exhibited high accuracy (0.998 and 0.995, respectively) and precision (0.974 and 0.977, respectively). The coefficient of variability was slightly higher than that declared by the manufacturer (6.2% versus 5.0%). Total protein content and the following proteins were recognized in all samples: lipophilin A lysozyme C, tear lipocalin-1, zinc-alpha-2-glycoprotein, serotransferrin, lactotransferrin, and exudated serum albumin.ConclusionsOur data demonstrate that this chip-based tear protein analysis is a reliable method of instrumental diagnosis in daily clinical activity and may provide supporting evaluation parameters for diagnosing and managing tear-based disorders.

Project description:Understanding the dynamics of biological systems in evolving environments is a challenge due to their scale and complexity. Here, we present a computational framework for the timescale decomposition of biochemical reaction networks to distill essential patterns from their intricate dynamics. This approach identifies timescale hierarchies, concentration pools, and coherent structures from time-series data, providing a system-level description of reaction networks at physiologically important timescales. We apply this technique to kinetic models of hypothetical and biological pathways, validating it by reproducing analytically characterized or previously known concentration pools of these pathways. Moreover, by analyzing the timescale hierarchy of the glycolytic pathway, we elucidate the connections between the stoichiometric and dissipative structures of reaction networks and the temporal organization of coherent structures. Specifically, we show that glycolysis is a cofactor-driven pathway, the slowest dynamics of which are described by a balance between high-energy phosphate bond and redox trafficking. Overall, this approach provides more biologically interpretable characterizations of network dynamics than large-scale kinetic models, thus facilitating model reduction and personalized medicine applications. IMPORTANCE Complex interactions within interconnected biochemical reaction networks enable cellular responses to a wide range of unpredictable environmental perturbations. Understanding how biological functions arise from these intricate interactions has been a long-standing problem in biology. Here, we introduce a computational approach to dissect complex biological systems' dynamics in evolving environments. This approach characterizes the timescale hierarchies of complex reaction networks, offering a system-level understanding at physiologically relevant timescales. Analyzing various hypothetical and biological pathways, we show how stoichiometric properties shape the way energy is dissipated throughout reaction networks. Notably, we establish that glycolysis operates as a cofactor-driven pathway, where the slowest dynamics are governed by a balance between high-energy phosphate bonds and redox trafficking. This approach enhances our understanding of network dynamics and facilitates the development of reduced-order kinetic models with biologically interpretable components.

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A quantitative approach to evaluating the GWP timescale through implicit discount rates.

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A quantitative approach to evaluating the GWP timescale through implicit discount rates.

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