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Related Concept Videos

Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Propagation of Uncertainty from Random Error00:59

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Uncertainty: Overview00:59

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Stability of Equilibrium Configuration: Problem Solving01:13

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The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
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The Uncertainty Principle04:08

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Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
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Generation and Coherent Control of Pulsed Quantum Frequency Combs
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Uncertainty in non-CO

Mathijs Harmsen1,2, Charlotte Tabak3, Lena Höglund-Isaksson4

  • 1PBL Netherlands Environmental Assessment Agency, Bezuidenhoutseweg 30, NL-2594, AV, The Hague, the Netherlands. mathijs.harmsen@pbl.nl.

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Mitigating non-CO2 greenhouse gases (NCGGs) is crucial for climate policy, but uncertainty in NCGG mitigation potential impacts reaching Paris Agreement goals. This study quantifies NCGG mitigation uncertainty, revealing challenges for climate targets.

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Area of Science:

  • Climate Science
  • Environmental Policy
  • Greenhouse Gas Emissions

Background:

  • Non-CO2 greenhouse gas (NCGG) mitigation is vital for achieving global climate policy objectives, including the Paris Agreement goals.
  • Significant uncertainties in NCGG mitigation potential pose challenges to climate modeling and policy development.
  • Accurate assessment of NCGG mitigation is essential for evaluating the feasibility of limiting global warming.

Purpose of the Study:

  • To systematically estimate the total uncertainty in non-CO2 greenhouse gas mitigation.
  • To develop 'optimistic', 'default', and 'pessimistic' long-term NCGG marginal abatement cost (MAC) curves.
  • To assess the implications of NCGG mitigation uncertainty for global climate targets.

Main Methods:

  • A comprehensive literature review of NCGG mitigation options was conducted.
  • Marginal Abatement Cost (MAC) curves were developed for optimistic, default, and pessimistic scenarios.
  • The impact of MAC uncertainty on climate targets, carbon budgets, and policy costs was analyzed.

Main Results:

  • The 1.5-degree climate target is unattainable under pessimistic MAC assumptions.
  • The 2-degree climate target may be unachievable under high emission scenarios.
  • MAC uncertainty results in a projected 40-58% range in relative NCGG reduction, a ±120 Gt CO2 uncertainty in carbon budget, and ±16% uncertainty in policy costs for a 2-degree scenario.

Conclusions:

  • NCGG mitigation uncertainty significantly impacts the feasibility of achieving climate policy goals.
  • A substantial portion of MAC uncertainty reflects technical limitations rather than solely a gap for human innovation.
  • Addressing NCGG mitigation uncertainty is critical for effective climate change mitigation strategies.