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相关概念视频

Global Climate Change01:50

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Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
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Carbon is the basis of all organic matter on Earth, and is recycled through the ecosystem in two primary processes: one in which carbon is exchanged among living organisms, and one in which carbon is cycled over long periods of time through fossilized organic remains, weathering of rocks, and volcanic activity. Human activities, including increased agricultural practices and the burning of fossil fuels, has greatly affected the balance of the natural carbon cycle.
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A phase diagram combines plots of pressure versus temperature for the liquid-gas, solid-liquid, and solid-gas phase-transition equilibria of a substance. These diagrams indicate the physical states that exist under specific conditions of pressure and temperature and also provide the pressure dependence of the phase-transition temperatures (melting points, sublimation points, boiling points). Regions or areas labeled solid, liquid, and gas represent single phases, while lines or curves represent...
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Using Generative Art to Convey Past and Future Climate Transitions
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在全球范围内预测国家CO2排放量.

Lorenzo Costantini1,2, Francesco Laio3, Manuel Sebastian Mariani4,5

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概括

紧急的气候行动需要了解碳排放驱动因素. 经济复杂性指标是关键,预测发达国家与发展中国家未来排放的分歧.

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科学领域:

  • 环境科学 环境科学
  • 气候变化建模模型
  • 社会经济学 社会经济学

背景情况:

  • 实现可持续发展目标需要采取紧急的气候行动,特别是减少碳排放.
  • 了解二氧化碳 (CO2) 排放的社会经济驱动因素对于准确的预测和有效的政策制定至关重要.
  • 现有的模型往往缺乏细节性,以捕捉经济指标和排放途径之间的复杂相互作用.

研究的目的:

  • 开发和应用全球建模框架,用于阻碍和预测二氧化碳排放.
  • 确定影响117个国家的二氧化碳排放的主要社会经济驱动因素.
  • 根据已识别的驱动因素和国家发展状况,预测到2035年的未来二氧化碳排放趋势.

主要方法:

  • 使用了两个全球建模框架:多变量回归和随机森林回归器 (RFR).
  • 在117个国家中,推迟预测到2021年的二氧化碳排放量和预测到2035年的排放量.
  • 分析了12个社会经济指标,包括经济福祉,绿色和复杂经济学以及能源消耗.

主要成果:

  • 确定了二氧化碳排放的主要驱动因素,经济复杂性领域的指标显著.
  • 根据各国的发展状况,揭示了不同的排放动态.
  • 预计到2035年 (相对于2020年),发达经济体的排放量将减少6.2%,发展中国家的排放量将增加19% (相对于2020年).

结论:

  • 经济复杂性和超越GDP的指标对于解释二氧化碳排放路径至关重要.
  • 不同的未来排放轨迹需要为发达国家和发展中国家量身定制的战略.
  • 在低产能环境中促进绿色增长和可持续发展对于减轻全球排放至关重要.