通过能源效率应对气候变化：基于证据的公共政策建议的数学模型
Tackling climate change through energy efficiency: mathematical models for evidence-based public policy recommendations
摘要：
促进和提高能源效率是减少二氧化碳排放和避免气候变化潜在破坏性影响的一个有希望的方法。问题是：我们如何引导文化或行为变化，使全国和全球的人们采取更节能的生活方式？我们提出了一个新的家庭的数学模型，离散选择理论的统计力学扩展的基础上，提供了一套正式的工具，系统地分析和量化这个问题。一个应用示例可以是预测选择购买新节能灯泡而不是传统白炽灯泡的人的百分比。通过对调查响应的统计评估，模型可以识别决策过程中的关键驱动因素;例如，人们相互模仿的程度。这些模型使我们能够将社会互动的影响纳入其中，可以帮助我们在社会层面上确定“临界点”。这些知识可以用来引发我们社会的结构性变化。研究结果可为决策者提供切实可行的循证政策选择。我们相信，这些模型为社会科学和物理科学的研究界以及私营和公共部门的决策者提供了一个机会，共同努力防止气候变化对社会、经济和环境的潜在破坏性影响。
英文摘要：
Promoting and increasing energy efficiency is a promising method of reducing CO2 emissions and avoiding the potentially devastating effects of climate change. The question is: How do we induce a cultural or behavioural change whereby people nationally and globally adopt more energy efficient lifestyles? We propose a new family of mathematical models, based on a statistical mechanics extension of discrete choice theory, that offer a set of formal tools to systematically analyse and quantify this problem. An application example could be to predict the percentage of people choosing to buy new energy efficient light bulbs instead of the traditional incandescent versions. Through statistical evaluation of survey responses, the models can identify the key driving factors in the decision-making process; for example, the extent to which people imitate each other. These models allow us to incorporate the effect of social interactions could help us identify 'tipping points' at a societal level. This knowledge could be used to trigger structural changes in our society. The results may provide tangible and deliverable evidence-based policy options to decision-makers. We believe that these models offer an opportunity for the research community-in both the social and physical sciences-and decision-makers in the private and public sectors to work together towards preventing the potentially devastating social, economic and environmental effects of climate change.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
