人口老龄化程度和碳排放:调解效应分析和多场景模拟分析
Shuyu Li1, Shun Jia1, Yang Liu1
1College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, PR China.
Journal of environmental management
|July 31, 2024
概括
人口老龄化通过各种影响影响碳排放,能源消耗和技术创新发挥了关键的缓和作用. 为了有效的气候治理,应将减排战略与区域老龄化水平进行调整.
科学领域:
- 环境科学 环境科学
- 人口统计学 人口统计学
- 经济学 经济学 经济学
背景情况:
- 全球可持续发展面临着人口老龄化增加带来的挑战.
- 准确测量衰老对碳排放的影响对于气候治理至关重要.
- 社会结构变化使对老龄化对排放的影响的评估变得复杂.
研究的目的:
- 探索人口老龄化对碳排放的影响的调解途径.
- 开发高精度预测模型,以模拟不同情景下的碳排放轨迹.
- 分析不同因素对人口老龄化中的碳排放的缓解效应.
主要方法:
- 构建了一个双向固定空间德宾模型来分析衰老对碳排放的影响.
- 开发并使用MNGM-ARIMA和MNGM-BPNN模型进行高精度的碳排放预测.
- 在多因素驾驶场景下模拟碳排放演变轨迹.
主要成果:
- 人口老龄化通过能源障碍,工业结构,消费增强,技术进步和劳动参与效应影响碳排放.
- 能源消耗 (10.74%) 和技术创新 (10.24%) 在衰老过程中显著减轻碳排放,而工业结构和劳动力参与率的影响较弱.
- 预测模型实现了超过97%的适合度;碳排放量在高衰老地区 (能源驱动的场景除外) 一般下降,在R&D和劳动力供应场景下,中低衰老地区缓慢下降.
结论:
- 建议采取针对区域老龄化程度的多样化减排措施.
- 加快供给侧升级和增加绿色消费是推的战略.
- 了解衰老和碳排放之间的复杂相互作用对于有效的气候政策至关重要.
相关概念视频
Mechanistic Models: Compartment Models in Individual and Population Analysis
35
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
35
Applications of Life Tables
57
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
57
Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
The Scientific Method
59.3K
Research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.
59.3K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
42
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
42
Statistical Methods for Analyzing Epidemiological Data
342
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
342


