ABSTRACT

There has been plenty of research on the influence of various socio-economic and demographic data on waste generation to develop effective and targeted waste reduction measures, including energy recovery. This study evaluates the relationship between the waste generation and Circular Material Use rate, Environmental Tax Revenue, and Global Innovation Index beyond the typical socio-economic factors (e.g., gross domestic product or population). Correlation analysis is conducted on the EU-27 datasets before the development of the predictive model. The correlation strength between the factors is discussed to identify the potential rebound effect from the central driver of economic growth and development. A positive correlation and partial rebound effect are identified in the data. The waste amount ending in disposal and energy recovery treatment increases with the Circular Material Use rate, suggesting that the expected gains from Circular Material Use rate are offset by other socio-economic factors such as increasing population or gross domestic product. However, a diminishing trend is observed in the rebound effect over the years. Multiple linear regression with validation is applied to identify the best fit model for predicting waste generation. Using population, gross domestic product, Circular Material Use rate, and Environmental Tax Revenues as independent variables, a model is generated with a mean absolute percentage error of 18.65% (7% lower than the benchmark) and R² (coefficient of determination) of 0.995.

摘要

有大量关于各种社会经济和人口数据对废物产生的影响的研究，以制定有效和有针对性的废物减少措施，包括能源回收。本研究评估了废物产生与循环材料使用率、环境税收和全球创新指数之间的关系，超出了典型的社会经济因素（例如，国内生产总值或人口）。在开发预测模型之前，对 EU-27 数据集进行相关分析。讨论了这些因素之间的相关强度，以确定经济增长和发展的核心驱动因素的潜在反弹效应。数据中确定了正相关和部分反弹效应。以处置和能源回收处理结束的废物量随着循环材料使用率的增加而增加，这表明循环材料使用率的预期收益被其他社会经济因素如人口增长或国内生产总值所抵消。然而，多年来反弹效应呈递减趋势。应用带有验证的多元线性回归来确定预测废物产生的最佳拟合模型。使用人口、国内生产总值、循环材料使用率和环境税收作为自变量，生成一个平均绝对百分比误差为 18.65%（比基准低 7%）的模型，并且 表明循环材料使用率的预期收益被其他社会经济因素所抵消，例如人口增长或国内生产总值。然而，多年来反弹效应呈递减趋势。应用带有验证的多元线性回归来确定预测废物产生的最佳拟合模型。使用人口、国内生产总值、循环材料使用率和环境税收作为自变量，生成一个平均绝对百分比误差为 18.65%（比基准低 7%）的模型，并且 表明循环材料使用率的预期收益被其他社会经济因素所抵消，例如人口增长或国内生产总值。然而，多年来反弹效应呈递减趋势。应用带有验证的多元线性回归来确定预测废物产生的最佳拟合模型。使用人口、国内生产总值、循环材料使用率和环境税收作为自变量，生成一个平均绝对百分比误差为 18.65%（比基准低 7%）的模型，并且R ² (决定系数)为0.995。