Fujian Engineering and Research Center of Rural Sewage Treatment and Water Safety, School of Environmental Science and Engineering, Xiamen University of Technology, Xiamen, 361024, China.
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China.
Environ Sci Pollut Res Int. 2024 Feb;31(10):15424-15442. doi: 10.1007/s11356-024-32165-9. Epub 2024 Feb 1.
This study develops a novel Taguchi-STIRPAT input-output (TSIO) model for exploring pathways to reduce carbon emission from the perspective of household consumption, through incorporating input-output model (IOM), Taguchi design (TD), and STIRPAT model. TSIO can not only identify the main factors (carbon emission intensity, consumption structure, per capita consumption, and population) and evaluate their effects on indirect household carbon emissions (IHC), but also predict IHC from a long-term perspective to achieve the dual-carbon target. TSIO is then applied to Fujian province (China), where multiple scenarios related to multiple factors with multiple levels are examined. Results reveal that (i) among all sectors, the highest contributors to IHC are residence (RES), followed by food, cigarettes, and drinks (FCD), and transport and communication (TC); it is suggested that the government can consider market mechanism to control these high-carbon emission consumption behaviors; (ii) the decline in the share of RES consumption has the largest effect on rural and urban IHC; the share of RES consumption is considered to be a key factor in predicting carbon emissions; (iii) under the optimal scenario, IHC would peak in 2025 and decrease to 10.07 × 10 ton in 2060; this scenario can effectively mitigate household carbon emissions by reducing carbon emission intensity and the share of RES consumption; at the same time, it can ensure a sustained increase in per capita consumption. The results unveil the pathways of household carbon reduction under the dual-carbon target in Fujian province and suggest the local government should adopt policies (such as taxation and financial incentives) to limit residential consumptions with high carbon emission intensity.
本研究开发了一种新颖的 Taguchi-STIRPAT 投入产出（TSIO）模型，通过纳入投入产出模型（IOM）、田口设计（TD）和 STIRPAT 模型，从家庭消费的角度探索减少碳排放的途径。TSIO 不仅可以识别主要因素（碳排放强度、消费结构、人均消费和人口）并评估它们对间接家庭碳排放（IHC）的影响，还可以从长期角度预测 IHC，以实现双碳目标。然后，将 TSIO 应用于中国福建省，研究了与多个因素和多个水平相关的多个情景。结果表明：（i）在所有部门中，对 IHC 贡献最大的是居住（RES），其次是食品、香烟和饮料（FCD）以及交通和通讯（TC）；建议政府可以考虑利用市场机制来控制这些高碳排放消费行为；（ii）RES 消费份额的下降对农村和城市 IHC 的影响最大；RES 消费份额被认为是预测碳排放的关键因素；（iii）在最优情景下，IHC 将在 2025 年达到峰值，并在 2060 年降至 10.07×10 吨；该情景可以通过降低碳排放强度和 RES 消费份额来有效减少家庭碳排放；同时，可以确保人均消费持续增长。研究结果揭示了福建省在双碳目标下家庭减排的途径，并建议地方政府应采取政策（如税收和财政激励）来限制具有高碳排放强度的住宅消费。
