基于STRPAT模型的碳排放情景分析

Scenario Analysis on carbon Emission Based on the STIRPAT model

摘要:

科学合理预测碳排放发展,对建设低碳城市具有重要的指导意义。本文以东莞市为例,采用基于扩展STIRPAT模型,通过岭回归拟合得到碳排放量与GDP、人口、城市化、人均消费支出、工业化及能源利用效率的多元线性模型,在此基础上,根据低碳社会发展各个不同阶段设定基准情景、低碳情景、节能情景等3种情景,对碳排放量进行预测及减排潜力分析。结果表明,人口数量对碳排放的影响最大,城市化率影响最小,碳排放量在基准情景下预计2020年为8246t,2025年达到8177t,而节能情景、低碳情景碳排放量均有不同程度的下降,在低碳发展的政策措施及一系列低碳发展行动与技术支撑下,东莞市碳排放仍具有较大的减排潜力。

关键词:STIRPAT;岭回归;碳排放;情景分析

Abstract:

It is of great guiding significant to prediction the carbon emission development for construction of low-carbon cities. Taking Dongguan City as an example, This paper built a expanded STIPRAT-based multivariate linear model fitted by a ridge regression to examine the relationship between carbon emissions and GDP, population, urbanization, per capita consumption expenditure, industrialization and energy efficiency. OnSthisSbasis, three scenarios: Business as Usual Scenario,Energy-saving Scenario,Low-carbon Scenario were set.we forecast carbon emission and analyze the emission reduction potential according to the different stages of the development of a low-carbon society. The results showed that the population had the greatest influence on carbon emission and urbanization rate has the least impact,SCarbon emissions are expected to be 8246t in 2020 and 8177t in 2025 under the Business as Usual Scenario, While carbon emissions have a different degree of decline on Energy-saving Scenario,Low-carbon Scenario. SDongguan city still has a great potential for carbon emission reduction for the Ssupport of low-carbon development policies and a series of low-carbon development actions and technologies.

Key words:STIRPAT; ridge regression; carbon emissions; scenario analysis