Examining the Driving Factors of Urban Residential Carbon Intensity Using the LMDI Method: Evidence from China's County-Level Cities.
Examining the Driving Factors of Urban Residential Carbon Intensity Using the LMDI Method: Evidence from China's County-Level Cities.
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DOI：
10.3390/ijerph18083929
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发表时间：
2021-04-08
影响因子：
--
通讯作者：
Liu Q
中科院分区：
文献类型：
--
作者：
Zhao J;Liu Q
提高碳效率、降低碳强度是减缓气候变化的有效手段。城市住宅能源消耗造成的碳排放量大幅增加，但目前缺乏对城市住宅碳强度的研究。本文分析了2001-2015年中国30个省份620个县级城市居民部门碳强度的时空变化特征，并利用对数平均Divisia指数（LMDI）分析了其变化原因。结果表明，我国碳强度较高的城市主要集中在北京、天津、上海等大城市。然而，这些城市的碳强度呈下降趋势。在影响因素方面，人均能源消费、城市扩张和土地需求是决定碳强度变化的三个最具影响力的因素。人均能源消费的影响主要是增加碳强度，其影响在省会城市市辖区高于其他类型城市。同样，城市蔓延效应也促进了碳强度的增加，并且在大城市中出现了更高程度的影响。然而，随着城市扩张的稳定，城市蔓延的影响会减弱。土地需求效应降低了碳强度，而且大城市土地需求效应对碳强度的影响程度也明显更强。研究结果表明，降低人均能源消费和优化土地利用结构是合理的努力方向，降低碳强度应重视影响因素差异的影响。
Improving carbon efficiency and reducing carbon intensity are effective means of mitigating climate change. Carbon emissions due to urban residential energy consumption have increased significantly; however, there is a lack of research on urban residential carbon intensity. This paper examines the spatiotemporal variation of carbon intensity in the residential sector during 2001–2015, and then identifies the causes of the variation by utilizing the logarithmic mean Divisia index (LMDI) with the help of Microsoft Excel 2016 for 620 county-level cities in 30 Chinese provinces. The results show that high carbon intensity is mainly found in large cities, such as Beijing, Tianjin, and Shanghai. However, these cities showed a downward trend in carbon intensity. In terms of influencing factors, the energy consumption per capita, urban sprawl, and land demand are the three most influential factors in determining the changes in carbon intensity. The effect of energy consumption per capita mainly increases the carbon intensity, and its impact is higher in the municipal districts of provincial capital cities than in other types of cities. Similarly, the urban sprawl effect also promotes increases in carbon intensity, and a higher degree of influence appears in large cities. However, as urban expansion plateaus, the effect of urban sprawl decreases. The land-demand effect reduces the carbon intensity, and the degree of influence of the land-demand effect on carbon intensity is also clearly stronger in big cities. Our findings show that lowering the energy consumption per capita and optimizing the land-use structure are a reasonable direction of efforts, and the effects of differences in influencing factors should be paid more attention to reduce carbon intensity.
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