中國四大城市群碳排放驅(qū)動因素時空分解研究

doi:10.12006/j.issn.1673-1719.2023.148

摘要/Abstract

摘要：

城市群是中國經(jīng)濟發(fā)展和能源消耗的集聚區(qū)域，也是碳排放的主要來源。研究中國典型城市群碳排放的時空演變特征及其影響因素對實現(xiàn)“雙碳”目標具有重要意義。文中應用ST-IDA模型（時空指數(shù)分解分析法）和LMDI（對數(shù)平均迪氏指數(shù)法）分解法，分析2000—2019年京津冀、長三角、珠三角和成渝城市群的碳排放驅(qū)動因素（人口規(guī)模、經(jīng)濟水平、產(chǎn)業(yè)結(jié)構(gòu)、能源強度和能源結(jié)構(gòu))。研究發(fā)現(xiàn)：2000—2019年間，四大城市群能源活動碳排放總體趨勢均由高速增長階段步入平穩(wěn)增長階段，其中成渝城市群已基本實現(xiàn)碳達峰；能源強度效應是影響碳排放空間差異的主要因素；人口規(guī)模擴張、經(jīng)濟發(fā)展水平提高和能源強度上升是促進碳排放增長的主要因素，產(chǎn)業(yè)結(jié)構(gòu)和能源消費結(jié)構(gòu)優(yōu)化起到抑制作用；四大城市群碳排放的時空演變主要取決于工業(yè)部門。鑒于四大城市群呈現(xiàn)出不同的碳排放特征，未來應探索差異化、多元化的城市群減排路徑，促進城市群碳減排。

關(guān)鍵詞: 碳排放, 驅(qū)動因素, ST-IDA模型, 時空分解, 城市群

Abstract:

Urban agglomerations are the agglomerations of China’s economic development and energy consumption, as well as the main source of carbon emissions. The study of the spatial-temporal evolution characteristics and driving factors of carbon emissions in China’s typical urban agglomerations is of great significance for the achievement of carbon peaking and carbon neutrality goals. The carbon emission driving factors (population size, economic level, industrial structure, energy intensity and energy structure) of Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta and Chengdu-Chongqing urban agglomerations were analyzed by using ST-IDA model and LMDI decomposition method. The results are as follows. During 2000-2019, the overall trend of CO₂ emissions from energy activities in the four major urban agglomerations stepped from the “high growth stage” to the “stable growth stage”, among which the Chengdu-Chongqing urban agglomeration have basically achieved the carbon peak; The energy intensity effect is the main factor affecting the spatial differences in carbon emissions; The expansion of population size, the increase of economic development level and the rise of energy intensity are the main factors contributing to the growth of carbon emissions in the four major urban agglomerations, while the optimization of industrial structure and energy consumption structure plays a suppressive role; The spatial and temporal evolution of carbon emissions in the four major urban agglomerations depends mainly on the industrial sector. Since the four major urban agglomerations present different carbon emission characteristics, differentiated and diversified emission reduction paths should be explored in the future to promote carbon emission reduction in urban agglomerations.

Key words: Carbon emissions, Driving factors, ST-IDA model, Spatial-temporal decomposition, Urban agglomerations

劉元欣, 賀鑠, 江雅婧, 羅旭, 袁家海. 中國四大城市群碳排放驅(qū)動因素時空分解研究[J]. 氣候變化研究進展, 2024, 20(2): 231-241.

LIU Yuan-Xin, HE Shuo, JIANG Ya-Jing, LUO Xu, YUAN Jia-Hai. Spatial-temporal decomposition of carbon emissions in China’s four major urban agglomerations[J]. Climate Change Research, 2024, 20(2): 231-241.

圖/表 5

圖1 2000—2019年中國碳排放總量及增長率

Fig. 1 Total carbon emissions and growth rate in China from 2000 to 2019

圖2 2000—2019年四大城市群碳排放變化(a)及各階段增長率(b)

Fig. 2 Changes (a) and growth rates (b) of carbon emissions in four major urban agglomerations from 2000 to 2019

圖3 2000—2019年四大城市群碳排放空間分解結(jié)果

Fig. 3 Spatial decomposition of carbon emissions in four urban agglomerations from 2000 to 2019

圖4 2000—2019年四大城市群能源結(jié)構(gòu) 注：數(shù)據(jù)來自于各市《統(tǒng)計年鑒》。

Fig. 4 Energy structure of four major urban agglomerations from 2000 to 2019

圖5 2000—2019年四大城市群碳排放時間分解結(jié)果

Fig. 5 Temporal decomposition of carbon emissions in four major urban agglomerations from 2000 to 2019

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