The spatio-temporal distribution response on building heating energy consumption of cities along “the Belt and Road” in Western China under multifactorial impact
YANG Wen1,2, ZHANG Guanjie2,LI Zhaoming2, ZHENG Heshan2, LIU Jiaping1,2
(1.State Key Laboratory of Green Building in Western China, Xi'an 710055, China; 2.School of Architecture, Xi'an Univ. of Arch. & Tech., Xi'an 710055, China)
In order to describe the spatial-temporal distribution response characteristics on the buildings heating energy consumption of cities along the “the Belt and Road” in western China under multifactorial impact, the spatial distribution law of heating energy consumption of buildings from 2010 to 2020 was obtained through spatial correlation analysis, and the standard deviation ellipse analysis method was used to describe the temporal evolution pattern of spatial distribution. Based on STIRPAT, a mathematical model is established to reveal the regular characteristics of building heating energy consumption affected by various factors(total population, urbanization rate, per capita area, tertiary industry growth index and technological innovation level).The results show that there is a spatial effect on the intensity and total amount of heating energy consumption in cities along “the Belt and Road” in western China, which is still in an unbalanced development stage. The weight distribution of influencing factors is also different. Except Qinghai, the main driving force of the total building heating energy consumption of provinces and autonomous regions along “the Belt and Road” in western China is the per capita building heating area. The main driving force of the building heating energy consumption intensity in Gansu, Ningxia and Qinghai is the level of technological innovation. The research results are expected to provide some support for the formulation of relevant policies.
图2 2010—2020年西部“一带一路”沿线省份及自治区的建筑能耗 Fig.2 Building energy consumption of provinces and autonomous regions along “the Belt and Road” in Western China from 2010 to 2020
图3 2010—2020年西部“一带一路”沿线省份及自治区的建筑供热能耗 Fig.3 Building heating energy consumption of provinces and autonomous regions along “the Belt and Road” in Western China from 2010 to 2020
图4 2010—2020年西部“一带一路”沿线省份及自治区的建筑供热能耗与建筑能耗对比 Fig.4 Comparison of building heating energy consumption and building energy consumption of provinces and autonomous regions along “the Belt and Road” in Western China from 2010 to 2020
图5 2010—2020年西部“一带一路”沿线城市建筑供热能耗总量空间分布 Fig.5 Spatial distribution of total heating energy consumption of urban buildings along “the Belt and Road” in Western China from 2010 to 2020
图6 2010—2020年西部“一带一路”沿线城市建筑供热能耗强度空间分布 Fig.6 Spatial distribution of heating energy consumption intensity of urban buildings along “the Belt and Road” in Western China from 2010 to 2020
表1 2010—2020年西部“一带一路”沿线城市的建筑供热能耗Moran's I指数 Tab.1 Moran's I index of building heating energy consumption in cities along “the Belt and Road” in Western China from 2010 to 2020
图7 典型年份西部“一带一路”沿线城市建筑供热能耗强度的莫兰散点图 Fig.7 Moran scatter diagram of heating energy consumption intensity of urban buildings along “the Belt and Road” in Western China in typical years
图8 2010—2020年西部“一带一路”沿线城市建筑供热能耗重心和标准差椭圆轨迹变化 Fig.8 Changes in the center of gravity and standard deviation ellipse of heating energy consumption of urban buildings along “the Belt and Road” in Western China from 2010 to 2020
表3 岭回归分析下西部“一带一路”沿线省份及自治区建筑供热能耗影响因素的权重分布 Tab.3 Weight distribution of factors influencing building heating energy consumption of provinces and autonomous regions along “the Belt and Road” in Western China under ridge regression analysis
表4 逐步回归分析下西部“一带一路”沿线省份及自治区建筑供热能耗影响因素的权重分布 Tab.4 Weight distribution of factors influencing building heating energy consumption of provinces and autonomous regions along “the Belt and Road” in Western China under stepwise regression analysis
ZHOU Jie. A study on the spatial and temporal distribution and influencing factors of energy intensity in China's construction industry [D]. Xi'an:Chang'an University, 2020.
SUN Hailing, WANG Hongping. Research on driving factors of urban building energy consumption growth based on ridge regression [J]. Research on Urban Development, 2013,20(5): 21-24.
LIU Xiaojun, HU Shengkai, LI Lingyan. Spatial and temporal distribution of building energy consumption in China's provinces and regions and analysis of influencing factors [J]. Mathematical Practice and Understanding, 2020,50(6): 74-85.
ZHAO Lu, ZHAO Zuoquan, WANG Wei. Changes in the economic spatial pattern of the eastern coastal areas of China [J]. Economic Geography, 2014, 34(2): 14-18,27.
HAN Meng. Coal consumption prediction and energy conservation potential analysis of central heating in northern provinces of China under urbanization [D]. Xuzhou:China University of Mining and Technology, 2014.
