Evaluating Carbon-Emission Efficiency in China’s Construction Industry: An SBM-Model Analysis of Interprovincial Building Heating

By inergency On Mar 14, 2024

4.1. DEA Result

Utilizing DEA Solver software (Dea solver Pro 5.0), the input–output analysis is conducted for each province to determine the carbon-emission efficiency of the buildings. Furthermore, in order to delineate the variations in heating across China, the regional carbon-emission efficiency is further segmented based on the provincial and municipal regional divisions in China. This paper delineates the northern region by using Qinling Mountains–Huaihe River as the boundary and the provincial administrative unit as the basic unit, taking into account economic and geographic factors [44,45,46]. The northern region includes 15 provinces, municipalities directly under the central government, and the following autonomous regions: Heilongjiang, Jilin, Liaoning, Inner Mongolia, Hebei, Beijing, Tianjin, Shaanxi, Shanxi, Ningxia, Gansu, Qinghai, Shandong, Henan, and Xinjiang. The southern region comprises 15 provinces, municipalities directly under the central government, or autonomous regions, including Jiangsu, Zhejiang, Shanghai, Anhui, Hubei, Hunan, Jiangxi, Sichuan, Chongqing, Guizhou, Yunnan, Guangxi, Fujian, Guangdong, and Hainan. The measured values are presented in Table 2. The calculated values and trends after excluding the influence of northern heating are shown in Table 3. In order to better demonstrate the inter-provincial differences in building heating, the distribution map of China’s buildings’ carbon-emission efficiency values is shown in Figure 1. (The right-hand column of the figure shows the national carbon efficiency of buildings excluding the effects of central heating). The average regional carbon efficiency is shown in Figure 2.

The combination of Table 2 and Figure 1 reveals that the buildings’ carbon-emission efficiency in Jiangsu, Zhejiang, Shanghai, Qinghai, Sichuan, and Chongqing consistently surpasses that of other regions in the country across all years. Additionally, these regions exhibit smaller annual fluctuations. The distribution map of China’s buildings’ carbon-emission efficiency values indicates that, overall, the northern region has lower building carbon-emission efficiency compared to the southern region. This phenomenon could be attributed to the significant reliance on fossil fuels in the northern region, coupled with the low efficiency of carbon emissions from buildings during winter heating. As shown in Table 3 and Figure 1, after excluding the carbon dioxide emissions caused by central heating in the northern region, it can be found that the average carbon emission efficiency in the northern region has increased, with the average efficiency in Ningxia reaching an effective level.

Overall, there has been a consistent increase in national construction’s carbon emission efficiency from 2005 to 2021, and the annual change trend of carbon-emission efficiency in the construction industry is similar in both the northern and southern regions. Between 2005 and 2008, there was a general upward trend in carbon emissions, primarily attributed to the rapid economic development of China during this period and the substantial investment in infrastructure construction, leading to an increase in carbon emissions. Following the economic crisis of 2008, economic growth decelerated, while construction activities continued to rise. Following the economic crisis in 2008, China experienced a deceleration in economic growth and construction speed, a decrease in carbon-emission efficiency, and fluctuating emission efficiency after 2008. The average carbon-emission efficiency and ranking of buildings from 2005 to 2021 is shown in Table 4.

Only nine provinces and cities, including Hainan, Beijing, Chongqing, Shanghai, Jiangsu, Qinghai, Sichuan, Shandong, and Zhejiang, have achieved an effective outcome. Hainan Province exhibits the highest average building-emission efficiency due to its tropical monsoon climate, resulting in an average annual temperature exceeding 20 °C and abundant light. The region also possesses various types of renewable energy resources, leading to the gradual replacement of traditional fossil energy with clean energy. In 2021, wind, solar, hydro, and other forms of power generation accounted for 32.33% of the total power generation. Qinghai Province demonstrates a superior performance in carbon-emission efficiency compared to other northwestern provinces, a result that can be attributed to its geomorphology and climate. Qinghai Province features a typical plateau continental climate characterized by low precipitation, dryness, strong winds, cold temperatures, extended periods of sunshine, and ample solar- and wind-energy resources. Consequently, residential buildings in this region do not heavily depend on fossil energy for heating.

Beijing, Chongqing, and Shanghai are three municipalities directly under the central government, and they are leading the efforts in energy conservation and emission-reduction publicity work and technology in the country. In 2014, “Interim Measures for the Management of Financial Incentive Funds for Developing Green Buildings” and “Promoting the Construction of Green Ecological Demonstration Areas in Beijing” were issued [47]. These measures established “Beijing Development of Green Buildings and Promoting the Construction of Green Ecological Demonstration Areas Incentive Funds”, which aims to provide incentives for public and residential building projects that have obtained the two- or three-star green building-operation label. The audited projects include public and residential buildings, as well as green eco-demonstration zones, that have met the specified criteria. As of December 2019, the total construction area of projects that have adopted green building standards in Beijing is close to 250 million m². Among these, approximately 75.86 million m² of green construction area has been finished. In the city, 409 projects have obtained certification with green building labels, encompassing a construction area of 47.18 million m². Furthermore, 93% of the construction area belongs to projects with a two-star rating or higher, including 52 operational labels and 357 design labels. In 2020, Beijing Municipal Commission of Housing and Urban-Rural Development (BCHURD), in collaboration with Municipal Planning and Natural Resources Commission (MPNRC) and the Municipal Finance Bureau (MFB), released “Interim Measures for the Management of Municipal Reward Funds for Projects” [47] related to Beijing’s assembly buildings, green buildings, and green ecological demonstration zones, with the aim of promoting their high-quality development [48]. By the conclusion of the “13th Five-Year Plan”, Chongqing Municipality has overseen the execution of 24,413,500 m² of high-star green buildings and 106,427,700 m² of green ecological residential communities. The percentage of green buildings in the urban areas of the city has risen to 57.2% in terms of new construction. The total area of energy-efficient buildings has reached 679 million m², and the utilization of renewable energy buildings has surpassed 15 million m². The installed area of renewable energy applications has surpassed 15 million m². Meanwhile, the Chongqing Municipality has actively promoted the advancement of sustainable buildings, investigating near-zero energy usage, low-carbon (zero-carbon) structures, and constructing the inaugural “zero-carbon cabin” in Chongqing in 2020. Shanghai has provided policy and financial incentives for ultra-low-energy buildings, carried out energy-saving renovations on public buildings covering an area of 16 million m², and advanced 42 ultra-low-energy building projects covering approximately 3.5 million m². The city’s system for monitoring buildings’ energy consumption encompasses 2100 buildings and 99 million m². These policies and measures have significantly contributed to enhancing the efficiency of reducing carbon emissions in buildings.

4.2. Influence Factors of Carbon-Emission Efficiency Based on the Tobit Regression

Based on the regional differences in the carbon-emission efficiency of centralized heating in buildings, this research uses the Tobit regression model to analyze its influencing factors. Based on the existing literature, factors such as science and technology levels, regional economic scale, government intervention, and industrial structure are selected as factors that affect the carbon-emission efficiency of centralized heating in buildings.

(1): Science and technology levels:

The differences in scientific and technological levels lead to differences in centralized heating technology, equipment, and modes, affecting carbon-emission efficiency [49,50,51,52,53,54]. The level of science and technology is often reflected in the level of research and development investment. Jun and Li et al. pointed out in 2023 that increasing investment in technology can significantly improve the carbon-emission efficiency of urban industries [55]. Wang and Zhao et al. found in 2019 that R & D investment plays an important role in carbon dioxide reduction [56]. This article uses the proportion of local fiscal science and technology expenditure to GDP as an indicator to measure the level of science and technology.

(2): Regional economic scale:

Different regions have different industrial development characteristics and economic levels. This research uses the proportion of regional GDP to national GDP to represent the scale of regional economy

(3): Government intervention:

The government’s macroeconomic regulation policies can affect resource allocation and industrial transfer between regions, indirectly affecting carbon emissions. This article uses the proportion of local fiscal expenditure to GDP as an indicator of government intervention level.

(4): Industrial structure:

The intensity of energy consumption varies significantly among different industries, and the industrial structure is a factor that affects the carbon-emission efficiency of centralized heating in buildings. Therefore, this research takes the proportion of local added value of the tertiary industry to GDP as an indicator of industrial structure.

The specific content of the influencing factors is shown in Table 5:

4.4. Tobit Regression Results

In summary, this article evaluates the impact of the above influencing factors on buildings’ carbon dioxide-emission efficiency, and constructs a Tobit regression model as

{e f f i c i e n c y}_{i, t} = β_{0} + β_{1} X_{i t} + β_{2} X_{i t} + β_{3} X_{i t} + β_{4} X_{i t} + u_{i t}

. The results of each parameter calculated through StataMP 15 are as follows (see Table 7).

According to the regression coefficient of 11.719, the level of science and technology is directly related to the carbon-emission efficiency of centralized heating in buildings at the 1% level. A building’s centralized heating system is more efficient at reducing carbon emissions the higher its level of science and technology. The regional economic level is significant at the 1% level, with a regression coefficient of 7.5717. This indicates that the higher the regional economic level, the more helpful it is to reduce regional buildings’ carbon emissions. Based on the super efficiency SBM-DEA, economically developed regions like Beijing, Shanghai, Jiangsu Province, etc., have a higher efficiency of carbon emissions, while economically underdeveloped regions like Gansu, Inner Mongolia, etc., have a lower efficiency of carbon emissions. Government intervention has a significant negative impact on buildings’ carbon-emission efficiency. Excessive government intervention in the economy is not conducive to improving carbon-emission efficiency. There is a non-significant negative correlation between industrial structure and buildings’ carbon-emission efficiency, which only affects carbon-emission efficiency to a certain extent.

Consistent with existing research findings, in regions rich in renewable energy, there is enormous potential for buildings’ carbon-emission reduction [59], and buildings’ heating dependence on fossil fuels is relatively low. The policy has promoted the transformation of buildings towards low carbon [60], and buildings’ carbon-emission changes are consistent with economic trends [61]. It is possible to reduce carbon emissions in regions abundant in renewable energy. The carbon emissions of the construction industry are also influenced by government policy support and economic development. Overall, in regions rich in renewable energy, buildings’ heating dependence on fossil fuels is relatively low. Policies play a negative role in influencing buildings’ carbon emissions in some cases, which is inconsistent with the conclusion that policies play a positive role in buildings’ carbon emissions [62,63].