The Stimulation and Coordination Mechanisms of the Carbon Emission Trading Market of Public Buildings in China

Li, Lingyan; Duan, Mimi; Guo, Xiaotong; Wang, Yao

doi:10.3389/fenrg.2021.715504

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…According to statistics, electricity consumption accounts for 60% of the total energy consumption of medical facilities [19]. By analyzing existing research data [25] and the energy consumption limit specification of comprehensive medical institutions in various regions [25][26][27], the annual per capita power consumption limit was used as the evaluation index to compare the design reference and the actual consumption values [28], as shown in Table 4. Through the data in Table 4, it can be seen that the H16-H18 and H20-H22 hospitals have built energy intelligent management platforms to adjust the energy consumption of different types in real time, and their actual energy consumption values have obvious advantages compared with other hospitals.…”

Section: Natural Gas Consumptionmentioning

confidence: 99%

Carbon Emission Accounting Model for Comprehensive Medical Facilities Based on Population Flow

Yan,

Luo,

Chen

et al. 2024

Buildings

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China is striving to reach a peak in its carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. The accurate accounting of carbon emissions is important for achieving these dual carbon goals. An extensive literature review and field measurements were conducted to investigate the specific impact of population density on carbon emissions in large integrated healthcare organizations. This research uses VOSviewer to visualize the literature analysis. We determined that the flow of people is a key factor affecting carbon emissions during the operational phase of large-scale comprehensive medical institutions. Through field measurements, the relationship between the density of pedestrian flow and indoor environment measurements was derived, and the incremental equipment operating loads caused by changes in the indoor environment were analyzed. Using the carbon emission factor method advocated by the IPCC, a carbon emission accounting model based on different flow intervals was constructed, and the energy consumption of different equipment was fully considered according to its proportion. The validation results showed that the error between the calculated value and the actual values of the model was 3.07% (less than 5%), which has good validity. The model calculates the direct and indirect carbon emissions in the operational phase based on the population flow perspective, which can provide a reference for the energy-saving design and green operation of large-scale comprehensive medical institutions. The research will continue to focus on the population flow, and the accounting model will be further optimized through machine learning algorithms.

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Section: Natural Gas Consumptionmentioning

confidence: 99%

Carbon Emission Accounting Model for Comprehensive Medical Facilities Based on Population Flow

Yan,

Luo,

Chen

et al. 2024

Buildings

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show abstract

“…Therefore, the low-carbon development of the construction industry is closely related to the realization of the "two-carbon" goal. Carbon emissions from public buildings [7][8][9] are the most dominant category of building carbon emissions, mainly from office buildings, hotels, shopping malls, health care centres, educational institutions, and other buildings, so its peak research is the key link in our "double carbon" work. There is a significant gap in the development speed between the coastal regions and the central and western regions of China.…”

Section: Introductionmentioning

confidence: 99%

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

Yangwen

Gong

et al. 2023

Sustainability

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With the continuous development of the social economy, carbon emissions from various buildings are increasing. As the most important category of building carbon emissions, the rapid peaking of public buildings is an important part of achieving carbon peak and carbon neutrality. This paper is based on the industrial background of the energy consumption structure of Henan Province, a central province in the developing country of China. Firstly, the energy consumption intensity of buildings and public buildings in Henan Province from 2010 to 2020 was calculated according to the energy balance sheet. The Kaya–LMDI decomposition method was also used to analyse the carbon emissions of public buildings, determining the impact of each influencing parameter on public buildings. Secondly, the scenario prediction model Monte Carlo was run 100,000 times to set the stochastic parameters of the variables in the model to predict the time of carbon peak and carbon emissions. The analysis results indicated that: ① Carbon emissions in Henan Province have exhibited a steady growth trend, increasing from 1533 t in 2010 to 6561 t in 2020; ② The primary factors influencing carbon emissions of public buildings in Henan Province were urbanization rate, public floor area per capita, and energy intensity per unit of public floor area; and ③ Carbon emissions of public buildings in Henan Province followed an inverted U-shaped distribution and are expected to peak at approximately 7423 t by the year 2035. The research method in this paper can guide the simulation study of peak carbon emission prediction in Henan Province based on the influencing parameters of carbon emission from different types of buildings. Moreover, the results of this paper can provide a reference for a more precise study of building carbon reduction in similar regions of developing countries.

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“…At present, many scholars [15][16][17][18] have carried out research work in the accounting method of carbon emissions, the spatial research of carbon emissions, and the relationship between lighting brightness and energy. Some achievements have been made, but there are limitations, as follows:…”

Section: Introductionmentioning

confidence: 99%

An Estimating Method for Carbon Emissions of China Based on Nighttime Lights Remote Sensing Satellite Images

et al. 2022

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In September 2020, China proposed the achievement of the emission reduction targets of “carbon peak” and “carbon neutral” by 2030 and 2060, respectively. As an important area of energy consumption in addition to industry and transportation, the construction industry has great energy-saving potential and is gradually becoming the key to achieving China’s energy-saving and emission-reduction goals. Energy data is an important basic support for measuring carbon emissions, analyzing energy-saving potential, and formulating energy-saving targets. In order to solve the he lack of data on China’s carbon emissions, this paper uses lamplight remote sensing image data in the study. Combined with China’s eastern, central, and western regions of building carbon emissions data and the establishment of a partition of China building carbon emissions calculation model, panel data found building carbon emissions and smooth lamp brightness values between the balanced relations. After that, using the building carbon emissions models of the three regions, the building carbon emissions of 30 provinces, 360 cities, and 2778 counties in China were measured, and the changing trends and temporal and spatial directions of building carbon emissions at three spatial scales were analyzed. The results showed that although the total carbon emissions of civil buildings in China has been increasing year by year, its average annual growth rate is gradually slowing down. In addition, the temporal and spatial development directions of carbon emissions from buildings of different spatial scales are basically the same, and they all show a trend of shifting to the east.

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The Stimulation and Coordination Mechanisms of the Carbon Emission Trading Market of Public Buildings in China

Cited by 6 publications

References 25 publications

Carbon Emission Accounting Model for Comprehensive Medical Facilities Based on Population Flow

Carbon Emission Accounting Model for Comprehensive Medical Facilities Based on Population Flow

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

An Estimating Method for Carbon Emissions of China Based on Nighttime Lights Remote Sensing Satellite Images

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