Calculation and Analysis of Carbon Emissions in the Construction Industry of Zhejiang Province

— High rise buildings with large volume, high energy consumption, and high carbon emission base have become the focus of emission reduction work in public building types. The key issue of reducing carbon emissions throughout the entire lifecycle of high-rise buildings is how to predict their carbon emissions during the design phase, which is also a current research hotspot. As a developed province in southern China, Zhejiang bears important emission reduction tasks and responsibilities in the construction industry. This article applies the carbon emission factor method to calculate the carbon dioxide emissions in the construction sector of Zhejiang Province from 2005 to 2022. Based on Kaya's identity, a carbon emission calculation model is established. Combined with scenario analysis method, the carbon emissions in the construction sector of Zhejiang Province from 2023 to 2060 are predicted and compared under different scenarios. The results show that under the scenario of technological breakthrough, the construction field can achieve the carbon peak goal by 2025, but in order to achieve the carbon neutrality goal by 2060, the existing energy conservation measures and carbon reduction technologies need to be strengthened.


Introduction
Due to the burning of fossil fuels such as coal and oil by humans, or the deforestation and burning of forests, a large amount of carbon dioxide, known as greenhouse gases, is produced. Greenhouse gases have a high penetration of visible light from solar radiation and a high absorption of longwave radiation emitted by the Earth, which can absorb a large amount of infrared radiation from ground radiation, leading to the greenhouse effect on the Earth. At present, the scale of public buildings in China is constantly expanding due to the development of urban construction. The energy consumption and carbon emissions in the construction industry are growing rapidly, and the greenhouse effect is becoming increasingly serious. In order to implement the "13th Five Year Plan for Comprehensive Work on Energy Conservation and Emission Reduction" issued by the State Council, it is necessary to further promote carbon reduction and emission reduction work in the field of construction engineering. The large size, high energy consumption, and large carbon emission base of high-rise buildings have become the focus of emission reduction work in public building types. The key issue of reducing carbon emissions throughout the entire lifecycle of high-rise buildings is how to predict their carbon emissions during the design phase, which is also a current research hotspot. Construction, transportation, and industry are considered the three major areas of energy consumption [1]. According to the "China Building Energy Consumption Research Report (2021)", the total carbon dioxide emissions from the entire construction process in China in 2019 were 49 9.7 billion tons, accounting for 50% of the total carbon emissions in China 6%, of which the carbon dioxide emissions during the construction and operation stages are 100 million tons and 2.1 300 million tons, accounting for 22. 5% of the total carbon emissions in China 6%. It can be seen that in order to achieve the carbon neutrality commitment on schedule, the construction field will assume a very important responsibility for energy conservation and emission reduction. As an important city in southern China, Zhejiang Province needs to play a leading role in energy conservation and carbon reduction. In order to develop a carbon neutrality policy and control path supported by data, it is very necessary to calculate and predict the carbon emissions in the construction field of Zhejiang Province in the medium and long term.

Research findings
With the continuous intensification of climate change issues, countries around the world have raised their governance and attention to climate change issues to new heights. Carbon emissions in the construction industry have also become a common development issue facing the world, and have increasingly attracted the attention of domestic and foreign scholars. Relevant research content has also made certain progress. Pan Yiqun et al. [2] predicted and compared the carbon emissions in the construction sector of Zhejiang Province from 2020 to 2060 under different scenarios. Finally, based on the predicted results, they proposed energy-saving and emission reduction measures for the construction sector in Shanghai. Based on the statistical yearbook of Fujian Province, Chen Yiding [3] analyzed the influencing factors of carbon emissions in the construction industry in Fujian Province using the STIRPAT model. Liang Bo [4] analyzes the carbon emissions of urban buildings in Beijing from three perspectives: total and intensity of carbon emissions, main energy consumption varieties, and segmented industries, and predicts the development trend of carbon emissions in the construction industry under different scenarios. Wang Cuikun [5] said that with the continuous improvement of urbanization, the newly added building area is about 2 billion square meters every year, which poses a huge challenge to China's realization of the goal of "2060 carbon neutrality". Carbon reduction in the construction field has become the "key link" to achieve the goal of carbon peaking and carbon neutrality in China, which is of great significance to the all-round march towards a low-carbon society and the realization of highquality development. Based on the analysis of the current situation of carbon emission trading in the construction industry both domestically and internationally, Ling Jihong [6] and others explored the relevant issues of carbon emission trading in public buildings such as hospitals, commercial, government offices, schools, and hotels in Tianjin, with a focus on analyzing the quota and baseline determination methods for carbon emission trading in the construction industry. Ren Hong et al. [7] used comparative analysis to compare existing practices at home and abroad, and finally proposed a preliminary proposal to establish a framework for carbon emission trading in the construction industry in China from the aspects of emission reduction nature, total amount determination, implementation route, allocation method, etc., to provide support for promoting carbon emission trading in construction. Peng Mengyue [8] analyzed the current situation and practice of carbon emissions trading in the construction industry both domestically and internationally, explored the favorable conditions and obstacles faced by carbon emissions trading in China's construction industry, and proposed the feasibility, goals, strategies, and roadmap for the development of carbon emissions trading in China's construction industry.Yin Tao et al. [9] compared carbon emissions during the construction stage, building material production, and transportation stages, and concluded that the carbon emissions of prefabricated construction methods were lower than those of traditional cast-in-place construction methods. They also proposed relevant suggestions, which can serve as a reference for achieving green development in engineering construction. Yin Shuai et al. [10] elaborated on the trading principles and characteristics of building carbon emissions rights, and combined with the actual situation of carbon trading in the construction field at home and abroad, analyzed the obstacles in implementing carbon trading in the construction field in terms of carbon emission accounting, carbon emission system, and supporting measures, and proposed preliminary implementation suggestions for carbon trading in the construction field in three aspects: overall framework, system setting, and system guarantee. On the basis of sorting out and analyzing the current situation of methods for calculating the total amount of building energy consumption and carbon emissions in China, Fan Peihong [11] and other researchers have constructed a more optimized multi-channel method for calculating the total amount of building energy consumption and carbon emissions, calculated the total amount of building energy consumption and carbon emissions, and proposed policy suggestions for improving the calculation of building energy consumption and carbon emissions. Hu Shan et al. [12] defined the energy consumption and greenhouse gas emissions in China's construction industry, and established a model for building energy consumption and emissions in China. Based on statistical data and measured research data, they calculated the energy consumption and emissions of China's construction scale, construction and operation stages. Combining the characteristics of energy consumption and emissions in China's construction industry, they proposed policy recommendations for energy conservation and low-carbon development in the construction industry. In terms of model construction, the IPAT identification model was first proposed by Ehrlich et al. [13] in 1971 to reveal the impact of population growth, economic development and technological progress on the environment. Based on this model, the STIRPAT model [14] and Kaya identity were derived. Kaya [15] identity was proposed by Kaya at a seminar of the IPCC in 1989, which decomposes the driving factors of carbon emissions into population, per capita UDP, energy intensity and carbon dioxide emissions per unit energy consumption, It has become a mainstream analytical model for analyzing the driving factors of carbon emissions and the reasons for global historical emission changes.
Looking at the above research content, there have been relatively rich achievements in the research of building carbon emission model algorithms both domestically and internationally. However, for the carbon emissions in the provincial construction field, it is still in the exploratory stage, and reasonable predictions need to be made on population size effects, per capita occupied area, and building area. This article uses the emission factor method to calculate the carbon emissions in the construction field of Zhejiang Province and cities over the years, And based on the Kaya model, establish a carbon emission model for the construction industry in Zhejiang Province. Combining scenario analysis methods, predict the peak year of carbon emissions in the construction industry from 2023 to 2060 and the future annual carbon emissions in the construction industry in Zhejiang Province, providing a theoretical basis for future carbon emission calculations in this field.

Research method
The research method of this article mainly includes combining Kaya's identity with macro data to establish a carbon emission calculation model for the construction industry, service industry, and urban living consumption. In order to obtain the total control path of carbon emissions in the construction industry in Zhejiang Province from 2020 to 2060, scenario analysis method is applied to analyze the trend of carbon emission changes under different policy scenarios.

Establishing Kaya identities
Kaya identity decomposes the driving factors of carbon emissions into population, GDP per capita, energy intensity and carbon dioxide emissions per unit energy consumption. The specific formula is as follows: In the formula, C, P, G, and E respectively represent total carbon dioxide emissions, population, regional GDP, and energy consumption.
When establishing a carbon emission calculation model for the construction industry in Zhejiang Province, it is considered that the direct influencing factors of carbon emissions in the construction industry include building scale, energy consumption intensity, and carbon emission factors, while economic factors such as construction industry output value, added value of the tertiary industry, and urban residents' income all indirectly affect carbon emissions. Therefore, Kaya's identity can be simply modified, Make it more suitable for the calculation and research of carbon dioxide emissions and control paths in the construction field. After the formula is deformed, the total annual carbon dioxide emissions Ct in the construction field can be described as: (2) In the formula, Ci represents the total annual carbon dioxide emissions of each stage, in 10000 tons. When i =1,2,3, it represents the construction stage, public building operation stage, and urban residential building operation stage, respectively. Pi is the population, in 10000 people. When i =1, it represents construction workers, and when i =2,3, it represents urban population. Ai is the area, in 10000 square meters. When i =1, 2, and 3, they respectively represent the construction area, public building area, and urban residential building area. Ei is the energy consumption (standard coal) of each stage, in 10000 tons. APi is the per capita area, expressed in m2/person. When i =1, 2, and 3, they respectively represent the per capita construction area of construction workers, per capita urban public building area, and per capita urban residential building area. EAi is the unit area energy consumption intensity of each stage, in tons/m2. CEi is the comprehensive carbon emission coefficient of energy for each stage.
In equation (2), the per capita area Api is influenced by many factors, such as the population engaged in the construction industry, the size and structure of households, economic and social development trends, residential cultural values, real estate market behavior, etc. These factors have varying degrees of impact on the per capita area. Existing research shows that the per capita construction area is mainly related to the overall labor productivity of the construction industry, the per capita public building area is related to the added value of the tertiary industry, and the per capita residential building area is mainly related to the per capita disposable income level of residents. From this, it is possible to establish per capita area models corresponding to different stages.
In equations (3) to (5), F1 , F2 and F3 represent the total labor productivity of the construction industry, the added value of the tertiary industry, and the per capita disposable income of urban residents, respectively.

Scenario analysis method
Scenario analysis method is a systematic method for predicting and evaluating the future state of objects with high uncertainty. A more systematic explanation first appeared in the book "2000-A Framework for the Future 33 Year Conjecture" co authored by Kahn and Wiener in 1967. Different from the trend extrapolation idea of "past present future" in traditional prediction techniques, different scenario analysis methods construct possible future scenarios for the research object by assuming, predicting, and simulating the possible development trends of key driving forces, and evaluate various possible scenarios and their impacts. They use future information from various scenarios to analyze uncertainty and develop response measures.

Data sources
The data required for establishing the model studied in this article mainly includes two aspects: firstly, economic and social development data, such as total labor productivity of the construction industry, permanent population, added value of the tertiary industry, urbanization rate, per capita disposable income of urban residents, etc. This type of data is mainly sourced from the Zhejiang Provincial Statistical Yearbook; The second is carbon dioxide emissions data, which does not have direct statistical data and needs to be calculated based on the energy balance table in the China Energy Statistical Yearbook.
There are currently three internationally recognized accounting methods for carbon emissions, namely emission factor method, mass balance method, and measurement method. Among them, emission factor method is the accounting method applicable to building carbon emissions. Therefore, this study is based on the energy consumption data in the construction sector in the Zhejiang Energy Balance

Carbon emission factors for fossil fuels
The calculation of carbon emission factors for fossil fuels is based on public data queries. The UB/T 2589-2020 "Comprehensive Energy Consumption Calculation Guidelines" lists the average low calorific value of fossil fuels, and the "Guidelines for the Compilation of Provincial Greenhouse Gas Inventories" lists the carbon content and carbon oxidation rate data per unit calorific value. The formula for calculating the carbon emission factor of fossil fuels is: FEx = VALCx * Cpcvx * Rco * 3.667 * 10-6 (6) In the formula, FEx is the carbon emission factor (kg/kg) of fossil energy x, VALCx is the average low calorific value (kJ/kg) of fossil energy x, Cpcvx is the carbon content per unit calorific value (t/Tf), Rco is the carbon oxidation rate, and 3.667 is the molecular weight ratio of CO2 to C.

Electric carbon factor data
Electric energy is a secondary energy source, and its CO2 emission factor is closely related to the power generation structure, with strong regional characteristics. Therefore, the emission factors in this article are based on the data provided by the Zhejiang Provincial Technology Platform, as shown in Table 1. Among them, since there are only data on the carbon emission factors of Zhejiang electric power in 2011 and 2021, the missing data from 2005 to 2020 are estimated using the linear interpolation method.

Carbon emission accounting results
The current status of carbon emissions in the construction industry in Zhejiang Province is shown in Table 2. It can be seen that the carbon emissions during the construction stage, public buildings, and urban residential buildings completion stage account for over 95% of the carbon emissions in the construction field. Due to the similar trend of carbon emissions in the construction field in Zhejiang Province and the carbon emissions during the completion and operation stage, there is a curve trend of first increasing and then decreasing. The peak carbon emissions in the construction field in Zhejiang Province reached 111.6335 million tons in 2017.  Table 3 shows the carbon emissions from fossil fuels and electricity generated by the construction phase, urban residential completed buildings, and public completed buildings in the construction industry.  carbon emissions in the construction field will decrease year by year. On the whole, the carbon emissions in the construction field will increase first and then decrease. The reasons for the reduction of carbon emissions in recent years may be affected by the COVID-19 epidemic. From the perspective of energy structure, the proportion of carbon emissions from fossil fuels is constantly decreasing, while the carbon emissions from electricity are constantly increasing, which is closely related to the energy consumption in the construction industry. Therefore, it can be seen that electricity consumption has a relatively significant impact on carbon emissions in the construction industry.

Carbon emission model during construction phase
According to equation (3), fit the functional relationship between the per capita construction area of construction workers and the total labor productivity, and the linear regression results are as follows: By combining the Kaya identity equation of the construction phase, the carbon emission calculation model of the construction phase can be obtained:

Model of carbon emissions during the completion stage of public buildings
According to equation (4), fit the functional relationship between the per capita public building area of public buildings and the added value of the tertiary industry in Zhejiang Province, and the regression results are as follows: By combining the Kaya identity equation for the completion stage of public buildings, a carbon emission calculation model for the construction stage can be obtained:

Model of carbon emissions during the completion stage of urban residential buildings
According to equation (5), fit the functional relationship between the per capita public living area of urban residential buildings and the per capita disposable income of urban residents in Zhejiang Province. The regression results are as follows: By combining the Kaya identity equation for the completion stage of public buildings, a carbon emission calculation model for the construction stage can be obtained:

Model of carbon emissions in the construction sector
The carbon emissions in the construction sector are the sum of carbon emissions during the construction phase, carbon emissions during the completion phase of public buildings, and carbon emissions during the completion phase of urban residential buildings. Add formulas (8), (10), and (12) together, and Ci is the annual carbon emissions in the construction sector.

Analysis of Various Scenarios of Carbon Emissions in the Construction Industry of Zhejiang Province
Based on the calculation model of carbon emissions in the construction sector of Zhejiang Province, this study predicts and analyzes the carbon emissions in the construction sector of Zhejiang Province from 2023 to 2060 under three scenarios: benchmark, policy support, and technological breakthroughs. The changes in carbon emissions in the construction sector of Zhejiang Province and the time nodes for achieving carbon peak under these three scenarios are determined. Under the benchmark scenario, according to the current development model, the carbon emissions in the construction industry will reach a peak of 120159100 tons by 2028, and will continue to slowly decrease in the following years. Under the lowcarbon emission scenario, the overall carbon emissions have all decreased, and the carbon peak is expected to reach a peak of 250.48 million tons in 2027, with a relatively rapid trend of decline in the coming years. In the context of technological breakthroughs, the growth of carbon emissions has been effectively suppressed, and good carbon reduction effects have been achieved in this scenario. The peak of carbon emissions is expected to reach 207.09 million tons in 2026, with a rapid decrease in carbon emissions year by year after reaching the peak. The prediction details are shown in Table 4.

Research Conclusion
This article calculates the carbon emissions of the construction industry in Zhejiang Province from 2005 to 2022 using the emission factor method, and establishes a carbon emission model for the construction industry in Zhejiang Province based on the Kaya model. By combining scenario analysis methods, the carbon emissions of the construction industry in Zhejiang Province from 2023 to 2060 were predicted, and the following conclusions were drawn: With the rapid development of urbanization and residents' living standards, the energy consumption level of urban living in the construction industry is constantly improving. However, the update and formulation of energy-saving policies in Zhejiang Province has also led to a significant decrease in the carbon emission factor of electricity and the energy consumption intensity per unit area. In addition, due to the impact of the epidemic from 2020 to 2022, the carbon emissions in the construction industry have decreased, Taking into account the above factors, the carbon emissions in the construction industry of Zhejiang Province from 2005 to 2022 showed a trend of first increasing and then decreasing.
Through scenario prediction analysis of carbon emissions in the construction sector of Zhejiang Province, it was found that under the baseline scenario, the construction sector of Zhejiang Province will achieve a peak in carbon emissions by 2028; Under the policy support scenario, the construction sector in Zhejiang Province will achieve carbon peak in 2026; Under the scenario of technological breakthroughs, the construction industry in Zhejiang Province will achieve the carbon peak target by 2025. The comparison and prediction results of each scenario show that carbon reduction technology has a particularly significant role in promoting carbon emission reduction in the construction field. In order to achieve the goal of carbon neutrality in 2060, existing energy conservation measures and carbon reduction technologies need to be strengthened.